Constructing realistic engrams: poststimulus activity of hippocampus and dorsal striatum predicts subsequent episodic memory.

PubMed

Ben-Yakov, Aya; Dudai, Yadin

2011-06-15

Encoding of real-life episodic memory commonly involves integration of information as the episode unfolds. Offline processing immediately following event offset is expected to play a role in encoding the episode into memory. In this study, we examined whether distinct human brain activity time-locked to the offset of short narrative audiovisual episodes could predict subsequent memory for the gist of the episodes. We found that a set of brain regions, most prominently the bilateral hippocampus and the bilateral caudate nucleus, exhibit memory-predictive activity time-locked to the stimulus offset. We propose that offline activity in these regions reflects registration to memory of integrated episodes.

An EEG Finger-Print of fMRI deep regional activation.

PubMed

Meir-Hasson, Yehudit; Kinreich, Sivan; Podlipsky, Ilana; Hendler, Talma; Intrator, Nathan

2014-11-15

This work introduces a general framework for producing an EEG Finger-Print (EFP) which can be used to predict specific brain activity as measured by fMRI at a given deep region. This new approach allows for improved EEG spatial resolution based on simultaneous fMRI activity measurements. Advanced signal processing and machine learning methods were applied on EEG data acquired simultaneously with fMRI during relaxation training guided by on-line continuous feedback on changing alpha/theta EEG measure. We focused on demonstrating improved EEG prediction of activation in sub-cortical regions such as the amygdala. Our analysis shows that a ridge regression model that is based on time/frequency representation of EEG data from a single electrode, can predict the amygdala related activity significantly better than a traditional theta/alpha activity sampled from the best electrode and about 1/3 of the times, significantly better than a linear combination of frequencies with a pre-defined delay. The far-reaching goal of our approach is to be able to reduce the need for fMRI scanning for probing specific sub-cortical regions such as the amygdala as the basis for brain-training procedures. On the other hand, activity in those regions can be characterized with higher temporal resolution than is obtained by fMRI alone thus revealing additional information about their processing mode. Copyright © 2013 Elsevier Inc. All rights reserved.

Regional brain activity during early-stage intense romantic love predicted relationship outcomes after 40 months: an fMRI assessment.

PubMed

Xu, Xiaomeng; Brown, Lucy; Aron, Arthur; Cao, Guikang; Feng, Tingyong; Acevedo, Bianca; Weng, Xuchu

2012-09-20

Early-stage romantic love is associated with activation in reward and motivation systems of the brain. Can these localized activations, or others, predict long-term relationship stability? We contacted participants from a previous fMRI study of early-stage love by Xu et al. [34] after 40 months from initial assessments. We compared brain activation during the initial assessment at early-stage love for those who were still together at 40 months and those who were apart, and surveyed those still together about their relationship happiness and commitment at 40 months. Six participants who were still with their partners at 40 months (compared to six who had broken up) showed less activation during early-stage love in the medial orbitofrontal cortex, right subcallosal cingulate and right accumbens, regions implicated in long-term love and relationship satisfaction [1,2]. These regions of deactivation at the early stage of love were also negatively correlated with relationship happiness scores collected at 40 months. Other areas involved were the caudate tail, and temporal and parietal lobes. These data are preliminary evidence that neural responses in the early stages of romantic love can predict relationship stability and quality up to 40 months later in the relationship. The brain regions involved suggest that forebrain reward functions may be predictive for relationship stability, as well as regions involved in social evaluation, emotional regulation, and mood. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Inferring deep-brain activity from cortical activity using functional near-infrared spectroscopy

PubMed Central

Liu, Ning; Cui, Xu; Bryant, Daniel M.; Glover, Gary H.; Reiss, Allan L.

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an increasingly popular technology for studying brain function because it is non-invasive, non-irradiating and relatively inexpensive. Further, fNIRS potentially allows measurement of hemodynamic activity with high temporal resolution (milliseconds) and in naturalistic settings. However, in comparison with other imaging modalities, namely fMRI, fNIRS has a significant drawback: limited sensitivity to hemodynamic changes in deep-brain regions. To overcome this limitation, we developed a computational method to infer deep-brain activity using fNIRS measurements of cortical activity. Using simultaneous fNIRS and fMRI, we measured brain activity in 17 participants as they completed three cognitive tasks. A support vector regression (SVR) learning algorithm was used to predict activity in twelve deep-brain regions using information from surface fNIRS measurements. We compared these predictions against actual fMRI-measured activity using Pearson’s correlation to quantify prediction performance. To provide a benchmark for comparison, we also used fMRI measurements of cortical activity to infer deep-brain activity. When using fMRI-measured activity from the entire cortex, we were able to predict deep-brain activity in the fusiform cortex with an average correlation coefficient of 0.80 and in all deep-brain regions with an average correlation coefficient of 0.67. The top 15% of predictions using fNIRS signal achieved an accuracy of 0.7. To our knowledge, this study is the first to investigate the feasibility of using cortical activity to infer deep-brain activity. This new method has the potential to extend fNIRS applications in cognitive and clinical neuroscience research. PMID:25798327

Appearance Matters: Neural Correlates of Food Choice and Packaging Aesthetics

PubMed Central

Van der Laan, Laura N.; De Ridder, Denise T. D.; Viergever, Max A.; Smeets, Paul A. M.

2012-01-01

Neuro-imaging holds great potential for predicting choice behavior from brain responses. In this study we used both traditional mass-univariate and state-of-the-art multivariate pattern analysis to establish which brain regions respond to preferred packages and to what extent neural activation patterns can predict realistic low-involvement consumer choices. More specifically, this was assessed in the context of package-induced binary food choices. Mass-univariate analyses showed that several regions, among which the bilateral striatum, were more strongly activated in response to preferred food packages. Food choices could be predicted with an accuracy of up to 61.2% by activation patterns in brain regions previously found to be involved in healthy food choices (superior frontal gyrus) and visual processing (middle occipital gyrus). In conclusion, this study shows that mass-univariate analysis can detect small package-induced differences in product preference and that MVPA can successfully predict realistic low-involvement consumer choices from functional MRI data. PMID:22848586

Mammalian genomic regulatory regions predicted by utilizing human genomics, transcriptomics, and epigenetics data

PubMed Central

Nguyen, Quan H; Tellam, Ross L; Naval-Sanchez, Marina; Porto-Neto, Laercio R; Barendse, William; Reverter, Antonio; Hayes, Benjamin; Kijas, James; Dalrymple, Brian P

2018-01-01

Abstract Genome sequences for hundreds of mammalian species are available, but an understanding of their genomic regulatory regions, which control gene expression, is only beginning. A comprehensive prediction of potential active regulatory regions is necessary to functionally study the roles of the majority of genomic variants in evolution, domestication, and animal production. We developed a computational method to predict regulatory DNA sequences (promoters, enhancers, and transcription factor binding sites) in production animals (cows and pigs) and extended its broad applicability to other mammals. The method utilizes human regulatory features identified from thousands of tissues, cell lines, and experimental assays to find homologous regions that are conserved in sequences and genome organization and are enriched for regulatory elements in the genome sequences of other mammalian species. Importantly, we developed a filtering strategy, including a machine learning classification method, to utilize a very small number of species-specific experimental datasets available to select for the likely active regulatory regions. The method finds the optimal combination of sensitivity and accuracy to unbiasedly predict regulatory regions in mammalian species. Furthermore, we demonstrated the utility of the predicted regulatory datasets in cattle for prioritizing variants associated with multiple production and climate change adaptation traits and identifying potential genome editing targets. PMID:29618048

Mammalian genomic regulatory regions predicted by utilizing human genomics, transcriptomics, and epigenetics data.

PubMed

Nguyen, Quan H; Tellam, Ross L; Naval-Sanchez, Marina; Porto-Neto, Laercio R; Barendse, William; Reverter, Antonio; Hayes, Benjamin; Kijas, James; Dalrymple, Brian P

2018-03-01

Genome sequences for hundreds of mammalian species are available, but an understanding of their genomic regulatory regions, which control gene expression, is only beginning. A comprehensive prediction of potential active regulatory regions is necessary to functionally study the roles of the majority of genomic variants in evolution, domestication, and animal production. We developed a computational method to predict regulatory DNA sequences (promoters, enhancers, and transcription factor binding sites) in production animals (cows and pigs) and extended its broad applicability to other mammals. The method utilizes human regulatory features identified from thousands of tissues, cell lines, and experimental assays to find homologous regions that are conserved in sequences and genome organization and are enriched for regulatory elements in the genome sequences of other mammalian species. Importantly, we developed a filtering strategy, including a machine learning classification method, to utilize a very small number of species-specific experimental datasets available to select for the likely active regulatory regions. The method finds the optimal combination of sensitivity and accuracy to unbiasedly predict regulatory regions in mammalian species. Furthermore, we demonstrated the utility of the predicted regulatory datasets in cattle for prioritizing variants associated with multiple production and climate change adaptation traits and identifying potential genome editing targets.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mandage, Revati S.; McAteer, R. T. James, E-mail: mcateer@nmsu.edu

A magnetic power spectral analysis is performed on 53 solar active regions, observed from 2011 August to 2012 July. Magnetic field data obtained from the Helioseismic and Magnetic Imager, inverted as Active Region Patches, are used to study the evolution of the magnetic power index as each region rotates across the solar disk. Active regions are classified based on the numbers and sizes of solar flares they produce in order to study the relationship between flare productivity and the magnetic power index. The choice of window size and inertial range plays a key role in determining the correct magnetic powermore » index. The overall distribution of magnetic power indices has a range of 1.0–2.5. Flare-quiet regions peak at a value of 1.6. However, flare-productive regions peak at a value of 2.2. Overall, the histogram of the distribution of power indices of flare-productive active regions is well separated from flare-quiet active regions. Only 12% of flare-quiet regions exhibit an index greater than 2, whereas 90% of flare-productive regions exhibit an index greater than 2. Flare-quiet regions exhibit a high temporal variance (i.e., the index fluctuates between high and low values), whereas flare-productive regions maintain an index greater than 2 for several days. This shows the importance of including the temporal evolution of active regions in flare prediction studies, and highlights the potential of a 2–3 day prediction window for space weather applications.« less

Neural substrates of updating the prediction through prediction error during decision making.

PubMed

Wang, Ying; Ma, Ning; He, Xiaosong; Li, Nan; Wei, Zhengde; Yang, Lizhuang; Zha, Rujing; Han, Long; Li, Xiaoming; Zhang, Daren; Liu, Ying; Zhang, Xiaochu

2017-08-15

Learning of prediction error (PE), including reward PE and risk PE, is crucial for updating the prediction in reinforcement learning (RL). Neurobiological and computational models of RL have reported extensive brain activations related to PE. However, the occurrence of PE does not necessarily predict updating the prediction, e.g., in a probability-known event. Therefore, the brain regions specifically engaged in updating the prediction remain unknown. Here, we conducted two functional magnetic resonance imaging (fMRI) experiments, the probability-unknown Iowa Gambling Task (IGT) and the probability-known risk decision task (RDT). Behavioral analyses confirmed that PEs occurred in both tasks but were only used for updating the prediction in the IGT. By comparing PE-related brain activations between the two tasks, we found that the rostral anterior cingulate cortex/ventral medial prefrontal cortex (rACC/vmPFC) and the posterior cingulate cortex (PCC) activated only during the IGT and were related to both reward and risk PE. Moreover, the responses in the rACC/vmPFC and the PCC were modulated by uncertainty and were associated with reward prediction-related brain regions. Electric brain stimulation over these regions lowered the performance in the IGT but not in the RDT. Our findings of a distributed neural circuit of PE processing suggest that the rACC/vmPFC and the PCC play a key role in updating the prediction through PE processing during decision making. Copyright © 2017 Elsevier Inc. All rights reserved.

fMRI Reactivity to High-Calorie Food Pictures Predicts Short- and Long-Term Outcome in a Weight-Loss Program

PubMed Central

Murdaugh, Donna L.; Cox, James E.; Cook, Edwin W.; Weller, Rosalyn E.

2011-01-01

Behavioral studies have suggested that food cues have stronger motivating effects in obese than in normal-weight individuals, which may be a risk factor underlying obesity. Previous cross-sectional neuroimaging studies have suggested that this difference is mediated by increased reactivity to food cues in parts of the reward system in obese individuals. To date, however, only a few prospective neuroimaging studies have been conducted to examine whether individual differences in brain activation elicited by food cues can predict differences in weight change. We used functional magnetic resonance imaging (fMRI) to investigate activation in reward-system as well as other brain regions in response to viewing high-calorie food vs. control pictures in 25 obese individuals before and after a 12-week psychosocial weight-loss treatment and at 9-mo follow-up. In those obese individuals who were least successful in losing weight during the treatment, we found greater pre-treatment activation to high-calorie food vs. control pictures in brain regions implicated in reward-system processes, such as the nucleus accumbens, anterior cingulate, and insula. We found similar correlations with weight loss in brain regions implicated by other studies in vision and attention, such as superior occipital cortex, inferior and superior parietal lobule, and prefrontal cortex. Furthermore, less successful weight maintenance at 9-mo follow-up was predicted by greater post-treatment activation in such brain regions as insula, ventral tegmental area, putamen, and fusiform gyrus. In summary, we found that greater activation in brain regions mediating motivational and attentional salience of food cues in obese individuals at the start of a weight-loss program was predictive of less success in the program and that such activation following the program predicted poorer weight control over a 9-mo follow-up period. PMID:22332246

Interactions between the nucleus accumbens and auditory cortices predict music reward value.

PubMed

Salimpoor, Valorie N; van den Bosch, Iris; Kovacevic, Natasa; McIntosh, Anthony Randal; Dagher, Alain; Zatorre, Robert J

2013-04-12

We used functional magnetic resonance imaging to investigate neural processes when music gains reward value the first time it is heard. The degree of activity in the mesolimbic striatal regions, especially the nucleus accumbens, during music listening was the best predictor of the amount listeners were willing to spend on previously unheard music in an auction paradigm. Importantly, the auditory cortices, amygdala, and ventromedial prefrontal regions showed increased activity during listening conditions requiring valuation, but did not predict reward value, which was instead predicted by increasing functional connectivity of these regions with the nucleus accumbens as the reward value increased. Thus, aesthetic rewards arise from the interaction between mesolimbic reward circuitry and cortical networks involved in perceptual analysis and valuation.

Prediction of Active-Region CME Productivity from Magnetograms

NASA Technical Reports Server (NTRS)

Falconer, D. A.; Moore, R. L.; Gary, G. A.

2004-01-01

We report results of an expanded evaluation of whole-active-region magnetic measures as predictors of active-region coronal mass ejection (CME) productivity. Previously, in a sample of 17 vector magnetograms of 12 bipolar active regions observed by the Marshall Space Flight Center (MSFC) vector magnetograph, from each magnetogram we extracted a measure of the size of the active region (the active region s total magnetic flux a) and four measures of the nonpotentiality of the active region: the strong-shear length L(sub SS), the strong-gradient length L(sub SG), the net vertical electric current I(sub N), and the net-current magnetic twist parameter alpha (sub IN). This sample size allowed us to show that each of the four nonpotentiality measures was statistically significantly correlated with active-region CME productivity in time windows of a few days centered on the day of the magnetogram. We have now added a fifth measure of active-region nonpotentiality (the best-constant-alpha magnetic twist parameter (alpha sub BC)), and have expanded the sample to 36 MSFC vector magnetograms of 31 bipolar active regions. This larger sample allows us to demonstrate statistically significant correlations of each of the five nonpotentiality measures with future CME productivity, in time windows of a few days starting from the day of the magnetogram. The two magnetic twist parameters (alpha (sub 1N) and alpha (sub BC)) are normalized measures of an active region s nonpotentially in that they do not depend directly on the size of the active region, while the other three nonpotentiality measures (L(sub SS), L(sub SG), and I(sub N)) are non-normalized measures in that they do depend directly on active-region size. We find (1) Each of the five nonpotentiality measures is statistically significantly correlated (correlation confidence level greater than 95%) with future CME productivity and has a CME prediction success rate of approximately 80%. (2) None of the nonpotentiality measures is a significantly better CME predictor than the others. (3) The active-region phi shows some correlation with CME productivity, but well below a statistically significant level (correlation confidence level less than approximately 80%; CME prediction success rate less than approximately 65%). (4) In addition to depending on magnetic twist, CME productivity appears to have some direct dependence on active-region size (rather than only an indirect dependence through a correlation of magnetic twist with active-region size), but it will take a still larger sample of active regions (50 or more) to certify this. (5) Of the five nonpotentiality measures, L(sub SG) appears to be the best for operational CME forecasting because it is as good or better a CME predictor than the others and it alone does not require a vector magnetogram; L(sub SG) can be measured from a line-of-sight magnetogram such as from the Michelson Doppler Imager (MDI) on the Solar and Heliospheric Observatory (SOHO).

Methods for estimating flood frequency in Montana based on data through water year 1998

USGS Publications Warehouse

Parrett, Charles; Johnson, Dave R.

2004-01-01

Annual peak discharges having recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years (T-year floods) were determined for 660 gaged sites in Montana and in adjacent areas of Idaho, Wyoming, and Canada, based on data through water year 1998. The updated flood-frequency information was subsequently used in regression analyses, either ordinary or generalized least squares, to develop equations relating T-year floods to various basin and climatic characteristics, equations relating T-year floods to active-channel width, and equations relating T-year floods to bankfull width. The equations can be used to estimate flood frequency at ungaged sites. Montana was divided into eight regions, within which flood characteristics were considered to be reasonably homogeneous, and the three sets of regression equations were developed for each region. A measure of the overall reliability of the regression equations is the average standard error of prediction. The average standard errors of prediction for the equations based on basin and climatic characteristics ranged from 37.4 percent to 134.1 percent. Average standard errors of prediction for the equations based on active-channel width ranged from 57.2 percent to 141.3 percent. Average standard errors of prediction for the equations based on bankfull width ranged from 63.1 percent to 155.5 percent. In most regions, the equations based on basin and climatic characteristics generally had smaller average standard errors of prediction than equations based on active-channel or bankfull width. An exception was the Southeast Plains Region, where all equations based on active-channel width had smaller average standard errors of prediction than equations based on basin and climatic characteristics or bankfull width. Methods for weighting estimates derived from the basin- and climatic-characteristic equations and the channel-width equations also were developed. The weights were based on the cross correlation of residuals from the different methods and the average standard errors of prediction. When all three methods were combined, the average standard errors of prediction ranged from 37.4 percent to 120.2 percent. Weighting of estimates reduced the standard errors of prediction for all T-year flood estimates in four regions, reduced the standard errors of prediction for some T-year flood estimates in two regions, and provided no reduction in average standard error of prediction in two regions. A computer program for solving the regression equations, weighting estimates, and determining reliability of individual estimates was developed and placed on the USGS Montana District World Wide Web page. A new regression method, termed Region of Influence regression, also was tested. Test results indicated that the Region of Influence method was not as reliable as the regional equations based on generalized least squares regression. Two additional methods for estimating flood frequency at ungaged sites located on the same streams as gaged sites also are described. The first method, based on a drainage-area-ratio adjustment, is intended for use on streams where the ungaged site of interest is located near a gaged site. The second method, based on interpolation between gaged sites, is intended for use on streams that have two or more streamflow-gaging stations.

Nonlinear analyses of interictal EEG map the brain interdependences in human focal epilepsy

NASA Astrophysics Data System (ADS)

Quyen, Michel Le Van; Martinerie, Jacques; Adam, Claude; Varela, Francisco J.

1999-03-01

The degree of interdependence between intracranial electroencephalographic (EEG) channels was investigated in epileptic patients with temporal lobe seizures during interictal (between seizures) periods. With a novel method to characterize nonlinear cross-predictability, that is, the predictability of one channel using another channel as data base, we demonstrated here a possibility to extract information on the spatio-temporal organization of interactions between multichannel recording sites. This method determines whether two channels contain common activity, and often, whether one channel contains activity induced by the activity of the other channel. In particular, the technique and the comparison with surrogate data demonstrated that transient large-scale nonlinear entrainments by the epileptogenic region can be identified, this with or without epileptic activity. Furthermore, these recurrent activities related with the epileptic foci occurred in well-defined spatio-temporal patterns. This suggests that the epileptogenic region can exhibit very subtle influences on other brain regions during an interictal period and raises the possibility that the cross-predictability analysis of interictal data may be used as a significant aid in locating epileptogenic foci.

An Automated Solar Synoptic Analysis Software System

NASA Astrophysics Data System (ADS)

Hong, S.; Lee, S.; Oh, S.; Kim, J.; Lee, J.; Kim, Y.; Lee, J.; Moon, Y.; Lee, D.

2012-12-01

We have developed an automated software system of identifying solar active regions, filament channels, and coronal holes, those are three major solar sources causing the space weather. Space weather forecasters of NOAA Space Weather Prediction Center produce the solar synoptic drawings as a daily basis to predict solar activities, i.e., solar flares, filament eruptions, high speed solar wind streams, and co-rotating interaction regions as well as their possible effects to the Earth. As an attempt to emulate this process with a fully automated and consistent way, we developed a software system named ASSA(Automated Solar Synoptic Analysis). When identifying solar active regions, ASSA uses high-resolution SDO HMI intensitygram and magnetogram as inputs and providing McIntosh classification and Mt. Wilson magnetic classification of each active region by applying appropriate image processing techniques such as thresholding, morphology extraction, and region growing. At the same time, it also extracts morphological and physical properties of active regions in a quantitative way for the short-term prediction of flares and CMEs. When identifying filament channels and coronal holes, images of global H-alpha network and SDO AIA 193 are used for morphological identification and also SDO HMI magnetograms for quantitative verification. The output results of ASSA are routinely checked and validated against NOAA's daily SRS(Solar Region Summary) and UCOHO(URSIgram code for coronal hole information). A couple of preliminary scientific results are to be presented using available output results. ASSA will be deployed at the Korean Space Weather Center and serve its customers in an operational status by the end of 2012.

Predicting the practice effects on the blood oxygenation level-dependent (BOLD) function of fMRI in a symbolic manipulation task

NASA Astrophysics Data System (ADS)

Qin, Yulin; Sohn, Myeong-Ho; Anderson, John R.; Stenger, V. Andrew; Fissell, Kate; Goode, Adam; Carter, Cameron S.

2003-04-01

Based on adaptive control of thought-rational (ACT-R), a cognitive architecture for cognitive modeling, researchers have developed an information-processing model to predict the blood oxygenation level-dependent (BOLD) response of functional MRI in symbol manipulation tasks. As an extension of this research, the current event-related functional MRI study investigates the effect of relatively extensive practice on the activation patterns of related brain regions. The task involved performing transformations on equations in an artificial algebra system. This paper shows that the base-level activation learning in the ACT-R theory can predict the change of the BOLD response in practice in a left prefrontal region reflecting retrieval of information. In contrast, practice has relatively little effect on the form of BOLD response in the parietal region reflecting imagined transformations to the equation or the motor region reflecting manual programming.

Impact of Intraseasonal Oscillations on the Tropical Cyclone Activity Over the Gulf of Mexico and Western Caribbean Sea in GFDL HiRAM

NASA Astrophysics Data System (ADS)

Gao, Kun; Chen, Jan-Huey; Harris, Lucas M.; Lin, Shian-Jiann; Xiang, Baoqiang; Zhao, Ming

2017-12-01

The tropical cyclones (TCs) that form over the warm waters in the Gulf of Mexico region pose a major threat to the surrounding coastal communities. Skillful subseasonal prediction of TC activity is important for early preparedness and reducing the TC damage in this region. In this study, we evaluate the performance of a 25 km resolution Geophysical Fluid Dynamics Laboratory (GFDL) High Resolution Atmospheric Model (HiRAM) in simulating the modulation of the TC activity in the Gulf of Mexico and western Caribbean Sea by the intraseasonal oscillation (ISO) based on multiyear retrospective seasonal predictions. We demonstrate that the HiRAM faithfully captures the observed influence of ISO on TC activity over the region of interest, including the formation of tropical storms and (major) hurricanes, as well as the landfalling storms. This is likely because of the realistic representation of the large-scale anomalies associated with boreal summer ISO over Northeast Pacific in HiRAM, especially the enhanced (reduced) moisture throughout the troposphere during the convectively enhanced (suppressed) phase of ISO. The reasonable performance of HiRAM suggests its potential for the subseasonal prediction of regional TC risk.

From Vivaldi to Beatles and back: predicting lateralized brain responses to music.

PubMed

Alluri, Vinoo; Toiviainen, Petri; Lund, Torben E; Wallentin, Mikkel; Vuust, Peter; Nandi, Asoke K; Ristaniemi, Tapani; Brattico, Elvira

2013-12-01

We aimed at predicting the temporal evolution of brain activity in naturalistic music listening conditions using a combination of neuroimaging and acoustic feature extraction. Participants were scanned using functional Magnetic Resonance Imaging (fMRI) while listening to two musical medleys, including pieces from various genres with and without lyrics. Regression models were built to predict voxel-wise brain activations which were then tested in a cross-validation setting in order to evaluate the robustness of the hence created models across stimuli. To further assess the generalizability of the models we extended the cross-validation procedure by including another dataset, which comprised continuous fMRI responses of musically trained participants to an Argentinean tango. Individual models for the two musical medleys revealed that activations in several areas in the brain belonging to the auditory, limbic, and motor regions could be predicted. Notably, activations in the medial orbitofrontal region and the anterior cingulate cortex, relevant for self-referential appraisal and aesthetic judgments, could be predicted successfully. Cross-validation across musical stimuli and participant pools helped identify a region of the right superior temporal gyrus, encompassing the planum polare and the Heschl's gyrus, as the core structure that processed complex acoustic features of musical pieces from various genres, with or without lyrics. Models based on purely instrumental music were able to predict activation in the bilateral auditory cortices, parietal, somatosensory, and left hemispheric primary and supplementary motor areas. The presence of lyrics on the other hand weakened the prediction of activations in the left superior temporal gyrus. Our results suggest spontaneous emotion-related processing during naturalistic listening to music and provide supportive evidence for the hemispheric specialization for categorical sounds with realistic stimuli. We herewith introduce a powerful means to predict brain responses to music, speech, or soundscapes across a large variety of contexts. © 2013.

Prediction of human errors by maladaptive changes in event-related brain networks.

PubMed

Eichele, Tom; Debener, Stefan; Calhoun, Vince D; Specht, Karsten; Engel, Andreas K; Hugdahl, Kenneth; von Cramon, D Yves; Ullsperger, Markus

2008-04-22

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve approximately 30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations.

Prediction of human errors by maladaptive changes in event-related brain networks

PubMed Central

Eichele, Tom; Debener, Stefan; Calhoun, Vince D.; Specht, Karsten; Engel, Andreas K.; Hugdahl, Kenneth; von Cramon, D. Yves; Ullsperger, Markus

2008-01-01

Humans engaged in monotonous tasks are susceptible to occasional errors that may lead to serious consequences, but little is known about brain activity patterns preceding errors. Using functional MRI and applying independent component analysis followed by deconvolution of hemodynamic responses, we studied error preceding brain activity on a trial-by-trial basis. We found a set of brain regions in which the temporal evolution of activation predicted performance errors. These maladaptive brain activity changes started to evolve ≈30 sec before the error. In particular, a coincident decrease of deactivation in default mode regions of the brain, together with a decline of activation in regions associated with maintaining task effort, raised the probability of future errors. Our findings provide insights into the brain network dynamics preceding human performance errors and suggest that monitoring of the identified precursor states may help in avoiding human errors in critical real-world situations. PMID:18427123

Prefrontal and parietal activity is modulated by the rule complexity of inductive reasoning and can be predicted by a cognitive model.

PubMed

Jia, Xiuqin; Liang, Peipeng; Shi, Lin; Wang, Defeng; Li, Kuncheng

2015-01-01

In neuroimaging studies, increased task complexity can lead to increased activation in task-specific regions or to activation of additional regions. How the brain adapts to increased rule complexity during inductive reasoning remains unclear. In the current study, three types of problems were created: simple rule induction (i.e., SI, with rule complexity of 1), complex rule induction (i.e., CI, with rule complexity of 2), and perceptual control. Our findings revealed that increased activations accompany increased rule complexity in the right dorsal lateral prefrontal cortex (DLPFC) and medial posterior parietal cortex (precuneus). A cognitive model predicted both the behavioral and brain imaging results. The current findings suggest that neural activity in frontal and parietal regions is modulated by rule complexity, which may shed light on the neural mechanisms of inductive reasoning. Copyright © 2014. Published by Elsevier Ltd.

Ground-Motion Prediction Equations (GMPEs) from a global dataset: the PEERPEER NGA equations

USGS Publications Warehouse

Boore, David M.; Akkar, Sinan; Gulkan, Polat; van Eck, Torild

2011-01-01

The PEER NGA ground-motion prediction equation s (GMPEs) were derived by five developer teams over several years, resulting in five sets of GMPEs. The teams used various subsets of a global database of ground motions and metadata from shallow earthquakes in tectonically active regions in the development of the equations. Since their publication, the predicted motions from these GMPEs have been compared with data from various parts of the world – data that largely were not used in the development of the GMPEs. The comparisons suggest that the NGA GMPEs are applicable globally for shallow earthquakes in tectonically active regions.

Punishing an error improves learning: the influence of punishment magnitude on error-related neural activity and subsequent learning.

PubMed

Hester, Robert; Murphy, Kevin; Brown, Felicity L; Skilleter, Ashley J

2010-11-17

Punishing an error to shape subsequent performance is a major tenet of individual and societal level behavioral interventions. Recent work examining error-related neural activity has identified that the magnitude of activity in the posterior medial frontal cortex (pMFC) is predictive of learning from an error, whereby greater activity in this region predicts adaptive changes in future cognitive performance. It remains unclear how punishment influences error-related neural mechanisms to effect behavior change, particularly in key regions such as pMFC, which previous work has demonstrated to be insensitive to punishment. Using an associative learning task that provided monetary reward and punishment for recall performance, we observed that when recall errors were categorized by subsequent performance--whether the failure to accurately recall a number-location association was corrected at the next presentation of the same trial--the magnitude of error-related pMFC activity predicted future correction. However, the pMFC region was insensitive to the magnitude of punishment an error received and it was the left insula cortex that predicted learning from the most aversive outcomes. These findings add further evidence to the hypothesis that error-related pMFC activity may reflect more than a prediction error in representing the value of an outcome. The novel role identified here for the insular cortex in learning from punishment appears particularly compelling for our understanding of psychiatric and neurologic conditions that feature both insular cortex dysfunction and a diminished capacity for learning from negative feedback or punishment.

Activity in the human brain predicting differential heart rate responses to emotional facial expressions.

PubMed

Critchley, Hugo D; Rotshtein, Pia; Nagai, Yoko; O'Doherty, John; Mathias, Christopher J; Dolan, Raymond J

2005-02-01

The James-Lange theory of emotion proposes that automatically generated bodily reactions not only color subjective emotional experience of stimuli, but also necessitate a mechanism by which these bodily reactions are differentially generated to reflect stimulus quality. To examine this putative mechanism, we simultaneously measured brain activity and heart rate to identify regions where neural activity predicted the magnitude of heart rate responses to emotional facial expressions. Using a forewarned reaction time task, we showed that orienting heart rate acceleration to emotional face stimuli was modulated as a function of the emotion depicted. The magnitude of evoked heart rate increase, both across the stimulus set and within each emotion category, was predicted by level of activity within a matrix of interconnected brain regions, including amygdala, insula, anterior cingulate, and brainstem. We suggest that these regions provide a substrate for translating visual perception of emotional facial expression into differential cardiac responses and thereby represent an interface for selective generation of visceral reactions that contribute to the embodied component of emotional reaction.

SOLAR FLARE PREDICTION USING SDO/HMI VECTOR MAGNETIC FIELD DATA WITH A MACHINE-LEARNING ALGORITHM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bobra, M. G.; Couvidat, S., E-mail: couvidat@stanford.edu

2015-01-10

We attempt to forecast M- and X-class solar flares using a machine-learning algorithm, called support vector machine (SVM), and four years of data from the Solar Dynamics Observatory's Helioseismic and Magnetic Imager, the first instrument to continuously map the full-disk photospheric vector magnetic field from space. Most flare forecasting efforts described in the literature use either line-of-sight magnetograms or a relatively small number of ground-based vector magnetograms. This is the first time a large data set of vector magnetograms has been used to forecast solar flares. We build a catalog of flaring and non-flaring active regions sampled from a databasemore » of 2071 active regions, comprised of 1.5 million active region patches of vector magnetic field data, and characterize each active region by 25 parameters. We then train and test the machine-learning algorithm and we estimate its performances using forecast verification metrics with an emphasis on the true skill statistic (TSS). We obtain relatively high TSS scores and overall predictive abilities. We surmise that this is partly due to fine-tuning the SVM for this purpose and also to an advantageous set of features that can only be calculated from vector magnetic field data. We also apply a feature selection algorithm to determine which of our 25 features are useful for discriminating between flaring and non-flaring active regions and conclude that only a handful are needed for good predictive abilities.« less

Automatic prediction of solar flares and super geomagnetic storms

NASA Astrophysics Data System (ADS)

Song, Hui

Space weather is the response of our space environment to the constantly changing Sun. As the new technology advances, mankind has become more and more dependent on space system, satellite-based services. A geomagnetic storm, a disturbance in Earth's magnetosphere, may produce many harmful effects on Earth. Solar flares and Coronal Mass Ejections (CMEs) are believed to be the major causes of geomagnetic storms. Thus, establishing a real time forecasting method for them is very important in space weather study. The topics covered in this dissertation are: the relationship between magnetic gradient and magnetic shear of solar active regions; the relationship between solar flare index and magnetic features of solar active regions; based on these relationships a statistical ordinal logistic regression model is developed to predict the probability of solar flare occurrences in the next 24 hours; and finally the relationship between magnetic structures of CME source regions and geomagnetic storms, in particular, the super storms when the D st index decreases below -200 nT is studied and proved to be able to predict those super storms. The results are briefly summarized as follows: (1) There is a significant correlation between magnetic gradient and magnetic shear of active region. Furthermore, compared with magnetic shear, magnetic gradient might be a better proxy to locate where a large flare occurs. It appears to be more accurate in identification of sources of X-class flares than M-class flares; (2) Flare index, defined by weighting the SXR flares, is proved to have positive correlation with three magnetic features of active region; (3) A statistical ordinal logistic regression model is proposed for solar flare prediction. The results are much better than those data published in the NASA/SDAC service, and comparable to the data provided by the NOAA/SEC complicated expert system. To our knowledge, this is the first time that logistic regression model has been applied in solar physics to predict flare occurrences; (4) The magnetic orientation angle [straight theta], determined from a potential field model, is proved to be able to predict the probability of super geomagnetic storms (D= st <=-200nT). The results show that those active regions associated with | [straight theta]| < 90° are more likely to cause a super geomagnetic storm.

Engagement of the left extrastriate body area during body-part metaphor comprehension.

PubMed

Lacey, Simon; Stilla, Randall; Deshpande, Gopikrishna; Zhao, Sinan; Stephens, Careese; McCormick, Kelly; Kemmerer, David; Sathian, K

2017-03-01

Grounded cognition explanations of metaphor comprehension predict activation of sensorimotor cortices relevant to the metaphor's source domain. We tested this prediction for body-part metaphors using functional magnetic resonance imaging while participants heard sentences containing metaphorical or literal references to body parts, and comparable control sentences. Localizer scans identified body-part-specific motor, somatosensory and visual cortical regions. Both subject- and item-wise analyses showed that, relative to control sentences, metaphorical but not literal sentences evoked limb metaphor-specific activity in the left extrastriate body area (EBA), paralleling the EBA's known visual limb-selectivity. The EBA focus exhibited resting-state functional connectivity with ipsilateral semantic processing regions. In some of these regions, the strength of resting-state connectivity correlated with individual preference for verbal processing. Effective connectivity analyses showed that, during metaphor comprehension, activity in some semantic regions drove that in the EBA. These results provide converging evidence for grounding of metaphor processing in domain-specific sensorimotor cortical activity. Published by Elsevier Inc.

The influence of visual training on predicting complex action sequences.

PubMed

Cross, Emily S; Stadler, Waltraud; Parkinson, Jim; Schütz-Bosbach, Simone; Prinz, Wolfgang

2013-02-01

Linking observed and executable actions appears to be achieved by an action observation network (AON), comprising parietal, premotor, and occipitotemporal cortical regions of the human brain. AON engagement during action observation is thought to aid in effortless, efficient prediction of ongoing movements to support action understanding. Here, we investigate how the AON responds when observing and predicting actions we cannot readily reproduce before and after visual training. During pre- and posttraining neuroimaging sessions, participants watched gymnasts and wind-up toys moving behind an occluder and pressed a button when they expected each agent to reappear. Between scanning sessions, participants visually trained to predict when a subset of stimuli would reappear. Posttraining scanning revealed activation of inferior parietal, superior temporal, and cerebellar cortices when predicting occluded actions compared to perceiving them. Greater activity emerged when predicting untrained compared to trained sequences in occipitotemporal cortices and to a lesser degree, premotor cortices. The occipitotemporal responses when predicting untrained agents showed further specialization, with greater responses within body-processing regions when predicting gymnasts' movements and in object-selective cortex when predicting toys' movements. The results suggest that (1) select portions of the AON are recruited to predict the complex movements not easily mapped onto the observer's body and (2) greater recruitment of these AON regions supports prediction of less familiar sequences. We suggest that the findings inform both the premotor model of action prediction and the predictive coding account of AON function. Copyright © 2011 Wiley Periodicals, Inc.

Emotion and resilience: a multilevel investigation of hemispheric electroencephalogram asymmetry and emotion regulation in maltreated and nonmaltreated children.

PubMed

Curtis, W John; Cicchetti, Dante

2007-01-01

The current study was a multilevel investigation of resilience, emotion regulation, and hemispheric electroencephalogram (EEG) asymmetry in a sample of maltreated and nonmaltreated school age children. It was predicted that the positive emotionality and increased emotion regulatory ability associated with resilient functioning would be associated with relatively greater left frontal EEG activity. The study also investigated differences in pathways to resilience between maltreated and nonmaltreated children. The findings indicated that EEG asymmetry across central cortical regions distinguished between resilient and nonresilient children, with greater left hemisphere activity characterizing those who were resilient. In addition, nonmaltreated children showed greater left hemisphere EEG activity across parietal cortical regions. There was also a significant interaction between resilience, maltreatment status, and gender for asymmetry at anterior frontal electrodes, where nonmaltreated resilient females had greater relative left frontal activity compared to more right frontal activity exhibited by resilient maltreated females. An observational measure of emotion regulation significantly contributed to the prediction of resilience in the maltreated and nonmaltreated children, but EEG asymmetry in central cortical regions independently predicted resilience only in the maltreated group. The findings are discussed in terms of their meaning for the development of resilient functioning.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Chang; Deng, Na; Wang, Haimin

Adverse space-weather effects can often be traced to solar flares, the prediction of which has drawn significant research interests. The Helioseismic and Magnetic Imager (HMI) produces full-disk vector magnetograms with continuous high cadence, while flare prediction efforts utilizing this unprecedented data source are still limited. Here we report results of flare prediction using physical parameters provided by the Space-weather HMI Active Region Patches (SHARP) and related data products. We survey X-ray flares that occurred from 2010 May to 2016 December and categorize their source regions into four classes (B, C, M, and X) according to the maximum GOES magnitude ofmore » flares they generated. We then retrieve SHARP-related parameters for each selected region at the beginning of its flare date to build a database. Finally, we train a machine-learning algorithm, called random forest (RF), to predict the occurrence of a certain class of flares in a given active region within 24 hr, evaluate the classifier performance using the 10-fold cross-validation scheme, and characterize the results using standard performance metrics. Compared to previous works, our experiments indicate that using the HMI parameters and RF is a valid method for flare forecasting with fairly reasonable prediction performance. To our knowledge, this is the first time that RF has been used to make multiclass predictions of solar flares. We also find that the total unsigned quantities of vertical current, current helicity, and flux near the polarity inversion line are among the most important parameters for classifying flaring regions into different classes.« less

PREDICTION OF SOLAR FLARES USING UNIQUE SIGNATURES OF MAGNETIC FIELD IMAGES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raboonik, Abbas; Safari, Hossein; Alipour, Nasibe

Prediction of solar flares is an important task in solar physics. The occurrence of solar flares is highly dependent on the structure and topology of solar magnetic fields. A new method for predicting large (M- and X-class) flares is presented, which uses machine learning methods applied to the Zernike moments (ZM) of magnetograms observed by the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory for a period of six years from 2010 June 2 to 2016 August 1. Magnetic field images consisting of the radial component of the magnetic field are converted to finite sets of ZMs andmore » fed to the support vector machine classifier. ZMs have the capability to elicit unique features from any 2D image, which may allow more accurate classification. The results indicate whether an arbitrary active region has the potential to produce at least one large flare. We show that the majority of large flares can be predicted within 48 hr before their occurrence, with only 10 false negatives out of 385 flaring active region magnetograms and 21 false positives out of 179 non-flaring active region magnetograms. Our method may provide a useful tool for the prediction of solar flares, which can be employed alongside other forecasting methods.« less

"Neural overlap of L1 and L2 semantic representations across visual and auditory modalities: a decoding approach".

PubMed

Van de Putte, Eowyn; De Baene, Wouter; Price, Cathy J; Duyck, Wouter

2018-05-01

This study investigated whether brain activity in Dutch-French bilinguals during semantic access to concepts from one language could be used to predict neural activation during access to the same concepts from another language, in different language modalities/tasks. This was tested using multi-voxel pattern analysis (MVPA), within and across language comprehension (word listening and word reading) and production (picture naming). It was possible to identify the picture or word named, read or heard in one language (e.g. maan, meaning moon) based on the brain activity in a distributed bilateral brain network while, respectively, naming, reading or listening to the picture or word in the other language (e.g. lune). The brain regions identified differed across tasks. During picture naming, brain activation in the occipital and temporal regions allowed concepts to be predicted across languages. During word listening and word reading, across-language predictions were observed in the rolandic operculum and several motor-related areas (pre- and postcentral, the cerebellum). In addition, across-language predictions during reading were identified in regions typically associated with semantic processing (left inferior frontal, middle temporal cortex, right cerebellum and precuneus) and visual processing (inferior and middle occipital regions and calcarine sulcus). Furthermore, across modalities and languages, the left lingual gyrus showed semantic overlap across production and word reading. These findings support the idea of at least partially language- and modality-independent semantic neural representations. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Task-Relevant Information Modulates Primary Motor Cortex Activity Before Movement Onset.

PubMed

Calderon, Cristian B; Van Opstal, Filip; Peigneux, Philippe; Verguts, Tom; Gevers, Wim

2018-01-01

Monkey neurophysiology research supports the affordance competition hypothesis (ACH) proposing that cognitive information useful for action selection is integrated in sensorimotor areas. In this view, action selection would emerge from the simultaneous representation of competing action plans, in parallel biased by relevant task factors. This biased competition would take place up to primary motor cortex (M1). Although ACH is plausible in environments affording choices between actions, its relevance for human decision making is less clear. To address this issue, we designed an functional magnetic resonance imaging (fMRI) experiment modeled after monkey neurophysiology studies in which human participants processed cues conveying predictive information about upcoming button presses. Our results demonstrate that, as predicted by the ACH, predictive information (i.e., the relevant task factor) biases activity of primary motor regions. Specifically, first, activity before movement onset in contralateral M1 increases as the competition is biased in favor of a specific button press relative to activity in ipsilateral M1. Second, motor regions were more tightly coupled with fronto-parietal regions when competition between potential actions was high, again suggesting that motor regions are also part of the biased competition network. Our findings support the idea that action planning dynamics as proposed in the ACH are valid both in human and non-human primates.

Open magnetic fields in active regions

NASA Technical Reports Server (NTRS)

Svestka, Z.; Solodyna, C. V.; Howard, R.; Levine, R. H.

1977-01-01

Soft X-ray images and magnetograms of several active regions and coronal holes are examined which support the interpretation that some of the dark X-ray gaps seen between interconnecting loops and inner cores of active regions are foot points of open field lines inside the active regions. Characteristics of the investigated dark gaps are summarized. All the active regions with dark X-ray gaps at the proper place and with the correct polarity predicted by global potential extrapolation of photospheric magnetic fields are shown to be old active regions, indicating that field opening is accomplished only in a late phase of active-region development. It is noted that some of the observed dark gaps probably have nothing in common with open fields, but are either due to the decreased temperature in low-lying portions of interconnecting loops or are the roots of higher and less dense or cooler loops.

The timing of associative memory formation: frontal lobe and anterior medial temporal lobe activity at associative binding predicts memory

PubMed Central

Hales, J. B.

2011-01-01

The process of associating items encountered over time and across variable time delays is fundamental for creating memories in daily life, such as for stories and episodes. Forming associative memory for temporally discontiguous items involves medial temporal lobe structures and additional neocortical processing regions, including prefrontal cortex, parietal lobe, and lateral occipital regions. However, most prior memory studies, using concurrently presented stimuli, have failed to examine the temporal aspect of successful associative memory formation to identify when activity in these brain regions is predictive of associative memory formation. In the current study, functional MRI data were acquired while subjects were shown pairs of sequentially presented visual images with a fixed interitem delay within pairs. This design allowed the entire time course of the trial to be analyzed, starting from onset of the first item, across the 5.5-s delay period, and through offset of the second item. Subjects then completed a postscan recognition test for the items and associations they encoded during the scan and their confidence for each. After controlling for item-memory strength, we isolated brain regions selectively involved in associative encoding. Consistent with prior findings, increased regional activity predicting subsequent associative memory success was found in anterior medial temporal lobe regions of left perirhinal and entorhinal cortices and in left prefrontal cortex and lateral occipital regions. The temporal separation within each pair, however, allowed extension of these findings by isolating the timing of regional involvement, showing that increased response in these regions occurs during binding but not during maintenance. PMID:21248058

Differences between chronological and brain age are related to education and self-reported physical activity.

PubMed

Steffener, Jason; Habeck, Christian; O'Shea, Deirdre; Razlighi, Qolamreza; Bherer, Louis; Stern, Yaakov

2016-04-01

This study investigated the relationship between education and physical activity and the difference between a physiological prediction of age and chronological age (CA). Cortical and subcortical gray matter regional volumes were calculated from 331 healthy adults (range: 19-79 years). Multivariate analyses identified a covariance pattern of brain volumes best predicting CA (R(2) = 47%). Individual expression of this brain pattern served as a physiologic measure of brain age (BA). The difference between CA and BA was predicted by education and self-report measures of physical activity. Education and the daily number of flights of stairs climbed (FOSC) were the only 2 significant predictors of decreased BA. Effect sizes demonstrated that BA decreased by 0.95 years for each year of education and by 0.58 years for 1 additional FOSC daily. Effects of education and FOSC on regional brain volume were largely driven by temporal and subcortical volumes. These results demonstrate that higher levels of education and daily FOSC are related to larger brain volume than predicted by CA which supports the utility of regional gray matter volume as a biomarker of healthy brain aging. Copyright © 2016 Elsevier Inc. All rights reserved.

A modelling framework to predict bat activity patterns on wind farms: An outline of possible applications on mountain ridges of North Portugal.

PubMed

Silva, Carmen; Cabral, João Alexandre; Hughes, Samantha Jane; Santos, Mário

2017-03-01

Worldwide ecological impact assessments of wind farms have gathered relevant information on bat activity patterns. Since conventional bat study methods require intensive field work, the prediction of bat activity might prove useful by anticipating activity patterns and estimating attractiveness concomitant with the wind farm location. A novel framework was developed, based on the stochastic dynamic methodology (StDM) principles, to predict bat activity on mountain ridges with wind farms. We illustrate the framework application using regional data from North Portugal by merging information from several environmental monitoring programmes associated with diverse wind energy facilities that enable integrating the multifactorial influences of meteorological conditions, land cover and geographical variables on bat activity patterns. Output from this innovative methodology can anticipate episodes of exceptional bat activity, which, if correlated with collision probability, can be used to guide wind farm management strategy such as halting wind turbines during hazardous periods. If properly calibrated with regional gradients of environmental variables from mountain ridges with windfarms, the proposed methodology can be used as a complementary tool in environmental impact assessments and ecological monitoring, using predicted bat activity to assist decision making concerning the future location of wind farms and the implementation of effective mitigation measures. Copyright © 2016 Elsevier B.V. All rights reserved.

Seasonal forecasting of lightning and thunderstorm activity in tropical and temperate regions of the world.

PubMed

Dowdy, Andrew J

2016-02-11

Thunderstorms are convective systems characterised by the occurrence of lightning. Lightning and thunderstorm activity has been increasingly studied in recent years in relation to the El Niño/Southern Oscillation (ENSO) and various other large-scale modes of atmospheric and oceanic variability. Large-scale modes of variability can sometimes be predictable several months in advance, suggesting potential for seasonal forecasting of lightning and thunderstorm activity in various regions throughout the world. To investigate this possibility, seasonal lightning activity in the world's tropical and temperate regions is examined here in relation to numerous different large-scale modes of variability. Of the seven modes of variability examined, ENSO has the strongest relationship with lightning activity during each individual season, with relatively little relationship for the other modes of variability. A measure of ENSO variability (the NINO3.4 index) is significantly correlated to local lightning activity at 53% of locations for one or more seasons throughout the year. Variations in atmospheric parameters commonly associated with thunderstorm activity are found to provide a plausible physical explanation for the variations in lightning activity associated with ENSO. It is demonstrated that there is potential for accurately predicting lightning and thunderstorm activity several months in advance in various regions throughout the world.

Seasonal forecasting of lightning and thunderstorm activity in tropical and temperate regions of the world

PubMed Central

Dowdy, Andrew J.

2016-01-01

Thunderstorms are convective systems characterised by the occurrence of lightning. Lightning and thunderstorm activity has been increasingly studied in recent years in relation to the El Niño/Southern Oscillation (ENSO) and various other large-scale modes of atmospheric and oceanic variability. Large-scale modes of variability can sometimes be predictable several months in advance, suggesting potential for seasonal forecasting of lightning and thunderstorm activity in various regions throughout the world. To investigate this possibility, seasonal lightning activity in the world’s tropical and temperate regions is examined here in relation to numerous different large-scale modes of variability. Of the seven modes of variability examined, ENSO has the strongest relationship with lightning activity during each individual season, with relatively little relationship for the other modes of variability. A measure of ENSO variability (the NINO3.4 index) is significantly correlated to local lightning activity at 53% of locations for one or more seasons throughout the year. Variations in atmospheric parameters commonly associated with thunderstorm activity are found to provide a plausible physical explanation for the variations in lightning activity associated with ENSO. It is demonstrated that there is potential for accurately predicting lightning and thunderstorm activity several months in advance in various regions throughout the world. PMID:26865431

Neural responses to social threat and predictors of cognitive behavioral therapy and acceptance and commitment therapy in social anxiety disorder.

PubMed

Burklund, Lisa J; Torre, Jared B; Lieberman, Matthew D; Taylor, Shelley E; Craske, Michelle G

2017-03-30

Previous research has often highlighted hyperactivity in emotion regions to simple, static social threat cues in social anxiety disorder (SAD). Investigation of the neurobiology of SAD using more naturalistic paradigms can further reveal underlying mechanisms and how these relate to clinical outcomes. We used fMRI to investigate responses to novel dynamic rejection stimuli in individuals with SAD (N=70) and healthy controls (HC; N=17), and whether these responses predicted treatment outcomes following cognitive behavioral therapy (CBT) or acceptance and commitment therapy (ACT). Both HC and SAD groups reported greater distress to rejection compared to neutral social stimuli. At the neural level, HCs exhibited greater activations in social pain/rejection regions, including dorsal anterior cingulate cortex and anterior insula, to rejection stimuli. The SAD group evidenced a different pattern, with no differences in these rejection regions and relatively greater activations in the amygdala and other regions to neutral stimuli. Greater responses in anterior cingulate cortex and the amygdala to rejection vs. neutral stimuli predicted better CBT outcomes. In contrast, enhanced activity in sensory-focused posterior insula predicted ACT responses. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Climate Dynamics and Experimental Prediction (CDEP) and Regional Integrated Science Assessments (RISA) Programs at NOAA Office of Global Programs

NASA Astrophysics Data System (ADS)

Bamzai, A.

2003-04-01

This talk will highlight science and application activities of the CDEP and RISA programs at NOAA OGP. CDEP, through a set of Applied Research Centers (ARCs), supports NOAA's program of quantitative assessments and predictions of global climate variability and its regional implications on time scales of seasons to centuries. The RISA program consolidates results from ongoing disciplinary process research under an integrative framework. Examples of joint CDEP-RISA activities will be presented. Future directions and programmatic challenges will also be discussed.

Predicting Major Solar Eruptions

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2016-05-01

Coronal mass ejections (CMEs) and solar flares are two examples of major explosions from the surface of the Sun but theyre not the same thing, and they dont have to happen at the same time. A recent study examines whether we can predict which solar flares will be closely followed by larger-scale CMEs.Image of a solar flare from May 2013, as captured by NASAs Solar Dynamics Observatory. [NASA/SDO]Flares as a Precursor?A solar flare is a localized burst of energy and X-rays, whereas a CME is an enormous cloud of magnetic flux and plasma released from the Sun. We know that some magnetic activity on the surface of the Sun triggers both a flare and a CME, whereas other activity only triggers a confined flare with no CME.But what makes the difference? Understanding this can help us learn about the underlying physical drivers of flares and CMEs. It also might help us to better predict when a CME which can pose a risk to astronauts, disrupt radio transmissions, and cause damage to satellites might occur.In a recent study, Monica Bobra and Stathis Ilonidis (Stanford University) attempt to improve our ability to make these predictions by using a machine-learning algorithm.Classification by ComputerUsing a combination of 6 or more features results in a much better predictive success (measured by the True Skill Statistic; higher positive value = better prediction) for whether a flare will be accompanied by a CME. [Bobra Ilonidis 2016]Bobra and Ilonidis used magnetic-field data from an instrument on the Solar Dynamics Observatory to build a catalog of solar flares, 56 of which were accompanied by a CME and 364 of which were not. The catalog includes information about 18 different features associated with the photospheric magnetic field of each flaring active region (for example, the mean gradient of the horizontal magnetic field).The authors apply a machine-learning algorithm known as a binary classifier to this catalog. This algorithm tries to predict, given a set of features, whether an active region that produces a flare will also produce a CME. Bobra and Ilonidis then use a feature-selection algorithm to try to understand which features distinguish between flaring regions that dont produce a CME and those that do.Predictors of CMEsThe authors reach several interesting conclusions:Under the right conditions, their algorithm is able to predict whether an active region with a given set of features will produce a CME as well as a flare with a fairly high rate of success.None of the 18 features they tested are good predictors in isolation: its necessary to look at a combination of at least 6 features to have success predicting whether a flare will be accompanied by a CME.The features that are the best predictors are all intensive features ones that stay the same independent of the active regions size. Extensive features ones that change as the active region grows or shrinks are less successful predictors.Only the magnetic field properties of the photosphere were considered, so a logical next step is to extend this study to consider properties of the solar corona above active regions as well. In the meantime, these are interesting first results that may well help us better predict these major solar eruptions.BonusCheck out this video for a great description from NASA of the difference between solar flares and CMEs (as well as some awesome observations of both).CitationM. G. Bobra and S. Ilonidis 2016 ApJ 821 127. doi:10.3847/0004-637X/821/2/127

Abstract Linguistic Structure Correlates with Temporal Activity during Naturalistic Comprehension

PubMed Central

Brennan, Jonathan R.; Stabler, Edward P.; Van Wagenen, Sarah E.; Luh, Wen-Ming; Hale, John T.

2016-01-01

Neurolinguistic accounts of sentence comprehension identify a network of relevant brain regions, but do not detail the information flowing through them. We investigate syntactic information. Does brain activity implicate a computation over hierarchical grammars or does it simply reflect linear order, as in a Markov chain? To address this question, we quantify the cognitive states implied by alternative parsing models. We compare processing-complexity predictions from these states against fMRI timecourses from regions that have been implicated in sentence comprehension. We find that hierarchical grammars independently predict timecourses from left anterior and posterior temporal lobe. Markov models are predictive in these regions and across a broader network that includes the inferior frontal gyrus. These results suggest that while linear effects are wide-spread across the language network, certain areas in the left temporal lobe deal with abstract, hierarchical syntactic representations. PMID:27208858

Spatially aggregated multiclass pattern classification in functional MRI using optimally selected functional brain areas.

PubMed

Zheng, Weili; Ackley, Elena S; Martínez-Ramón, Manel; Posse, Stefan

2013-02-01

In previous works, boosting aggregation of classifier outputs from discrete brain areas has been demonstrated to reduce dimensionality and improve the robustness and accuracy of functional magnetic resonance imaging (fMRI) classification. However, dimensionality reduction and classification of mixed activation patterns of multiple classes remain challenging. In the present study, the goals were (a) to reduce dimensionality by combining feature reduction at the voxel level and backward elimination of optimally aggregated classifiers at the region level, (b) to compare region selection for spatially aggregated classification using boosting and partial least squares regression methods and (c) to resolve mixed activation patterns using probabilistic prediction of individual tasks. Brain activation maps from interleaved visual, motor, auditory and cognitive tasks were segmented into 144 functional regions. Feature selection reduced the number of feature voxels by more than 50%, leaving 95 regions. The two aggregation approaches further reduced the number of regions to 30, resulting in more than 75% reduction of classification time and misclassification rates of less than 3%. Boosting and partial least squares (PLS) were compared to select the most discriminative and the most task correlated regions, respectively. Successful task prediction in mixed activation patterns was feasible within the first block of task activation in real-time fMRI experiments. This methodology is suitable for sparsifying activation patterns in real-time fMRI and for neurofeedback from distributed networks of brain activation. Copyright © 2013 Elsevier Inc. All rights reserved.

Diagnostic Classification of Schizophrenia Patients on the Basis of Regional Reward-Related fMRI Signal Patterns

PubMed Central

Koch, Stefan P.; Hägele, Claudia; Haynes, John-Dylan; Heinz, Andreas; Schlagenhauf, Florian; Sterzer, Philipp

2015-01-01

Functional neuroimaging has provided evidence for altered function of mesolimbic circuits implicated in reward processing, first and foremost the ventral striatum, in patients with schizophrenia. While such findings based on significant group differences in brain activations can provide important insights into the pathomechanisms of mental disorders, the use of neuroimaging results from standard univariate statistical analysis for individual diagnosis has proven difficult. In this proof of concept study, we tested whether the predictive accuracy for the diagnostic classification of schizophrenia patients vs. healthy controls could be improved using multivariate pattern analysis (MVPA) of regional functional magnetic resonance imaging (fMRI) activation patterns for the anticipation of monetary reward. With a searchlight MVPA approach using support vector machine classification, we found that the diagnostic category could be predicted from local activation patterns in frontal, temporal, occipital and midbrain regions, with a maximal cluster peak classification accuracy of 93% for the right pallidum. Region-of-interest based MVPA for the ventral striatum achieved a maximal cluster peak accuracy of 88%, whereas the classification accuracy on the basis of standard univariate analysis reached only 75%. Moreover, using support vector regression we could additionally predict the severity of negative symptoms from ventral striatal activation patterns. These results show that MVPA can be used to substantially increase the accuracy of diagnostic classification on the basis of task-related fMRI signal patterns in a regionally specific way. PMID:25799236

Neural Activity During Health Messaging Predicts Reductions in Smoking Above and Beyond Self-Report

PubMed Central

Falk, Emily B.; Berkman, Elliot T.; Whalen, Danielle; Lieberman, Matthew D.

2011-01-01

Objective The current study tested whether neural activity in response to messages designed to help smokers quit could predict smoking reduction, above and beyond self-report. Design Using neural activity in an a priori region of interest (a subregion of medial prefrontal cortex [MPFC]), in response to ads designed to help smokers quit smoking, we prospectively predicted reductions in smoking in a community sample of smokers (N = 28) who were attempting to quit smoking. Smoking was assessed via expired carbon monoxide (CO; a biological measure of recent smoking) at baseline and 1 month following exposure to professionally developed quitting ads. Results A positive relationship was observed between activity in the MPFC region of interest and successful quitting (increased activity in MPFC was associated with a greater decrease in expired CO). The addition of neural activity to a model predicting changes in CO from self-reported intentions, self-efficacy, and ability to relate to the messages significantly improved model fit, doubling the variance explained ( Rself−report2=.15,Rself−report+neuralactivity2=.35,Rchange2=.20). Conclusion: Neural activity is a useful complement to existing self-report measures. In this investigation, we extend prior work predicting behavior change based on neural activity in response to persuasive media to an important health domain and discuss potential psychological interpretations of the brain–behavior link. Our results support a novel use of neuroimaging technology for understanding the psychology of behavior change and facilitating health promotion. PMID:21261410

Progressive and regressive developmental changes in neural substrates for face processing: Testing specific predictions of the Interactive Specialization account

PubMed Central

Joseph, Jane E.; Gathers, Ann D.; Bhatt, Ramesh S.

2010-01-01

Face processing undergoes a fairly protracted developmental time course but the neural underpinnings are not well understood. Prior fMRI studies have only examined progressive changes (i.e., increases in specialization in certain regions with age), which would be predicted by both the Interactive Specialization (IS) and maturational theories of neural development. To differentiate between these accounts, the present study also examined regressive changes (i.e., decreases in specialization in certain regions with age), which is predicted by the IS but not maturational account. The fMRI results show that both progressive and regressive changes occur, consistent with IS. Progressive changes mostly occurred in occipital-fusiform and inferior frontal cortex whereas regressive changes largely emerged in parietal and lateral temporal cortices. Moreover, inconsistent with the maturational account, all of the regions involved in face viewing in adults were active in children, with some regions already specialized for face processing by 5 years of age and other regions activated in children but not specifically for faces. Thus, neurodevelopment of face processing involves dynamic interactions among brain regions including age-related increases and decreases in specialization and the involvement of different regions at different ages. These results are more consistent with IS than maturational models of neural development. PMID:21399706

On the same wavelength: predictable language enhances speaker-listener brain-to-brain synchrony in posterior superior temporal gyrus.

PubMed

Dikker, Suzanne; Silbert, Lauren J; Hasson, Uri; Zevin, Jason D

2014-04-30

Recent research has shown that the degree to which speakers and listeners exhibit similar brain activity patterns during human linguistic interaction is correlated with communicative success. Here, we used an intersubject correlation approach in fMRI to test the hypothesis that a listener's ability to predict a speaker's utterance increases such neural coupling between speakers and listeners. Nine subjects listened to recordings of a speaker describing visual scenes that varied in the degree to which they permitted specific linguistic predictions. In line with our hypothesis, the temporal profile of listeners' brain activity was significantly more synchronous with the speaker's brain activity for highly predictive contexts in left posterior superior temporal gyrus (pSTG), an area previously associated with predictive auditory language processing. In this region, predictability differentially affected the temporal profiles of brain responses in the speaker and listeners respectively, in turn affecting correlated activity between the two: whereas pSTG activation increased with predictability in the speaker, listeners' pSTG activity instead decreased for more predictable sentences. Listeners additionally showed stronger BOLD responses for predictive images before sentence onset, suggesting that highly predictable contexts lead comprehenders to preactivate predicted words.

Numerical Simulations of Flare-productive Active Regions: δ-sunspots, Sheared Polarity Inversion Lines, Energy Storage, and Predictions

NASA Astrophysics Data System (ADS)

Toriumi, Shin; Takasao, Shinsuke

2017-11-01

Solar active regions (ARs) that produce strong flares and coronal mass ejections (CMEs) are known to have a relatively high non-potentiality and are characterized by δ-sunspots and sheared magnetic structures. In this study, we conduct a series of flux emergence simulations from the convection zone to the corona and model four types of active regions that have been observationally suggested to cause strong flares, namely the spot-spot, spot-satellite, quadrupole, and inter-AR cases. As a result, we confirm that δ-spot formation is due to the complex geometry and interaction of emerging magnetic fields, and we find that the strong-field, high-gradient, highly sheared polarity inversion line (PIL) is created by the combined effect of the advection, stretching, and compression of magnetic fields. We show that free magnetic energy builds up in the form of a current sheet above the PIL. It is also revealed that photospheric magnetic parameters that predict flare eruptions reflect the stored free energy with high accuracy, while CME-predicting parameters indicate the magnetic relationship between flaring zones and entire ARs.

Radon soil gas measurements in a geological versatile region as basis to improve the prediction of areas with a high radon potential.

PubMed

Kabrt, Franz; Seidel, Claudia; Baumgartner, Andreas; Friedmann, Harry; Rechberger, Fabian; Schuff, Michael; Maringer, Franz Josef

2014-07-01

With the aim to predict the radon potential by geological data, radon soil gas measurements were made in a selected region in Styria, Austria. This region is characterised by mean indoor radon potentials of 130-280 Bq m(-3) and a high geological diversity. The distribution of the individual measuring sites was selected on the basis of geological aspects and the distribution of area settlements. In this work, the radon soil gas activity concentration and the soil permeability were measured at 100 sites, each with three single measurements. Furthermore, the local dose rate was determined and soil samples were taken at each site to determine the activity concentration of natural radionuclides. During two investigation periods, long-term soil gas radon measurements were made to study the time dependency of the radon activity concentration. All the results will be compared and investigated for correlation among each other to improve the prediction of areas with high radon potential. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Constraining hot plasma in a non-flaring solar active region with FOXSI hard X-ray observations

NASA Astrophysics Data System (ADS)

Ishikawa, Shin-nosuke; Glesener, Lindsay; Christe, Steven; Ishibashi, Kazunori; Brooks, David H.; Williams, David R.; Shimojo, Masumi; Sako, Nobuharu; Krucker, Säm

2014-12-01

We present new constraints on the high-temperature emission measure of a non-flaring solar active region using observations from the recently flown Focusing Optics X-ray Solar Imager (FOXSI) sounding rocket payload. FOXSI has performed the first focused hard X-ray (HXR) observation of the Sun in its first successful flight on 2012 November 2. Focusing optics, combined with small strip detectors, enable high-sensitivity observations with respect to previous indirect imagers. This capability, along with the sensitivity of the HXR regime to high-temperature emission, offers the potential to better characterize high-temperature plasma in the corona as predicted by nanoflare heating models. We present a joint analysis of the differential emission measure (DEM) of active region 11602 using coordinated observations by FOXSI, Hinode/XRT, and Hinode/EIS. The Hinode-derived DEM predicts significant emission measure between 1 MK and 3 MK, with a peak in the DEM predicted at 2.0-2.5 MK. The combined XRT and EIS DEM also shows emission from a smaller population of plasma above 8 MK. This is contradicted by FOXSI observations that significantly constrain emission above 8 MK. This suggests that the Hinode DEM analysis has larger uncertainties at higher temperatures and that > 8 MK plasma above an emission measure of 3 × 1044 cm-3 is excluded in this active region.

Functional overlap between regions involved in speech perception and in monitoring one's own voice during speech production.

PubMed

Zheng, Zane Z; Munhall, Kevin G; Johnsrude, Ingrid S

2010-08-01

The fluency and the reliability of speech production suggest a mechanism that links motor commands and sensory feedback. Here, we examined the neural organization supporting such links by using fMRI to identify regions in which activity during speech production is modulated according to whether auditory feedback matches the predicted outcome or not and by examining the overlap with the network recruited during passive listening to speech sounds. We used real-time signal processing to compare brain activity when participants whispered a consonant-vowel-consonant word ("Ted") and either heard this clearly or heard voice-gated masking noise. We compared this to when they listened to yoked stimuli (identical recordings of "Ted" or noise) without speaking. Activity along the STS and superior temporal gyrus bilaterally was significantly greater if the auditory stimulus was (a) processed as the auditory concomitant of speaking and (b) did not match the predicted outcome (noise). The network exhibiting this Feedback Type x Production/Perception interaction includes a superior temporal gyrus/middle temporal gyrus region that is activated more when listening to speech than to noise. This is consistent with speech production and speech perception being linked in a control system that predicts the sensory outcome of speech acts and that processes an error signal in speech-sensitive regions when this and the sensory data do not match.

Functional overlap between regions involved in speech perception and in monitoring one’s own voice during speech production

PubMed Central

Zheng, Zane Z.; Munhall, Kevin G; Johnsrude, Ingrid S

2009-01-01

The fluency and reliability of speech production suggests a mechanism that links motor commands and sensory feedback. Here, we examine the neural organization supporting such links by using fMRI to identify regions in which activity during speech production is modulated according to whether auditory feedback matches the predicted outcome or not, and examining the overlap with the network recruited during passive listening to speech sounds. We use real-time signal processing to compare brain activity when participants whispered a consonant-vowel-consonant word (‘Ted’) and either heard this clearly, or heard voice-gated masking noise. We compare this to when they listened to yoked stimuli (identical recordings of ‘Ted’ or noise) without speaking. Activity along the superior temporal sulcus (STS) and superior temporal gyrus (STG) bilaterally was significantly greater if the auditory stimulus was a) processed as the auditory concomitant of speaking and b) did not match the predicted outcome (noise). The network exhibiting this Feedback type by Production/Perception interaction includes an STG/MTG region that is activated more when listening to speech than to noise. This is consistent with speech production and speech perception being linked in a control system that predicts the sensory outcome of speech acts, and that processes an error signal in speech-sensitive regions when this and the sensory data do not match. PMID:19642886

In sync: gamma oscillations and emotional memory

PubMed Central

Headley, Drew B.; Paré, Denis

2013-01-01

Emotional experiences leave vivid memories that can last a lifetime. The emotional facilitation of memory has been attributed to the engagement of diffusely projecting neuromodulatory systems that enhance the consolidation of synaptic plasticity in regions activated by the experience. This process requires the propagation of signals between brain regions, and for those signals to induce long-lasting synaptic plasticity. Both of these demands are met by gamma oscillations, which reflect synchronous population activity on a fast timescale (35–120 Hz). Regions known to participate in the formation of emotional memories, such as the basolateral amygdala, also promote gamma-band activation throughout cortical and subcortical circuits. Recent studies have demonstrated that gamma oscillations are enhanced during emotional situations, coherent between regions engaged by salient stimuli, and predict subsequent memory for cues associated with aversive stimuli. Furthermore, neutral stimuli that come to predict emotional events develop enhanced gamma oscillations, reflecting altered processing in the brain, which may underpin how past emotional experiences color future learning and memory. PMID:24319416

In sync: gamma oscillations and emotional memory.

PubMed

Headley, Drew B; Paré, Denis

2013-11-21

Emotional experiences leave vivid memories that can last a lifetime. The emotional facilitation of memory has been attributed to the engagement of diffusely projecting neuromodulatory systems that enhance the consolidation of synaptic plasticity in regions activated by the experience. This process requires the propagation of signals between brain regions, and for those signals to induce long-lasting synaptic plasticity. Both of these demands are met by gamma oscillations, which reflect synchronous population activity on a fast timescale (35-120 Hz). Regions known to participate in the formation of emotional memories, such as the basolateral amygdala, also promote gamma-band activation throughout cortical and subcortical circuits. Recent studies have demonstrated that gamma oscillations are enhanced during emotional situations, coherent between regions engaged by salient stimuli, and predict subsequent memory for cues associated with aversive stimuli. Furthermore, neutral stimuli that come to predict emotional events develop enhanced gamma oscillations, reflecting altered processing in the brain, which may underpin how past emotional experiences color future learning and memory.

Co-endemicity of Pulmonary Tuberculosis and Intestinal Helminth Infection in the People’s Republic of China

PubMed Central

Li, Xin-Xu; Ren, Zhou-Peng; Wang, Li-Xia; Zhang, Hui; Jiang, Shi-Wen; Chen, Jia-Xu; Wang, Jin-Feng; Zhou, Xiao-Nong

2016-01-01

Both pulmonary tuberculosis (PTB) and intestinal helminth infection (IHI) affect millions of individuals every year in China. However, the national-scale estimation of prevalence predictors and prevalence maps for these diseases, as well as co-endemic relative risk (RR) maps of both diseases’ prevalence are not well developed. There are co-endemic, high prevalence areas of both diseases, whose delimitation is essential for devising effective control strategies. Bayesian geostatistical logistic regression models including socio-economic, climatic, geographical and environmental predictors were fitted separately for active PTB and IHI based on data from the national surveys for PTB and major human parasitic diseases that were completed in 2010 and 2004, respectively. Prevalence maps and co-endemic RR maps were constructed for both diseases by means of Bayesian Kriging model and Bayesian shared component model capable of appraising the fraction of variance of spatial RRs shared by both diseases, and those specific for each one, under an assumption that there are unobserved covariates common to both diseases. Our results indicate that gross domestic product (GDP) per capita had a negative association, while rural regions, the arid and polar zones and elevation had positive association with active PTB prevalence; for the IHI prevalence, GDP per capita and distance to water bodies had a negative association, the equatorial and warm zones and the normalized difference vegetation index had a positive association. Moderate to high prevalence of active PTB and low prevalence of IHI were predicted in western regions, low to moderate prevalence of active PTB and low prevalence of IHI were predicted in north-central regions and the southeast coastal regions, and moderate to high prevalence of active PTB and high prevalence of IHI were predicted in the south-western regions. Thus, co-endemic areas of active PTB and IHI were located in the south-western regions of China, which might be determined by socio-economic factors, such as GDP per capita. PMID:27088504

Flare Prediction Using Photospheric and Coronal Image Data

NASA Astrophysics Data System (ADS)

Jonas, E.; Shankar, V.; Bobra, M.; Recht, B.

2016-12-01

We attempt to forecast M-and X-class solar flares using a machine-learning algorithm and five years of image data from both the Helioseismic and Magnetic Imager (HMI) and Atmospheric Imaging Assembly (AIA) instruments aboard the Solar Dynamics Observatory. HMI is the first instrument to continuously map the full-disk photospheric vector magnetic field from space (Schou et al., 2012). The AIA instrument maps the transition region and corona using various ultraviolet wavelengths (Lemen et al., 2012). HMI and AIA data are taken nearly simultaneously, providing an opportunity to study the entire solar atmosphere at a rapid cadence. Most flare forecasting efforts described in the literature use some parameterization of solar data - typically of the photospheric magnetic field within active regions. These numbers are considered to capture the information in any given image relevant to predicting solar flares. In our approach, we use HMI and AIA images of solar active regions and a deep convolutional kernel network to predict solar flares. This is effectively a series of shallow-but-wide random convolutional neural networks stacked and then trained with a large-scale block-weighted least squares solver. This algorithm automatically determines which patterns in the image data are most correlated with flaring activity and then uses these patterns to predict solar flares. Using the recently-developed KeystoneML machine learning framework, we construct a pipeline to process millions of images in a few hours on commodity cloud computing infrastructure. This is the first time vector magnetic field images have been combined with coronal imagery to forecast solar flares. This is also the first time such a large dataset of solar images, some 8.5 terabytes of images that together capture over 3000 active regions, has been used to forecast solar flares. We evaluate our method using various flare prediction windows defined in the literature (e.g. Ahmed et al., 2013) and a novel per-hour time series we've constructed which more closely mimics the demands of an operational solar flare prediction system. We estimate the performance of our algorithm using the True Skill Statistic (TSS; Bloomfield et al., 2012). We find that our algorithm gives a high TSS score and predictive abilities.

Interannual variability and predictability over the Arabian Penuinsula Winter monsoon region

NASA Astrophysics Data System (ADS)

Adnan Abid, Muhammad; Kucharski, Fred; Almazroui, Mansour; Kang, In-Sik

2016-04-01

Interannual winter rainfall variability and its predictability are analysed over the Arabian Peninsula region by using observed and hindcast datasets from the state-of-the-art European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal prediction System 4 for the period 1981-2010. An Arabian winter monsoon index (AWMI) is defined to highlight the Arabian Peninsula as the most representative region for the Northern Hemispheric winter dominating the summer rainfall. The observations show that the rainfall variability is relatively large over the northeast of the Arabian Peninsula. The correlation coefficient between the Nino3.4 index and rainfall in this region is 0.33, suggesting potentially some modest predictability, and indicating that El Nino increases and La Nina decreases the rainfall. Regression analysis shows that upper-level cyclonic circulation anomalies that are forced by El Nino Southern Oscillation (ENSO) are responsible for the winter rainfall anomalies over the Arabian region. The stronger (weaker) mean transient-eddy activity related to the upper-level trough induced by the warm (cold) sea-surface temperatures during El Nino (La Nina) tends to increase (decrease) the rainfall in the region. The model hindcast dataset reproduces the ENSO-rainfall connection. The seasonal mean predictability of the northeast Arabian rainfall index is 0.35. It is shown that the noise variance is larger than the signal over the Arabian Peninsula region, which tends to limit the prediction skill. The potential predictability is generally increased in ENSO years and is, in particular, larger during La Nina compared to El Nino years in the region. Furthermore, central Pacific ENSO events and ENSO events with weak signals in the Indian Ocean tend to increase predictability over the Arabian region.

ACTIVE REGION MORPHOLOGIES SELECTED FROM NEAR-SIDE HELIOSEISMIC DATA

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacDonald, G. A.; McAteer, R. T. J.; Henney, C. J.

We estimate the morphology of near-side active regions using near-side helioseismology. Active regions from two data sets, Air Force Data Assimilative Photospheric flux Transport synchronic maps and Global Oscillation Network Group near-side helioseismic maps, were matched and their morphologies compared. Our algorithm recognizes 382 helioseismic active regions between 2002 April 25 and 2005 December 31 and matches them to their corresponding magnetic active regions with 100% success. A magnetic active region occupies 30% of the area of its helioseismic signature. Recovered helioseismic tilt angles are in good agreement with magnetic tilt angles. Approximately 20% of helioseismic active regions can bemore » decomposed into leading and trailing polarity. Leading polarity components show no discernible scaling relationship, but trailing magnetic polarity components occupy approximately 25% of the area of the trailing helioseismic component. A nearside phase-magnetic calibration is in close agreement with a previous far-side helioseismic calibration and provides confidence that these morphological relationships can be used with far-side helioseismic data. Including far-side active region morphology in synchronic maps will have implications for coronal magnetic topology predictions and solar wind forecasts.« less

Behavior of predicted convective clouds and precipitation in the high-resolution Unified Model over the Indian summer monsoon region

NASA Astrophysics Data System (ADS)

Jayakumar, A.; Sethunadh, Jisesh; Rakhi, R.; Arulalan, T.; Mohandas, Saji; Iyengar, Gopal R.; Rajagopal, E. N.

2017-05-01

National Centre for Medium Range Weather Forecasting high-resolution regional convective-scale Unified Model with latest tropical science settings is used to evaluate vertical structure of cloud and precipitation over two prominent monsoon regions: Western Ghats (WG) and Monsoon Core Zone (MCZ). Model radar reflectivity generated using Cloud Feedback Model Intercomparison Project Observation Simulator Package along with CloudSat profiling radar reflectivity is sampled for an active synoptic situation based on a new method using Budyko's index of turbulence (BT). Regime classification based on BT-precipitation relationship is more predominant during the active monsoon period when convective-scale model's resolution increases from 4 km to 1.5 km. Model predicted precipitation and vertical distribution of hydrometeors are found to be generally in agreement with Global Precipitation Measurement products and BT-based CloudSat observation, respectively. Frequency of occurrence of radar reflectivity from model implies that the low-level clouds below freezing level is underestimated compared to the observations over both regions. In addition, high-level clouds in the model predictions are much lesser over WG than MCZ.

Clinical value of gallium-67 scintigraphy in assessment of disease activity in Wegener's granulomatosis

PubMed Central

Slart, R; Jager, P; Poot, L; Piers, D; Cohen, T; Stegeman, C

2003-01-01

Background: Diagnosis of active pulmonary and paranasal involvement in patients with Wegener's granulomatosis (WG) can be difficult. The diagnostic value of gallium-67 scintigraphy in WG is unclear. Objective: To evaluate the added diagnostic value of gallium-67 scintigraphy in patients with WG with suspected granulomatous inflammation in the paranasal and chest regions. Methods: Retrospectively, the diagnostic contribution of chest and head planar gallium scans in 40 episodes of suspected vasculitis disease activity in 28 patients with WG was evaluated. Scans were grouped into normal or increased uptake for each region. Histological proof or response to treatment was the "gold standard" for the presence of WG activity. Results: WG activity was confirmed in 8 (20%) episodes, with pulmonary locations in three, paranasal in four, and both in one (n=7 patients); all these gallium scans showed increased gallium uptake (sensitivity 100%). Gallium scans were negative for the pulmonary area in 23/36 scans (specificity 64%), and negative for paranasal activity in 13/16 scans (specificity 81%) in episodes without WG activity. Positive predictive value of WG activity for lungs and paranasal region was 24% and 63%, respectively, negative predictive value was 100% for both regions. False positive findings were caused by bacterial or viral infections. Conclusion: Gallium scans are clinically helpful as a negative scan virtually excludes active WG. Gallium scintigraphy of chest and nasal region has a high sensitivity for the detection of disease activity in WG. However, because of positive scans in cases of bacterial or viral infections, specificity was lower. PMID:12810430

Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub-continental scales.

PubMed

Collins, Sarah M; Oliver, Samantha K; Lapierre, Jean-Francois; Stanley, Emily H; Jones, John R; Wagner, Tyler; Soranno, Patricia A

2017-07-01

Production in many ecosystems is co-limited by multiple elements. While a known suite of drivers associated with nutrient sources, nutrient transport, and internal processing controls concentrations of phosphorus (P) and nitrogen (N) in lakes, much less is known about whether the drivers of single nutrient concentrations can also explain spatial or temporal variation in lake N:P stoichiometry. Predicting stoichiometry might be more complex than predicting concentrations of individual elements because some drivers have similar relationships with N and P, leading to a weak relationship with their ratio. Further, the dominant controls on elemental concentrations likely vary across regions, resulting in context dependent relationships between drivers, lake nutrients and their ratios. Here, we examine whether known drivers of N and P concentrations can explain variation in N:P stoichiometry, and whether explaining variation in stoichiometry differs across regions. We examined drivers of N:P in ~2,700 lakes at a sub-continental scale and two large regions nested within the sub-continental study area that have contrasting ecological context, including differences in the dominant type of land cover (agriculture vs. forest). At the sub-continental scale, lake nutrient concentrations were correlated with nutrient loading and lake internal processing, but stoichiometry was only weakly correlated to drivers of lake nutrients. At the regional scale, drivers that explained variation in nutrients and stoichiometry differed between regions. In the Midwestern U.S. region, dominated by agricultural land use, lake depth and the percentage of row crop agriculture were strong predictors of stoichiometry because only phosphorus was related to lake depth and only nitrogen was related to the percentage of row crop agriculture. In contrast, all drivers were related to N and P in similar ways in the Northeastern U.S. region, leading to weak relationships between drivers and stoichiometry. Our results suggest ecological context mediates controls on lake nutrients and stoichiometry. Predicting stoichiometry was generally more difficult than predicting nutrient concentrations, but human activity may decouple N and P, leading to better prediction of N:P stoichiometry in regions with high anthropogenic activity. © 2017 by the Ecological Society of America.

Lake nutrient stoichiometry is less predictable than nutrient concentrations at regional and sub-continental scales

USGS Publications Warehouse

Collins, Sarah M.; Oliver, Samantha K.; Lapierre, Jean-Francois; Stanley, Emily H.; Jones, John R.; Wagner, Tyler; Soranno, Patricia A.

2017-01-01

Production in many ecosystems is co-limited by multiple elements. While a known suite of drivers associated with nutrient sources, nutrient transport, and internal processing controls concentrations of phosphorus (P) and nitrogen (N) in lakes, much less is known about whether the drivers of single nutrient concentrations can also explain spatial or temporal variation in lake N:P stoichiometry. Predicting stoichiometry might be more complex than predicting concentrations of individual elements because some drivers have similar relationships with N and P, leading to a weak relationship with their ratio. Further, the dominant controls on elemental concentrations likely vary across regions, resulting in context dependent relationships between drivers, lake nutrients and their ratios. Here, we examine whether known drivers of N and P concentrations can explain variation in N:P stoichiometry, and whether explaining variation in stoichiometry differs across regions. We examined drivers of N:P in ~2,700 lakes at a sub-continental scale and two large regions nested within the sub-continental study area that have contrasting ecological context, including differences in the dominant type of land cover (agriculture vs. forest). At the sub-continental scale, lake nutrient concentrations were correlated with nutrient loading and lake internal processing, but stoichiometry was only weakly correlated to drivers of lake nutrients. At the regional scale, drivers that explained variation in nutrients and stoichiometry differed between regions. In the Midwestern U.S. region, dominated by agricultural land use, lake depth and the percentage of row crop agriculture were strong predictors of stoichiometry because only phosphorus was related to lake depth and only nitrogen was related to the percentage of row crop agriculture. In contrast, all drivers were related to N and P in similar ways in the Northeastern U.S. region, leading to weak relationships between drivers and stoichiometry. Our results suggest ecological context mediates controls on lake nutrients and stoichiometry. Predicting stoichiometry was generally more difficult than predicting nutrient concentrations, but human activity may decouple N and P, leading to better prediction of N:P stoichiometry in regions with high anthropogenic activity.

Distortion in the spacer region of Pm during activation of middle transcription of phage Mu.

PubMed Central

Artsimovitch, I; Kahmeyer-Gabbe, M; Howe, M M

1996-01-01

Transcription from the middle promoter, Pm, of phage Mu is initiated by Escherichia coli RNA polymerase holoenzyme (E sigma 70; RNAP) and the phage-encoded activator, Mor. Point mutations in the spacer region between the -10 hexamer and the Mor binding site result in changes of promoter activity in vivo. These mutations are located at the junction between a rigid T-tract and adjacent, potentially deformable G + C-rich DNA segment, suggesting that deformation of the spacer region may play a role in the transcriptional activation of Pm. This prediction was tested by using dimethyl sulfate and potassium permanganate footprinting analyses. Helical distortion involving strand separation was detected at positions -32 to -34, close to the predicted interface between Mor and RNAP. Promoter mutants in which this distortion was not detected exhibited a lack of melting in the -12 to -1 region and reduced promoter activity in vivo. We propose that complexes containing the distortion represent stressed intermediates rather than stable open complexes and thus can be envisaged as a transition state in the kinetic pathway of Pm activation in which stored torsional energy could be used to facilitate melting around the transcription start point. Images Fig. 2 Fig. 3 Fig. 4 PMID:8790343

Structure-Based Predictions of Activity Cliffs

PubMed Central

Husby, Jarmila; Bottegoni, Giovanni; Kufareva, Irina; Abagyan, Ruben; Cavalli, Andrea

2015-01-01

In drug discovery, it is generally accepted that neighboring molecules in a given descriptors' space display similar activities. However, even in regions that provide strong predictability, structurally similar molecules can occasionally display large differences in potency. In QSAR jargon, these discontinuities in the activity landscape are known as ‘activity cliffs’. In this study, we assessed the reliability of ligand docking and virtual ligand screening schemes in predicting activity cliffs. We performed our calculations on a diverse, independently collected database of cliff-forming co-crystals. Starting from ideal situations, which allowed us to establish our baseline, we progressively moved toward simulating more realistic scenarios. Ensemble- and template-docking achieved a significant level of accuracy, suggesting that, despite the well-known limitations of empirical scoring schemes, activity cliffs can be accurately predicted by advanced structure-based methods. PMID:25918827

Does oculomotor readiness mediate exogenous capture of visual attention?

PubMed

MacLean, Gregory H; Klein, Raymond M; Hilchey, Matthew D

2015-10-01

The oculomotor readiness hypothesis makes 2 predictions: Shifts in covert attention are accompanied by preparedness to move one's eyes to the attended region, and preparedness to move one's eyes to a region in space is accompanied by a shift in covert attention to the prepared location. Both predictions have been disconfirmed using an endogenous attention task. In the 2 experiments presented here, the same 2 predictions were tested using an exogenous attention task. It was found that participants experienced covert capture without accompanying oculomotor activation and experienced oculomotor activation without accompanying covert capture. While under everyday conditions the overt and covert orienting systems may be strongly linked, apparently they can nonetheless operate with a high degree of independence from one another. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Proceedings, 1995 meeting of the Northern Global Change Program; 1995 March 14-16; Pittsburgh, PA. : Introduction/Environmental Change

Treesearch

John Hom; Richard Birdsey; Kelly O' Brian; eds.

1996-01-01

Contains articles presented at the 1995 Northern Global Change Program meeting on the following topics: monitoring and predicting regional environmental change, responses of northern tree species to regional stress, responses of ecosystem processes to regional stress, forest and landscape responses to regional stress and management activities, human-forest interactions...

Superoxide radical-generating compounds activate a predicted promoter site for paraquat-inducible genes of the Chromobacterium violaceum bacterium in a dose-dependent manner.

PubMed

Gabriel, J E; Guerra-Slompo, E P; de Souza, E M; de Carvalho, F A L; Madeira, H M F; de Vasconcelos, A T R

2015-08-21

The purpose of the present study was to functionally evaluate the influence of superoxide radical-generating compounds on the heterologous induction of a predicted promoter region of open reading frames for paraquat-inducible genes (pqi genes) revealed during genome annotation analyses of the Chromobacterium violaceum bacterium. A 388-bp fragment corresponding to a pqi gene promoter of C. violaceum was amplified using specific primers and cloned into a conjugative vector containing the Escherichia coli lacZ gene without a promoter. Assessments of the expression of the β-galactosidase enzyme were performed in the presence of menadione (MEN) and phenazine methosulfate (PMS) compounds at different final concentrations to evaluate the heterologous activation of the predicted promoter region of interest in C. violaceum induced by these substrates. Under these experimental conditions, the MEN reagent promoted highly significant increases in the expression of the β-galactosidase enzyme modulated by activating the promoter region of the pqi genes at all concentrations tested. On the other hand, significantly higher levels in the expression of the β-galactosidase enzyme were detected exclusively in the presence of the PMS reagent at a final concentration of 50 μg/mL. The findings described in the present study demonstrate that superoxide radical-generating compounds can activate a predicted promoter DNA motif for pqi genes of the C. violaceum bacterium in a dose-dependent manner.

Concepts in context: Processing mental state concepts with internal or external focus involves different neural systems

PubMed Central

Oosterwijk, Suzanne; Mackey, Scott; Wilson-Mendenhall, Christine; Winkielman, Piotr; Paulus, Martin P.

2015-01-01

According to embodied cognition theories concepts are contextually-situated and grounded in neural systems that produce experiential states. This view predicts that processing mental state concepts recruits neural regions associated with different aspects of experience depending on the context in which people understand a concept. This neuroimaging study tested this prediction using a set of sentences that described emotional (e.g., fear, joy) and non-emotional (e.g., thinking, hunger) mental states with internal focus (i.e. focusing on bodily sensations and introspection) or external focus (i.e. focusing on expression and action). Consistent with our predictions, data suggested that the inferior frontal gyrus, a region associated with action representation, was engaged more by external than internal sentences. By contrast, the ventromedial prefrontal cortex, a region associated with the generation of internal states, was engaged more by internal emotion sentences than external sentence categories. Similar patterns emerged when we examined the relationship between neural activity and independent ratings of sentence focus. Furthermore, ratings of emotion were associated with activation in the medial prefrontal cortex, whereas ratings of activity were associated with activation in the inferior frontal gyrus. These results suggest that mental state concepts are represented in a dynamic way, using context-relevant interoceptive and sensorimotor resources. PMID:25748274

Words in Context: The Effects of Length, Frequency, and Predictability on Brain Responses During Natural Reading

PubMed Central

Schuster, Sarah; Hawelka, Stefan; Hutzler, Florian; Kronbichler, Martin; Richlan, Fabio

2016-01-01

Word length, frequency, and predictability count among the most influential variables during reading. Their effects are well-documented in eye movement studies, but pertinent evidence from neuroimaging primarily stem from single-word presentations. We investigated the effects of these variables during reading of whole sentences with simultaneous eye-tracking and functional magnetic resonance imaging (fixation-related fMRI). Increasing word length was associated with increasing activation in occipital areas linked to visual analysis. Additionally, length elicited a U-shaped modulation (i.e., least activation for medium-length words) within a brain stem region presumably linked to eye movement control. These effects, however, were diminished when accounting for multiple fixation cases. Increasing frequency was associated with decreasing activation within left inferior frontal, superior parietal, and occipito-temporal regions. The function of the latter region—hosting the putative visual word form area—was originally considered as limited to sublexical processing. An exploratory analysis revealed that increasing predictability was associated with decreasing activation within middle temporal and inferior frontal regions previously implicated in memory access and unification. The findings are discussed with regard to their correspondence with findings from single-word presentations and with regard to neurocognitive models of visual word recognition, semantic processing, and eye movement control during reading. PMID:27365297

What Fraction of Global Fire Activity Can Be Forecast Using Sea Surface Temperatures?

NASA Astrophysics Data System (ADS)

Chen, Y.; Randerson, J. T.; Morton, D. C.; Andela, N.; Giglio, L.

2015-12-01

Variations in sea surface temperatures (SSTs) can influence climate dynamics in local and remote land areas, and thus influence fire-climate interactions that govern burned area. SST information has been recently used in statistical models to create seasonal outlooks of fire season severity in South America and as the initial condition for dynamical model predictions of fire activity in Indonesia. However, the degree to which large-scale ocean-atmosphere interactions can influence burned area in other continental regions has not been systematically explored. Here we quantified the amount of global burned area that can be predicted using SSTs in 14 different oceans regions as statistical predictors. We first examined lagged correlations between GFED4s burned area and the 14 ocean climate indices (OCIs) individually. The maximum correlations from different OCIs were used to construct a global map of fire predictability. About half of the global burned area can be forecast by this approach 3 months before the peak burning month (with a Pearson's r of 0.5 or higher), with the highest levels of predictability in Central America and Equatorial Asia. Several hotspots of predictability were identified using k-means cluster analysis. Within these regions, we tested the improvements of the forecast by using two OCIs from different oceans. Our forecast models were based on near-real-time SST data and may therefore support the development of new seasonal outlooks for fire activity that can aid the sustainable management of these fire-prone ecosystems.

Software Displays Data on Active Regions of the Sun

NASA Technical Reports Server (NTRS)

Golightly, Mike; Weyland, Mark; Raben, Vern

2011-01-01

The Solar Active Region Display System is a computer program that generates, in near real time, a graphical display of parameters indicative of the spatial and temporal variations of activity on the Sun. These parameters include histories and distributions of solar flares, active region growth, coronal mass ejections, size, and magnetic configuration. By presenting solar-activity data in graphical form, this program accelerates, facilitates, and partly automates what had previously been a time-consuming mental process of interpretation of solar-activity data presented in tabular and textual formats. Intended for original use in predicting space weather in order to minimize the exposure of astronauts to ionizing radiation, the program might also be useful on Earth for predicting solar-wind-induced ionospheric effects, electric currents, and potentials that could affect radio-communication systems, navigation systems, pipelines, and long electric-power lines. Raw data for the display are obtained automatically from the Space Environment Center (SEC) of the National Oceanic and Atmospheric Administration (NOAA). Other data must be obtained from the NOAA SEC by verbal communication and entered manually. The Solar Active Region Display System automatically accounts for the latitude dependence of the rate of rotation of the Sun, by use of a mathematical model that is corrected with NOAA SEC active-region position data once every 24 hours. The display includes the date, time, and an image of the Sun in H light overlaid with latitude and longitude coordinate lines, dots that mark locations of active regions identified by NOAA, identifying numbers assigned by NOAA to such regions, and solar-region visual summary (SRVS) indicators associated with some of the active regions. Each SRVS indicator is a small pie chart containing five equal sectors, each of which is color-coded to provide a semiquantitative indication of the degree of hazard posed by one aspect of the activity at the indicated location. The five aspects in question are the history of solar flares, the history of coronal mass ejections, the growth or decay of activity, the overall size, and the magnetic configuration. Mouse-clicking on an active-region-marking dot, SRVS indicator, or NOAA region number causes the program to generate a solar-region summary table (SRT) for the active region in question. The SRT contains additional quantitative and qualitative data, beyond those contained in the SRVS: These data include the solar coordinates of the region, the area of the region and its change in area during the past 24 hours, the change in the number of sunspots in the region during the past 24 hours, the magnetic configuration, and the types, dates, and times of the most recent flare and coronal mass ejection.

Implicit Race Bias Decreases the Similarity of Neural Representations of Black and White Faces

PubMed Central

Brosch, Tobias; Bar-David, Eyal; Phelps, Elizabeth A.

2013-01-01

Implicit race bias has been shown to affect decisions and behaviors. It may also change perceptual experience by increasing perceived differences between social groups. We investigated how this phenomenon may be expressed at the neural level by testing whether the distributed blood-oxygenation-level-dependent (BOLD) patterns representing Black and White faces are more dissimilar in participants with higher implicit race bias. We used multivoxel pattern analysis to predict the race of faces participants were viewing. We successfully predicted the race of the faces on the basis of BOLD activation patterns in early occipital visual cortex, occipital face area, and fusiform face area (FFA). Whereas BOLD activation patterns in early visual regions, likely reflecting different perceptual features, allowed successful prediction for all participants, successful prediction on the basis of BOLD activation patterns in FFA, a high-level face-processing region, was restricted to participants with high pro-White bias. These findings suggest that stronger implicit pro-White bias decreases the similarity of neural representations of Black and White faces. PMID:23300228

GABA(A) receptors in visual and auditory cortex and neural activity changes during basic visual stimulation.

PubMed

Qin, Pengmin; Duncan, Niall W; Wiebking, Christine; Gravel, Paul; Lyttelton, Oliver; Hayes, Dave J; Verhaeghe, Jeroen; Kostikov, Alexey; Schirrmacher, Ralf; Reader, Andrew J; Northoff, Georg

2012-01-01

Recent imaging studies have demonstrated that levels of resting γ-aminobutyric acid (GABA) in the visual cortex predict the degree of stimulus-induced activity in the same region. These studies have used the presentation of discrete visual stimulus; the change from closed eyes to open also represents a simple visual stimulus, however, and has been shown to induce changes in local brain activity and in functional connectivity between regions. We thus aimed to investigate the role of the GABA system, specifically GABA(A) receptors, in the changes in brain activity between the eyes closed (EC) and eyes open (EO) state in order to provide detail at the receptor level to complement previous studies of GABA concentrations. We conducted an fMRI study involving two different modes of the change from EC to EO: an EO and EC block design, allowing the modeling of the haemodynamic response, followed by longer periods of EC and EO to allow the measuring of functional connectivity. The same subjects also underwent [(18)F]Flumazenil PET to measure GABA(A) receptor binding potentials. It was demonstrated that the local-to-global ratio of GABA(A) receptor binding potential in the visual cortex predicted the degree of changes in neural activity from EC to EO. This same relationship was also shown in the auditory cortex. Furthermore, the local-to-global ratio of GABA(A) receptor binding potential in the visual cortex also predicted the change in functional connectivity between the visual and auditory cortex from EC to EO. These findings contribute to our understanding of the role of GABA(A) receptors in stimulus-induced neural activity in local regions and in inter-regional functional connectivity.

THE POSSIBLE IMPACT OF L5 MAGNETOGRAMS ON NON-POTENTIAL SOLAR CORONAL MAGNETIC FIELD SIMULATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weinzierl, Marion; Yeates, Anthony R.; Mackay, Duncan H.

The proposed Carrington-L5 mission would bring instruments to the L5 Lagrange point to provide us with crucial data for space weather prediction. To assess the importance of including a magnetograph, we consider the possible differences in non-potential solar coronal magnetic field simulations when magnetograph observations are available from the L5 point, compared with an L1-based field of view (FOV). A timeseries of synoptic radial magnetic field maps is constructed to capture the emergence of two active regions from the L5 FOV. These regions are initially absent in the L1 magnetic field maps, but are included once they rotate into themore » L1 FOV. Non-potential simulations for these two sets of input data are compared in detail. Within the bipolar active regions themselves, differences in the magnetic field structure can exist between the two simulations once the active regions are included in both. These differences tend to reduce within 5 days of the active region being included in L1. The delayed emergence in L1 can, however, lead to significant persistent differences in long-range connectivity between the active regions and the surrounding fields, and also in the global magnetic energy. In particular, the open magnetic flux and the location of open magnetic footpoints, are sensitive to capturing the real-time of emergence. These results suggest that a magnetograph at L5 could significantly improve predictions of the non-potential corona, the interplanetary magnetic field, and of solar wind source regions on the Sun.« less

Toward Skillful Subseasonal Prediction of North Atlantic Hurricanes with regionally-refined GFDL HiRAM

NASA Astrophysics Data System (ADS)

Gao, K.; Harris, L.; Chen, J. H.; Lin, S. J.

2017-12-01

Skillful subseasonal prediction of hurricane activity (from two weeks to less than a season) is important for early preparedness and reducing the hurricane damage in coastal regions. In this study, we will present evaluations of the performance of GFDL HiRAM (High-Resolution Atmospheric Model) for the simulation and prediction of the North Atlantic hurricane activity on the sub-seasonal time scale. A series of sub-seasonal (30-day duration) retrospective predictions were performed over the years 2000-2014 using two configurations of HiRAM: a) global uniform 25km-resolution grid and b) two-way nested grid with a 8km-resolution nest over North Atlantic. The analysis of hurricane structure from the two sets of simulations indicates the two-way-nesting method is an efficient way to improve the representation of hurricanes in global models: the two-way nested configuration produces realistic hurricane inner-core size and structure, which leads to improved lifetime maximum intensity distribution. Both configurations show very promising performance in the subseasonal hurricane genesis prediction, but the two-way nested configuration shows better performance in the prediction of major hurricane (Categories 3-5) activity because of the improved intensity simulation. We will also present the analysis of how the phase and magnitude of MJO, as well as the initial SST anomaly affect the model's prediction skill.

HOT PLASMA FROM SOLAR ACTIVE REGION CORES: A TEST OF AC AND DC CORONAL HEATING MODELS?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmelz, J. T.; Christian, G. M.; Dhaliwal, R. S.

2015-06-20

Direct current (DC) models of solar coronal heating invoke magnetic reconnection to convert magnetic free energy into heat, whereas alternating current (AC) models invoke wave dissipation. In both cases the energy is supplied by photospheric footpoint motions. For a given footpoint velocity amplitude, DC models predict lower average heating rates but greater temperature variability when compared to AC models. Therefore, evidence of hot plasma (T > 5 MK) in the cores of active regions could be one of the ways for current observations to distinguish between AC and DC models. We have analyzed data from the X-Ray Telescope (XRT) andmore » the Atmospheric Imaging Assembly for 12 quiescent active region cores, all of which were observed in the XRT Be-thick channel. We did Differential Emission Measure (DEM) analysis and achieved good fits for each data set. We then artificially truncated the hot plasma of the DEM model at 5 MK and examined the resulting fits to the data. For some regions in our sample, the XRT intensities continued to be well-matched by the DEM predictions, even without the hot plasma. This truncation, however, resulted in unacceptable fits for the other regions. This result indicates that the hot plasma is present in these regions, even if the precise DEM distribution cannot be determined with the data available. We conclude that reconnection may be heating the hot plasma component of these active regions.« less

Dissociable effects of surprise and model update in parietal and anterior cingulate cortex

PubMed Central

O’Reilly, Jill X.; Schüffelgen, Urs; Cuell, Steven F.; Behrens, Timothy E. J.; Mars, Rogier B.; Rushworth, Matthew F. S.

2013-01-01

Brains use predictive models to facilitate the processing of expected stimuli or planned actions. Under a predictive model, surprising (low probability) stimuli or actions necessitate the immediate reallocation of processing resources, but they can also signal the need to update the underlying predictive model to reflect changes in the environment. Surprise and updating are often correlated in experimental paradigms but are, in fact, distinct constructs that can be formally defined as the Shannon information (IS) and Kullback–Leibler divergence (DKL) associated with an observation. In a saccadic planning task, we observed that distinct behaviors and brain regions are associated with surprise/IS and updating/DKL. Although surprise/IS was associated with behavioral reprogramming as indexed by slower reaction times, as well as with activity in the posterior parietal cortex [human lateral intraparietal area (LIP)], the anterior cingulate cortex (ACC) was specifically activated during updating of the predictive model (DKL). A second saccade-sensitive region in the inferior posterior parietal cortex (human 7a), which has connections to both LIP and ACC, was activated by surprise and modulated by updating. Pupillometry revealed a further dissociation between surprise and updating with an early positive effect of surprise and late negative effect of updating on pupil area. These results give a computational account of the roles of the ACC and two parietal saccade regions, LIP and 7a, by which their involvement in diverse tasks can be understood mechanistically. The dissociation of functional roles between regions within the reorienting/reprogramming network may also inform models of neurological phenomena, such as extinction and Balint syndrome, and neglect. PMID:23986499

Magnetic Causes of Solar Coronal Mass Ejections: Dominance of the Free Magnetic Energy Over the Magnetic Twist Alone

NASA Technical Reports Server (NTRS)

Falconer, D. A.; Moore, R. L.; Gary, g. A.

2006-01-01

We examine the magnetic causes of coronal mass ejections (CMEs) by examining, along with the correlations of active-region magnetic measures with each other, the correlations of these measures with active-region CME productivity observed in time windows of a few days, either centered on or extending forward from the day of the magnetic measurement. The measures are from 36 vector magnetograms of bipolar active regions observed within -30" of disk center by the Marshal Space Flight Center (MSFC) vector magnetograph. From each magnetogram, we extract six whole-active-region measures twice, once from the original plane-of-the-sky magnetogram and again a h r deprojection of the magnetogram to disk center. Three of the measures are alternative measures of the total nonpotentiality of the active region, two are alternative measures of the overall twist in the active-region's magnetic field, and one is a measure of the magnetic size of the active region (the active region's magnetic flux content). From the deprojected magnetograms, we find evidence that (1) magnetic twist and magnetic size are separate but comparably strong causes of active-region CME Productivity, and (2) the total free magnetic energy in an active region's magnetic field is a stronger determinant of the active region's CME productivity than is the field's overall twist (or helicity) alone. From comparison of results from the non-deprojected magnetograms with corresponding results from the deprojected magnetograms, we find evidence that (for prediction of active-region CME productivity and for further studies of active-region magnetic size as a cause of CMEs), for active regions within approx.30deg of disk center, active-region total nonpotentiality and flux content can be adequately measured from line-of-sight magnetograms, such as from SOH0 MDI.

Neural representations of the concepts in simple sentences: Concept activation prediction and context effects.

PubMed

Just, Marcel Adam; Wang, Jing; Cherkassky, Vladimir L

2017-08-15

Although it has been possible to identify individual concepts from a concept's brain activation pattern, there have been significant obstacles to identifying a proposition from its fMRI signature. Here we demonstrate the ability to decode individual prototype sentences from readers' brain activation patterns, by using theory-driven regions of interest and semantic properties. It is possible to predict the fMRI brain activation patterns evoked by propositions and words which are entirely new to the model with reliably above-chance rank accuracy. The two core components implemented in the model that reflect the theory were the choice of intermediate semantic features and the brain regions associated with the neurosemantic dimensions. This approach also predicts the neural representation of object nouns across participants, studies, and sentence contexts. Moreover, we find that the neural representation of an agent-verb-object proto-sentence is more accurately characterized by the neural signatures of its components as they occur in a similar context than by the neural signatures of these components as they occur in isolation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mega-region freight movements : a case study of the Texas triangle.

DOT National Transportation Integrated Search

2011-09-01

U.S. population growth is predicted to substantially increase over the next 40 years, particularly in areas : with large regional economies forecasted to contain over two-thirds of the national economic activity. In : Texas, population growth from 20...

Mapping and mutagenesis of the amino-terminal transcriptional repression domain of the Drosophila Krüppel protein.

PubMed Central

Licht, J D; Hanna-Rose, W; Reddy, J C; English, M A; Ro, M; Grossel, M; Shaknovich, R; Hansen, U

1994-01-01

We previously demonstrated that the Drosophila Krüppel protein is a transcriptional repressor with separable DNA-binding and transcriptional repression activities. In this study, the minimal amino (N)-terminal repression region of the Krüppel protein was defined by transferring regions of the Krüppel protein to a heterologous DNA-binding protein, the lacI protein. Fusion of a predicted alpha-helical region from amino acids 62 to 92 in the N terminus of the Krüppel protein was sufficient to transfer repression activity. This putative alpha-helix has several hydrophobic surfaces, as well as a glutamine-rich surface. Mutants containing multiple amino acid substitutions of the glutamine residues demonstrated that this putative alpha-helical region is essential for repression activity of a Krüppel protein containing the entire N-terminal and DNA-binding regions. Furthermore, one point mutant with only a single glutamine on this surface altered to lysine abolished the ability of the Krüppel protein to repress, indicating the importance of the amino acid at residue 86 for repression. The N terminus also contained an adjacent activation region localized between amino acids 86 and 117. Finally, in accordance with predictions from primary amino acid sequence similarity, a repression region from the Drosophila even-skipped protein, which was six times more potent than that of the Krüppel protein in the mammalian cells, was characterized. This segment included a hydrophobic stretch of 11 consecutive alanine residues and a proline-rich region. Images PMID:8196644

Sustained anterior cingulate cortex activation during reward processing predicts response to psychotherapy in major depressive disorder.

PubMed

Carl, Hannah; Walsh, Erin; Eisenlohr-Moul, Tory; Minkel, Jared; Crowther, Andrew; Moore, Tyler; Gibbs, Devin; Petty, Chris; Bizzell, Josh; Dichter, Gabriel S; Smoski, Moria J

2016-10-01

The purpose of the present investigation was to evaluate whether pre-treatment neural activation in response to rewards is a predictor of clinical response to Behavioral Activation Therapy for Depression (BATD), an empirically validated psychotherapy that decreases depressive symptoms by increasing engagement with rewarding stimuli and reducing avoidance behaviors. Participants were 33 outpatients with major depressive disorder (MDD) and 20 matched controls. We examined group differences in activation, and the capacity to sustain activation, across task runs using functional magnetic resonance imaging (fMRI) and the monetary incentive delay (MID) task. Hierarchical linear modeling was used to investigate whether pre-treatment neural responses predicted change in depressive symptoms over the course of BATD treatment. MDD and Control groups differed in sustained activation during reward outcomes in the right nucleus accumbens, such that the MDD group experienced a significant decrease in activation in this region from the first to second task run relative to controls. Pretreatment anhedonia severity and pretreatment task-related reaction times were predictive of response to treatment. Furthermore, sustained activation in the anterior cingulate cortex during reward outcomes predicted response to psychotherapy; patients with greater sustained activation in this region were more responsive to BATD treatment. The current study only included a single treatment condition, thus it unknown whether these predictors of treatment response are specific to BATD or psychotherapy in general. Findings add to the growing body of literature suggesting that the capacity to sustain neural responses to rewards may be a critical endophenotype of MDD. Copyright © 2016 Elsevier B.V. All rights reserved.

Top-down attentional control in spatially coincident stimuli enhances activity in both task-relevant and task-irrelevant regions of cortex

PubMed Central

Erickson, Kirk I.; Prakash, Ruchika Shaurya; Kim, Jennifer S.; Sutton, Bradley P.; Colcombe, Stanley J.; Kramer, Arthur F.

2010-01-01

Models of selective attention predict that focused attention to spatially contiguous stimuli may result in enhanced activity in areas of cortex specialized for processing task-relevant and task-irrelevant information. We examined this hypothesis by localizing color-sensitive areas (CSA) and word and letter sensitive areas of cortex and then examining modulation of these regions during performance of a modified version of the Stroop task in which target and distractors are spatially coincident. We report that only the incongruent condition with the highest cognitive demand showed increased activity in CSA relative to other conditions, indicating an attentional enhancement in target processing areas. We also found an enhancement of activity in one region sensitive to word/letter processing during the most cognitively demanding incongruent condition indicating greater processing of the distractor dimension. Correlations with performance revealed that top-down modulation during the task was critical for effective filtering of irrelevant information in conflict conditions. These results support predictions made by models of selective attention and suggest an important mechanism of top-down attentional control in spatially contiguous stimuli. PMID:18804123

The rostromedial tegmental nucleus (RMTg), a major GABAergic afferent to midbrain dopamine neurons, selectively encodes aversive stimuli and promotes behavioral inhibition

PubMed Central

Jhou, Thomas C.; Fields, Howard L.; Baxter, Mark G.; Saper, Clifford B.; Holland, Peter C.

2009-01-01

Summary Separate studies have implicated the lateral habenula (LHb) or amygdala-related regions in processing aversive stimuli, but their relationships to each other and to appetitive motivational systems are poorly understood. We show that neurons in the recently identified GABAergic rostromedial tegmental nucleus (RMTg), which receive a major LHb input, project heavily to midbrain dopamine neurons, and show phasic activations and/or Fos induction after aversive stimuli (footshocks, shock-predictive cues, food deprivation, or reward omission) and inhibitions after rewards or reward-predictive stimuli. RMTg lesions markedly reduce passive fear behaviors (freezing, open-arm avoidance) dependent on the extended amygdala, periaqueductal gray, or septum, all regions that project directly to the RMTg. In contrast, RMTg lesions spare or enhance active fear responses (treading, escape) in these same paradigms. These findings suggest that aversive inputs from widespread brain regions and stimulus modalities converge onto the RMTg, which opposes reward and motor-activating functions of midbrain dopamine neurons PMID:19285474

Classifying adolescent attention-deficit/hyperactivity disorder (ADHD) based on functional and structural imaging.

PubMed

Iannaccone, Reto; Hauser, Tobias U; Ball, Juliane; Brandeis, Daniel; Walitza, Susanne; Brem, Silvia

2015-10-01

Attention-deficit/hyperactivity disorder (ADHD) is a common disabling psychiatric disorder associated with consistent deficits in error processing, inhibition and regionally decreased grey matter volumes. The diagnosis is based on clinical presentation, interviews and questionnaires, which are to some degree subjective and would benefit from verification through biomarkers. Here, pattern recognition of multiple discriminative functional and structural brain patterns was applied to classify adolescents with ADHD and controls. Functional activation features in a Flanker/NoGo task probing error processing and inhibition along with structural magnetic resonance imaging data served to predict group membership using support vector machines (SVMs). The SVM pattern recognition algorithm correctly classified 77.78% of the subjects with a sensitivity and specificity of 77.78% based on error processing. Predictive regions for controls were mainly detected in core areas for error processing and attention such as the medial and dorsolateral frontal areas reflecting deficient processing in ADHD (Hart et al., in Hum Brain Mapp 35:3083-3094, 2014), and overlapped with decreased activations in patients in conventional group comparisons. Regions more predictive for ADHD patients were identified in the posterior cingulate, temporal and occipital cortex. Interestingly despite pronounced univariate group differences in inhibition-related activation and grey matter volumes the corresponding classifiers failed or only yielded a poor discrimination. The present study corroborates the potential of task-related brain activation for classification shown in previous studies. It remains to be clarified whether error processing, which performed best here, also contributes to the discrimination of useful dimensions and subtypes, different psychiatric disorders, and prediction of treatment success across studies and sites.

Three-dimensional quantitative structure-activity relationship studies on novel series of benzotriazine based compounds acting as Src inhibitors using CoMFA and CoMSIA.

PubMed

Gueto, Carlos; Ruiz, José L; Torres, Juan E; Méndez, Jefferson; Vivas-Reyes, Ricardo

2008-03-01

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of benzotriazine derivatives, as Src inhibitors. Ligand molecular superimposition on the template structure was performed by database alignment method. The statistically significant model was established of 72 molecules, which were validated by a test set of six compounds. The CoMFA model yielded a q(2)=0.526, non cross-validated R(2) of 0.781, F value of 88.132, bootstrapped R(2) of 0.831, standard error of prediction=0.587, and standard error of estimate=0.351 while the CoMSIA model yielded the best predictive model with a q(2)=0.647, non cross-validated R(2) of 0.895, F value of 115.906, bootstrapped R(2) of 0.953, standard error of prediction=0.519, and standard error of estimate=0.178. The contour maps obtained from 3D-QSAR studies were appraised for activity trends for the molecules analyzed. Results indicate that small steric volumes in the hydrophobic region, electron-withdrawing groups next to the aryl linker region, and atoms close to the solvent accessible region increase the Src inhibitory activity of the compounds. In fact, adding substituents at positions 5, 6, and 8 of the benzotriazine nucleus were generated new compounds having a higher predicted activity. The data generated from the present study will further help to design novel, potent, and selective Src inhibitors as anticancer therapeutic agents.

High resolution solar observations in the context of space weather prediction

NASA Astrophysics Data System (ADS)

Yang, Guo

Space weather has a great impact on the Earth and human life. It is important to study and monitor active regions on the solar surface and ultimately to predict space weather based on the Sun's activity. In this study, a system that uses the full power of speckle masking imaging by parallel processing to obtain high-spatial resolution images of the solar surface in near real-time has been developed and built. The application of this system greatly improves the ability to monitor the evolution of solar active regions and to predict the adverse effects of space weather. The data obtained by this system have also been used to study fine structures on the solar surface and their effects on the upper solar atmosphere. A solar active region has been studied using high resolution data obtained by speckle masking imaging. Evolution of a pore in an active region presented. Formation of a rudimentary penumbra is studied. The effects of the change of the magnetic fields on the upper level atmosphere is discussed. Coronal Mass Ejections (CMEs) have a great impact on space weather. To study the relationship between CMEs and filament disappearance, a list of 431 filament and prominence disappearance events has been compiled. Comparison of this list with CME data obtained by satellite has shown that most filament disappearances seem to have no corresponding CME events. Even for the limb events, only thirty percent of filament disappearances are associated with CMEs. A CME event that was observed on March 20, 2000 has been studied in detail. This event did not show the three-parts structure of typical CMEs. The kinematical and morphological properties of this event were examined.

Solar prediction analysis

NASA Technical Reports Server (NTRS)

Smith, Jesse B.

1992-01-01

Solar Activity prediction is essential to definition of orbital design and operational environments for space flight. This task provides the necessary research to better understand solar predictions being generated by the solar community and to develop improved solar prediction models. The contractor shall provide the necessary manpower and facilities to perform the following tasks: (1) review, evaluate, and assess the time evolution of the solar cycle to provide probable limits of solar cycle behavior near maximum end during the decline of solar cycle 22, and the forecasts being provided by the solar community and the techniques being used to generate these forecasts; and (2) develop and refine prediction techniques for short-term solar behavior flare prediction within solar active regions, with special emphasis on the correlation of magnetic shear with flare occurrence.

Separate neural mechanisms underlie choices and strategic preferences in risky decision making.

PubMed

Venkatraman, Vinod; Payne, John W; Bettman, James R; Luce, Mary Frances; Huettel, Scott A

2009-05-28

Adaptive decision making in real-world contexts often relies on strategic simplifications of decision problems. Yet, the neural mechanisms that shape these strategies and their implementation remain largely unknown. Using an economic decision-making task, we dissociate brain regions that predict specific choices from those predicting an individual's preferred strategy. Choices that maximized gains or minimized losses were predicted by functional magnetic resonance imaging activation in ventromedial prefrontal cortex or anterior insula, respectively. However, choices that followed a simplifying strategy (i.e., attending to overall probability of winning) were associated with activation in parietal and lateral prefrontal cortices. Dorsomedial prefrontal cortex, through differential functional connectivity with parietal and insular cortex, predicted individual variability in strategic preferences. Finally, we demonstrate that robust decision strategies follow from neural sensitivity to rewards. We conclude that decision making reflects more than compensatory interaction of choice-related regions; in addition, specific brain systems potentiate choices depending on strategies, traits, and context.

Separate neural mechanisms underlie choices and strategic preferences in risky decision making

PubMed Central

Venkatraman, Vinod; Payne, John W.; Bettman, James R.; Luce, Mary Frances; Huettel, Scott A.

2011-01-01

Adaptive decision making in real-world contexts often relies on strategic simplifications of decision problems. Yet, the neural mechanisms that shape these strategies and their implementation remain largely unknown. Using a novel economic decision-making task, we dissociate brain regions that predict specific choices from those predicting an individual’s preferred strategy. Choices that maximized gains or minimized losses were predicted by fMRI activation in ventromedial prefrontal cortex or anterior insula, respectively. However, choices that followed a simplifying strategy (i.e., attending to overall probability of winning) were associated with activation in parietal and lateral prefrontal cortices. Dorsomedial prefrontal cortex, through differential functional connectivity with parietal and insular cortex, predicted individual variability in strategic preferences. Finally, we demonstrate that robust decision strategies follow from neural sensitivity to rewards. We conclude that decision making reflects more than compensatory interaction of choice-related regions; in addition, specific brain systems potentiate choices depending upon strategies, traits, and context. PMID:19477159

Statistical study of free magnetic energy and flare productivity of solar active regions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Su, J. T.; Jing, J.; Wang, S.

Photospheric vector magnetograms from the Helioseismic and Magnetic Imager on board the Solar Dynamic Observatory are utilized as the boundary conditions to extrapolate both nonlinear force-free and potential magnetic fields in solar corona. Based on the extrapolations, we are able to determine the free magnetic energy (FME) stored in active regions (ARs). Over 3000 vector magnetograms in 61 ARs were analyzed. We compare FME with the ARs' flare index (FI) and find that there is a weak correlation (<60%) between FME and FI. FME shows slightly improved flare predictability relative to the total unsigned magnetic flux of ARs in themore » following two aspects: (1) the flare productivity predicted by FME is higher than that predicted by magnetic flux and (2) the correlation between FI and FME is higher than that between FI and magnetic flux. However, this improvement is not significant enough to make a substantial difference in time-accumulated FI, rather than individual flare, predictions.« less

The Role of Small-Scale Processes in Solar Active Region Decay

NASA Astrophysics Data System (ADS)

Meyer, Karen; Mackay, Duncan

2017-08-01

Active regions are locations of intense magnetic activity on the Sun, whose evolution can result in highly energetic eruptive phenomena such as solar flares and coronal mass ejections (CMEs). Therefore, fast and accurate simulation of their evolution and decay is essential in the prediction of Space Weather events. In this talk we present initial results from our new model for the photospheric evolution of active region magnetic fields. Observations show that small-scale processes appear to play a role in the dispersal and decay of solar active regions, for example through cancellation at the boundary of sunspot outflows and erosion of flux by surrounding convective cells. Our active region model is coupled to our existing model for the evolution of small-scale photospheric magnetic features. Focusing first on the active region decay phase, we consider the evolution of its magnetic field due to both large-scale (e.g. differential rotation) and small-scale processes, such as its interaction with surrounding small-scale magnetic features and convective flows.This project is funded by The Carnegie Trust for the Universities of Scotland, through their Research Incentives Grant scheme.

Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

NASA Astrophysics Data System (ADS)

Zhang, Ying; Moges, Semu; Block, Paul

2018-01-01

Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS) values of up to 0.5 and 33 %, respectively. The general skill (after bias correction) of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

Are Regional Habitat Models Useful at a Local-Scale? A Case Study of Threatened and Common Insectivorous Bats in South-Eastern Australia

PubMed Central

McConville, Anna; Law, Bradley S.; Mahony, Michael J.

2013-01-01

Habitat modelling and predictive mapping are important tools for conservation planning, particularly for lesser known species such as many insectivorous bats. However, the scale at which modelling is undertaken can affect the predictive accuracy and restrict the use of the model at different scales. We assessed the validity of existing regional-scale habitat models at a local-scale and contrasted the habitat use of two morphologically similar species with differing conservation status (Mormopterus norfolkensis and Mormopterus species 2). We used negative binomial generalised linear models created from indices of activity and environmental variables collected from systematic acoustic surveys. We found that habitat type (based on vegetation community) best explained activity of both species, which were more active in floodplain areas, with most foraging activity recorded in the freshwater wetland habitat type. The threatened M. norfolkensis avoided urban areas, which contrasts with M. species 2 which occurred frequently in urban bushland. We found that the broad habitat types predicted from local-scale models were generally consistent with those from regional-scale models. However, threshold-dependent accuracy measures indicated a poor fit and we advise caution be applied when using the regional models at a fine scale, particularly when the consequences of false negatives or positives are severe. Additionally, our study illustrates that habitat type classifications can be important predictors and we suggest they are more practical for conservation than complex combinations of raw variables, as they are easily communicated to land managers. PMID:23977296

Effects of aging on functional connectivity of the amygdala for subsequent memory of negative pictures: a network analysis of functional magnetic resonance imaging data.

PubMed

St Jacques, Peggy L; Dolcos, Florin; Cabeza, Roberto

2009-01-01

Aging is associated with preserved enhancement of emotional memory, as well as with age-related reductions in memory for negative stimuli, but the neural networks underlying such alterations are not clear. We used a subsequent-memory paradigm to identify brain activity predicting enhanced emotional memory in young and older adults. Activity in the amygdala predicted enhanced emotional memory, with subsequent-memory activity greater for negative stimuli than for neutral stimuli, across age groups, a finding consistent with an overall enhancement of emotional memory. However, older adults recruited greater activity in anterior regions and less activity in posterior regions in general for negative stimuli that were subsequently remembered. Functional connectivity of the amygdala with the rest of the brain was consistent with age-related reductions in memory for negative stimuli: Older adults showed decreased functional connectivity between the amygdala and the hippocampus, but increased functional connectivity between the amygdala and dorsolateral prefrontal cortices. These findings suggest that age-related differences in the enhancement of emotional memory might reflect decreased connectivity between the amygdala and typical subsequent-memory regions, as well as the engagement of regulatory processes that inhibit emotional responses.

Imaging systems level consolidation of novel associate memories: A longitudinal neuroimaging study

PubMed Central

Smith, Jason F; Alexander, Gene E; Chen, Kewei; Husain, Fatima T; Kim, Jieun; Pajor, Nathan; Horwitz, Barry

2010-01-01

Previously, a standard theory of systems level memory consolidation was developed to describe how memory recall becomes independent of the medial temporal memory system. More recently, an extended consolidation theory was proposed that predicts seven changes in regional neural activity and inter-regional functional connectivity. Using longitudinal event related functional magnetic resonance imaging of an associate memory task, we simultaneously tested all predictions and additionally tested for consolidation related changes in recall of associate memories at a sub-trial temporal resolution, analyzing cue, delay and target periods of each trial separately. Results consistent with the theoretical predictions were observed though two inconsistent results were also obtained. In particular, while recall-related delay period activity decreased with consolidation as predicted, visual cue activity increased for consolidated memories. Though the extended theory of memory consolidation is largely supported by our study, these results suggest the extended theory needs further refinement and the medial temporal memory system has multiple, temporally distinct roles in associate memory recall. Neuroimaging analysis at a sub-trial temporal resolution, as used here, may further clarify the role of the hippocampal complex in memory consolidation. PMID:19948227

Visual Predictions in the Orbitofrontal Cortex Rely on Associative Content

PubMed Central

Chaumon, Maximilien; Kveraga, Kestutis; Barrett, Lisa Feldman; Bar, Moshe

2014-01-01

Predicting upcoming events from incomplete information is an essential brain function. The orbitofrontal cortex (OFC) plays a critical role in this process by facilitating recognition of sensory inputs via predictive feedback to sensory cortices. In the visual domain, the OFC is engaged by low spatial frequency (LSF) and magnocellular-biased inputs, but beyond this, we know little about the information content required to activate it. Is the OFC automatically engaged to analyze any LSF information for meaning? Or is it engaged only when LSF information matches preexisting memory associations? We tested these hypotheses and show that only LSF information that could be linked to memory associations engages the OFC. Specifically, LSF stimuli activated the OFC in 2 distinct medial and lateral regions only if they resembled known visual objects. More identifiable objects increased activity in the medial OFC, known for its function in affective responses. Furthermore, these objects also increased the connectivity of the lateral OFC with the ventral visual cortex, a crucial region for object identification. At the interface between sensory, memory, and affective processing, the OFC thus appears to be attuned to the associative content of visual information and to play a central role in visuo-affective prediction. PMID:23771980

Successful emotion regulation is predicted by amygdala activity and aspects of personality: A latent variable approach.

PubMed

Morawetz, Carmen; Alexandrowicz, Rainer W; Heekeren, Hauke R

2017-04-01

The experience of emotions and their cognitive control are based upon neural responses in prefrontal and subcortical regions and could be affected by personality and temperamental traits. Previous studies established an association between activity in reappraisal-related brain regions (e.g., inferior frontal gyrus and amygdala) and emotion regulation success. Given these relationships, we aimed to further elucidate how individual differences in emotion regulation skills relate to brain activity within the emotion regulation network on the one hand, and personality/temperamental traits on the other. We directly examined the relationship between personality and temperamental traits, emotion regulation success and its underlying neuronal network in a large sample (N = 82) using an explicit emotion regulation task and functional MRI (fMRI). We applied a multimethodological analysis approach, combing standard activation-based analyses with structural equation modeling. First, we found that successful downregulation is predicted by activity in key regions related to emotion processing. Second, the individual ability to successfully upregulate emotions is strongly associated with the ability to identify feelings, conscientiousness, and neuroticism. Third, the successful downregulation of emotion is modulated by openness to experience and habitual use of reappraisal. Fourth, the ability to regulate emotions is best predicted by a combination of brain activity and personality as well temperamental traits. Using a multimethodological analysis approach, we provide a first step toward a causal model of individual differences in emotion regulation ability by linking biological systems underlying emotion regulation with descriptive constructs. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Neuroscience of inhibition for addiction medicine: From prediction of initiation to prediction of relapse

PubMed Central

Moeller, Scott J.; Bederson, Lucia; Alia-Klein, Nelly; Goldstein, Rita Z.

2017-01-01

A core deficit in drug addiction is the inability to inhibit maladaptive drug-seeking behavior. Consistent with this deficit, drug-addicted individuals show reliable cross-sectional differences from healthy non-addicted controls during tasks of response inhibition accompanied by brain activation abnormalities as revealed by functional neuroimaging. However, it is less clear whether inhibition-related deficits predate the transition to problematic use, and, in turn, whether these deficits predict the transition out of problematic substance use. Here, we review longitudinal studies of response inhibition in children/adolescents with little substance experience and longitudinal studies of already-addicted individuals attempting to sustain abstinence. Results show that response inhibition, and its underlying neural correlates, predict both substance use outcomes (onset and abstinence). Neurally, key roles were observed for multiple regions of the frontal cortex (e.g., inferior frontal gyrus, dorsal anterior cingulate cortex, and dorsolateral prefrontal cortex). In general, less activation of these regions during response inhibition predicted not only the onset of substance use, but interestingly, also better abstinence-related outcomes among individuals already addicted. The role of subcortical areas, although potentially important, is less clear because of inconsistent results and because these regions are less classically reported in studies of healthy response inhibition. Overall, this review indicates that response inhibition is not simply a manifestation of current drug addiction, but rather a core neurocognitive dimension that predicts key substance use outcomes. Early intervention in inhibitory deficits could have high clinical and public health relevance. PMID:26806776

Regionalization and dependence of coda Q on frequency and lapse time in the seismically active Peloritani region (northeastern Sicily, Italy)

NASA Astrophysics Data System (ADS)

Giampiccolo, Elisabetta; Tuvè, Tiziana

2018-05-01

The Peloritani region is one of the most seismically active regions in Italy and, consequently, the quantification of attenuation of the medium plays an important role for seismic risk evaluation. Moreover, it is necessary for the prediction of earth ground motion and future seismic source studies. An in depth analysis has been made here to understand the frequency and lapse time dependence of attenuation characteristics of the region by using the coda of local earthquakes. A regionalization is likewise performed in order to investigate the spatial variation of coda Q across the whole region. Finally, our results are jointly interpreted with those obtained from recently published 3D velocity tomographies for further insights.

Evaluation of Ground-Motion Modeling Techniques for Use in Global ShakeMap - A Critique of Instrumental Ground-Motion Prediction Equations, Peak Ground Motion to Macroseismic Intensity Conversions, and Macroseismic Intensity Predictions in Different Tectonic Settings

USGS Publications Warehouse

Allen, Trevor I.; Wald, David J.

2009-01-01

Regional differences in ground-motion attenuation have long been thought to add uncertainty in the prediction of ground motion. However, a growing body of evidence suggests that regional differences in ground-motion attenuation may not be as significant as previously thought and that the key differences between regions may be a consequence of limitations in ground-motion datasets over incomplete magnitude and distance ranges. Undoubtedly, regional differences in attenuation can exist owing to differences in crustal structure and tectonic setting, and these can contribute to differences in ground-motion attenuation at larger source-receiver distances. Herein, we examine the use of a variety of techniques for the prediction of several ground-motion metrics (peak ground acceleration and velocity, response spectral ordinates, and macroseismic intensity) and compare them against a global dataset of instrumental ground-motion recordings and intensity assignments. The primary goal of this study is to determine whether existing ground-motion prediction techniques are applicable for use in the U.S. Geological Survey's Global ShakeMap and Prompt Assessment of Global Earthquakes for Response (PAGER). We seek the most appropriate ground-motion predictive technique, or techniques, for each of the tectonic regimes considered: shallow active crust, subduction zone, and stable continental region.

Regional Homogeneity Predicts Creative Insight: A Resting-State fMRI Study.

PubMed

Lin, Jiabao; Cui, Xuan; Dai, Xiaoying; Mo, Lei

2018-01-01

Creative insight plays an important role in our daily life. Previous studies have investigated the neural correlates of creative insight by functional magnetic resonance imaging (fMRI), however, the intrinsic resting-state brain activity associated with creative insight is still unclear. In the present study, we used regional homogeneity (ReHo) as an index in resting-state fMRI (rs-fMRI) to identify brain regions involved in individual differences in creative insight, which was compued by the response time (RT) of creative Chinese character chunk decomposition. The findings indicated that ReHo in the anterior cingulate cortex (ACC)/caudate nucleus (CN) and angular gyrus (AG)/superior temporal gyrus (STG)/inferior parietal lobe (IPL) negatively predicted creative insight. Furthermore, these findings suggested that spontaneous brain activity in multiple regions related to breaking and establishing mental sets, goal-directed solutions exploring, shifting attention, forming new associations and emotion experience contributes to creative insight. In conclusion, the present study provides new evidence to further understand the cognitive processing and neural correlates of creative insight.

Echoes of the spoken past: how auditory cortex hears context during speech perception

PubMed Central

Skipper, Jeremy I.

2014-01-01

What do we hear when someone speaks and what does auditory cortex (AC) do with that sound? Given how meaningful speech is, it might be hypothesized that AC is most active when other people talk so that their productions get decoded. Here, neuroimaging meta-analyses show the opposite: AC is least active and sometimes deactivated when participants listened to meaningful speech compared to less meaningful sounds. Results are explained by an active hypothesis-and-test mechanism where speech production (SP) regions are neurally re-used to predict auditory objects associated with available context. By this model, more AC activity for less meaningful sounds occurs because predictions are less successful from context, requiring further hypotheses be tested. This also explains the large overlap of AC co-activity for less meaningful sounds with meta-analyses of SP. An experiment showed a similar pattern of results for non-verbal context. Specifically, words produced less activity in AC and SP regions when preceded by co-speech gestures that visually described those words compared to those words without gestures. Results collectively suggest that what we ‘hear’ during real-world speech perception may come more from the brain than our ears and that the function of AC is to confirm or deny internal predictions about the identity of sounds. PMID:25092665

Predictive Suppression of Cortical Excitability and Its Deficit in Schizophrenia

PubMed Central

Schroeder, Charles E.; Leitman, David I.

2013-01-01

Recent neuroscience advances suggest that when interacting with our environment, along with previous experience, we use contextual cues and regularities to form predictions that guide our perceptions and actions. The goal of such active “predictive sensing” is to selectively enhance the processing and representation of behaviorally relevant information in an efficient manner. Since a hallmark of schizophrenia is impaired information selection, we tested whether this deficiency stems from dysfunctional predictive sensing by measuring the degree to which neuronal activity predicts relevant events. In healthy subjects, we established that these mechanisms are engaged in an effort-dependent manner and that, based on a correspondence between human scalp and intracranial nonhuman primate recordings, their main role is a predictive suppression of excitability in task-irrelevant regions. In contrast, schizophrenia patients displayed a reduced alignment of neuronal activity to attended stimuli, which correlated with their behavioral performance deficits and clinical symptoms. These results support the relevance of predictive sensing for normal and aberrant brain function, and highlight the importance of neuronal mechanisms that mold internal ongoing neuronal activity to model key features of the external environment. PMID:23843536

The time course of activity in dorsolateral prefrontal cortex and anterior cingulate cortex during top-down attentional control.

PubMed

Silton, Rebecca Levin; Heller, Wendy; Towers, David N; Engels, Anna S; Spielberg, Jeffrey M; Edgar, J Christopher; Sass, Sarah M; Stewart, Jennifer L; Sutton, Bradley P; Banich, Marie T; Miller, Gregory A

2010-04-15

A network of brain regions has been implicated in top-down attentional control, including left dorsolateral prefrontal cortex (LDLPFC) and dorsal anterior cingulate cortex (dACC). The present experiment evaluated predictions of the cascade-of-control model (Banich, 2009), which predicts that during attentionally-demanding tasks, LDLPFC imposes a top-down attentional set which precedes late-stage selection performed by dACC. Furthermore, the cascade-of-control model argues that dACC must increase its activity to compensate when top-down control by LDLPFC is poor. The present study tested these hypotheses using fMRI and dense-array ERP data collected from the same 80 participants in separate sessions. fMRI results guided ERP source modeling to characterize the time course of activity in LDLPFC and dACC. As predicted, dACC activity subsequent to LDLPFC activity distinguished congruent and incongruent conditions on the Stroop task. Furthermore, when LDLPFC activity was low, the level of dACC activity was related to performance outcome. These results demonstrate that dACC responds to attentional demand in a flexible manner that is dependent on the level of LDLPFC activity earlier in a trial. Overall, results were consistent with the temporal course of regional brain function proposed by the cascade-of-control model. Copyright 2009 Elsevier Inc. All rights reserved.

Spontaneous activity in default-mode network predicts ascription of self-relatedness to stimuli.

PubMed

Qin, Pengmin; Grimm, Simone; Duncan, Niall W; Fan, Yan; Huang, Zirui; Lane, Timothy; Weng, Xuchu; Bajbouj, Malek; Northoff, Georg

2016-04-01

Spontaneous activity levels prior to stimulus presentation can determine how that stimulus will be perceived. It has also been proposed that such spontaneous activity, particularly in the default-mode network (DMN), is involved in self-related processing. We therefore hypothesised that pre-stimulus activity levels in the DMN predict whether a stimulus is judged as self-related or not. Participants were presented in the MRI scanner with a white noise stimulus that they were instructed contained their name or another. They then had to respond with which name they thought they heard. Regions where there was an activity level difference between self and other response trials 2 s prior to the stimulus being presented were identified. Pre-stimulus activity levels were higher in the right temporoparietal junction, the right temporal pole and the left superior temporal gyrus in trials where the participant responded that they heard their own name than trials where they responded that they heard another. Pre-stimulus spontaneous activity levels in particular brain regions, largely overlapping with the DMN, predict the subsequent judgement of stimuli as self-related. This extends our current knowledge of self-related processing and its apparent relationship with intrinsic brain activity in what can be termed a rest-self overlap. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Predicting fecal indicator organism contamination in Oregon coastal streams.

PubMed

Pettus, Paul; Foster, Eugene; Pan, Yangdong

2015-12-01

In this study, we used publicly available GIS layers and statistical tree-based modeling (CART and Random Forest) to predict pathogen indicator counts at a regional scale using 88 spatially explicit landscape predictors and 6657 samples from non-estuarine streams in the Oregon Coast Range. A total of 532 frequently sampled sites were parsed down to 93 pathogen sampling sites to control for spatial and temporal biases. This model's 56.5% explanation of variance, was comparable to other regional models, while still including a large number of variables. Analysis showed the most important predictors on bacteria counts to be: forest and natural riparian zones, cattle related activities, and urban land uses. This research confirmed linkages to anthropogenic activities, with the research prediction mapping showing increased bacteria counts in agricultural and urban land use areas and lower counts with more natural riparian conditions. Copyright © 2015 Elsevier Ltd. All rights reserved.

BOLD responses in reward regions to hypothetical and imaginary monetary rewards

PubMed Central

Miyapuram, Krishna P.; Tobler, Philippe N.; Gregorios-Pippas, Lucy; Schultz, Wolfram

2015-01-01

Monetary rewards are uniquely human. Because money is easy to quantify and present visually, it is the reward of choice for most fMRI studies, even though it cannot be handed over to participants inside the scanner. A typical fMRI study requires hundreds of trials and thus small amounts of monetary rewards per trial (e.g. 5p) if all trials are to be treated equally. However, small payoffs can have detrimental effects on performance due to their limited buying power. Hypothetical monetary rewards can overcome the limitations of smaller monetary rewards but it is less well known whether predictors of hypothetical rewards activate reward regions. In two experiments, visual stimuli were associated with hypothetical monetary rewards. In Experiment 1, we used stimuli predicting either visually presented or imagined hypothetical monetary rewards, together with non-rewarding control pictures. Activations to reward predictive stimuli occurred in reward regions, namely the medial orbitofrontal cortex and midbrain. In Experiment 2, we parametrically varied the amount of visually presented hypothetical monetary reward keeping constant the amount of actually received reward. Graded activation in midbrain was observed to stimuli predicting increasing hypothetical rewards. The results demonstrate the efficacy of using hypothetical monetary rewards in fMRI studies. PMID:21985912

BOLD responses in reward regions to hypothetical and imaginary monetary rewards.

PubMed

Miyapuram, Krishna P; Tobler, Philippe N; Gregorios-Pippas, Lucy; Schultz, Wolfram

2012-01-16

Monetary rewards are uniquely human. Because money is easy to quantify and present visually, it is the reward of choice for most fMRI studies, even though it cannot be handed over to participants inside the scanner. A typical fMRI study requires hundreds of trials and thus small amounts of monetary rewards per trial (e.g. 5p) if all trials are to be treated equally. However, small payoffs can have detrimental effects on performance due to their limited buying power. Hypothetical monetary rewards can overcome the limitations of smaller monetary rewards but it is less well known whether predictors of hypothetical rewards activate reward regions. In two experiments, visual stimuli were associated with hypothetical monetary rewards. In Experiment 1, we used stimuli predicting either visually presented or imagined hypothetical monetary rewards, together with non-rewarding control pictures. Activations to reward predictive stimuli occurred in reward regions, namely the medial orbitofrontal cortex and midbrain. In Experiment 2, we parametrically varied the amount of visually presented hypothetical monetary reward keeping constant the amount of actually received reward. Graded activation in midbrain was observed to stimuli predicting increasing hypothetical rewards. The results demonstrate the efficacy of using hypothetical monetary rewards in fMRI studies. Copyright © 2011 Elsevier Inc. All rights reserved.

Expertise with artificial non-speech sounds recruits speech-sensitive cortical regions

PubMed Central

Leech, Robert; Holt, Lori L.; Devlin, Joseph T.; Dick, Frederic

2009-01-01

Regions of the human temporal lobe show greater activation for speech than for other sounds. These differences may reflect intrinsically specialized domain-specific adaptations for processing speech, or they may be driven by the significant expertise we have in listening to the speech signal. To test the expertise hypothesis, we used a video-game-based paradigm that tacitly trained listeners to categorize acoustically complex, artificial non-linguistic sounds. Before and after training, we used functional MRI to measure how expertise with these sounds modulated temporal lobe activation. Participants’ ability to explicitly categorize the non-speech sounds predicted the change in pre- to post-training activation in speech-sensitive regions of the left posterior superior temporal sulcus, suggesting that emergent auditory expertise may help drive this functional regionalization. Thus, seemingly domain-specific patterns of neural activation in higher cortical regions may be driven in part by experience-based restructuring of high-dimensional perceptual space. PMID:19386919

Remembering forward: Neural correlates of memory and prediction in human motor adaptation

PubMed Central

Scheidt, Robert A; Zimbelman, Janice L; Salowitz, Nicole M G; Suminski, Aaron J; Mosier, Kristine M; Houk, James; Simo, Lucia

2011-01-01

We used functional MR imaging (FMRI), a robotic manipulandum and systems identification techniques to examine neural correlates of predictive compensation for spring-like loads during goal-directed wrist movements in neurologically-intact humans. Although load changed unpredictably from one trial to the next, subjects nevertheless used sensorimotor memories from recent movements to predict and compensate upcoming loads. Prediction enabled subjects to adapt performance so that the task was accomplished with minimum effort. Population analyses of functional images revealed a distributed, bilateral network of cortical and subcortical activity supporting predictive load compensation during visual target capture. Cortical regions - including prefrontal, parietal and hippocampal cortices - exhibited trial-by-trial fluctuations in BOLD signal consistent with the storage and recall of sensorimotor memories or “states” important for spatial working memory. Bilateral activations in associative regions of the striatum demonstrated temporal correlation with the magnitude of kinematic performance error (a signal that could drive reward-optimizing reinforcement learning and the prospective scaling of previously learned motor programs). BOLD signal correlations with load prediction were observed in the cerebellar cortex and red nuclei (consistent with the idea that these structures generate adaptive fusimotor signals facilitating cancellation of expected proprioceptive feedback, as required for conditional feedback adjustments to ongoing motor commands and feedback error learning). Analysis of single subject images revealed that predictive activity was at least as likely to be observed in more than one of these neural systems as in just one. We conclude therefore that motor adaptation is mediated by predictive compensations supported by multiple, distributed, cortical and subcortical structures. PMID:21840405

Hyperdeactivation of the Default Mode Network in People With Schizophrenia When Focusing Attention in Space.

PubMed

Hahn, Britta; Harvey, Alexander N; Gold, James M; Fischer, Bernard A; Keller, William R; Ross, Thomas J; Stein, Elliot A

2016-09-01

When studying selective attention in people with schizophrenia (PSZ), a counterintuitive but replicated finding has been that PSZ display larger performance benefits than healthy control subjects (HCS) by cues that predicts the location of a target stimulus relative to non-predictive cues. Possible explanations are that PSZ hyperfocus attention in response to predictive cues, or that an inability to maintain a broad attentional window impairs performance when the cue is non-predictive. Over-recruitment of regions involved in top-down focusing of spatial attention in response to predictive cues would support the former possibility, and an inappropriate recruitment of these regions in response to non-predictive cues the latter. We probed regions of the dorsal attention network while PSZ (N = 20) and HCS (N = 20) performed a visuospatial attention task. A central cue either predicted at which of 4 peripheral locations a target signal would appear, or it gave no information about the target location. As observed previously, PSZ displayed a larger reaction time difference between predictive and non-predictive cue trials than HCS. Activity in frontoparietal and occipital regions was greater for predictive than non-predictive cues. This effect was almost identical between PSZ and HCS. There was no sign of over-recruitment when the cue was predictive, or of inappropriate recruitment when the cue was non-predictive. However, PSZ differed from HCS in their cue-dependent deactivation of the default mode network. Unexpectedly, PSZ displayed significantly greater deactivation than HCS in predictive cue trials, which may reflect a tendency to expend more processing resources when focusing attention in space. © The Author 2016. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Space-weather Parameters for 1,000 Active Regions Observed by SDO/HMI

NASA Astrophysics Data System (ADS)

Bobra, M.; Liu, Y.; Hoeksema, J. T.; Sun, X.

2013-12-01

We present statistical studies of several space-weather parameters, derived from observations of the photospheric vector magnetic field by the Helioseismic and Magnetic Imager (HMI) aboard the Solar Dynamics Observatory, for a thousand active regions. Each active region has been observed every twelve minutes during the entirety of its disk passage. Some of these parameters, such as energy density and shear angle, indicate the deviation of the photospheric magnetic field from that of a potential field. Other parameters include flux, helicity, field gradients, polarity inversion line properties, and measures of complexity. We show that some of these parameters are useful for event prediction.

Brain activity in valuation regions while thinking about the future predicts individual discount rates.

PubMed

Cooper, Nicole; Kable, Joseph W; Kim, B Kyu; Zauberman, Gal

2013-08-07

People vary widely in how much they discount delayed rewards, yet little is known about the sources of these differences. Here we demonstrate that neural activity in ventromedial prefrontal cortex (VMPFC) and ventral striatum (VS) when human subjects are asked to merely think about the future--specifically, to judge the subjective length of future time intervals--predicts delay discounting. High discounters showed lower activity for longer time delays, while low discounters showed the opposite pattern. Our results demonstrate that the correlation between VMPFC and VS activity and discounting occurs even in the absence of choices about future rewards, and does not depend on a person explicitly evaluating future outcomes or judging their self-relevance. This suggests a link between discounting and basic processes involved in thinking about the future, such as temporal perception. Our results also suggest that reducing impatience requires not suppression of VMPFC and VS activity altogether, but rather modulation of how these regions respond to the present versus the future.

Brain Activity in Valuation Regions while Thinking about the Future Predicts Individual Discount Rates

PubMed Central

Cooper, Nicole; Kim, B. Kyu; Zauberman, Gal

2013-01-01

People vary widely in how much they discount delayed rewards, yet little is known about the sources of these differences. Here we demonstrate that neural activity in ventromedial prefrontal cortex (VMPFC) and ventral striatum (VS) when human subjects are asked to merely think about the future—specifically, to judge the subjective length of future time intervals—predicts delay discounting. High discounters showed lower activity for longer time delays, while low discounters showed the opposite pattern. Our results demonstrate that the correlation between VMPFC and VS activity and discounting occurs even in the absence of choices about future rewards, and does not depend on a person explicitly evaluating future outcomes or judging their self-relevance. This suggests a link between discounting and basic processes involved in thinking about the future, such as temporal perception. Our results also suggest that reducing impatience requires not suppression of VMPFC and VS activity altogether, but rather modulation of how these regions respond to the present versus the future. PMID:23926268

The 5' non-translated region of Varroa destructor virus 1 (genus Iflavirus): structure prediction and IRES activity in Lymantria dispar cells.

PubMed

Ongus, Juliette R; Roode, Els C; Pleij, Cornelis W A; Vlak, Just M; van Oers, Monique M

2006-11-01

Structure prediction of the 5' non-translated region (NTR) of four iflavirus RNAs revealed two types of potential internal ribosome entry site (IRES), which are discriminated by size and level of complexity, in this group of viruses. In contrast to the intergenic IRES of dicistroviruses, the potential 5' IRES structures of iflaviruses do not have pseudoknots. To test the activity of one of these, a bicistronic construct was made in which the 5' NTR of Varroa destructor virus 1 (VDV-1) containing a putative IRES was cloned in between two reporter genes, enhanced green fluorescent protein and firefly luciferase (Fluc). The presence of the 5' NTR of VDV-1 greatly enhanced the expression levels of the second reporter gene (Fluc) in Lymantria dispar Ld652Y cells. The 5' NTR was active in a host-specific manner, as it showed lower activity in Spodoptera frugiperda Sf21 cells and no activity in Drosophila melanogaster S2 cells.

Engineering a hyper-catalytic enzyme by photo-activated conformation modulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agarwal, Pratul K

2012-01-01

Enzyme engineering for improved catalysis has wide implications. We describe a novel chemical modification of Candida antarctica lipase B that allows modulation of the enzyme conformation to promote catalysis. Computational modeling was used to identify dynamical enzyme regions that impact the catalytic mechanism. Surface loop regions located distal to active site but showing dynamical coupling to the reaction were connected by a chemical bridge between Lys136 and Pro192, containing a derivative of azobenzene. The conformational modulation of the enzyme was achieved using two sources of light that alternated the azobenzene moiety in cis and trans conformations. Computational model predicted thatmore » mechanical energy from the conformational fluctuations facilitate the reaction in the active-site. The results were consistent with predictions as the activity of the engineered enzyme was found to be enhanced with photoactivation. Preliminary estimations indicate that the engineered enzyme achieved 8-52 fold better catalytic activity than the unmodulated enzyme.« less

Modeling preferential water flow and solute transport in unsaturated soil using the active region model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sheng, F.; Wang, K.; Zhang, R.

2009-03-15

Preferential flow and solute transport are common processes in the unsaturated soil, in which distributions of soil water content and solute concentrations are often characterized as fractal patterns. An active region model (ARM) was recently proposed to describe the preferential flow and transport patterns. In this study, ARM governing equations were derived to model the preferential soil water flow and solute transport processes. To evaluate the ARM equations, dye infiltration experiments were conducted, in which distributions of soil water content and Cl{sup -} concentration were measured. Predicted results using the ARM and the mobile-immobile region model (MIM) were compared withmore » the measured distributions of soil water content and Cl{sup -} concentration. Although both the ARM and the MIM are two-region models, they are fundamental different in terms of treatments of the flow region. The models were evaluated based on the modeling efficiency (ME). The MIM provided relatively poor prediction results of the preferential flow and transport with negative ME values or positive ME values less than 0.4. On the contrary, predicted distributions of soil water content and Cl- concentration using the ARM agreed reasonably well with the experimental data with ME values higher than 0.8. The results indicated that the ARM successfully captured the macroscopic behavior of preferential flow and solute transport in the unsaturated soil.« less

UK Environmental Prediction - integration and evaluation at the convective scale

NASA Astrophysics Data System (ADS)

Fallmann, Joachim; Lewis, Huw; Castillo, Juan Manuel; Pearson, David; Harris, Chris; Saulter, Andy; Bricheno, Lucy; Blyth, Eleanor

2016-04-01

Traditionally, the simulation of regional ocean, wave and atmosphere components of the Earth System have been considered separately, with some information on other components provided by means of boundary or forcing conditions. More recently, the potential value of a more integrated approach, as required for global climate and Earth System prediction, for regional short-term applications has begun to gain increasing research effort. In the UK, this activity is motivated by an understanding that accurate prediction and warning of the impacts of severe weather requires an integrated approach to forecasting. The substantial impacts on individuals, businesses and infrastructure of such events indicate a pressing need to understand better the value that might be delivered through more integrated environmental prediction. To address this need, the Met Office, NERC Centre for Ecology & Hydrology and NERC National Oceanography Centre have begun to develop the foundations of a coupled high resolution probabilistic forecast system for the UK at km-scale. This links together existing model components of the atmosphere, coastal ocean, land surface and hydrology. Our initial focus has been on a 2-year Prototype project to demonstrate the UK coupled prediction concept in research mode. This presentation will provide an update on UK environmental prediction activities. We will present the results from the initial implementation of an atmosphere-land-ocean coupled system, including a new eddy-permitting resolution ocean component, and discuss progress and initial results from further development to integrate wave interactions in this relatively high resolution system. We will discuss future directions and opportunities for collaboration in environmental prediction, and the challenges to realise the potential of integrated regional coupled forecasting for improving predictions and applications.

Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.

PubMed

Averill, Colin; Waring, Bonnie G; Hawkes, Christine V

2016-05-01

Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442-887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios. © 2016 John Wiley & Sons Ltd.

Individual differences in brainstem and basal ganglia structure predict postural control and balance loss in young and older adults.

PubMed

Boisgontier, Matthieu P; Cheval, Boris; Chalavi, Sima; van Ruitenbeek, Peter; Leunissen, Inge; Levin, Oron; Nieuwboer, Alice; Swinnen, Stephan P

2017-02-01

It remains unclear which specific brain regions are the most critical for human postural control and balance, and whether they mediate the effect of age. Here, associations between postural performance and corticosubcortical brain regions were examined in young and older adults using multiple structural imaging and linear mixed models. Results showed that of the regions involved in posture, the brainstem was the strongest predictor of postural control and balance: lower brainstem volume predicted larger center of pressure deviation and higher odds of balance loss. Analyses of white and gray matter in the brainstem showed that the pedunculopontine nucleus area appeared to be critical for postural control in both young and older adults. In addition, the brainstem mediated the effect of age on postural control, underscoring the brainstem's fundamental role in aging. Conversely, lower basal ganglia volume predicted better postural performance, suggesting an association between greater neural resources in the basal ganglia and greater movement vigor, resulting in exaggerated postural adjustments. Finally, results showed that practice, shorter height and heavier weight (i.e., higher body mass index), higher total physical activity, and larger ankle active (but not passive) range of motion were predictive of more stable posture, irrespective of age. Copyright © 2016 Elsevier Inc. All rights reserved.

Using spatio-temporal modeling to predict long-term exposure to black smoke at fine spatial and temporal scale

NASA Astrophysics Data System (ADS)

Dadvand, Payam; Rushton, Stephen; Diggle, Peter J.; Goffe, Louis; Rankin, Judith; Pless-Mulloli, Tanja

2011-01-01

Whilst exposure to air pollution is linked to a wide range of adverse health outcomes, assessing levels of this exposure has remained a challenge. This study reports a modeling approach for the estimation of weekly levels of ambient black smoke (BS) at residential postcodes across Northeast England (2055 km 2) over a 12 year period (1985-1996). A two-stage modeling strategy was developed using monitoring data on BS together with a range of covariates including data on traffic, population density, industrial activity, land cover (remote sensing), and meteorology. The first stage separates the temporal trend in BS for the region as a whole from within-region spatial variation and the second stage is a linear model which predicts BS levels at all locations in the region using spatially referenced covariate data as predictors and the regional predicted temporal trend as an offset. Traffic and land cover predictors were included in the final model, which predicted 70% of the spatio-temporal variation in BS across the study region over the study period. This modeling approach appears to provide a robust way of estimating exposure to BS at an inter-urban scale.

Investigation of mindfulness meditation practitioners with voxel-based morphometry

PubMed Central

Hölzel, Britta K.; Ott, Ulrich; Gard, Tim; Hempel, Hannes; Weygandt, Martin; Morgen, Katrin; Vaitl, Dieter

2008-01-01

Mindfulness meditators practice the non-judgmental observation of the ongoing stream of internal experiences as they arise. Using voxel-based morphometry, this study investigated MRI brain images of 20 mindfulness (Vipassana) meditators (mean practice 8.6 years; 2 h daily) and compared the regional gray matter concentration to that of non-meditators matched for sex, age, education and handedness. Meditators were predicted to show greater gray matter concentration in regions that are typically activated during meditation. Results confirmed greater gray matter concentration for meditators in the right anterior insula, which is involved in interoceptive awareness. This group difference presumably reflects the training of bodily awareness during mindfulness meditation. Furthermore, meditators had greater gray matter concentration in the left inferior temporal gyrus and right hippocampus. Both regions have previously been found to be involved in meditation. The mean value of gray matter concentration in the left inferior temporal gyrus was predictable by the amount of meditation training, corroborating the assumption of a causal impact of meditation training on gray matter concentration in this region. Results suggest that meditation practice is associated with structural differences in regions that are typically activated during meditation and in regions that are relevant for the task of meditation. PMID:19015095

k-Nearest neighbour local linear prediction of scalp EEG activity during intermittent photic stimulation.

PubMed

Erla, Silvia; Faes, Luca; Tranquillini, Enzo; Orrico, Daniele; Nollo, Giandomenico

2011-05-01

The characterization of the EEG response to photic stimulation (PS) is an important issue with significant clinical relevance. This study aims to quantify and map the complexity of the EEG during PS, where complexity is measured as the degree of unpredictability resulting from local linear prediction. EEG activity was recorded with eyes closed (EC) and eyes open (EO) during resting and PS at 5, 10, and 15 Hz in a group of 30 healthy subjects and in a case-report of a patient suffering from cerebral ischemia. The mean squared prediction error (MSPE) resulting from k-nearest neighbour local linear prediction was calculated in each condition as an index of EEG unpredictability. The linear or nonlinear nature of the system underlying EEG activity was evaluated quantifying MSPE as a function of the neighbourhood size during local linear prediction, and by surrogate data analysis as well. Unpredictability maps were obtained for each subject interpolating MSPE values over a schematic head representation. Results on healthy subjects evidenced: (i) the prevalence of linear mechanisms in the generation of EEG dynamics, (ii) the lower predictability of EO EEG, (iii) the desynchronization of oscillatory mechanisms during PS leading to increased EEG complexity, (iv) the entrainment of alpha rhythm during EC obtained by 10 Hz PS, and (v) differences of EEG predictability among different scalp regions. Ischemic patient showed different MSPE values in healthy and damaged regions. The EEG predictability decreased moving from the early acute stage to a stage of partial recovery. These results suggest that nonlinear prediction can be a useful tool to characterize EEG dynamics during PS protocols, and may consequently constitute a complement of quantitative EEG analysis in clinical applications. Copyright © 2010 IPEM. Published by Elsevier Ltd. All rights reserved.

Prediction-error in the context of real social relationships modulates reward system activity.

PubMed

Poore, Joshua C; Pfeifer, Jennifer H; Berkman, Elliot T; Inagaki, Tristen K; Welborn, Benjamin L; Lieberman, Matthew D

2012-01-01

The human reward system is sensitive to both social (e.g., validation) and non-social rewards (e.g., money) and is likely integral for relationship development and reputation building. However, data is sparse on the question of whether implicit social reward processing meaningfully contributes to explicit social representations such as trust and attachment security in pre-existing relationships. This event-related fMRI experiment examined reward system prediction-error activity in response to a potent social reward-social validation-and this activity's relation to both attachment security and trust in the context of real romantic relationships. During the experiment, participants' expectations for their romantic partners' positive regard of them were confirmed (validated) or violated, in either positive or negative directions. Primary analyses were conducted using predefined regions of interest, the locations of which were taken from previously published research. Results indicate that activity for mid-brain and striatal reward system regions of interest was modulated by social reward expectation violation in ways consistent with prior research on reward prediction-error. Additionally, activity in the striatum during viewing of disconfirmatory information was associated with both increases in post-scan reports of attachment anxiety and decreases in post-scan trust, a finding that follows directly from representational models of attachment and trust.

Frontal-striatum dysfunction during reward processing: Relationships to amotivation in schizophrenia.

PubMed

Chung, Yu Sun; Barch, Deanna M

2016-04-01

Schizophrenia is characterized by deficits of context processing, thought to be related to dorsolateral prefrontal cortex (DLPFC) impairment. Despite emerging evidence suggesting a crucial role of the DLPFC in integrating reward and goal information, we do not know whether individuals with schizophrenia can represent and integrate reward-related context information to modulate cognitive control. To address this question, 36 individuals with schizophrenia (n = 29) or schizoaffective disorder (n = 7) and 27 healthy controls performed a variant of a response conflict task (Padmala & Pessoa, 2011) during fMRI scanning, in both baseline and reward conditions, with monetary incentives on some reward trials. We used a mixed state-item design that allowed us to examine both sustained and transient reward effects on cognitive control. Different from predictions about impaired DLPFC function in schizophrenia, we found an intact pattern of increased sustained DLPFC activity during reward versus baseline blocks in individuals with schizophrenia at a group level but blunted sustained activations in the putamen. Contrary to our predictions, individuals with schizophrenia showed blunted cue-related activations in several regions of the basal ganglia responding to reward-predicting cues. Importantly, as predicted, individual differences in anhedonia/amotivation symptoms severity were significantly associated with reduced sustained DLPFC activation in the same region that showed overall increased activity as a function of reward. These results suggest that individual differences in motivational impairments in schizophrenia may be related to dysfunction of the DLPFC and striatum in motivationally salient situations. (c) 2016 APA, all rights reserved).

Regional coseismic landslide hazard assessment without historical landslide inventories: A new approach

NASA Astrophysics Data System (ADS)

Kritikos, Theodosios; Robinson, Tom R.; Davies, Tim R. H.

2015-04-01

Currently, regional coseismic landslide hazard analyses require comprehensive historical landslide inventories as well as detailed geotechnical data. Consequently, such analyses have not been possible where these data are not available. A new approach is proposed herein to assess coseismic landslide hazard at regional scale for specific earthquake scenarios in areas without historical landslide inventories. The proposed model employs fuzzy logic and geographic information systems to establish relationships between causative factors and coseismic slope failures in regions with well-documented and substantially complete coseismic landslide inventories. These relationships are then utilized to estimate the relative probability of landslide occurrence in regions with neither historical landslide inventories nor detailed geotechnical data. Statistical analyses of inventories from the 1994 Northridge and 2008 Wenchuan earthquakes reveal that shaking intensity, topography, and distance from active faults and streams are the main controls on the spatial distribution of coseismic landslides. Average fuzzy memberships for each factor are developed and aggregated to model the relative coseismic landslide hazard for both earthquakes. The predictive capabilities of the models are assessed and show good-to-excellent model performance for both events. These memberships are then applied to the 1999 Chi-Chi earthquake, using only a digital elevation model, active fault map, and isoseismal data, replicating prediction of a future event in a region lacking historic inventories and/or geotechnical data. This similarly results in excellent model performance, demonstrating the model's predictive potential and confirming it can be meaningfully applied in regions where previous methods could not. For such regions, this method may enable a greater ability to analyze coseismic landslide hazard from specific earthquake scenarios, allowing for mitigation measures and emergency response plans to be better informed of earthquake-related hazards.

Seasonal forecasting of fire over Kalimantan, Indonesia

NASA Astrophysics Data System (ADS)

Spessa, A. C.; Field, R. D.; Pappenberger, F.; Langner, A.; Englhart, S.; Weber, U.; Stockdale, T.; Siegert, F.; Kaiser, J. W.; Moore, J.

2015-03-01

Large-scale fires occur frequently across Indonesia, particularly in the southern region of Kalimantan and eastern Sumatra. They have considerable impacts on carbon emissions, haze production, biodiversity, health, and economic activities. In this study, we demonstrate that severe fire and haze events in Indonesia can generally be predicted months in advance using predictions of seasonal rainfall from the ECMWF System 4 coupled ocean-atmosphere model. Based on analyses of long, up-to-date series observations on burnt area, rainfall, and tree cover, we demonstrate that fire activity is negatively correlated with rainfall and is positively associated with deforestation in Indonesia. There is a contrast between the southern region of Kalimantan (high fire activity, high tree cover loss, and strong non-linear correlation between observed rainfall and fire) and the central region of Kalimantan (low fire activity, low tree cover loss, and weak, non-linear correlation between observed rainfall and fire). The ECMWF seasonal forecast provides skilled forecasts of burnt and fire-affected area with several months lead time explaining at least 70% of the variance between rainfall and burnt and fire-affected area. Results are strongly influenced by El Niño years which show a consistent positive bias. Overall, our findings point to a high potential for using a more physical-based method for predicting fires with several months lead time in the tropics rather than one based on indexes only. We argue that seasonal precipitation forecasts should be central to Indonesia's evolving fire management policy.

Prediction of survival with multi-scale radiomic analysis in glioblastoma patients.

PubMed

Chaddad, Ahmad; Sabri, Siham; Niazi, Tamim; Abdulkarim, Bassam

2018-06-19

We propose a multiscale texture features based on Laplacian-of Gaussian (LoG) filter to predict progression free (PFS) and overall survival (OS) in patients newly diagnosed with glioblastoma (GBM). Experiments use the extracted features derived from 40 patients of GBM with T1-weighted imaging (T1-WI) and Fluid-attenuated inversion recovery (FLAIR) images that were segmented manually into areas of active tumor, necrosis, and edema. Multiscale texture features were extracted locally from each of these areas of interest using a LoG filter and the relation between features to OS and PFS was investigated using univariate (i.e., Spearman's rank correlation coefficient, log-rank test and Kaplan-Meier estimator) and multivariate analyses (i.e., Random Forest classifier). Three and seven features were statistically correlated with PFS and OS, respectively, with absolute correlation values between 0.32 and 0.36 and p < 0.05. Three features derived from active tumor regions only were associated with OS (p < 0.05) with hazard ratios (HR) of 2.9, 3, and 3.24, respectively. Combined features showed an AUC value of 85.37 and 85.54% for predicting the PFS and OS of GBM patients, respectively, using the random forest (RF) classifier. We presented a multiscale texture features to characterize the GBM regions and predict he PFS and OS. The efficiency achievable suggests that this technique can be developed into a GBM MR analysis system suitable for clinical use after a thorough validation involving more patients. Graphical abstract Scheme of the proposed model for characterizing the heterogeneity of GBM regions and predicting the overall survival and progression free survival of GBM patients. (1) Acquisition of pretreatment MRI images; (2) Affine registration of T1-WI image with its corresponding FLAIR images, and GBM subtype (phenotypes) labelling; (3) Extraction of nine texture features from the three texture scales fine, medium, and coarse derived from each of GBM regions; (4) Comparing heterogeneity between GBM regions by ANOVA test; Survival analysis using Univariate (Spearman rank correlation between features and survival (i.e., PFS and OS) based on each of the GBM regions, Kaplan-Meier estimator and log-rank test to predict the PFS and OS of patient groups that grouped based on median of feature), and multivariate (random forest model) for predicting the PFS and OS of patients groups that grouped based on median of PFS and OS.

Effects of Plant Traits on Ecosystem and Regional Processes: a Conceptual Framework for Predicting the Consequences of Global Change

PubMed Central

CHAPIN, F. STUART

2003-01-01

Human activities are causing widespread changes in the species composition of natural and managed ecosystems, but the consequences of these changes are poorly understood. This paper presents a conceptual framework for predicting the ecosystem and regional consequences of changes in plant species composition. Changes in species composition have greatest ecological effects when they modify the ecological factors that directly control (and respond to) ecosystem processes. These interactive controls include: functional types of organisms present in the ecosystem; soil resources used by organisms to grow and reproduce; modulators such as microclimate that influence the activity of organisms; disturbance regime; and human activities. Plant traits related to size and growth rate are particularly important because they determine the productive capacity of vegetation and the rates of decomposition and nitrogen mineralization. Because the same plant traits affect most key processes in the cycling of carbon and nutrients, changes in plant traits tend to affect most biogeochemical cycling processes in parallel. Plant traits also have landscape and regional effects through their effects on water and energy exchange and disturbance regime. PMID:12588725

The Ordered Network Structure and Prediction Summary for M≥7 Earthquakes in Xinjiang Region of China

NASA Astrophysics Data System (ADS)

Men, Ke-Pei; Zhao, Kai

2014-12-01

M ≥7 earthquakes have showed an obvious commensurability and orderliness in Xinjiang of China and its adjacent region since 1800. The main orderly values are 30 a × k (k = 1,2,3), 11 12 a, 41 43 a, 18 19 a, and 5 6 a. In the guidance of the information forecasting theory of Wen-Bo Weng, based on previous research results, combining ordered network structure analysis with complex network technology, we focus on the prediction summary of M ≥ 7 earthquakes by using the ordered network structure, and add new information to further optimize network, hence construct the 2D- and 3D-ordered network structure of M ≥ 7 earthquakes. In this paper, the network structure revealed fully the regularity of seismic activity of M ≥ 7 earthquakes in the study region during the past 210 years. Based on this, the Karakorum M7.1 earthquake in 1996, the M7.9 earthquake on the frontier of Russia, Mongol, and China in 2003, and two Yutian M7.3 earthquakes in 2008 and 2014 were predicted successfully. At the same time, a new prediction opinion is presented that the future two M ≥ 7 earthquakes will probably occur around 2019 - 2020 and 2025 - 2026 in this region. The results show that large earthquake occurred in defined region can be predicted. The method of ordered network structure analysis produces satisfactory results for the mid-and-long term prediction of M ≥ 7 earthquakes.

Distributions of exotic plants in eastern Asia and North America

USGS Publications Warehouse

Guo, Q.; Qian, H.; Ricklefs, R.E.; Xi, W.

2006-01-01

Although some plant traits have been linked to invasion success, the possible effects of regional factors, such as diversity, habitat suitability, and human activity are not well understood. Each of these mechanisms predicts a different pattern of distribution at the regional scale. Thus, where climate and soils are similar, predictions based on regional hypotheses for invasion success can be tested by comparisons of distributions in the source and receiving regions. Here, we analyse the native and alien geographic ranges of all 1567 plant species that have been introduced between eastern Asia and North America or have been introduced to both regions from elsewhere. The results reveal correlations between the spread of exotics and both the native species richness and transportation networks of recipient regions. This suggests that both species interactions and human-aided dispersal influence exotic distributions, although further work on the relative importance of these processes is needed. ?? 2006 Blackwell Publishing Ltd/CNRS.

Neuroscience of inhibition for addiction medicine: from prediction of initiation to prediction of relapse.

PubMed

Moeller, Scott J; Bederson, Lucia; Alia-Klein, Nelly; Goldstein, Rita Z

2016-01-01

A core deficit in drug addiction is the inability to inhibit maladaptive drug-seeking behavior. Consistent with this deficit, drug-addicted individuals show reliable cross-sectional differences from healthy nonaddicted controls during tasks of response inhibition accompanied by brain activation abnormalities as revealed by functional neuroimaging. However, it is less clear whether inhibition-related deficits predate the transition to problematic use, and, in turn, whether these deficits predict the transition out of problematic substance use. Here, we review longitudinal studies of response inhibition in children/adolescents with little substance experience and longitudinal studies of already addicted individuals attempting to sustain abstinence. Results show that response inhibition and its underlying neural correlates predict both substance use outcomes (onset and abstinence). Neurally, key roles were observed for multiple regions of the frontal cortex (e.g., inferior frontal gyrus, dorsal anterior cingulate cortex, and dorsolateral prefrontal cortex). In general, less activation of these regions during response inhibition predicted not only the onset of substance use, but interestingly also better abstinence-related outcomes among individuals already addicted. The role of subcortical areas, although potentially important, is less clear because of inconsistent results and because these regions are less classically reported in studies of healthy response inhibition. Overall, this review indicates that response inhibition is not simply a manifestation of current drug addiction, but rather a core neurocognitive dimension that predicts key substance use outcomes. Early intervention in inhibitory deficits could have high clinical and public health relevance. © 2016 Elsevier B.V. All rights reserved.

Participant adherence indicatiors predict changes in blood pressure, anthropometric measures, and self-reported physical activity in a lifestyle intervention: HUB City Steps

USDA-ARS?s Scientific Manuscript database

Purpose. To evaluate several adherence indicators, created using 2 measures, separately and in combination, for predicting health outcome changes. Design. Non-experimental with pre-post measures. Setting. Mid-sized city in southern region of United States. Subjects. 269 primarily African-America...

Mesencephalic representations of recent experience influence decision making.

PubMed

Thompson, John A; Costabile, Jamie D; Felsen, Gidon

2016-07-25

Decisions are influenced by recent experience, but the neural basis for this phenomenon is not well understood. Here, we address this question in the context of action selection. We focused on activity in the pedunculopontine tegmental nucleus (PPTg), a mesencephalic region that provides input to several nuclei in the action selection network, in well-trained mice selecting actions based on sensory cues and recent trial history. We found that, at the time of action selection, the activity of many PPTg neurons reflected the action on the previous trial and its outcome, and the strength of this activity predicted the upcoming choice. Further, inactivating the PPTg predictably decreased the influence of recent experience on action selection. These findings suggest that PPTg input to downstream motor regions, where it can be integrated with other relevant information, provides a simple mechanism for incorporating recent experience into the computations underlying action selection.

Expression, fermentation and purification of a predicted intrinsically disordered region of the transcription factor, NFAT5.

PubMed

DuMond, Jenna F; He, Yi; Burg, Maurice B; Ferraris, Joan D

2015-11-01

Hypertonicity stimulates Nuclear Factor of Activated T-cells 5 (NFAT5) nuclear localization and transactivating activity. Many transcription factors are known to contain intrinsically disordered regions (IDRs) which become more structured with local environmental changes such as osmolality, temperature and tonicity. The transactivating domain of NFAT5 is predicted to be intrinsically disordered under normal tonicity, and under high NaCl, the activity of this domain is increased. To study the binding of co-regulatory proteins at IDRs a cDNA construct expressing the NFAT5 TAD was created and transformed into Escherichia coli cells. Transformed E. coli cells were mass produced by fermentation and extracted by cell lysis to release the NFAT5 TAD. The NFAT5 TAD was subsequently purified using a His-tag column, cation exchange chromatography as well as hydrophobic interaction chromatography and then characterized by mass spectrometry (MS). Published by Elsevier Inc.

Extrapolating cetacean densities to quantitatively assess human impacts on populations in the high seas.

PubMed

Mannocci, Laura; Roberts, Jason J; Miller, David L; Halpin, Patrick N

2017-06-01

As human activities expand beyond national jurisdictions to the high seas, there is an increasing need to consider anthropogenic impacts to species inhabiting these waters. The current scarcity of scientific observations of cetaceans in the high seas impedes the assessment of population-level impacts of these activities. We developed plausible density estimates to facilitate a quantitative assessment of anthropogenic impacts on cetacean populations in these waters. Our study region extended from a well-surveyed region within the U.S. Exclusive Economic Zone into a large region of the western North Atlantic sparsely surveyed for cetaceans. We modeled densities of 15 cetacean taxa with available line transect survey data and habitat covariates and extrapolated predictions to sparsely surveyed regions. We formulated models to reduce the extent of extrapolation beyond covariate ranges, and constrained them to model simple and generalizable relationships. To evaluate confidence in the predictions, we mapped where predictions were made outside sampled covariate ranges, examined alternate models, and compared predicted densities with maps of sightings from sources that could not be integrated into our models. Confidence levels in model results depended on the taxon and geographic area and highlighted the need for additional surveying in environmentally distinct areas. With application of necessary caution, our density estimates can inform management needs in the high seas, such as the quantification of potential cetacean interactions with military training exercises, shipping, fisheries, and deep-sea mining and be used to delineate areas of special biological significance in international waters. Our approach is generally applicable to other marine taxa and geographic regions for which management will be implemented but data are sparse. © 2016 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Imagine All the People: How the Brain Creates and Uses Personality Models to Predict Behavior

PubMed Central

Hassabis, Demis; Spreng, R. Nathan; Rusu, Andrei A.; Robbins, Clifford A.; Mar, Raymond A.; Schacter, Daniel L.

2014-01-01

The behaviors of other people are often central to envisioning the future. The ability to accurately predict the thoughts and actions of others is essential for successful social interactions, with far-reaching consequences. Despite its importance, little is known about how the brain represents people in order to predict behavior. In this functional magnetic resonance imaging study, participants learned the unique personality of 4 protagonists and imagined how each would behave in different scenarios. The protagonists' personalities were composed of 2 traits: Agreeableness and Extraversion. Which protagonist was being imagined was accurately inferred based solely on activity patterns in the medial prefrontal cortex using multivariate pattern classification, providing novel evidence that brain activity can reveal whom someone is thinking about. Lateral temporal and posterior cingulate cortex discriminated between different degrees of agreeableness and extraversion, respectively. Functional connectivity analysis confirmed that regions associated with trait-processing and individual identities were functionally coupled. Activity during the imagination task, and revealed by functional connectivity, was consistent with the default network. Our results suggest that distinct regions code for personality traits, and that the brain combines these traits to represent individuals. The brain then uses this “personality model” to predict the behavior of others in novel situations. PMID:23463340

Seasonal Extratropical Storm Activity Potential Predictability and its Origins during the Cold Seasons

NASA Astrophysics Data System (ADS)

Pingree-Shippee, K. A.; Zwiers, F. W.; Atkinson, D. E.

2016-12-01

Extratropical cyclones (ETCs) often produce extreme hazardous weather conditions, such as high winds, blizzard conditions, heavy precipitation, and flooding, all of which can have detrimental socio-economic impacts. The North American east and west coastal regions are both strongly influenced by ETCs and, subsequently, land-based, coastal, and maritime economic sectors in Canada and the USA all experience strong adverse impacts from extratropical storm activity from time to time. Society would benefit if risks associated with ETCs and storm activity variability could be reliably predicted for the upcoming season. Skillful prediction would enable affected sectors to better anticipate, prepare for, manage, and respond to storm activity variability and the associated risks and impacts. In this study, the potential predictability of seasonal variations in extratropical storm activity is investigated using analysis of variance to provide quantitative and geographical observational evidence indicative of whether it may be possible to predict storm activity on the seasonal timescale. This investigation will also identify origins of the potential predictability using composite analysis and large-scale teleconnections (Southern Oscillation, Pacific Decadal Oscillation, and North Atlantic Oscillation), providing the basis upon which seasonal predictions can be developed. Seasonal potential predictability and its origins are investigated for the cold seasons (OND, NDJ, DJF, JFM) during the 1979-2015 time period using daily mean sea level pressure, absolute pressure tendency, and 10-m wind speed from the ECMWF ERA-Interim reanalysis as proxies for extratropical storm activity. Results indicate potential predictability of seasonal variations in storm activity in areas strongly influenced by ETCs and with origins in the investigated teleconnections. For instance, the North Pacific storm track has considerable potential predictability and with notable origins in the SO and PDO.

Prioritizing human pharmaceuticals for ecological risks in the freshwater environment of Korea.

PubMed

Ji, Kyunghee; Han, Eun Jeong; Back, Sunhyoung; Park, Jeongim; Ryu, Jisung; Choi, Kyungho

2016-04-01

Pharmaceutical residues are potential threats to aquatic ecosystems. Because more than 3000 active pharmaceutical ingredients (APIs) are in use, identifying high-priority pharmaceuticals is important for developing appropriate management options. Priority pharmaceuticals may vary by geographical region, because their occurrence levels can be influenced by demographic, societal, and regional characteristics. In the present study, the authors prioritized human pharmaceuticals of potential ecological risk in the Korean water environment, based on amount of use, biological activity, and regional hydrologic characteristics. For this purpose, the authors estimated the amounts of annual production of 695 human APIs in Korea. Then derived predicted environmental concentrations, using 2 approaches, to develop an initial candidate list of target pharmaceuticals. Major antineoplastic drugs and hormones were added in the initial candidate list regardless of their production amount because of their high biological activity potential. The predicted no effect concentrations were derived for those pharmaceuticals based on ecotoxicity information available in the literature or by model prediction. Priority lists of human pharmaceuticals were developed based on ecological risks and availability of relevant information. Those priority APIs identified include acetaminophen, clarithromycin, ciprofloxacin, ofloxacin, metformin, and norethisterone. Many of these pharmaceuticals have been neither adequately monitored nor assessed for risks in Korea. Further efforts are needed to improve these lists and to develop management decisions for these compounds in Korean water. © 2015 SETAC.

Different forms of effective connectivity in primate frontotemporal pathways.

PubMed

Petkov, Christopher I; Kikuchi, Yukiko; Milne, Alice E; Mishkin, Mortimer; Rauschecker, Josef P; Logothetis, Nikos K

2015-01-23

It is generally held that non-primary sensory regions of the brain have a strong impact on frontal cortex. However, the effective connectivity of pathways to frontal cortex is poorly understood. Here we microstimulate sites in the superior temporal and ventral frontal cortex of monkeys and use functional magnetic resonance imaging to evaluate the functional activity resulting from the stimulation of interconnected regions. Surprisingly, we find that, although certain earlier stages of auditory cortical processing can strongly activate frontal cortex, downstream auditory regions, such as voice-sensitive cortex, appear to functionally engage primarily an ipsilateral temporal lobe network. Stimulating other sites within this activated temporal lobe network shows strong activation of frontal cortex. The results indicate that the relative stage of sensory processing does not predict the level of functional access to the frontal lobes. Rather, certain brain regions engage local networks, only parts of which have a strong functional impact on frontal cortex.

Different forms of effective connectivity in primate frontotemporal pathways

PubMed Central

Petkov, Christopher I.; Kikuchi, Yukiko; Milne, Alice E.; Mishkin, Mortimer; Rauschecker, Josef P.; Logothetis, Nikos K.

2015-01-01

It is generally held that non-primary sensory regions of the brain have a strong impact on frontal cortex. However, the effective connectivity of pathways to frontal cortex is poorly understood. Here we microstimulate sites in the superior temporal and ventral frontal cortex of monkeys and use functional magnetic resonance imaging to evaluate the functional activity resulting from the stimulation of interconnected regions. Surprisingly, we find that, although certain earlier stages of auditory cortical processing can strongly activate frontal cortex, downstream auditory regions, such as voice-sensitive cortex, appear to functionally engage primarily an ipsilateral temporal lobe network. Stimulating other sites within this activated temporal lobe network shows strong activation of frontal cortex. The results indicate that the relative stage of sensory processing does not predict the level of functional access to the frontal lobes. Rather, certain brain regions engage local networks, only parts of which have a strong functional impact on frontal cortex. PMID:25613079

Space-time characteristics and statistical predictability of extreme daily precipitation events in the Ohio River Basin

NASA Astrophysics Data System (ADS)

Farnham, D. J.; Doss-Gollin, J.; Lall, U.

2016-12-01

In this study we identify the atmospheric conditions that precede and accompany regional extreme precipitation events with the potential to cause flooding. We begin by identifying a coherent space-time structure in the record of extreme precipitation within the Ohio River Basin through both a Hidden Markov Model and a composite analysis. The transition probabilities associated with the Hidden Markov Model illustrate a tendency for west to east migration of extreme precipitation events (> 99th percentile) at individual stations within the Ohio River Basin. We compute a record of regional extreme precipitation days by requiring that > p% of the basin's stations simultaneously experience extreme precipitation days. A composite analysis of low-level geopotential heights and column integrated precipitable water content for all non-summer seasons confirms a west to east migration and intensification of 1) a low (high) pressure center to the west (east) of the basin, and 2) enhanced precipitable water vapor content that stretches from the Gulf of Mexico to the Northeast US region in the days leading up to regional extreme precipitation days. We define a daily dipole index to summarize the strength of the paired cylonic and aniticyclonic systems to the west and east of the basin and analyze its temporal characteristics and its relationship to the regional extreme precipitation events. Lastly, we investigate and discuss the subseasonal predictability of individual extreme precipitation events and the seasonal predictability of active and inactive seasons, where the activity level is defined by the expected frequency of regional extreme precipitation events.

Brain mediators of predictive cue effects on perceived pain

PubMed Central

Atlas, Lauren Y.; Bolger, Niall; Lindquist, Martin A.; Wager, Tor D.

2010-01-01

Information about upcoming pain strongly influences pain experience in experimental and clinical settings, but little is known about the brain mechanisms that link expectation and experience. To identify the pathways by which informational cues influence perception, analyses must jointly consider both the effects of cues on brain responses and the relationship between brain responses and changes in reported experience. Our task and analysis strategy were designed to test these relationships. Auditory cues elicited expectations for low or high painful thermal stimulation, and we assessed how cues influenced human subjects’ pain reports and BOLD fMRI responses to matched levels of noxious heat. We used multi-level mediation analysis to identify brain regions that 1) are modulated by predictive cues, 2) predict trial-to-trial variations in pain reports, and 3) formally mediate the relationship between cues and reported pain. Cues influenced heat-evoked responses in most canonical pain-processing regions, including both medial and lateral pain pathways. Effects on several regions correlated with pre-task expectations, suggesting that expectancy plays a prominent role. A subset of pain-processing regions, including anterior cingulate cortex, anterior insula, and thalamus, formally mediated cue effects on pain. Effects on these regions were in turn mediated by cue-evoked anticipatory activity in the medial orbitofrontal cortex (OFC) and ventral striatum, areas not previously directly implicated in nociception. These results suggest that activity in pain-processing regions reflects a combination of nociceptive input and top-down information related to expectations, and that anticipatory processes in OFC and striatum may play a key role in modulating pain processing. PMID:20881115

Seasonal Storminess in the North Pacific, Bering Sea, and Alaskan Regions

NASA Astrophysics Data System (ADS)

Shippee, N. J.; Atkinson, D. E.; Walsh, J. E.; Partain, J.; Gottschalck, J.; Marra, J.

2012-12-01

Annually, extra-tropical cyclones present a high impact natural hazard to the North Pacific, Bering Sea, and Alaskan regions. In these regions, extensive subsistence and commercial fishing, new oil and gas field development, tourism, growing interest in and exploitation of new commercial shipping potential, and increasing military and Coast Guard activity, all represent potential parties impacted by storms in these waters. It is of interest to many parties to begin developing capacity to provide some indication of storm activity at a monthly- to seasonal-outlook (30 to 90 days) timeframe. Using storm track data from NOAA's Climate Prediction Center for the North Pacific and Alaskan region, an experimental seasonal storminess outlook product, using eigen-based methods similar to the operational seasonal temperature and precipitation products currently produced at NOAA CPC, has been created and tested in hindcast mode using predicted states of ENSO, the Pacific Decadal Oscillation (PDO), the Pacific-North American Pattern (PNA), and the Arctic Oscillation (AO). A sample of the seasonal storminess outlook product will be shown along with a discussion of the utility of individual teleconnection patterns in the generation of the product.

The canonical semantic network supports residual language function in chronic post-stroke aphasia

PubMed Central

Griffis, Joseph C.; Nenert, Rodolphe; Allendorfer, Jane B.; Vannest, Jennifer; Holland, Scott; Dietz, Aimee; Szaflarski, Jerzy P.

2016-01-01

Current theories of language recovery after stroke are limited by a reliance on small studies. Here, we aimed to test predictions of current theory and resolve inconsistencies regarding right hemispheric contributions to long-term recovery. We first defined the canonical semantic network in 43 healthy controls. Then, in a group of 43 patients with chronic post-stroke aphasia, we tested whether activity in this network predicted performance on measures of semantic comprehension, naming, and fluency while controlling for lesion volume effects. Canonical network activation accounted for 22–33% of the variance in language test scores. Whole-brain analyses corroborated these findings, and revealed a core set of regions showing positive relationships to all language measures. We next evaluated the relationship between activation magnitudes in left and right hemispheric portions of the network, and characterized how right hemispheric activation related to the extent of left hemispheric damage. Activation magnitudes in each hemispheric network were strongly correlated, but four right frontal regions showed heightened activity in patients with large lesions. Activity in two of these regions (inferior frontal gyrus pars opercularis and supplementary motor area) was associated with better language abilities in patients with larger lesions, but poorer language abilities in patients with smaller lesions. Our results indicate that bilateral language networks support language processing after stroke, and that right hemispheric activations related to extensive left hemisphere damage occur outside of the canonical semantic network and differentially relate to behavior depending on the extent of left hemispheric damage. PMID:27981674

Patterns of Activity in A Global Model of A Solar Active Region

NASA Technical Reports Server (NTRS)

Bradshaw, S. J.; Viall, N. M.

2016-01-01

In this work we investigate the global activity patterns predicted from a model active region heated by distributions of nanoflares that have a range of frequencies. What differs is the average frequency of the distributions. The activity patterns are manifested in time lag maps of narrow-band instrument channel pairs. We combine hydrodynamic and forward modeling codes with a magnetic field extrapolation to create a model active region and apply the time lag method to synthetic observations. Our aim is not to reproduce a particular set of observations in detail, but to recover some typical properties and patterns observed in active regions. Our key findings are the following. (1) Cooling dominates the time lag signature and the time lags between the channel pairs are generally consistent with observed values. (2) Shorter coronal loops in the core cool more quickly than longer loops at the periphery. (3) All channel pairs show zero time lag when the line of sight passes through coronal loop footpoints. (4) There is strong evidence that plasma must be re-energized on a timescale comparable to the cooling timescale to reproduce the observed coronal activity, but it is likely that a relatively broad spectrum of heating frequencies are operating across active regions. (5) Due to their highly dynamic nature, we find nanoflare trains produce zero time lags along entire flux tubes in our model active region that are seen between the same channel pairs in observed active regions.

Computational and experimental analysis of TMS-induced electric field vectors critical to neuronal activation

NASA Astrophysics Data System (ADS)

Krieg, Todd D.; Salinas, Felipe S.; Narayana, Shalini; Fox, Peter T.; Mogul, David J.

2015-08-01

Objective. Transcranial magnetic stimulation (TMS) represents a powerful technique to noninvasively modulate cortical neurophysiology in the brain. However, the relationship between the magnetic fields created by TMS coils and neuronal activation in the cortex is still not well-understood, making predictable cortical activation by TMS difficult to achieve. Our goal in this study was to investigate the relationship between induced electric fields and cortical activation measured by blood flow response. Particularly, we sought to discover the E-field characteristics that lead to cortical activation. Approach. Subject-specific finite element models (FEMs) of the head and brain were constructed for each of six subjects using magnetic resonance image scans. Positron emission tomography (PET) measured each subject’s cortical response to image-guided robotically-positioned TMS to the primary motor cortex. FEM models that employed the given coil position, orientation, and stimulus intensity in experimental applications of TMS were used to calculate the electric field (E-field) vectors within a region of interest for each subject. TMS-induced E-fields were analyzed to better understand what vector components led to regional cerebral blood flow (CBF) responses recorded by PET. Main results. This study found that decomposing the E-field into orthogonal vector components based on the cortical surface geometry (and hence, cortical neuron directions) led to significant differences between the regions of cortex that were active and nonactive. Specifically, active regions had significantly higher E-field components in the normal inward direction (i.e., parallel to pyramidal neurons in the dendrite-to-axon orientation) and in the tangential direction (i.e., parallel to interneurons) at high gradient. In contrast, nonactive regions had higher E-field vectors in the outward normal direction suggesting inhibitory responses. Significance. These results provide critical new understanding of the factors by which TMS induces cortical activation necessary for predictive and repeatable use of this noninvasive stimulation modality.

The Correlations between Airport Sustainability and Indonesian Economic Growth

NASA Astrophysics Data System (ADS)

Setiawan, M. I.; Dhaniarti, I.; Utomo, W. M.; Sukoco, A.; Mudjanarko, S. W.; Hasyim, C.; Prasetijo, J.; Kurniasih, N.; Wajdi, M. B. N.; Purworusmiardi, T.; Suyono, J.; Sudapet, I. N.; Nasihien, R. D.; Wulandari, D. A. R.; Ade, R. T.; Atmaja, W. M. T.; Sugeng; Wulandari, A.

2018-04-01

This study aims to analyze the correlation between airport performances with Gross domestic product-regional (GDP-regional) performance. This research uses quantitative research method with correlation study approach. Based on the T-Value Test Result, the T-value for the Airport Performance variable is 14,264. T-Value Test Results and compared with T-table equal to 1,976 (significant level 0,05) hence T-count> T-table so variable of Airport Perform predicted have significant correlation to GDP-regional. This means that good airport performance will either improve the performance of Water supply, Sewerage, Waste Management and Remediation Activities; Wholesale and Retail Trade; Repair of Motor Vehicles and Motorcycles; Accommodation and Food Service Activities; Financial and Insurance Activities; Business Activities; Public Administration and Defence; Compulsory Social Security; Education; Human Health and Social Work Activities; Other Services Activities; Manufacturing; and Electricity and Gas, better.

Mapping and predicting sinkholes by integration of remote sensing and spectroscopy methods

NASA Astrophysics Data System (ADS)

Goldshleger, N.; Basson, U.; Azaria, I.

2013-08-01

The Dead Sea coastal area is exposed to the destructive process of sinkhole collapse. The increase in sinkhole activity in the last two decades has been substantial, resulting from the continuous decrease in the Dead Sea's level, with more than 1,000 sinkholes developing as a result of upper layer collapse. Large sinkholes can reach 25 m in diameter. They are concentrated mainly in clusters in several dozens of sites with different characteristics. In this research, methods for mapping, monitoring and predicting sinkholes were developed using active and passive remote-sensing methods: field spectrometer, geophysical ground penetration radar (GPR) and a frequency domain electromagnetic instrument (FDEM). The research was conducted in three stages: 1) literature review and data collection; 2) mapping regions abundant with sinkholes in various stages and regions vulnerable to sinkholes; 3) analyzing the data and translating it into cognitive and accessible scientific information. Field spectrometry enabled a comparison between the spectral signatures of soil samples collected near active or progressing sinkholes, and those collected in regions with no visual sign of sinkhole occurrence. FDEM and GPR investigations showed that electrical conductivity and soil moisture are higher in regions affected by sinkholes. Measurements taken at different time points over several seasons allowed monitoring the progress of an 'embryonic' sinkhole.

The Solar Wind and Geomagnetic Activity as a Function of Time Relative to Corotating Interaction Regions

NASA Technical Reports Server (NTRS)

McPherron, Robert L.; Weygand, James

2006-01-01

Corotating interaction regions during the declining phase of the solar cycle are the cause of recurrent geomagnetic storms and are responsible for the generation of high fluxes of relativistic electrons. These regions are produced by the collision of a high-speed stream of solar wind with a slow-speed stream. The interface between the two streams is easily identified with plasma and field data from a solar wind monitor upstream of the Earth. The properties of the solar wind and interplanetary magnetic field are systematic functions of time relative to the stream interface. Consequently the coupling of the solar wind to the Earth's magnetosphere produces a predictable sequence of events. Because the streams persist for many solar rotations it should be possible to use terrestrial observations of past magnetic activity to predict future activity. Also the high-speed streams are produced by large unipolar magnetic regions on the Sun so that empirical models can be used to predict the velocity profile of a stream expected at the Earth. In either case knowledge of the statistical properties of the solar wind and geomagnetic activity as a function of time relative to a stream interface provides the basis for medium term forecasting of geomagnetic activity. In this report we use lists of stream interfaces identified in solar wind data during the years 1995 and 2004 to develop probability distribution functions for a variety of different variables as a function of time relative to the interface. The results are presented as temporal profiles of the quartiles of the cumulative probability distributions of these variables. We demonstrate that the storms produced by these interaction regions are generally very weak. Despite this the fluxes of relativistic electrons produced during those storms are the highest seen in the solar cycle. We attribute this to the specific sequence of events produced by the organization of the solar wind relative to the stream interfaces. We also show that there are large quantitative differences in various parameters between the two cycles.

Patterns of neural activity associated with honest and dishonest moral decisions

PubMed Central

Greene, Joshua D.; Paxton, Joseph M.

2009-01-01

What makes people behave honestly when confronted with opportunities for dishonest gain? Research on the interplay between controlled and automatic processes in decision making suggests 2 hypotheses: According to the “Will” hypothesis, honesty results from the active resistance of temptation, comparable to the controlled cognitive processes that enable the delay of reward. According to the “Grace” hypothesis, honesty results from the absence of temptation, consistent with research emphasizing the determination of behavior by the presence or absence of automatic processes. To test these hypotheses, we examined neural activity in individuals confronted with opportunities for dishonest gain. Subjects undergoing functional magnetic resonance imaging (fMRI) gained money by accurately predicting the outcomes of computerized coin-flips. In some trials, subjects recorded their predictions in advance. In other trials, subjects were rewarded based on self-reported accuracy, allowing them to gain money dishonestly by lying about the accuracy of their predictions. Many subjects behaved dishonestly, as indicated by improbable levels of “accuracy.” Our findings support the Grace hypothesis. Individuals who behaved honestly exhibited no additional control-related activity (or other kind of activity) when choosing to behave honestly, as compared with a control condition in which there was no opportunity for dishonest gain. In contrast, individuals who behaved dishonestly exhibited increased activity in control-related regions of prefrontal cortex, both when choosing to behave dishonestly and on occasions when they refrained from dishonesty. Levels of activity in these regions correlated with the frequency of dishonesty in individuals. PMID:19622733

Emotion Awareness Predicts Body Mass Index Percentile Trajectories in Youth.

PubMed

Whalen, Diana J; Belden, Andy C; Barch, Deanna; Luby, Joan

2015-10-01

To examine the rate of change in body mass index (BMI) percentile across 3 years in relation to emotion identification ability and brain-based reactivity in emotional processing regions. A longitudinal sample of 202 youths completed 3 functional magnetic resonance imaging-based facial processing tasks and behavioral emotion differentiation tasks. We examined the rate of change in the youth's BMI percentile as a function of reactivity in emotional processing brain regions and behavioral emotion identification tasks using multilevel modeling. Lower correct identification of both happiness and sadness measured behaviorally predicted increases in BMI percentile across development, whereas higher correct identification of both happiness and sadness predicted decreases in BMI percentile, while controlling for children's pubertal status, sex, ethnicity, IQ score, exposure to antipsychotic medication, family income-to-needs ratio, and externalizing, internalizing, and depressive symptoms. Greater neural activation in emotional reactivity regions to sad faces also predicted increases in BMI percentile during development, also controlling for the aforementioned covariates. Our findings provide longitudinal developmental data demonstrating links between both emotion identification ability and greater neural reactivity in emotional processing regions with trajectories of BMI percentiles across childhood. Copyright © 2015 Elsevier Inc. All rights reserved.

Neural Correlates of Four Broad Temperament Dimensions: Testing Predictions for a Novel Construct of Personality

PubMed Central

Brown, Lucy L.; Acevedo, Bianca; Fisher, Helen E.

2013-01-01

Four suites of behavioral traits have been associated with four broad neural systems: the 1) dopamine and related norepinephrine system; 2) serotonin; 3) testosterone; 4) and estrogen and oxytocin system. A 56-item questionnaire, the Fisher Temperament Inventory (FTI), was developed to define four temperament dimensions associated with these behavioral traits and neural systems. The questionnaire has been used to suggest romantic partner compatibility. The dimensions were named: Curious/Energetic; Cautious/Social Norm Compliant; Analytical/Tough-minded; and Prosocial/Empathetic. For the present study, the FTI was administered to participants in two functional magnetic resonance imaging studies that elicited feelings of love and attachment, near-universal human experiences. Scores for the Curious/Energetic dimension co-varied with activation in a region of the substantia nigra, consistent with the prediction that this dimension reflects activity in the dopamine system. Scores for the Cautious/Social Norm Compliant dimension correlated with activation in the ventrolateral prefrontal cortex in regions associated with social norm compliance, a trait linked with the serotonin system. Scores on the Analytical/Tough-minded scale co-varied with activity in regions of the occipital and parietal cortices associated with visual acuity and mathematical thinking, traits linked with testosterone. Also, testosterone contributes to brain architecture in these areas. Scores on the Prosocial/Empathetic scale correlated with activity in regions of the inferior frontal gyrus, anterior insula and fusiform gyrus. These are regions associated with mirror neurons or empathy, a trait linked with the estrogen/oxytocin system, and where estrogen contributes to brain architecture. These findings, replicated across two studies, suggest that the FTI measures influences of four broad neural systems, and that these temperament dimensions and neural systems could constitute foundational mechanisms in personality structure and play a role in romantic partnerships. PMID:24236043

Neural correlates of four broad temperament dimensions: testing predictions for a novel construct of personality.

PubMed

Brown, Lucy L; Acevedo, Bianca; Fisher, Helen E

2013-01-01

Four suites of behavioral traits have been associated with four broad neural systems: the 1) dopamine and related norepinephrine system; 2) serotonin; 3) testosterone; 4) and estrogen and oxytocin system. A 56-item questionnaire, the Fisher Temperament Inventory (FTI), was developed to define four temperament dimensions associated with these behavioral traits and neural systems. The questionnaire has been used to suggest romantic partner compatibility. The dimensions were named: Curious/Energetic; Cautious/Social Norm Compliant; Analytical/Tough-minded; and Prosocial/Empathetic. For the present study, the FTI was administered to participants in two functional magnetic resonance imaging studies that elicited feelings of love and attachment, near-universal human experiences. Scores for the Curious/Energetic dimension co-varied with activation in a region of the substantia nigra, consistent with the prediction that this dimension reflects activity in the dopamine system. Scores for the Cautious/Social Norm Compliant dimension correlated with activation in the ventrolateral prefrontal cortex in regions associated with social norm compliance, a trait linked with the serotonin system. Scores on the Analytical/Tough-minded scale co-varied with activity in regions of the occipital and parietal cortices associated with visual acuity and mathematical thinking, traits linked with testosterone. Also, testosterone contributes to brain architecture in these areas. Scores on the Prosocial/Empathetic scale correlated with activity in regions of the inferior frontal gyrus, anterior insula and fusiform gyrus. These are regions associated with mirror neurons or empathy, a trait linked with the estrogen/oxytocin system, and where estrogen contributes to brain architecture. These findings, replicated across two studies, suggest that the FTI measures influences of four broad neural systems, and that these temperament dimensions and neural systems could constitute foundational mechanisms in personality structure and play a role in romantic partnerships.

Spatial representation of organic carbon and active-layer thickness of high latitude soils in CMIP5 earth system models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mishra, Umakant; Drewniak, Beth; Jastrow, Julie D.

Soil properties such as soil organic carbon (SOC) stocks and active-layer thickness are used in earth system models (F.SMs) to predict anthropogenic and climatic impacts on soil carbon dynamics, future changes in atmospheric greenhouse gas concentrations, and associated climate changes in the permafrost regions. Accurate representation of spatial and vertical distribution of these soil properties in ESMs is a prerequisite for redudng existing uncertainty in predicting carbon-climate feedbacks. We compared the spatial representation of SOC stocks and active-layer thicknesses predicted by the coupled Modellntercomparison Project Phase 5 { CMIP5) ESMs with those predicted from geospatial predictions, based on observation datamore » for the state of Alaska, USA. For the geospatial modeling. we used soil profile observations {585 for SOC stocks and 153 for active-layer thickness) and environmental variables (climate, topography, land cover, and surficial geology types) and generated fine-resolution (50-m spatial resolution) predictions of SOC stocks (to 1-m depth) and active-layer thickness across Alaska. We found large inter-quartile range (2.5-5.5 m) in predicted active-layer thickness of CMIP5 modeled results and small inter-quartile range (11.5-22 kg m-2) in predicted SOC stocks. The spatial coefficient of variability of active-layer thickness and SOC stocks were lower in CMIP5 predictions compared to our geospatial estimates when gridded at similar spatial resolutions (24.7 compared to 30% and 29 compared to 38%, respectively). However, prediction errors. when calculated for independent validation sites, were several times larger in ESM predictions compared to geospatial predictions. Primaly factors leading to observed differences were ( 1) lack of spatial heterogeneity in ESM predictions, (2) differences in assumptions concerning environmental controls, and (3) the absence of pedogenic processes in ESM model structures. Our results suggest that efforts to incorporate these factors in F.SMs should reduce current uncertainties associated with ESM predictions of carbon-climate feedbacks.« less

Evaluating Fire Risk in the Northeastern United States in the Past, Present, and Future

NASA Astrophysics Data System (ADS)

Miller, D.; Bradley, R. S.

2017-12-01

One poorly understood consequence of climate change is its effects on extreme events such as wildfires. Robust associations between wildfire frequency and climatic variability have been shown to exist, indicating that future climate change may continue to have a significant effect on wildfire activity. The Northeastern United States (NEUS) has seen some of the most infamous and largest historic fires in North America, such as the Miramichi Fire of 1825 and the fires of 1947. Although return intervals for large fires in the NEUS are long (hundreds of years), wildfires have played a critical role in ecosystem development and forest structure in the region. Understanding and predicting fire occurrence and vulnerability in the NEUS, especially in a changing climate, is economically and culturally important yet remains difficult due to human impacts (i.e. fire suppression activities and human disturbance). Thus, an alternative method for investigating fire risk in the NEUS is needed. Here, we present a compilation of meteorological data collected from Automated Surface Observing Systems (ASOS) from the NEUS throughout the 20th century through present day. We use these data to compute fifteen common "fire danger indices" employed in the USA and Canada to investigate changes in the region's fire risk over time, as well as the skill of each of these indices at predicting wildfire activity relative to the historical record of fires in the NEUS. We use dynamically-downscaled regional climate model output for the 21st century to project future wildfire activity based on the fire danger indices capable of capturing historical fire activity in the NEUS. These projections will aid in predicting how fire risk in the NEUS will evolve with anticipated climate change.

Coherent activity between brain regions that code for value is linked to the malleability of human behavior

PubMed Central

Cooper, Nicole; Bassett, Danielle S.; Falk, Emily B.

2017-01-01

Brain activity in medial prefrontal cortex (MPFC) during exposure to persuasive messages can predict health behavior change. This brain-behavior relationship has been linked to areas of MPFC previously associated with self-related processing; however, the mechanism underlying this relationship is unclear. We explore two components of self-related processing – self-reflection and subjective valuation – and examine coherent activity between relevant networks of brain regions during exposure to health messages encouraging exercise and discouraging sedentary behaviors. We find that objectively logged reductions in sedentary behavior in the following month are linked to functional connectivity within brain regions associated with positive valuation, but not within regions associated with self-reflection on personality traits. Furthermore, functional connectivity between valuation regions contributes additional information compared to average brain activation within single brain regions. These data support an account in which MPFC integrates the value of messages to the self during persuasive health messaging and speak to broader questions of how humans make decisions about how to behave. PMID:28240271

Characteristics of voxel prediction power in full-brain Granger causality analysis of fMRI data

NASA Astrophysics Data System (ADS)

Garg, Rahul; Cecchi, Guillermo A.; Rao, A. Ravishankar

2011-03-01

Functional neuroimaging research is moving from the study of "activations" to the study of "interactions" among brain regions. Granger causality analysis provides a powerful technique to model spatio-temporal interactions among brain regions. We apply this technique to full-brain fMRI data without aggregating any voxel data into regions of interest (ROIs). We circumvent the problem of dimensionality using sparse regression from machine learning. On a simple finger-tapping experiment we found that (1) a small number of voxels in the brain have very high prediction power, explaining the future time course of other voxels in the brain; (2) these voxels occur in small sized clusters (of size 1-4 voxels) distributed throughout the brain; (3) albeit small, these clusters overlap with most of the clusters identified with the non-temporal General Linear Model (GLM); and (4) the method identifies clusters which, while not determined by the task and not detectable by GLM, still influence brain activity.

Right Lateral Cerebellum Represents Linguistic Predictability.

PubMed

Lesage, Elise; Hansen, Peter C; Miall, R Chris

2017-06-28

Mounting evidence indicates that posterolateral portions of the cerebellum (right Crus I/II) contribute to language processing, but the nature of this role remains unclear. Based on a well-supported theory of cerebellar motor function, which ascribes to the cerebellum a role in short-term prediction through internal modeling, we hypothesize that right cerebellar Crus I/II supports prediction of upcoming sentence content. We tested this hypothesis using event-related fMRI in male and female human subjects by manipulating the predictability of written sentences. Our design controlled for motor planning and execution, as well as for linguistic features and working memory load; it also allowed separation of the prediction interval from the presentation of the final sentence item. In addition, three further fMRI tasks captured semantic, phonological, and orthographic processing to shed light on the nature of the information processed. As hypothesized, activity in right posterolateral cerebellum correlated with the predictability of the upcoming target word. This cerebellar region also responded to prediction error during the outcome of the trial. Further, this region was engaged in phonological, but not semantic or orthographic, processing. This is the first imaging study to demonstrate a right cerebellar contribution in language comprehension independently from motor, cognitive, and linguistic confounds. These results complement our work using other methodologies showing cerebellar engagement in linguistic prediction and suggest that internal modeling of phonological representations aids language production and comprehension. SIGNIFICANCE STATEMENT The cerebellum is traditionally seen as a motor structure that allows for smooth movement by predicting upcoming signals. However, the cerebellum is also consistently implicated in nonmotor functions such as language and working memory. Using fMRI, we identify a cerebellar area that is active when words are predicted and when these predictions are violated. This area is active in a separate task that requires phonological processing, but not in tasks that require semantic or visuospatial processing. Our results support the idea of prediction as a unifying cerebellar function in motor and nonmotor domains. We provide new insights by linking the cerebellar role in prediction to its role in verbal working memory, suggesting that these predictions involve phonological processing. Copyright © 2017 Lesage et al.

The Great "Non-Event" of 7 January 2014: Challenges in CME Arrival Time and Geomagnetic Storm Strength Prediction

NASA Astrophysics Data System (ADS)

Mays, M. L.; Thompson, B. J.; Jian, L.; Evans, R. M.; Savani, N.; Odstrcil, D.; Nieves-Chinchilla, T.; Richardson, I. G.

2014-12-01

We present a case study of the 7 January 2014 event in order to highlight current challenges in space weather forecasting of CME arrival time and geomagnetic storm strength. On 7 January 2014 an X1.2 flare and CME with a radial speed ~2400 km/s was observed from active region 11943. The flaring region was only ten degrees southwest of disk center with extensive dimming south of the active region and preliminary analysis indicated a fairly rapid arrival at Earth (~36 hours). Of the eleven forecasting groups world-wide who participated in CCMC's Space Weather Scoreboard (http://kauai.ccmc.gsfc.nasa.gov/SWScoreBoard), nine predicted early arrivals and six predicted dramatic geomagnetic storm impacts (Kp predictions ranged from 6 to 9). However, the CME only had a glancing blow arrival at Earth - Kp did not rise above 3 and there was no geomagnetic storm. What happened? One idea is that the large coronal hole to the northeast of the active region could have deflected the CME. This coronal hole produced a high speed stream near Earth reaching an uncommon speed of 900 km/s four days after the observed CME arrival. However, no clear CME deflection was observed in the outer coronagraph fields of view (~5-20Rs) where CME measurements are derived to initiate models, therefore deflection seems unlikely. Another idea is the effect of the CME flux rope orientation with respect to Earth orbit. We show that using elliptical major and minor axis widths obtained by GCS fitting for the initial CME parameters in ENLIL would have improved the forecast to better reflect the observed glancing blow in-situ signature. We also explore the WSA-ENLIL+Cone simulations, the background solar wind solution, and compare with the observed CME arrival at Venus (from Venus Express) and Earth.

Ross River virus and Barmah Forest virus infections: a review of history, ecology, and predictive models, with implications for tropical northern Australia.

PubMed

Jacups, Susan P; Whelan, Peter I; Currie, Bart J

2008-04-01

The purpose of the present article is to present a review of the Ross River virus (RRV) and Barmah Forest virus (BFV) literature in relation to potential implications for future disease in tropical northern Australia. Ross River virus infection is the most common and most widespread arboviral disease in Australia, with an average of 4,800 national notifications annually. Of recent concern is the sudden rise in BFV infections; the 2005-2006 summer marked the largest BFV epidemic on record in Australia, with 1,895 notifications. Although not life-threatening, infection with either virus can cause arthritis, myalgia, and fatigue for 6 months or longer, resulting in substantial morbidity and economic impact. The geographic distribution of mosquito species and their seasonal activity is determined in large part by temperature and rainfall. Predictive models can be useful tools in providing early warning systems for epidemics of RRV and BFV infection. Various models have been developed to predict RRV outbreaks, but these appear to be mostly only regionally valid, being dependent on local ecological factors. Difficulties have arisen in developing useful models for the tropical northern parts of Australia, and to date no models have been developed for the Northern Territory. Only one model has been developed for predicting BFV infections using climate and tide variables. It is predicted that the exacerbation of current greenhouse conditions will result in longer periods of high mosquito activity in the tropical regions where RRV and BFV are already common. In addition, the endemic locations may expand further within temperate regions, and epidemics may become more frequent in those areas. Further development of predictive models should benefit public health planning by providing early warning systems of RRV and BFV infection outbreaks in different geographical locations.

Analysis of the dimensional dependence of semiconductor optical amplifier recovery speeds

NASA Astrophysics Data System (ADS)

Giller, Robin; Manning, Robert J.; Talli, Giuseppe; Webb, Roderick P.; Adams, Michael J.

2007-02-01

We investigate the dependence of the speed of recovery of optically excited semiconductor optical amplifiers (SOAs) on the active region dimensions. We use a picosecond pump-probe arrangement to experimentally measure and compare the gain and phase dynamics of four SOAs with varying active region dimensions. A sophisticated time domain SOA model incorporating amplified spontaneous emission (ASE) agrees well with the measurements and shows that, in the absence of a continuous wave (CW) beam, the ASE plays a similar role to such a holding beam. The experimental results are shown to be consistent with a recovery rate which is inversely proportional to the optical area. A significant speed increase is predicted for an appropriate choice of active region dimensions.

Applying Mondrian Cross-Conformal Prediction To Estimate Prediction Confidence on Large Imbalanced Bioactivity Data Sets.

PubMed

Sun, Jiangming; Carlsson, Lars; Ahlberg, Ernst; Norinder, Ulf; Engkvist, Ola; Chen, Hongming

2017-07-24

Conformal prediction has been proposed as a more rigorous way to define prediction confidence compared to other application domain concepts that have earlier been used for QSAR modeling. One main advantage of such a method is that it provides a prediction region potentially with multiple predicted labels, which contrasts to the single valued (regression) or single label (classification) output predictions by standard QSAR modeling algorithms. Standard conformal prediction might not be suitable for imbalanced data sets. Therefore, Mondrian cross-conformal prediction (MCCP) which combines the Mondrian inductive conformal prediction with cross-fold calibration sets has been introduced. In this study, the MCCP method was applied to 18 publicly available data sets that have various imbalance levels varying from 1:10 to 1:1000 (ratio of active/inactive compounds). Our results show that MCCP in general performed well on bioactivity data sets with various imbalance levels. More importantly, the method not only provides confidence of prediction and prediction regions compared to standard machine learning methods but also produces valid predictions for the minority class. In addition, a compound similarity based nonconformity measure was investigated. Our results demonstrate that although it gives valid predictions, its efficiency is much worse than that of model dependent metrics.

Functional brain imaging predicts public health campaign success

PubMed Central

O’Donnell, Matthew Brook; Tompson, Steven; Gonzalez, Richard; Dal Cin, Sonya; Strecher, Victor; Cummings, Kenneth Michael; An, Lawrence

2016-01-01

Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a ‘self-localizer’ defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400 000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R2 up to 0.65) and (ii) this relationship depends on message content—self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns. PMID:26400858

Understanding Human Original Actions Directed at Real-World Goals: The Role of the Lateral Prefrontal Cortex

PubMed Central

Sitnikova, Tatiana; Rosen, Bruce R.; Lord, Louis-David; West, W. Caroline

2014-01-01

Adaptive, original actions, which can succeed in multiple contextual situations, require understanding of what is relevant to a goal. Recognizing what is relevant may also help in predicting kinematics of observed, original actions. During action observation, comparisons between sensory input and expected action kinematics have been argued critical to accurate goal inference. Experimental studies with laboratory tasks, both in humans and nonhuman primates, demonstrated that the lateral prefrontal cortex (LPFC) can learn, hierarchically organize, and use goal-relevant information. To determine whether this LPFC capacity is generalizable to real-world cognition, we recorded functional magnetic resonance imaging (fMRI) data in the human brain during comprehension of original and usual object-directed actions embedded in video-depictions of real-life behaviors. We hypothesized that LPFC will contribute to forming goal-relevant representations necessary for kinematic predictions of original actions. Additionally, resting-state fMRI was employed to examine functional connectivity between the brain regions delineated in the video fMRI experiment. According to behavioral data, original videos could be understood by identifying elements relevant to real-life goals at different levels of abstraction. Patterns of enhanced activity in four regions in the left LPFC, evoked by original, relative to usual, video scenes, were consistent with previous neuroimaging findings on representing abstract and concrete stimuli dimensions relevant to laboratory goals. In the anterior left LPFC, the activity increased selectively when representations of broad classes of objects and actions, which could achieve the perceived overall behavioral goal, were likely to bias kinematic predictions of original actions. In contrast, in the more posterior regions, the activity increased even when concrete properties of the target object were more likely to bias the kinematic prediction. Functional connectivity was observed between contiguous regions along the rostro-caudal LPFC axis, but not between the regions that were not immediately adjacent. These findings generalize the representational hierarchy account of LPFC function to diverse core principles that can govern both production and comprehension of flexible real-life behavior. PMID:25224997

NDVI-Based analysis on the influence of human activities on vegetation variation on Hainan Island

NASA Astrophysics Data System (ADS)

Luo, Hongxia; Dai, Shengpei; Xie, Zhenghui; Fang, Jihua

2018-02-01

Using the Moderate Resolution Imaging Spectroradiometer-normalized difference vegetation index (NDVI) dataset, we analyzed the predicted NDVI values variation and the influence of human activities on vegetation on Hainan Island during 2001-2015. We investigated the roles of human activities in vegetation variation, particularly from 2002 when implemented the Grain-for-Greenprogram on Hainan Island. The trend analysis, linear regression model and residual analysis were used to analyze the data. The results of the study showed that (1) The predicted vegetation on Hainan Island showed an general upward trend with a linear growth rate of 0.0025/10y (p<0.05) over the past 15 years. The areas where vegetation increasedaccounted for 52.28%, while the areas where vegetation decreased accounted for 47.72%. (2) The residual NDVI values across the region significantly increased, with a growth rate of 0.023/10y.The vegetation increased across 35.95% of Hainan Island, while it decreased in 20.2% of the area as a result of human activities. (3) In general, human activities had played a positive role in the vegetation increase on Hainan Island, and the residual NDVI trend of this region showed positive outcomes for vegetation variation after implementing ecological engineering projects. However, it indicated a growing risk of vegetation degradation in the coastal region of Hainan Island as a result of rapid urbanization, land reclamation.

Contextual Processing of Abstract Concepts Reveals Neural Representations of Non-Linguistic Semantic Content

PubMed Central

Wilson-Mendenhall, Christine D.; Simmons, W. Kyle; Martin, Alex; Barsalou, Lawrence W.

2014-01-01

Concepts develop for many aspects of experience, including abstract internal states and abstract social activities that do not refer to concrete entities in the world. The current study assessed the hypothesis that, like concrete concepts, distributed neural patterns of relevant, non-linguistic semantic content represent the meanings of abstract concepts. In a novel neuroimaging paradigm, participants processed two abstract concepts (convince, arithmetic) and two concrete concepts (rolling, red) deeply and repeatedly during a concept-scene matching task that grounded each concept in typical contexts. Using a catch trial design, neural activity associated with each concept word was separated from neural activity associated with subsequent visual scenes to assess activations underlying the detailed semantics of each concept. We predicted that brain regions underlying mentalizing and social cognition (e.g., medial prefrontal cortex, superior temporal sulcus) would become active to represent semantic content central to convince, whereas brain regions underlying numerical cognition (e.g., bilateral intraparietal sulcus) would become active to represent semantic content central to arithmetic. The results supported these predictions, suggesting that the meanings of abstract concepts arise from distributed neural systems that represent concept-specific content. PMID:23363408

Context Memory Decline in Middle Aged Adults is Related to Changes in Prefrontal Cortex Function

PubMed Central

Kwon, Diana; Maillet, David; Pasvanis, Stamatoula; Ankudowich, Elizabeth; Grady, Cheryl L.; Rajah, M. Natasha

2016-01-01

The ability to encode and retrieve spatial and temporal contextual details of episodic memories (context memory) begins to decline at midlife. In the current study, event-related fMRI was used to investigate the neural correlates of context memory decline in healthy middle aged adults (MA) compared with young adults (YA). Participants were scanned while performing easy and hard versions of spatial and temporal context memory tasks. Scans were obtained at encoding and retrieval. Significant reductions in context memory retrieval accuracy were observed in MA, compared with YA. The fMRI results revealed that overall, both groups exhibited similar patterns of brain activity in parahippocampal cortex, ventral occipito-temporal regions and prefrontal cortex (PFC) during encoding. In contrast, at retrieval, there were group differences in ventral occipito-temporal and PFC activity, due to these regions being more activated in MA, compared with YA. Furthermore, only in YA, increased encoding activity in ventrolateral PFC, and increased retrieval activity in occipital cortex, predicted increased retrieval accuracy. In MA, increased retrieval activity in anterior PFC predicted increased retrieval accuracy. These results suggest that there are changes in PFC contributions to context memory at midlife. PMID:25882039

Neural correlates of the happy life: the amplitude of spontaneous low frequency fluctuations predicts subjective well-being.

PubMed

Kong, Feng; Hu, Siyuan; Wang, Xu; Song, Yiying; Liu, Jia

2015-02-15

Subjective well-being is assumed to be distributed in the hedonic hotspots of subcortical and cortical structures. However, the precise neural correlates underlying this construct, especially how it is maintained during the resting state, are still largely unknown. Here, we explored the neural basis of subjective well-being by correlating the regional fractional amplitude of low frequency fluctuations (fALFF) with the self-reported subjective well-being of healthy individuals. Behaviorally, we demonstrated that subjective well-being contained two related but distinct components: cognitive and affective well-being. Neurally, we showed that the fALFF in the bilateral posterior superior temporal gyrus (pSTG), right posterior mid-cingulate cortex (pMCC), right thalamus, left postcentral gyrus (PCG), right lingual gyrus, and left planum temporale (PT) positively predicted cognitive well-being, whereas the fALFF in the bilateral superior frontal gyrus (SFG), right orbitofrontal cortex (OFC), and left inferior temporal gyrus (ITG) negatively predicted cognitive well-being. In contrast, only the fALFF in the right amygdala reliably predicted affective well-being. Furthermore, emotional intelligence partially mediated the effects of the right pSTG and thalamus on cognitive well-being, as well as the effect of the right amygdala on affective well-being. In summary, we provide the first evidence that spontaneous brain activity in multiple regions associated with sensation, social perception, cognition, and emotion contributes to cognitive well-being, whereas the spontaneous brain activity in only one emotion-related region contributes to affective well-being, suggesting that the spontaneous activity of the human brain reflect the efficiency of subjective well-being. Copyright © 2014 Elsevier Inc. All rights reserved.

Specificity of regional brain activity in anxiety types during emotion processing.

PubMed

Engels, Anna S; Heller, Wendy; Mohanty, Aprajita; Herrington, John D; Banich, Marie T; Webb, Andrew G; Miller, Gregory A

2007-05-01

The present study tested the hypothesis that anxious apprehension involves more left- than right-hemisphere activity and that anxious arousal is associated with the opposite pattern. Behavioral and fMRI responses to threat stimuli in an emotional Stroop task were examined in nonpatient groups reporting anxious apprehension, anxious arousal, or neither. Reaction times were longer for negative than for neutral words. As predicted, brain activation distinguished anxious groups in a left inferior frontal region associated with speech production and in a right-hemisphere inferior temporal area. Addressing a second hypothesis about left-frontal involvement in emotion, distinct left frontal regions were associated with anxious apprehension versus processing of positive information. Results support the proposed distinction between the two types of anxiety and resolve an inconsistency about the role of left-frontal activation in emotion and psychopathology.

Projecting the past and future impacts of hurricanes on the carbon balance of eastern U.S. forests (1851-2100)

NASA Astrophysics Data System (ADS)

Fisk, J.; Hurtt, G. C.; Chambers, J. Q.; Zeng, H.

2009-12-01

In U.S. Atlantic coastal areas, hurricanes are a principal agent of catastrophic wind damage, with dramatic impacts on the structure and functioning of forests. Estimates of the carbon emissions resulting from single storms range as high as ~100 Tg C, an amount equivalent to the annual U.S. carbon sink in forest trees. Recent studies have estimated the historic regional carbon emissions from hurricane activity using an empirically based approach. Here, we use a mechanistic ecosystem model, the Ecosystem Demography (ED) model, driven by maps of mortality and damage based on historic hurricane tracks and future scenarios to predict the past and future impacts of hurricanes on the carbon balance of eastern U.S. forests. Model estimates compare well to previous empirically based estimates, with mean annual biomass loss of 26 Tg C yr-1 (range 0 to ~225 Tg C yr-1) resulting from hurricanes during the period 1851-2000. Using the mechanistic model, we are able to include the effects of both disturbance and recovery on the net carbon flux. We find a regional carbon sink throughout much of the 20th century resulting from forest recovery following a peak in hurricane activity during the late 19th century exceeding biomass loss. Recent increased hurricane activity has resulted in the region becoming a net carbon source. For the future, several recent studies have linked increased sea surface temperatures expected with climate change to increased hurricane activity. Based on these relationships, we investigate a range of scenarios of future hurricane activity and find the potential for substantial increases in emissions from hurricane mortality and reductions in regional carbon stocks. In our scenario with the largest increase in hurricane activity, we find a 35% increase in area disturbed by 2100, but due to the reduction of standing biomass, only a 20% increase in biomass loss per year. Developing this kind of predictive modeling capability that tracks disturbance events and recovery is key to our understanding and ability to predict the carbon balance of forests of the eastern U.S.

Deep learning of the regulatory grammar of yeast 5′ untranslated regions from 500,000 random sequences

PubMed Central

Groves, Benjamin; Kuchina, Anna; Rosenberg, Alexander B.; Jojic, Nebojsa; Fields, Stanley; Seelig, Georg

2017-01-01

Our ability to predict protein expression from DNA sequence alone remains poor, reflecting our limited understanding of cis-regulatory grammar and hampering the design of engineered genes for synthetic biology applications. Here, we generate a model that predicts the protein expression of the 5′ untranslated region (UTR) of mRNAs in the yeast Saccharomyces cerevisiae. We constructed a library of half a million 50-nucleotide-long random 5′ UTRs and assayed their activity in a massively parallel growth selection experiment. The resulting data allow us to quantify the impact on protein expression of Kozak sequence composition, upstream open reading frames (uORFs), and secondary structure. We trained a convolutional neural network (CNN) on the random library and showed that it performs well at predicting the protein expression of both a held-out set of the random 5′ UTRs as well as native S. cerevisiae 5′ UTRs. The model additionally was used to computationally evolve highly active 5′ UTRs. We confirmed experimentally that the great majority of the evolved sequences led to higher protein expression rates than the starting sequences, demonstrating the predictive power of this model. PMID:29097404

Estimation of Source and Attenuation Parameters from Ground Motion Observations for Induced Seismicity in Alberta

NASA Astrophysics Data System (ADS)

Novakovic, M.; Atkinson, G. M.

2015-12-01

We use a generalized inversion to solve for site response, regional source and attenuation parameters, in order to define a region-specific ground-motion prediction equation (GMPE) from ground motion observations in Alberta, following the method of Atkinson et al. (2015 BSSA). The database is compiled from over 200 small to moderate seismic events (M 1 to 4.2) recorded at ~50 regional stations (distances from 30 to 500 km), over the last few years; almost all of the events have been identified as being induced by oil and gas activity. We remove magnitude scaling and geometric spreading functions from observed ground motions and invert for stress parameter, regional attenuation and site amplification. Resolving these parameters allows for the derivation of a regionally-calibrated GMPE that can be used to accurately predict amplitudes across the region in real time, which is useful for ground-motion-based alerting systems and traffic light protocols. The derived GMPE has further applications for the evaluation of hazards from induced seismicity.

Audience preferences are predicted by temporal reliability of neural processing

PubMed Central

Dmochowski, Jacek P.; Bezdek, Matthew A.; Abelson, Brian P.; Johnson, John S.; Schumacher, Eric H.; Parra, Lucas C.

2014-01-01

Naturalistic stimuli evoke highly reliable brain activity across viewers. Here we record neural activity from a group of naive individuals while viewing popular, previously-broadcast television content for which the broad audience response is characterized by social media activity and audience ratings. We find that the level of inter-subject correlation in the evoked encephalographic responses predicts the expressions of interest and preference among thousands. Surprisingly, ratings of the larger audience are predicted with greater accuracy than those of the individuals from whom the neural data is obtained. An additional functional magnetic resonance imaging study employing a separate sample of subjects shows that the level of neural reliability evoked by these stimuli covaries with the amount of blood-oxygenation-level-dependent (BOLD) activation in higher-order visual and auditory regions. Our findings suggest that stimuli which we judge favourably may be those to which our brains respond in a stereotypical manner shared by our peers. PMID:25072833

Audience preferences are predicted by temporal reliability of neural processing.

PubMed

Dmochowski, Jacek P; Bezdek, Matthew A; Abelson, Brian P; Johnson, John S; Schumacher, Eric H; Parra, Lucas C

2014-07-29

Naturalistic stimuli evoke highly reliable brain activity across viewers. Here we record neural activity from a group of naive individuals while viewing popular, previously-broadcast television content for which the broad audience response is characterized by social media activity and audience ratings. We find that the level of inter-subject correlation in the evoked encephalographic responses predicts the expressions of interest and preference among thousands. Surprisingly, ratings of the larger audience are predicted with greater accuracy than those of the individuals from whom the neural data is obtained. An additional functional magnetic resonance imaging study employing a separate sample of subjects shows that the level of neural reliability evoked by these stimuli covaries with the amount of blood-oxygenation-level-dependent (BOLD) activation in higher-order visual and auditory regions. Our findings suggest that stimuli which we judge favourably may be those to which our brains respond in a stereotypical manner shared by our peers.

Reinforcement Learning Models and Their Neural Correlates: An Activation Likelihood Estimation Meta-Analysis

PubMed Central

Kumar, Poornima; Eickhoff, Simon B.; Dombrovski, Alexandre Y.

2015-01-01

Reinforcement learning describes motivated behavior in terms of two abstract signals. The representation of discrepancies between expected and actual rewards/punishments – prediction error – is thought to update the expected value of actions and predictive stimuli. Electrophysiological and lesion studies suggest that mesostriatal prediction error signals control behavior through synaptic modification of cortico-striato-thalamic networks. Signals in the ventromedial prefrontal and orbitofrontal cortex are implicated in representing expected value. To obtain unbiased maps of these representations in the human brain, we performed a meta-analysis of functional magnetic resonance imaging studies that employed algorithmic reinforcement learning models, across a variety of experimental paradigms. We found that the ventral striatum (medial and lateral) and midbrain/thalamus represented reward prediction errors, consistent with animal studies. Prediction error signals were also seen in the frontal operculum/insula, particularly for social rewards. In Pavlovian studies, striatal prediction error signals extended into the amygdala, while instrumental tasks engaged the caudate. Prediction error maps were sensitive to the model-fitting procedure (fixed or individually-estimated) and to the extent of spatial smoothing. A correlate of expected value was found in a posterior region of the ventromedial prefrontal cortex, caudal and medial to the orbitofrontal regions identified in animal studies. These findings highlight a reproducible motif of reinforcement learning in the cortico-striatal loops and identify methodological dimensions that may influence the reproducibility of activation patterns across studies. PMID:25665667

What is the Best Model Specification and Earth Observation Product for Predicting Regional Grain Yields in Food Insecure Countries?

NASA Astrophysics Data System (ADS)

Davenport, F., IV; Harrison, L.; Shukla, S.; Husak, G. J.; Funk, C. C.

2017-12-01

We evaluate the predictive accuracy of an ensemble of empirical model specifications that use earth observation data to predict sub-national grain yields in Mexico and East Africa. Products that are actively used for seasonal drought monitoring are tested as yield predictors. Our research is driven by the fact that East Africa is a region where decisions regarding agricultural production are critical to preventing the loss of economic livelihoods and human life. Regional grain yield forecasts can be used to anticipate availability and prices of key staples, which can turn can inform decisions about targeting humanitarian response such as food aid. Our objective is to identify-for a given region, grain, and time year- what type of model and/or earth observation can most accurately predict end of season yields. We fit a set of models to county level panel data from Mexico, Kenya, Sudan, South Sudan, and Somalia. We then examine out of sample predicative accuracy using various linear and non-linear models that incorporate spatial and time varying coefficients. We compare accuracy within and across models that use predictor variables from remotely sensed measures of precipitation, temperature, soil moisture, and other land surface processes. We also examine at what point in the season a given model or product is most useful for determining predictive accuracy. Finally we compare predictive accuracy across a variety of agricultural regimes including high intensity irrigated commercial agricultural and rain fed subsistence level farms.

Genome-wide prediction of cis-regulatory regions using supervised deep learning methods.

PubMed

Li, Yifeng; Shi, Wenqiang; Wasserman, Wyeth W

2018-05-31

In the human genome, 98% of DNA sequences are non-protein-coding regions that were previously disregarded as junk DNA. In fact, non-coding regions host a variety of cis-regulatory regions which precisely control the expression of genes. Thus, Identifying active cis-regulatory regions in the human genome is critical for understanding gene regulation and assessing the impact of genetic variation on phenotype. The developments of high-throughput sequencing and machine learning technologies make it possible to predict cis-regulatory regions genome wide. Based on rich data resources such as the Encyclopedia of DNA Elements (ENCODE) and the Functional Annotation of the Mammalian Genome (FANTOM) projects, we introduce DECRES based on supervised deep learning approaches for the identification of enhancer and promoter regions in the human genome. Due to their ability to discover patterns in large and complex data, the introduction of deep learning methods enables a significant advance in our knowledge of the genomic locations of cis-regulatory regions. Using models for well-characterized cell lines, we identify key experimental features that contribute to the predictive performance. Applying DECRES, we delineate locations of 300,000 candidate enhancers genome wide (6.8% of the genome, of which 40,000 are supported by bidirectional transcription data), and 26,000 candidate promoters (0.6% of the genome). The predicted annotations of cis-regulatory regions will provide broad utility for genome interpretation from functional genomics to clinical applications. The DECRES model demonstrates potentials of deep learning technologies when combined with high-throughput sequencing data, and inspires the development of other advanced neural network models for further improvement of genome annotations.

Spontaneous cortical activity alternates between motifs defined by regional axonal projections

PubMed Central

Mohajerani, Majid H.; Chan, Allen W.; Mohsenvand, Mostafa; LeDue, Jeffrey; Liu, Rui; McVea, David A.; Boyd, Jamie D.; Wang, Yu Tian; Reimers, Mark; Murphy, Timothy H.

2014-01-01

In lightly anaesthetized or awake adult mice using millisecond timescale voltage sensitive dye imaging, we show that a palette of sensory-evoked and hemisphere-wide activity motifs are represented in spontaneous activity. These motifs can reflect multiple modes of sensory processing including vision, audition, and touch. Similar cortical networks were found with direct cortical activation using channelrhodopsin-2. Regional analysis of activity spread indicated modality specific sources such as primary sensory areas, and a common posterior-medial cortical sink where sensory activity was extinguished within the parietal association area, and a secondary anterior medial sink within the cingulate/secondary motor cortices for visual stimuli. Correlation analysis between functional circuits and intracortical axonal projections indicated a common framework corresponding to long-range mono-synaptic connections between cortical regions. Maps of intracortical mono-synaptic structural connections predicted hemisphere-wide patterns of spontaneous and sensory-evoked depolarization. We suggest that an intracortical monosynaptic connectome shapes the ebb and flow of spontaneous cortical activity. PMID:23974708

An fMRI investigation of the relationship between future imagination and cognitive flexibility

PubMed Central

Roberts, R.P.; Wiebels, K.; Sumner, R.L.; van Mulukom, V.; Grady, C.L.; Schacter, D.L.; Addis, D.R.

2016-01-01

While future imagination is largely considered to be a cognitive process grounded in default mode network activity, studies have shown that future imagination recruits regions in both default mode and frontoparietal control networks. In addition, it has recently been shown that the ability to imagine the future is associated with cognitive flexibility, and that tasks requiring cognitive flexibility result in increased coupling of the default mode network with frontoparietal control and salience networks. In the current study, we investigated the neural correlates underlying the association between cognitive flexibility and future imagination in two ways. First, we experimentally varied the degree of cognitive flexibility required during future imagination by manipulating the disparateness of episodic details contributing to imagined events. To this end, participants generated episodic details (persons, locations, objects) within three social spheres; during fMRI scanning they were presented with sets of three episodic details all taken from the same social sphere (Congruent condition) or different social spheres (Incongruent condition) and required to imagine a future event involving the three details. We predicted that, relative to the Congruent condition, future simulation in the Incongruent condition would be associated with increased activity in regions of the default mode, frontoparietal and salience networks. Second, we hypothesized that individual differences in cognitive flexibility, as measured by performance on the Alternate Uses Task, would correspond to individual differences in the brain regions recruited during future imagination. A task partial least squares (PLS) analysis showed that the Incongruent condition resulted in an increase in activity in regions in salience networks (e.g. the insula) but, contrary to our prediction, reduced activity in many regions of the default mode network (including the hippocampus). A subsequent functional connectivity (within-subject seed PLS) analysis showed that the insula exhibited increased coupling with default mode regions during the Incongruent condition. Finally, a behavioral PLS analysis showed that individual differences in cognitive flexibility were associated with differences in activity in a number of regions from frontoparietal, salience and default-mode networks during both future imagination conditions, further highlighting that the cognitive flexibility underlying future imagination is grounded in the complex interaction of regions in these networks. PMID:27908591

Seasonal prediction of lightning activity in North Western Venezuela: Large-scale versus local drivers

NASA Astrophysics Data System (ADS)

Muñoz, Á. G.; Díaz-Lobatón, J.; Chourio, X.; Stock, M. J.

2016-05-01

The Lake Maracaibo Basin in North Western Venezuela has the highest annual lightning rate of any place in the world (~ 200 fl km- 2 yr- 1), whose electrical discharges occasionally impact human and animal lives (e.g., cattle) and frequently affect economic activities like oil and natural gas exploitation. Lightning activity is so common in this region that it has a proper name: Catatumbo Lightning (plural). Although short-term lightning forecasts are now common in different parts of the world, to the best of the authors' knowledge, seasonal prediction of lightning activity is still non-existent. This research discusses the relative role of both large-scale and local climate drivers as modulators of lightning activity in the region, and presents a formal predictability study at seasonal scale. Analysis of the Catatumbo Lightning Regional Mode, defined in terms of the second Empirical Orthogonal Function of monthly Lightning Imaging Sensor (LIS-TRMM) and Optical Transient Detector (OTD) satellite data for North Western South America, permits the identification of potential predictors at seasonal scale via a Canonical Correlation Analysis. Lightning activity in North Western Venezuela responds to well defined sea-surface temperature patterns (e.g., El Niño-Southern Oscillation, Atlantic Meridional Mode) and changes in the low-level meridional wind field that are associated with the Inter-Tropical Convergence Zone migrations, the Caribbean Low Level Jet and tropical cyclone activity, but it is also linked to local drivers like convection triggered by the topographic configuration and the effect of the Maracaibo Basin Nocturnal Low Level Jet. The analysis indicates that at seasonal scale the relative contribution of the large-scale drivers is more important than the local (basin-wide) ones, due to the synoptic control imposed by the former. Furthermore, meridional CAPE transport at 925 mb is identified as the best potential predictor for lightning activity in the Lake Maracaibo Basin. It is found that the predictive skill is slightly higher for the minimum lightning season (Jan-Feb) than for the maximum one (Sep-Oct), but that in general the skill is high enough to be useful for decision-making processes related to human safety, oil and natural gas exploitation, energy and food security.

Functional connections between activated and deactivated brain regions mediate emotional interference during externally directed cognition.

PubMed

Di Plinio, Simone; Ferri, Francesca; Marzetti, Laura; Romani, Gian Luca; Northoff, Georg; Pizzella, Vittorio

2018-04-24

Recent evidence shows that task-deactivations are functionally relevant for cognitive performance. Indeed, higher cognitive engagement has been associated with higher suppression of activity in task-deactivated brain regions - usually ascribed to the Default Mode Network (DMN). Moreover, a negative correlation between these regions and areas actively engaged by the task is associated with better performance. DMN regions show positive modulation during autobiographical, social, and emotional tasks. However, it is not clear how processing of emotional stimuli affects the interplay between the DMN and executive brain regions. We studied this interplay in an fMRI experiment using emotional negative stimuli as distractors. Activity modulations induced by the emotional interference of negative stimuli were found in frontal, parietal, and visual areas, and were associated with modulations of functional connectivity between these task-activated areas and DMN regions. A worse performance was predicted both by lower activity in the superior parietal cortex and higher connectivity between visual areas and frontal DMN regions. Connectivity between right inferior frontal gyrus and several DMN regions in the left hemisphere was related to the behavioral performance. This relation was weaker in the negative than in the neutral condition, likely suggesting less functional inhibitions of DMN regions during emotional processing. These results show that both executive and DMN regions are crucial for the emotional interference process and suggest that DMN connections are related to the interplay between externally-directed and internally-focused processes. Among DMN regions, superior frontal gyrus may be a key node in regulating the interference triggered by emotional stimuli. © 2018 Wiley Periodicals, Inc.

Top-down controlled alpha band activity in somatosensory areas determines behavioral performance in a discrimination task.

PubMed

Haegens, Saskia; Händel, Barbara F; Jensen, Ole

2011-04-06

The brain receives a rich flow of information which must be processed according to behavioral relevance. How is the state of the sensory system adjusted to up- or downregulate processing according to anticipation? We used magnetoencephalography to investigate whether prestimulus alpha band activity (8-14 Hz) reflects allocation of attentional resources in the human somatosensory system. Subjects performed a tactile discrimination task where a visual cue directed attention to their right or left hand. The strength of attentional modulation was controlled by varying the reliability of the cue in three experimental blocks (100%, 75%, or 50% valid cueing). While somatosensory prestimulus alpha power lateralized strongly with a fully predictive cue (100%), lateralization was decreased with lower cue reliability (75%) and virtually absent if the cue had no predictive value at all (50%). Importantly, alpha lateralization influenced the subjects' behavioral performance positively: both accuracy and speed of response improved with the degree of alpha lateralization. This study demonstrates that prestimulus alpha lateralization in the somatosensory system behaves similarly to posterior alpha activity observed in visual attention tasks. Our findings extend the notion that alpha band activity is involved in shaping the functional architecture of the working brain by determining both the engagement and disengagement of specific regions: the degree of anticipation modulates the alpha activity in sensory regions in a graded manner. Thus, the alpha activity is under top-down control and seems to play an important role for setting the state of sensory regions to optimize processing.

Estimating direction in brain-behavior interactions: Proactive and reactive brain states in driving.

PubMed

Garcia, Javier O; Brooks, Justin; Kerick, Scott; Johnson, Tony; Mullen, Tim R; Vettel, Jean M

2017-04-15

Conventional neuroimaging analyses have ascribed function to particular brain regions, exploiting the power of the subtraction technique in fMRI and event-related potential analyses in EEG. Moving beyond this convention, many researchers have begun exploring network-based neurodynamics and coordination between brain regions as a function of behavioral parameters or environmental statistics; however, most approaches average evoked activity across the experimental session to study task-dependent networks. Here, we examined on-going oscillatory activity as measured with EEG and use a methodology to estimate directionality in brain-behavior interactions. After source reconstruction, activity within specific frequency bands (delta: 2-3Hz; theta: 4-7Hz; alpha: 8-12Hz; beta: 13-25Hz) in a priori regions of interest was linked to continuous behavioral measurements, and we used a predictive filtering scheme to estimate the asymmetry between brain-to-behavior and behavior-to-brain prediction using a variant of Granger causality. We applied this approach to a simulated driving task and examined directed relationships between brain activity and continuous driving performance (steering behavior or vehicle heading error). Our results indicated that two neuro-behavioral states may be explored with this methodology: a Proactive brain state that actively plans the response to the sensory information and is characterized by delta-beta activity, and a Reactive brain state that processes incoming information and reacts to environmental statistics primarily within the alpha band. Published by Elsevier Inc.

Neural Mechanisms of Grief Regulation

PubMed Central

Freed, Peter J.; Yanagihara, Ted K.; Hirsch, Joy; Mann, J. John

2009-01-01

Background: The death of an attachment figure triggers intrusive thoughts of the deceased, sadness, and yearning for reunion. Recovery requires reduction of symptoms. We hypothesized that symptoms might correlate with a capacity to regulate attention toward reminders of the deceased, and activity in, and functional connectivity between, prefrontal regulatory regions and the amygdala. Methods: Twenty recently bereaved subjects rated intrusive thoughts of the deceased versus a capacity to avoid thoughts (grief style). Reaction time was measured while subjects completed an Emotional Stroop (ES) task contrasting deceased-related with control words during functional magnetic resonance imaging (fMRI). Subjects subsequently visualized the death of the deceased and rated induced emotions. Results: Subjects demonstrated attentional bias toward deceased-related words. Bias magnitude correlated with amygdala, insula, dorsolateral prefrontal cortex (DLPFC) activity. Amygdala activity predicted induced sadness intensity. A double dissociation between grief style and both prefrontal and amygdala subregion activity was found. Intrusiveness correlated with activation of ventral amygdala and rostral anterior cingulate (rACC); avoidance correlated with deactivation of dorsal amygdala and DLPFC. A double dissociation between regulatory region and task-dependent functional connectivity (FC) was found. High DLPFC-amygdala FC correlated with reduced attentional bias, while low rACC-amygdala FC predicted sadness intensity. Conclusions: Results are consistent with a model in which activity in and functional connectivity between the amygdala and prefrontal regulatory regions indexes differences in mourners' regulation of attention and sadness during pangs of grief, and may be used to distinguish between clinically relevant differences in grief style. PMID:19249748

The future of soil invertebrate communities in polar regions: different climate change responses in the Arctic and Antarctic?

PubMed

Nielsen, Uffe N; Wall, Diana H

2013-03-01

The polar regions are experiencing rapid climate change with implications for terrestrial ecosystems. Here, despite limited knowledge, we make some early predictions on soil invertebrate community responses to predicted twenty-first century climate change. Geographic and environmental differences suggest that climate change responses will differ between the Arctic and Antarctic. We predict significant, but different, belowground community changes in both regions. This change will be driven mainly by vegetation type changes in the Arctic, while communities in Antarctica will respond to climate amelioration directly and indirectly through changes in microbial community composition and activity, and the development of, and/or changes in, plant communities. Climate amelioration is likely to allow a greater influx of non-native species into both the Arctic and Antarctic promoting landscape scale biodiversity change. Non-native competitive species could, however, have negative effects on local biodiversity particularly in the Arctic where the communities are already species rich. Species ranges will shift in both areas as the climate changes potentially posing a problem for endemic species in the Arctic where options for northward migration are limited. Greater soil biotic activity may move the Arctic towards a trajectory of being a substantial carbon source, while Antarctica could become a carbon sink. © 2013 Blackwell Publishing Ltd/CNRS.

Mesencephalic representations of recent experience influence decision making

PubMed Central

Thompson, John A; Costabile, Jamie D; Felsen, Gidon

2016-01-01

Decisions are influenced by recent experience, but the neural basis for this phenomenon is not well understood. Here, we address this question in the context of action selection. We focused on activity in the pedunculopontine tegmental nucleus (PPTg), a mesencephalic region that provides input to several nuclei in the action selection network, in well-trained mice selecting actions based on sensory cues and recent trial history. We found that, at the time of action selection, the activity of many PPTg neurons reflected the action on the previous trial and its outcome, and the strength of this activity predicted the upcoming choice. Further, inactivating the PPTg predictably decreased the influence of recent experience on action selection. These findings suggest that PPTg input to downstream motor regions, where it can be integrated with other relevant information, provides a simple mechanism for incorporating recent experience into the computations underlying action selection. DOI: http://dx.doi.org/10.7554/eLife.16572.001 PMID:27454033

A TEST OF THE FORMATION MECHANISM OF THE BROAD LINE REGION IN ACTIVE GALACTIC NUCLEI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Czerny, Bozena; Du, Pu; Wang, Jian-Min

2016-11-20

The origin of the broad line region (BLR) in active galaxies remains unknown. It seems to be related to the underlying accretion disk, but an efficient mechanism is required to raise the material from the disk surface without giving signatures of the outflow that are too strong in the case of the low ionization lines. We discuss in detail two proposed mechanisms: (1) radiation pressure acting on dust in the disk atmosphere creating a failed wind and (2) the gravitational instability of the underlying disk. We compare the predicted location of the inner radius of the BLR in those two scenarios withmore » the observed position obtained from the reverberation studies of several active galaxies. The failed dusty outflow model well represents the observational data while the predictions of the self-gravitational instability are not consistent with observations. The issue that remains is why do we not see any imprints of the underlying disk instability in the BLR properties.« less

Rapid prediction of phenolic compounds and antioxidant activity of Sudanese honey using Raman and Fourier transform infrared (FT-IR) spectroscopy.

PubMed

Tahir, Haroon Elrasheid; Xiaobo, Zou; Zhihua, Li; Jiyong, Shi; Zhai, Xiaodong; Wang, Sheng; Mariod, Abdalbasit Adam

2017-07-01

Fourier transform infrared with attenuated total reflectance (FTIR-ATR) and Raman spectroscopy combined with partial least square regression (PLSR) were applied for the prediction of phenolic compounds and antioxidant activity in honey. Standards of catechin, syringic, vanillic, and chlorogenic acids were used for the identification and quantification of the individual phenolic compounds in six honey varieties using HPLC-DAD. Total antioxidant activity (TAC) and ferrous chelating capacity were measured spectrophotometrically. For the establishment of PLSR model, Raman spectra with Savitzky-Golay smoothing in wavenumber region 1500-400cm -1 was used while for FTIR-ATR the wavenumber regions of 1800-700 and 3000-2800cm -1 with multiplicative scattering correction (MSC) and Savitzky-Golay smoothing were used. The determination coefficients (R 2 ) were ranged from 0.9272 to 0.9992 for Raman while from 0.9461 to 0.9988 for FTIT-ART. The FTIR-ATR and Raman demonstrated to be simple, rapid and nondestructive methods to quantify phenolic compounds and antioxidant activities in honey. Copyright © 2017 Elsevier Ltd. All rights reserved.

Functional imaging of semantic memory predicts postoperative episodic memory functions in chronic temporal lobe epilepsy.

PubMed

Köylü, Bülent; Walser, Gerald; Ischebeck, Anja; Ortler, Martin; Benke, Thomas

2008-08-05

Medial temporal (MTL) structures have crucial functions in episodic (EM), but also in semantic memory (SM) processing. Preoperative functional magnetic resonance imaging (fMRI) activity within the MTL is increasingly used to predict post-surgical memory capacities. Based on the hypothesis that EM and SM memory functions are both hosted by the MTL the present study wanted to explore the relationship between SM related activations in the MTL as assessed before and the capacity of EM functions after surgery. Patients with chronic unilateral left (n=14) and right (n=12) temporal lobe epilepsy (TLE) performed a standard word list learning test pre- and postoperatively, and a fMRI procedure before the operation using a semantic decision task. SM processing caused significant bilateral MTL activations in both patient groups. While right TLE patients showed asymmetry of fMRI activation with more activation in the left MTL, left TLE patients had almost equal activation in both MTL regions. Contrasting left TLE versus right TLE patients revealed greater activity within the right MTL, whereas no significant difference was observed for the reverse contrast. Greater effect size in the MTL region ipsilateral to the seizure focus was significantly and positively correlated with preoperative EM abilities. Greater effect size in the contralateral MTL was correlated with better postoperative verbal EM, especially in left TLE patients. These results suggest that functional imaging of SM tasks may be useful to predict postoperative verbal memory in TLE. They also advocate a common neuroanatomical basis for SM and EM processes in the MTL.

Cultural modulation of self-referential brain activity for personality traits and social identities.

PubMed

Sul, Sunhae; Choi, Incheol; Kang, Pyungwon

2012-01-01

Cross-cultural studies have shown that personality traits are less central and social identities are more important to the selfhood of collectivistic people. However, most cultural neuroscience studies using the self-reference effect (SRE) paradigm have only used personality traits to explore cultural differences in the neural circuits of self-referential processes. In the present study, we used both personality traits and social identities as stimuli in the SRE paradigm and investigated whether and how one's cultural orientation (i.e., individualism vs. collectivism) affects the SRE in the brain. The results showed that the medial prefrontal cortex, anterior cingulate, bilateral temporoparietal regions, and precuneus were involved in self-representation for both personality traits and social identities. Importantly, cultural orientation predicted differential activation patterns in these regions. Collectivists showed stronger activation in the left temporoparietal regions than individualists, who mainly recruited the medial prefrontal regions. Our findings suggest that the personal and social self share common neural substrates, the activation of which can be modulated by one's cultural orientation.

Functional Overlap between Regions Involved in Speech Perception and in Monitoring One's Own Voice during Speech Production

ERIC Educational Resources Information Center

Zheng, Zane Z.; Munhall, Kevin G.; Johnsrude, Ingrid S.

2010-01-01

The fluency and the reliability of speech production suggest a mechanism that links motor commands and sensory feedback. Here, we examined the neural organization supporting such links by using fMRI to identify regions in which activity during speech production is modulated according to whether auditory feedback matches the predicted outcome or…

Recognition memory of newly learned faces.

PubMed

Ishai, Alumit; Yago, Elena

2006-12-11

We used event-related fMRI to study recognition memory of newly learned faces. Caucasian subjects memorized unfamiliar, neutral and happy South Korean faces and 4 days later performed a memory retrieval task in the MR scanner. We predicted that previously seen faces would be recognized faster and more accurately and would elicit stronger neural activation than novel faces. Consistent with our hypothesis, novel faces were recognized more slowly and less accurately than previously seen faces. We found activation in a distributed cortical network that included face-responsive regions in the visual cortex, parietal and prefrontal regions, and the hippocampus. Within all regions, correctly recognized, previously seen faces evoked stronger activation than novel faces. Additionally, in parietal and prefrontal cortices, stronger activation was observed during correct than incorrect trials. Finally, in the hippocampus, false alarms to happy faces elicited stronger responses than false alarms to neutral faces. Our findings suggest that face recognition memory is mediated by stimulus-specific representations stored in extrastriate regions; parietal and prefrontal regions where old and new items are classified; and the hippocampus where veridical memory traces are recovered.

Predicting the Maximum Earthquake Magnitude from Seismic Data in Israel and Its Neighboring Countries.

PubMed

Last, Mark; Rabinowitz, Nitzan; Leonard, Gideon

2016-01-01

This paper explores several data mining and time series analysis methods for predicting the magnitude of the largest seismic event in the next year based on the previously recorded seismic events in the same region. The methods are evaluated on a catalog of 9,042 earthquake events, which took place between 01/01/1983 and 31/12/2010 in the area of Israel and its neighboring countries. The data was obtained from the Geophysical Institute of Israel. Each earthquake record in the catalog is associated with one of 33 seismic regions. The data was cleaned by removing foreshocks and aftershocks. In our study, we have focused on ten most active regions, which account for more than 80% of the total number of earthquakes in the area. The goal is to predict whether the maximum earthquake magnitude in the following year will exceed the median of maximum yearly magnitudes in the same region. Since the analyzed catalog includes only 28 years of complete data, the last five annual records of each region (referring to the years 2006-2010) are kept for testing while using the previous annual records for training. The predictive features are based on the Gutenberg-Richter Ratio as well as on some new seismic indicators based on the moving averages of the number of earthquakes in each area. The new predictive features prove to be much more useful than the indicators traditionally used in the earthquake prediction literature. The most accurate result (AUC = 0.698) is reached by the Multi-Objective Info-Fuzzy Network (M-IFN) algorithm, which takes into account the association between two target variables: the number of earthquakes and the maximum earthquake magnitude during the same year.

Predicting the Maximum Earthquake Magnitude from Seismic Data in Israel and Its Neighboring Countries

PubMed Central

2016-01-01

This paper explores several data mining and time series analysis methods for predicting the magnitude of the largest seismic event in the next year based on the previously recorded seismic events in the same region. The methods are evaluated on a catalog of 9,042 earthquake events, which took place between 01/01/1983 and 31/12/2010 in the area of Israel and its neighboring countries. The data was obtained from the Geophysical Institute of Israel. Each earthquake record in the catalog is associated with one of 33 seismic regions. The data was cleaned by removing foreshocks and aftershocks. In our study, we have focused on ten most active regions, which account for more than 80% of the total number of earthquakes in the area. The goal is to predict whether the maximum earthquake magnitude in the following year will exceed the median of maximum yearly magnitudes in the same region. Since the analyzed catalog includes only 28 years of complete data, the last five annual records of each region (referring to the years 2006–2010) are kept for testing while using the previous annual records for training. The predictive features are based on the Gutenberg-Richter Ratio as well as on some new seismic indicators based on the moving averages of the number of earthquakes in each area. The new predictive features prove to be much more useful than the indicators traditionally used in the earthquake prediction literature. The most accurate result (AUC = 0.698) is reached by the Multi-Objective Info-Fuzzy Network (M-IFN) algorithm, which takes into account the association between two target variables: the number of earthquakes and the maximum earthquake magnitude during the same year. PMID:26812351

Hydrological Response to Land Cover Changes and Human Activities in Arid Regions Using a Geographic Information System and Remote Sensing

PubMed Central

Mahmoud, Shereif H.; Alazba, A. A.

2015-01-01

The hydrological response to land cover changes induced by human activities in arid regions has attracted increased research interest in recent decades. The study reported herein assessed the spatial and quantitative changes in surface runoff resulting from land cover change in the Al-Baha region of Saudi Arabia between 1990 and 2000 using an ArcGIS-surface runoff model and predicted land cover and surface runoff depth in 2030 using Markov chain analysis. Land cover maps for 1990 and 2000 were derived from satellite images using ArcGIS 10.1. The findings reveal a 26% decrease in forest and shrubland area, 28% increase in irrigated cropland, 1.5% increase in sparsely vegetated land and 0.5% increase in bare soil between 1990 and 2000. Overall, land cover changes resulted in a significant decrease in runoff depth values in most of the region. The decrease in surface runoff depth ranged from 25-106 mm/year in a 7020-km2 area, whereas the increase in such depth reached only 10 mm/year in a 243-km2 area. A maximum increase of 73 mm/year was seen in a limited area. The surface runoff depth decreased to the greatest extent in the central region of the study area due to the huge transition in land cover classes associated with the construction of 25 rainwater harvesting dams. The land cover prediction revealed a greater than twofold increase in irrigated cropland during the 2000-2030 period, whereas forest and shrubland are anticipated to occupy just 225 km2 of land area by 2030, a significant decrease from the 747 km2 they occupied in 2000. Overall, changes in land cover are predicted to result in an annual increase in irrigated cropland and dramatic decline in forest area in the study area over the next few decades. The increase in surface runoff depth is likely to have significant implications for irrigation activities. PMID:25923712

After the Maples--What Then?

ERIC Educational Resources Information Center

Trisler, Carmen E.

1994-01-01

Uses models to illustrate the possible "migration route" of the sugar maple in response to predicted global climate change. Curriculum activities for students are provided that specifically address the sugar maple forests of the Great Lakes regions. (ZWH)

Feature Selection, Flaring Size and Time-to-Flare Prediction Using Support Vector Regression, and Automated Prediction of Flaring Behavior Based on Spatio-Temporal Measures Using Hidden Markov Models

NASA Astrophysics Data System (ADS)

Al-Ghraibah, Amani

Solar flares release stored magnetic energy in the form of radiation and can have significant detrimental effects on earth including damage to technological infrastructure. Recent work has considered methods to predict future flare activity on the basis of quantitative measures of the solar magnetic field. Accurate advanced warning of solar flare occurrence is an area of increasing concern and much research is ongoing in this area. Our previous work 111] utilized standard pattern recognition and classification techniques to determine (classify) whether a region is expected to flare within a predictive time window, using a Relevance Vector Machine (RVM) classification method. We extracted 38 features which describing the complexity of the photospheric magnetic field, the result classification metrics will provide the baseline against which we compare our new work. We find a true positive rate (TPR) of 0.8, true negative rate (TNR) of 0.7, and true skill score (TSS) of 0.49. This dissertation proposes three basic topics; the first topic is an extension to our previous work [111, where we consider a feature selection method to determine an appropriate feature subset with cross validation classification based on a histogram analysis of selected features. Classification using the top five features resulting from this analysis yield better classification accuracies across a large unbalanced dataset. In particular, the feature subsets provide better discrimination of the many regions that flare where we find a TPR of 0.85, a TNR of 0.65 sightly lower than our previous work, and a TSS of 0.5 which has an improvement comparing with our previous work. In the second topic, we study the prediction of solar flare size and time-to-flare using support vector regression (SVR). When we consider flaring regions only, we find an average error in estimating flare size of approximately half a GOES class. When we additionally consider non-flaring regions, we find an increased average error of approximately 3/4 a GOES class. We also consider thresholding the regressed flare size for the experiment containing both flaring and non-flaring regions and find a TPR. of 0.69 and a TNR of 0.86 for flare prediction, consistent with our previous studies of flare prediction using the same magnetic complexity features. The results for both of these size regression experiments are consistent across a wide range of predictive time windows, indicating that the magnetic complexity features may be persistent in appearance long before flare activity. This conjecture is supported by our larger error rates of some 40 hours in the time-to-flare regression problem. The magnetic complexity features considered here appear to have discriminative potential for flare size, but their persistence in time makes them less discriminative for the time-to-flare problem. We also study the prediction of solar flare size and time-to-flare using two temporal features, namely the ▵- and ▵-▵-features, the same average size and time-to-flare regression error are found when these temporal features are used in size and time-to-flare prediction. In the third topic, we study the temporal evolution of active region magnetic fields using Hidden Markov Models (HMMs) which is one of the efficient temporal analyses found in literature. We extracted 38 features which describing the complexity of the photospheric magnetic field. These features are converted into a sequence of symbols using k-nearest neighbor search method. We study many parameters before prediction; like the length of the training window Wtrain which denotes to the number of history images use to train the flare and non-flare HMMs, and number of hidden states Q. In training phase, the model parameters of the HMM of each category are optimized so as to best describe the training symbol sequences. In testing phase, we use the best flare and non-flare models to predict/classify active regions as a flaring or non-flaring region using a sliding window method. The best prediction result is found where the length of the history training images are 15 images (i.e., Wtrain= 15) and the length of the sliding testing window is less than or equal to W train, the best result give a TPR of 0.79 consistent with previous flare prediction work, TNR of 0.87 arid TSS of 0.66, where both are higher than our previous flare prediction work. We find that the best number of hidden states which can describe the temporal evolution of the solar ARs is equal to five states, at the same time, a close resultant metrics are found using different number of states.

The morphology of flare phenomena, magnetic fields, and electric currents in active regions. I - Introduction and methods

NASA Technical Reports Server (NTRS)

Canfield, Richard C.; De La Beaujardiere, J.-F.; Fan, Yuhong; Leka, K. D.; Mcclymont, A. N.; Metcalf, Thomas R.; Mickey, Donald L.; Wuelser, Jean-Pierre; Lites, Bruce W.

1993-01-01

Electric current systems in solar active regions and their spatial relationship to sites of electron precipitation and high-pressure in flares were studied with the purpose of providing observational evidence for or against the flare models commonly discussed in the literature. The paper describes the instrumentation, the data used, and the data analysis methods, as well as improvements made upon earlier studies. Several flare models are overviewed, and the predictions yielded by each model for the relationships of flares to the vertical current systems are discussed.

SEMI-EMPIRICAL MODELING OF THE PHOTOSPHERE, CHROMOPSHERE, TRANSITION REGION, AND CORONA OF THE M-DWARF HOST STAR GJ 832

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fontenla, J. M.; Linsky, Jeffrey L.; Witbrod, Jesse

Stellar radiation from X-rays to the visible provides the energy that controls the photochemistry and mass loss from exoplanet atmospheres. The important extreme ultraviolet (EUV) region (10–91.2 nm) is inaccessible and should be computed from a reliable stellar model. It is essential to understand the formation regions and physical processes responsible for the various stellar emission features to predict how the spectral energy distribution varies with age and activity levels. We compute a state-of-the-art semi-empirical atmospheric model and the emergent high-resolution synthetic spectrum of the moderately active M2 V star GJ 832 as the first of a series of modelsmore » for stars with different activity levels. We construct a one-dimensional simple model for the physical structure of the star’s chromosphere, chromosphere-corona transition region, and corona using non-LTE radiative transfer techniques and many molecular lines. The synthesized spectrum for this model fits the continuum and lines across the UV-to-optical spectrum. Particular emphasis is given to the emission lines at wavelengths that are shorter than 300 nm observed with the Hubble Space Telescope , which have important effects on the photochemistry of the exoplanet atmospheres. The FUV line ratios indicate that the transition region of GJ 832 is more biased to hotter material than that of the quiet Sun. The excellent agreement of our computed EUV luminosity with that obtained by two other techniques indicates that our model predicts reliable EUV emission from GJ 832. We find that the unobserved EUV flux of GJ 832, which heats the outer atmospheres of exoplanets and drives their mass loss, is comparable to the active Sun.« less

Time perspective and the theory of planned behavior: moderate predictors of physical activity among central Appalachian adolescents.

PubMed

Gulley, Tauna; Boggs, Dusta

2014-01-01

The purpose of this study was to determine how well time perspective and the Theory of Planned Behavior (TPB) predicted physical activity among adolescents residing in the central Appalachian region of the United States. A descriptive, correlational design was used. The setting was a rural high school in central Appalachia. The sample included 185 students in grades 9 through 12. Data were collected in school. Variables included components of the TPB, time perspective, and various levels of exercise. Data were analyzed using Pearson's correlation coefficients and multiple regression analysis. The TPB was a moderate predictor of exercise frequency among central Appalachian adolescents, accounting for 42% of the variance. Time perspective did not add to the predictive ability of the TPB to predict exercise frequency in this sample. This study provides support for the TPB for predicting frequency of exercise among central Appalachian adolescents. By understanding the role of the TPB in predicting physical activity among adolescents, nurse practitioners will be able to adapt intervention strategies to improve the physical activity behaviors of this population. Copyright © 2014 National Association of Pediatric Nurse Practitioners. Published by Mosby, Inc. All rights reserved.

Efficient search, mapping, and optimization of multi-protein genetic systems in diverse bacteria

PubMed Central

Farasat, Iman; Kushwaha, Manish; Collens, Jason; Easterbrook, Michael; Guido, Matthew; Salis, Howard M

2014-01-01

Developing predictive models of multi-protein genetic systems to understand and optimize their behavior remains a combinatorial challenge, particularly when measurement throughput is limited. We developed a computational approach to build predictive models and identify optimal sequences and expression levels, while circumventing combinatorial explosion. Maximally informative genetic system variants were first designed by the RBS Library Calculator, an algorithm to design sequences for efficiently searching a multi-protein expression space across a > 10,000-fold range with tailored search parameters and well-predicted translation rates. We validated the algorithm's predictions by characterizing 646 genetic system variants, encoded in plasmids and genomes, expressed in six gram-positive and gram-negative bacterial hosts. We then combined the search algorithm with system-level kinetic modeling, requiring the construction and characterization of 73 variants to build a sequence-expression-activity map (SEAMAP) for a biosynthesis pathway. Using model predictions, we designed and characterized 47 additional pathway variants to navigate its activity space, find optimal expression regions with desired activity response curves, and relieve rate-limiting steps in metabolism. Creating sequence-expression-activity maps accelerates the optimization of many protein systems and allows previous measurements to quantitatively inform future designs. PMID:24952589

Short-term solar activity forecasting

NASA Technical Reports Server (NTRS)

Xie-Zhen, C.; Ai-Di, Z.

1979-01-01

A method of forecasting the level of activity of every active region on the surface of the Sun within one to three days is proposed in order to estimate the possibility of the occurrence of ionospheric disturbances and proton events. The forecasting method is a probability process based on statistics. In many of the cases, the accuracy in predicting the short term solar activity was in the range of 70%, although there were many false alarms.

Dorsomedial prefrontal cortex mediates rapid evaluations predicting the outcome of romantic interactions

PubMed Central

Cooper, Jeffrey C.; Dunne, Simon; Furey, Teresa; O’Doherty, John P.

2012-01-01

Humans frequently make real-world decisions based on rapid evaluations of minimal information – for example, should we talk to an attractive stranger at a party? Little is known, however, about how the brain makes rapid evaluations with real and immediate social consequences. To address this question, we scanned participants with FMRI while they viewed photos of individuals that they subsequently met at real-life “speed-dating” events. Neural activity in two areas of dorsomedial prefrontal cortex, paracingulate cortex and rostromedial prefrontal cortex (RMPFC), was predictive of whether each individual would be ultimately pursued for a romantic relationship or rejected. Activity in these areas was attributable to two distinct components of romantic evaluation: either consensus judgments about physical beauty (paracingulate cortex) or individualized preferences based on a partner’s perceived personality (RMPFC). These data identify novel computational roles for these regions of the dorsomedial prefrontal cortex in even very rapid social evaluations. Even a first glance, then, can accurately predict romantic desire, but that glance involves a mix of physical and psychological judgments that depend on specific regions of dorsomedial prefrontal cortex. PMID:23136406

Neuronal pattern separation of motion-relevant input in LIP activity

PubMed Central

Berberian, Nareg; MacPherson, Amanda; Giraud, Eloïse; Richardson, Lydia

2016-01-01

In various regions of the brain, neurons discriminate sensory stimuli by decreasing the similarity between ambiguous input patterns. Here, we examine whether this process of pattern separation may drive the rapid discrimination of visual motion stimuli in the lateral intraparietal area (LIP). Starting with a simple mean-rate population model that captures neuronal activity in LIP, we show that overlapping input patterns can be reformatted dynamically to give rise to separated patterns of neuronal activity. The population model predicts that a key ingredient of pattern separation is the presence of heterogeneity in the response of individual units. Furthermore, the model proposes that pattern separation relies on heterogeneity in the temporal dynamics of neural activity and not merely in the mean firing rates of individual neurons over time. We confirm these predictions in recordings of macaque LIP neurons and show that the accuracy of pattern separation is a strong predictor of behavioral performance. Overall, results propose that LIP relies on neuronal pattern separation to facilitate decision-relevant discrimination of sensory stimuli. NEW & NOTEWORTHY A new hypothesis is proposed on the role of the lateral intraparietal (LIP) region of cortex during rapid decision making. This hypothesis suggests that LIP alters the representation of ambiguous inputs to reduce their overlap, thus improving sensory discrimination. A combination of computational modeling, theoretical analysis, and electrophysiological data shows that the pattern separation hypothesis links neural activity to behavior and offers novel predictions on the role of LIP during sensory discrimination. PMID:27881719

Frontal and limbic activation during inhibitory control predicts treatment response in major depressive disorder.

PubMed

Langenecker, Scott A; Kennedy, Susan E; Guidotti, Leslie M; Briceno, Emily M; Own, Lawrence S; Hooven, Thomas; Young, Elizabeth A; Akil, Huda; Noll, Douglas C; Zubieta, Jon-Kar

2007-12-01

Inhibitory control or regulatory difficulties have been explored in major depressive disorder (MDD) but typically in the context of affectively salient information. Inhibitory control is addressed specifically by using a task devoid of affectively-laden stimuli, to disentangle the effects of altered affect and altered inhibitory processes in MDD. Twenty MDD and 22 control volunteer participants matched by age and gender completed a contextual inhibitory control task, the Parametric Go/No-go (PGNG) task during functional magnetic resonance imaging. The PGNG includes three levels of difficulty, a typical continuous performance task and two progressively more difficult versions including Go/No-go hit and rejection trials. After this test, 15 of 20 MDD patients completed a full 10-week treatment with s-citalopram. There was a significant interaction among response time (control subjects better), hits (control subjects better), and rejections (patients better). The MDD participants had greater activation compared with the control group in frontal and anterior temporal areas during correct rejections (inhibition). Activation during successful inhibitory events in bilateral inferior frontal and left amygdala, insula, and nucleus accumbens and during unsuccessful inhibition (commission errors) in rostral anterior cingulate predicted post-treatment improvement in depression symptoms. The imaging findings suggest that in MDD subjects, greater neural activation in frontal, limbic, and temporal regions during correct rejection of lures is necessary to achieve behavioral performance equivalent to control subjects. Greater activation in similar regions was further predictive of better treatment response in MDD.

Measurement of the underlying event activity using charged-particle jets in proton-proton collisions at √{s}=2.76 TeV

NASA Astrophysics Data System (ADS)

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Knünz, V.; König, A.; Krammer, M.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Cornelis, T.; de Wolf, E. A.; Janssen, X.; Knutsson, A.; Lauwers, J.; Luyckx, S.; Ochesanu, S.; Rougny, R.; van de Klundert, M.; van Haevermaet, H.; van Mechelen, P.; van Remortel, N.; van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; Daci, N.; de Bruyn, I.; Deroover, K.; Heracleous, N.; Keaveney, J.; Lowette, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Strom, D.; Tavernier, S.; van Doninck, W.; van Mulders, P.; van Onsem, G. P.; van Parijs, I.; Barria, P.; Caillol, C.; Clerbaux, B.; de Lentdecker, G.; Delannoy, H.; Dobur, D.; Fasanella, G.; Favart, L.; Gay, A. P. R.; Grebenyuk, A.; Lenzi, T.; Léonard, A.; Maerschalk, T.; Mohammadi, A.; Perniè, L.; Randle-Conde, A.; Reis, T.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Yonamine, R.; Zenoni, F.; Zhang, F.; Beernaert, K.; Benucci, L.; Cimmino, A.; Crucy, S.; Fagot, A.; Garcia, G.; Gul, M.; McCartin, J.; Ocampo Rios, A. A.; Poyraz, D.; Ryckbosch, D.; Salva, S.; Sigamani, M.; Strobbe, N.; Tytgat, M.; van Driessche, W.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bondu, O.; Bruno, G.; Castello, R.; Caudron, A.; Ceard, L.; da Silveira, G. G.; Delaere, C.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Mertens, A.; Nuttens, C.; Perrini, L.; Pin, A.; Piotrzkowski, K.; Popov, A.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Beliy, N.; Caebergs, T.; Hammad, G. H.; Aldá Júnior, W. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Dos Reis Martins, T.; Hensel, C.; Mora Herrera, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Custódio, A.; da Costa, E. M.; de Jesus Damiao, D.; de Oliveira Martins, C.; Fonseca de Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado da Silva, W. L.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; de Souza Santos, A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Genchev, V.; Hadjiiska, R.; Iaydjiev, P.; Marinov, A.; Piperov, S.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Cheng, T.; Du, R.; Jiang, C. H.; Plestina, R.; Romeo, F.; Shaheen, S. M.; Tao, J.; Wang, C.; Wang, Z.; Zhang, H.; Asawatangtrakuldee, C.; Ban, Y.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Zou, W.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; Gomez Moreno, B.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Kadija, K.; Luetic, J.; Sudic, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Bodlak, M.; Finger, M.; Finger, M.; Aly, R.; Aly, S.; Assran, Y.; Elgammal, S.; Ellithi Kamel, A.; Lotfy, A.; Mahmoud, M. A.; Radi, A.; Sayed, A.; Calpas, B.; Kadastik, M.; Murumaa, M.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Zghiche, A.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Dahms, T.; Davignon, O.; Filipovic, N.; Florent, A.; Granier de Cassagnac, R.; Lisniak, S.; Mastrolorenzo, L.; Miné, P.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Regnard, S.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Goetzmann, C.; Le Bihan, A.-C.; Merlin, J. A.; Skovpen, K.; van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Bouvier, E.; Brochet, S.; Carrillo Montoya, C. A.; Chasserat, J.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Ruiz Alvarez, J. D.; Sabes, D.; Sgandurra, L.; Sordini, V.; Donckt, M. Vander; Verdier, P.; Viret, S.; Xiao, H.; Toriashvili, T.; Bagaturia, I.; Autermann, C.; Beranek, S.; Edelhoff, M.; Feld, L.; Heister, A.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Ostapchuk, A.; Preuten, M.; Raupach, F.; Sammet, J.; Schael, S.; Schulte, J. F.; Verlage, T.; Weber, H.; Wittmer, B.; Zhukov, V.; Ata, M.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Klingebiel, D.; Knutzen, S.; Kreuzer, P.; Merschmeyer, M.; Meyer, A.; Millet, P.; Olschewski, M.; Padeken, K.; Papacz, P.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Erdogan, Y.; Flügge, G.; Geenen, H.; Geisler, M.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Künsken, A.; Lingemann, J.; Nehrkorn, A.; Nowack, A.; Nugent, I. M.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Asin, I.; Bartosik, N.; Behnke, O.; Behrens, U.; Bell, A. J.; Borras, K.; Burgmeier, A.; Cakir, A.; Calligaris, L.; Campbell, A.; Choudhury, S.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Dooling, S.; Dorland, T.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Flucke, G.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Gunnellini, P.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Karacheban, O.; Kasemann, M.; Katsas, P.; Kieseler, J.; Kleinwort, C.; Korol, I.; Lange, W.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Mankel, R.; Marfin, I.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Nayak, A.; Ntomari, E.; Perrey, H.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Ribeiro Cipriano, P. M.; Roland, B.; Sahin, M. Ö.; Salfeld-Nebgen, J.; Saxena, P.; Schoerner-Sadenius, T.; Schröder, M.; Seitz, C.; Spannagel, S.; Trippkewitz, K. D.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Erfle, J.; Garutti, E.; Goebel, K.; Gonzalez, D.; Görner, M.; Haller, J.; Hoffmann, M.; Höing, R. S.; Junkes, A.; Klanner, R.; Kogler, R.; Lapsien, T.; Lenz, T.; Marchesini, I.; Marconi, D.; Nowatschin, D.; Ott, J.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Pietsch, N.; Poehlsen, J.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Schwandt, J.; Seidel, M.; Sola, V.; Stadie, H.; Steinbrück, G.; Tholen, H.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Akbiyik, M.; Barth, C.; Baus, C.; Berger, J.; Böser, C.; Butz, E.; Chwalek, T.; Colombo, F.; de Boer, W.; Descroix, A.; Dierlamm, A.; Feindt, M.; Frensch, F.; Giffels, M.; Gilbert, A.; Hartmann, F.; Husemann, U.; Kassel, F.; Katkov, I.; Kornmayer, A.; Lobelle Pardo, P.; Mozer, M. U.; Müller, T.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Röcker, S.; Roscher, F.; Simonis, H. J.; Stober, F. M.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Markou, A.; Psallidas, A.; Topsis-Giotis, I.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Tziaferi, E.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Loukas, N.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Bencze, G.; Hajdu, C.; Hazi, A.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Molnar, J.; Szillasi, Z.; Bartók, M.; Makovec, A.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Mal, P.; Mandal, K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Gupta, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Mehta, A.; Mittal, M.; Nishu, N.; Singh, J. B.; Walia, G.; Kumar, Ashok; Kumar, Arun; Bhardwaj, A.; Choudhary, B. C.; Garg, R. B.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, R.; Sharma, V.; Banerjee, S.; Bhattacharya, S.; Chatterjee, K.; Dey, S.; Dutta, S.; Jain, Sa.; Jain, Sh.; Khurana, R.; Majumdar, N.; Modak, A.; Mondal, K.; Mukherjee, S.; Mukhopadhyay, S.; Roy, A.; Roy, D.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Abdulsalam, A.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Banerjee, S.; Bhowmik, S.; Chatterjee, R. M.; Dewanjee, R. K.; Dugad, S.; Ganguly, S.; Ghosh, S.; Guchait, M.; Gurtu, A.; Kole, G.; Kumar, S.; Mahakud, B.; Maity, M.; Majumder, G.; Mazumdar, K.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sarkar, T.; Sudhakar, K.; Sur, N.; Sutar, B.; Wickramage, N.; Sharma, S.; Bakhshiansohi, H.; Behnamian, H.; Etesami, S. M.; Fahim, A.; Goldouzian, R.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Caputo, C.; Chhibra, S. S.; Colaleo, A.; Creanza, D.; Cristella, L.; de Filippis, N.; de Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Travaglini, R.; Cappello, G.; Chiorboli, M.; Costa, S.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Gonzi, S.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Tropiano, A.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Calvelli, V.; Ferro, F.; Lo Vetere, M.; Robutti, E.; Tosi, S.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Gerosa, R.; Ghezzi, A.; Govoni, P.; Malvezzi, S.; Manzoni, R. A.; Marzocchi, B.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Ragazzi, S.; Redaelli, N.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; di Guida, S.; Esposito, M.; Fabozzi, F.; Iorio, A. O. M.; Lanza, G.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Bellato, M.; Bisello, D.; Carlin, R.; Carvalho Antunes de Oliveira, A.; Checchia, P.; Dall'Osso, M.; Dorigo, T.; Fantinel, S.; Fanzago, F.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Tosi, M.; Zanetti, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Braghieri, A.; Gabusi, M.; Magnani, A.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Biasini, M.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Spiezia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Broccolo, G.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fedi, G.; Foà, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Serban, A. T.; Spagnolo, P.; Squillacioti, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; D'Imperio, G.; Del Re, D.; Diemoz, M.; Gelli, S.; Jorda, C.; Longo, E.; Margaroli, F.; Meridiani, P.; Micheli, F.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Traczyk, P.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bellan, R.; Biino, C.; Cartiglia, N.; Costa, M.; Covarelli, R.; Degano, A.; Dellacasa, G.; Demaria, N.; Finco, L.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Musich, M.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Ravera, F.; Romero, A.; Ruspa, M.; Sacchi, R.; Solano, A.; Staiano, A.; Tamponi, U.; Belforte, S.; Candelise, V.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Gobbo, B.; La Licata, C.; Marone, M.; Schizzi, A.; Umer, T.; Zanetti, A.; Chang, S.; Kropivnitskaya, A.; Nam, S. K.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Kong, D. J.; Lee, S.; Oh, Y. D.; Sakharov, A.; Son, D. C.; Brochero Cifuentes, J. A.; Kim, H.; Kim, T. J.; Ryu, M. S.; Song, S.; Choi, S.; Go, Y.; Gyun, D.; Hong, B.; Jo, M.; Kim, H.; Kim, Y.; Lee, B.; Lee, K.; Lee, K. S.; Lee, S.; Park, S. K.; Roh, Y.; Yoo, H. D.; Choi, M.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Ryu, G.; Choi, Y.; Choi, Y. K.; Goh, J.; Kim, D.; Kwon, E.; Lee, J.; Yu, I.; Juodagalvis, A.; Vaitkus, J.; Ahmed, I.; Ibrahim, Z. A.; Komaragiri, J. R.; Md Ali, M. A. B.; Mohamad Idris, F.; Wan Abdullah, W. A. T.; Casimiro Linares, E.; Castilla-Valdez, H.; de La Cruz-Burelo, E.; Heredia-de La Cruz, I.; Hernandez-Almada, A.; Lopez-Fernandez, R.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Vazquez Valencia, F.; Carpinteyro, S.; Pedraza, I.; Salazar Ibarguen, H. A.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Reucroft, S.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. A.; Khurshid, T.; Shoaib, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Brona, G.; Bunkowski, K.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Walczak, M.; Bargassa, P.; Beirão da Cruz E Silva, C.; di Francesco, A.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Lloret Iglesias, L.; Nguyen, F.; Rodrigues Antunes, J.; Seixas, J.; Toldaiev, O.; Vadruccio, D.; Varela, J.; Vischia, P.; Afanasiev, S.; Bunin, P.; Gavrilenko, M.; Golutvin, I.; Gorbunov, I.; Kamenev, A.; Karjavin, V.; Konoplyanikov, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Zarubin, A.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sulimov, V.; Uvarov, L.; Vavilov, S.; Vorobyev, A.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Karneyeu, A.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Spiridonov, A.; Vlasov, E.; Zhokin, A.; Bylinkin, A.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Mesyats, G.; Rusakov, S. V.; Vinogradov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Dudko, L.; Ershov, A.; Gribushin, A.; Khein, L.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Myagkov, I.; Obraztsov, S.; Petrushanko, S.; Savrin, V.; Snigirev, A.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Tourtchanovitch, L.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Ekmedzic, M.; Milosevic, J.; Rekovic, V.; Wang, W. Y.; Alcaraz Maestre, J.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; de La Cruz, B.; Delgado Peris, A.; Domínguez Vázquez, D.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro de Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Albajar, C.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Brun, H.; Cuevas, J.; Fernandez Menendez, J.; Folgueras, S.; Gonzalez Caballero, I.; Palencia Cortezon, E.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Castiñeiras de Saa, J. R.; de Castro Manzano, P.; Duarte Campderros, J.; Fernandez, M.; Gomez, G.; Graziano, A.; Lopez Virto, A.; Marco, J.; Marco, R.; Martinez Rivero, C.; Matorras, F.; Munoz Sanchez, F. J.; Piedra Gomez, J.; Rodrigo, T.; Rodríguez-Marrero, A. Y.; Ruiz-Jimeno, A.; Scodellaro, L.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Bachtis, M.; Baillon, P.; Ball, A. H.; Barney, D.; Benaglia, A.; Bendavid, J.; Benhabib, L.; Benitez, J. F.; Berruti, G. M.; Bianchi, G.; Bloch, P.; Bocci, A.; Bonato, A.; Botta, C.; Breuker, H.; Camporesi, T.; Cerminara, G.; Colafranceschi, S.; D'Alfonso, M.; D'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; de Gruttola, M.; de Guio, F.; de Roeck, A.; de Visscher, S.; di Marco, E.; Dobson, M.; Dordevic, M.; Du Pree, T.; Dupont, N.; Elliott-Peisert, A.; Eugster, J.; Franzoni, G.; Funk, W.; Gigi, D.; Gill, K.; Giordano, D.; Girone, M.; Glege, F.; Guida, R.; Gundacker, S.; Guthoff, M.; Hammer, J.; Hansen, M.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kirschenmann, H.; Kortelainen, M. J.; Kousouris, K.; Krajczar, K.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Magini, N.; Malgeri, L.; Mannelli, M.; Marrouche, J.; Martelli, A.; Masetti, L.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Nemallapudi, M. V.; Neugebauer, H.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Piparo, D.; Racz, A.; Rolandi, G.; Rovere, M.; Ruan, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Sharma, A.; Silva, P.; Simon, M.; Sphicas, P.; Spiga, D.; Steggemann, J.; Stieger, B.; Stoye, M.; Takahashi, Y.; Treille, D.; Tsirou, A.; Veres, G. I.; Wardle, N.; Wöhri, H. K.; Zagozdzinska, A.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Buchmann, M. A.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Lustermann, W.; Mangano, B.; Marini, A. C.; Marionneau, M.; Martinez Ruiz Del Arbol, P.; Masciovecchio, M.; Meister, D.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrozzi, L.; Peruzzi, M.; Quittnat, M.; Rossini, M.; Starodumov, A.; Takahashi, M.; Tavolaro, V. R.; Theofilatos, K.; Wallny, R.; Weber, H. A.; Aarrestad, T. K.; Amsler, C.; Canelli, M. F.; Chiochia, V.; de Cosa, A.; Galloni, C.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Ngadiuba, J.; Pinna, D.; Robmann, P.; Ronga, F. J.; Salerno, D.; Taroni, S.; Yang, Y.; Cardaci, M.; Chen, K. H.; Doan, T. H.; Ferro, C.; Konyushikhin, M.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Volpe, R.; Yu, S. S.; Bartek, R.; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Fiori, F.; Grundler, U.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Miñano Moya, M.; Petrakou, E.; Tsai, J. F.; Tzeng, Y. M.; Asavapibhop, B.; Kovitanggoon, K.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Cerci, S.; Dozen, C.; Girgis, S.; Gokbulut, G.; Guler, Y.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kayis Topaksu, A.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Tali, B.; Topakli, H.; Vergili, M.; Zorbilmez, C.; Akin, I. V.; Bilin, B.; Bilmis, S.; Isildak, B.; Karapinar, G.; Surat, U. E.; Yalvac, M.; Zeyrek, M.; Albayrak, E. A.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, T.; Cankocak, K.; Sen, S.; Vardarlı, F. I.; Grynyov, B.; Levchuk, L.; Sorokin, P.; Aggleton, R.; Ball, F.; Beck, L.; Brooke, J. J.; Clement, E.; Cussans, D.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Meng, Z.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Seif El Nasr-Storey, S.; Senkin, S.; Smith, D.; Smith, V. J.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Thomas, L.; Tomalin, I. R.; Williams, T.; Womersley, W. J.; Worm, S. D.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Bundock, A.; Burton, D.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Cripps, N.; Dauncey, P.; Davies, G.; de Wit, A.; Della Negra, M.; Dunne, P.; Elwood, A.; Ferguson, W.; Fulcher, J.; Futyan, D.; Hall, G.; Iles, G.; Karapostoli, G.; Kenzie, M.; Lane, R.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Raymond, D. M.; Richards, A.; Rose, A.; Seez, C.; Sharp, P.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leggat, D.; Leslie, D.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Dittmann, J.; Hatakeyama, K.; Kasmi, A.; Liu, H.; Pastika, N.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Gastler, D.; Lawson, P.; Rankin, D.; Richardson, C.; Rohlf, J.; St. John, J.; Sulak, L.; Zou, D.; Alimena, J.; Berry, E.; Bhattacharya, S.; Cutts, D.; Dhingra, N.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Sagir, S.; Sinthuprasith, T.; Breedon, R.; Breto, G.; Calderon de La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Gardner, M.; Ko, W.; Lander, R.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Farrell, C.; Hauser, J.; Ignatenko, M.; Rakness, G.; Saltzberg, D.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Ivova Paneva, M.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Luthra, A.; Malberti, M.; Olmedo Negrete, M.; Shrinivas, A.; Sumowidagdo, S.; Wei, H.; Wimpenny, S.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Holzner, A.; Kelley, R.; Klein, D.; Letts, J.; MacNeill, I.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Tu, Y.; Vartak, A.; Wasserbaech, S.; Welke, C.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Barge, D.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Incandela, J.; Justus, C.; McColl, N.; Mullin, S. D.; Richman, J.; Stuart, D.; Suarez, I.; To, W.; West, C.; Yoo, J.; Anderson, D.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Pierini, M.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhu, R. Y.; Azzolini, V.; Calamba, A.; Carlson, B.; Ferguson, T.; Iiyama, Y.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Gaz, A.; Jensen, F.; Johnson, A.; Krohn, M.; Mulholland, T.; Nauenberg, U.; Smith, J. G.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chatterjee, A.; Chaves, J.; Chu, J.; Dittmer, S.; Eggert, N.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Sun, W.; Tan, S. M.; Teo, W. D.; Thom, J.; Thompson, J.; Tucker, J.; Weng, Y.; Wittich, P.; Abdullin, S.; Albrow, M.; Anderson, J.; Apollinari, G.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; Hare, D.; Harris, R. M.; Hirschauer, J.; Hooberman, B.; Hu, Z.; Jindariani, S.; Johnson, M.; Joshi, U.; Jung, A. W.; Klima, B.; Kreis, B.; Kwan, S.; Lammel, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lopes de Sá, R.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Martinez Outschoorn, V. I.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mishra, K.; Mrenna, S.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Prokofyev, O.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Whitbeck, A.; Yang, F.; Yin, H.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Carnes, A.; Carver, M.; Curry, D.; Das, S.; di Giovanni, G. P.; Field, R. D.; Fisher, M.; Furic, I. K.; Hugon, J.; Konigsberg, J.; Korytov, A.; Low, J. F.; Ma, P.; Matchev, K.; Mei, H.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Rank, D.; Shchutska, L.; Snowball, M.; Sperka, D.; Wang, S.; Yelton, J.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, J. R.; Adams, T.; Askew, A.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Khatiwada, A.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Bhopatkar, V.; Hohlmann, M.; Kalakhety, H.; Mareskas-Palcek, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Kurt, P.; O'Brien, C.; Sandoval Gonzalez, I. D.; Silkworth, C.; Turner, P.; Varelas, N.; Wu, Z.; Zakaria, M.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tan, P.; Tiras, E.; Wetzel, J.; Yi, K.; Anderson, I.; Barnett, B. A.; Blumenfeld, B.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Nash, K.; Osherson, M.; Swartz, M.; Xiao, M.; Xin, Y.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Gray, J.; Kenny, R. P.; Majumder, D.; Malek, M.; Murray, M.; Noonan, D.; Sanders, S.; Stringer, R.; Wang, Q.; Wood, J. S.; Chakaberia, I.; Ivanov, A.; Kaadze, K.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Skhirtladze, N.; Svintradze, I.; Toda, S.; Lange, D.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Gomez, J. A.; Hadley, N. J.; Jabeen, S.; Kellogg, R. G.; Kolberg, T.; Kunkle, J.; Lu, Y.; Mignerey, A. C.; Pedro, K.; Shin, Y. H.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Baty, A.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; Demiragli, Z.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; McGinn, C.; Niu, X.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Stephans, G. S. F.; Sumorok, K.; Varma, M.; Velicanu, D.; Veverka, J.; Wang, J.; Wang, T. W.; Wyslouch, B.; Yang, M.; Zhukova, V.; Dahmes, B.; Finkel, A.; Gude, A.; Hansen, P.; Kalafut, S.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Meier, F.; Monroy, J.; Ratnikov, F.; Siado, J. E.; Snow, G. R.; Alyari, M.; Dolen, J.; George, J.; Godshalk, A.; Iashvili, I.; Kaisen, J.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira de Lima, R.; Trocino, D.; Wang, R.-J.; Wood, D.; Zhang, J.; Hahn, K. A.; Kubik, A.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Trovato, M.; Velasco, M.; Won, S.; Brinkerhoff, A.; Dev, N.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Lynch, S.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Pearson, T.; Planer, M.; Ruchti, R.; Smith, G.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hart, A.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Liu, B.; Luo, W.; Puigh, D.; Rodenburg, M.; Winer, B. L.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Palmer, C.; Piroué, P.; Quan, X.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Malik, S.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Miller, D. H.; Neumeister, N.; Primavera, F.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Sun, J.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Zablocki, J.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Redjimi, R.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Betchart, B.; Bodek, A.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Hindrichs, O.; Khukhunaishvili, A.; Petrillo, G.; Verzetti, M.; Demortier, L.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Lath, A.; Panwalkar, S.; Park, M.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Foerster, M.; Riley, G.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Castaneda Hernandez, A.; Dalchenko, M.; de Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Krutelyov, V.; Montalvo, R.; Mueller, R.; Osipenkov, I.; Pakhotin, Y.; Patel, R.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Undleeb, S.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Wolfe, E.; Wood, J.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Christian, A.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Gomber, B.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ross, I.; Ruggles, T.; Sarangi, T.; Savin, A.; Sharma, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.

2015-09-01

A measurement of the underlying event (UE) activity in proton-proton collisions is performed using events with charged-particle jets produced in the central pseudorapidity region (| η jet| < 2) and with transverse momentum 1 ≤ p T jet < 100 GeV. The analysis uses a data sample collected at a centre-of-mass energy of 2.76 TeV with the CMS experiment at the LHC. The UE activity is measured as a function of p T jet in terms of the average multiplicity and scalar sum of transverse momenta ( p T) of charged particles, with | η| < 2 and p T > 0.5 GeV, in the azimuthal region transverse to the highest p T jet direction. By further dividing the transverse region into two regions of smaller and larger activity, various components of the UE activity are separated. The measurements are compared to previous results at 0.9 and 7 TeV, and to predictions of several Monte Carlo event generators, providing constraints on the modelling of the UE dynamics. [Figure not available: see fulltext.

Functional brain imaging predicts public health campaign success.

PubMed

Falk, Emily B; O'Donnell, Matthew Brook; Tompson, Steven; Gonzalez, Richard; Dal Cin, Sonya; Strecher, Victor; Cummings, Kenneth Michael; An, Lawrence

2016-02-01

Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a 'self-localizer' defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400,000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R(2) up to 0.65) and (ii) this relationship depends on message content-self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

[Effectiveness of the Federal Inspectorate for the Protection of Consumer Rights and Human Welfare in the Novosibirsk Region in 2007 to 2009].

PubMed

Mikheev, V N; Ivanova, L K; Iagudin, B I; Turbinskiĭ, V V

2010-01-01

A system for monitoring and analyzing the effectiveness and efficiency of the performance of the Board of the Federal Inspectorate for the Protection of Consumer Rights and Human Welfare in the Novosibirsk Region was introduced into its activities to estimate the provision of the Novosibirsk Region's population with sanitary epidemiological wellbeing in 2007-2009. The introduction of monitoring was ascertained to increase the effectiveness of budgetary fund surveillance and spending, by predicting the effectiveness and choice of priority lines of activities, by increasing the quality of budgetary services rendered in the provision of sanitary and epidemiological well-being to the population.

Particle Swarm Optimization for Programming Deep Brain Stimulation Arrays

PubMed Central

Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D.

2017-01-01

Objective Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main Results The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (≤9.2%) and ROA (≤1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n=3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies of <1% between approaches. Significance The PSO algorithm provides a computationally efficient way to program DBS systems especially those with higher electrode counts. PMID:28068291

Particle swarm optimization for programming deep brain stimulation arrays

NASA Astrophysics Data System (ADS)

Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D.

2017-02-01

Objective. Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach. Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main results. The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (⩽9.2%) and ROA (⩽1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n  =  3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies of  <1% between approaches. Significance. The PSO algorithm provides a computationally efficient way to program DBS systems especially those with higher electrode counts.

Correlation of the Coronal Mass Ejection Productivity of Solar Active Regions with Measures of their Global Nonpotentiality from Vector Magnetograms: Baseline Results

NASA Technical Reports Server (NTRS)

Falconer, D. A.; Moore, R. L.; Gary, G. A.

2002-01-01

Conventional magnetograms and chromospheric and coronal images show qualitatively that the fastest coronal mass ejections (CMEs) are magnetic explosions from sunspot active regions where the magnetic field is globally strongly sheared and twisted from its minimum-energy potential configuration. We present measurements from active region vector magnetograms that start to quantify the dependence of an active region's CME productivity on the global nonpotentiality of its magnetic field. From each of 17 magnetograms of 12 bipolar active regions, we measured the size of the active region (the magnetic flux content, phi) and three separate measures of the global nonpotentiality (L(sub SS), the length of strong-shear, strong-field main neutral line: I(sub N), the net electric current connecting one polarity to the other; and alpha = (mu)I(sub N)/phi), a flux normalized measure of the field twist). From these measurements and the observed CME productivity of the active regions, we find that: (1) All three measures of global nonpotentiality are statistically correlated with the active region flux content and with each other; (2) All three measures of global nonpotentiality are significantly correlated with CME productivity. The flux content correlates with CME productivity, but at a lower statistically significant confidence level (less than 95%); (3) The net current is less closely correlated with CME productivity than alpha and the correlation of CME productivity with flux content is even weaker. If these differences in correlation strength, and a significant correlation of alpha with flux content, persist to larger active regions, this would imply that the size of active regions does not affect CME productivity except through global nonpotentiality; and (4) For each of the four global magnetic quantities, the correlation with CME productivity is stronger for a two-day time window for the CME production than for windows half as wide or twice as wide. This plausibly is a result of the most counterproductive active regions producing less than one CME per day, and from the active region's evolution often significantly changing the global nonpotentiality over the course of several days. These results establish that measures of active region global nonpotentiality from vector magnetograms (such as L(sub SS), I(sub N), and alpha) should be useful for prediction a active region CMEs.

Prediction of Peaks of Seasonal Influenza in Military Health-Care Data

PubMed Central

Buczak, Anna L.; Baugher, Benjamin; Guven, Erhan; Moniz, Linda; Babin, Steven M.; Chretien, Jean-Paul

2016-01-01

Influenza is a highly contagious disease that causes seasonal epidemics with significant morbidity and mortality. The ability to predict influenza peak several weeks in advance would allow for timely preventive public health planning and interventions to be used to mitigate these outbreaks. Because influenza may also impact the operational readiness of active duty personnel, the US military places a high priority on surveillance and preparedness for seasonal outbreaks. A method for creating models for predicting peak influenza visits per total health-care visits (ie, activity) weeks in advance has been developed using advanced data mining techniques on disparate epidemiological and environmental data. The model results are presented and compared with those of other popular data mining classifiers. By rigorously testing the model on data not used in its development, it is shown that this technique can predict the week of highest influenza activity for a specific region with overall better accuracy than other methods examined in this article. PMID:27127415

Regional Variation in Geniohyoid Muscle Strain During Suckling in the Infant Pig

PubMed Central

HOLMAN, SHAINA DEVI; KONOW, NICOLAI; LUKASIK, STACEY L.; GERMAN, REBECCA Z.

2014-01-01

The geniohyoid muscle (GH) is a critical suprahyoid muscle in most mammalian oropharyngeal motor activities. We used sonomicrometry to evaluate regional strain (i.e., changes in length) in the muscle origin, belly, and insertion during suckling in infant pigs, and compared the results to existing information on strain heterogeneity in the hyoid musculature. We tested the hypothesis that during rhythmic activity, the GH shows regional variation in muscle strain. We used sonomicrometry transducer pairs to divide the muscle into three regions from anterior to posterior. The results showed differences in strain among the regions within a feeding cycle; however, no region consistently shortened or lengthened over the course of a cycle. Moreover, regional strain patterns were not correlated with timing of the suck cycles, neither (1) relative to a swallow cycle (before or after) nor (2) to the time in feeding sequence (early or late). We also found a tight relationship between muscle activity and muscle strain, however, the relative timing of muscle activity and muscle strain was different in some muscle regions and between individuals. A dissection of the C1 innervations of the geniohyoid showed that there are between one and three branches entering the muscle, possibly explaining the variation seen in regional activity and strain. In combination, our findings suggest that regional heterogeneity in muscle strain during patterned suckling behavior functions to stabilize the hyoid bone, whereas the predictable regional strain differences in reflexive behaviors may be necessary for faster and higher amplitude movements of the hyoid bone. PMID:22549885

Structural and functional bases of inhibited temperament.

PubMed

Clauss, Jacqueline A; Seay, April L; VanDerKlok, Ross M; Avery, Suzanne N; Cao, Aize; Cowan, Ronald L; Benningfield, Margaret M; Blackford, Jennifer Urbano

2014-12-01

Children born with an inhibited temperament are at heightened risk for developing anxiety, depression and substance use. Inhibited temperament is believed to have a biological basis; however, little is known about the structural brain basis of this vulnerability trait. Structural MRI scans were obtained from 84 (44 inhibited, 40 uninhibited) young adults. Given previous findings of amygdala hyperactivity in inhibited individuals, groups were compared on three measures of amygdala structure. To identify novel substrates of inhibited temperament, a whole brain analysis was performed. Functional activation and connectivity were examined across both groups. Inhibited adults had larger amygdala and caudate volume and larger volume predicted greater activation to neutral faces. In addition, larger amygdala volume predicted greater connectivity with subcortical and higher order visual structures. Larger caudate volume predicted greater connectivity with the basal ganglia, and less connectivity with primary visual and auditory cortex. We propose that larger volume in these salience detection regions may result in increased activation and enhanced connectivity in response to social stimuli. Given the strong link between inhibited temperament and risk for psychiatric illness, novel therapeutics that target these brain regions and related neural circuits have the potential to reduce rates of illness in vulnerable individuals. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Lung Metabolic Activation as an Early Biomarker of the Acute Respiratory Distress Syndrome and Local Gene Expression Heterogeneity

PubMed Central

Wellman, Tyler J.; de Prost, Nicolas; Tucci, Mauro; Winkler, Tilo; Baron, Rebecca M.; Filipczak, Piotr; Raby, Benjamin; Chu, Jen-hwa; Harris, R. Scott; Musch, Guido; dos Reis Falcao, Luiz F.; Capelozzi, Vera; Venegas, Jose; Melo, Marcos F. Vidal

2016-01-01

Background The acute respiratory distress syndrome (ARDS) is an inflammatory condition comprising diffuse lung edema and alveolar damage. ARDS frequently results from regional injury mechanisms. However, it is unknown whether detectable inflammation precedes lung edema and opacification, and whether topographically differential gene expression consistent with heterogeneous injury occurs in early ARDS. We aimed to determine the temporal relationship between pulmonary metabolic activation and density in a large animal model of early ARDS, and to assess gene expression in differentially activated regions. Methods We produced ARDS in sheep with intravenous LPS (10ng/kg/h) and mechanical ventilation for 20h. Using positron emission tomography, we assessed regional cellular metabolic activation with 2-deoxy-2-[(18)F]fluoro-D-glucose, perfusion and ventilation with 13NN-saline, and aeration using transmission scans. Species-specific micro-array technology was used to assess regional gene expression. Results Metabolic activation preceded detectable increases in lung density (as required for clinical diagnosis) and correlated with subsequent histological injury, suggesting its predictive value for severity of disease progression. Local time-courses of metabolic activation varied, with highly perfused and less aerated dependent lung regions activated earlier than non-dependent regions. These regions of distinct metabolic trajectories demonstrated differential gene expression for known and potential novel candidates for ARDS pathogenesis. Conclusions Heterogeneous lung metabolic activation precedes increases in lung density in the development of ARDS due to endotoxemia and mechanical ventilation. Local differential gene expression occurs in these early stages and reveals molecular pathways relevant to ARDS biology and of potential use as treatment targets. PMID:27611185

Active Region Moss: Doppler Shifts from Hinode/EIS Observations

NASA Technical Reports Server (NTRS)

Tripathi, Durgesh; Mason, Helen E.; Klimchuk, James A.

2012-01-01

Studying the Doppler shifts and the temperature dependence of Doppler shifts in moss regions can help us understand the heating processes in the core of the active regions. In this paper we have used an active region observation recorded by the Extreme-ultraviolet Imaging Spectrometer (EIS) onboard Hinode on 12-Dec- 2007 to measure the Doppler shifts in the moss regions. We have distinguished the moss regions from the rest of the active region by defining a low density cut-off as derived by Tripathi et al. (2010). We have carried out a very careful analysis of the EIS wavelength calibration based on the method described in Young, O Dwyer and Mason (2012). For spectral lines having maximum sensitivity between log T = 5.85 and log T = 6.25 K, we find that the velocity distribution peaks at around 0 km/s with an estimated error of 4 km/s. The width of the distribution decreases with temperature. The mean of the distribution shows a blue shift which increases with increasing temperature and the distribution also shows asymmetries towards blue-shift. Comparing these results with observables predicted from different coronal heating models, we find that these results are consistent with both steady and impulsive heating scenarios. Further observational constraints are needed to distinguish between these two heating scenarios.

Predicting Growth in Word Level Reading Skills in Children With Developmental Dyslexia Using an Object Rhyming Functional Neuroimaging Task.

PubMed

Farris, Emily A; Ring, Jeremiah; Black, Jeffrey; Lyon, G Reid; Odegard, Timothy N

2016-04-01

An object rhyming task that does not require text reading and is suitable for younger children was used to predict gains in word level reading skills following an intensive 2-year reading intervention for children with developmental dyslexia. The task evoked activation in bilateral inferior frontal regions. Growth in untimed pseudoword reading was associated with increased pre-intervention activation of the left inferior frontal gyrus, and growth in timed word reading was associated with pre-intervention activation of the left and right inferior frontal gyri. These analyses help identify pre-intervention factors that facilitate reading skill improvements in children with developmental dyslexia.

The magnificent outburst of the 2016 Perseids, the analyses

NASA Astrophysics Data System (ADS)

Miskotte, Koen; Vandeputte, Michel

2017-03-01

Enhanced Perseid activity had been predicted for 2016 as a result of a sequence of encounters with some dust trails as well as the effect of perturbations by Jupiter which made Earth crossing the main stream deeper through more dense regions. Visual observations resulted in a detailed activity profile and population index profile, the observed features in these profiles could be matched with the predicted passages through the different dust trails. The 4 Rev (1479) dust trail in particular produced a distinct peak while the 7 Rev (1079) dust trail remained rather at a somehow disappointing low level. The traditional annual Perseid maximum displayed enhanced activity due to the 12 Rev (441) dust trail.

Prediction of Low Community Sanitation Coverage Using Environmental and Sociodemographic Factors in Amhara Region, Ethiopia

PubMed Central

Oswald, William E.; Stewart, Aisha E. P.; Flanders, W. Dana; Kramer, Michael R.; Endeshaw, Tekola; Zerihun, Mulat; Melaku, Birhanu; Sata, Eshetu; Gessesse, Demelash; Teferi, Tesfaye; Tadesse, Zerihun; Guadie, Birhan; King, Jonathan D.; Emerson, Paul M.; Callahan, Elizabeth K.; Moe, Christine L.; Clasen, Thomas F.

2016-01-01

This study developed and validated a model for predicting the probability that communities in Amhara Region, Ethiopia, have low sanitation coverage, based on environmental and sociodemographic conditions. Community sanitation coverage was measured between 2011 and 2014 through trachoma control program evaluation surveys. Information on environmental and sociodemographic conditions was obtained from available data sources and linked with community data using a geographic information system. Logistic regression was used to identify predictors of low community sanitation coverage (< 20% versus ≥ 20%). The selected model was geographically and temporally validated. Model-predicted probabilities of low community sanitation coverage were mapped. Among 1,502 communities, 344 (22.90%) had coverage below 20%. The selected model included measures for high topsoil gravel content, an indicator for low-lying land, population density, altitude, and rainfall and had reasonable predictive discrimination (area under the curve = 0.75, 95% confidence interval = 0.72, 0.78). Measures of soil stability were strongly associated with low community sanitation coverage, controlling for community wealth, and other factors. A model using available environmental and sociodemographic data predicted low community sanitation coverage for areas across Amhara Region with fair discrimination. This approach could assist sanitation programs and trachoma control programs, scaling up or in hyperendemic areas, to target vulnerable areas with additional activities or alternate technologies. PMID:27430547

THE FUTURE OF TOXICOLOGY-PREDICTIVE TOXICOLOGY ...

EPA Pesticide Factsheets

A chemistry approach to predictive toxicology relies on structure−activity relationship (SAR) modeling to predict biological activity from chemical structure. Such approaches have proven capabilities when applied to well-defined toxicity end points or regions of chemical space. These approaches are less well-suited, however, to the challenges of global toxicity prediction, i.e., to predicting the potential toxicity of structurally diverse chemicals across a wide range of end points of regulatory and pharmaceutical concern. New approaches that have the potential to significantly improve capabilities in predictive toxicology are elaborating the “activity” portion of the SAR paradigm. Recent advances in two areas of endeavor are particularly promising. Toxicity data informatics relies on standardized data schema, developed for particular areas of toxicological study, to facilitate data integration and enable relational exploration and mining of data across both historical and new areas of toxicological investigation. Bioassay profiling refers to large-scale high-throughput screening approaches that use chemicals as probes to broadly characterize biological response space, extending the concept of chemical “properties” to the biological activity domain. The effective capture and representation of legacy and new toxicity data into mineable form and the large-scale generation of new bioassay data in relation to chemical toxicity, both employing chemical stru

Comparing GIS-based habitat models for applications in EIA and SEA

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gontier, Mikael, E-mail: gontier@kth.s; Moertberg, Ulla, E-mail: mortberg@kth.s; Balfors, Berit, E-mail: balfors@kth.s

Land use changes, urbanisation and infrastructure developments in particular, cause fragmentation of natural habitats and threaten biodiversity. Tools and measures must be adapted to assess and remedy the potential effects on biodiversity caused by human activities and developments. Within physical planning, environmental impact assessment (EIA) and strategic environmental assessment (SEA) play important roles in the prediction and assessment of biodiversity-related impacts from planned developments. However, adapted prediction tools to forecast and quantify potential impacts on biodiversity components are lacking. This study tested and compared four different GIS-based habitat models and assessed their relevance for applications in environmental assessment. The modelsmore » were implemented in the Stockholm region in central Sweden and applied to data on the crested tit (Parus cristatus), a sedentary bird species of coniferous forest. All four models performed well and allowed the distribution of suitable habitats for the crested tit in the Stockholm region to be predicted. The models were also used to predict and quantify habitat loss for two regional development scenarios. The study highlighted the importance of model selection in impact prediction. Criteria that are relevant for the choice of model for predicting impacts on biodiversity were identified and discussed. Finally, the importance of environmental assessment for the preservation of biodiversity within the general frame of biodiversity conservation is emphasised.« less

A false alarm based on electrical activity recorded at a VAN-Station in northern Greece in December 1990

NASA Astrophysics Data System (ADS)

Drakopoulos, John; Stavrakakis, George N.

A VAN-prediction was announced on January 6, 1991, through the French newspaper “Le Monde” and on January 8-10, 1991, through Greek newspapers and TV stations. We evaluate this prediction on the basis of a letter which was sent by Prof. Varotsos (without date) to the Greek Minister of Public Works, and by considering previous VAN-publications as well as recent seismological data for the candidate regions. We conclude that what was observed at ASS station (northern Greece) on December 31, 1990, was not SES-activity but another disturbance or noise.

Activity flow over resting-state networks shapes cognitive task activations.

PubMed

Cole, Michael W; Ito, Takuya; Bassett, Danielle S; Schultz, Douglas H

2016-12-01

Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allowed prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations.

Activity flow over resting-state networks shapes cognitive task activations

PubMed Central

Cole, Michael W.; Ito, Takuya; Bassett, Danielle S.; Schultz, Douglas H.

2016-01-01

Resting-state functional connectivity (FC) has helped reveal the intrinsic network organization of the human brain, yet its relevance to cognitive task activations has been unclear. Uncertainty remains despite evidence that resting-state FC patterns are highly similar to cognitive task activation patterns. Identifying the distributed processes that shape localized cognitive task activations may help reveal why resting-state FC is so strongly related to cognitive task activations. We found that estimating task-evoked activity flow (the spread of activation amplitudes) over resting-state FC networks allows prediction of cognitive task activations in a large-scale neural network model. Applying this insight to empirical functional MRI data, we found that cognitive task activations can be predicted in held-out brain regions (and held-out individuals) via estimated activity flow over resting-state FC networks. This suggests that task-evoked activity flow over intrinsic networks is a large-scale mechanism explaining the relevance of resting-state FC to cognitive task activations. PMID:27723746

The neural components of empathy: predicting daily prosocial behavior.

PubMed

Morelli, Sylvia A; Rameson, Lian T; Lieberman, Matthew D

2014-01-01

Previous neuroimaging studies on empathy have not clearly identified neural systems that support the three components of empathy: affective congruence, perspective-taking, and prosocial motivation. These limitations stem from a focus on a single emotion per study, minimal variation in amount of social context provided, and lack of prosocial motivation assessment. In the current investigation, 32 participants completed a functional magnetic resonance imaging session assessing empathic responses to individuals experiencing painful, anxious, and happy events that varied in valence and amount of social context provided. They also completed a 14-day experience sampling survey that assessed real-world helping behaviors. The results demonstrate that empathy for positive and negative emotions selectively activates regions associated with positive and negative affect, respectively. In addition, the mirror system was more active during empathy for context-independent events (pain), whereas the mentalizing system was more active during empathy for context-dependent events (anxiety, happiness). Finally, the septal area, previously linked to prosocial motivation, was the only region that was commonly activated across empathy for pain, anxiety, and happiness. Septal activity during each of these empathic experiences was predictive of daily helping. These findings suggest that empathy has multiple input pathways, produces affect-congruent activations, and results in septally mediated prosocial motivation.

Context Memory Decline in Middle Aged Adults is Related to Changes in Prefrontal Cortex Function.

PubMed

Kwon, Diana; Maillet, David; Pasvanis, Stamatoula; Ankudowich, Elizabeth; Grady, Cheryl L; Rajah, M Natasha

2016-06-01

The ability to encode and retrieve spatial and temporal contextual details of episodic memories (context memory) begins to decline at midlife. In the current study, event-related fMRI was used to investigate the neural correlates of context memory decline in healthy middle aged adults (MA) compared with young adults (YA). Participants were scanned while performing easy and hard versions of spatial and temporal context memory tasks. Scans were obtained at encoding and retrieval. Significant reductions in context memory retrieval accuracy were observed in MA, compared with YA. The fMRI results revealed that overall, both groups exhibited similar patterns of brain activity in parahippocampal cortex, ventral occipito-temporal regions and prefrontal cortex (PFC) during encoding. In contrast, at retrieval, there were group differences in ventral occipito-temporal and PFC activity, due to these regions being more activated in MA, compared with YA. Furthermore, only in YA, increased encoding activity in ventrolateral PFC, and increased retrieval activity in occipital cortex, predicted increased retrieval accuracy. In MA, increased retrieval activity in anterior PFC predicted increased retrieval accuracy. These results suggest that there are changes in PFC contributions to context memory at midlife. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Distracted and down: neural mechanisms of affective interference in subclinical depression

PubMed Central

Andrews-Hanna, Jessica R.; Spielberg, Jeffrey M.; Warren, Stacie L.; Sutton, Bradley P.; Miller, Gregory A.; Heller, Wendy; Banich, Marie T.

2015-01-01

Previous studies have shown that depressed individuals have difficulty directing attention away from negative distractors, a phenomenon known as affective interference. However, findings are mixed regarding the neural mechanisms and network dynamics of affective interference. The present study addressed these issues by comparing neural activation during emotion-word and color-word Stroop tasks in participants with varying levels of (primarily subclinical) depression. Depressive symptoms predicted increased activation to negative distractors in areas of dorsal anterior cingulate cortex (dACC) and posterior cingulate cortex (PCC), regions implicated in cognitive control and internally directed attention, respectively. Increased dACC activity was also observed in the group-average response to incongruent distractors, suggesting that dACC activity during affective interference is related to overtaxed cognitive control. In contrast, regions of PCC were deactivated across the group in response to incongruent distractors, suggesting that PCC activity during affective interference represents task-independent processing. A psychophysiological interaction emerged in which higher depression predicted more positively correlated activity between dACC and PCC during affective interference, i.e. greater connectivity between cognitive control and internal-attention systems. These findings suggest that, when individuals high in depression are confronted by negative material, increased attention to internal thoughts and difficulty shifting resources to the external world interfere with goal-directed behavior. PMID:25062838

The neural components of empathy: Predicting daily prosocial behavior

PubMed Central

Rameson, Lian T.; Lieberman, Matthew D.

2014-01-01

Previous neuroimaging studies on empathy have not clearly identified neural systems that support the three components of empathy: affective congruence, perspective-taking, and prosocial motivation. These limitations stem from a focus on a single emotion per study, minimal variation in amount of social context provided, and lack of prosocial motivation assessment. In the current investigation, 32 participants completed a functional magnetic resonance imaging session assessing empathic responses to individuals experiencing painful, anxious, and happy events that varied in valence and amount of social context provided. They also completed a 14-day experience sampling survey that assessed real-world helping behaviors. The results demonstrate that empathy for positive and negative emotions selectively activates regions associated with positive and negative affect, respectively. In addition, the mirror system was more active during empathy for context-independent events (pain), whereas the mentalizing system was more active during empathy for context-dependent events (anxiety, happiness). Finally, the septal area, previously linked to prosocial motivation, was the only region that was commonly activated across empathy for pain, anxiety, and happiness. Septal activity during each of these empathic experiences was predictive of daily helping. These findings suggest that empathy has multiple input pathways, produces affect-congruent activations, and results in septally mediated prosocial motivation. PMID:22887480

Baseline dental plaque activity, mutans streptococci culture, and future caries experience in children.

PubMed

Hallett, Kerrod B; O'Rourke, Peter K

2013-01-01

The purpose of this study was to evaluate a chairside caries risk assessment protocol utilizing a caries prediction instrument, adenosine triphosphate (ATP) activity in dental plaque, mutans streptococci (MS) culture, and routine dental examination in five- to 10-year-old children at two regional Australian schools with high caries experience. Clinical indicators for future caries were assessed at baseline examination using a standardized prediction instrument. Plaque ATP activity was measured directly in relative light units (RLU) using a bioluminescence meter, and MS culture data were recorded. Each child's dentition was examined clinically and radiographically, and caries experience was recorded using enamel white spot lesions and decayed, missing, and filled surfaces for primary and permanent teeth indices. Univariate one-way analysis of variance between selected clinical indicators, ATP activity, MS count at baseline, and future new caries activity was performed, and a generalized linear model for prediction of new caries activity at 24 months was constructed. Future new caries activity was significantly associated with the presence of visible cavitations, reduced saliva flow, and orthodontic appliances at baseline (R(2)=0.2, P<.001). Baseline plaque adenosine triphosphate activity and mutans streptococci counts were not significantly associated with caries activity at 24 months.

Prediction of household and commercial BMW generation according to socio-economic and other factors for the Dublin region.

PubMed

Purcell, M; Magette, W L

2009-04-01

Both planning and design of integrated municipal solid waste management systems require accurate prediction of waste generation. This research predicted the quantity and distribution of biodegradable municipal waste (BMW) generation within a diverse 'landscape' of residential areas, as well as from a variety of commercial establishments (restaurants, hotels, hospitals, etc.) in the Dublin (Ireland) region. Socio-economic variables, housing types, and the sizes and main activities of commercial establishments were hypothesized as the key determinants contributing to the spatial variability of BMW generation. A geographical information system (GIS) 'model' of BMW generation was created using ArcMap, a component of ArcGIS 9. Statistical data including socio-economic status and household size were mapped on an electoral district basis. Historical research and data from scientific literature were used to assign BMW generation rates to residential and commercial establishments. These predictions were combined to give overall BMW estimates for the region, which can aid waste planning and policy decisions. This technique will also aid the design of future waste management strategies, leading to policy and practice alterations as a function of demographic changes and development. The household prediction technique gave a more accurate overall estimate of household waste generation than did the social class technique. Both techniques produced estimates that differed from the reported local authority data; however, given that local authority reported figures for the region are below the national average, with some of the waste generated from apartment complexes being reported as commercial waste, predictions arising from this research are believed to be closer to actual waste generation than a comparison to reported data would suggest. By changing the input data, this estimation tool can be adapted for use in other locations. Although focusing on waste in the Dublin region, this method of waste prediction can have significant potential benefits if a universal method can be found to apply it effectively.

How the brain attunes to sentence processing: Relating behavior, structure, and function

PubMed Central

Fengler, Anja; Meyer, Lars; Friederici, Angela D.

2016-01-01

Unlike other aspects of language comprehension, the ability to process complex sentences develops rather late in life. Brain maturation as well as verbal working memory (vWM) expansion have been discussed as possible reasons. To determine the factors contributing to this functional development, we assessed three aspects in different age-groups (5–6 years, 7–8 years, and adults): first, functional brain activity during the processing of increasingly complex sentences; second, brain structure in language-related ROIs; and third, the behavioral comprehension performance on complex sentences and the performance on an independent vWM test. At the whole-brain level, brain functional data revealed a qualitatively similar neural network in children and adults including the left pars opercularis (PO), the left inferior parietal lobe together with the posterior superior temporal gyrus (IPL/pSTG), the supplementary motor area, and the cerebellum. While functional activation of the language-related ROIs PO and IPL/pSTG predicted sentence comprehension performance for all age-groups, only adults showed a functional selectivity in these brain regions with increased activation for more complex sentences. The attunement of both the PO and IPL/pSTG toward a functional selectivity for complex sentences is predicted by region-specific gray matter reduction while that of the IPL/pSTG is additionally predicted by vWM span. Thus, both structural brain maturation and vWM expansion provide the basis for the emergence of functional selectivity in language-related brain regions leading to more efficient sentence processing during development. PMID:26777477

In Silico Prediction Analysis of Idiotope-Driven T–B Cell Collaboration in Multiple Sclerosis

PubMed Central

Høglund, Rune A.; Lossius, Andreas; Johansen, Jorunn N.; Homan, Jane; Benth, Jūratė Šaltytė; Robins, Harlan; Bogen, Bjarne; Bremel, Robert D.; Holmøy, Trygve

2017-01-01

Memory B cells acting as antigen-presenting cells are believed to be important in multiple sclerosis (MS), but the antigen they present remains unknown. We hypothesized that B cells may activate CD4+ T cells in the central nervous system of MS patients by presenting idiotopes from their own immunoglobulin variable regions on human leukocyte antigen (HLA) class II molecules. Here, we use bioinformatics prediction analysis of B cell immunoglobulin variable regions from 11 MS patients and 6 controls with other inflammatory neurological disorders (OINDs), to assess whether the prerequisites for such idiotope-driven T–B cell collaboration are present. Our findings indicate that idiotopes from the complementarity determining region (CDR) 3 of MS patients on average have high predicted affinities for disease associated HLA-DRB1*15:01 molecules and are predicted to be endosomally processed by cathepsin S and L in positions that allows such HLA binding to occur. Additionally, complementarity determining region 3 sequences from cerebrospinal fluid (CSF) B cells from MS patients contain on average more rare T cell-exposed motifs that could potentially escape tolerance and stimulate CD4+ T cells than CSF B cells from OIND patients. Many of these features were associated with preferential use of the IGHV4 gene family by CSF B cells from MS patients. This is the first study to combine high-throughput sequencing of patient immune repertoires with large-scale prediction analysis and provides key indicators for future in vitro and in vivo analyses. PMID:29038659

In Silico Prediction Analysis of Idiotope-Driven T-B Cell Collaboration in Multiple Sclerosis.

PubMed

Høglund, Rune A; Lossius, Andreas; Johansen, Jorunn N; Homan, Jane; Benth, Jūratė Šaltytė; Robins, Harlan; Bogen, Bjarne; Bremel, Robert D; Holmøy, Trygve

2017-01-01

Memory B cells acting as antigen-presenting cells are believed to be important in multiple sclerosis (MS), but the antigen they present remains unknown. We hypothesized that B cells may activate CD4 + T cells in the central nervous system of MS patients by presenting idiotopes from their own immunoglobulin variable regions on human leukocyte antigen (HLA) class II molecules. Here, we use bioinformatics prediction analysis of B cell immunoglobulin variable regions from 11 MS patients and 6 controls with other inflammatory neurological disorders (OINDs), to assess whether the prerequisites for such idiotope-driven T-B cell collaboration are present. Our findings indicate that idiotopes from the complementarity determining region (CDR) 3 of MS patients on average have high predicted affinities for disease associated HLA-DRB1*15:01 molecules and are predicted to be endosomally processed by cathepsin S and L in positions that allows such HLA binding to occur. Additionally, complementarity determining region 3 sequences from cerebrospinal fluid (CSF) B cells from MS patients contain on average more rare T cell-exposed motifs that could potentially escape tolerance and stimulate CD4 + T cells than CSF B cells from OIND patients. Many of these features were associated with preferential use of the IGHV4 gene family by CSF B cells from MS patients. This is the first study to combine high-throughput sequencing of patient immune repertoires with large-scale prediction analysis and provides key indicators for future in vitro and in vivo analyses.

Neuroimaging studies of practice-related change: fMRI and meta-analytic evidence of a domain-general control network for learning.

PubMed

Chein, Jason M; Schneider, Walter

2005-12-01

Functional magnetic resonance imaging and a meta-analysis of prior neuroimaging studies were used to characterize cortical changes resulting from extensive practice and to evaluate a dual-processing account of the neural mechanisms underlying human learning. Three core predictions of the dual processing theory are evaluated: 1) that practice elicits generalized reductions in regional activity by reducing the load on the cognitive control mechanisms that scaffold early learning; 2) that these control mechanisms are domain-general; and 3) that no separate processing pathway emerges as skill develops. To evaluate these predictions, a meta-analysis of prior neuroimaging studies and a within-subjects fMRI experiment contrasting unpracticed to practiced performance in a paired-associate task were conducted. The principal effect of practice was found to be a reduction in the extent and magnitude of activity in a cortical network spanning bilateral dorsal prefrontal, left ventral prefrontal, medial frontal (anterior cingulate), left insular, bilateral parietal, and occipito-temporal (fusiform) areas. These activity reductions are shown to occur in common regions across prior neuroimaging studies and for both verbal and nonverbal paired-associate learning in the present fMRI experiment. The implicated network of brain regions is interpreted as a domain-general system engaged specifically to support novice, but not practiced, performance.

Wavelength tunable InGaN/GaN nano-ring LEDs via nano-sphere lithography

PubMed Central

Wang, Sheng-Wen; Hong, Kuo-Bin; Tsai, Yu-Lin; Teng, Chu-Hsiang; Tzou, An-Jye; Chu, You-Chen; Lee, Po-Tsung; Ku, Pei-Cheng; Lin, Chien-Chung; Kuo, Hao-Chung

2017-01-01

In this research, nano-ring light-emitting diodes (NRLEDs) with different wall width (120 nm, 80 nm and 40 nm) were fabricated by specialized nano-sphere lithography technology. Through the thinned wall, the effective bandgaps of nano-ring LEDs can be precisely tuned by reducing the strain inside the active region. Photoluminescence (PL) and time-resolved PL measurements indicated the lattice-mismatch induced strain inside the active region was relaxed when the wall width is reduced. Through the simulation, we can understand the strain distribution of active region inside NRLEDs. The simulation results not only revealed the exact distribution of strain but also predicted the trend of wavelength-shifted behavior of NRLEDs. Finally, the NRLEDs devices with four-color emission on the same wafer were demonstrated. PMID:28256529

Theory of Mind: A Neural Prediction Problem

PubMed Central

Koster-Hale, Jorie; Saxe, Rebecca

2014-01-01

Predictive coding posits that neural systems make forward-looking predictions about incoming information. Neural signals contain information not about the currently perceived stimulus, but about the difference between the observed and the predicted stimulus. We propose to extend the predictive coding framework from high-level sensory processing to the more abstract domain of theory of mind; that is, to inferences about others’ goals, thoughts, and personalities. We review evidence that, across brain regions, neural responses to depictions of human behavior, from biological motion to trait descriptions, exhibit a key signature of predictive coding: reduced activity to predictable stimuli. We discuss how future experiments could distinguish predictive coding from alternative explanations of this response profile. This framework may provide an important new window on the neural computations underlying theory of mind. PMID:24012000

Regional Arctic sea-ice prediction: potential versus operational seasonal forecast skill

NASA Astrophysics Data System (ADS)

Bushuk, Mitchell; Msadek, Rym; Winton, Michael; Vecchi, Gabriel; Yang, Xiaosong; Rosati, Anthony; Gudgel, Rich

2018-06-01

Seasonal predictions of Arctic sea ice on regional spatial scales are a pressing need for a broad group of stakeholders, however, most assessments of predictability and forecast skill to date have focused on pan-Arctic sea-ice extent (SIE). In this work, we present the first direct comparison of perfect model (PM) and operational (OP) seasonal prediction skill for regional Arctic SIE within a common dynamical prediction system. This assessment is based on two complementary suites of seasonal prediction ensemble experiments performed with a global coupled climate model. First, we present a suite of PM predictability experiments with start dates spanning the calendar year, which are used to quantify the potential regional SIE prediction skill of this system. Second, we assess the system's OP prediction skill for detrended regional SIE using a suite of retrospective initialized seasonal forecasts spanning 1981-2016. In nearly all Arctic regions and for all target months, we find a substantial skill gap between PM and OP predictions of regional SIE. The PM experiments reveal that regional winter SIE is potentially predictable at lead times beyond 12 months, substantially longer than the skill of their OP counterparts. Both the OP and PM predictions display a spring prediction skill barrier for regional summer SIE forecasts, indicating a fundamental predictability limit for summer regional predictions. We find that a similar barrier exists for pan-Arctic sea-ice volume predictions, but is not present for predictions of pan-Arctic SIE. The skill gap identified in this work indicates a promising potential for future improvements in regional SIE predictions.

Shape perception simultaneously up- and downregulates neural activity in the primary visual cortex.

PubMed

Kok, Peter; de Lange, Floris P

2014-07-07

An essential part of visual perception is the grouping of local elements (such as edges and lines) into coherent shapes. Previous studies have shown that this grouping process modulates neural activity in the primary visual cortex (V1) that is signaling the local elements [1-4]. However, the nature of this modulation is controversial. Some studies find that shape perception reduces neural activity in V1 [2, 5, 6], while others report increased V1 activity during shape perception [1, 3, 4, 7-10]. Neurocomputational theories that cast perception as a generative process [11-13] propose that feedback connections carry predictions (i.e., the generative model), while feedforward connections signal the mismatch between top-down predictions and bottom-up inputs. Within this framework, the effect of feedback on early visual cortex may be either enhancing or suppressive, depending on whether the feedback signal is met by congruent bottom-up input. Here, we tested this hypothesis by quantifying the spatial profile of neural activity in V1 during the perception of illusory shapes using population receptive field mapping. We find that shape perception concurrently increases neural activity in regions of V1 that have a receptive field on the shape but do not receive bottom-up input and suppresses activity in regions of V1 that receive bottom-up input that is predicted by the shape. These effects were not modulated by task requirements. Together, these findings suggest that shape perception changes lower-order sensory representations in a highly specific and automatic manner, in line with theories that cast perception in terms of hierarchical generative models. Copyright © 2014 Elsevier Ltd. All rights reserved.

LMethyR-SVM: Predict Human Enhancers Using Low Methylated Regions based on Weighted Support Vector Machines.

PubMed

Xu, Jingting; Hu, Hong; Dai, Yang

The identification of enhancers is a challenging task. Various types of epigenetic information including histone modification have been utilized in the construction of enhancer prediction models based on a diverse panel of machine learning schemes. However, DNA methylation profiles generated from the whole genome bisulfite sequencing (WGBS) have not been fully explored for their potential in enhancer prediction despite the fact that low methylated regions (LMRs) have been implied to be distal active regulatory regions. In this work, we propose a prediction framework, LMethyR-SVM, using LMRs identified from cell-type-specific WGBS DNA methylation profiles and a weighted support vector machine learning framework. In LMethyR-SVM, the set of cell-type-specific LMRs is further divided into three sets: reliable positive, like positive and likely negative, according to their resemblance to a small set of experimentally validated enhancers in the VISTA database based on an estimated non-parametric density distribution. Then, the prediction model is obtained by solving a weighted support vector machine. We demonstrate the performance of LMethyR-SVM by using the WGBS DNA methylation profiles derived from the human embryonic stem cell type (H1) and the fetal lung fibroblast cell type (IMR90). The predicted enhancers are highly conserved with a reasonable validation rate based on a set of commonly used positive markers including transcription factors, p300 binding and DNase-I hypersensitive sites. In addition, we show evidence that the large fraction of the LMethyR-SVM predicted enhancers are not predicted by ChromHMM in H1 cell type and they are more enriched for the FANTOM5 enhancers. Our work suggests that low methylated regions detected from the WGBS data are useful as complementary resources to histone modification marks in developing models for the prediction of cell-type-specific enhancers.

MAGNETIC NON-POTENTIALITY OF SOLAR ACTIVE REGIONS AND PEAK X-RAY FLUX OF THE ASSOCIATED FLARES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tiwari, Sanjiv Kumar; Venkatakrishnan, P.; Gosain, Sanjay, E-mail: pvk@prl.res.i, E-mail: sgosain@prl.res.i

Predicting the severity of solar eruptive phenomena such as flares and coronal mass ejections remains a great challenge despite concerted efforts to do so over the past several decades. However, the advent of high-quality vector magnetograms obtained from Hinode (SOT/SP) has increased the possibility of meeting this challenge. In particular, the spatially averaged signed shear angle (SASSA) seems to be a unique parameter for quantifying the non-potentiality of active regions. We demonstrate the usefulness of the SASSA for predicting flare severity. For this purpose, we present case studies of the evolution of magnetic non-potentiality using 115 vector magnetograms of fourmore » active regions, namely, ARs NOAA 10930, 10960, 10961, and 10963 during 2006 December 8-15, 2007 June 3-10, 2007 June 28-July 5, and 2007 July 10-17, respectively. The NOAA ARs 10930 and 10960 were very active and produced X and M class flares, respectively, along with many smaller X-ray flares. On the other hand, the NOAA ARs 10961 and 10963 were relatively less active and produced only very small (mostly A- and B-class) flares. For this study, we have used a large number of high-resolution vector magnetograms obtained from Hinode (SOT/SP). Our analysis shows that the peak X-ray flux of the most intense solar flare emanating from the active regions depends on the magnitude of the SASSA at the time of the flare. This finding of the existence of a lower limit of the SASSA for a given class of X-ray flares will be very useful for space weather forecasting. We have also studied another non-potentiality parameter called the mean weighted shear angle (MWSA) of the vector magnetograms along with the SASSA. We find that the MWSA does not show such distinction as the SASSA for upper limits of the GOES X-ray flux of solar flares; however, both the quantities show similar trends during the evolution of all active regions studied.« less

Distinct Contributions of Ventromedial and Dorsolateral Subregions of the Human Substantia Nigra to Appetitive and Aversive Learning

PubMed Central

Larsen, Tobias; Collette, Sven; Tyszka, Julian M.; Seymour, Ben; O'Doherty, John P.

2015-01-01

The role of neurons in the substantia nigra (SN) and ventral tegmental area (VTA) of the midbrain in contributing to the elicitation of reward prediction errors during appetitive learning has been well established. Less is known about the differential contribution of these midbrain regions to appetitive versus aversive learning, especially in humans. Here we scanned human participants with high-resolution fMRI focused on the SN and VTA while they participated in a sequential Pavlovian conditioning paradigm involving an appetitive outcome (a pleasant juice), as well as an aversive outcome (an unpleasant bitter and salty flavor). We found a degree of regional specialization within the SN: Whereas a region of ventromedial SN correlated with a temporal difference reward prediction error during appetitive Pavlovian learning, a dorsolateral area correlated instead with an aversive expected value signal in response to the most distal cue, and to a reward prediction error in response to the most proximal cue to the aversive outcome. Furthermore, participants' affective reactions to both the appetitive and aversive conditioned stimuli more than 1 year after the fMRI experiment was conducted correlated with activation in the ventromedial and dorsolateral SN obtained during the experiment, respectively. These findings suggest that, whereas the human ventromedial SN contributes to long-term learning about rewards, the dorsolateral SN may be particularly important for long-term learning in aversive contexts. SIGNIFICANCE STATEMENT The role of the substantia nigra (SN) and ventral tegmental area (VTA) in appetitive learning is well established, but less is known about their contribution to aversive compared with appetitive learning, especially in humans. We used high-resolution fMRI to measure activity in the SN and VTA while participants underwent higher-order Pavlovian learning. We found a regional specialization within the SN: a ventromedial area was selectively engaged during appetitive learning, and a dorsolateral area during aversive learning. Activity in these areas predicted affective reactions to appetitive and aversive conditioned stimuli over 1 year later. These findings suggest that, whereas the human ventromedial SN contributes to long-term learning about rewards, the dorsolateral SN may be particularly important for long-term learning in aversive contexts. PMID:26490862

HOT PLASMA FROM SOLAR ACTIVE-REGION CORES: CONSTRAINTS FROM THE HINODE X-RAY TELESCOPE

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmelz, J. T.; Christian, G. M.; Matheny, P. O., E-mail: jschmelz@usra.edu

2016-12-20

Mechanisms invoked to heat the solar corona to millions of degrees kelvin involve either magnetic waves or magnetic reconnections. Turbulence in the convection zone produces MHD waves, which travel upward and dissipate. Photospheric motions continuously build up magnetic energy, which is released through magnetic reconnection. In this paper, we concentrate on hot non-flaring plasma with temperatures of 5 MK <  T  < 10 MK because it is one of the few observables for which wave and reconnection models make different predictions. Wave models predict no (or little) hot plasma, whereas reconnection models predict it, although in amounts that are challenging to detectmore » with current instrumentation. We used data from the X-ray Telescope (XRT) and the Atmospheric Imaging Assembly (AIA). We requested a special XRT observing sequence, which cycled through the thickest XRT filter several times per hour so we could average these images and improve the signal-to-noise. We did differential emission measure (DEM) analysis using the time-averaged thick-filter data as well as all available channels from both the XRT and AIA for regions observed on 2014 December 11. Whereas our earlier work was only able to determine that plasma with a temperature greater than 5 MK was present , we are now able to find a well-constrained DEM distribution. We have therefore added a strong observational constraint that must be explained by any viable coronal heating model. Comparing state-of-the-art wave and reconnection model predictions, we can conclude that reconnection is heating the hot plasma in these active regions.« less

Choice from non-choice: Predicting consumer preferences from BOLD signals obtained during passive viewing

PubMed Central

Levy, Ifat; Lazzaro, Stephanie C.; Rutledge, Robb B.; Glimcher, Paul W.

2011-01-01

Decision-making is often viewed as a two-stage process, where subjective values are first assigned to each option and then the option of the highest value is selected. Converging evidence suggests that these subjective values are represented in the striatum and medial prefrontal cortex (MPFC). A separate line of evidence suggests that activation in the same areas represents the values of rewards even when choice is not required, as in classical conditioning tasks. However, it is unclear whether the same neural mechanism is engaged in both cases. To address this question we measured brain activation with fMRI while human subjects passively viewed individual consumer goods. We then sampled activation from predefined regions of interest and used it to predict subsequent choices between the same items made outside of the scanner. Our results show that activation in the striatum and MPFC in the absence of choice predicts subsequent choices, suggesting that these brain areas represent value in a similar manner whether or not choice is required. PMID:21209196

Many human accelerated regions are developmental enhancers

PubMed Central

Capra, John A.; Erwin, Genevieve D.; McKinsey, Gabriel; Rubenstein, John L. R.; Pollard, Katherine S.

2013-01-01

The genetic changes underlying the dramatic differences in form and function between humans and other primates are largely unknown, although it is clear that gene regulatory changes play an important role. To identify regulatory sequences with potentially human-specific functions, we and others used comparative genomics to find non-coding regions conserved across mammals that have acquired many sequence changes in humans since divergence from chimpanzees. These regions are good candidates for performing human-specific regulatory functions. Here, we analysed the DNA sequence, evolutionary history, histone modifications, chromatin state and transcription factor (TF) binding sites of a combined set of 2649 non-coding human accelerated regions (ncHARs) and predicted that at least 30% of them function as developmental enhancers. We prioritized the predicted ncHAR enhancers using analysis of TF binding site gain and loss, along with the functional annotations and expression patterns of nearby genes. We then tested both the human and chimpanzee sequence for 29 ncHARs in transgenic mice, and found 24 novel developmental enhancers active in both species, 17 of which had very consistent patterns of activity in specific embryonic tissues. Of these ncHAR enhancers, five drove expression patterns suggestive of different activity for the human and chimpanzee sequence at embryonic day 11.5. The changes to human non-coding DNA in these ncHAR enhancers may modify the complex patterns of gene expression necessary for proper development in a human-specific manner and are thus promising candidates for understanding the genetic basis of human-specific biology. PMID:24218637

Predicting the Occurrence of Haze Events in Southeast Asia using Machine Learning Algorithms

NASA Astrophysics Data System (ADS)

Lee, H. H.; Chulakadabba, A.; Tonks, A.; Yang, Z.; Wang, C.

2017-12-01

Severe local- and regional-scale air pollution episodes typically originate from 1) high emissions of air pollutants, 2) poor dispersion conditions, and 3) trans-boundary pollutant transport. Biomass burning activities have become more frequent in Southeast Asia, especially in Sumatra, Borneo, and the mainland Southeast. Trans-boundary transport of biomass burning aerosols often lead to air quality problems in the region. Furthermore, particulate pollutants from human activities besides biomass burning also play an important role in the air quality of Southeast Asia. Singapore, for example, has a dynamic industrial sector including chemical, electric and metallurgic industries, and is the region's major petroleum-refining center. In addition, natural gas and oil power plants, waste incinerators, active port traffic, and a major regional airport further complicate Singapore's air quality issues. In this study, we compare five Machine Learning algorithms: k-Nearest Neighbors, Linear Support Vector Machine, Decision Tree, Random Forest and Artificial Neural Network, to identify haze patterns and determine variable importance. The algorithms were trained using local atmospheric data (i.e. months, atmospheric conditions, wind direction and relative humidity) from three observation stations in Singapore (Changi, Seletar and Paya Labar). We find that the algorithms reveal the associations in data within and between the stations, and provide in-depth interpretation of the haze sources. The algorithms also allow us to predict the probability of haze episodes in Singapore and to determine the correlation between this probability and atmospheric conditions.

Solar-Terrestrial Predictions: Proceedings of a workshop. Volume 2: Geomagnetic and space environment papers and ionosphere papers

NASA Astrophysics Data System (ADS)

Thompson, R. J.; Cole, D. G.; Wilkinson, P. J.; Shea, M. A.; Smart, D.

1990-11-01

The following subject areas were covered: a probability forecast for geomagnetic activity; cost recovery in solar-terrestrial predictions; magnetospheric specification and forecasting models; a geomagnetic forecast and monitoring system for power system operation; some aspects of predicting magnetospheric storms; some similarities in ionospheric disturbance characteristics in equatorial, mid-latitude, and sub-auroral regions; ionospheric support for low-VHF radio transmission; a new approach to prediction of ionospheric storms; a comparison of the total electron content of the ionosphere around L=4 at low sunspot numbers with the IRI model; the French ionospheric radio propagation predictions; behavior of the F2 layer at mid-latitudes; and the design of modern ionosondes.

Associations of physical activity and sedentary behaviour with metabolic syndrome in rural Australian adults.

PubMed

Mitchell, Braden L; Smith, Ashleigh E; Rowlands, Alex V; Parfitt, Gaynor; Dollman, James

2018-05-22

Associations between objectively measured sedentary behaviour, physical activity (PA) and metabolic syndrome (MetS)-classified using three different definitions were investigated in an inactive sample of rural Australian adults. Quantitative, cross-sectional. 171 adults (50.7±12.4years) from two rural South Australian regions underwent seven-day accelerometer activity monitoring and MetS classification using the National Cholesterol Education Program, the International Diabetes Federation and the Harmonized definitions. Associations between sedentary and activity variables and MetS (adjusted for age, sex, diet and smoking status) were modelled using logistic regression. In secondary modelling, associations of sedentary and activity outcomes for each MetS definition were assessed, adjusting for other activity and sedentary variables. Prediction differences across the definitions of MetS were directly compared using Akaike's Information Criterion. Sedentary behaviour increased MetS risk, whereas light physical activity (LPA) and moderate-to-vigorous physical activity (MVPA) reduced MetS risk, irrespective of definition. In secondary models, LPA predicted MetS independently of MVPA and total sedentary time. Time spent in sedentary bouts (>30min) predicted MetS independently of MVPA and the number of sedentary bouts predicted MetS independently of LPA and MVPA. Prediction differences for MetS definitions failed to reach the critical threshold for difference (>10). This study highlights the importance of sedentary behaviour and LPA on the prevalence of MetS in an inactive sample of rural Australian adults. Studies assessing the efficacy of increasing LPA on MetS in this population are needed. Minimal predictive differences across the three MetS definitions suggest evidence from previous studies can be considered cumulative. Copyright © 2018 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

Lateralization is predicted by reduced coupling from the left to right prefrontal cortex during semantic decisions on written words.

PubMed

Seghier, Mohamed L; Josse, Goulven; Leff, Alexander P; Price, Cathy J

2011-07-01

Over 90% of people activate the left hemisphere more than the right hemisphere for language processing. Here, we show that the degree to which language is left lateralized is inversely related to the degree to which left frontal regions drive activity in homotopic right frontal regions. Lateralization was assessed in 60 subjects using functional magnetic resonance imaging (fMRI) activation for semantic decisions on verbal (written words) and nonverbal (pictures of objects) stimuli. Regional interactions between left and right ventral and dorsal frontal regions were assessed using dynamic causal modeling (DCM), random-effects Bayesian model selection at the family level, and Bayesian model averaging at the connection level. We found that 1) semantic decisions on words and pictures modulated interhemispheric coupling between the left and right dorsal frontal regions, 2) activation was more left lateralized for words than pictures, and 3) for words only, left lateralization was greater when the coupling from the left to right dorsal frontal cortex was reduced. These results have theoretical implications for understanding how left and right hemispheres communicate with one another during the processing of lateralized functions.

MAGNETIC FLUX TRANSPORT AND THE LONG-TERM EVOLUTION OF SOLAR ACTIVE REGIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ugarte-Urra, Ignacio; Upton, Lisa; Warren, Harry P.

2015-12-20

With multiple vantage points around the Sun, Solar Terrestrial Relations Observatory (STEREO) and Solar Dynamics Observatory imaging observations provide a unique opportunity to view the solar surface continuously. We use He ii 304 Å data from these observatories to isolate and track ten active regions and study their long-term evolution. We find that active regions typically follow a standard pattern of emergence over several days followed by a slower decay that is proportional in time to the peak intensity in the region. Since STEREO does not make direct observations of the magnetic field, we employ a flux-luminosity relationship to infermore » the total unsigned magnetic flux evolution. To investigate this magnetic flux decay over several rotations we use a surface flux transport model, the Advective Flux Transport model, that simulates convective flows using a time-varying velocity field and find that the model provides realistic predictions when information about the active region's magnetic field strength and distribution at peak flux is available. Finally, we illustrate how 304 Å images can be used as a proxy for magnetic flux measurements when magnetic field data is not accessible.« less

Performance on an episodic encoding task yields further insight into functional brain development.

PubMed

McAuley, Tara; Brahmbhatt, Shefali; Barch, Deanna M

2007-01-15

To further characterize changes in functional brain development that are associated with the emergence of cognitive control, participants 14 to 28 years of age were scanned while performing an episodic encoding task with a levels-of-processing manipulation. Using data from the 12 youngest and oldest participants (endpoint groups), 18 regions were identified that showed group differences in task-related activity as a function of processing depth. One region, located in left inferior frontal gyrus, showed enhanced activity in deep relative to shallow encoding that was larger in magnitude for the older group. Seventeen regions showed enhanced activity in shallow relative to deep encoding that was larger in magnitude for the youngest group. These regions were distributed across a broad network that included both cortical and subcortical areas. Regression analyses using the entire sample showed that age made a significant contribution to the difference in beta weights between deep and shallow encoding for 17 of the 18 identified regions in the direction predicted by the endpoint analysis. We conclude that the patterns of brain activation associated with deep and shallow encoding differ between adolescents and young adults in a manner that is consistent with the interactive specialization account of functional brain development.

Quantitative structure activity relationships from optimised ab initio bond lengths: steroid binding affinity and antibacterial activity of nitrofuran derivatives

NASA Astrophysics Data System (ADS)

Smith, P. J.; Popelier, P. L. A.

2004-02-01

The present day abundance of cheap computing power enables the use of quantum chemical ab initio data in Quantitative Structure-Activity Relationships (QSARs). Optimised bond lengths are a new such class of descriptors, which we have successfully used previously in representing electronic effects in medicinal and ecological QSARs (enzyme inhibitory activity, hydrolysis rate constants and pKas). Here we use AM1 and HF/3-21G* bond lengths in conjunction with Partial Least Squares (PLS) and a Genetic Algorithm (GA) to predict the Corticosteroid-Binding Globulin (CBG) binding activity of the classic steroid data set, and the antibacterial activity of nitrofuran derivatives. The current procedure, which does not require molecular alignment, produces good r2 and q2 values. Moreover, it highlights regions in the common steroid skeleton deemed relevant to the active regions of the steroids and nitrofuran derivatives.

Comparison of 3D quantitative structure-activity relationship methods: Analysis of the in vitro antimalarial activity of 154 artemisinin analogues by hypothetical active-site lattice and comparative molecular field analysis

NASA Astrophysics Data System (ADS)

Woolfrey, John R.; Avery, Mitchell A.; Doweyko, Arthur M.

1998-03-01

Two three-dimensional quantitative structure-activity relationship (3D-QSAR) methods, comparative molecular field analysis (CoMFA) and hypothetical active site lattice (HASL), were compared with respect to the analysis of a training set of 154 artemisinin analogues. Five models were created, including a complete HASL and two trimmed versions, as well as two CoMFA models (leave-one-out standard CoMFA and the guided-region selection protocol). Similar r2 and q2 values were obtained by each method, although some striking differences existed between CoMFA contour maps and the HASL output. Each of the four predictive models exhibited a similar ability to predict the activity of a test set of 23 artemisinin analogues, although some differences were noted as to which compounds were described well by either model.

Megaregion freight movements : a case study of the Texas Triangle.

DOT National Transportation Integrated Search

2011-09-01

U.S. population growth is predicted to substantially increase over the next 40 years, particularly in areas with large regional economies forecasted to contain over two-thirds of the national economic activity. In Texas, population growth from 2000 t...

Time of Day Differences in Neural Reward Functioning in Healthy Young Men.

PubMed

Byrne, Jamie E M; Hughes, Matthew E; Rossell, Susan L; Johnson, Sheri L; Murray, Greg

2017-09-13

Reward function appears to be modulated by the circadian system, but little is known about the neural basis of this interaction. Previous research suggests that the neural reward response may be different in the afternoon; however, the direction of this effect is contentious. Reward response may follow the diurnal rhythm in self-reported positive affect, peaking in the early afternoon. An alternative is that daily reward response represents a type of prediction error, with neural reward activation relatively high at times of day when rewards are unexpected (i.e., early and late in the day). The present study measured neural reward activation in the context of a validated reward task at 10.00 h, 14.00 h, and 19.00 h in healthy human males. A region of interest BOLD fMRI protocol was used to investigate the diurnal waveform of activation in reward-related brain regions. Multilevel modeling found, as expected, a highly significant quadratic time-of-day effect focusing on the left putamen ( p < 0.001). Consistent with the "prediction error" hypothesis, activation was significantly higher at 10.00 h and 19.00 h compared with 14.00 h. It is provisionally concluded that the putamen may be particularly important in endogenous priming of reward motivation at different times of day, with the pattern of activation consistent with circadian-modulated reward expectancies in neural pathways (i.e., greater activation to reward stimuli at unexpected times of day). This study encourages further research into circadian modulation of reward and underscores the methodological importance of accounting for time of day in fMRI protocols. SIGNIFICANCE STATEMENT This is one of the first studies to use a repeated-measures imaging procedure to explore the diurnal rhythm of reward activation. Although self-reported reward (most often operationalized as positive affect) peaks in the afternoon, the present findings indicate that neural activation is lowest at this time. We conclude that the diurnal neural activation pattern may reflect a prediction error of the brain, where rewards at unexpected times (10.00 h and 19.00 h) elicit higher activation in reward brain regions than at expected (14.00 h) times. These data also have methodological significance, suggesting that there may be a time of day influence, which should be accounted for in neural reward studies. Copyright © 2017 the authors 0270-6474/17/378895-06$15.00/0.

Laser Remote Sensing at NASA

NASA Technical Reports Server (NTRS)

Barnes, Norman P.

2005-01-01

NASA is developing active remote sensors to monitor the health of Planet Earth and for exploration of other planets. Development and deployment of these remote sensors can have a huge economic impact. Lasers for these active remote sensors span the spectral range from the ultraviolet to the mid infrared spectral regions. Development activities range from quantum mechanical modeling and prediction of new laser materials to the design, development, and demonstration be deployed in the field.

A quantitative study of shape descriptors from glioblastoma multiforme phenotypes for predicting survival outcome

PubMed Central

Desrosiers, Christian; Hassan, Lama; Tanougast, Camel

2016-01-01

Objective: Predicting the survival outcome of patients with glioblastoma multiforme (GBM) is of key importance to clinicians for selecting the optimal course of treatment. The goal of this study was to evaluate the usefulness of geometric shape features, extracted from MR images, as a potential non-invasive way to characterize GBM tumours and predict the overall survival times of patients with GBM. Methods: The data of 40 patients with GBM were obtained from the Cancer Genome Atlas and Cancer Imaging Archive. The T1 weighted post-contrast and fluid-attenuated inversion-recovery volumes of patients were co-registered and segmented into delineate regions corresponding to three GBM phenotypes: necrosis, active tumour and oedema/invasion. A set of two-dimensional shape features were then extracted slicewise from each phenotype region and combined over slices to describe the three-dimensional shape of these phenotypes. Thereafter, a Kruskal–Wallis test was employed to identify shape features with significantly different distributions across phenotypes. Moreover, a Kaplan–Meier analysis was performed to find features strongly associated with GBM survival. Finally, a multivariate analysis based on the random forest model was used for predicting the survival group of patients with GBM. Results: Our analysis using the Kruskal–Wallis test showed that all but one shape feature had statistically significant differences across phenotypes, with p-value < 0.05, following Holm–Bonferroni correction, justifying the analysis of GBM tumour shapes on a per-phenotype basis. Furthermore, the survival analysis based on the Kaplan–Meier estimator identified three features derived from necrotic regions (i.e. Eccentricity, Extent and Solidity) that were significantly correlated with overall survival (corrected p-value < 0.05; hazard ratios between 1.68 and 1.87). In the multivariate analysis, features from necrotic regions gave the highest accuracy in predicting the survival group of patients, with a mean area under the receiver-operating characteristic curve (AUC) of 63.85%. Combining the features of all three phenotypes increased the mean AUC to 66.99%, suggesting that shape features from different phenotypes can be used in a synergic manner to predict GBM survival. Conclusion: Results show that shape features, in particular those extracted from necrotic regions, can be used effectively to characterize GBM tumours and predict the overall survival of patients with GBM. Advances in knowledge: Simple volumetric features have been largely used to characterize the different phenotypes of a GBM tumour (i.e. active tumour, oedema and necrosis). This study extends previous work by considering a wide range of shape features, extracted in different phenotypes, for the prediction of survival in patients with GBM. PMID:27781499

A brief history of Regional Warning Center China (RWC-China)

NASA Astrophysics Data System (ADS)

He, Han; Wang, Huaning; Du, Zhanle; Huang, Xin; Yan, Yan; Dai, Xinghua; Guo, Juan; Wang, Jialong

2018-03-01

Solar-terrestrial prediction services in China began in 1969 at the Beijing Astronomical Observatory (BAO), Chinese Academy of Sciences (CAS). In 1990, BAO joined the International URSIgram and World Days Service (IUWDS) and started solar-terrestrial data and prediction interchanges with other members of IUWDS. The short-term solar activity prediction service with standard URSIgram codes began in January 1991 at BAO, and forecasts have been issued routinely every weekday from then on. The Regional Warning Center Beijing (RWC-Beijing) of IUWDS was officially approved in China in 1991 and was formally established in February 1992. In 1996, the IUWDS was changed to the current name, the International Space Environment Service (ISES). In 2000, the RWC-Beijing was renamed RWC-China according to ISES requirements. In 2001, the National Astronomical Observatories, CAS (NAOC) was established. All the solar-terrestrial data and prediction services of BAO were taken up by NAOC. The headquarters of RWC-China is located on the campus of NAOC.

Fragments of a larger whole: retrieval cues constrain observed neural correlates of memory encoding.

PubMed

Otten, Leun J

2007-09-01

Laying down a new memory involves activity in a number of brain regions. Here, it is shown that the particular regions associated with successful encoding depend on the way in which memory is probed. Event-related functional magnetic resonance imaging signals were acquired while subjects performed an incidental encoding task on a series of visually presented words denoting objects. A recognition memory test using the Remember/Know procedure to separate responses based on recollection and familiarity followed 1 day later. Critically, half of the studied objects were cued with a corresponding spoken word, and half with a corresponding picture. Regardless of cue, activity in prefrontal and hippocampal regions predicted subsequent recollection of a word. Type of retrieval cue modulated activity in prefrontal, temporal, and parietal cortices. Words subsequently recognized on the basis of a sense of familiarity were at study also associated with differential activity in a number of brain regions, some of which were probe dependent. Thus, observed neural correlates of successful encoding are constrained by type of retrieval cue, and are only fragments of all encoding-related neural activity. Regions exhibiting cue-specific effects may be sites that support memory through the degree of overlap between the processes engaged during encoding and those engaged during retrieval.

Combining a Spatial Model and Demand Forecasts to Map Future Surface Coal Mining in Appalachia

PubMed Central

Strager, Michael P.; Strager, Jacquelyn M.; Evans, Jeffrey S.; Dunscomb, Judy K.; Kreps, Brad J.; Maxwell, Aaron E.

2015-01-01

Predicting the locations of future surface coal mining in Appalachia is challenging for a number of reasons. Economic and regulatory factors impact the coal mining industry and forecasts of future coal production do not specifically predict changes in location of future coal production. With the potential environmental impacts from surface coal mining, prediction of the location of future activity would be valuable to decision makers. The goal of this study was to provide a method for predicting future surface coal mining extents under changing economic and regulatory forecasts through the year 2035. This was accomplished by integrating a spatial model with production demand forecasts to predict (1 km2) gridded cell size land cover change. Combining these two inputs was possible with a ratio which linked coal extraction quantities to a unit area extent. The result was a spatial distribution of probabilities allocated over forecasted demand for the Appalachian region including northern, central, southern, and eastern Illinois coal regions. The results can be used to better plan for land use alterations and potential cumulative impacts. PMID:26090883

Predicting enhancer activity and variant impact using gkm-SVM.

PubMed

Beer, Michael A

2017-09-01

We participated in the Critical Assessment of Genome Interpretation eQTL challenge to further test computational models of regulatory variant impact and their association with human disease. Our prediction model is based on a discriminative gapped-kmer SVM (gkm-SVM) trained on genome-wide chromatin accessibility data in the cell type of interest. The comparisons with massively parallel reporter assays (MPRA) in lymphoblasts show that gkm-SVM is among the most accurate prediction models even though all other models used the MPRA data for model training, and gkm-SVM did not. In addition, we compare gkm-SVM with other MPRA datasets and show that gkm-SVM is a reliable predictor of expression and that deltaSVM is a reliable predictor of variant impact in K562 cells and mouse retina. We further show that DHS (DNase-I hypersensitive sites) and ATAC-seq (assay for transposase-accessible chromatin using sequencing) data are equally predictive substrates for training gkm-SVM, and that DHS regions flanked by H3K27Ac and H3K4me1 marks are more predictive than DHS regions alone. © 2017 Wiley Periodicals, Inc.

Computational study of β-N-acetylhexosaminidase from Talaromyces flavus, a glycosidase with high substrate flexibility.

PubMed

Kulik, Natallia; Slámová, Kristýna; Ettrich, Rüdiger; Křen, Vladimír

2015-01-28

β-N-Acetylhexosaminidase (GH20) from the filamentous fungus Talaromyces flavus, previously identified as a prominent enzyme in the biosynthesis of modified glycosides, lacks a high resolution three-dimensional structure so far. Despite of high sequence identity to previously reported Aspergillus oryzae and Penicilluim oxalicum β-N-acetylhexosaminidases, this enzyme tolerates significantly better substrate modification. Understanding of key structural features, prediction of effective mutants and potential substrate characteristics prior to their synthesis are of general interest. Computational methods including homology modeling and molecular dynamics simulations were applied to shad light on the structure-activity relationship in the enzyme. Primary sequence analysis revealed some variable regions able to influence difference in substrate affinity of hexosaminidases. Moreover, docking in combination with consequent molecular dynamics simulations of C-6 modified glycosides enabled us to identify the structural features required for accommodation and processing of these bulky substrates in the active site of hexosaminidase from T. flavus. To access the reliability of predictions on basis of the reported model, all results were confronted with available experimental data that demonstrated the principal correctness of the predictions as well as the model. The main variable regions in β-N-acetylhexosaminidases determining difference in modified substrate affinity are located close to the active site entrance and engage two loops. Differences in primary sequence and the spatial arrangement of these loops and their interplay with active site amino acids, reflected by interaction energies and dynamics, account for the different catalytic activity and substrate specificity of the various fungal and bacterial β-N-acetylhexosaminidases.

Multiple brain networks for visual self-recognition with different sensitivity for motion and body part.

PubMed

Sugiura, Motoaki; Sassa, Yuko; Jeong, Hyeonjeong; Miura, Naoki; Akitsuki, Yuko; Horie, Kaoru; Sato, Shigeru; Kawashima, Ryuta

2006-10-01

Multiple brain networks may support visual self-recognition. It has been hypothesized that the left ventral occipito-temporal cortex processes one's own face as a symbol, and the right parieto-frontal network processes self-image in association with motion-action contingency. Using functional magnetic resonance imaging, we first tested these hypotheses based on the prediction that these networks preferentially respond to a static self-face and to moving one's whole body, respectively. Brain activation specifically related to self-image during familiarity judgment was compared across four stimulus conditions comprising a two factorial design: factor Motion contrasted picture (Picture) and movie (Movie), and factor Body part a face (Face) and whole body (Body). Second, we attempted to segregate self-specific networks using a principal component analysis (PCA), assuming an independent pattern of inter-subject variability in activation over the four stimulus conditions in each network. The bilateral ventral occipito-temporal and the right parietal and frontal cortices exhibited self-specific activation. The left ventral occipito-temporal cortex exhibited greater self-specific activation for Face than for Body, in Picture, consistent with the prediction for this region. The activation profiles of the right parietal and frontal cortices did not show preference for Movie Body predicted by the assumed roles of these regions. The PCA extracted two cortical networks, one with its peaks in the right posterior, and another in frontal cortices; their possible roles in visuo-spatial and conceptual self-representations, respectively, were suggested by previous findings. The results thus supported and provided evidence of multiple brain networks for visual self-recognition.

Sexual sensation seeking and Internet sex-seeking of Middle Eastern men who have sex with men.

PubMed

Matarelli, Steven A

2013-10-01

Despite recent evidence of stabilization in many developed nations, new human immunodeficiency virus (HIV) infections remain a public health concern globally. Efforts remain fragile in a number of world regions due to incomplete or inconsistent social policies concerning HIV, criminalization of same-sex encounters, social stigma, and religious doctrine. Middle Eastern men who have sex with men (MSM) remain one of the most hidden and stigmatized of all HIV risk groups. High-risk sexual bridging networks from these men to low prevalence populations (e.g., to spouse to offspring) are emerging HIV transmission pathways throughout the region. This cross-sectional, exploratory study investigated Sexual Sensation Seeking Scale (SSSS) scores to predict numbers of recent MSM sexual activities and to predict any recent unprotected receptive anal intercourse (URAI) activities in 86 Middle Eastern MSM who resided in the Middle East and who used the Internet to sex-seek. In a multivariate hierarchical regression, higher SSSS scores predicted higher numbers of recent MSM sexual activities (p = .028) and URAI (p = .022). In a logistic regression, higher SSSS scores increased the likelihood of engaging in URAI activities threefold (OR 3.0, 95 % CI 1.15-7.85, p = .025). Age and drug/alcohol use during sexual activities served as covariates in the regression models and were not significant in any analyses. Despite numerous hurdles, adopting Internet-based, non-restricted HIV education and prevention public health programs in the Middle East could instrumentally enhance efforts toward reducing the likelihood of new HIV transmissions in MSM and their sexual partners, ultimately contributing to an improved quality of life.

An Integrative Perspective on the Role of Dopamine in Schizophrenia

PubMed Central

Maia, Tiago V.; Frank, Michael J.

2017-01-01

We propose that schizophrenia involves a combination of decreased phasic dopamine responses for relevant stimuli and increased spontaneous phasic dopamine release. Using insights from computational reinforcement-learning models and basic-science studies of the dopamine system, we show that each of these two disturbances contributes to a specific symptom domain and explains a large set of experimental findings associated with that domain. Reduced phasic responses for relevant stimuli help to explain negative symptoms and provide a unified explanation for the following experimental findings in schizophrenia, most of which have been shown to correlate with negative symptoms: reduced learning from rewards; blunted activation of the ventral striatum, midbrain, and other limbic regions for rewards and positive prediction errors; blunted activation of the ventral striatum during reward anticipation; blunted autonomic responding for relevant stimuli; blunted neural activation for aversive outcomes and aversive prediction errors; reduced willingness to expend effort for rewards; and psychomotor slowing. Increased spontaneous phasic dopamine release helps to explain positive symptoms and provides a unified explanation for the following experimental findings in schizophrenia, most of which have been shown to correlate with positive symptoms: aberrant learning for neutral cues (assessed with behavioral and autonomic responses), and aberrant, increased activation of the ventral striatum, midbrain, and other limbic regions for neutral cues, neutral outcomes, and neutral prediction errors. Taken together, then, these two disturbances explain many findings in schizophrenia. We review evidence supporting their co-occurrence and consider their differential implications for the treatment of positive and negative symptoms. PMID:27452791

Accumulation of transposable elements in Hox gene clusters during adaptive radiation of Anolis lizards.

PubMed

Feiner, Nathalie

2016-10-12

Transposable elements (TEs) are DNA sequences that can insert elsewhere in the genome and modify genome structure and gene regulation. The role of TEs in evolution is contentious. One hypothesis posits that TE activity generates genomic incompatibilities that can cause reproductive isolation between incipient species. This predicts that TEs will accumulate during speciation events. Here, I tested the prediction that extant lineages with a relatively high rate of speciation have a high number of TEs in their genomes. I sequenced and analysed the TE content of a marker genomic region (Hox clusters) in Anolis lizards, a classic case of an adaptive radiation. Unlike other vertebrates, including closely related lizards, Anolis lizards have high numbers of TEs in their Hox clusters, genomic regions that regulate development of the morphological adaptations that characterize habitat specialists in these lizards. Following a burst of TE activity in the lineage leading to extant Anolis, TEs have continued to accumulate during or after speciation events, resulting in a positive relationship between TE density and lineage speciation rate. These results are consistent with the prediction that TE activity contributes to adaptive radiation by promoting speciation. Although there was no evidence that TE density per se is associated with ecological morphology, the activity of TEs in Hox clusters could have been a rich source for phenotypic variation that may have facilitated the rapid parallel morphological adaptation to microhabitats seen in extant Anolis lizards. © 2016 The Author(s).

Accumulation of transposable elements in Hox gene clusters during adaptive radiation of Anolis lizards

PubMed Central

2016-01-01

Transposable elements (TEs) are DNA sequences that can insert elsewhere in the genome and modify genome structure and gene regulation. The role of TEs in evolution is contentious. One hypothesis posits that TE activity generates genomic incompatibilities that can cause reproductive isolation between incipient species. This predicts that TEs will accumulate during speciation events. Here, I tested the prediction that extant lineages with a relatively high rate of speciation have a high number of TEs in their genomes. I sequenced and analysed the TE content of a marker genomic region (Hox clusters) in Anolis lizards, a classic case of an adaptive radiation. Unlike other vertebrates, including closely related lizards, Anolis lizards have high numbers of TEs in their Hox clusters, genomic regions that regulate development of the morphological adaptations that characterize habitat specialists in these lizards. Following a burst of TE activity in the lineage leading to extant Anolis, TEs have continued to accumulate during or after speciation events, resulting in a positive relationship between TE density and lineage speciation rate. These results are consistent with the prediction that TE activity contributes to adaptive radiation by promoting speciation. Although there was no evidence that TE density per se is associated with ecological morphology, the activity of TEs in Hox clusters could have been a rich source for phenotypic variation that may have facilitated the rapid parallel morphological adaptation to microhabitats seen in extant Anolis lizards. PMID:27733546

Predicting Solar Activity Using Machine-Learning Methods

NASA Astrophysics Data System (ADS)

Bobra, M.

2017-12-01

Of all the activity observed on the Sun, two of the most energetic events are flares and coronal mass ejections. However, we do not, as of yet, fully understand the physical mechanism that triggers solar eruptions. A machine-learning algorithm, which is favorable in cases where the amount of data is large, is one way to [1] empirically determine the signatures of this mechanism in solar image data and [2] use them to predict solar activity. In this talk, we discuss the application of various machine learning algorithms - specifically, a Support Vector Machine, a sparse linear regression (Lasso), and Convolutional Neural Network - to image data from the photosphere, chromosphere, transition region, and corona taken by instruments aboard the Solar Dynamics Observatory in order to predict solar activity on a variety of time scales. Such an approach may be useful since, at the present time, there are no physical models of flares available for real-time prediction. We discuss our results (Bobra and Couvidat, 2015; Bobra and Ilonidis, 2016; Jonas et al., 2017) as well as other attempts to predict flares using machine-learning (e.g. Ahmed et al., 2013; Nishizuka et al. 2017) and compare these results with the more traditional techniques used by the NOAA Space Weather Prediction Center (Crown, 2012). We also discuss some of the challenges in using machine-learning algorithms for space science applications.

Vulnerability of Coastal Wetlands in the Southeastern United States: Climate Change Research Results, 1992-97.

DTIC Science & Technology

1998-09-01

pro- jected to have significant regional impacts on resource management and use of these public lands . Southeastern coastal wetlands have also... land tree and shrub species. Measures of plant physiological activity using experi- mentally simulated environmental conditions predicted to occur...Hence, short- term rates of marsh transgression may be meaningless and may not be useful tools to predict wetland habitat change, at least for some

Cross-modal activation of auditory regions during visuo-spatial working memory in early deafness.

PubMed

Ding, Hao; Qin, Wen; Liang, Meng; Ming, Dong; Wan, Baikun; Li, Qiang; Yu, Chunshui

2015-09-01

Early deafness can reshape deprived auditory regions to enable the processing of signals from the remaining intact sensory modalities. Cross-modal activation has been observed in auditory regions during non-auditory tasks in early deaf subjects. In hearing subjects, visual working memory can evoke activation of the visual cortex, which further contributes to behavioural performance. In early deaf subjects, however, whether and how auditory regions participate in visual working memory remains unclear. We hypothesized that auditory regions may be involved in visual working memory processing and activation of auditory regions may contribute to the superior behavioural performance of early deaf subjects. In this study, 41 early deaf subjects (22 females and 19 males, age range: 20-26 years, age of onset of deafness < 2 years) and 40 age- and gender-matched hearing controls underwent functional magnetic resonance imaging during a visuo-spatial delayed recognition task that consisted of encoding, maintenance and recognition stages. The early deaf subjects exhibited faster reaction times on the spatial working memory task than did the hearing controls. Compared with hearing controls, deaf subjects exhibited increased activation in the superior temporal gyrus bilaterally during the recognition stage. This increased activation amplitude predicted faster and more accurate working memory performance in deaf subjects. Deaf subjects also had increased activation in the superior temporal gyrus bilaterally during the maintenance stage and in the right superior temporal gyrus during the encoding stage. These increased activation amplitude also predicted faster reaction times on the spatial working memory task in deaf subjects. These findings suggest that cross-modal plasticity occurs in auditory association areas in early deaf subjects. These areas are involved in visuo-spatial working memory. Furthermore, amplitudes of cross-modal activation during the maintenance stage were positively correlated with the age of onset of hearing aid use and were negatively correlated with the percentage of lifetime hearing aid use in deaf subjects. These findings suggest that earlier and longer hearing aid use may inhibit cross-modal reorganization in early deaf subjects. Granger causality analysis revealed that, compared to the hearing controls, the deaf subjects had an enhanced net causal flow from the frontal eye field to the superior temporal gyrus. These findings indicate that a top-down mechanism may better account for the cross-modal activation of auditory regions in early deaf subjects.See MacSweeney and Cardin (doi:10/1093/awv197) for a scientific commentary on this article. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Predicting emissions from oil and gas operations in the Uinta Basin, Utah.

PubMed

Wilkey, Jonathan; Kelly, Kerry; Jaramillo, Isabel Cristina; Spinti, Jennifer; Ring, Terry; Hogue, Michael; Pasqualini, Donatella

2016-05-01

In this study, emissions of ozone precursors from oil and gas operations in Utah's Uinta Basin are predicted (with uncertainty estimates) from 2015-2019 using a Monte-Carlo model of (a) drilling and production activity, and (b) emission factors. Cross-validation tests against actual drilling and production data from 2010-2014 show that the model can accurately predict both types of activities, returning median results that are within 5% of actual values for drilling, 0.1% for oil production, and 4% for gas production. A variety of one-time (drilling) and ongoing (oil and gas production) emission factors for greenhouse gases, methane, and volatile organic compounds (VOCs) are applied to the predicted oil and gas operations. Based on the range of emission factor values reported in the literature, emissions from well completions are the most significant source of emissions, followed by gas transmission and production. We estimate that the annual average VOC emissions rate for the oil and gas industry over the 2010-2015 time period was 44.2E+06 (mean) ± 12.8E+06 (standard deviation) kg VOCs per year (with all applicable emissions reductions). On the same basis, over the 2015-2019 period annual average VOC emissions from oil and gas operations are expected to drop 45% to 24.2E+06 ± 3.43E+06 kg VOCs per year, due to decreases in drilling activity and tighter emission standards. This study improves upon previous methods for estimating emissions of ozone precursors from oil and gas operations in Utah's Uinta Basin by tracking one-time and ongoing emission events on a well-by-well basis. The proposed method has proven highly accurate at predicting drilling and production activity and includes uncertainty estimates to describe the range of potential emissions inventory outcomes. If similar input data are available in other oil and gas producing regions, then the method developed here could be applied to those regions as well.

Activation Time of Cardiac Tissue In Response to a Linear Array of Spatial Alternating Bipolar Electrodes

NASA Astrophysics Data System (ADS)

Mashburn, David; Wikswo, John

2007-11-01

Prevailing theories about the response of the heart to high field shocks predict that local regions of high resistivity distributed throughout the heart create multiple small virtual electrodes that hyperpolarize or depolarize tissue and lead to widespread activation. This resetting of bulk tissue is responsible for the successful functioning of cardiac defibrillators. By activating cardiac tissue with regular linear arrays of spatially alternating bipolar currents, we can simulate these potentials locally. We have studied the activation time due to distributed currents in both a 1D Beeler-Reuter model and on the surface of the whole heart, varying the strength of each source and the separation between them. By comparison with activation time data from actual field shock of a whole heart in a bath, we hope to better understand these transient virtual electrodes. Our work was done on rabbit RV using florescent optical imaging and our Phased Array Stimulator for driving the 16 current sources. Our model shows that for a total absolute current delivered to a region of tissue, the entire region activates faster if above-threshold sources are more distributed.

Measurement of the underlying event activity using charged-particle jets in proton-proton collisions at $$\\sqrt{s}$$ = 2.76 TeV

DOE PAGES

Khachatryan, V.

2015-09-21

A measurement of the underlying event (UE) activity in proton-proton collisions is performed using events with charged-particle jets produced in the central pseudorapidity region (|η jet| < 2) and with transverse momentum 1 ≤ p T jet < 100 GeV. The analysis uses a data sample collected at a centre-of-mass energy of 2.76 TeV with the CMS experiment at the LHC. The UE activity is measured as a function of p T jet in terms of the average multiplicity and scalar sum of transverse momenta (p T) of charged particles, with |η| < 2 and p T >more » 0.5 GeV, in the azimuthal region transverse to the highest p T jet direction. By further dividing the transverse region into two regions of smaller and larger activity, various components of the UE activity are separated. As a result, the measurements are compared to previous results at 0.9 and 7 TeV, and to predictions of several Monte Carlo event generators, providing constraints on the modelling of the UE dynamics« less

The Neural Correlates of Hierarchical Predictions for Perceptual Decisions.

PubMed

Weilnhammer, Veith A; Stuke, Heiner; Sterzer, Philipp; Schmack, Katharina

2018-05-23

Sensory information is inherently noisy, sparse, and ambiguous. In contrast, visual experience is usually clear, detailed, and stable. Bayesian theories of perception resolve this discrepancy by assuming that prior knowledge about the causes underlying sensory stimulation actively shapes perceptual decisions. The CNS is believed to entertain a generative model aligned to dynamic changes in the hierarchical states of our volatile sensory environment. Here, we used model-based fMRI to study the neural correlates of the dynamic updating of hierarchically structured predictions in male and female human observers. We devised a crossmodal associative learning task with covertly interspersed ambiguous trials in which participants engaged in hierarchical learning based on changing contingencies between auditory cues and visual targets. By inverting a Bayesian model of perceptual inference, we estimated individual hierarchical predictions, which significantly biased perceptual decisions under ambiguity. Although "high-level" predictions about the cue-target contingency correlated with activity in supramodal regions such as orbitofrontal cortex and hippocampus, dynamic "low-level" predictions about the conditional target probabilities were associated with activity in retinotopic visual cortex. Our results suggest that our CNS updates distinct representations of hierarchical predictions that continuously affect perceptual decisions in a dynamically changing environment. SIGNIFICANCE STATEMENT Bayesian theories posit that our brain entertains a generative model to provide hierarchical predictions regarding the causes of sensory information. Here, we use behavioral modeling and fMRI to study the neural underpinnings of such hierarchical predictions. We show that "high-level" predictions about the strength of dynamic cue-target contingencies during crossmodal associative learning correlate with activity in orbitofrontal cortex and the hippocampus, whereas "low-level" conditional target probabilities were reflected in retinotopic visual cortex. Our findings empirically corroborate theorizations on the role of hierarchical predictions in visual perception and contribute substantially to a longstanding debate on the link between sensory predictions and orbitofrontal or hippocampal activity. Our work fundamentally advances the mechanistic understanding of perceptual inference in the human brain. Copyright © 2018 the authors 0270-6474/18/385008-14$15.00/0.

Neural activity during affect labeling predicts expressive writing effects on well-being: GLM and SVM approaches

PubMed Central

Memarian, Negar; Torre, Jared B.; Haltom, Kate E.; Stanton, Annette L.

2017-01-01

Abstract Affect labeling (putting feelings into words) is a form of incidental emotion regulation that could underpin some benefits of expressive writing (i.e. writing about negative experiences). Here, we show that neural responses during affect labeling predicted changes in psychological and physical well-being outcome measures 3 months later. Furthermore, neural activity of specific frontal regions and amygdala predicted those outcomes as a function of expressive writing. Using supervised learning (support vector machines regression), improvements in four measures of psychological and physical health (physical symptoms, depression, anxiety and life satisfaction) after an expressive writing intervention were predicted with an average of 0.85% prediction error [root mean square error (RMSE) %]. The predictions were significantly more accurate with machine learning than with the conventional generalized linear model method (average RMSE: 1.3%). Consistent with affect labeling research, right ventrolateral prefrontal cortex (RVLPFC) and amygdalae were top predictors of improvement in the four outcomes. Moreover, RVLPFC and left amygdala predicted benefits due to expressive writing in satisfaction with life and depression outcome measures, respectively. This study demonstrates the substantial merit of supervised machine learning for real-world outcome prediction in social and affective neuroscience. PMID:28992270

Predictions interact with missing sensory evidence in semantic processing areas.

PubMed

Scharinger, Mathias; Bendixen, Alexandra; Herrmann, Björn; Henry, Molly J; Mildner, Toralf; Obleser, Jonas

2016-02-01

Human brain function draws on predictive mechanisms that exploit higher-level context during lower-level perception. These mechanisms are particularly relevant for situations in which sensory information is compromised or incomplete, as for example in natural speech where speech segments may be omitted due to sluggish articulation. Here, we investigate which brain areas support the processing of incomplete words that were predictable from semantic context, compared with incomplete words that were unpredictable. During functional magnetic resonance imaging (fMRI), participants heard sentences that orthogonally varied in predictability (semantically predictable vs. unpredictable) and completeness (complete vs. incomplete, i.e. missing their final consonant cluster). The effects of predictability and completeness interacted in heteromodal semantic processing areas, including left angular gyrus and left precuneus, where activity did not differ between complete and incomplete words when they were predictable. The same regions showed stronger activity for incomplete than for complete words when they were unpredictable. The interaction pattern suggests that for highly predictable words, the speech signal does not need to be complete for neural processing in semantic processing areas. Hum Brain Mapp 37:704-716, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Pollinator communities in strawberry crops - variation at multiple spatial scales.

PubMed

Ahrenfeldt, E J; Klatt, B K; Arildsen, J; Trandem, N; Andersson, G K S; Tscharntke, T; Smith, H G; Sigsgaard, L

2015-08-01

Predicting potential pollination services of wild bees in crops requires knowledge of their spatial distribution within fields. Field margins can serve as nesting and foraging habitats for wild bees and can be a source of pollinators. Regional differences in pollinator community composition may affect this spill-over of bees. We studied how regional and local differences affect the spatial distribution of wild bee species richness, activity-density and body size in crop fields. We sampled bees both from the field centre and at two different types of semi-natural field margins, grass strips and hedges, in 12 strawberry fields. The fields were distributed over four regions in Northern Europe, representing an almost 1100 km long north-south gradient. Even over this gradient, daytime temperatures during sampling did not differ significantly between regions and did therefore probably not impact bee activity. Bee species richness was higher in field margins compared with field centres independent of field size. However, there was no difference between centre and margin in body-size or activity-density. In contrast, bee activity-density increased towards the southern regions, whereas the mean body size increased towards the north. In conclusion, our study revealed a general pattern across European regions of bee diversity, but not activity-density, declining towards the field interior which suggests that the benefits of functional diversity of pollinators may be difficult to achieve through spill-over effects from margins to crop. We also identified dissimilar regional patterns in bee diversity and activity-density, which should be taken into account in conservation management.

The role of the thalamus and hippocampus in episodic memory performance in patients with multiple sclerosis.

PubMed

Koenig, Katherine A; Rao, Stephen M; Lowe, Mark J; Lin, Jian; Sakaie, Ken E; Stone, Lael; Bermel, Robert A; Trapp, Bruce D; Phillips, Micheal D

2018-03-01

Episodic memory loss is one of the most common cognitive symptoms in patients with multiple sclerosis (MS), but the pathophysiology of this symptom remains unclear. Both the hippocampus and thalamus have been implicated in episodic memory and show regional atrophy in patients with MS. In this work, we used functional magnetic resonance imaging (fMRI) during a verbal episodic memory task, lesion load, and volumetric measures of the hippocampus and thalamus to assess the relative contributions to verbal and visual-spatial episodic memory. Functional activation, lesion load, and volumetric measures from 32 patients with MS and 16 healthy controls were used in a predictive analysis of episodic memory function. After adjusting for disease duration, immediate recall performance on a visual-spatial episodic memory task was significantly predicted by hippocampal volume ( p < 0.003). Delayed recall on the same task was significantly predicted by volume of the left thalamus ( p < 0.003). For both memory measures, functional activation of the thalamus during encoding was more predictive than that of volume measures ( p < 0.002). Our results suggest that functional activation may be useful as a predictive measure of episodic memory loss in patients with MS.

High Resolution Forecasts in the Florida Straits: Predicting the Modulations of the Florida Current and Connectivity Around South Florida and Cuba

NASA Astrophysics Data System (ADS)

Kourafalou, V.; Kang, H.; Perlin, N.; Le Henaff, M.; Lamkin, J. T.

2016-02-01

Connectivity around the South Florida coastal regions and between South Florida and Cuba are largely influenced by a) local coastal processes and b) circulation in the Florida Straits, which is controlled by the larger scale Florida Current variability. Prediction of the physical connectivity is a necessary component for several activities that require ocean forecasts, such as oil spills, fisheries research, search and rescue. This requires a predictive system that can accommodate the intense coastal to offshore interactions and the linkages to the complex regional circulation. The Florida Straits, South Florida and Florida Keys Hybrid Coordinate Ocean Model is such a regional ocean predictive system, covering a large area over the Florida Straits and the adjacent land areas, representing both coastal and oceanic processes. The real-time ocean forecast system is high resolution ( 900m), embedded in larger scale predictive models. It includes detailed coastal bathymetry, high resolution/high frequency atmospheric forcing and provides 7-day forecasts, updated daily (see: http://coastalmodeling.rsmas.miami.edu/). The unprecedented high resolution and coastal details of this system provide value added on global forecasts through downscaling and allow a variety of applications. Examples will be presented, focusing on the period of a 2015 fisheries cruise around the coastal areas of Cuba, where model predictions helped guide the measurements on biophysical connectivity, under intense variability of the mesoscale eddy field and subsequent Florida Current meandering.

Observations of magnetic fields on solar-type stars

NASA Technical Reports Server (NTRS)

Marcy, G. W.

1982-01-01

Magnetic-field observations were carried out for 29 G and K main-sequence stars. The area covering-factors of magnetic regions tends to be greater in the K dwarfs than in the G dwarfs. However, no spectral-type dependence is found for the field strengths, contrary to predictions that pressure equilibrium with the ambient photospheric gas pressure would determine the surface field strengths. Coronal soft X-ray fluxes from the G and K dwarfs correlate well with the fraction of the stellar surface covered by magnetic regions. The dependence of coronal soft X-ray fluxes on photospheric field strengths is consistent with Stein's predicted generation-rates for Alfven waves. These dependences are inconsistent with the one dynamo model for which a specific prediction is offered. Finally, time variability of magnetic fields is seen on the two active stars that have been extensively monitored. Significant changes in magnetic fields are seen to occur on timescales as short as one day.

Changing Arctic snow cover: A review of recent developments and assessment of future needs for observations, modelling, and impacts.

PubMed

Bokhorst, Stef; Pedersen, Stine Højlund; Brucker, Ludovic; Anisimov, Oleg; Bjerke, Jarle W; Brown, Ross D; Ehrich, Dorothee; Essery, Richard L H; Heilig, Achim; Ingvander, Susanne; Johansson, Cecilia; Johansson, Margareta; Jónsdóttir, Ingibjörg Svala; Inga, Niila; Luojus, Kari; Macelloni, Giovanni; Mariash, Heather; McLennan, Donald; Rosqvist, Gunhild Ninis; Sato, Atsushi; Savela, Hannele; Schneebeli, Martin; Sokolov, Aleksandr; Sokratov, Sergey A; Terzago, Silvia; Vikhamar-Schuler, Dagrun; Williamson, Scott; Qiu, Yubao; Callaghan, Terry V

2016-09-01

Snow is a critically important and rapidly changing feature of the Arctic. However, snow-cover and snowpack conditions change through time pose challenges for measuring and prediction of snow. Plausible scenarios of how Arctic snow cover will respond to changing Arctic climate are important for impact assessments and adaptation strategies. Although much progress has been made in understanding and predicting snow-cover changes and their multiple consequences, many uncertainties remain. In this paper, we review advances in snow monitoring and modelling, and the impact of snow changes on ecosystems and society in Arctic regions. Interdisciplinary activities are required to resolve the current limitations on measuring and modelling snow characteristics through the cold season and at different spatial scales to assure human well-being, economic stability, and improve the ability to predict manage and adapt to natural hazards in the Arctic region.

Model and observation comparison of the universal time and IMF by dependence of the ionospheric polar hole

NASA Technical Reports Server (NTRS)

Sojka, J. J.; Schunk, R. W.; Hoegy, W. R.; Grebowsky, J. M.

1991-01-01

The polar ionospheric F-region often exhibits regions of marked density depletion. These depletions have been observed by a variety of polar orbiting ionospheric satellites over a full range of solar cycle, season, magnetic activity, and universal time (UT). An empirical model of these observations has recently been developed to describe the polar depletion dependence on these parameters. Specifically, the dependence has been defined as a function of F10.7 (solar), summer or winter, Kp (magnetic), and UT. Polar cap depletions have also been predicted /1, 2/ and are, hence, present in physical models of the high latitude ionosphere. Using the Utah State University Time Dependent Ionospheric Model (TDIM) the predicted polar depletion characteristics are compared with those described by the above empirical model. In addition, the TDIM is used to predict the IMF By dependence of the polar hole feature.

Changing Arctic Snow Cover: A Review of Recent Developments and Assessment of Future Needs for Observations, Modelling, and Impacts

NASA Technical Reports Server (NTRS)

Bokhorst, Stef; Pedersen, Stine Hojlund; Brucker, Ludovic; Anisimov, Oleg; Bjerke, Jarle W.; Brown, Ross D.; Ehrich, Dorothee; Essery, Richard L. H.; Heilig, Achim; Ingvander, Susanne;

In Silico Prediction and In Vitro Characterization of Multifunctional Human RNase3

PubMed Central

Kuo, Ping-Hsueh; Chen, Chien-Jung; Chang, Hsiu-Hui; Fang, Shun-lung; Wu, Wei-Shuo; Lai, Yiu-Kay; Pai, Tun-Wen; Chang, Margaret Dah-Tsyr

2013-01-01

Human ribonucleases A (hRNaseA) superfamily consists of thirteen members with high-structure similarities but exhibits divergent physiological functions other than RNase activity. Evolution of hRNaseA superfamily has gained novel functions which may be preserved in a unique region or domain to account for additional molecular interactions. hRNase3 has multiple functions including ribonucleolytic, heparan sulfate (HS) binding, cellular binding, endocytic, lipid destabilization, cytotoxic, and antimicrobial activities. In this study, three putative multifunctional regions, 34RWRCK38 (HBR1), 75RSRFR79 (HBR2), and 101RPGRR105 (HBR3), of hRNase3 have been identified employing in silico sequence analysis and validated employing in vitro activity assays. A heparin binding peptide containing HBR1 is characterized to act as a key element associated with HS binding, cellular binding, and lipid binding activities. In this study, we provide novel insights to identify functional regions of hRNase3 that may have implications for all hRNaseA superfamily members. PMID:23484086

Does the Sound of a Barking Dog Activate its Corresponding Visual Form? An fMRI Investigation of Modality-Specific Semantic Access

PubMed Central

Reilly, Jamie; Garcia, Amanda; Binney, Richard J.

2016-01-01

Much remains to be learned about the neural architecture underlying word meaning. Fully distributed models of semantic memory predict that the sound of a barking dog will conjointly engage a network of distributed sensorimotor spokes. An alternative framework holds that modality-specific features additionally converge within transmodal hubs. Participants underwent functional MRI while covertly naming familiar objects versus newly learned novel objects from only one of their constituent semantic features (visual form, characteristic sound, or point-light motion representation). Relative to the novel object baseline, familiar concepts elicited greater activation within association regions specific to that presentation modality. Furthermore, visual form elicited activation within high-level auditory association cortex. Conversely, environmental sounds elicited activation in regions proximal to visual association cortex. Both conditions commonly engaged a putative hub region within lateral anterior temporal cortex. These results support hybrid semantic models in which local hubs and distributed spokes are dually engaged in service of semantic memory. PMID:27289210

HARPs: Tracked Active Region Patch Data Product from SDO/HMI

NASA Astrophysics Data System (ADS)

Turmon, M.; Hoeksema, J. T.; Sun, X.; Bobra, M.

2012-12-01

We describe an HMI data product consisting of tracked magnetic features on the scale of solar active regions, abbreviated HARPs (HMI Active Region Patches). The HARP data series has been helpful for subsetting individual active regions, for development of near-real-time (NRT) space weather indices for individual active regions, and for defining closed magnetic structures for computationally-intensive algorithms like vector field disambiguation. The data series builds upon the 720s cadence activity masks, which identify large-scale instantaneously-observed magnetic features. Using these masks as a starting point, large spatially-coherent structures are identified using convolution with a longitudinally-extended kernel on a spherical domain. The resulting set of identified regions is then tracked from image to image. The metric for inter-image association is area of overlap between the best current estimate of AR location, as predicted by temporally extrapolating each currently tracked object, and the set of instantaneously-observed magnetic structures. Once completed tracks have been extracted, they are made into a standardized HARP data series by finding the smallest constant-angular-velocity box, of constant width in latitude and longitude, that encompasses all appearances of the active region. This data product is currently available, in definitive and near-real-time forms, with accompanying region-strength, location, and NOAA-AR metadata, on HMI's Joint Science Operations Center (JSOC) data portal.; HARP outlines for three days (2001 February 14, 15, and 16, 00:00 TAI, flipped N-S, selected from the 12-minute cadence original data product). HARPs are shown in the same color (some colors repeated) with a thin white box surrounding each HARP. HARPs are tracked and associated from image to image. HARPs, such as the yellow one in the images above, need not be connected regions. Merges and splits, such as the light blue region, are accounted for automatically.

Development of Prediction Model and Experimental Validation in Predicting the Curcumin Content of Turmeric (Curcuma longa L.).

PubMed

Akbar, Abdul; Kuanar, Ananya; Joshi, Raj K; Sandeep, I S; Mohanty, Sujata; Naik, Pradeep K; Mishra, Antaryami; Nayak, Sanghamitra

2016-01-01

The drug yielding potential of turmeric ( Curcuma longa L.) is largely due to the presence of phyto-constituent 'curcumin.' Curcumin has been found to possess a myriad of therapeutic activities ranging from anti-inflammatory to neuroprotective. Lack of requisite high curcumin containing genotypes and variation in the curcumin content of turmeric at different agro climatic regions are the major stumbling blocks in commercial production of turmeric. Curcumin content of turmeric is greatly influenced by environmental factors. Hence, a prediction model based on artificial neural network (ANN) was developed to map genome environment interaction basing on curcumin content, soli and climatic factors from different agroclimatic regions for prediction of maximum curcumin content at various sites to facilitate the selection of suitable region for commercial cultivation of turmeric. The ANN model was developed and tested using a data set of 119 generated by collecting samples from 8 different agroclimatic regions of Odisha. The curcumin content from these samples was measured that varied from 7.2% to 0.4%. The ANN model was trained with 11 parameters of soil and climatic factors as input and curcumin content as output. The results showed that feed-forward ANN model with 8 nodes (MLFN-8) was the most suitable one with R 2 value of 0.91. Sensitivity analysis revealed that minimum relative humidity, altitude, soil nitrogen content and soil pH had greater effect on curcumin content. This ANN model has shown proven efficiency for predicting and optimizing the curcumin content at a specific site.

Development of Prediction Model and Experimental Validation in Predicting the Curcumin Content of Turmeric (Curcuma longa L.)

PubMed Central

Akbar, Abdul; Kuanar, Ananya; Joshi, Raj K.; Sandeep, I. S.; Mohanty, Sujata; Naik, Pradeep K.; Mishra, Antaryami; Nayak, Sanghamitra

2016-01-01

The drug yielding potential of turmeric (Curcuma longa L.) is largely due to the presence of phyto-constituent ‘curcumin.’ Curcumin has been found to possess a myriad of therapeutic activities ranging from anti-inflammatory to neuroprotective. Lack of requisite high curcumin containing genotypes and variation in the curcumin content of turmeric at different agro climatic regions are the major stumbling blocks in commercial production of turmeric. Curcumin content of turmeric is greatly influenced by environmental factors. Hence, a prediction model based on artificial neural network (ANN) was developed to map genome environment interaction basing on curcumin content, soli and climatic factors from different agroclimatic regions for prediction of maximum curcumin content at various sites to facilitate the selection of suitable region for commercial cultivation of turmeric. The ANN model was developed and tested using a data set of 119 generated by collecting samples from 8 different agroclimatic regions of Odisha. The curcumin content from these samples was measured that varied from 7.2% to 0.4%. The ANN model was trained with 11 parameters of soil and climatic factors as input and curcumin content as output. The results showed that feed-forward ANN model with 8 nodes (MLFN-8) was the most suitable one with R2 value of 0.91. Sensitivity analysis revealed that minimum relative humidity, altitude, soil nitrogen content and soil pH had greater effect on curcumin content. This ANN model has shown proven efficiency for predicting and optimizing the curcumin content at a specific site. PMID:27766103

Load-related brain activation predicts spatial working memory performance in youth aged 9–12 and is associated with executive function at earlier ages

PubMed Central

Huang, Anna S.; Klein, Daniel N.; Leung, Hoi-Chung

2015-01-01

Spatial working memory is a central cognitive process that matures through adolescence in conjunction with major changes in brain function and anatomy. Here we focused on late childhood and early adolescence to more closely examine the neural correlates of performance variability during this important transition period. Using a modified spatial 1-back task with two memory load conditions in an fMRI study, we examined the relationship between load-dependent neural responses and task performance in a sample of 39 youth aged 9–12 years. Our data revealed that between-subject differences in task performance was predicted by load-dependent deactivation in default network regions, including the ventral anterior cingulate cortex (vACC) and posterior cingulate cortex (PCC). Although load-dependent increases in activation in prefrontal and posterior parietal regions were only weakly correlated with performance, increased prefrontal-parietal coupling was associated with better performance. Furthermore, behavioral measures of executive function from as early as age 3 predicted current load-dependent deactivation in vACC and PCC. These findings suggest that both task positive and task negative brain activation during spatial working memory contributed to successful task performance in late childhood/early adolescence. This may serve as a good model for studying executive control deficits in developmental disorders. PMID:26562059

Load-related brain activation predicts spatial working memory performance in youth aged 9-12 and is associated with executive function at earlier ages.

PubMed

Huang, Anna S; Klein, Daniel N; Leung, Hoi-Chung

2016-02-01

Spatial working memory is a central cognitive process that matures through adolescence in conjunction with major changes in brain function and anatomy. Here we focused on late childhood and early adolescence to more closely examine the neural correlates of performance variability during this important transition period. Using a modified spatial 1-back task with two memory load conditions in an fMRI study, we examined the relationship between load-dependent neural responses and task performance in a sample of 39 youth aged 9-12 years. Our data revealed that between-subject differences in task performance was predicted by load-dependent deactivation in default network regions, including the ventral anterior cingulate cortex (vACC) and posterior cingulate cortex (PCC). Although load-dependent increases in activation in prefrontal and posterior parietal regions were only weakly correlated with performance, increased prefrontal-parietal coupling was associated with better performance. Furthermore, behavioral measures of executive function from as early as age 3 predicted current load-dependent deactivation in vACC and PCC. These findings suggest that both task positive and task negative brain activation during spatial working memory contributed to successful task performance in late childhood/early adolescence. This may serve as a good model for studying executive control deficits in developmental disorders. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Flare Prediction Using Photospheric and Coronal Image Data

NASA Astrophysics Data System (ADS)

Jonas, Eric; Bobra, Monica; Shankar, Vaishaal; Todd Hoeksema, J.; Recht, Benjamin

2018-03-01

The precise physical process that triggers solar flares is not currently understood. Here we attempt to capture the signature of this mechanism in solar-image data of various wavelengths and use these signatures to predict flaring activity. We do this by developing an algorithm that i) automatically generates features in 5.5 TB of image data taken by the Solar Dynamics Observatory of the solar photosphere, chromosphere, transition region, and corona during the time period between May 2010 and May 2014, ii) combines these features with other features based on flaring history and a physical understanding of putative flaring processes, and iii) classifies these features to predict whether a solar active region will flare within a time period of T hours, where T = 2 and 24. Such an approach may be useful since, at the present time, there are no physical models of flares available for real-time prediction. We find that when optimizing for the True Skill Score (TSS), photospheric vector-magnetic-field data combined with flaring history yields the best performance, and when optimizing for the area under the precision-recall curve, all of the data are helpful. Our model performance yields a TSS of 0.84 ±0.03 and 0.81 ±0.03 in the T = 2- and 24-hour cases, respectively, and a value of 0.13 ±0.07 and 0.43 ±0.08 for the area under the precision-recall curve in the T=2- and 24-hour cases, respectively. These relatively high scores are competitive with previous attempts at solar prediction, but our different methodology and extreme care in task design and experimental setup provide an independent confirmation of these results. Given the similar values of algorithm performance across various types of models reported in the literature, we conclude that we can expect a certain baseline predictive capacity using these data. We believe that this is the first attempt to predict solar flares using photospheric vector-magnetic field data as well as multiple wavelengths of image data from the chromosphere, transition region, and corona, and it points the way towards greater data integration across diverse sources in future work.

Brain activity elicited by viewing pictures of the own virtually amputated body predicts xenomelia.

PubMed

Oddo-Sommerfeld, Silvia; Hänggi, Jürgen; Coletta, Ludovico; Skoruppa, Silke; Thiel, Aylin; Stirn, Aglaja V

2018-01-08

Xenomelia is a rare condition characterized by the persistent desire for the amputation of physically healthy limbs. Prior studies highlighted the importance of superior and inferior parietal lobuli (SPL/IPL) and other sensorimotor regions as key brain structures associated with xenomelia. We expected activity differences in these areas in response to pictures showing the desired body state, i.e. that of an amputee in xenomelia. Functional magnetic resonance images were acquired in 12 xenomelia individuals and 11 controls while they viewed pictures of their own real and virtually amputated body. Pictures were rated on several dimensions. Multivariate statistics using machine learning was performed on imaging data. Brain activity when viewing pictures of one's own virtually amputated body predicted group membership accurately with a balanced accuracy of 82.58% (p = 0.002), sensitivity of 83.33% (p = 0.018), specificity of 81.82% (p = 0.015) and an area under the ROC curve of 0.77. Among the highest predictive brain regions were bilateral SPL, IPL, and caudate nucleus, other limb representing areas, but also occipital regions. Pleasantness and attractiveness ratings were higher for amputated bodies in xenomelia. Findings show that neuronal processing in response to pictures of one's own desired body state is different in xenomelia compared with controls and might represent a neuronal substrate of the xenomelia complaints that become behaviourally relevant, at least when rating the pleasantness and attractiveness of one's own body. Our findings converge with structural peculiarities reported in xenomelia and partially overlap in task and results with that of anorexia and transgender research. Copyright © 2017 Elsevier Ltd. All rights reserved.

Seismic activity prediction using computational intelligence techniques in northern Pakistan

NASA Astrophysics Data System (ADS)

Asim, Khawaja M.; Awais, Muhammad; Martínez-Álvarez, F.; Iqbal, Talat

2017-10-01

Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar's statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.

Distracted and down: neural mechanisms of affective interference in subclinical depression.

PubMed

Kaiser, Roselinde H; Andrews-Hanna, Jessica R; Spielberg, Jeffrey M; Warren, Stacie L; Sutton, Bradley P; Miller, Gregory A; Heller, Wendy; Banich, Marie T

2015-05-01

Previous studies have shown that depressed individuals have difficulty directing attention away from negative distractors, a phenomenon known as affective interference. However, findings are mixed regarding the neural mechanisms and network dynamics of affective interference. The present study addressed these issues by comparing neural activation during emotion-word and color-word Stroop tasks in participants with varying levels of (primarily subclinical) depression. Depressive symptoms predicted increased activation to negative distractors in areas of dorsal anterior cingulate cortex (dACC) and posterior cingulate cortex (PCC), regions implicated in cognitive control and internally directed attention, respectively. Increased dACC activity was also observed in the group-average response to incongruent distractors, suggesting that dACC activity during affective interference is related to overtaxed cognitive control. In contrast, regions of PCC were deactivated across the group in response to incongruent distractors, suggesting that PCC activity during affective interference represents task-independent processing. A psychophysiological interaction emerged in which higher depression predicted more positively correlated activity between dACC and PCC during affective interference, i.e. greater connectivity between cognitive control and internal-attention systems. These findings suggest that, when individuals high in depression are confronted by negative material, increased attention to internal thoughts and difficulty shifting resources to the external world interfere with goal-directed behavior. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Global conditions in the solar corona from 2010 to 2017

PubMed Central

Morgan, Huw; Taroyan, Youra

2017-01-01

Through reduction of a huge data set spanning 2010–2017, we compare mean global changes in temperature, emission measure (EM), and underlying photospheric magnetic field of the solar corona over most of the last activity cycle. The quiet coronal mean temperature rises from 1.4 to 1.8 MK, whereas EM increases by almost a factor of 50% from solar minimum to maximum. An increased high-temperature component near 3 MK at solar maximum drives the increase in quiet coronal mean temperature, whereas the bulk of the plasma remains near 1.6 MK throughout the cycle. The mean, spatially smoothed magnitude of the quiet Sun magnetic field rises from 1.6 G in 2011 to peak at 2.0 G in 2015. Active region conditions are highly variable, but their mean remains approximately constant over the cycle, although there is a consistent decrease in active region high-temperature emission (near 3 MK) between the peak of solar maximum and present. Active region mean temperature, EM, and magnetic field magnitude are highly correlated. Correlation between sunspot/active region area and quiet coronal conditions shows the important influence of decaying sunspots in driving global changes, although we find no appreciable delay between changes in active region area and quiet Sun magnetic field strength. The hot coronal contribution to extreme ultraviolet (EUV) irradiance is dominated by the quiet corona throughout most of the cycle, whereas the high variability is driven by active regions. Solar EUV irradiance cannot be predicted accurately by sunspot index alone, highlighting the need for continued measurements. PMID:28740861

Interpolation Approaches for Characterizing Spatial Variability of Soil Properties in Tuz Lake Basin of Turkey

NASA Astrophysics Data System (ADS)

Gorji, Taha; Sertel, Elif; Tanik, Aysegul

2017-12-01

Soil management is an essential concern in protecting soil properties, in enhancing appropriate soil quality for plant growth and agricultural productivity, and in preventing soil erosion. Soil scientists and decision makers require accurate and well-distributed spatially continuous soil data across a region for risk assessment and for effectively monitoring and managing soils. Recently, spatial interpolation approaches have been utilized in various disciplines including soil sciences for analysing, predicting and mapping distribution and surface modelling of environmental factors such as soil properties. The study area selected in this research is Tuz Lake Basin in Turkey bearing ecological and economic importance. Fertile soil plays a significant role in agricultural activities, which is one of the main industries having great impact on economy of the region. Loss of trees and bushes due to intense agricultural activities in some parts of the basin lead to soil erosion. Besides, soil salinization due to both human-induced activities and natural factors has exacerbated its condition regarding agricultural land development. This study aims to compare capability of Local Polynomial Interpolation (LPI) and Radial Basis Functions (RBF) as two interpolation methods for mapping spatial pattern of soil properties including organic matter, phosphorus, lime and boron. Both LPI and RBF methods demonstrated promising results for predicting lime, organic matter, phosphorous and boron. Soil samples collected in the field were used for interpolation analysis in which approximately 80% of data was used for interpolation modelling whereas the remaining for validation of the predicted results. Relationship between validation points and their corresponding estimated values in the same location is examined by conducting linear regression analysis. Eight prediction maps generated from two different interpolation methods for soil organic matter, phosphorus, lime and boron parameters were examined based on R2 and RMSE values. The outcomes indicate that RBF performance in predicting lime, organic matter and boron put forth better results than LPI. However, LPI shows better results for predicting phosphorus.

Landscape scale prediction of earthquake-induced landsliding based on seismological and geomorphological parameters.

NASA Astrophysics Data System (ADS)

Marc, O.; Hovius, N.; Meunier, P.; Rault, C.

2017-12-01

In tectonically active areas, earthquakes are an important trigger of landslides with significant impact on hillslopes and river evolutions. However, detailed prediction of landslides locations and properties for a given earthquakes remain difficult.In contrast we propose, landscape scale, analytical prediction of bulk coseismic landsliding, that is total landslide area and volume (Marc et al., 2016a) as well as the regional area within which most landslide must distribute (Marc et al., 2017). The prediction is based on a limited number of seismological (seismic moment, source depth) and geomorphological (landscape steepness, threshold acceleration) parameters, and therefore could be implemented in landscape evolution model aiming at engaging with erosion dynamics at the scale of the seismic cycle. To assess the model we have compiled and normalized estimates of total landslide volume, total landslide area and regional area affected by landslides for 40, 17 and 83 earthquakes, respectively. We have found that low landscape steepness systematically leads to overprediction of the total area and volume of landslides. When this effect is accounted for, the model is able to predict within a factor of 2 the landslide areas and associated volumes for about 70% of the cases in our databases. The prediction of regional area affected do not require a calibration for the landscape steepness and gives a prediction within a factor of 2 for 60% of the database. For 7 out of 10 comprehensive inventories we show that our prediction compares well with the smallest region around the fault containing 95% of the total landslide area. This is a significant improvement on a previously published empirical expression based only on earthquake moment.Some of the outliers seems related to exceptional rock mass strength in the epicentral area or shaking duration and other seismic source complexities ignored by the model. Applications include prediction on the mass balance of earthquakes and this model predicts that only earthquakes generated on a narrow range of fault sizes may cause more erosion than uplift (Marc et al., 2016b), while very large earthquakes are expected to always build topography. The model could also be used to physically calibrate hillslope erosion or perturbations to river network within landscape evolution model.

Magnetogram Forecast: An All-Clear Space Weather Forecasting System

NASA Technical Reports Server (NTRS)

Barghouty, Nasser; Falconer, David

2015-01-01

Solar flares and coronal mass ejections (CMEs) are the drivers of severe space weather. Forecasting the probability of their occurrence is critical in improving space weather forecasts. The National Oceanic and Atmospheric Administration (NOAA) currently uses the McIntosh active region category system, in which each active region on the disk is assigned to one of 60 categories, and uses the historical flare rates of that category to make an initial forecast that can then be adjusted by the NOAA forecaster. Flares and CMEs are caused by the sudden release of energy from the coronal magnetic field by magnetic reconnection. It is believed that the rate of flare and CME occurrence in an active region is correlated with the free energy of an active region. While the free energy cannot be measured directly with present observations, proxies of the free energy can instead be used to characterize the relative free energy of an active region. The Magnetogram Forecast (MAG4) (output is available at the Community Coordinated Modeling Center) was conceived and designed to be a databased, all-clear forecasting system to support the operational goals of NASA's Space Radiation Analysis Group. The MAG4 system automatically downloads nearreal- time line-of-sight Helioseismic and Magnetic Imager (HMI) magnetograms on the Solar Dynamics Observatory (SDO) satellite, identifies active regions on the solar disk, measures a free-energy proxy, and then applies forecasting curves to convert the free-energy proxy into predicted event rates for X-class flares, M- and X-class flares, CMEs, fast CMEs, and solar energetic particle events (SPEs). The forecast curves themselves are derived from a sample of 40,000 magnetograms from 1,300 active region samples, observed by the Solar and Heliospheric Observatory Michelson Doppler Imager. Figure 1 is an example of MAG4 visual output

Predicting human age using regional morphometry and inter-regional morphological similarity

NASA Astrophysics Data System (ADS)

Wang, Xun-Heng; Li, Lihua

2016-03-01

The goal of this study is predicting human age using neuro-metrics derived from structural MRI, as well as investigating the relationships between age and predictive neuro-metrics. To this end, a cohort of healthy subjects were recruited from 1000 Functional Connectomes Project. The ages of the participations were ranging from 7 to 83 (36.17+/-20.46). The structural MRI for each subject was preprocessed using FreeSurfer, resulting in regional cortical thickness, mean curvature, regional volume and regional surface area for 148 anatomical parcellations. The individual age was predicted from the combination of regional and inter-regional neuro-metrics. The prediction accuracy is r = 0.835, p < 0.00001, evaluated by Pearson correlation coefficient between predicted ages and actual ages. Moreover, the LASSO linear regression also found certain predictive features, most of which were inter-regional features. The turning-point of the developmental trajectories in human brain was around 40 years old based on regional cortical thickness. In conclusion, structural MRI could be potential biomarkers for the aging in human brain. The human age could be successfully predicted from the combination of regional morphometry and inter-regional morphological similarity. The inter-regional measures could be beneficial to investigating human brain connectome.

Functional activation independently contributes to naming ability and relates to lesion site in post-stroke aphasia.

PubMed

Skipper-Kallal, Laura M; Lacey, Elizabeth H; Xing, Shihui; Turkeltaub, Peter E

2017-04-01

Language network reorganization in aphasia may depend on the degree of damage in critical language areas, making it difficult to determine how reorganization impacts performance. Prior studies on remapping of function in aphasia have not accounted for the location of the lesion relative to critical language areas. They rectified this problem by using a multimodal approach, combining multivariate lesion-symptom mapping and fMRI in chronic aphasia to understand the independent contributions to naming performance of the lesion and the activity in both hemispheres. Activity was examined during two stages of naming: covert retrieval, and overt articulation. Regions of interest were drawn based on over- and under-activation, and in areas where activity had a bivariate relationship with naming. Regressions then tested whether activation of these regions predicted naming ability, while controlling for lesion size and damage in critical left hemisphere naming areas, as determined by lesion-symptom mapping. Engagement of the right superior temporal sulcus (STS) and disengagement of the left dorsal pars opercularis (dPOp) during overt naming was associated with better than predicted naming performance. Lesions in the left STS prevented right STS engagement and resulted in persistent left dPOp activation. In summary, changes in activity during overt articulation independently relate to naming outcomes, controlling for stroke severity. Successful remapping relates to network disruptions that depend on the location of the lesion in the left hemisphere. Hum Brain Mapp 38:2051-2066, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Adjustment of regional regression equations for urban storm-runoff quality using at-site data

USGS Publications Warehouse

Barks, C.S.

1996-01-01

Regional regression equations have been developed to estimate urban storm-runoff loads and mean concentrations using a national data base. Four statistical methods using at-site data to adjust the regional equation predictions were developed to provide better local estimates. The four adjustment procedures are a single-factor adjustment, a regression of the observed data against the predicted values, a regression of the observed values against the predicted values and additional local independent variables, and a weighted combination of a local regression with the regional prediction. Data collected at five representative storm-runoff sites during 22 storms in Little Rock, Arkansas, were used to verify, and, when appropriate, adjust the regional regression equation predictions. Comparison of observed values of stormrunoff loads and mean concentrations to the predicted values from the regional regression equations for nine constituents (chemical oxygen demand, suspended solids, total nitrogen as N, total ammonia plus organic nitrogen as N, total phosphorus as P, dissolved phosphorus as P, total recoverable copper, total recoverable lead, and total recoverable zinc) showed large prediction errors ranging from 63 percent to more than several thousand percent. Prediction errors for 6 of the 18 regional regression equations were less than 100 percent and could be considered reasonable for water-quality prediction equations. The regression adjustment procedure was used to adjust five of the regional equation predictions to improve the predictive accuracy. For seven of the regional equations the observed and the predicted values are not significantly correlated. Thus neither the unadjusted regional equations nor any of the adjustments were appropriate. The mean of the observed values was used as a simple estimator when the regional equation predictions and adjusted predictions were not appropriate.

Predicting forest insect flight activity: A Bayesian network approach

PubMed Central

Pawson, Stephen M.; Marcot, Bruce G.; Woodberry, Owen G.

2017-01-01

Daily flight activity patterns of forest insects are influenced by temporal and meteorological conditions. Temperature and time of day are frequently cited as key drivers of activity; however, complex interactions between multiple contributing factors have also been proposed. Here, we report individual Bayesian network models to assess the probability of flight activity of three exotic insects, Hylurgus ligniperda, Hylastes ater, and Arhopalus ferus in a managed plantation forest context. Models were built from 7,144 individual hours of insect sampling, temperature, wind speed, relative humidity, photon flux density, and temporal data. Discretized meteorological and temporal variables were used to build naïve Bayes tree augmented networks. Calibration results suggested that the H. ater and A. ferus Bayesian network models had the best fit for low Type I and overall errors, and H. ligniperda had the best fit for low Type II errors. Maximum hourly temperature and time since sunrise had the largest influence on H. ligniperda flight activity predictions, whereas time of day and year had the greatest influence on H. ater and A. ferus activity. Type II model errors for the prediction of no flight activity is improved by increasing the model’s predictive threshold. Improvements in model performance can be made by further sampling, increasing the sensitivity of the flight intercept traps, and replicating sampling in other regions. Predicting insect flight informs an assessment of the potential phytosanitary risks of wood exports. Quantifying this risk allows mitigation treatments to be targeted to prevent the spread of invasive species via international trade pathways. PMID:28953904

A multivariate prediction model for Rho-dependent termination of transcription.

PubMed

Nadiras, Cédric; Eveno, Eric; Schwartz, Annie; Figueroa-Bossi, Nara; Boudvillain, Marc

2018-06-21

Bacterial transcription termination proceeds via two main mechanisms triggered either by simple, well-conserved (intrinsic) nucleic acid motifs or by the motor protein Rho. Although bacterial genomes can harbor hundreds of termination signals of either type, only intrinsic terminators are reliably predicted. Computational tools to detect the more complex and diversiform Rho-dependent terminators are lacking. To tackle this issue, we devised a prediction method based on Orthogonal Projections to Latent Structures Discriminant Analysis [OPLS-DA] of a large set of in vitro termination data. Using previously uncharacterized genomic sequences for biochemical evaluation and OPLS-DA, we identified new Rho-dependent signals and quantitative sequence descriptors with significant predictive value. Most relevant descriptors specify features of transcript C>G skewness, secondary structure, and richness in regularly-spaced 5'CC/UC dinucleotides that are consistent with known principles for Rho-RNA interaction. Descriptors collectively warrant OPLS-DA predictions of Rho-dependent termination with a ∼85% success rate. Scanning of the Escherichia coli genome with the OPLS-DA model identifies significantly more termination-competent regions than anticipated from transcriptomics and predicts that regions intrinsically refractory to Rho are primarily located in open reading frames. Altogether, this work delineates features important for Rho activity and describes the first method able to predict Rho-dependent terminators in bacterial genomes.

The role of the posterior cingulate cortex in cognition and disease

PubMed Central

Sharp, David J.

2014-01-01

The posterior cingulate cortex is a highly connected and metabolically active brain region. Recent studies suggest it has an important cognitive role, although there is no consensus about what this is. The region is typically discussed as having a unitary function because of a common pattern of relative deactivation observed during attentionally demanding tasks. One influential hypothesis is that the posterior cingulate cortex has a central role in supporting internally-directed cognition. It is a key node in the default mode network and shows increased activity when individuals retrieve autobiographical memories or plan for the future, as well as during unconstrained ‘rest’ when activity in the brain is ‘free-wheeling’. However, other evidence suggests that the region is highly heterogeneous and may play a direct role in regulating the focus of attention. In addition, its activity varies with arousal state and its interactions with other brain networks may be important for conscious awareness. Understanding posterior cingulate cortex function is likely to be of clinical importance. It is well protected against ischaemic stroke, and so there is relatively little neuropsychological data about the consequences of focal lesions. However, in other conditions abnormalities in the region are clearly linked to disease. For example, amyloid deposition and reduced metabolism is seen early in Alzheimer’s disease. Functional neuroimaging studies show abnormalities in a range of neurological and psychiatric disorders including Alzheimer’s disease, schizophrenia, autism, depression and attention deficit hyperactivity disorder, as well as ageing. Our own work has consistently shown abnormal posterior cingulate cortex function following traumatic brain injury, which predicts attentional impairments. Here we review the anatomy and physiology of the region and how it is affected in a range of clinical conditions, before discussing its proposed functions. We synthesize key findings into a novel model of the region’s function (the ‘Arousal, Balance and Breadth of Attention’ model). Dorsal and ventral subcomponents are functionally separated and differences in regional activity are explained by considering: (i) arousal state; (ii) whether attention is focused internally or externally; and (iii) the breadth of attentional focus. The predictions of the model can be tested within the framework of complex dynamic systems theory, and we propose that the dorsal posterior cingulate cortex influences attentional focus by ‘tuning’ whole-brain metastability and so adjusts how stable brain network activity is over time. PMID:23869106

A balance of activity in brain control and reward systems predicts self-regulatory outcomes

PubMed Central

Chen, Pin-Hao A.; Huckins, Jeremy F.; Hofmann, Wilhelm; Kelley, William M.; Heatherton, Todd F.

2017-01-01

Abstract Previous neuroimaging work has shown that increased reward-related activity following exposure to food cues is predictive of self-control failure. The balance model suggests that self-regulation failures result from an imbalance in reward and executive control mechanisms. However, an open question is whether the relative balance of activity in brain systems associated with executive control (vs reward) supports self-regulatory outcomes when people encounter tempting cues in daily life. Sixty-nine chronic dieters, a population known for frequent lapses in self-control, completed a food cue-reactivity task during an fMRI scanning session, followed by a weeklong sampling of daily eating behaviors via ecological momentary assessment. We related participants’ food cue activity in brain systems associated with executive control and reward to real-world eating patterns. Specifically, a balance score representing the amount of activity in brain regions associated with self-regulatory control, relative to automatic reward-related activity, predicted dieters’ control over their eating behavior during the following week. This balance measure may reflect individual self-control capacity and be useful for examining self-regulation success in other domains and populations. PMID:28158874

A balance of activity in brain control and reward systems predicts self-regulatory outcomes.

PubMed

Lopez, Richard B; Chen, Pin-Hao A; Huckins, Jeremy F; Hofmann, Wilhelm; Kelley, William M; Heatherton, Todd F

2017-05-01

Previous neuroimaging work has shown that increased reward-related activity following exposure to food cues is predictive of self-control failure. The balance model suggests that self-regulation failures result from an imbalance in reward and executive control mechanisms. However, an open question is whether the relative balance of activity in brain systems associated with executive control (vs reward) supports self-regulatory outcomes when people encounter tempting cues in daily life. Sixty-nine chronic dieters, a population known for frequent lapses in self-control, completed a food cue-reactivity task during an fMRI scanning session, followed by a weeklong sampling of daily eating behaviors via ecological momentary assessment. We related participants' food cue activity in brain systems associated with executive control and reward to real-world eating patterns. Specifically, a balance score representing the amount of activity in brain regions associated with self-regulatory control, relative to automatic reward-related activity, predicted dieters' control over their eating behavior during the following week. This balance measure may reflect individual self-control capacity and be useful for examining self-regulation success in other domains and populations. © The Author (2017). Published by Oxford University Press.

Metabolic Activity in the Insular Cortex and Hypothalamus Predicts Hot Flashes: An FDG-PET Study

PubMed Central

Deckersbach, Thilo; Lin, Nancy U.; Makris, Nikos; Skaar, Todd C.; Rauch, Scott L.; Dougherty, Darin D.; Hall, Janet E.

2012-01-01

Context: Hot flashes are a common side effect of adjuvant endocrine therapies (AET; leuprolide, tamoxifen, aromatase inhibitors) that reduce quality of life and treatment adherence in breast cancer patients. Because hot flashes affect only some women, preexisting neurobiological traits might predispose to their development. Previous studies have implicated the insula during the perception of hot flashes and the hypothalamus in thermoregulatory dysfunction. Objective: The aim of the study was to understand whether neurobiological factors predict hot flashes. Design: [18F]-Fluorodeoxyglucose (FDG) positron emission tomography (PET) brain scans coregistered with structural magnetic resonance imaging were used to determine whether metabolic activity in the insula and hypothalamic thermoregulatory and estrogen-feedback regions measured before and in response to AET predict hot flashes. Findings were correlated with CYP2D6 genotype because of CYP2D6 polymorphism associations with tamoxifen-induced hot flashes. Outcome Measures: We measured regional cerebral metabolic rate of glucose uptake (rCMRglu) in the insula and hypothalamus on FDG-PET. Results: Of 18 women without hot flashes who began AET, new-onset hot flashes were reported by 10 (55.6%) and were detected objectively in nine (50%) participants. Prior to the use of all AET, rCMRglu in the insula (P ≤ 0.01) and hypothalamic thermoregulatory (P = 0.045) and estrogen-feedback (P = 0.007) regions was lower in women who reported developing hot flashes. In response to AET, rCMRglu was further reduced in the insula in women developing hot flashes (P ≤ 0.02). Insular and hypothalamic rCMRglu levels were lower in intermediate than extensive CYP2D6 metabolizers. Conclusions: Trait neurobiological characteristics predict hot flashes. Genetic variability in CYP2D6 may underlie the neurobiological predisposition to hot flashes induced by AET. PMID:22723326

Feedback Interactions of Polymerized Actin with the Cell Membrane: Waves, Pulses, and Oscillations

NASA Astrophysics Data System (ADS)

Carlsson, Anders

Polymerized filaments of the protein actin have crucial functions in cell migration, and in bending the cell membrane to drive endocytosis or the formation of protrusions. The nucleation and polymerization of actin filaments are controlled by upstream agents in the cell membrane, including nucleation-promoting factors (NPFs) that activate the Arp2/3 complex to form new branches on pre-existing filaments. But polymerized actin (F-actin) also feeds back on the assembly of NPFs. We explore the effects of the resulting feedback loop of F-actin and NPFs on two phenomena: actin pulses that drive endocytosis in yeast, and actin waves traveling along the membrane of several cell types. In our model of endocytosis in yeast, the actin network is grown explicitly in three dimensions, exerts a negative feedback interaction on localized patch of NPFs in the membrane, and bends the membrane by exerting a distribution of forces. This model explains observed actin and NPF pulse dynamics, and the effects of several interventions including i) NPF mutations, ii) inhibition of actin polymerization, and iii) deletion of a protein that allows F-actin to bend the cell membrane. The model predicts that mutation of the active region of an NPF will enhance the accumulation of that NPF, and we confirm this prediction by quantitative fluorescence microscopy. For actin waves, we treat a similar model, with NPFs distributed over a larger region of the cell membrane. This model naturally generates actin waves, and predicts a transition from wave behavior to spatially localized oscillations when NPFs are confined to a small region. We also predict a transition from waves to static polarization as the negative-feedback coupling between F-actin and the NPFs is reduced. Supported by NIGMS Grant R01 GM107667.

Forecasting Solar Flares Using Magnetogram-based Predictors and Machine Learning

NASA Astrophysics Data System (ADS)

Florios, Kostas; Kontogiannis, Ioannis; Park, Sung-Hong; Guerra, Jordan A.; Benvenuto, Federico; Bloomfield, D. Shaun; Georgoulis, Manolis K.

2018-02-01

We propose a forecasting approach for solar flares based on data from Solar Cycle 24, taken by the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) mission. In particular, we use the Space-weather HMI Active Region Patches (SHARP) product that facilitates cut-out magnetograms of solar active regions (AR) in the Sun in near-realtime (NRT), taken over a five-year interval (2012 - 2016). Our approach utilizes a set of thirteen predictors, which are not included in the SHARP metadata, extracted from line-of-sight and vector photospheric magnetograms. We exploit several machine learning (ML) and conventional statistics techniques to predict flares of peak magnitude {>} M1 and {>} C1 within a 24 h forecast window. The ML methods used are multi-layer perceptrons (MLP), support vector machines (SVM), and random forests (RF). We conclude that random forests could be the prediction technique of choice for our sample, with the second-best method being multi-layer perceptrons, subject to an entropy objective function. A Monte Carlo simulation showed that the best-performing method gives accuracy ACC=0.93(0.00), true skill statistic TSS=0.74(0.02), and Heidke skill score HSS=0.49(0.01) for {>} M1 flare prediction with probability threshold 15% and ACC=0.84(0.00), TSS=0.60(0.01), and HSS=0.59(0.01) for {>} C1 flare prediction with probability threshold 35%.

The medial temporal lobe-conduit of parallel connectivity: a model for attention, memory, and perception.

PubMed

Mozaffari, Brian

2014-01-01

Based on the notion that the brain is equipped with a hierarchical organization, which embodies environmental contingencies across many time scales, this paper suggests that the medial temporal lobe (MTL)-located deep in the hierarchy-serves as a bridge connecting supra- to infra-MTL levels. Bridging the upper and lower regions of the hierarchy provides a parallel architecture that optimizes information flow between upper and lower regions to aid attention, encoding, and processing of quick complex visual phenomenon. Bypassing intermediate hierarchy levels, information conveyed through the MTL "bridge" allows upper levels to make educated predictions about the prevailing context and accordingly select lower representations to increase the efficiency of predictive coding throughout the hierarchy. This selection or activation/deactivation is associated with endogenous attention. In the event that these "bridge" predictions are inaccurate, this architecture enables the rapid encoding of novel contingencies. A review of hierarchical models in relation to memory is provided along with a new theory, Medial-temporal-lobe Conduit for Parallel Connectivity (MCPC). In this scheme, consolidation is considered as a secondary process, occurring after a MTL-bridged connection, which eventually allows upper and lower levels to access each other directly. With repeated reactivations, as contingencies become consolidated, less MTL activity is predicted. Finally, MTL bridging may aid processing transient but structured perceptual events, by allowing communication between upper and lower levels without calling on intermediate levels of representation.

Lingering effects of preceding strong El Niño events on the typhoon activity in early summer: Case study of sub-seasonal and seasonal predictions in 2016

NASA Astrophysics Data System (ADS)

Takaya, Y.; Kubo, Y.; Yamaguchi, M.; Vitart, F.; Hirahara, S.; Maeda, S.

2016-12-01

Strong El Niño events have lingering effects on the seasonal variability in the Indo- western Pacific region in the mature-decay phase of El Niño. Specifically, in the decay phase, a low-level anticyclonic circulation and suppressed convection in the western North Pacific are enforced as a result of a local air-sea feedback in the western North Pacific and remote response to the Indian Ocean warming due to El Niño. The typhoon activity in the western North Pacific is also modulated by the lingering effects in the early typhoon season (boreal spring to early summer) following the strong El Niño events. This study investigates underlying mechanisms and predictability by analyzing the historical analysis data, subseasonal and seasonal reforecast data, and sensitivity experiments with the use of an atmosphere-ocean coupled model for the 2016 typhoon season. In this study, we focus on the remote response of the typhoon activity in the Indo-Pacific region. First, we examined the case of 2016, which exhibited the striking inactive typhoon activity and marked the second latest genesis of the first typhoon of the year since 1977 (Typhoon Nipartak on 3 July 2016). The inactive typhoon activity in the early typhoon season of 2016 is plausibly related to the lingering effects of the preceding strong El Niño in 2015/2016 winter. And the inactive typhoon condition and its related atmosphere-ocean conditions in the western north Pacific were successfully predicted with sub-seasonal prediction systems and JMA seasonal prediction system (JMA/MRI-CPS2) well in advance. A composite analysis using historical analysis data indicates that the typhoon activity tends to be suppressed associated with the Indian Ocean warming in boreal spring to summer following El Niño winters. This is relatively well replicated in reforecasts of JMA/MRI-CPS2. We also carried out sensitivity experiments with JMA/MRI-CPS2, where we strongly nudge sea surface temperature (SST) in the Indian Ocean to climatological SST. The typhoon activity in the western North Pacific is enhanced in the sensitivity experiment, implying that the the Indian Ocean played a role in shaping the inactive typhoon conditions in the 2016 typhoon season. We will further discuss the underlying mechanisms and predictability using the series of experiments.

A Data Base for Predicting Consequences of Chemical Disposal Operations

DTIC Science & Technology

1973-01-01

the concentrations of these harmless hydrclysis products in the intermediate region will increase. Li The rate of solution of mustard is dependent...other trivalent arsenicals, is a potent herbicide . In the pentavalent state, both the herbicidal activities and the mammalian toxicities of most

Earthquake Hazards.

ERIC Educational Resources Information Center

Donovan, Neville

1979-01-01

Provides a survey and a review of earthquake activity and global tectonics from the advancement of the theory of continental drift to the present. Topics include: an identification of the major seismic regions of the earth, seismic measurement techniques, seismic design criteria for buildings, and the prediction of earthquakes. (BT)

Anterior Insula Activity Predicts the Influence of Positively-Framed Messages on Decision Making

PubMed Central

Krawitz, Adam; Fukunaga, Rena; Brown, Joshua W.

2010-01-01

The neural mechanisms underlying the influence of persuasive messages on decision making are largely unknown. We address this using event-related functional magnetic resonance imaging to investigate how informative messages alter risk appraisal during choice. Participants performed the Iowa Gambling Task while viewing a positively-framed, negatively-framed, or control message about the options. Right anterior insula correlated with improvement in choice behavior due to the positively-framed, but not the negatively-framed, message. With the positively-framed message there was increased activation proportional to message effectiveness when less-preferred options were chosen, consistent with a role in the prediction of adverse outcomes. In addition, dorsomedial and left dorsolateral prefrontal cortex correlated with overall decision quality regardless of message type. The dorsomedial region mediated the relationship between right anterior insula and decision quality with the positively-framed messages. These findings suggest a network of frontal brain regions that integrate informative messages into the evaluation of options during decision-making. PMID:20805540

Static and Impulsive Models of Solar Active Regions

NASA Technical Reports Server (NTRS)

Patsourakos, S.; Klimchuk, James A.

2008-01-01

The physical modeling of active regions (ARs) and of the global coronal is receiving increasing interest lately. Recent attempts to model ARs using static equilibrium models were quite successful in reproducing AR images of hot soft X-ray (SXR) loops. They however failed to predict the bright EUV warm loops permeating ARs: the synthetic images were dominated by intense footpoint emission. We demonstrate that this failure is due to the very weak dependence of loop temperature on loop length which cannot simultaneously account for both hot and warm loops in the same AR. We then consider time-dependent AR models based on nanoflare heating. We demonstrate that such models can simultaneously reproduce EUV and SXR loops in ARs. Moreover, they predict radial intensity variations consistent with the localized core and extended emissions in SXR and EUV AR observations respectively. We finally show how the AR morphology can be used as a gauge of the properties (duration, energy, spatial dependence, repetition time) of the impulsive heating.

Dissociating visual form from lexical frequency using Japanese.

PubMed

Twomey, Tae; Kawabata Duncan, Keith J; Hogan, John S; Morita, Kenji; Umeda, Kazumasa; Sakai, Katsuyuki; Devlin, Joseph T

2013-05-01

In Japanese, the same word can be written in either morphographic Kanji or syllabographic Hiragana and this provides a unique opportunity to disentangle a word's lexical frequency from the frequency of its visual form - an important distinction for understanding the neural information processing in regions engaged by reading. Behaviorally, participants responded more quickly to high than low frequency words and to visually familiar relative to less familiar words, independent of script. Critically, the imaging results showed that visual familiarity, as opposed to lexical frequency, had a strong effect on activation in ventral occipito-temporal cortex. Activation here was also greater for Kanji than Hiragana words and this was not due to their inherent differences in visual complexity. These findings can be understood within a predictive coding framework in which vOT receives bottom-up information encoding complex visual forms and top-down predictions from regions encoding non-visual attributes of the stimulus. Copyright © 2012 Elsevier Inc. All rights reserved.

Towards Bridging the Gaps in Holistic Transition Prediction via Numerical Simulations

NASA Technical Reports Server (NTRS)

Choudhari, Meelan M.; Li, Fei; Duan, Lian; Chang, Chau-Lyan; Carpenter, Mark H.; Streett, Craig L.; Malik, Mujeeb R.

2013-01-01

The economic and environmental benefits of laminar flow technology via reduced fuel burn of subsonic and supersonic aircraft cannot be realized without minimizing the uncertainty in drag prediction in general and transition prediction in particular. Transition research under NASA's Aeronautical Sciences Project seeks to develop a validated set of variable fidelity prediction tools with known strengths and limitations, so as to enable "sufficiently" accurate transition prediction and practical transition control for future vehicle concepts. This paper provides a summary of selected research activities targeting the current gaps in high-fidelity transition prediction, specifically those related to the receptivity and laminar breakdown phases of crossflow induced transition in a subsonic swept-wing boundary layer. The results of direct numerical simulations are used to obtain an enhanced understanding of the laminar breakdown region as well as to validate reduced order prediction methods.

The CME Flare Arcade and the Width of the CME in the Outer Corona

NASA Technical Reports Server (NTRS)

Moore, Ron; Falconer, David; Sterling, Alphonse

2008-01-01

Moore, Sterling, & Suess (2007, ApJ, 668, 1221) present evidence that (1) a CME is typically a magnetic bubble, a low-beta gplasmoid with legs h having roughly the 3D shape of a light bulb, and (2) in the outer corona the CME plasmoid is in lateral pressure equilibrium with the ambient magnetic field. They present three CMEs observed by SOHO/LASCO, each from a very different source located near the limb. One of these CMEs came from a compact ejective eruption from a small part of a sunspot active region, another came from a large quiet-region filament eruption, and the third CME, an extremely large and fast one, was produced in tandem with an X20 flare arcade that was centered on a huge delta sunspot. Each of these CMEs had more or less the classic lightbulb silhouette and attained a constant heliocentric angular width in the outer corona. This indicates that the CME plasmoid attained lateral magnetic pressure balance with the ambient radial magnetic field in the outer corona. This lateral pressure balance, together with the standard scenario for CME production by the eruption of a sheared-core magnetic arcade, yields the following simple estimate of the strength B(sub Flare) of the magnetic field in the flare arcade produced together with the CME: B(sub Flare) 1.4(theta CME/theta Flare)sup 2 G, where theta (sub CME) is the heliocentric angular width of the CME plasmoid in the outer corona and theta (sub Flare) is the heliocentric angular width of the full-grown flare arcade. Conversely, theta (sub CME) approximately equal to (R(sub Sun)sup -1(phi(sub Flare)/1.4)sup 1/2 radians, where Flare is the magnetic flux covered by the full-grown flare arcade. In addition to presenting the three CMEs of Moore, Sterling, & Suess (2007) and their agreement with this relation between CME and Flare, we present a further empirical test of this relation. For CMEs that erupt from active regions, the co-produced flare arcade seldom if ever covers the entire active region: if AR is the total magnetic flux of the active region, Flare . AR, and we predict that CME. (R(sub Sun))sup -1(theta AR/1.4)sup 1/2 radians. For a random sample of 31 CMEs that erupted from active regions within 30 of the limb, for each CME we have measured CME from LASCO/C3 and have measured AR from a SOHO/MDI magnetogram of the source active region when it was within 30 of disk center. We find that each CME obeys the above predicted inequality, none having width greater than half of the upper bound given by theta(sub AR). Thus, an active region's magnetic flux content, together with its location on the solar disk, largely determines whether the active region can possibly produce a CME that is wide enough to intercept the Earth.

Collaboratory for the Study of Earthquake Predictability

NASA Astrophysics Data System (ADS)

Schorlemmer, D.; Jordan, T. H.; Zechar, J. D.; Gerstenberger, M. C.; Wiemer, S.; Maechling, P. J.

2006-12-01

Earthquake prediction is one of the most difficult problems in physical science and, owing to its societal implications, one of the most controversial. The study of earthquake predictability has been impeded by the lack of an adequate experimental infrastructure---the capability to conduct scientific prediction experiments under rigorous, controlled conditions and evaluate them using accepted criteria specified in advance. To remedy this deficiency, the Southern California Earthquake Center (SCEC) is working with its international partners, which include the European Union (through the Swiss Seismological Service) and New Zealand (through GNS Science), to develop a virtual, distributed laboratory with a cyberinfrastructure adequate to support a global program of research on earthquake predictability. This Collaboratory for the Study of Earthquake Predictability (CSEP) will extend the testing activities of SCEC's Working Group on Regional Earthquake Likelihood Models, from which we will present first results. CSEP will support rigorous procedures for registering prediction experiments on regional and global scales, community-endorsed standards for assessing probability-based and alarm-based predictions, access to authorized data sets and monitoring products from designated natural laboratories, and software to allow researchers to participate in prediction experiments. CSEP will encourage research on earthquake predictability by supporting an environment for scientific prediction experiments that allows the predictive skill of proposed algorithms to be rigorously compared with standardized reference methods and data sets. It will thereby reduce the controversies surrounding earthquake prediction, and it will allow the results of prediction experiments to be communicated to the scientific community, governmental agencies, and the general public in an appropriate research context.

Solar flare predictions and warnings

NASA Technical Reports Server (NTRS)

White, K. P., III; Mayfield, E. B.

1973-01-01

The real-time solar monitoring information supplied to support SPARCS-equipped rocket launches, the routine collection and analysis of 3.3-mm solar radio maps, short-term flare forecasts based on these maps, longer-term forecasts based on the recurrence of active regions, and results of the synoptic study of solar active regions at 3.3-mm wavelength are presented. Forecasted flares in the 24-hour forecasts were 81% accurate, and those in the 28-day forecasts were 97% accurate. Synoptic radio maps at 3.3-mm wavelength are presented for twenty-three solar rotations in 1967 and 1968, as well as synoptic flare charts for the same period.

Benzene patterns in different urban environments and a prediction model for benzene rates based on NOx values

NASA Astrophysics Data System (ADS)

Paz, Shlomit; Goldstein, Pavel; Kordova-Biezuner, Levana; Adler, Lea

2017-04-01

Exposure to benzene has been associated with multiple severe impacts on health. This notwithstanding, at most monitoring stations, benzene is not monitored on a regular basis. The aims of the study were to compare benzene rates in different urban environments (region with heavy traffic and industrial region), to analyse the relationship between benzene and meteorological parameters in a Mediterranean climate type, to estimate the linkages between benzene and NOx and to suggest a prediction model for benzene rates based on NOx levels in order contribute to a better estimation of benzene. Data were used from two different monitoring stations, located on the eastern Mediterranean coast: 1) a traffic monitoring station in Tel Aviv, Israel (TLV) located in an urban region with heavy traffic; 2) a general air quality monitoring station in Haifa Bay (HIB), located in Israel's main industrial region. At each station, hourly, daily, monthly, seasonal, and annual data of benzene, NOx, mean temperature, relative humidity, inversion level, and temperature gradient were analysed over three years: 2008, 2009, and 2010. A prediction model for benzene rates based on NOx levels (which are monitored regularly) was developed to contribute to a better estimation of benzene. The severity of benzene pollution was found to be considerably higher at the traffic monitoring station (TLV) than at the general air quality station (HIB), despite the location of the latter in an industrial area. Hourly, daily, monthly, seasonal, and annual patterns have been shown to coincide with anthropogenic activities (traffic), the day of the week, and atmospheric conditions. A strong correlation between NOx and benzene allowed the development of a prediction model for benzene rates, based on NOx, the day of the week, and the month. The model succeeded in predicting the benzene values throughout the year (except for September). The severity of benzene pollution was found to be considerably higher at the traffic station (TLV) than at the general air quality station (HIB), despite being located in an industrial area. Hourly, daily, seasonal, and annual patterns of benzene rates have been shown to coincide with anthropogenic activities (traffic), day of the week, and atmospheric conditions. A prediction model for benzene rates was developed, based on NOx, the day of the week, and the month. The model suggested in this study might be useful for identifying potential risk of benzene in other urban environments.

fMRI as a Preimplant Objective Tool to Predict Children's Postimplant Auditory and Language Outcomes as Measured by Parental Observations.

PubMed

Deshpande, Aniruddha K; Tan, Lirong; Lu, Long J; Altaye, Mekibib; Holland, Scott K

2018-05-01

The trends in cochlear implantation candidacy and benefit have changed rapidly in the last two decades. It is now widely accepted that early implantation leads to better postimplant outcomes. Although some generalizations can be made about postimplant auditory and language performance, neural mechanisms need to be studied to predict individual prognosis. The aim of this study was to use functional magnetic resonance imaging (fMRI) to identify preimplant neuroimaging biomarkers that predict children's postimplant auditory and language outcomes as measured by parental observation/reports. This is a pre-post correlational measures study. Twelve possible cochlear implant candidates with bilateral severe to profound hearing loss were recruited via referrals for a clinical magnetic resonance imaging to ensure structural integrity of the auditory nerve for implantation. Participants underwent cochlear implantation at a mean age of 19.4 mo. All children used the advanced combination encoder strategy (ACE, Cochlear Corporation™, Nucleus ® Freedom cochlear implants). Three participants received an implant in the right ear; one in the left ear whereas eight participants received bilateral implants. Participants' preimplant neuronal activation in response to two auditory stimuli was studied using an event-related fMRI method. Blood oxygen level dependent contrast maps were calculated for speech and noise stimuli. The general linear model was used to create z-maps. The Auditory Skills Checklist (ASC) and the SKI-HI Language Development Scale (SKI-HI LDS) were administered to the parents 2 yr after implantation. A nonparametric correlation analysis was implemented between preimplant fMRI activation and postimplant auditory and language outcomes based on ASC and SKI-HI LDS. Statistical Parametric Mapping software was used to create regression maps between fMRI activation and scores on the aforementioned tests. Regression maps were overlaid on the Imaging Research Center infant template and visualized in MRIcro. Regression maps revealed two clusters of brain activation for the speech versus silence contrast and five clusters for the noise versus silence contrast that were significantly correlated with the parental reports. These clusters included auditory and extra-auditory regions such as the middle temporal gyrus, supramarginal gyrus, precuneus, cingulate gyrus, middle frontal gyrus, subgyral, and middle occipital gyrus. Both positive and negative correlations were observed. Correlation values for the different clusters ranged from -0.90 to 0.95 and were significant at a corrected p value of <0.05. Correlations suggest that postimplant performance may be predicted by activation in specific brain regions. The results of the present study suggest that (1) fMRI can be used to identify neuroimaging biomarkers of auditory and language performance before implantation and (2) activation in certain brain regions may be predictive of postimplant auditory and language performance as measured by parental observation/reports. American Academy of Audiology.

Surprised at All the Entropy: Hippocampal, Caudate and Midbrain Contributions to Learning from Prediction Errors

PubMed Central

Schiffer, Anne-Marike; Ahlheim, Christiane; Wurm, Moritz F.; Schubotz, Ricarda I.

2012-01-01

Influential concepts in neuroscientific research cast the brain a predictive machine that revises its predictions when they are violated by sensory input. This relates to the predictive coding account of perception, but also to learning. Learning from prediction errors has been suggested for take place in the hippocampal memory system as well as in the basal ganglia. The present fMRI study used an action-observation paradigm to investigate the contributions of the hippocampus, caudate nucleus and midbrain dopaminergic system to different types of learning: learning in the absence of prediction errors, learning from prediction errors, and responding to the accumulation of prediction errors in unpredictable stimulus configurations. We conducted analyses of the regions of interests' BOLD response towards these different types of learning, implementing a bootstrapping procedure to correct for false positives. We found both, caudate nucleus and the hippocampus to be activated by perceptual prediction errors. The hippocampal responses seemed to relate to the associative mismatch between a stored representation and current sensory input. Moreover, its response was significantly influenced by the average information, or Shannon entropy of the stimulus material. In accordance with earlier results, the habenula was activated by perceptual prediction errors. Lastly, we found that the substantia nigra was activated by the novelty of sensory input. In sum, we established that the midbrain dopaminergic system, the hippocampus, and the caudate nucleus were to different degrees significantly involved in the three different types of learning: acquisition of new information, learning from prediction errors and responding to unpredictable stimulus developments. We relate learning from perceptual prediction errors to the concept of predictive coding and related information theoretic accounts. PMID:22570715

The neural basis of involuntary episodic memories.

PubMed

Hall, Shana A; Rubin, David C; Miles, Amanda; Davis, Simon W; Wing, Erik A; Cabeza, Roberto; Berntsen, Dorthe

2014-10-01

Voluntary episodic memories require an intentional memory search, whereas involuntary episodic memories come to mind spontaneously without conscious effort. Cognitive neuroscience has largely focused on voluntary memory, leaving the neural mechanisms of involuntary memory largely unknown. We hypothesized that, because the main difference between voluntary and involuntary memory is the controlled retrieval processes required by the former, there would be greater frontal activity for voluntary than involuntary memories. Conversely, we predicted that other components of the episodic retrieval network would be similarly engaged in the two types of memory. During encoding, all participants heard sounds, half paired with pictures of complex scenes and half presented alone. During retrieval, paired and unpaired sounds were presented, panned to the left or to the right. Participants in the involuntary group were instructed to indicate the spatial location of the sound, whereas participants in the voluntary group were asked to additionally recall the pictures that had been paired with the sounds. All participants reported the incidence of their memories in a postscan session. Consistent with our predictions, voluntary memories elicited greater activity in dorsal frontal regions than involuntary memories, whereas other components of the retrieval network, including medial-temporal, ventral occipitotemporal, and ventral parietal regions were similarly engaged by both types of memories. These results clarify the distinct role of dorsal frontal and ventral occipitotemporal regions in predicting strategic retrieval and recalled information, respectively, and suggest that, although there are neural differences in retrieval, involuntary memories share neural components with established voluntary memory systems.

The Neural Basis of Involuntary Episodic Memories

PubMed Central

Hall, Shana A.; Rubin, David C.; Miles, Amanda; Davis, Simon W.; Wing, Erik A.; Cabeza, Roberto; Berntsen, Dorthe

2014-01-01

Voluntary episodic memories require an intentional memory search, whereas involuntary episodic memories come to mind spontaneously without conscious effort. Cognitive neuroscience has largely focused on voluntary memory, leaving the neural mechanisms of involuntary memory largely unknown. We hypothesized that because the main difference between voluntary and involuntary memory is the controlled retrieval processes required by the former, there would be greater frontal activity for voluntary than involuntary memories. Conversely, we predicted that other components of the episodic retrieval network would be similarly engaged in the two types of memory. During encoding, all participants heard sounds, half paired with pictures of complex scenes and half presented alone. During retrieval, paired and unpaired sounds were presented panned to the left or to the right. Participants in the involuntary group were instructed to indicate the spatial location of the sound, whereas participants in the voluntary group were asked to additionally recall the pictures that had been paired with the sounds. All participants reported the incidence of their memories in a post-scan session. Consistent with our predictions, voluntary memories elicited greater activity in dorsal frontal regions than involuntary memories, whereas other components of the retrieval network, including medial temporal, ventral occipitotemporal, and ventral parietal regions were similarly engaged by both types of memories. These results clarify the distinct role of dorsal frontal and ventral occipitotemporal regions in predicting strategic retrieval and recalled information, respectively, and suggest that while there are neural differences in retrieval, involuntary memories share neural components with established voluntary memory systems. PMID:24702453

α-Oscillations in the monkey sensorimotor network influence discrimination performance by rhythmical inhibition of neuronal spiking.

PubMed

Haegens, Saskia; Nácher, Verónica; Luna, Rogelio; Romo, Ranulfo; Jensen, Ole

2011-11-29

Extensive work in humans using magneto- and electroencephalography strongly suggests that decreased oscillatory α-activity (8-14 Hz) facilitates processing in a given region, whereas increased α-activity serves to actively suppress irrelevant or interfering processing. However, little work has been done to understand how α-activity is linked to neuronal firing. Here, we simultaneously recorded local field potentials and spikes from somatosensory, premotor, and motor regions while a trained monkey performed a vibrotactile discrimination task. In the local field potentials we observed strong activity in the α-band, which decreased in the sensorimotor regions during the discrimination task. This α-power decrease predicted better discrimination performance. Furthermore, the α-oscillations demonstrated a rhythmic relation with the spiking, such that firing was highest at the trough of the α-cycle. Firing rates increased with a decrease in α-power. These findings suggest that α-oscillations exercise a strong inhibitory influence on both spike timing and firing rate. Thus, the pulsed inhibition by α-oscillations plays an important functional role in the extended sensorimotor system.

A systems approach to hemostasis: 3. Thrombus consolidation regulates intrathrombus solute transport and local thrombin activity

PubMed Central

Welsh, John D.; Tomaiuolo, Maurizio; Wu, Jie; Colace, Thomas V.; Diamond, Scott L.

2014-01-01

Hemostatic thrombi formed after a penetrating injury have a distinctive structure in which a core of highly activated, closely packed platelets is covered by a shell of less-activated, loosely packed platelets. We have shown that differences in intrathrombus molecular transport emerge in parallel with regional differences in platelet packing density and predicted that these differences affect thrombus growth and stability. Here we test that prediction in a mouse vascular injury model. The studies use a novel method for measuring thrombus contraction in vivo and a previously characterized mouse line with a defect in integrin αIIbβ3 outside-in signaling that affects clot retraction ex vivo. The results show that the mutant mice have a defect in thrombus consolidation following vascular injury, resulting in an increase in intrathrombus transport rates and, as predicted by computational modeling, a decrease in thrombin activity and platelet activation in the thrombus core. Collectively, these data (1) demonstrate that in addition to the activation state of individual platelets, the physical properties of the accumulated mass of adherent platelets is critical in determining intrathrombus agonist distribution and platelet activation and (2) define a novel role for integrin signaling in the regulation of intrathrombus transport rates and localization of thrombin activity. PMID:24951426

Measurement of electroweak production of two jets in association with a Z boson in proton-proton collisions at

NASA Astrophysics Data System (ADS)

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V.; Vinogradov, A.; Belyaev, A.; Boos, E.; Ershov, A.; Gribushin, A.; Khein, L.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Lukina, O.; Obraztsov, S.; Petrushanko, S.; Savrin, V.; Snigirev, A.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Tourtchanovitch, L.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Ekmedzic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Battilana, C.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Domínguez Vázquez, D.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Merino, G.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Albajar, C.; de Trocóniz, J. 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L.; Adams, T.; Askew, A.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Hohlmann, M.; Kalakhety, H.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Bazterra, V. E.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Khalatyan, S.; Kurt, P.; Moon, D. H.; O'Brien, C.; Silkworth, C.; Turner, P.; Varelas, N.; Albayrak, E. A.; Bilki, B.; Clarida, W.; Dilsiz, K.; Duru, F.; Haytmyradov, M.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Rahmat, R.; Sen, S.; Tan, P.; Tiras, E.; Wetzel, J.; Yetkin, T.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Swartz, M.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Kenny, R. P.; Malek, M.; Murray, M.; Noonan, D.; Sanders, S.; Sekaric, J.; Stringer, R.; Wang, Q.; Wood, J. S.; Barfuss, A. F.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Shrestha, S.; Skhirtladze, N.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, A.; Belloni, A.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Kellogg, R. G.; Kolberg, T.; Lu, Y.; Marionneau, M.; Mignerey, A. C.; Pedro, K.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Bauer, G.; Busza, W.; Cali, I. A.; Chan, M.; Di Matteo, L.; Dutta, V.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Klute, M.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Ma, T.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Stephans, G. S. F.; Stöckli, F.; Sumorok, K.; Velicanu, D.; Veverka, J.; Wyslouch, B.; Yang, M.; Yoon, A. S.; Zanetti, M.; Zhukova, V.; Dahmes, B.; De Benedetti, A.; Gude, A.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Cremaldi, L. M.; Kroeger, R.; Oliveros, S.; Perera, L.; Sanders, D. A.; Summers, D.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Gonzalez Suarez, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Malik, S.; Meier, F.; Snow, G. R.; Dolen, J.; Godshalk, A.; Iashvili, I.; Jain, S.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Haley, J.; Massironi, A.; Nash, D.; Orimoto, T.; Trocino, D.; Wang, R.-J.; Wood, D.; Zhang, J.; Anastassov, A.; Hahn, K. A.; Kubik, A.; Lusito, L.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Velasco, M.; Won, S.; Brinkerhoff, A.; Chan, K. M.; Drozdetskiy, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Pearson, T.; Planer, M.; Ruchti, R.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Smith, G.; Winer, B. L.; Wolfe, H.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hebda, P.; Hunt, A.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Brownson, E.; Mendez, H.; Ramirez Vargas, J. E.; Barnes, V. E.; Benedetti, D.; Bolla, G.; Bortoletto, D.; De Mattia, M.; Hu, Z.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Lopes Pegna, D.; Maroussov, V.; Merkel, P.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Yoo, H. D.; Zablocki, J.; Zheng, Y.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Ecklund, K. M.; Geurts, F. J. M.; Li, W.; Michlin, B.; Padley, B. P.; Redjimi, R.; Roberts, J.; Zabel, J.; Betchart, B.; Bodek, A.; Covarelli, R.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Khukhunaishvili, A.; Petrillo, G.; Vishnevskiy, D.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Lungu, G.; Mesropian, C.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Kaplan, S.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Salur, S.; Schnetzer, S.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Hernandez, A. Castaneda; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Krutelyov, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Sakuma, T.; Suarez, I.; Tatarinov, A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kovitanggoon, K.; Kunori, S.; Lee, S. W.; Libeiro, T.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Sharma, M.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Wood, J.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Lazaridis, C.; Levine, A.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ross, I.; Sarangi, T.; Savin, A.; Smith, W. H.; Vuosalo, C.; Woods, N.

2015-02-01

The purely electroweak (EW) cross section for the production of two jets in association with a Z boson, in proton-proton collisions at , is measured using data recorded by the CMS experiment at the CERN LHC, corresponding to an integrated luminosity of 19.7. The electroweak cross section for the final state (with or and j representing the quarks produced in the hard interaction) in the kinematic region defined by , , transverse momentum , and pseudorapidity , is found to be , in agreement with the standard model prediction. The associated jet activity of the selected events is studied, in particular in a signal-enriched region of phase space, and the measurements are found to be in agreement with QCD predictions.

Predicting Persuasion-Induced Behavior Change from the Brain

PubMed Central

Falk, Emily B.; Berkman, Elliot T.; Mann, Traci; Harrison, Brittany; Lieberman, Matthew D.

2011-01-01

Although persuasive messages often alter people’s self-reported attitudes and intentions to perform behaviors, these self-reports do not necessarily predict behavior change. We demonstrate that neural responses to persuasive messages can predict variability in behavior change in the subsequent week. Specifically, an a priori region of interest (ROI) in medial prefrontal cortex (MPFC) was reliably associated with behavior change (r = 0.49, p < 0.05). Additionally, an iterative cross-validation approach using activity in this MPFC ROI predicted an average 23% of the variance in behavior change beyond the variance predicted by self-reported attitudes and intentions. Thus, neural signals can predict behavioral changes that are not predicted from self-reported attitudes and intentions alone. Additionally, this is the first functional magnetic resonance imaging study to demonstrate that a neural signal can predict complex real world behavior days in advance. PMID:20573889

Particulate matter pollution in the coal-producing regions of the Appalachian Mountains: Integrated ground-based measurements and satellite analysis.

PubMed

Aneja, Viney P; Pillai, Priya R; Isherwood, Aaron; Morgan, Peter; Aneja, Saurabh P

2017-04-01

This study integrates the relationship between measured surface concentrations of particulate matter 10 μm or less in diameter (PM 10 ), satellite-derived aerosol optical depth (AOD), and meteorology in Roda, Virginia, during 2008. A multiple regression model was developed to predict the concentrations of particles 2.5 μm or less in diameter (PM 2.5 ) at an additional location in the Appalachia region, Bristol, TN. The model was developed by combining AOD retrievals from Moderate Resolution Imaging Spectro-radiometer (MODIS) sensor on board the EOS Terra and Aqua Satellites with the surface meteorological observations. The multiple regression model predicted PM 2.5 (r 2 = 0.62), and the two-variable (AOD-PM 2.5 ) model predicted PM 2.5 (r 2 = 0.4). The developed model was validated using particulate matter recordings and meteorology observations from another location in the Appalachia region, Hazard, Kentucky. The model was extrapolated to the Roda, VA, sampling site to predict PM 2.5 mass concentrations. We used 10 km x 10 km resolution MODIS 550 nm AOD to predict ground level PM 2.5 . For the relevant period in 2008, in Roda, VA, the predicted PM 2.5 mass concentration is 9.11 ± 5.16 μg m -3 (mean ± 1SD). This is the first study that couples ground-based Particulate Matter measurements with satellite retrievals to predict surface air pollution at Roda, Virginia. Roda is representative of the Appalachian communities that are commonly located in narrow valleys, or "hollows," where homes are placed directly along the roads in a region of active mountaintop mining operations. Our study suggests that proximity to heavy coal truck traffic subjects these communities to chronic exposure to coal dust and leads us to conclude that there is an urgent need for new regulations to address the primary sources of this particulate matter.

The neural correlates of dreaming.

PubMed

Siclari, Francesca; Baird, Benjamin; Perogamvros, Lampros; Bernardi, Giulio; LaRocque, Joshua J; Riedner, Brady; Boly, Melanie; Postle, Bradley R; Tononi, Giulio

2017-06-01

Consciousness never fades during waking. However, when awakened from sleep, we sometimes recall dreams and sometimes recall no experiences. Traditionally, dreaming has been identified with rapid eye-movement (REM) sleep, characterized by wake-like, globally 'activated', high-frequency electroencephalographic activity. However, dreaming also occurs in non-REM (NREM) sleep, characterized by prominent low-frequency activity. This challenges our understanding of the neural correlates of conscious experiences in sleep. Using high-density electroencephalography, we contrasted the presence and absence of dreaming in NREM and REM sleep. In both NREM and REM sleep, reports of dream experience were associated with local decreases in low-frequency activity in posterior cortical regions. High-frequency activity in these regions correlated with specific dream contents. Monitoring this posterior 'hot zone' in real time predicted whether an individual reported dreaming or the absence of dream experiences during NREM sleep, suggesting that it may constitute a core correlate of conscious experiences in sleep.

Neural Networks Involved in Adolescent Reward Processing: An Activation Likelihood Estimation Meta-Analysis of Functional Neuroimaging Studies

PubMed Central

Silverman, Merav H.; Jedd, Kelly; Luciana, Monica

2015-01-01

Behavioral responses to, and the neural processing of, rewards change dramatically during adolescence and may contribute to observed increases in risk-taking during this developmental period. Functional MRI (fMRI) studies suggest differences between adolescents and adults in neural activation during reward processing, but findings are contradictory, and effects have been found in non-predicted directions. The current study uses an activation likelihood estimation (ALE) approach for quantitative meta-analysis of functional neuroimaging studies to: 1) confirm the network of brain regions involved in adolescents’ reward processing, 2) identify regions involved in specific stages (anticipation, outcome) and valence (positive, negative) of reward processing, and 3) identify differences in activation likelihood between adolescent and adult reward-related brain activation. Results reveal a subcortical network of brain regions involved in adolescent reward processing similar to that found in adults with major hubs including the ventral and dorsal striatum, insula, and posterior cingulate cortex (PCC). Contrast analyses find that adolescents exhibit greater likelihood of activation in the insula while processing anticipation relative to outcome and greater likelihood of activation in the putamen and amygdala during outcome relative to anticipation. While processing positive compared to negative valence, adolescents show increased likelihood for activation in the posterior cingulate cortex (PCC) and ventral striatum. Contrasting adolescent reward processing with the existing ALE of adult reward processing (Liu et al., 2011) reveals increased likelihood for activation in limbic, frontolimbic, and striatal regions in adolescents compared with adults. Unlike adolescents, adults also activate executive control regions of the frontal and parietal lobes. These findings support hypothesized elevations in motivated activity during adolescence. PMID:26254587

Neural activity predicts attitude change in cognitive dissonance.

PubMed

van Veen, Vincent; Krug, Marie K; Schooler, Jonathan W; Carter, Cameron S

2009-11-01

When our actions conflict with our prior attitudes, we often change our attitudes to be more consistent with our actions. This phenomenon, known as cognitive dissonance, is considered to be one of the most influential theories in psychology. However, the neural basis of this phenomenon is unknown. Using a Solomon four-group design, we scanned participants with functional MRI while they argued that the uncomfortable scanner environment was nevertheless a pleasant experience. We found that cognitive dissonance engaged the dorsal anterior cingulate cortex and anterior insula; furthermore, we found that the activation of these regions tightly predicted participants' subsequent attitude change. These effects were not observed in a control group. Our findings elucidate the neural representation of cognitive dissonance, and support the role of the anterior cingulate cortex in detecting cognitive conflict and the neural prediction of attitude change.

Figure-ground segregation in a recurrent network architecture.

PubMed

Roelfsema, Pieter R; Lamme, Victor A F; Spekreijse, Henk; Bosch, Holger

2002-05-15

Here we propose a model of how the visual brain segregates textured scenes into figures and background. During texture segregation, locations where the properties of texture elements change abruptly are assigned to boundaries, whereas image regions that are relatively homogeneous are grouped together. Boundary detection and grouping of image regions require different connection schemes, which are accommodated in a single network architecture by implementing them in different layers. As a result, all units carry signals related to boundary detection as well as grouping of image regions, in accordance with cortical physiology. Boundaries yield an early enhancement of network responses, but at a later point, an entire figural region is grouped together, because units that respond to it are labeled with enhanced activity. The model predicts which image regions are preferentially perceived as figure or as background and reproduces the spatio-temporal profile of neuronal activity in the visual cortex during texture segregation in intact animals, as well as in animals with cortical lesions.

Visuospatial processing in children with neurofibromatosis type 1

PubMed Central

Clements-Stephens, Amy M.; Rimrodt, Sheryl L.; Gaur, Pooja; Cutting, Laurie E.

2008-01-01

Neuroimaging studies investigating the neural network of visuospatial processing have revealed a right hemisphere network of activation including inferior parietal lobe, dorsolateral prefrontal cortex, and extrastriate regions. Impaired visuospatial processing, indicated by the Judgment of Line Orientation (JLO), is commonly seen in individuals with Neurofibromatosis type 1 (NF-1). Nevertheless, few studies have examined the neural activity associated with visuospatial processing in NF-1, in particular, during a JLO task. This study used functional neuroimaging to explore differences in volume of activation in predefined regions of interest between 13 individuals with NF-1 and 13 controls while performing an analogue JLO task. We hypothesized that participants with NF-1 would show anomalous right hemisphere activation and therefore would recruit regions within the left hemisphere to complete the task. Multivariate analyses of variance were used to test for differences between groups in frontal, temporal, parietal, and occipital regions. Results indicate that, as predicted, controls utilized various right hemisphere regions to complete the task, while the NF-1 group tended to recruit left hemisphere regions. These results suggest that the NF-1 group has an inefficient right hemisphere network. An additional unexpected finding was that the NF-1 group showed decreased volume of activation in primary visual cortex (BA 17). Future studies are needed to examine whether the decrease in primary visual cortex is related to a deficit in basic visual processing; findings could ultimately lead to a greater understanding of the nature of deficits in NF-1 and have implications for remediation. PMID:17988695

A long-duration active region: Evolution and quadrature observations of ejective events

NASA Astrophysics Data System (ADS)

Cremades, H.; Mandrini, C. H.; Fuentes, M. C. López; Merenda, L.; Cabello, I.; López, F. M.; Poisson, M.

2017-10-01

Unknown aspects of the initiation, evolution, and associated phenomena of coronal mass ejections (CMEs), together with their capability of perturbing the fragile technological equilibrium on which nowadays society depends, turn them a compelling subject of study. While space weather forecasts are thus far not able to predict when and where in the Sun will the next CME take place, various CME triggering mechanisms have been proposed, without reaching consensus on which is the predominant one. To improve our knowledge in these respects, we investigate a long-duration active region throughout its life, from birth until decay along five solar rotations, in connection with its production of ejective events. We benefit from the wealth of solar remote-sensing data with improved temporal, spatial, and spectral resolution provided by the ground-breaking space missions STEREO, SDO, and SOHO. During the investigated time interval, which covers the months July - November 2010, the STEREO spacecraft were nearly 180 degrees apart, allowing for the uninterrupted tracking of the active region and its ensuing CMEs. The ejective aspect is examined from multi-viewpoint coronagraphic images, while the dynamics of the active region photospheric magnetic field are inspected by means of SDO/HMI data for specific subintervals of interest. The ultimate goal of this work in progress is to identify common patterns in the ejective aspect that can be connected with the active region characteristics.

Cerebrocerebellar networks during articulatory rehearsal and verbal working memory tasks.

PubMed

Chen, S H Annabel; Desmond, John E

2005-01-15

Converging evidence has implicated the cerebellum in verbal working memory. The current fMRI study sought to further characterize cerebrocerebellar participation in this cognitive process by revealing regions of activation common to a verbal working task and an articulatory control task, as well as regions that are uniquely activated by working memory. Consistent with our model's predictions, load-dependent activations were observed in Broca's area (BA 44/6) and the superior cerebellar hemisphere (VI/CrusI) for both working memory and motoric rehearsal. In contrast, activations unique to verbal working memory were found in the inferior parietal lobule (BA 40) and the right inferior cerebellum hemisphere (VIIB). These findings provide evidence for two cerebrocerebellar networks for verbal working memory: a frontal/superior cerebellar articulatory control system and a parietal/inferior cerebellar phonological storage system.

Vegetation fires and air pollution in Vietnam.

PubMed

Le, Thanh Ha; Thanh Nguyen, Thi Nhat; Lasko, Kristofer; Ilavajhala, Shriram; Vadrevu, Krishna Prasad; Justice, Chris

2014-12-01

Forest fires are a significant source of air pollution in Asia. In this study, we integrate satellite remote sensing data and ground-based measurements to infer fire-air pollution relationships in selected regions of Vietnam. We first characterized the active fires and burnt areas at a regional scale from MODIS satellite data. We then used satellite-derived active fire data to correlate the resulting atmospheric pollution. Further, we analyzed the relationship between satellite atmospheric variables and ground-based air pollutant parameters. Our results show peak fire activity during March in Vietnam, with hotspots in the Northwest and Central Highlands. Active fires were significantly correlated with UV Aerosol Index (UVAI), aerosol extinction absorption optical depth (AAOD), and Carbon Monoxide. The use of satellite aerosol optical thickness improved the prediction of Particulate Matter (PM) concentration significantly. Copyright © 2014 Elsevier Ltd. All rights reserved.

On the context-dependent nature of the contribution of the ventral premotor cortex to speech perception

PubMed Central

Tremblay, Pascale; Small, Steven L.

2011-01-01

What is the nature of the interface between speech perception and production, where auditory and motor representations converge? One set of explanations suggests that during perception, the motor circuits involved in producing a perceived action are in some way enacting the action without actually causing movement (covert simulation) or sending along the motor information to be used to predict its sensory consequences (i.e., efference copy). Other accounts either reject entirely the involvement of motor representations in perception, or explain their role as being more supportive than integral, and not employing the identical circuits used in production. Using fMRI, we investigated whether there are brain regions that are conjointly active for both speech perception and production, and whether these regions are sensitive to articulatory (syllabic) complexity during both processes, which is predicted by a covert simulation account. A group of healthy young adults (1) observed a female speaker produce a set of familiar words (perception), and (2) observed and then repeated the words (production). There were two types of words, varying in articulatory complexity, as measured by the presence or absence of consonant clusters. The simple words contained no consonant cluster (e.g. “palace”), while the complex words contained one to three consonant clusters (e.g. “planet”). Results indicate that the left ventral premotor cortex (PMv) was significantly active during speech perception and speech production but that activation in this region was scaled to articulatory complexity only during speech production, revealing an incompletely specified efferent motor signal during speech perception. The right planum temporal (PT) was also active during speech perception and speech production, and activation in this region was scaled to articulatory complexity during both production and perception. These findings are discussed in the context of current theories theory of speech perception, with particular attention to accounts that include an explanatory role for mirror neurons. PMID:21664275

Neurophysiology and Neuroanatomy of Reflexive and Volitional Saccades: Evidence from Studies of Humans

PubMed Central

McDowell, Jennifer E.; Dyckman, Kara A.; Austin, Benjamin; Clementz, Brett A.

2008-01-01

This review provides a summary of the contributions made by human functional neuroimaging studies to the understanding of neural correlates of saccadic control. The generation of simple visually-guided saccades (redirections of gaze to a visual stimulus or prosaccades) and more complex volitional saccades require similar basic neural circuitry with additional neural regions supporting requisite higher level processes. The saccadic system has been studied extensively in non-human primates (e.g. single unit recordings) and humans (e.g. lesions and neuroimaging). Considerable knowledge of this system’s functional neuroanatomy makes it useful for investigating models of cognitive control. The network involved in prosaccade generation (by definition exogenously-driven) includes subcortical (striatum, thalamus, superior colliculus, and cerebellar vermis) and cortical structures (primary visual, extrastriate, and parietal cortices, and frontal and supplementary eye fields). Activation in these regions is also observed during endogenously-driven voluntary saccades (e.g. antisaccades, ocular motor delayed response or memory saccades, predictive tracking tasks and anticipatory saccades, and saccade sequencing), all of which require complex cognitive processes like inhibition and working memory. These additional requirements are supported by changes in neural activity in basic saccade circuitry and by recruitment of additional neural regions (such as prefrontal and anterior cingulate cortices). Activity in visual cortex is modulated as a function of task demands and may predict the type of saccade to be generated, perhaps via top-down control mechanisms. Neuroimaging studies suggest two foci of activation within FEF - medial and lateral - which may correspond to volitional and reflexive demands, respectively. Future research on saccade control could usefully (i) delineate important anatomical subdivisions that underlie functional differences, (ii) evaluate functional connectivity of anatomical regions supporting saccade generation using methods such as ICA and structural equation modeling, (iii) investigate how context affects behavior and brain activity, and (iv) use multi-modal neuroimaging to maximize spatial and temporal resolution. PMID:18835656

Superactive amidated COOH-terminal glucagon analogues with no methionine or tryptophan.

PubMed

Murphy, W A; Coy, D H; Lance, V A

1986-01-01

The functions of the Trp-25 and Met-27 residues and the free carboxy terminus of glucagon have been debated for many years. Despite some semi-synthetic data to the contrary, comparison of the glucagon sequence with the other 5 members of this family of peptides, all of them amides and particularly growth hormone-releasing factor(1-29) amide and its recently described analogues, suggests that alterations to these positions should be quite well tolerated in terms of biological activity. To test this prediction, [Phe-25,Leu-27]-glucagon amide was synthesized in high yield and was found to actually have superior glycogenolytic activity (196%) to glucagon in the rat. Replacement of Gly-4 by D-Phe, which has been shown to give much enhanced glycogenolytic activity than glucagon itself, also increased the activity of [D-Phe-4,Phe-25,Leu-27]-glucagon amide (518%). The L-Phe-4-analogue, [Phe-4,25,Leu-27]-glucagon amide, in contrast, was 20 times less active (30%), strongly suggesting the presence of a beta-bend in this N-terminal region of glucagon. This was supported by Chou-Fasman structural predictions which indicate extensive folding in the 1-15 region. Indeed, additional conformational restriction by substitution of D-Ser in position 2 of glucagon also increased activity to 226%. [D-Gln-3]-glucagon was slightly less active (74%) than glucagon. Chou-Fasman calculations on glucagon were compared to similar treatments of the VIP, secretin, PHI, and GRF(1-29) sequences.

Choice from non-choice: predicting consumer preferences from blood oxygenation level-dependent signals obtained during passive viewing.

PubMed

Levy, Ifat; Lazzaro, Stephanie C; Rutledge, Robb B; Glimcher, Paul W

2011-01-05

Decision-making is often viewed as a two-stage process, where subjective values are first assigned to each option and then the option of the highest value is selected. Converging evidence suggests that these subjective values are represented in the striatum and medial prefrontal cortex (MPFC). A separate line of evidence suggests that activation in the same areas represents the values of rewards even when choice is not required, as in classical conditioning tasks. However, it is unclear whether the same neural mechanism is engaged in both cases. To address this question we measured brain activation with functional magnetic resonance imaging while human subjects passively viewed individual consumer goods. We then sampled activation from predefined regions of interest and used it to predict subsequent choices between the same items made outside of the scanner. Our results show that activation in the striatum and MPFC in the absence of choice predicts subsequent choices, suggesting that these brain areas represent value in a similar manner whether or not choice is required.

A gastric acid secretion model.

PubMed Central

de Beus, A M; Fabry, T L; Lacker, H M

1993-01-01

A theory of gastric acid production and self-protection is formulated mathematically and examined for clinical and experimental correlations, implications, and predictions using analytic and numerical techniques. In our model, gastric acid secretion in the stomach, as represented by an archetypal gastron, consists of two chambers, circulatory and luminal, connected by two different regions of ion exchange. The capillary circulation of the gastric mucosa is arranged in arterial-venous arcades which pass from the gastric glands up to the surface epithelial lining of the lumen; therefore the upstream region of the capillary chamber communicates with oxyntic cells, while the downstream region communicates with epithelial cells. Both cell types abut the gastric lumen. Ion currents across the upstream region are calculated from a steady-state oxyntic cell model with active ion transport, while the downstream ion fluxes are (facilitated) diffusion driven or secondarily active. Water transport is considered iso-osmotic. The steady-state model is solved in closed form for low gastric lumen pH. A wide variety of previously performed static and dynamic experiments on ion and CO2 transport in the gastric lumen and gastric blood supply are for the first time correlated with each other for an (at least) semiquantitative test of current concepts of gastric acid secretion and for the purpose of model verification. Agreement with the data is reported with a few outstanding and instructive exceptions. Model predictions and implications are also discussed. Images FIGURE 1 PMID:8396457

GOES-R Proving Ground Activities at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

NASA Technical Reports Server (NTRS)

Molthan, Andrew

2011-01-01

SPoRT is actively involved in GOES-R Proving Ground activities in a number of ways: (1) Applying the paradigm of product development, user training, and interaction to foster interaction with end users at NOAA forecast offices national centers. (2) Providing unique capabilities in collaboration with other GOES-R Proving Ground partners (a) Hybrid GOES-MODIS imagery (b) Pseudo-GLM via regional lightning mapping arrays (c) Developing new RGB imagery from EUMETSAT guidelines

fMRI as a Preimplant Objective Tool to Predict Postimplant Oral Language Outcomes in Children with Cochlear Implants.

PubMed

Deshpande, Aniruddha K; Tan, Lirong; Lu, Long J; Altaye, Mekibib; Holland, Scott K

2016-01-01

Despite the positive effects of cochlear implantation, postimplant variability in speech perception and oral language outcomes is still difficult to predict. The aim of this study was to identify neuroimaging biomarkers of postimplant speech perception and oral language performance in children with hearing loss who receive a cochlear implant. The authors hypothesized positive correlations between blood oxygen level-dependent functional magnetic resonance imaging (fMRI) activation in brain regions related to auditory language processing and attention and scores on the Clinical Evaluation of Language Fundamentals-Preschool, Second Edition (CELF-P2) and the Early Speech Perception Test for Profoundly Hearing-Impaired Children (ESP), in children with congenital hearing loss. Eleven children with congenital hearing loss were recruited for the present study based on referral for clinical MRI and other inclusion criteria. All participants were <24 months at fMRI scanning and <36 months at first implantation. A silent background fMRI acquisition method was performed to acquire fMRI during auditory stimulation. A voxel-based analysis technique was utilized to generate z maps showing significant contrast in brain activation between auditory stimulation conditions (spoken narratives and narrow band noise). CELF-P2 and ESP were administered 2 years after implantation. Because most participants reached a ceiling on ESP, a voxel-wise regression analysis was performed between preimplant fMRI activation and postimplant CELF-P2 scores alone. Age at implantation and preimplant hearing thresholds were controlled in this regression analysis. Four brain regions were found to be significantly correlated with CELF-P2 scores. These clusters of positive correlation encompassed the temporo-parieto-occipital junction, areas in the prefrontal cortex and the cingulate gyrus. For the story versus silence contrast, CELF-P2 core language score demonstrated significant positive correlation with activation in the right angular gyrus (r = 0.95), left medial frontal gyrus (r = 0.94), and left cingulate gyrus (r = 0.96). For the narrow band noise versus silence contrast, the CELF-P2 core language score exhibited significant positive correlation with activation in the left angular gyrus (r = 0.89; for all clusters, corrected p < 0.05). Four brain regions related to language function and attention were identified that correlated with CELF-P2. Children with better oral language performance postimplant displayed greater activation in these regions preimplant. The results suggest that despite auditory deprivation, these regions are more receptive to gains in oral language development performance of children with hearing loss who receive early intervention via cochlear implantation. The present study suggests that oral language outcome following cochlear implant may be predicted by preimplant fMRI with auditory stimulation using natural speech.

An Integrative Perspective on the Role of Dopamine in Schizophrenia.

PubMed

Maia, Tiago V; Frank, Michael J

2017-01-01

We propose that schizophrenia involves a combination of decreased phasic dopamine responses for relevant stimuli and increased spontaneous phasic dopamine release. Using insights from computational reinforcement-learning models and basic-science studies of the dopamine system, we show that each of these two disturbances contributes to a specific symptom domain and explains a large set of experimental findings associated with that domain. Reduced phasic responses for relevant stimuli help to explain negative symptoms and provide a unified explanation for the following experimental findings in schizophrenia, most of which have been shown to correlate with negative symptoms: reduced learning from rewards; blunted activation of the ventral striatum, midbrain, and other limbic regions for rewards and positive prediction errors; blunted activation of the ventral striatum during reward anticipation; blunted autonomic responding for relevant stimuli; blunted neural activation for aversive outcomes and aversive prediction errors; reduced willingness to expend effort for rewards; and psychomotor slowing. Increased spontaneous phasic dopamine release helps to explain positive symptoms and provides a unified explanation for the following experimental findings in schizophrenia, most of which have been shown to correlate with positive symptoms: aberrant learning for neutral cues (assessed with behavioral and autonomic responses), and aberrant, increased activation of the ventral striatum, midbrain, and other limbic regions for neutral cues, neutral outcomes, and neutral prediction errors. Taken together, then, these two disturbances explain many findings in schizophrenia. We review evidence supporting their co-occurrence and consider their differential implications for the treatment of positive and negative symptoms. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Temporal and spatial variation in allocating annual traffic activity across an urban region and implications for air quality assessments

PubMed Central

Batterman, Stuart

2015-01-01

Patterns of traffic activity, including changes in the volume and speed of vehicles, vary over time and across urban areas and can substantially affect vehicle emissions of air pollutants. Time-resolved activity at the street scale typically is derived using temporal allocation factors (TAFs) that allow the development of emissions inventories needed to predict concentrations of traffic-related air pollutants. This study examines the spatial and temporal variation of TAFs, and characterizes prediction errors resulting from their use. Methods are presented to estimate TAFs and their spatial and temporal variability and used to analyze total, commercial and non-commercial traffic in the Detroit, Michigan, U.S. metropolitan area. The variability of total volume estimates, quantified by the coefficient of variation (COV) representing the percentage departure from expected hourly volume, was 21, 33, 24 and 33% for weekdays, Saturdays, Sundays and holidays, respectively. Prediction errors mostly resulted from hour-to-hour variability on weekdays and Saturdays, and from day-to-day variability on Sundays and holidays. Spatial variability was limited across the study roads, most of which were large freeways. Commercial traffic had different temporal patterns and greater variability than noncommercial vehicle traffic, e.g., the weekday variability of hourly commercial volume was 28%. The results indicate that TAFs for a metropolitan region can provide reasonably accurate estimates of hourly vehicle volume on major roads. While vehicle volume is only one of many factors that govern on-road emission rates, air quality analyses would be strengthened by incorporating information regarding the uncertainty and variability of traffic activity. PMID:26688671

Prediction of global ionospheric VTEC maps using an adaptive autoregressive model

NASA Astrophysics Data System (ADS)

Wang, Cheng; Xin, Shaoming; Liu, Xiaolu; Shi, Chuang; Fan, Lei

2018-02-01

In this contribution, an adaptive autoregressive model is proposed and developed to predict global ionospheric vertical total electron content maps (VTEC). Specifically, the spherical harmonic (SH) coefficients are predicted based on the autoregressive model, and the order of the autoregressive model is determined adaptively using the F-test method. To test our method, final CODE and IGS global ionospheric map (GIM) products, as well as altimeter TEC data during low and mid-to-high solar activity period collected by JASON, are used to evaluate the precision of our forecasting products. Results indicate that the predicted products derived from the model proposed in this paper have good consistency with the final GIMs in low solar activity, where the annual mean of the root-mean-square value is approximately 1.5 TECU. However, the performance of predicted vertical TEC in periods of mid-to-high solar activity has less accuracy than that during low solar activity periods, especially in the equatorial ionization anomaly region and the Southern Hemisphere. Additionally, in comparison with forecasting products, the final IGS GIMs have the best consistency with altimeter TEC data. Future work is needed to investigate the performance of forecasting products using the proposed method in an operational environment, rather than using the SH coefficients from the final CODE products, to understand the real-time applicability of the method.

Resting-state functional connectivity and motor imagery brain activation

PubMed Central

Saiote, Catarina; Tacchino, Andrea; Brichetto, Giampaolo; Roccatagliata, Luca; Bommarito, Giulia; Cordano, Christian; Battaglia, Mario; Mancardi, Giovanni Luigi; Inglese, Matilde

2016-01-01

Motor imagery (MI) relies on the mental simulation of an action without any overt motor execution (ME), and can facilitate motor learning and enhance the effect of rehabilitation in patients with neurological conditions. While functional magnetic resonance imaging (fMRI) during MI and ME reveals shared cortical representations, the role and functional relevance of the resting-state functional connectivity (RSFC) of brain regions involved in MI is yet unknown. Here, we performed resting-state fMRI followed by fMRI during ME and MI with the dominant hand. We used a behavioral chronometry test to measure ME and MI movement duration and compute an index of performance (IP). Then, we analyzed the voxel-matched correlation between the individual MI parameter estimates and seed-based RSFC maps in the MI network to measure the correspondence between RSFC and MI fMRI activation. We found that inter-individual differences in intrinsic connectivity in the MI network predicted several clusters of activation. Taken together, present findings provide first evidence that RSFC within the MI network is predictive of the activation of MI brain regions, including those associated with behavioral performance, thus suggesting a role for RSFC in obtaining a deeper understanding of neural substrates of MI and of MI ability. PMID:27273577

Individual Differences in Typical Reappraisal Use Predict Amygdala and Prefrontal Responses

PubMed Central

Drabant, Emily M.; McRae, Kateri; Manuck, Stephen B.; Hariri, Ahmad R.; Gross, James J.

2010-01-01

Background Participants who are instructed to use reappraisal to downregulate negative emotion show decreased amygdala responses and increased prefrontal responses. However, it is not known whether individual differences in the tendency to use reappraisal manifests in similar neural responses when individuals are spontaneously confronted with negative situations. Such spontaneous emotion regulation might play an important role in normal and pathological responses to the emotional challenges of everyday life. Methods Fifty-six healthy women completed a blood oxygenation-level dependent functional magnetic resonance imaging challenge paradigm involving the perceptual processing of emotionally negative facial expressions. Participants also completed measures of typical emotion regulation use, trait anxiety, and neuroticism. Results Greater use of reappraisal in everyday life was related to decreased amygdala activity and increased prefrontal and parietal activity during the processing of negative emotional facial expressions. These associations were not attributable to variation in trait anxiety, neuroticism, or the use of another common form of emotion regulation, namely suppression. Conclusions These findings suggest that, like instructed reappraisal, individual differences in reappraisal use are associated with decreased activation in ventral emotion generative regions and increased activation in prefrontal control regions in response to negative stimuli. Such individual differences in emotion regulation might predict successful coping with emotional challenges as well as the onset of affective disorders. PMID:18930182

Potential for thermal tolerance to mediate climate change effects on three members of a cool temperate lizard genus, Niveoscincus.

PubMed

Caldwell, Amanda J; While, Geoffrey M; Beeton, Nicholas J; Wapstra, Erik

2015-08-01

Climatic changes are predicted to be greater in higher latitude and mountainous regions but species specific impacts are difficult to predict. This is partly due to inter-specific variance in the physiological traits which mediate environmental temperature effects at the organismal level. We examined variation in the critical thermal minimum (CTmin), critical thermal maximum (CTmax) and evaporative water loss rates (EWL) of a widespread lowland (Niveoscincus ocellatus) and two range restricted highland (N. microlepidotus and N. greeni) members of a cool temperate Tasmanian lizard genus. The widespread lowland species had significantly higher CTmin and CTmax and significantly lower EWL than both highland species. Implications of inter-specific variation in thermal tolerance for activity were examined under contemporary and future climate change scenarios. Instances of air temperatures below CTmin were predicted to decline in frequency for the widespread lowland and both highland species. Air temperatures of high altitude sites were not predicted to exceed the CTmax of either highland species throughout the 21st century. In contrast, the widespread lowland species is predicted to experience air temperatures in excess of CTmax on 1 or 2 days by three of six global circulation models from 2068-2096. To estimate climate change effects on activity we reran the thermal tolerance models using minimum and maximum temperatures selected for activity. A net gain in available activity time was predicted under climate change for all three species; while air temperatures were predicted to exceed maximum temperatures selected for activity with increasing frequency, the change was not as great as the predicted decline in air temperatures below minimum temperatures selected for activity. We hypothesise that the major effect of rising air temperatures under climate change is an increase in available activity period for both the widespread lowland and highland species. The consequences of a greater available activity period will depend on the extent to which changes in climate alters other related factors, such as the nature and level of competition between the respective species. Copyright © 2015 Elsevier Ltd. All rights reserved.

Longitudinal Growth Curves of Brain Function Underlying Inhibitory Control through Adolescence

PubMed Central

Foran, William; Velanova, Katerina; Luna, Beatriz

2013-01-01

Neuroimaging studies suggest that developmental improvements in inhibitory control are primarily supported by changes in prefrontal executive function. However, studies are contradictory with respect to how activation in prefrontal regions changes with age, and they have yet to analyze longitudinal data using growth curve modeling, which allows characterization of dynamic processes of developmental change, individual differences in growth trajectories, and variables that predict any interindividual variability in trajectories. In this study, we present growth curves modeled from longitudinal fMRI data collected over 302 visits (across ages 9 to 26 years) from 123 human participants. Brain regions within circuits known to support motor response control, executive control, and error processing (i.e., aspects of inhibitory control) were investigated. Findings revealed distinct developmental trajectories for regions within each circuit and indicated that a hierarchical pattern of maturation of brain activation supports the gradual emergence of adult-like inhibitory control. Mean growth curves of activation in motor response control regions revealed no changes with age, although interindividual variability decreased with development, indicating equifinality with maturity. Activation in certain executive control regions decreased with age until adolescence, and variability was stable across development. Error-processing activation in the dorsal anterior cingulate cortex showed continued increases into adulthood and no significant interindividual variability across development, and was uniquely associated with task performance. These findings provide evidence that continued maturation of error-processing abilities supports the protracted development of inhibitory control over adolescence, while motor response control regions provide early-maturing foundational capacities and suggest that some executive control regions may buttress immature networks as error processing continues to mature. PMID:24227721

The signer and the sign: cortical correlates of person identity and language processing from point-light displays.

PubMed

Campbell, Ruth; Capek, Cheryl M; Gazarian, Karine; MacSweeney, Mairéad; Woll, Bencie; David, Anthony S; McGuire, Philip K; Brammer, Michael J

2011-09-01

In this study, the first to explore the cortical correlates of signed language (SL) processing under point-light display conditions, the observer identified either a signer or a lexical sign from a display in which different signers were seen producing a number of different individual signs. Many of the regions activated by point-light under these conditions replicated those previously reported for full-image displays, including regions within the inferior temporal cortex that are specialised for face and body-part identification, although such body parts were invisible in the display. Right frontal regions were also recruited - a pattern not usually seen in full-image SL processing. This activation may reflect the recruitment of information about person identity from the reduced display. A direct comparison of identify-signer and identify-sign conditions showed these tasks relied to a different extent on the posterior inferior regions. Signer identification elicited greater activation than sign identification in (bilateral) inferior temporal gyri (BA 37/19), fusiform gyri (BA 37), middle and posterior portions of the middle temporal gyri (BAs 37 and 19), and superior temporal gyri (BA 22 and 42). Right inferior frontal cortex was a further focus of differential activation (signer>sign). These findings suggest that the neural systems supporting point-light displays for the processing of SL rely on a cortical network including areas of the inferior temporal cortex specialized for face and body identification. While this might be predicted from other studies of whole body point-light actions (Vaina, Solomon, Chowdhury, Sinha, & Belliveau, 2001) it is not predicted from the perspective of spoken language processing, where voice characteristics and speech content recruit distinct cortical regions (Stevens, 2004) in addition to a common network. In this respect, our findings contrast with studies of voice/speech recognition (Von Kriegstein, Kleinschmidt, Sterzer, & Giraud, 2005). Inferior temporal regions associated with the visual recognition of a person appear to be required during SL processing, for both carrier and content information. Crown Copyright © 2011. Published by Elsevier Ltd. All rights reserved.

Revised techniques for estimating peak discharges from channel width in Montana

USGS Publications Warehouse

Parrett, Charles; Hull, J.A.; Omang, R.J.

1987-01-01

This study was conducted to develop new estimating equations based on channel width and the updated flood frequency curves of previous investigations. Simple regression equations for estimating peak discharges with recurrence intervals of 2, 5, 10 , 25, 50, and 100 years were developed for seven regions in Montana. The standard errors of estimates for the equations that use active channel width as the independent variables ranged from 30% to 87%. The standard errors of estimate for the equations that use bankfull width as the independent variable ranged from 34% to 92%. The smallest standard errors generally occurred in the prediction equations for the 2-yr flood, 5-yr flood, and 10-yr flood, and the largest standard errors occurred in the prediction equations for the 100-yr flood. The equations that use active channel width and the equations that use bankfull width were determined to be about equally reliable in five regions. In the West Region, the equations that use bankfull width were slightly more reliable than those based on active channel width, whereas in the East-Central Region the equations that use active channel width were slightly more reliable than those based on bankfull width. Compared with similar equations previously developed, the standard errors of estimate for the new equations are substantially smaller in three regions and substantially larger in two regions. Limitations on the use of the estimating equations include: (1) The equations are based on stable conditions of channel geometry and prevailing water and sediment discharge; (2) The measurement of channel width requires a site visit, preferably by a person with experience in the method, and involves appreciable measurement errors; (3) Reliability of results from the equations for channel widths beyond the range of definition is unknown. In spite of the limitations, the estimating equations derived in this study are considered to be as reliable as estimating equations based on basin and climatic variables. Because the two types of estimating equations are independent, results from each can be weighted inversely proportional to their variances, and averaged. The weighted average estimate has a variance less than either individual estimate. (Author 's abstract)

Identification of brain regions predicting epileptogenesis by serial [18F]GE-180 positron emission tomography imaging of neuroinflammation in a rat model of temporal lobe epilepsy.

PubMed

Russmann, Vera; Brendel, Matthias; Mille, Erik; Helm-Vicidomini, Angela; Beck, Roswitha; Günther, Lisa; Lindner, Simon; Rominger, Axel; Keck, Michael; Salvamoser, Josephine D; Albert, Nathalie L; Bartenstein, Peter; Potschka, Heidrun

2017-01-01

Excessive activation of inflammatory signaling pathways seems to be a hallmark of epileptogenesis. Positron emission tomography (PET) allows in vivo detection of brain inflammation with spatial information and opportunities for longitudinal follow-up scanning protocols. Here, we assessed whether molecular imaging of the 18 kDa translocator protein (TSPO) can serve as a biomarker for the development of epilepsy. Therefore, brain uptake of [ 18 F]GE-180, a highly selective radioligand of TSPO, was investigated in a longitudinal PET study in a chronic rat model of temporal lobe epilepsy. Analyses revealed that the influence of the epileptogenic insult on [ 18 F]GE-180 brain uptake was most pronounced in the earlier phase of epileptogenesis. Differences were evident in various brain regions during earlier phases of epileptogenesis with [ 18 F]GE-180 standardized uptake value enhanced by 2.1 to 2.7fold. In contrast, brain regions exhibiting differences seemed to be more restricted with less pronounced increases of tracer uptake by 1.8-2.5fold four weeks following status epilepticus and by 1.5-1.8fold in the chronic phase. Based on correlation analysis, we were able to identify regions with a predictive value showing a correlation with seizure development. These regions include the amygdala as well as a cluster of brain areas. This cluster comprises parts of different brain regions, e.g. the hippocampus, parietal cortex, thalamus, and somatosensory cortex. In conclusion, the data provide evidence that [ 18 F]GE-180 PET brain imaging can serve as a biomarker of epileptogenesis. The identification of brain regions with predictive value might facilitate the development of preventive concepts as well as the early assessment of the interventional success. Future studies are necessary to further confirm the predictivity of the approach.

Streamflow Prediction in Ungauged, Irrigated Basins

NASA Astrophysics Data System (ADS)

Zhang, M.; Thompson, S. E.

2016-12-01

The international "predictions in ungauged basins" or "PUB" effort has broadened and improved the tools available to support water resources management in sparsely observed regions. These tools have, however, been primarily focused on regions with limited diversion of surface or shallow groundwater resources. Incorporating anthropogenic activity into PUB methods is essential given the high level of development of many basins. We extended an existing stochastic framework used to predict the flow duration curve to explore the effects of irrigation on streamflow dynamics. Four canonical scenarios were considered in which irrigation water was (i) primarily sourced from water imports, (ii) primarily sourced from direct in-channel diversions, (iii) sourced from shallow groundwater with direct connectivity to stream channels, or (iv) sourced from deep groundwater that is indirectly connected to surface flow via a shallow aquifer. By comparing the predicted flow duration curves to those predicted by accounting for climate and geomorphic factors in isolation, specific "fingerprints" of human water withdrawals could be identified for the different irrigation scenarios, and shown to be sensitive to irrigation volumes and scheduling. The results provide a first insight into PUB methodologies that could be employed in heavily managed basins.

Development of optically pumped DBR-free semiconductor disk lasers (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yang, Zhou; Albrecht, Alexander R.; Cederberg, Jeffrey G.; Sheik-Bahae, Mansoor

2017-03-01

Semiconductor disk lasers (SDLs) are attractive for applications requiring good beam quality, wavelength versatility, and high output powers. Typical SDLs utilize the active mirror geometry, where a semiconductor DBR is integrated with the active region by growth or post-growth bonding. This imposes restrictions for the SDL design, like material system choice, thermal management, and effective gain bandwidth. In DBR-free geometry, these restrictions can be alleviated. An integrated gain model predicts DBR-free geometry with twice the gain bandwidth of typical SDLs, which has been experimentally verified with active regions near 1 μm and 1.15 μm. The lift-off and bonding technique enables the integration of semiconductor active regions with arbitrary high quality substrates, allowing novel monolithic geometries. Bonding an active region onto a straight side of a commercial fused silica right angle prism, and attaching a high reflectivity mirror onto the hypotenuse side, with quasi CW pumping at 780 nm, lasing operation was achieved at 1037 nm with 0.2 mW average power at 1.6 mW average pump power. Laser dynamics show that thermal lens generation in the active region bottlenecks the laser efficiency. Investigations on total internal reflection based monolithic ring cavities are ongoing. These geometries would allow the intracavity integration of 2D materials or other passive absorbers, which could be relevant for stable mode locking. Unlike typical monolithic microchip SDLs, with the evanescent wave coupling technique, these monolithic geometries allow variable coupling efficiency.

Constraining slip rates and spacings for active normal faults

NASA Astrophysics Data System (ADS)

Cowie, Patience A.; Roberts, Gerald P.

2001-12-01

Numerous observations of extensional provinces indicate that neighbouring faults commonly slip at different rates and, moreover, may be active over different time intervals. These published observations include variations in slip rate measured along-strike of a fault array or fault zone, as well as significant across-strike differences in the timing and rates of movement on faults that have a similar orientation with respect to the regional stress field. Here we review published examples from the western USA, the North Sea, and central Greece, and present new data from the Italian Apennines that support the idea that such variations are systematic and thus to some extent predictable. The basis for the prediction is that: (1) the way in which a fault grows is fundamentally controlled by the ratio of maximum displacement to length, and (2) the regional strain rate must remain approximately constant through time. We show how data on fault lengths and displacements can be used to model the observed patterns of long-term slip rate where measured values are sparse. Specifically, we estimate the magnitude of spatial variation in slip rate along-strike and relate it to the across-strike spacing between active faults.

Influence of dorsolateral prefrontal cortex and ventral striatum on risk avoidance in addiction: a mediation analysis.

PubMed

Yamamoto, Dorothy J; Woo, Choong-Wan; Wager, Tor D; Regner, Michael F; Tanabe, Jody

2015-04-01

Alterations in frontal and striatal function are hypothesized to underlie risky decision making in drug users, but how these regions interact to affect behavior is incompletely understood. We used mediation analysis to investigate how prefrontal cortex and ventral striatum together influence risk avoidance in abstinent drug users. Thirty-seven abstinent substance-dependent individuals (SDI) and 43 controls underwent fMRI while performing a decision-making task involving risk and reward. Analyses of a priori regions-of-interest tested whether activity in dorsolateral prefrontal cortex (DLPFC) and ventral striatum (VST) explained group differences in risk avoidance. Whole-brain analysis was conducted to identify brain regions influencing the negative VST-risk avoidance relationship. Right DLPFC (RDLPFC) positively mediated the group-risk avoidance relationship (p < 0.05); RDLPFC activity was higher in SDI and predicted higher risk avoidance across groups, controlling for SDI vs. Conversely, VST activity negatively influenced risk avoidance (p < 0.05); it was higher in SDI, and predicted lower risk avoidance. Whole-brain analysis revealed that, across group, RDLPFC and left temporal-parietal junction positively (p ≤ 0.001) while right thalamus and left middle frontal gyrus negatively (p < 0.005) mediated the VST activity-risk avoidance relationship. RDLPFC activity mediated less risky decision making while VST mediated more risky decision making across drug users and controls. These results suggest a dual pathway underlying decision making, which, if imbalanced, may adversely influence choices involving risk. Modeling contributions of multiple brain systems to behavior through mediation analysis could lead to a better understanding of mechanisms of behavior and suggest neuromodulatory treatments for addiction. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Parietal control network activation during memory tasks may be associated with the co-occurrence of externally and internally directed cognition: A cross-function meta-analysis.

PubMed

Kim, Hongkeun

2018-03-15

Functional neuroimaging studies on episodic memory retrieval consistently indicated the activation of the precuneus (PCU), mid-cingulate cortex (MCC), and lateral intraparietal sulcus (latIPS) regions. Although studies typically interpreted these activations in terms of memory retrieval processes, resting-state functional connectivity data indicate that these regions are part of the frontoparietal control network, suggesting a more general, cross-functional role. In this regard, this study proposes a novel hypothesis which suggests that the parietal control network plays a strong role in accommodating the co-occurrence of externally directed cognition (EDC) and internally directed cognition (IDC), which are typically antagonistic to each other. To evaluate how well this dual cognitive processes hypothesis can account for parietal activation patterns during memory tasks, this study provides a cross-function meta-analysis involving 3 different memory paradigms, namely, retrieval success (hit > correct rejection), repetition enhancement (repeated > novel), and subsequent forgetting (forgotten > remembered). Common to these paradigms is that the target condition may involve both EDC (stimulus processing and motor responding) and IDC (intentional remembering, involuntary awareness of previous encounter, or task-unrelated thoughts) strongly, whereas the reference condition may involve EDC to a greater extent, but IDC to a lesser extent. Thus, the dual cognitive processes hypothesis predicts that each of these paradigms will activate similar, overlapping PCU, MCC, and latIPS regions. The results were fully consistent with the prediction, supporting the dual cognitive processes hypothesis. Evidence from relevant prior studies suggests that the dual cognitive processes hypothesis may also apply to non-memory domain tasks. Copyright © 2018 Elsevier B.V. All rights reserved.

Influence of dorsolateral prefrontal cortex and ventral striatum on risk avoidance in addiction: a mediation analysis*

PubMed Central

Yamamoto, Dorothy J.; Woo, Choong-Wan; Wager, Tor D.; Regner, Michael F.; Tanabe, Jody

2015-01-01

Background Alterations in frontal and striatal function are hypothesized to underlie risky decision-making in drug users, but how these regions interact to affect behavior is incompletely understood. We used mediation analysis to investigate how prefrontal cortex and ventral striatum together influence risk avoidance in abstinent drug users. Method Thirty-seven abstinent substance-dependent individuals (SDI) and 43 controls underwent fMRI while performing a decision-making task involving risk and reward. Analyses of a priori regions-of-interest tested whether activity in dorsolateral prefrontal cortex (DLPFC) and ventral striatum (VST) explained group differences in risk avoidance. Whole-brain analysis was conducted to identify brain regions influencing the negative VST-risk avoidance relationship. Results Right DLPFC (RDLPFC) positively mediated the group-risk avoidance relationship (p < 0.05); RDLPFC activity was higher in SDI and predicted higher risk avoidance across groups, controlling for SDI vs. controls. Conversely, VST activity negatively influenced risk avoidance (p < 0.05); it was higher in SDI, and predicted lower risk avoidance. Whole-brain analysis revealed that, across group, RDLPFC and left temporal-parietal junction positively (p ≤ 0.001) while right thalamus and left middle frontal gyrus negatively (p < 0.005) mediated the VST activity-risk avoidance relationship. Conclusion RDLPFC activity mediated less risky decision-making while VST mediated more risky decision-making across drug users and controls. These results suggest a dual pathway underlying decision-making, which, if imbalanced, may adversely influence choices involving risk. Modeling contributions of multiple brain systems to behavior through mediation analysis could lead to a better understanding of mechanisms of behavior and suggest neuromodulatory treatments for addiction. PMID:25736619

fMRI of alterations in reward selection, anticipation, and feedback in major depressive disorder.

PubMed

Smoski, Moria J; Felder, Jennifer; Bizzell, Joshua; Green, Steven R; Ernst, Monique; Lynch, Thomas R; Dichter, Gabriel S

2009-11-01

The purpose of the present investigation was to evaluate reward processing in unipolar major depressive disorder (MDD). Specifically, we investigated whether adults with MDD demonstrated hyporesponsivity in striatal brain regions and/or hyperresponsivity in cortical brain regions involved in conflict monitoring using a Wheel of Fortune task designed to probe responses during reward selection, reward anticipation, and reward feedback. Functional magnetic resonance imaging (fMRI) data indicated that the MDD group was characterized by reduced activation of striatal reward regions during reward selection, reward anticipation, and reward feedback, supporting previous data indicating hyporesponsivity of reward systems in MDD. Support was not found for hyperresponsivity of cognitive control regions during reward selection or reward anticipation. Instead, MDD participants showed hyperresponsivity in orbitofrontal cortex, a region associated with assessment of risk and reward, during reward selection, as well as decreased activation of the middle frontal gyrus and the rostral cingulate gyrus during reward selection and anticipation. Finally, depression severity was predicted by activation in bilateral midfrontal gyrus during reward selection. Results indicate that MDD is characterized by striatal hyporesponsivity, and that future studies of MDD treatments that seek to improve responses to rewarding stimuli should assess striatal functioning.

Real-Time CME Forecasting Using HMI Active-Region Magnetograms and Flare History

NASA Technical Reports Server (NTRS)

Falconer, David; Moore, Ron; Barghouty, Abdulnasser F.; Khazanov, Igor

2011-01-01

We have recently developed a method of predicting an active region s probability of producing a CME, an X-class Flare, an M-class Flare, or a Solar Energetic Particle Event from a free-energy proxy measured from SOHO/MDI line-of-sight magnetograms. This year we have added three major improvements to our forecast tool: 1) Transition from MDI magnetogram to SDO/HMI magnetogram allowing us near-real-time forecasts, 2) Automation of acquisition and measurement of HMI magnetograms giving us near-real-time forecasts (no older than 2 hours), and 3) Determination of how to improve forecast by using the active region s previous flare history in combination with its free-energy proxy. HMI was turned on in May 2010 and MDI was turned off in April 2011. Using the overlap period, we have calibrated HMI to yield what MDI would measure. This is important since the value of the free-energy proxy used for our forecast is resolution dependent, and the forecasts are made from results of a 1996-2004 database of MDI observations. With near-real-time magnetograms from HMI, near-real-time forecasts are now possible. We have augmented the code so that it continually acquires and measures new magnetograms as they become available online, and updates the whole-sun forecast from the coming day. The next planned improvement is to use an active region s previous flare history, in conjunction with its free-energy proxy, to forecast the active region s event rate. It has long been known that active regions that have produced flares in the past are likely to produce flares in the future, and that active regions that are nonpotential (have large free-energy) are more likely to produce flares in the future. This year we have determined that persistence of flaring is not just a reflection of an active region s free energy. In other words, after controlling for free energy, we have found that active regions that have flared recently are more likely to flare in the future.

Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions.

PubMed

Teklehaimanot, Hailay D; Schwartz, Joel; Teklehaimanot, Awash; Lipsitch, Marc

2004-11-19

Timely and accurate information about the onset of malaria epidemics is essential for effective control activities in epidemic-prone regions. Early warning methods that provide earlier alerts (usually by the use of weather variables) may permit control measures to interrupt transmission earlier in the epidemic, perhaps at the expense of some level of accuracy. Expected case numbers were modeled using a Poisson regression with lagged weather factors in a 4th-degree polynomial distributed lag model. For each week, the numbers of malaria cases were predicted using coefficients obtained using all years except that for which the prediction was being made. The effectiveness of alerts generated by the prediction system was compared against that of alerts based on observed cases. The usefulness of the prediction system was evaluated in cold and hot districts. The system predicts the overall pattern of cases well, yet underestimates the height of the largest peaks. Relative to alerts triggered by observed cases, the alerts triggered by the predicted number of cases performed slightly worse, within 5% of the detection system. The prediction-based alerts were able to prevent 10-25% more cases at a given sensitivity in cold districts than in hot ones. The prediction of malaria cases using lagged weather performed well in identifying periods of increased malaria cases. Weather-derived predictions identified epidemics with reasonable accuracy and better timeliness than early detection systems; therefore, the prediction of malarial epidemics using weather is a plausible alternative to early detection systems.

Impacts of West Nile Virus on wildlife

USGS Publications Warehouse

Saito, E.K.; Wild, M.A.

2004-01-01

The recent epidemic of West Nile virus in the United States proved to be unexpectedly active and was the largest epidemic of the virus ever recorded. Much remains to be discovered about the ecology and epidemiology of West Nile virus in the United States, including which species are important in maintaining the virus in nature, why some species are more susceptible to lethal infection, and what environmental factors are important in predicting future epidemics. These factors will likely vary regionally, depending on local ecological characteristics. Until scientists better understand the virus and factors influencing its activity, predicting its effects for future seasons is impossible. However, experts are certain about one thing: West Nile virus is here to stay.

Coronal Heating: Testing Models of Coronal Heating by Forward-Modeling the AIA Emission of the Ansample of Coronal Loops

NASA Astrophysics Data System (ADS)

Malanushenko, A. V.

2015-12-01

We present a systemic exploration of the properties of coronal heating, by forward-modeling the emission of the ensemble of 1D quasi-steady loops. This approximations were used in many theoretical models of the coronal heating. The latter is described in many such models in the form of power laws, relating heat flux through the photosphere or volumetric heating to the strength of the magnetic field and length of a given field line. We perform a large search in the parameter space of these power laws, amongst other variables, and compare the resulting emission of the active region to that observed by AIA. We use a recently developed magnetic field model which uses shapes of coronal loops to guide the magnetic model; the result closely resembles observed structures by design. We take advantage of this, by comparing, in individual sub-regions of the active region, the emission of the active region and its synthetic model. This study allows us to rule out many theoretical models and formulate predictions for the heating models to come.

Using Mid Infrared Spectroscopy to Predict the Decomposability of Soil Organic Matter Stored in Arctic Tundra Soils

NASA Astrophysics Data System (ADS)

Matamala, R.; Fan, Z.; Jastrow, J. D.; Liang, C.; Calderon, F.; Michaelson, G.; Ping, C. L.; Mishra, U.; Hofmann, S. M.

2016-12-01

The large amounts of organic matter stored in permafrost-region soils are preserved in a relatively undecomposed state by the cold and wet environmental conditions limiting decomposer activity. With pending climate changes and the potential for warming of Arctic soils, there is a need to better understand the amount and potential susceptibility to mineralization of the carbon stored in the soils of this region. Studies have suggested that soil C:N ratio or other indicators based on the molecular composition of soil organic matter could be good predictors of potential decomposability. In this study, we investigated the capability of Fourier-transform mid infrared spectroscopy (MidIR) spectroscopy to predict the evolution of carbon dioxide (CO2) produced by Arctic tundra soils during a 60-day laboratory incubation. Soils collected from four tundra sites on the Coastal Plain, and Arctic Foothills of the North Slope of Alaska were separated into active-layer organic, active-layer mineral, and upper permafrost and incubated at 1, 4, 8 and 16 °C. Carbon dioxide production was measured throughout the incubations. Total soil organic carbon (SOC) and total nitrogen (TN) concentrations, salt (0.5 M K2SO4) extractable organic matter (SEOM), and MidIR spectra of the soils were measured before and after incubation. Multivariate partial least squares (PLS) modeling was used to predict cumulative CO2 production, decay rates, and the other measurements. MidIR reliably estimated SOC and TN and SEOM concentrations. The MidIR prediction models of CO2 production were very good for active-layer mineral and upper permafrost soils and good for the active-layer organic soils. SEOM was also a very good predictor of CO2 produced during the incubations. Analysis of the standardized beta coefficients from the PLS models of CO2 production for the three soil layers indicated a small number (9) of influential spectral bands. Of these, bands associated with O-H and N-H stretch, carbonates, and ester C-O appeared to be most important for predicting CO2 production for both active-layer mineral and upper permafrost soils. Further analysis of these influential bands and their relationships to SEOM in soil will be explored. Our results show that the MidIR spectra contains valuable information that can be related to decomposability of soils.

A Comparison of Five FMRI Protocols for Mapping Speech Comprehension Systems

PubMed Central

Binder, Jeffrey R.; Swanson, Sara J.; Hammeke, Thomas A.; Sabsevitz, David S.

2008-01-01

Aims Many fMRI protocols for localizing speech comprehension have been described, but there has been little quantitative comparison of these methods. We compared five such protocols in terms of areas activated, extent of activation, and lateralization. Methods FMRI BOLD signals were measured in 26 healthy adults during passive listening and active tasks using words and tones. Contrasts were designed to identify speech perception and semantic processing systems. Activation extent and lateralization were quantified by counting activated voxels in each hemisphere for each participant. Results Passive listening to words produced bilateral superior temporal activation. After controlling for pre-linguistic auditory processing, only a small area in the left superior temporal sulcus responded selectively to speech. Active tasks engaged an extensive, bilateral attention and executive processing network. Optimal results (consistent activation and strongly lateralized pattern) were obtained by contrasting an active semantic decision task with a tone decision task. There was striking similarity between the network of brain regions activated by the semantic task and the network of brain regions that showed task-induced deactivation, suggesting that semantic processing occurs during the resting state. Conclusions FMRI protocols for mapping speech comprehension systems differ dramatically in pattern, extent, and lateralization of activation. Brain regions involved in semantic processing were identified only when an active, non-linguistic task was used as a baseline, supporting the notion that semantic processing occurs whenever attentional resources are not controlled. Identification of these lexical-semantic regions is particularly important for predicting language outcome in patients undergoing temporal lobe surgery. PMID:18513352

Prediction, Assessment of the Rift Valley Fever Activity in East and Southern Africa 2006–2008 and Possible Vector Control Strategies

PubMed Central

Anyamba, Assaf; Linthicum, Kenneth J.; Small, Jennifer; Britch, Seth C.; Pak, Edwin; de La Rocque, Stephane; Formenty, Pierre; Hightower, Allen W.; Breiman, Robert F.; Chretien, Jean-Paul; Tucker, Compton J.; Schnabel, David; Sang, Rosemary; Haagsma, Karl; Latham, Mark; Lewandowski, Henry B.; Magdi, Salih Osman; Mohamed, Mohamed Ally; Nguku, Patrick M.; Reynes, Jean-Marc; Swanepoel, Robert

2010-01-01

Historical outbreaks of Rift Valley fever (RVF) since the early 1950s have been associated with cyclical patterns of the El Niño/Southern Oscillation (ENSO) phenomenon, which results in elevated and widespread rainfall over the RVF endemic areas of Africa. Using satellite measurements of global and regional elevated sea surface temperatures, elevated rainfall, and satellite derived-normalized difference vegetation index data, we predicted with lead times of 2–4 months areas where outbreaks of RVF in humans and animals were expected and occurred in the Horn of Africa, Sudan, and Southern Africa at different time periods from September 2006 to March 2008. Predictions were confirmed by entomological field investigations of virus activity and by reported cases of RVF in human and livestock populations. This represents the first series of prospective predictions of RVF outbreaks and provides a baseline for improved early warning, control, response planning, and mitigation into the future. PMID:20682905

Blunted ventral striatal responses to anticipated rewards foreshadow problematic drug use in novelty-seeking adolescents

PubMed Central

Büchel, Christian; Peters, Jan; Banaschewski, Tobias; Bokde, Arun L. W.; Bromberg, Uli; Conrod, Patricia J.; Flor, Herta; Papadopoulos, Dimitri; Garavan, Hugh; Gowland, Penny; Heinz, Andreas; Walter, Henrik; Ittermann, Bernd; Mann, Karl; Martinot, Jean-Luc; Paillère-Martinot, Marie-Laure; Nees, Frauke; Paus, Tomas; Pausova, Zdenka; Poustka, Luise; Rietschel, Marcella; Robbins, Trevor W.; Smolka, Michael N.; Gallinat, Juergen; Schumann, Gunter; Knutson, Brian; Arroyo, Mercedes; Artiges, Eric; Aydin, Semiha; Bach, Christine; Barbot, Alexis; Barker, Gareth; Bruehl, Ruediger; Cattrell, Anna; Constant, Patrick; Crombag, Hans; Czech, Katharina; Dalley, Jeffrey; Decideur, Benjamin; Desrivieres, Sylvane; Fadai, Tahmine; Fauth-Buhler, Mira; Feng, Jianfeng; Filippi, Irinia; Frouin, Vincent; Fuchs, Birgit; Gemmeke, Isabel; Genauck, Alexander; Hanratty, Eanna; Heinrichs, Bert; Heym, Nadja; Hubner, Thomas; Ihlenfeld, Albrecht; Ing, Alex; Ireland, James; Jia, Tianye; Jones, Jennifer; Jurk, Sarah; Kaviani, Mehri; Klaassen, Arno; Kruschwitz, Johann; Lalanne, Christophe; Lanzerath, Dirk; Lathrop, Mark; Lawrence, Claire; Lemaitre, Hervé; Macare, Christine; Mallik, Catherine; Mar, Adam; Martinez-Medina, Lourdes; Mennigen, Eva; de Carvahlo, Fabiana Mesquita; Mignon, Xavier; Millenet, Sabina; Miranda, Ruben; Müller, Kathrin; Nymberg, Charlotte; Parchetka, Caroline; Pena-Oliver, Yolanda; Pentilla, Jani; Poline, Jean-Baptiste; Quinlan, Erin Burke; Rapp, Michael; Ripke, Stephan; Ripley, Tamzin; Robert, Gabriel; Rogers, John; Romanowski, Alexander; Ruggeri, Barbara; Schmäl, Christine; Schmidt, Dirk; Schneider, Sophia; Schubert, Florian; Schwartz, Yannick; Sommer, Wolfgang; Spanagel, Rainer; Speiser, Claudia; Spranger, Tade; Stedman, Alicia; Stephens, Dai; Strache, Nicole; Ströhle, Andreas; Struve, Maren; Subramaniam, Naresh; Theobald, David; Vetter, Nora; Vulser, Helene; Weiss, Katharina; Whelan, Robert; Williams, Steve; Xu, Bing; Yacubian, Juliana; Yu, Tao; Ziesch, Veronika

2017-01-01

Novelty-seeking tendencies in adolescents may promote innovation as well as problematic impulsive behaviour, including drug abuse. Previous research has not clarified whether neural hyper- or hypo-responsiveness to anticipated rewards promotes vulnerability in these individuals. Here we use a longitudinal design to track 144 novelty-seeking adolescents at age 14 and 16 to determine whether neural activity in response to anticipated rewards predicts problematic drug use. We find that diminished BOLD activity in mesolimbic (ventral striatal and midbrain) and prefrontal cortical (dorsolateral prefrontal cortex) regions during reward anticipation at age 14 predicts problematic drug use at age 16. Lower psychometric conscientiousness and steeper discounting of future rewards at age 14 also predicts problematic drug use at age 16, but the neural responses independently predict more variance than psychometric measures. Together, these findings suggest that diminished neural responses to anticipated rewards in novelty-seeking adolescents may increase vulnerability to future problematic drug use. PMID:28221370

Predicting future spatial distribution of SOC across entire France

NASA Astrophysics Data System (ADS)

Meersmans, Jeroen; Van Rompaey, Anton; Quine, Tim; Martin, Manuel; Pagé, Christian; Arrouays, Dominique

2013-04-01

Soil organic carbon (SOC) is widely recognized as a key factor controlling soil quality and as a crucial and active component of the global C-cycle. Hence, there exists a growing interest in monitoring and modeling the spatial and temporal behavior of this pool. So far, a large attempt has been made to map SOC at national scales for current and/or past situations. Despite some coarse predictions, detailed spatial SOC predictions for the future are still lacking. In this study we aim to predict future spatial evolution of SOC driven by climate and land use change for France up to the year 2100. Therefore, we combined 1) an existing model, predicting SOC as a function of soil type, climate, land use and management (Meersmans et al 2012), with 2) eight different IPCC spatial explicit climate change predictions (conducted by CERFACS) and 3) Land use change scenario predictions. We created business-as-usual land use change scenarios by extrapolating observed trends and calibrating logistic regression models, incorporating a large set of physical and socio-economic factors, at the regional level in combination with a multi-objective land allocation (MOLA) procedure. The resultant detailed projections of future SOC evolution across all regions of France, allow us to identify regions that are most likely to be characterized by a significant gain or loss of SOC and the degree to which land use decisions/outcomes control the scale of loss and gain. Therefore, this methodology and resulting maps can be considered as powerful tools to aid decision making concerning appropriate soil management, in order to enlarge SOC storage possibilities and reduce soil related CO2 fluxes.

Neural activity during affect labeling predicts expressive writing effects on well-being: GLM and SVM approaches.

PubMed

Memarian, Negar; Torre, Jared B; Haltom, Kate E; Stanton, Annette L; Lieberman, Matthew D

2017-09-01

Affect labeling (putting feelings into words) is a form of incidental emotion regulation that could underpin some benefits of expressive writing (i.e. writing about negative experiences). Here, we show that neural responses during affect labeling predicted changes in psychological and physical well-being outcome measures 3 months later. Furthermore, neural activity of specific frontal regions and amygdala predicted those outcomes as a function of expressive writing. Using supervised learning (support vector machines regression), improvements in four measures of psychological and physical health (physical symptoms, depression, anxiety and life satisfaction) after an expressive writing intervention were predicted with an average of 0.85% prediction error [root mean square error (RMSE) %]. The predictions were significantly more accurate with machine learning than with the conventional generalized linear model method (average RMSE: 1.3%). Consistent with affect labeling research, right ventrolateral prefrontal cortex (RVLPFC) and amygdalae were top predictors of improvement in the four outcomes. Moreover, RVLPFC and left amygdala predicted benefits due to expressive writing in satisfaction with life and depression outcome measures, respectively. This study demonstrates the substantial merit of supervised machine learning for real-world outcome prediction in social and affective neuroscience. © The Author (2017). Published by Oxford University Press.

Sleep deprivation alters functioning within the neural network underlying the covert orienting of attention.

PubMed

Mander, Bryce A; Reid, Kathryn J; Davuluri, Vijay K; Small, Dana M; Parrish, Todd B; Mesulam, M-Marsel; Zee, Phyllis C; Gitelman, Darren R

2008-06-27

One function of spatial attention is to enable goal-directed interactions with the environment through the allocation of neural resources to motivationally relevant parts of space. Studies have shown that responses are enhanced when spatial attention is predictively biased towards locations where significant events are expected to occur. Previous studies suggest that the ability to bias attention predictively is related to posterior cingulate cortex (PCC) activation [Small, D.M., et al., 2003. The posterior cingulate and medial prefrontal cortex mediate the anticipatory allocation of spatial attention. Neuroimage 18, 633-41]. Sleep deprivation (SD) impairs selective attention and reduces PCC activity [Thomas, M., et al., 2000. Neural basis of alertness and cognitive performance impairments during sleepiness. I. Effects of 24 h of sleep deprivation on waking human regional brain activity. J. Sleep Res. 9, 335-352]. Based on these findings, we hypothesized that SD would affect PCC function and alter the ability to predictively allocate spatial attention. Seven healthy, young adults underwent functional magnetic resonance imaging (fMRI) following normal rest and 34-36 h of SD while performing a task in which attention was shifted in response to peripheral targets preceded by spatially informative (valid), misleading (invalid), or uninformative (neutral) cues. When rested, but not when sleep-deprived, subjects responded more quickly to targets that followed valid cues than those after neutral or invalid cues. Brain activity during validly cued trials with a reaction time benefit was compared to activity in trials with no benefit. PCC activation was greater during trials with a reaction time benefit following normal rest. In contrast, following SD, reaction time benefits were associated with activation in the left intraparietal sulcus, a region associated with receptivity to stimuli at unexpected locations. These changes may render sleep-deprived individuals less able to anticipate the locations of upcoming events, and more susceptible to distraction by stimuli at irrelevant locations.

Predicting Potential C Mineralization of Tundra Soils Using Spectroscopy Techniques

USDA-ARS?s Scientific Manuscript database

The large amounts of organic matter stored in permafrost-region soils are preserved in a relatively undecomposed state by the cold and wet environmental conditions limiting decomposer activity. With pending climate changes and the potential for warming of Arctic soils, there is a need to better unde...

Modeling emissions and environmental impacts of transportation activities associated with high volume horizontal hydraulic fracturing operations in the Marcellus Shale Formation : final report.

DOT National Transportation Integrated Search

2015-09-18

The researchers' initial University Transportation Research Center (UTRC) research project identified routes and road segments with predicted high volumes of truck traffic related to natural gas extraction in the Marcellus Shale region. Results also ...

The needs for prediction and real-time monitoring for the flare build-up study

NASA Technical Reports Server (NTRS)

Svestka, Z.

1979-01-01

Similarities between plasma instabilities occurring in the magnetospheric tail and in active regions on the Sun are discussed. Intense observations of the flare build-up processes on the Sun planned for May and June 1980 as a part of the Solar Maximum Year are described.

Combining Regional- and Local-Scale Air Quality Models with Exposure Models for Use in Environmental Health Studies

EPA Science Inventory

Population-based human exposure models predict the distribution of personal exposures to pollutants of outdoor origin using a variety of inputs, including: air pollution concentrations; human activity patterns, such as the amount of time spent outdoors vs. indoors, commuting, wal...

Sequence fingerprints distinguish erroneous from correct predictions of intrinsically disordered protein regions.

PubMed

Saravanan, Konda Mani; Dunker, A Keith; Krishnaswamy, Sankaran

2017-12-27

More than 60 prediction methods for intrinsically disordered proteins (IDPs) have been developed over the years, many of which are accessible on the World Wide Web. Nearly, all of these predictors give balanced accuracies in the ~65%-~80% range. Since predictors are not perfect, further studies are required to uncover the role of amino acid residues in native IDP as compared to predicted IDP regions. In the present work, we make use of sequences of 100% predicted IDP regions, false positive disorder predictions, and experimentally determined IDP regions to distinguish the characteristics of native versus predicted IDP regions. A higher occurrence of asparagine is observed in sequences of native IDP regions but not in sequences of false positive predictions of IDP regions. The occurrences of certain combinations of amino acids at the pentapeptide level provide a distinguishing feature in the IDPs with respect to globular proteins. The distinguishing features presented in this paper provide insights into the sequence fingerprints of amino acid residues in experimentally determined as compared to predicted IDP regions. These observations and additional work along these lines should enable the development of improvements in the accuracy of disorder prediction algorithm.

Influences of misprediction costs on solar flare prediction

NASA Astrophysics Data System (ADS)

Huang, Xin; Wang, HuaNing; Dai, XingHua

2012-10-01

The mispredictive costs of flaring and non-flaring samples are different for different applications of solar flare prediction. Hence, solar flare prediction is considered a cost sensitive problem. A cost sensitive solar flare prediction model is built by modifying the basic decision tree algorithm. Inconsistency rate with the exhaustive search strategy is used to determine the optimal combination of magnetic field parameters in an active region. These selected parameters are applied as the inputs of the solar flare prediction model. The performance of the cost sensitive solar flare prediction model is evaluated for the different thresholds of solar flares. It is found that more flaring samples are correctly predicted and more non-flaring samples are wrongly predicted with the increase of the cost for wrongly predicting flaring samples as non-flaring samples, and the larger cost of wrongly predicting flaring samples as non-flaring samples is required for the higher threshold of solar flares. This can be considered as the guide line for choosing proper cost to meet the requirements in different applications.

Now or Later? An fMRI study of the effects of endogenous opioid blockade on a decision-making network

PubMed Central

Boettiger, Charlotte A.; Kelley, Elizabeth A.; Mitchell, Jennifer M.; D’Esposito, Mark; Fields, Howard L.

2009-01-01

Previously, we found that distinct brain areas predict individual selection bias in decisions between small immediate (“Now”) and larger delayed rewards (“Later”). Furthermore, such selection bias can be manipulated by endogenous opioid blockade. To test whether blocking endogenous opioids with Naltrexone (NTX) alters brain activity during decision-making in areas predicting individual bias, we compared fMRI BOLD signal correlated with Now versus Later decision-making after acute administration of NTX (50 mg) or placebo. We tested abstinent alcoholics and control subjects in a double-blind two-session design. We defined regions of interest (ROI) centered on activation peaks predicting Now versus Later selection bias. NTX administration significantly increased BOLD signal during decision-making in the right lateral orbital gyrus ROI, an area where enhanced activity during decision-making predicts Later bias. Exploratory analyses identified additional loci where BOLD signal during decision-making was enhanced (left orbitofrontal cortex, left inferior temporal gyrus, and cerebellum) or reduced (right superior temporal pole) by NTX. Additional analyses identified sites, including the right lateral orbital gyrus, in which NTX effects on BOLD signal predicted NTX effects on selection bias. These data agree with opioid receptor expression in human frontal and temporal cortices, and suggest possible mechanisms of NTX’s therapeutic effects. PMID:19258022

Prediction of hot regions in protein-protein interaction by combining density-based incremental clustering with feature-based classification.

PubMed

Hu, Jing; Zhang, Xiaolong; Liu, Xiaoming; Tang, Jinshan

2015-06-01

Discovering hot regions in protein-protein interaction is important for drug and protein design, while experimental identification of hot regions is a time-consuming and labor-intensive effort; thus, the development of predictive models can be very helpful. In hot region prediction research, some models are based on structure information, and others are based on a protein interaction network. However, the prediction accuracy of these methods can still be improved. In this paper, a new method is proposed for hot region prediction, which combines density-based incremental clustering with feature-based classification. The method uses density-based incremental clustering to obtain rough hot regions, and uses feature-based classification to remove the non-hot spot residues from the rough hot regions. Experimental results show that the proposed method significantly improves the prediction performance of hot regions. Copyright © 2015 Elsevier Ltd. All rights reserved.

The neural bases of cognitive conflict and control in moral judgment.

PubMed

Greene, Joshua D; Nystrom, Leigh E; Engell, Andrew D; Darley, John M; Cohen, Jonathan D

2004-10-14

Traditional theories of moral psychology emphasize reasoning and "higher cognition," while more recent work emphasizes the role of emotion. The present fMRI data support a theory of moral judgment according to which both "cognitive" and emotional processes play crucial and sometimes mutually competitive roles. The present results indicate that brain regions associated with abstract reasoning and cognitive control (including dorsolateral prefrontal cortex and anterior cingulate cortex) are recruited to resolve difficult personal moral dilemmas in which utilitarian values require "personal" moral violations, violations that have previously been associated with increased activity in emotion-related brain regions. Several regions of frontal and parietal cortex predict intertrial differences in moral judgment behavior, exhibiting greater activity for utilitarian judgments. We speculate that the controversy surrounding utilitarian moral philosophy reflects an underlying tension between competing subsystems in the brain.

Quantification of observed flare parameters in relation to a shear-index and verification of MHD models for flare prediction

NASA Technical Reports Server (NTRS)

Wu, S. T.

1987-01-01

The goal for the SAMEX magnetograph's optical system is to accurately measure the polarization state of sunlight in a narrow spectral bandwidth over the field of view of an active region to make an accurate determination of the magnetic field in that region. The instrumental polarization is characterized. The optics and coatings were designed to minimize this spurious polarization introduced by foreoptics. The method developed to calculate the instrumental polarization of the SAMEX optics is described.

Impact of Land Use Management and Soil Properties on Denitrifier Communities of Namibian Savannas.

PubMed

Braker, Gesche; Matthies, Diethart; Hannig, Michael; Brandt, Franziska Barbara; Brenzinger, Kristof; Gröngröft, Alexander

2015-11-01

We studied potential denitrification activity and the underlying denitrifier communities in soils from a semiarid savanna ecosystem of the Kavango region in NE Namibia to help in predicting future changes in N(2)O emissions due to continuing changes of land use in this region. Soil type and land use (pristine, fallow, and cultivated soils) influenced physicochemical characteristics of the soils that are relevant to denitrification activity and N(2)O fluxes from soils and affected potential denitrification activity. Potential denitrification activity was assessed by using the denitrifier enzyme activity (DEA) assay as a proxy for denitrification activity in the soil. Soil type and land use influenced C and N contents of the soils. Pristine soils that had never been cultivated had a particularly high C content. Cultivation reduced soil C content and the abundance of denitrifiers and changed the composition of the denitrifier communities. DEA was strongly and positively correlated with soil C content and was higher in pristine than in fallow or recently cultivated soils. Soil type and the composition of both the nirK- and nirS-type denitrifier communities also influenced DEA. In contrast, other soil characteristics like N content, C:N ratio, and pH did not predict DEA. These findings suggest that due to greater availability of soil organic matter, and hence a more effective N cycling, the natural semiarid grasslands emit more N(2)O than managed lands in Namibia.

Transcription map of Xq27: candidates for several X-linked diseases.

PubMed

Zucchi, I; Jones, J; Affer, M; Montagna, C; Redolfi, E; Susani, L; Vezzoni, P; Parvari, R; Schlessinger, D; Whyte, M P; Mumm, S

1999-04-15

Human Xq27 contains candidate regions for several disorders, yet is predicted to be a gene-poor cytogenetic band. We have developed a transcription map for the entire cytogenetic band to facilitate the identification of the relatively small number of expected candidate genes. Two approaches were taken to identify genes: (1) a group of 64 unique STSs that were generated during the physical mapping of the region were used in RT-PCR with RNA from human adult and fetal brain and (2) ESTs that have been broadly mapped to this region of the chromosome were finely mapped using a high-resolution yeast artificial chromosome contig. This combined approach identified four distinct regions of transcriptional activity within the Xq27 band. Among them is a region at the centromeric boundary that contains candidate regions for several rare developmental disorders (X-linked recessive hypoparathyroidism, thoracoabdominal syndrome, albinism-deafness syndrome, and Borjeson-Forssman-Lehman syndrome). Two transcriptionally active regions were identified in the center of Xq27 and include candidate regions for X-linked mental retardation syndrome 6, X-linked progressive cone dystrophy, X-linked retinitis pigmentosa 24, and a prostate cancer susceptibility locus. The fourth region of transcriptional activity encompasses the FMR1 (FRAXA) and FMR2 (FRAXE) genes. The analysis thus suggests clustered transcription in Xq27 and provides candidates for several heritable disorders for which the causative genes have not yet been found. Copyright 1999 Academic Press.

Cloud-Based Numerical Weather Prediction for Near Real-Time Forecasting and Disaster Response

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Case, Jonathan; Venners, Jason; Schroeder, Richard; Checchi, Milton; Zavodsky, Bradley; Limaye, Ashutosh; O'Brien, Raymond

2015-01-01

The use of cloud computing resources continues to grow within the public and private sector components of the weather enterprise as users become more familiar with cloud-computing concepts, and competition among service providers continues to reduce costs and other barriers to entry. Cloud resources can also provide capabilities similar to high-performance computing environments, supporting multi-node systems required for near real-time, regional weather predictions. Referred to as "Infrastructure as a Service", or IaaS, the use of cloud-based computing hardware in an on-demand payment system allows for rapid deployment of a modeling system in environments lacking access to a large, supercomputing infrastructure. Use of IaaS capabilities to support regional weather prediction may be of particular interest to developing countries that have not yet established large supercomputing resources, but would otherwise benefit from a regional weather forecasting capability. Recently, collaborators from NASA Marshall Space Flight Center and Ames Research Center have developed a scripted, on-demand capability for launching the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS), which includes pre-compiled binaries of the latest version of the Weather Research and Forecasting (WRF) model. The WRF-EMS provides scripting for downloading appropriate initial and boundary conditions from global models, along with higher-resolution vegetation, land surface, and sea surface temperature data sets provided by the NASA Short-term Prediction Research and Transition (SPoRT) Center. This presentation will provide an overview of the modeling system capabilities and benchmarks performed on the Amazon Elastic Compute Cloud (EC2) environment. In addition, the presentation will discuss future opportunities to deploy the system in support of weather prediction in developing countries supported by NASA's SERVIR Project, which provides capacity building activities in environmental monitoring and prediction across a growing number of regional hubs throughout the world. Capacity-building applications that extend numerical weather prediction to developing countries are intended to provide near real-time applications to benefit public health, safety, and economic interests, but may have a greater impact during disaster events by providing a source for local predictions of weather-related hazards, or impacts that local weather events may have during the recovery phase.

Reading a Suspenseful Literary Text Activates Brain Areas Related to Social Cognition and Predictive Inference

PubMed Central

Lehne, Moritz; Engel, Philipp; Rohrmeier, Martin; Menninghaus, Winfried; Jacobs, Arthur M.; Koelsch, Stefan

2015-01-01

Stories can elicit powerful emotions. A key emotional response to narrative plots (e.g., novels, movies, etc.) is suspense. Suspense appears to build on basic aspects of human cognition such as processes of expectation, anticipation, and prediction. However, the neural processes underlying emotional experiences of suspense have not been previously investigated. We acquired functional magnetic resonance imaging (fMRI) data while participants read a suspenseful literary text (E.T.A. Hoffmann's “The Sandman”) subdivided into short text passages. Individual ratings of experienced suspense obtained after each text passage were found to be related to activation in the medial frontal cortex, bilateral frontal regions (along the inferior frontal sulcus), lateral premotor cortex, as well as posterior temporal and temporo-parietal areas. The results indicate that the emotional experience of suspense depends on brain areas associated with social cognition and predictive inference. PMID:25946306

SOLAR CYCLE 25: ANOTHER MODERATE CYCLE?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cameron, R. H.; Schüssler, M.; Jiang, J., E-mail: cameron@mps.mpg.de

2016-06-01

Surface flux transport simulations for the descending phase of Cycle 24 using random sources (emerging bipolar magnetic regions) with empirically determined scatter of their properties provide a prediction of the axial dipole moment during the upcoming activity minimum together with a realistic uncertainty range. The expectation value for the dipole moment around 2020 (2.5 ± 1.1 G) is comparable to that observed at the end of Cycle 23 (about 2 G). The empirical correlation between the dipole moment during solar minimum and the strength of the subsequent cycle thus suggests that Cycle 25 will be of moderate amplitude, not muchmore » higher than that of the current cycle. However, the intrinsic uncertainty of such predictions resulting from the random scatter of the source properties is considerable and fundamentally limits the reliability with which such predictions can be made before activity minimum is reached.« less

Assessing Strategies Against Gambiense Sleeping Sickness Through Mathematical Modeling

PubMed Central

Rock, Kat S; Ndeffo-Mbah, Martial L; Castaño, Soledad; Palmer, Cody; Pandey, Abhishek; Atkins, Katherine E; Ndung’u, Joseph M; Hollingsworth, T Déirdre; Galvani, Alison; Bever, Caitlin; Chitnis, Nakul; Keeling, Matt J

2018-01-01

Abstract Background Control of gambiense sleeping sickness relies predominantly on passive and active screening of people, followed by treatment. Methods Mathematical modeling explores the potential of 3 complementary interventions in high- and low-transmission settings. Results Intervention strategies that included vector control are predicted to halt transmission most quickly. Targeted active screening, with better and more focused coverage, and enhanced passive surveillance, with improved access to diagnosis and treatment, are both estimated to avert many new infections but, when used alone, are unlikely to halt transmission before 2030 in high-risk settings. Conclusions There was general model consensus in the ranking of the 3 complementary interventions studied, although with discrepancies between the quantitative predictions due to differing epidemiological assumptions within the models. While these predictions provide generic insights into improving control, the most effective strategy in any situation depends on the specific epidemiology in the region and the associated costs. PMID:29860287

Evaluating Google Flu Trends in Latin America: Important Lessons for the Next Phase of Digital Disease Detection.

PubMed

Pollett, Simon; Boscardin, W John; Azziz-Baumgartner, Eduardo; Tinoco, Yeny O; Soto, Giselle; Romero, Candice; Kok, Jen; Biggerstaff, Matthew; Viboud, Cecile; Rutherford, George W

2017-01-01

 Latin America has a substantial burden of influenza and rising Internet access and could benefit from real-time influenza epidemic prediction web tools such as Google Flu Trends (GFT) to assist in risk communication and resource allocation during epidemics. However, there has never been a published assessment of GFT's accuracy in most Latin American countries or in any low- to middle-income country. Our aim was to evaluate GFT in Argentina, Bolivia, Brazil, Chile, Mexico, Paraguay, Peru, and Uruguay.  Weekly influenza-test positive proportions for the eight countries were obtained from FluNet for the period January 2011-December 2014. Concurrent weekly Google-predicted influenza activity in the same countries was abstracted from GFT. Pearson correlation coefficients between observed and Google-predicted influenza activity trends were determined for each country. Permutation tests were used to examine background seasonal correlation between FluNet and GFT by country.  There were frequent GFT prediction errors, with correlation ranging from r = -0.53 to 0.91. GFT-predicted influenza activity best correlated with FluNet data in Mexico follow by Uruguay, Argentina, Chile, Brazil, Peru, Bolivia and Paraguay. Correlation was generally highest in the more temperate countries with more regular influenza seasonality and lowest in tropical regions. A substantial amount of autocorrelation was noted, suggestive that GFT is not fully specific for influenza virus activity.  We note substantial inaccuracies with GFT-predicted influenza activity compared with FluNet throughout Latin America, particularly among tropical countries with irregular influenza seasonality. Our findings offer valuable lessons for future Internet-based biosurveillance tools. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Spatial Attention, Motor Intention, and Bayesian Cue Predictability in the Human Brain.

PubMed

Kuhns, Anna B; Dombert, Pascasie L; Mengotti, Paola; Fink, Gereon R; Vossel, Simone

2017-05-24

Predictions about upcoming events influence how we perceive and respond to our environment. There is increasing evidence that predictions may be generated based upon previous observations following Bayesian principles, but little is known about the underlying cortical mechanisms and their specificity for different cognitive subsystems. The present study aimed at identifying common and distinct neural signatures of predictive processing in the spatial attentional and motor intentional system. Twenty-three female and male healthy human volunteers performed two probabilistic cueing tasks with either spatial or motor cues while lying in the fMRI scanner. In these tasks, the percentage of cue validity changed unpredictably over time. Trialwise estimates of cue predictability were derived from a Bayesian observer model of behavioral responses. These estimates were included as parametric regressors for analyzing the BOLD time series. Parametric effects of cue predictability in valid and invalid trials were considered to reflect belief updating by precision-weighted prediction errors. The brain areas exhibiting predictability-dependent effects dissociated between the spatial attention and motor intention task, with the right temporoparietal cortex being involved during spatial attention and the left angular gyrus and anterior cingulate cortex during motor intention. Connectivity analyses revealed that all three areas showed predictability-dependent coupling with the right hippocampus. These results suggest that precision-weighted prediction errors of stimulus locations and motor responses are encoded in distinct brain regions, but that crosstalk with the hippocampus may be necessary to integrate new trialwise outcomes in both cognitive systems. SIGNIFICANCE STATEMENT The brain is able to infer the environments' statistical structure and responds strongly to expectancy violations. In the spatial attentional domain, it has been shown that parts of the attentional networks are sensitive to the predictability of stimuli. It remains unknown, however, whether these effects are ubiquitous or if they are specific for different cognitive systems. The present study compared the influence of model-derived cue predictability on brain activity in the spatial attentional and motor intentional system. We identified areas with distinct predictability-dependent activation for spatial attention and motor intention, but also common connectivity changes of these regions with the hippocampus. These findings provide novel insights into the generality and specificity of predictive processing signatures in the human brain. Copyright © 2017 the authors 0270-6474/17/375334-11$15.00/0.

The medial temporal lobe—conduit of parallel connectivity: a model for attention, memory, and perception

PubMed Central

Mozaffari, Brian

2014-01-01

Based on the notion that the brain is equipped with a hierarchical organization, which embodies environmental contingencies across many time scales, this paper suggests that the medial temporal lobe (MTL)—located deep in the hierarchy—serves as a bridge connecting supra- to infra—MTL levels. Bridging the upper and lower regions of the hierarchy provides a parallel architecture that optimizes information flow between upper and lower regions to aid attention, encoding, and processing of quick complex visual phenomenon. Bypassing intermediate hierarchy levels, information conveyed through the MTL “bridge” allows upper levels to make educated predictions about the prevailing context and accordingly select lower representations to increase the efficiency of predictive coding throughout the hierarchy. This selection or activation/deactivation is associated with endogenous attention. In the event that these “bridge” predictions are inaccurate, this architecture enables the rapid encoding of novel contingencies. A review of hierarchical models in relation to memory is provided along with a new theory, Medial-temporal-lobe Conduit for Parallel Connectivity (MCPC). In this scheme, consolidation is considered as a secondary process, occurring after a MTL-bridged connection, which eventually allows upper and lower levels to access each other directly. With repeated reactivations, as contingencies become consolidated, less MTL activity is predicted. Finally, MTL bridging may aid processing transient but structured perceptual events, by allowing communication between upper and lower levels without calling on intermediate levels of representation. PMID:25426036

Triangulation of the neurocomputational architecture underpinning reading aloud

PubMed Central

Hoffman, Paul; Lambon Ralph, Matthew A.; Woollams, Anna M.

2015-01-01

The goal of cognitive neuroscience is to integrate cognitive models with knowledge about underlying neural machinery. This significant challenge was explored in relation to word reading, where sophisticated computational-cognitive models exist but have made limited contact with neural data. Using distortion-corrected functional MRI and dynamic causal modeling, we investigated the interactions between brain regions dedicated to orthographic, semantic, and phonological processing while participants read words aloud. We found that the lateral anterior temporal lobe exhibited increased activation when participants read words with irregular spellings. This area is implicated in semantic processing but has not previously been considered part of the reading network. We also found meaningful individual differences in the activation of this region: Activity was predicted by an independent measure of the degree to which participants use semantic knowledge to read. These characteristics are predicted by the connectionist Triangle Model of reading and indicate a key role for semantic knowledge in reading aloud. Premotor regions associated with phonological processing displayed the reverse characteristics. Changes in the functional connectivity of the reading network during irregular word reading also were consistent with semantic recruitment. These data support the view that reading aloud is underpinned by the joint operation of two neural pathways. They reveal that (i) the ATL is an important element of the ventral semantic pathway and (ii) the division of labor between the two routes varies according to both the properties of the words being read and individual differences in the degree to which participants rely on each route. PMID:26124121

Evidence for holistic episodic recollection via hippocampal pattern completion.

PubMed

Horner, Aidan J; Bisby, James A; Bush, Daniel; Lin, Wen-Jing; Burgess, Neil

2015-07-02

Recollection is thought to be the hallmark of episodic memory. Here we provide evidence that the hippocampus binds together the diverse elements forming an event, allowing holistic recollection via pattern completion of all elements. Participants learn complex 'events' from multiple overlapping pairs of elements, and are tested on all pairwise associations. At encoding, element 'types' (locations, people and objects/animals) produce activation in distinct neocortical regions, while hippocampal activity predicts memory performance for all within-event pairs. When retrieving a pairwise association, neocortical activity corresponding to all event elements is reinstated, including those incidental to the task. Participant's degree of incidental reinstatement correlates with their hippocampal activity. Our results suggest that event elements, represented in distinct neocortical regions, are bound into coherent 'event engrams' in the hippocampus that enable episodic recollection--the re-experiencing or holistic retrieval of all aspects of an event--via a process of hippocampal pattern completion and neocortical reinstatement.

Spontaneous membrane formation and self-encapsulation of active rods in an inhomogeneous motility field

NASA Astrophysics Data System (ADS)

Grauer, Jens; Löwen, Hartmut; Janssen, Liesbeth M. C.

2018-02-01

We study the collective dynamics of self-propelled rods in an inhomogeneous motility field. At the interface between two regions of constant but different motility, a smectic rod layer is spontaneously created through aligning interactions between the active rods, reminiscent of an artificial, semipermeable membrane. This "active membrane" engulfes rods which are locally trapped in low-motility regions and thereby further enhances the trapping efficiency by self-organization, an effect which we call "self-encapsulation." Our results are gained by computer simulations of self-propelled rod models confined on a two-dimensional planar or spherical surface with a stepwise constant motility field, but the phenomenon should be observable in any geometry with sufficiently large spatial inhomogeneity. We also discuss possibilities to verify our predictions of active-membrane formation in experiments of self-propelled colloidal rods and vibrated granular matter.

ENSO controls interannual fire activity in southeast Australia

NASA Astrophysics Data System (ADS)

Mariani, M.; Fletcher, M.-S.; Holz, A.; Nyman, P.

2016-10-01

El Niño-Southern Oscillation (ENSO) is the main mode controlling the variability in the ocean-atmosphere system in the South Pacific. While the ENSO influence on rainfall regimes in the South Pacific is well documented, its role in driving spatiotemporal trends in fire activity in this region has not been rigorously investigated. This is particularly the case for the highly flammable and densely populated southeast Australian sector, where ENSO is a major control over climatic variability. Here we conduct the first region-wide analysis of how ENSO controls fire activity in southeast Australia. We identify a significant relationship between ENSO and both fire frequency and area burnt. Critically, wavelet analyses reveal that despite substantial temporal variability in the ENSO system, ENSO exerts a persistent and significant influence on southeast Australian fire activity. Our analysis has direct application for developing robust predictive capacity for the increasingly important efforts at fire management.

Hydroclimatological Controls of Endemic and Non-endemic Cholera of the 20th Century

NASA Astrophysics Data System (ADS)

Jutla, A. S.; Whitcombe, E.; Colwell, R.

2012-12-01

Cholera remains a major public health threat for the developing countries. Since the causative agent, Vibrio cholerae, is autochthonous to aquatic environment, it is not possible to eradicate the agent of the disease. Hydroclimatology based prediction and prevention strategies can be implemented in disease susceptible regions for reducing incidence rates. However, the precise role of hydrological and climatological processes, which will further aid in development of suitable prediction models, in creating spatial and temporal environmental conditions favorable for disease outbreak has not been adequately quantified. Here, we show distinction between seasonality and occurrence of cholera in epidemic and non-endemic regions. Using historical cholera mortality data, from the late 1800s for 27 locations in the Indian subcontinent, we show that non-endemic regions are generally located close to regional river systems but away from the coasts and are characterized by single sporadic outbreak in a given year. Increase in air temperature during the low river flow season increases evaporation, leading to an optimal salinity and pH required for bacterial growth. Thereafter, monsoonal rainfall, leads to interactions of contaminated river waters via human activity resulting in cholera epidemics. Endemic regions are located close to coasts where cholera outbreak occurs twice (spring and fall) in a year. Spring outbreak is generally associated with intrusion of bacterial seawater to inland whereas the fall peak is correlated with widespread flooding and cross-contamination of water resources via increased precipitation. This may be one of the first studies to hydroclimatologically quantitatively the seasonality of cholera in both endemic and non-endemic regions. Our results prompt the need of region and cause-specific prediction models for cholera, employing appropriate environmental determinants.

Relationships between structure, in vivo function and long-range axonal target of cortical pyramidal tract neurons.

PubMed

Rojas-Piloni, Gerardo; Guest, Jason M; Egger, Robert; Johnson, Andrew S; Sakmann, Bert; Oberlaender, Marcel

2017-10-11

Pyramidal tract neurons (PTs) represent the major output cell type of the neocortex. To investigate principles of how the results of cortical processing are broadcasted to different downstream targets thus requires experimental approaches, which provide access to the in vivo electrophysiology of PTs, whose subcortical target regions are identified. On the example of rat barrel cortex (vS1), we illustrate that retrograde tracer injections into multiple subcortical structures allow identifying the long-range axonal targets of individual in vivo recorded PTs. Here we report that soma depth and dendritic path lengths within each cortical layer of vS1, as well as spiking patterns during both periods of ongoing activity and during sensory stimulation, reflect the respective subcortical target regions of PTs. We show that these cellular properties result in a structure-function parameter space that allows predicting a PT's subcortical target region, without the need to inject multiple retrograde tracers.The major output cell type of the neocortex - pyramidal tract neurons (PTs) - send axonal projections to various subcortical areas. Here the authors combined in vivo recordings, retrograde tracings, and reconstructions of PTs in rat somatosensory cortex to show that PT structure and activity can predict specific subcortical targets.

Altered neural reward and loss processing and prediction error signalling in depression

PubMed Central

Ubl, Bettina; Kuehner, Christine; Kirsch, Peter; Ruttorf, Michaela

2015-01-01

Dysfunctional processing of reward and punishment may play an important role in depression. However, functional magnetic resonance imaging (fMRI) studies have shown heterogeneous results for reward processing in fronto-striatal regions. We examined neural responsivity associated with the processing of reward and loss during anticipation and receipt of incentives and related prediction error (PE) signalling in depressed individuals. Thirty medication-free depressed persons and 28 healthy controls performed an fMRI reward paradigm. Regions of interest analyses focused on neural responses during anticipation and receipt of gains and losses and related PE-signals. Additionally, we assessed the relationship between neural responsivity during gain/loss processing and hedonic capacity. When compared with healthy controls, depressed individuals showed reduced fronto-striatal activity during anticipation of gains and losses. The groups did not significantly differ in response to reward and loss outcomes. In depressed individuals, activity increases in the orbitofrontal cortex and nucleus accumbens during reward anticipation were associated with hedonic capacity. Depressed individuals showed an absence of reward-related PEs but encoded loss-related PEs in the ventral striatum. Depression seems to be linked to blunted responsivity in fronto-striatal regions associated with limited motivational responses for rewards and losses. Alterations in PE encoding might mirror blunted reward- and enhanced loss-related associative learning in depression. PMID:25567763

The language of future-thought: an fMRI study of embodiment and tense processing.

PubMed

Gilead, Michael; Liberman, Nira; Maril, Anat

2013-01-15

The ability to comprehend and represent the temporal properties of an occurrence is a crucial aspect of human language and cognition. Despite advances in neurolinguistic research into semantic processing, surprisingly little is known regarding the mechanisms which support the comprehension of temporal semantics. We used fMRI to investigate neural activity associated with processing of concrete and abstract sentences across the three temporal categories: past, present, and future. Theories of embodied cognition predict that concreteness-related activity would be evident in sensory and motor areas regardless of tense. Contrastingly, relying upon construal level theory we hypothesized that: (1) the neural markers associated with concrete language processing would appear for past and present tense sentences, but not for future sentences; (2) future tense sentences would activate intention-processing areas. Consistent with our first prediction, the results showed that activation in the parahippocampal gyrus differentiated between concrete and abstract sentences for past and present tense sentences, but not for future sentences. Not consistent with our second prediction, future tense sentences did not activate most of the regions that are implicated in the processing of intentions, but only activated the vmPFC. We discuss the implications of the current results to theories of embodied cognition and tense semantics. Copyright © 2012 Elsevier Inc. All rights reserved.

Seasonal prediction of extreme precipitation events and frequency of rainy days over Costa Rica, Central America, using Canonical Correlation Analysis

NASA Astrophysics Data System (ADS)

Maldonado, T.; Alfaro, E.; Fallas-López, B.; Alvarado, L.

2013-04-01

High mountains divide Costa Rica, Central America, into two main climate regions, the Pacific and Caribbean slopes, which are lee and windward, respectively, according to the North Atlantic trade winds - the dominant wind regime. The rain over the Pacific slope has a bimodal annual cycle, having two maxima, one in May-June and the other in August-September-October (ASO), separated by the mid-summer drought in July. A first maximum of deep convection activity, and hence a first maximum of precipitation, is reached when sea surface temperature (SST) exceeds 29 °C (around May). Then, the SST decreases to around 1 °C due to diminished downwelling solar radiation and stronger easterly winds (during July and August), resulting in a decrease in deep convection activity. Such a reduction in deep convection activity allows an increase in down welling solar radiation and a slight increase in SST (about 28.5 °C) by the end of August and early September, resulting once again in an enhanced deep convection activity, and, consequently, in a second maximum of precipitation. Most of the extreme events are found during ASO. Central American National Meteorological and Hydrological Services (NMHS) have periodic Regional Climate Outlook Fora (RCOF) to elaborate seasonal predictions. Recently, meetings after RCOF with different socioeconomic stakeholders took place to translate the probable climate impacts from predictions. From the feedback processes of these meetings has emerged that extreme event and rainy days seasonal predictions are necessary for different sectors. As is shown in this work, these predictions can be tailored using Canonical Correlation Analysis for rain during ASO, showing that extreme events and rainy days in Central America are influenced by interannual variability related to El Niño-Southern Oscillation and decadal variability associated mainly with Atlantic Multidecadal Oscillation. Analyzing the geographical distribution of the ASO-2010 disaster reports, we noticed that they did not necessarily agree with the geographical extreme precipitation event distribution, meaning that social variables, like population vulnerability, should be included in the extreme events impact analysis.

Residual Inhibition Functions Overlap Tinnitus Spectra and the Region of Auditory Threshold Shift

PubMed Central

Moffat, Graeme; Baumann, Michael; Ward, Lawrence M.

2008-01-01

Animals exposed to noise trauma show augmented synchronous neural activity in tonotopically reorganized primary auditory cortex consequent on hearing loss. Diminished intracortical inhibition in the reorganized region appears to enable synchronous network activity that develops when deafferented neurons begin to respond to input via their lateral connections. In humans with tinnitus accompanied by hearing loss, this process may generate a phantom sound that is perceived in accordance with the location of the affected neurons in the cortical place map. The neural synchrony hypothesis predicts that tinnitus spectra, and heretofore unmeasured “residual inhibition functions” that relate residual tinnitus suppression to the center frequency of masking sounds, should cover the region of hearing loss in the audiogram. We confirmed these predictions in two independent cohorts totaling 90 tinnitus subjects, using computer-based tools designed to assess the psychoacoustic properties of tinnitus. Tinnitus spectra and residual inhibition functions for depth and duration increased with the amount of threshold shift over the region of hearing impairment. Residual inhibition depth was shallower when the masking sounds that were used to induce residual inhibition showed decreased correspondence with the frequency spectrum and bandwidth of the tinnitus. These findings suggest that tinnitus and its suppression in residual inhibition depend on processes that span the region of hearing impairment and not on mechanisms that enhance cortical representations for sound frequencies at the audiometric edge. Hearing thresholds measured in age-matched control subjects without tinnitus implicated hearing loss as a factor in tinnitus, although elevated thresholds alone were not sufficient to cause tinnitus. PMID:18712566

Profiling of histone H3 lysine 9 trimethylation levels predicts transcription factor activity and survival in acute myeloid leukemia.

PubMed

Müller-Tidow, Carsten; Klein, Hans-Ulrich; Hascher, Antje; Isken, Fabienne; Tickenbrock, Lara; Thoennissen, Nils; Agrawal-Singh, Shuchi; Tschanter, Petra; Disselhoff, Christine; Wang, Yipeng; Becker, Anke; Thiede, Christian; Ehninger, Gerhard; zur Stadt, Udo; Koschmieder, Steffen; Seidl, Matthias; Müller, Frank U; Schmitz, Wilhelm; Schlenke, Peter; McClelland, Michael; Berdel, Wolfgang E; Dugas, Martin; Serve, Hubert

2010-11-04

Acute myeloid leukemia (AML) is commonly associated with alterations in transcription factors because of altered expression or gene mutations. These changes might induce leukemia-specific patterns of histone modifications. We used chromatin-immunoprecipitation on microarray to analyze histone 3 lysine 9 trimethylation (H3K9me3) patterns in primary AML (n = 108), acute lymphoid leukemia (n = 28), CD34(+) cells (n = 21) and white blood cells (n = 15) specimens. Hundreds of promoter regions in AML showed significant alterations in H3K9me3 levels. H3K9me3 deregulation in AML occurred preferentially as a decrease in H3K9me3 levels at core promoter regions. The altered genomic regions showed an overrepresentation of cis-binding sites for ETS and cyclic adenosine monophosphate response elements (CREs) for transcription factors of the CREB/CREM/ATF1 family. The decrease in H3K9me3 levels at CREs was associated with increased CRE-driven promoter activity in AML blasts in vivo. AML-specific H3K9me3 patterns were not associated with known cytogenetic abnormalities. But a signature derived from H3K9me3 patterns predicted event-free survival in AML patients. When the H3K9me3 signature was combined with established clinical prognostic markers, it outperformed prognosis prediction based on clinical parameters alone. These findings demonstrate widespread changes of H3K9me3 levels at gene promoters in AML. Signatures of histone modification patterns are associated with patient prognosis in AML.

GABAergic modulation of visual gamma and alpha oscillations and its consequences for working memory performance.

PubMed

Lozano-Soldevilla, Diego; ter Huurne, Niels; Cools, Roshan; Jensen, Ole

2014-12-15

Impressive in vitro research in rodents and computational modeling has uncovered the core mechanisms responsible for generating neuronal oscillations. In particular, GABAergic interneurons play a crucial role for synchronizing neural populations. Do these mechanistic principles apply to human oscillations associated with function? To address this, we recorded ongoing brain activity using magnetoencephalography (MEG) in healthy human subjects participating in a double-blind pharmacological study receiving placebo, 0.5 mg and 1.5 mg of lorazepam (LZP; a benzodiazepine upregulating GABAergic conductance). Participants performed a demanding visuospatial working memory (WM) task. We found that occipital gamma power associated with WM recognition increased with LZP dosage. Importantly, the frequency of the gamma activity decreased with dosage, as predicted by models derived from the rat hippocampus. A regionally specific gamma increase correlated with the drug-related performance decrease. Despite the system-wide pharmacological intervention, gamma power drug modulations were specific to visual cortex: sensorimotor gamma power and frequency during button presses remained unaffected. In contrast, occipital alpha power modulations during the delay interval decreased parametrically with drug dosage, predicting performance impairment. Consistent with alpha oscillations reflecting functional inhibition, LZP affected alpha power strongly in early visual regions not required for the task demonstrating a regional specific occipital impairment. GABAergic interneurons are strongly implicated in the generation of gamma and alpha oscillations in human occipital cortex where drug-induced power modulations predicted WM performance. Our findings bring us an important step closer to linking neuronal dynamics to behavior by embracing established animal models. Copyright © 2014 Elsevier Ltd. All rights reserved.

Structure Predictions of Two Bauhinia variegata Lectins Reveal Patterns of C-Terminal Properties in Single Chain Legume Lectins

PubMed Central

Moreira, Gustavo M. S. G.; Conceição, Fabricio R.; McBride, Alan J. A.; Pinto, Luciano da S.

2013-01-01

Bauhinia variegata lectins (BVL-I and BVL-II) are single chain lectins isolated from the plant Bauhinia variegata. Single chain lectins undergo post-translational processing on its N-terminal and C-terminal regions, which determines their physiological targeting, carbohydrate binding activity and pattern of quaternary association. These two lectins are isoforms, BVL-I being highly glycosylated, and thus far, it has not been possible to determine their structures. The present study used prediction and validation algorithms to elucidate the likely structures of BVL-I and -II. The program Bhageerath-H was chosen from among three different structure prediction programs due to its better overall reliability. In order to predict the C-terminal region cleavage sites, other lectins known to have this modification were analysed and three rules were created: (1) the first amino acid of the excised peptide is small or hydrophobic; (2) the cleavage occurs after an acid, polar, or hydrophobic residue, but not after a basic one; and (3) the cleavage spot is located 5-8 residues after a conserved Leu amino acid. These rules predicted that BVL-I and –II would have fifteen C-terminal residues cleaved, and this was confirmed experimentally by Edman degradation sequencing of BVL-I. Furthermore, the C-terminal analyses predicted that only BVL-II underwent α-helical folding in this region, similar to that seen in SBA and DBL. Conversely, BVL-I and -II contained four conserved regions of a GS-I association, providing evidence of a previously undescribed X4+unusual oligomerisation between the truncated BVL-I and the intact BVL-II. This is the first report on the structural analysis of lectins from Bauhinia spp. and therefore is important for the characterisation C-terminal cleavage and patterns of quaternary association of single chain lectins. PMID:24260572

Structure predictions of two Bauhinia variegata lectins reveal patterns of C-terminal properties in single chain legume lectins.

PubMed

Moreira, Gustavo M S G; Conceição, Fabricio R; McBride, Alan J A; Pinto, Luciano da S

2013-01-01

Bauhinia variegata lectins (BVL-I and BVL-II) are single chain lectins isolated from the plant Bauhinia variegata. Single chain lectins undergo post-translational processing on its N-terminal and C-terminal regions, which determines their physiological targeting, carbohydrate binding activity and pattern of quaternary association. These two lectins are isoforms, BVL-I being highly glycosylated, and thus far, it has not been possible to determine their structures. The present study used prediction and validation algorithms to elucidate the likely structures of BVL-I and -II. The program Bhageerath-H was chosen from among three different structure prediction programs due to its better overall reliability. In order to predict the C-terminal region cleavage sites, other lectins known to have this modification were analysed and three rules were created: (1) the first amino acid of the excised peptide is small or hydrophobic; (2) the cleavage occurs after an acid, polar, or hydrophobic residue, but not after a basic one; and (3) the cleavage spot is located 5-8 residues after a conserved Leu amino acid. These rules predicted that BVL-I and -II would have fifteen C-terminal residues cleaved, and this was confirmed experimentally by Edman degradation sequencing of BVL-I. Furthermore, the C-terminal analyses predicted that only BVL-II underwent α-helical folding in this region, similar to that seen in SBA and DBL. Conversely, BVL-I and -II contained four conserved regions of a GS-I association, providing evidence of a previously undescribed X4+unusual oligomerisation between the truncated BVL-I and the intact BVL-II. This is the first report on the structural analysis of lectins from Bauhinia spp. and therefore is important for the characterisation C-terminal cleavage and patterns of quaternary association of single chain lectins.

PREDICTION OF SOLAR FLARE SIZE AND TIME-TO-FLARE USING SUPPORT VECTOR MACHINE REGRESSION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boucheron, Laura E.; Al-Ghraibah, Amani; McAteer, R. T. James

We study the prediction of solar flare size and time-to-flare using 38 features describing magnetic complexity of the photospheric magnetic field. This work uses support vector regression to formulate a mapping from the 38-dimensional feature space to a continuous-valued label vector representing flare size or time-to-flare. When we consider flaring regions only, we find an average error in estimating flare size of approximately half a geostationary operational environmental satellite (GOES) class. When we additionally consider non-flaring regions, we find an increased average error of approximately three-fourths a GOES class. We also consider thresholding the regressed flare size for the experimentmore » containing both flaring and non-flaring regions and find a true positive rate of 0.69 and a true negative rate of 0.86 for flare prediction. The results for both of these size regression experiments are consistent across a wide range of predictive time windows, indicating that the magnetic complexity features may be persistent in appearance long before flare activity. This is supported by our larger error rates of some 40 hr in the time-to-flare regression problem. The 38 magnetic complexity features considered here appear to have discriminative potential for flare size, but their persistence in time makes them less discriminative for the time-to-flare problem.« less

Potential predictability of a Colombian river flow

NASA Astrophysics Data System (ADS)

Córdoba-Machado, Samir; Palomino-Lemus, Reiner; Quishpe-Vásquez, César; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

In this study the predictability of an important Colombian river (Cauca) has been analysed based on the use of climatic variables as potential predictors. Cauca River is considered one of the most important rivers of Colombia because its basin supports important productive activities related with the agriculture, such as the production of coffee or sugar. Potential relationships between the Cauca River seasonal streamflow anomalies and different climatic variables such as sea surface temperature (SST), precipitation (Pt), temperature over land (Tm) and soil water (Sw) have been analysed for the period 1949-2009. For this end, moving correlation analysis of 30 years have been carried out for lags from one to four seasons for the global SST, and from one to two seasons for South America Pt, Tm and Sw. Also, the stability of the significant correlations have been also studied, identifying the regions used as potential predictors of streamflow. Finally, in order to establish a prediction scheme based on the previous stable correlations, a Principal Component Analysis (PCA) applied on the potential predictor regions has been carried out in order to obtain a representative time series for each predictor field. Significant and stable correlations between the seasonal streamflow and the tropical Pacific SST (El Niño region) are found for lags from one to four (one-year) season. Additionally, some regions in the Indian and Atlantic Oceans also show significant and stable correlations at different lags, highlighting the importance that exerts the Atlantic SST on the hydrology of Colombia. Also significant and stable correlations are found with the Pt, Tm and Sw for some regions over South America, at lags of one and two seasons. The prediction of Cauca seasonal streamflow based on this scheme shows an acceptable skill and represents a relative improvement compared with the predictability obtained using the teleconnection indices associated with El Niño. Keywords: Streamflow, predictability, Cauca, Colombia. Acknowledgements: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía-Spain) and CGL2013-48539-R (MINECO-Spain, FEDER).

Genome-scale prediction of proteins with long intrinsically disordered regions.

PubMed

Peng, Zhenling; Mizianty, Marcin J; Kurgan, Lukasz

2014-01-01

Proteins with long disordered regions (LDRs), defined as having 30 or more consecutive disordered residues, are abundant in eukaryotes, and these regions are recognized as a distinct class of biologically functional domains. LDRs facilitate various cellular functions and are important for target selection in structural genomics. Motivated by the lack of methods that directly predict proteins with LDRs, we designed Super-fast predictor of proteins with Long Intrinsically DisordERed regions (SLIDER). SLIDER utilizes logistic regression that takes an empirically chosen set of numerical features, which consider selected physicochemical properties of amino acids, sequence complexity, and amino acid composition, as its inputs. Empirical tests show that SLIDER offers competitive predictive performance combined with low computational cost. It outperforms, by at least a modest margin, a comprehensive set of modern disorder predictors (that can indirectly predict LDRs) and is 16 times faster compared to the best currently available disorder predictor. Utilizing our time-efficient predictor, we characterized abundance and functional roles of proteins with LDRs over 110 eukaryotic proteomes. Similar to related studies, we found that eukaryotes have many (on average 30.3%) proteins with LDRs with majority of proteomes having between 25 and 40%, where higher abundance is characteristic to proteomes that have larger proteins. Our first-of-its-kind large-scale functional analysis shows that these proteins are enriched in a number of cellular functions and processes including certain binding events, regulation of catalytic activities, cellular component organization, biogenesis, biological regulation, and some metabolic and developmental processes. A webserver that implements SLIDER is available at http://biomine.ece.ualberta.ca/SLIDER/. Copyright © 2013 Wiley Periodicals, Inc.

Understanding the Effect of Land Cover Classification on Model Estimates of Regional Carbon Cycling in the Boreal Forest Biome

NASA Technical Reports Server (NTRS)

Kimball, John; Kang, Sinkyu

2003-01-01

The original objectives of this proposed 3-year project were to: 1) quantify the respective contributions of land cover and disturbance (i.e., wild fire) to uncertainty associated with regional carbon source/sink estimates produced by a variety of boreal ecosystem models; 2) identify the model processes responsible for differences in simulated carbon source/sink patterns for the boreal forest; 3) validate model outputs using tower and field- based estimates of NEP and NPP; and 4) recommend/prioritize improvements to boreal ecosystem carbon models, which will better constrain regional source/sink estimates for atmospheric C02. These original objectives were subsequently distilled to fit within the constraints of a 1 -year study. This revised study involved a regional model intercomparison over the BOREAS study region involving Biome-BGC, and TEM (A.D. McGuire, UAF) ecosystem models. The major focus of these revised activities involved quantifying the sensitivity of regional model predictions associated with land cover classification uncertainties. We also evaluated the individual and combined effects of historical fire activity, historical atmospheric CO2 concentrations, and climate change on carbon and water flux simulations within the BOREAS study region.

The sequential structure of brain activation predicts skill.

PubMed

Anderson, John R; Bothell, Daniel; Fincham, Jon M; Moon, Jungaa

2016-01-29

In an fMRI study, participants were trained to play a complex video game. They were scanned early and then again after substantial practice. While better players showed greater activation in one region (right dorsal striatum) their relative skill was better diagnosed by considering the sequential structure of whole brain activation. Using a cognitive model that played this game, we extracted a characterization of the mental states that are involved in playing a game and the statistical structure of the transitions among these states. There was a strong correspondence between this measure of sequential structure and the skill of different players. Using multi-voxel pattern analysis, it was possible to recognize, with relatively high accuracy, the cognitive states participants were in during particular scans. We used the sequential structure of these activation-recognized states to predict the skill of individual players. These findings indicate that important features about information-processing strategies can be identified from a model-based analysis of the sequential structure of brain activation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Hippocampal and posterior parietal contributions to developmental increases in visual short-term memory capacity.

PubMed

von Allmen, David Yoh; Wurmitzer, Karoline; Klaver, Peter

2014-10-01

Developmental increases in visual short-term memory (VSTM) capacity have been associated with changes in attention processing limitations and changes in neural activity within neural networks including the posterior parietal cortex (PPC). A growing body of evidence suggests that the hippocampus plays a role in VSTM, but it is unknown whether the hippocampus contributes to the capacity increase across development. We investigated the functional development of the hippocampus and PPC in 57 children, adolescents and adults (age 8-27 years) who performed a visuo-spatial change detection task. A negative relationship between age and VSTM related activity was found in the right posterior hippocampus that was paralleled by a positive age-activity relationship in the right PPC. In the posterior hippocampus, VSTM related activity predicted individual capacity in children, whereas neural activity in the right anterior hippocampus predicted individual capacity in adults. The findings provide first evidence that VSTM development is supported by an integrated neural network that involves hippocampal and posterior parietal regions.

Identifying open magnetic field regions of the Sun and their heliospheric counterparts

NASA Astrophysics Data System (ADS)

Krista, L. D.; Reinard, A.

2017-12-01

Open magnetic regions on the Sun are either long-lived (coronal holes) or transient (dimmings) in nature. Both phenomena are fundamental to our understanding of the solar behavior as a whole. Coronal holes are the sources of high-speed solar wind streams that cause recurrent geomagnetic storms. Furthermore, the variation of coronal hole properties (area, location, magnetic field strength) over the solar activity cycle is an important marker of the global evolution of the solar magnetic field. Dimming regions, on the other hand, are short-lived coronal holes that often emerge in the wake of solar eruptions. By analyzing their physical properties and their temporal evolution, we aim to understand their connection with their eruptive counterparts (flares and coronal mass ejections) and predict the possibility of a geomagnetic storm. The author developed the Coronal Hole Automated Recognition and Monitoring (CHARM) and the Coronal Dimming Tracker (CoDiT) algorithms. These tools not only identify but track the evolution of open magnetic field regions. CHARM also provides daily coronal hole maps, that are used for forecasts at the NOAA Space Weather Prediction Center. Our goal is to better understand the processes that give rise to eruptive and non-eruptive open field regions and investigate how these regions evolve over time and influence space weather.

Sticking with the nice guy: trait warmth information impairs learning and modulates person perception brain network activity.

PubMed

Lee, Victoria K; Harris, Lasana T

2014-12-01

Social learning requires inferring social information about another person, as well as evaluating outcomes. Previous research shows that prior social information biases decision making and reduces reliance on striatal activity during learning (Delgado, Frank, & Phelps, Nature Neuroscience 8 (11): 1611-1618, 2005). A rich literature in social psychology on person perception demonstrates that people spontaneously infer social information when viewing another person (Fiske & Taylor, 2013) and engage a network of brain regions, including the medial prefrontal cortex, temporal parietal junction, superior temporal sulcus, and precuneus (Amodio & Frith, Nature Reviews Neuroscience, 7(4), 268-277, 2006; Haxby, Gobbini, & Montgomery, 2004; van Overwalle Human Brain Mapping, 30, 829-858, 2009). We investigate the role of these brain regions during social learning about well-established dimensions of person perception-trait warmth and trait competence. We test the hypothesis that activity in person perception brain regions interacts with learning structures during social learning. Participants play an investment game where they must choose an agent to invest on their behalf. This choice is guided by cues signaling trait warmth or trait competence based on framing of monetary returns. Trait warmth information impairs learning about human but not computer agents, while trait competence information produces similar learning rates for human and computer agents. We see increased activation to warmth information about human agents in person perception brain regions. Interestingly, activity in person perception brain regions during the decision phase negatively predicts activity in the striatum during feedback for trait competence inferences about humans. These results suggest that social learning may engage additional processing within person perception brain regions that hampers learning in economic contexts.

Solar-Terrestrial Predictions

NASA Astrophysics Data System (ADS)

Thompson, R. J.; Cole, D. G.; Wilkinson, P. J.; Shea, M. A.; Smart, D.

1990-11-01

Volume 1: The following subject areas are covered: the magnetosphere environment; forecasting magnetically quiet periods; radiation hazards to human in deep space (a summary with special reference to large solar particle events); solar proton events (review and status); problems of the physics of solar-terrestrial interactions; prediction of solar proton fluxes from x-ray signatures; rhythms in solar activity and the prediction of episodes of large flares; the role of persistence in the 24-hour flare forecast; on the relationship between the observed sunspot number and the number of solar flares; the latitudinal distribution of coronal holes and geomagnetic storms due to coronal holes; and the signatures of flares in the interplanetary medium at 1 AU. Volume 2: The following subject areas were covered: a probability forecast for geomagnetic activity; cost recovery in solar-terrestrial predictions; magnetospheric specification and forecasting models; a geomagnetic forecast and monitoring system for power system operation; some aspects of predicting magnetospheric storms; some similarities in ionospheric disturbance characteristics in equatorial, mid-latitude, and sub-auroral regions; ionospheric support for low-VHF radio transmission; a new approach to prediction of ionospheric storms; a comparison of the total electron content of the ionosphere around L=4 at low sunspot numbers with the IRI model; the French ionospheric radio propagation predictions; behavior of the F2 layer at mid-latitudes; and the design of modern ionosondes.

The self and its resting state in consciousness: an investigation of the vegetative state.

PubMed

Huang, Zirui; Dai, Rui; Wu, Xuehai; Yang, Zhi; Liu, Dongqiang; Hu, Jin; Gao, Liang; Tang, Weijun; Mao, Ying; Jin, Yi; Wu, Xing; Liu, Bin; Zhang, Yao; Lu, Lu; Laureys, Steven; Weng, Xuchu; Northoff, Georg

2014-05-01

Recent studies have demonstrated resting-state abnormalities in midline regions in vegetative state/unresponsive wakefulness syndrome and minimally conscious state patients. However, the functional implications of these resting-state abnormalities remain unclear. Recent findings in healthy subjects have revealed a close overlap between the neural substrate of self-referential processing and the resting-state activity in cortical midline regions. As such, we investigated task-related neural activity during active self-referential processing and various measures of resting-state activity in 11 patients with disorders of consciousness (DOC) and 12 healthy control subjects. Overall, the results revealed that DOC patients exhibited task-specific signal changes in anterior and posterior midline regions, including the perigenual anterior cingulate cortex (PACC) and posterior cingulate cortex (PCC). However, the degree of signal change was significantly lower in DOC patients compared with that in healthy subjects. Moreover, reduced signal differentiation in the PACC predicted the degree of consciousness in DOC patients. Importantly, the same midline regions (PACC and PCC) in DOC patients also exhibited severe abnormalities in the measures of resting-state activity, that is functional connectivity and the amplitude of low-frequency fluctuations. Taken together, our results provide the first evidence of neural abnormalities in both the self-referential processing and the resting state in midline regions in DOC patients. This novel finding has important implications for clinical utility and general understanding of the relationship between the self, the resting state, and consciousness. Copyright © 2013 Wiley Periodicals, Inc.

Non-neutralized Electric Currents in Solar Active Regions and Flare Productivity

NASA Astrophysics Data System (ADS)

Kontogiannis, Ioannis; Georgoulis, Manolis K.; Park, Sung-Hong; Guerra, Jordan A.

2017-11-01

We explore the association of non-neutralized currents with solar flare occurrence in a sizable sample of observations, aiming to show the potential of such currents in solar flare prediction. We used the high-quality vector magnetograms that are regularly produced by the Helioseismic Magnetic Imager, and more specifically, the Space weather HMI Active Region Patches (SHARP). Through a newly established method that incorporates detailed error analysis, we calculated the non-neutralized currents contained in active regions (AR). Two predictors were produced, namely the total and the maximum unsigned non-neutralized current. Both were tested in AR time-series and a representative sample of point-in-time observations during the interval 2012 - 2016. The average values of non-neutralized currents in flaring active regions are higher by more than an order of magnitude than in non-flaring regions and correlate very well with the corresponding flare index. The temporal evolution of these parameters appears to be connected to physical processes, such as flux emergence and/or magnetic polarity inversion line formation, that are associated with increased solar flare activity. Using Bayesian inference of flaring probabilities, we show that the total unsigned non-neutralized current significantly outperforms the total unsigned magnetic flux and other well-established current-related predictors. It therefore shows good prospects for inclusion in an operational flare-forecasting service. We plan to use the new predictor in the framework of the FLARECAST project along with other highly performing predictors.

Mathematics anxiety: separating the math from the anxiety.

PubMed

Lyons, Ian M; Beilock, Sian L

2012-09-01

Anxiety about math is tied to low math grades and standardized test scores, yet not all math-anxious individuals perform equally poorly in math. We used functional magnetic resonance imaging to separate neural activity during the anticipation of doing math from activity during math performance itself. For higher (but not lower) math-anxious individuals, increased activity in frontoparietal regions when simply anticipating doing math mitigated math-specific performance deficits. This network included bilateral inferior frontal junction, a region involved in cognitive control and reappraisal of negative emotional responses. Furthermore, the relation between frontoparietal anticipatory activity and highly math-anxious individuals' math deficits was fully mediated (or accounted for) by activity in caudate, nucleus accumbens, and hippocampus during math performance. These subcortical regions are important for coordinating task demands and motivational factors during skill execution. Individual differences in how math-anxious individuals recruit cognitive control resources prior to doing math and motivational resources during math performance predict the extent of their math deficits. This work suggests that educational interventions emphasizing control of negative emotional responses to math stimuli (rather than merely additional math training) will be most effective in revealing a population of mathematically competent individuals, who might otherwise go undiscovered.

Skillful regional prediction of Arctic sea ice on seasonal timescales

NASA Astrophysics Data System (ADS)

Bushuk, Mitchell; Msadek, Rym; Winton, Michael; Vecchi, Gabriel A.; Gudgel, Rich; Rosati, Anthony; Yang, Xiaosong

2017-05-01

Recent Arctic sea ice seasonal prediction efforts and forecast skill assessments have primarily focused on pan-Arctic sea ice extent (SIE). In this work, we move toward stakeholder-relevant spatial scales, investigating the regional forecast skill of Arctic sea ice in a Geophysical Fluid Dynamics Laboratory (GFDL) seasonal prediction system. Using a suite of retrospective initialized forecasts spanning 1981-2015 made with a coupled atmosphere-ocean-sea ice-land model, we show that predictions of detrended regional SIE are skillful at lead times up to 11 months. Regional prediction skill is highly region and target month dependent and generically exceeds the skill of an anomaly persistence forecast. We show for the first time that initializing the ocean subsurface in a seasonal prediction system can yield significant regional skill for winter SIE. Similarly, as suggested by previous work, we find that sea ice thickness initial conditions provide a crucial source of skill for regional summer SIE.

Predicting Motivation: Computational Models of PFC Can Explain Neural Coding of Motivation and Effort-based Decision-making in Health and Disease.

PubMed

Vassena, Eliana; Deraeve, James; Alexander, William H

2017-10-01

Human behavior is strongly driven by the pursuit of rewards. In daily life, however, benefits mostly come at a cost, often requiring that effort be exerted to obtain potential benefits. Medial PFC (MPFC) and dorsolateral PFC (DLPFC) are frequently implicated in the expectation of effortful control, showing increased activity as a function of predicted task difficulty. Such activity partially overlaps with expectation of reward and has been observed both during decision-making and during task preparation. Recently, novel computational frameworks have been developed to explain activity in these regions during cognitive control, based on the principle of prediction and prediction error (predicted response-outcome [PRO] model [Alexander, W. H., & Brown, J. W. Medial prefrontal cortex as an action-outcome predictor. Nature Neuroscience, 14, 1338-1344, 2011], hierarchical error representation [HER] model [Alexander, W. H., & Brown, J. W. Hierarchical error representation: A computational model of anterior cingulate and dorsolateral prefrontal cortex. Neural Computation, 27, 2354-2410, 2015]). Despite the broad explanatory power of these models, it is not clear whether they can also accommodate effects related to the expectation of effort observed in MPFC and DLPFC. Here, we propose a translation of these computational frameworks to the domain of effort-based behavior. First, we discuss how the PRO model, based on prediction error, can explain effort-related activity in MPFC, by reframing effort-based behavior in a predictive context. We propose that MPFC activity reflects monitoring of motivationally relevant variables (such as effort and reward), by coding expectations and discrepancies from such expectations. Moreover, we derive behavioral and neural model-based predictions for healthy controls and clinical populations with impairments of motivation. Second, we illustrate the possible translation to effort-based behavior of the HER model, an extended version of PRO model based on hierarchical error prediction, developed to explain MPFC-DLPFC interactions. We derive behavioral predictions that describe how effort and reward information is coded in PFC and how changing the configuration of such environmental information might affect decision-making and task performance involving motivation.

Trial-to-trial Adaptation: Parsing out the Roles of Cerebellum and BG in Predictive Motor Timing.

PubMed

Lungu, Ovidiu V; Bares, Martin; Liu, Tao; Gomez, Christopher M; Cechova, Ivica; Ashe, James

2016-07-01

We previously demonstrated that predictive motor timing (i.e., timing requiring visuomotor coordination in anticipation of a future event, such as catching or batting a ball) is impaired in patients with spinocerebellar ataxia (SCA) types 6 and 8 relative to healthy controls. Specifically, SCA patients had difficulties postponing their motor response while estimating the target kinematics. This behavioral difference relied on the activation of both cerebellum and striatum in healthy controls, but not in cerebellar patients, despite both groups activating certain parts of cerebellum during the task. However, the role of these two key structures in the dynamic adaptation of the motor timing to target kinematic properties remained unexplored. In the current paper, we analyzed these data with the aim of characterizing the trial-by-trial changes in brain activation. We found that in healthy controls alone, and in comparison with SCA patients, the activation in bilateral striatum was exclusively associated with past successes and that in the left putamen, with maintaining a successful performance across successive trials. In healthy controls, relative to SCA patients, a larger network was involved in maintaining a successful trial-by-trial strategy; this included cerebellum and fronto-parieto-temporo-occipital regions that are typically part of attentional network and action monitoring. Cerebellum was also part of a network of regions activated when healthy participants postponed their motor response from one trial to the next; SCA patients showed reduced activation relative to healthy controls in both cerebellum and striatum in the same contrast. These findings support the idea that cerebellum and striatum play complementary roles in the trial-by-trial adaptation in predictive motor timing. In addition to expanding our knowledge of brain structures involved in time processing, our results have implications for the understanding of BG disorders, such as Parkinson disease where feedback processing or reward learning is affected.

Improving Accuracy in Arrhenius Models of Cell Death: Adding a Temperature-Dependent Time Delay.

PubMed

Pearce, John A

2015-12-01

The Arrhenius formulation for single-step irreversible unimolecular reactions has been used for many decades to describe the thermal damage and cell death processes. Arrhenius predictions are acceptably accurate for structural proteins, for some cell death assays, and for cell death at higher temperatures in most cell lines, above about 55 °C. However, in many cases--and particularly at hyperthermic temperatures, between about 43 and 55 °C--the particular intrinsic cell death or damage process under study exhibits a significant "shoulder" region that constant-rate Arrhenius models are unable to represent with acceptable accuracy. The primary limitation is that Arrhenius calculations always overestimate the cell death fraction, which leads to severely overoptimistic predictions of heating effectiveness in tumor treatment. Several more sophisticated mathematical model approaches have been suggested and show much-improved performance. But simpler models that have adequate accuracy would provide useful and practical alternatives to intricate biochemical analyses. Typical transient intrinsic cell death processes at hyperthermic temperatures consist of a slowly developing shoulder region followed by an essentially constant-rate region. The shoulder regions have been demonstrated to arise chiefly from complex functional protein signaling cascades that generate delays in the onset of the constant-rate region, but may involve heat shock protein activity as well. This paper shows that acceptably accurate and much-improved predictions in the simpler Arrhenius models can be obtained by adding a temperature-dependent time delay. Kinetic coefficients and the appropriate time delay are obtained from the constant-rate regions of the measured survival curves. The resulting predictions are seen to provide acceptably accurate results while not overestimating cell death. The method can be relatively easily incorporated into numerical models. Additionally, evidence is presented to support the application of compensation law behavior to the cell death processes--that is, the strong correlation between the kinetic coefficients, ln{A} and E(a), is confirmed.

Neural predictors of purchases

PubMed Central

Knutson, Brian; Rick, Scott; Wimmer, G. Elliott; Prelec, Drazen; Loewenstein, George

2007-01-01

Microeconomic theory maintains that purchases are driven by a combination of consumer preference and price. Using event-related FMRI, we investigated how people weigh these factors to make purchasing decisions. Consistent with neuroimaging evidence suggesting that distinct circuits anticipate gain and loss, product preference activated the nucleus accumbens (NAcc), while excessive prices activated the insula and deactivated the mesial prefrontal cortex (MPFC) prior to the purchase decision. Activity from each of these regions independently predicted immediately subsequent purchases above and beyond self-report variables. These findings suggest that activation of distinct neural circuits related to anticipatory affect precedes and supports consumers’ purchasing decisions. PMID:17196537

Determination of GMPE functional form for an active region with limited strong motion data: application to the Himalayan region

NASA Astrophysics Data System (ADS)

Bajaj, Ketan; Anbazhagan, P.

2018-01-01

Advancement in the seismic networks results in formulation of different functional forms for developing any new ground motion prediction equation (GMPE) for a region. Till date, various guidelines and tools are available for selecting a suitable GMPE for any seismic study area. However, these methods are efficient in quantifying the GMPE but not for determining a proper functional form and capturing the epistemic uncertainty associated with selection of GMPE. In this study, the compatibility of the recent available functional forms for the active region is tested for distance and magnitude scaling. Analysis is carried out by determining the residuals using the recorded and the predicted spectral acceleration values at different periods. Mixed effect regressions are performed on the calculated residuals for determining the intra- and interevent residuals. Additionally, spatial correlation is used in mixed effect regression by changing its likelihood function. Distance scaling and magnitude scaling are respectively examined by studying the trends of intraevent residuals with distance and the trend of the event term with magnitude. Further, these trends are statistically studied for a respective functional form of a ground motion. Additionally, genetic algorithm and Monte Carlo method are used respectively for calculating the hinge point and standard error for magnitude and distance scaling for a newly determined functional form. The whole procedure is applied and tested for the available strong motion data for the Himalayan region. The functional form used for testing are five Himalayan GMPEs, five GMPEs developed under NGA-West 2 project, two from Pan-European, and one from Japan region. It is observed that bilinear functional form with magnitude and distance hinged at 6.5 M w and 300 km respectively is suitable for the Himalayan region. Finally, a new regression coefficient for peak ground acceleration for a suitable functional form that governs the attenuation characteristic of the Himalayan region is derived.

Relationship between BOLD amplitude and pattern classification of orientation-selective activity in the human visual cortex.

PubMed

Tong, Frank; Harrison, Stephenie A; Dewey, John A; Kamitani, Yukiyasu

2012-11-15

Orientation-selective responses can be decoded from fMRI activity patterns in the human visual cortex, using multivariate pattern analysis (MVPA). To what extent do these feature-selective activity patterns depend on the strength and quality of the sensory input, and might the reliability of these activity patterns be predicted by the gross amplitude of the stimulus-driven BOLD response? Observers viewed oriented gratings that varied in luminance contrast (4, 20 or 100%) or spatial frequency (0.25, 1.0 or 4.0 cpd). As predicted, activity patterns in early visual areas led to better discrimination of orientations presented at high than low contrast, with greater effects of contrast found in area V1 than in V3. A second experiment revealed generally better decoding of orientations at low or moderate as compared to high spatial frequencies. Interestingly however, V1 exhibited a relative advantage at discriminating high spatial frequency orientations, consistent with the finer scale of representation in the primary visual cortex. In both experiments, the reliability of these orientation-selective activity patterns was well predicted by the average BOLD amplitude in each region of interest, as indicated by correlation analyses, as well as decoding applied to a simple model of voxel responses to simulated orientation columns. Moreover, individual differences in decoding accuracy could be predicted by the signal-to-noise ratio of an individual's BOLD response. Our results indicate that decoding accuracy can be well predicted by incorporating the amplitude of the BOLD response into simple simulation models of cortical selectivity; such models could prove useful in future applications of fMRI pattern classification. Copyright © 2012 Elsevier Inc. All rights reserved.

Relationship between BOLD amplitude and pattern classification of orientation-selective activity in the human visual cortex

PubMed Central

Tong, Frank; Harrison, Stephenie A.; Dewey, John A.; Kamitani, Yukiyasu

2012-01-01

Orientation-selective responses can be decoded from fMRI activity patterns in the human visual cortex, using multivariate pattern analysis (MVPA). To what extent do these feature-selective activity patterns depend on the strength and quality of the sensory input, and might the reliability of these activity patterns be predicted by the gross amplitude of the stimulus-driven BOLD response? Observers viewed oriented gratings that varied in luminance contrast (4, 20 or 100%) or spatial frequency (0.25, 1.0 or 4.0 cpd). As predicted, activity patterns in early visual areas led to better discrimination of orientations presented at high than low contrast, with greater effects of contrast found in area V1 than in V3. A second experiment revealed generally better decoding of orientations at low or moderate as compared to high spatial frequencies. Interestingly however, V1 exhibited a relative advantage at discriminating high spatial frequency orientations, consistent with the finer scale of representation in the primary visual cortex. In both experiments, the reliability of these orientation-selective activity patterns was well predicted by the average BOLD amplitude in each region of interest, as indicated by correlation analyses, as well as decoding applied to a simple model of voxel responses to simulated orientation columns. Moreover, individual differences in decoding accuracy could be predicted by the signal-to-noise ratio of an individual's BOLD response. Our results indicate that decoding accuracy can be well predicted by incorporating the amplitude of the BOLD response into simple simulation models of cortical selectivity; such models could prove useful in future applications of fMRI pattern classification. PMID:22917989

Accuracy of increased thyroid activity during pertechnetate scintigraphy by subcutaneous injection for diagnosing hyperthyroidism in cats.

PubMed

Page, Richard B; Scrivani, Peter V; Dykes, Nathan L; Erb, Hollis N; Hobbs, Jeff M

2006-01-01

Our purpose was to determine the accuracy of increased thyroid activity for diagnosing hyperthyroidism in cats suspected of having that disease during pertechnetate scintigraphy using subcutaneous rather than intravenous radioisotope administration. Increased thyroid activity was determined by two methods: the thyroid:salivary ratio (T:S) and visual inspection. These assessments were made on the ventral scintigram of the head and neck. Scintigraphy was performed by injecting sodium pertechnetate (111 MBq, SQ) in the right-dorsal-lumbar region; static-acquisition images were obtained 20 min after injection. We used 49 cats; 34 (69%) had hyperthyroidism based on serum-chemistry analysis. Using a Wilcoxon's rank-sum test, a significant difference (P < 0.0001) was detected in the T:S between cats with and without hyperthyroidism. Using a decision criterion of 2.0 for the T:S, the test accurately predicted hyperthyroidism in 32/34 cats (sensitivity, 94%; 95% confidence interval (CI), 85-100%) and correctly predicted that hyperthyroidism was absent in 15/15 cats (specificity, 100%; CI, 97-100%). Using visual inspection, the test accurately predicted hyperthyroidism in 34/34 cats (sensitivity, 100%; CI, 99-100%) and correctly predicted that hyperthyroidism was absent in 12/15 cats (specificity, 80%; CI, 56-100%). The positive and negative predictive values were high for a wide range of prevalence of hyperthyroidism. And, the test had excellent agreement within and between examiners. Therefore, detecting increased thyroid activity during pertechnetate scintigraphy by subcutaneous injection is an accurate and reproducible test for feline hyperthyroidism.

Development of Lightning Observation Network in the Western Pacific Region for the Intensity Prediction of Severe Weather

NASA Astrophysics Data System (ADS)

Sato, M.; Takahashi, Y.; Yamashita, K.; Kubota, H.; Hamada, J. I.; Momota, E.; Marciano, J. J.

2017-12-01

Lightning activity represents the thunderstorm activity, that is, the precipitation and/or updraft intensity and area. Thunderstorm activity is also an important parameter in terms of the energy inputs from the ocean to the atmosphere inside tropical cyclone, which is one of severe weather events. Recent studies suggest that it is possible to predict the maximum wind velocity and minimum pressure near the center of the tropical cyclone by one or two days before if we monitor the lightning activities in the tropical cyclone. Many countries in the western Pacific region suffer from the attack of tropical cyclone (typhoon) and have a strong demand to predict the intensity development of typhoons. Thus, we started developing a new lightning observation system and installing the observation system at Guam, Palau, and Manila in the Philippines from this summer. The lightning observation system consists of a VLF sensor detecting lightning-excited electromagnetic waves in the frequency range of 1-5 kHz, an automatic data-processing unit, solar panels, and batteries. Lightning-excited pulse signals detected by the VLF sensor are automatically analyzed by the data-processing unit, and only the extracted information of the trigger time and pulse amplitude is transmitted to a data server via the 3G data communications. In addition, we are now developing an upgraded lightning and weather observation system, which will be installed at 50 automated weather stations in Metro Manila and 10 radar sites in the Philippines under the 5-year project (SATREPS) scheme. At the presentation, we will show the initial results derived from the lightning observation system in detail and will show the detailed future plan of the SATREPS project.

A cyber-event correlation framework and metrics

NASA Astrophysics Data System (ADS)

Kang, Myong H.; Mayfield, Terry

2003-08-01

In this paper, we propose a cyber-event fusion, correlation, and situation assessment framework that, when instantiated, will allow cyber defenders to better understand the local, regional, and global cyber-situation. This framework, with associated metrics, can be used to guide assessment of our existing cyber-defense capabilities, and to help evaluate the state of cyber-event correlation research and where we must focus our future cyber-event correlation research. The framework, based on the cyber-event gathering activities and analysis functions, consists of five operational steps, each of which provides a richer set of contextual information to support greater situational understanding. The first three steps are categorically depicted as increasingly richer and broader-scoped contexts achieved through correlation activity, while in the final two steps, these richer contexts are achieved through analytical activities (situation assessment, and threat analysis & prediction). Category 1 Correlation focuses on the detection of suspicious activities and the correlation of events from a single cyber-event source. Category 2 Correlation clusters the same or similar events from multiple detectors that are located at close proximity and prioritizes them. Finally, the events from different time periods and event sources at different location/regions are correlated at Category 3 to recognize the relationship among different events. This is the category that focuses on the detection of large-scale and coordinated attacks. The situation assessment step (Category 4) focuses on the assessment of cyber asset damage and the analysis of the impact on missions. The threat analysis and prediction step (Category 5) analyzes attacks based on attack traces and predicts the next steps. Metrics that can distinguish correlation and cyber-situation assessment tools for each category are also proposed.

The relations between sleep, time of physical activity, and time outdoors among adult women

PubMed Central

Godbole, Suneeta; Natarajan, Loki; Full, Kelsie; Hipp, J. Aaron; Glanz, Karen; Mitchell, Jonathan; Laden, Francine; James, Peter; Quante, Mirja; Kerr, Jacqueline

2017-01-01

Physical activity and time spent outdoors may be important non-pharmacological approaches to improve sleep quality and duration (or sleep patterns) but there is little empirical research evaluating the two simultaneously. The current study assesses the role of physical activity and time outdoors in predicting sleep health by using objective measurement of the three variables. A convenience sample of 360 adult women (mean age = 55.38 ±9.89 years; mean body mass index = 27.74 ±6.12) was recruited from different regions of the U.S. Participants wore a Global Positioning System device and ActiGraph GT3X+ accelerometers on the hip for 7 days and on the wrist for 7 days and 7 nights to assess total time and time of day spent outdoors, total minutes in moderate-to-vigorous physical activity per day, and 4 measures of sleep health, respectively. A generalized mixed-effects model was used to assess temporal associations between moderate-to-vigorous physical activity, outdoor time, and sleep at the daily level (days = 1931) within individuals. There was a significant interaction (p = 0.04) between moderate-to-vigorous physical activity and time spent outdoors in predicting total sleep time but not for predicting sleep efficiency. Increasing time outdoors in the afternoon (versus morning) predicted lower sleep efficiency, but had no effect on total sleep time. Time spent outdoors and the time of day spent outdoors may be important moderators in assessing the relation between physical activity and sleep. More research is needed in larger populations using experimental designs. PMID:28877192

Electroencephalographic identifiers of motor adaptation learning

NASA Astrophysics Data System (ADS)

Özdenizci, Ozan; Yalçın, Mustafa; Erdoğan, Ahmetcan; Patoğlu, Volkan; Grosse-Wentrup, Moritz; Çetin, Müjdat

2017-08-01

Objective. Recent brain-computer interface (BCI) assisted stroke rehabilitation protocols tend to focus on sensorimotor activity of the brain. Relying on evidence claiming that a variety of brain rhythms beyond sensorimotor areas are related to the extent of motor deficits, we propose to identify neural correlates of motor learning beyond sensorimotor areas spatially and spectrally for further use in novel BCI-assisted neurorehabilitation settings. Approach. Electroencephalographic (EEG) data were recorded from healthy subjects participating in a physical force-field adaptation task involving reaching movements through a robotic handle. EEG activity recorded during rest prior to the experiment and during pre-trial movement preparation was used as features to predict motor adaptation learning performance across subjects. Main results. Subjects learned to perform straight movements under the force-field at different adaptation rates. Both resting-state and pre-trial EEG features were predictive of individual adaptation rates with relevance of a broad network of beta activity. Beyond sensorimotor regions, a parieto-occipital cortical component observed across subjects was involved strongly in predictions and a fronto-parietal cortical component showed significant decrease in pre-trial beta-powers for users with higher adaptation rates and increase in pre-trial beta-powers for users with lower adaptation rates. Significance. Including sensorimotor areas, a large-scale network of beta activity is presented as predictive of motor learning. Strength of resting-state parieto-occipital beta activity or pre-trial fronto-parietal beta activity can be considered in BCI-assisted stroke rehabilitation protocols with neurofeedback training or volitional control of neural activity for brain-robot interfaces to induce plasticity.

The relations between sleep, time of physical activity, and time outdoors among adult women.

PubMed

Murray, Kate; Godbole, Suneeta; Natarajan, Loki; Full, Kelsie; Hipp, J Aaron; Glanz, Karen; Mitchell, Jonathan; Laden, Francine; James, Peter; Quante, Mirja; Kerr, Jacqueline

2017-01-01

Physical activity and time spent outdoors may be important non-pharmacological approaches to improve sleep quality and duration (or sleep patterns) but there is little empirical research evaluating the two simultaneously. The current study assesses the role of physical activity and time outdoors in predicting sleep health by using objective measurement of the three variables. A convenience sample of 360 adult women (mean age = 55.38 ±9.89 years; mean body mass index = 27.74 ±6.12) was recruited from different regions of the U.S. Participants wore a Global Positioning System device and ActiGraph GT3X+ accelerometers on the hip for 7 days and on the wrist for 7 days and 7 nights to assess total time and time of day spent outdoors, total minutes in moderate-to-vigorous physical activity per day, and 4 measures of sleep health, respectively. A generalized mixed-effects model was used to assess temporal associations between moderate-to-vigorous physical activity, outdoor time, and sleep at the daily level (days = 1931) within individuals. There was a significant interaction (p = 0.04) between moderate-to-vigorous physical activity and time spent outdoors in predicting total sleep time but not for predicting sleep efficiency. Increasing time outdoors in the afternoon (versus morning) predicted lower sleep efficiency, but had no effect on total sleep time. Time spent outdoors and the time of day spent outdoors may be important moderators in assessing the relation between physical activity and sleep. More research is needed in larger populations using experimental designs.

A Neuroimaging Study of Premotor Lateralization and Cerebellar Involvement in the Production of Phonemes and Syllables

ERIC Educational Resources Information Center

Ghosh, Satrajit S.; Tourville, Jason A.; Guenther, Frank H.

2008-01-01

Purpose: This study investigated the network of brain regions involved in overt production of vowels, monosyllables, and bisyllables to test hypotheses derived from the Directions Into Velocities of Articulators (DIVA) model of speech production (Guenther, Ghosh, & Tourville, 2006). The DIVA model predicts left lateralized activity in inferior…

Biodiversity and productivity

Treesearch

M.R. Willig

2011-01-01

Researchers predict that human activities especially landscape modification and climate change will have a considerable impact on the distribution and abundance of species at local, regional, and global scales in the 21st century ( 1, 2). This is a concern for a number of reasons, including the potential loss of goods and services that biodiversity provides to people...

Anxiety type modulates immediate versus delayed engagement of attention-related brain regions.

PubMed

Spielberg, Jeffrey M; De Leon, Angeline A; Bredemeier, Keith; Heller, Wendy; Engels, Anna S; Warren, Stacie L; Crocker, Laura D; Sutton, Bradley P; Miller, Gregory A

2013-09-01

Background Habituation of the fear response, critical for the treatment of anxiety, is inconsistently observed during exposure to threatening stimuli. One potential explanation for this inconsistency is differential attentional engagement with negatively valenced stimuli as a function of anxiety type. Methods The present study tested this hypothesis by examining patterns of neural habituation associated with anxious arousal, characterized by panic symptoms and immediate engagement with negatively valenced stimuli, versus anxious apprehension, characterized by engagement in worry to distract from negatively valenced stimuli. Results As predicted, the two anxiety types evidenced distinct patterns of attentional engagement. Anxious arousal was associated with immediate activation in attention-related brain regions that habituated over time, whereas anxious apprehension was associated with delayed activation in attention-related brain regions that occurred only after habituation in a worry-related brain region. Conclusions Results further elucidate mechanisms involved in attention to negatively valenced stimuli and indicate that anxiety is a heterogeneous construct with regard to attention to such stimuli.

Anxiety type modulates immediate versus delayed engagement of attention-related brain regions

PubMed Central

Spielberg, Jeffrey M; De Leon, Angeline A; Bredemeier, Keith; Heller, Wendy; Engels, Anna S; Warren, Stacie L; Crocker, Laura D; Sutton, Bradley P; Miller, Gregory A

2013-01-01

Background Habituation of the fear response, critical for the treatment of anxiety, is inconsistently observed during exposure to threatening stimuli. One potential explanation for this inconsistency is differential attentional engagement with negatively valenced stimuli as a function of anxiety type. Methods The present study tested this hypothesis by examining patterns of neural habituation associated with anxious arousal, characterized by panic symptoms and immediate engagement with negatively valenced stimuli, versus anxious apprehension, characterized by engagement in worry to distract from negatively valenced stimuli. Results As predicted, the two anxiety types evidenced distinct patterns of attentional engagement. Anxious arousal was associated with immediate activation in attention-related brain regions that habituated over time, whereas anxious apprehension was associated with delayed activation in attention-related brain regions that occurred only after habituation in a worry-related brain region. Conclusions Results further elucidate mechanisms involved in attention to negatively valenced stimuli and indicate that anxiety is a heterogeneous construct with regard to attention to such stimuli. PMID:24392275

Damping scaling factors for elastic response spectra for shallow crustal earthquakes in active tectonic regions: "average" horizontal component

USGS Publications Warehouse

Rezaeian, Sanaz; Bozorgnia, Yousef; Idriss, I.M.; Abrahamson, Norman; Campbell, Kenneth; Silva, Walter

2014-01-01

Ground motion prediction equations (GMPEs) for elastic response spectra are typically developed at a 5% viscous damping ratio. In reality, however, structural and nonstructural systems can have other damping ratios. This paper develops a new model for a damping scaling factor (DSF) that can be used to adjust the 5% damped spectral ordinates predicted by a GMPE for damping ratios between 0.5% to 30%. The model is developed based on empirical data from worldwide shallow crustal earthquakes in active tectonic regions. Dependencies of the DSF on potential predictor variables, such as the damping ratio, spectral period, ground motion duration, moment magnitude, source-to-site distance, and site conditions, are examined. The strong influence of duration is captured by the inclusion of both magnitude and distance in the DSF model. Site conditions show weak influence on the DSF. The proposed damping scaling model provides functional forms for the median and logarithmic standard deviation of DSF, and is developed for both RotD50 and GMRotI50 horizontal components. A follow-up paper develops a DSF model for vertical ground motion.

Computed Energetics of Nucleotides in Spatial Ribozyme Structures: An Accurate Identification of Functional Regions from Structure

PubMed Central

Torshin, Ivan Y.

2004-01-01

Ribozymes are functionally diverse RNA molecules with intrinsic catalytic activity. Multiple structural and biochemical studies are required to establish which nucleotide bases are involved in the catalysis. The relative energetic properties of the nucleotide bases have been analyzed in a set of the known ribozyme structures. It was found that many of the known catalytic nucleotides can be identified using only the structure without any additional biochemical data. The results of the calculations compare well with the available biochemical data on RNA stability. Extensive in silico mutagenesis suggests that most of the nucleotides in ribozymes stabilize the RNA. The calculations show that relative contribution of the catalytic bases to RNA stability observably differs from contributions of the noncatalytic bases. Distinction between the concepts of “relative stability” and “mutational stability” is suggested. As results of prediction for several models of ribozymes appear to be in agreement with the published data on the potential active site regions, the method can potentially be used for prediction of functional nucleotides from nucleic sequence. PMID:15105962

Predicting Stroop Effect from Spontaneous Neuronal Activity: A Study of Regional Homogeneity

PubMed Central

Liu, Congcong; Chen, Zhencai; Wang, Ting; Tang, Dandan; Hitchman, Glenn; Sun, Jiangzhou; Zhao, Xiaoyue; Wang, Lijun; Chen, Antao

2015-01-01

The Stroop effect is one of the most robust and well-studied phenomena in cognitive psychology and cognitive neuroscience. However, little is known about the relationship between intrinsic brain activity and the individual differences of this effect. In the present study, we explored this issue by examining whether resting-state functional magnetic resonance imaging (rs-fMRI) signals could predict individual differences in the Stroop effect of healthy individuals. A partial correlation analysis was calculated to examine the relationship between regional homogeneity (ReHo) and Stroop effect size, while controlling for age, sex, and framewise displacement (FD). The results showed positive correlations in the left inferior frontal gyrus (LIFG), the left insula, the ventral anterior cingulate cortex (vACC), and the medial frontal gyrus (MFG), and negative correlation in the left precentral gyrus (LPG). These results indicate the possible influences of the LIFG, the left insula, and the LPG on the efficiency of cognitive control, and demonstrate that the key nodes of default mode network (DMN) may be important in goal-directed behavior and/or mental effort during cognitive control tasks. PMID:25938442

Multifractal Detrended Fluctuation Analysis of Regional Precipitation Sequences Based on the CEEMDAN-WPT

NASA Astrophysics Data System (ADS)

Liu, Dong; Cheng, Chen; Fu, Qiang; Liu, Chunlei; Li, Mo; Faiz, Muhammad Abrar; Li, Tianxiao; Khan, Muhammad Imran; Cui, Song

2018-03-01

In this paper, the complete ensemble empirical mode decomposition with the adaptive noise (CEEMDAN) algorithm is introduced into the complexity research of precipitation systems to improve the traditional complexity measure method specific to the mode mixing of the Empirical Mode Decomposition (EMD) and incomplete decomposition of the ensemble empirical mode decomposition (EEMD). We combined the CEEMDAN with the wavelet packet transform (WPT) and multifractal detrended fluctuation analysis (MF-DFA) to create the CEEMDAN-WPT-MFDFA, and used it to measure the complexity of the monthly precipitation sequence of 12 sub-regions in Harbin, Heilongjiang Province, China. The results show that there are significant differences in the monthly precipitation complexity of each sub-region in Harbin. The complexity of the northwest area of Harbin is the lowest and its predictability is the best. The complexity and predictability of the middle and Midwest areas of Harbin are about average. The complexity of the southeast area of Harbin is higher than that of the northwest, middle, and Midwest areas of Harbin and its predictability is worse. The complexity of Shuangcheng is the highest and its predictability is the worst of all the studied sub-regions. We used terrain and human activity as factors to analyze the causes of the complexity of the local precipitation. The results showed that the correlations between the precipitation complexity and terrain are obvious, and the correlations between the precipitation complexity and human influence factors vary. The distribution of the precipitation complexity in this area may be generated by the superposition effect of human activities and natural factors such as terrain, general atmospheric circulation, land and sea location, and ocean currents. To evaluate the stability of the algorithm, the CEEMDAN-WPT-MFDFA was compared with the equal probability coarse graining LZC algorithm, fuzzy entropy, and wavelet entropy. The results show that the CEEMDAN-WPT-MFDFA was more stable than 3 contrast methods under the influence of white noise and colored noise, which proves that the CEEMDAN-WPT-MFDFA has a strong robustness under the influence of noise.

Occipital Alpha Activity during Stimulus Processing Gates the Information Flow to Object-Selective Cortex

PubMed Central

Zumer, Johanna M.; Scheeringa, René; Schoffelen, Jan-Mathijs; Norris, David G.; Jensen, Ole

2014-01-01

Given the limited processing capabilities of the sensory system, it is essential that attended information is gated to downstream areas, whereas unattended information is blocked. While it has been proposed that alpha band (8–13 Hz) activity serves to route information to downstream regions by inhibiting neuronal processing in task-irrelevant regions, this hypothesis remains untested. Here we investigate how neuronal oscillations detected by electroencephalography in visual areas during working memory encoding serve to gate information reflected in the simultaneously recorded blood-oxygenation-level-dependent (BOLD) signals recorded by functional magnetic resonance imaging in downstream ventral regions. We used a paradigm in which 16 participants were presented with faces and landscapes in the right and left hemifields; one hemifield was attended and the other unattended. We observed that decreased alpha power contralateral to the attended object predicted the BOLD signal representing the attended object in ventral object-selective regions. Furthermore, increased alpha power ipsilateral to the attended object predicted a decrease in the BOLD signal representing the unattended object. We also found that the BOLD signal in the dorsal attention network inversely correlated with visual alpha power. This is the first demonstration, to our knowledge, that oscillations in the alpha band are implicated in the gating of information from the visual cortex to the ventral stream, as reflected in the representationally specific BOLD signal. This link of sensory alpha to downstream activity provides a neurophysiological substrate for the mechanism of selective attention during stimulus processing, which not only boosts the attended information but also suppresses distraction. Although previous studies have shown a relation between the BOLD signal from the dorsal attention network and the alpha band at rest, we demonstrate such a relation during a visuospatial task, indicating that the dorsal attention network exercises top-down control of visual alpha activity. PMID:25333286

Reading visually embodied meaning from the brain: Visually grounded computational models decode visual-object mental imagery induced by written text.

PubMed

Anderson, Andrew James; Bruni, Elia; Lopopolo, Alessandro; Poesio, Massimo; Baroni, Marco

2015-10-15

Embodiment theory predicts that mental imagery of object words recruits neural circuits involved in object perception. The degree of visual imagery present in routine thought and how it is encoded in the brain is largely unknown. We test whether fMRI activity patterns elicited by participants reading objects' names include embodied visual-object representations, and whether we can decode the representations using novel computational image-based semantic models. We first apply the image models in conjunction with text-based semantic models to test predictions of visual-specificity of semantic representations in different brain regions. Representational similarity analysis confirms that fMRI structure within ventral-temporal and lateral-occipital regions correlates most strongly with the image models and conversely text models correlate better with posterior-parietal/lateral-temporal/inferior-frontal regions. We use an unsupervised decoding algorithm that exploits commonalities in representational similarity structure found within both image model and brain data sets to classify embodied visual representations with high accuracy (8/10) and then extend it to exploit model combinations to robustly decode different brain regions in parallel. By capturing latent visual-semantic structure our models provide a route into analyzing neural representations derived from past perceptual experience rather than stimulus-driven brain activity. Our results also verify the benefit of combining multimodal data to model human-like semantic representations. Copyright © 2015 Elsevier Inc. All rights reserved.

The influence of an atmospheric Two-Way coupled model system on the predictability of extratropical cyclones

NASA Astrophysics Data System (ADS)

Schuster, Mareike; Thürkow, Markus; Weiher, Stefan; Kirchner, Ingo; Ulbrich, Uwe; Will, Andreas

2016-04-01

A general bias of global atmosphere ocean models, and also of the MPI-ESM, is an under-representation of the high latitude cyclone activity and an overestimation of the mid latitude cyclone activity in the North Atlantic, thus representing the extra-tropical storm track too zonal. We will show, that this effect can be antagonized by applying an atmospheric Two-Way Coupling (TWC). In this study we present a newly developed Two-Way Coupled model system, which is based on the MPI-ESM, and show that it is able to capture the mean storm track location more accurate. It also influences the sub-decadal deterministic predictability of extra-tropical cyclones and shows significantly enhanced skill compared to the "uncoupled" MPI-ESM standalone system. This study evaluates a set of hindcast experiments performed with said Two-Way Coupled model system. The regional model COSMO CLM is Two-Way Coupled to the atmosphere of the global Max-Plack-Institute Earth System Model (MPI-ESM) and therefore integrates and exchanges the state of the atmosphere every 10 minutes (MPI-TWC-ESM). In the coupled source region (North Atlantic), mesoscale processes which are relevant for the formation and early-stage development of cyclones are expected to be better represented, and therefore influence the large scale dynamics of the target region (Europe). The database covers 102 "uncoupled" years and 102 Two-Way Coupled years of the recent climate (1960-2010). Results are validated against the ERA-Interim reanalysis. Besides the climatological point of view, the design of this single model ensemble allows for an analysis of the predictability of the first and second leadyears of the hindcasts. As a first step to understand the improved predictability of cyclones, we will show a detailed analysis of climatologies for specific cyclone categories, sorted by season and region. Especially for cyclones affecting Europe, the TWC is capable to counteract the AOGCM's biases in the North Atlantic. Also, cyclones which are generated in the northern North Atlantic and the Labrador Sea are to an extraordinary extent underestimated in the "uncoupled" MPI-ESM - for the latter region the TWC can balance this shortcoming. In the Northern Hemisphere annual mean statistics the TWC does not change the distribution of the strength of cyclones, but it changes the distribution of the lifetime of cyclones.

ACTIVE REGION MOSS: DOPPLER SHIFTS FROM HINODE/EXTREME-ULTRAVIOLET IMAGING SPECTROMETER OBSERVATIONS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tripathi, Durgesh; Mason, Helen E.; Klimchuk, James A.

2012-07-01

Studying the Doppler shifts and the temperature dependence of Doppler shifts in moss regions can help us understand the heating processes in the core of the active regions. In this paper, we have used an active region observation recorded by the Extreme-ultraviolet Imaging Spectrometer (EIS) on board Hinode on 2007 December 12 to measure the Doppler shifts in the moss regions. We have distinguished the moss regions from the rest of the active region by defining a low-density cutoff as derived by Tripathi et al. in 2010. We have carried out a very careful analysis of the EIS wavelength calibrationmore » based on the method described by Young et al. in 2012. For spectral lines having maximum sensitivity between log T = 5.85 and log T = 6.25 K, we find that the velocity distribution peaks at around 0 km s{sup -1} with an estimated error of 4-5 km s{sup -1}. The width of the distribution decreases with temperature. The mean of the distribution shows a blueshift which increases with increasing temperature and the distribution also shows asymmetries toward blueshift. Comparing these results with observables predicted from different coronal heating models, we find that these results are consistent with both steady and impulsive heating scenarios. However, the fact that there are a significant number of pixels showing velocity amplitudes that exceed the uncertainty of 5 km s{sup -1} is suggestive of impulsive heating. Clearly, further observational constraints are needed to distinguish between these two heating scenarios.« less

Nonlinear Interactions within the D-Region Ionosphere

NASA Astrophysics Data System (ADS)

Moore, Robert

2016-07-01

This paper highlights the best results obtained during D-region modification experiments performed by the University of Florida at the High-frequency Active Auroral Research Program (HAARP) observatory between 2007 and 2014. Over this period, we saw a tremendous improvement in ELF/VLF wave generation efficiency. We identified methods to characterize ambient and modified ionospheric properties and to discern and quantify specific types of interactions. We have demonstrated several important implications of HF cross-modulation effects, including "Doppler Spoofing" on HF radio waves. Throughout this talk, observations are compared with the predictions of an ionospheric HF heating model to provide context and guidance for future D-region modification experiments.

An analysis of cropland mask choice and ancillary data for annual corn yield forecasting using MODIS data

NASA Astrophysics Data System (ADS)

Shao, Yang; Campbell, James B.; Taff, Gregory N.; Zheng, Baojuan

2015-06-01

The Midwestern United States is one of the world's most important corn-producing regions. Monitoring and forecasting of corn yields in this intensive agricultural region are important activities to support food security, commodity markets, bioenergy industries, and formation of national policies. This study aims to develop forecasting models that have the capability to provide mid-season prediction of county-level corn yields for the entire Midwestern United States. We used multi-temporal MODIS NDVI (normalized difference vegetation index) 16-day composite data as the primary input, with digital elevation model (DEM) and parameter-elevation relationships on independent slopes model (PRISM) climate data as additional inputs. The DEM and PRISM data, along with three types of cropland masks were tested and compared to evaluate their impacts on model predictive accuracy. Our results suggested that the use of general cropland masks (e.g., summer crop or cultivated crops) generated similar results compared with use of an annual corn-specific mask. Leave-one-year-out cross-validation resulted in an average R2 of 0.75 and RMSE value of 1.10 t/ha. Using a DEM as an additional model input slightly improved performance, while inclusion of PRISM climate data appeared not to be important for our regional corn-yield model. Furthermore, our model has potential for real-time/early prediction. Our corn yield esitmates are available as early as late July, which is an improvement upon previous corn-yield prediction models. In addition to annual corn yield forecasting, we examined model uncertainties through spatial and temporal analysis of the model's predictive error distribution. The magnitude of predictive error (by county) appears to be associated with the spatial patterns of corn fields in the study area.

A model for solar constant secular changes

NASA Technical Reports Server (NTRS)

Schatten, Kenneth H.

1988-01-01

In this paper, contrast models for solar active region and global photospheric features are used to reproduce the observed Active Cavity Radiometer and Earth Radiation Budget secular trends in reasonably good fashion. A prediction for the next decade of solar constant variations is made using the model. Secular trends in the solar constant obtained from the present model support the view that the Maunder Minimum may be related to the Little Ice Age of the 17th century.

Intrinsic resting-state activity predicts working memory brain activation and behavioral performance.

PubMed

Zou, Qihong; Ross, Thomas J; Gu, Hong; Geng, Xiujuan; Zuo, Xi-Nian; Hong, L Elliot; Gao, Jia-Hong; Stein, Elliot A; Zang, Yu-Feng; Yang, Yihong

2013-12-01

Although resting-state brain activity has been demonstrated to correspond with task-evoked brain activation, the relationship between intrinsic and evoked brain activity has not been fully characterized. For example, it is unclear whether intrinsic activity can also predict task-evoked deactivation and whether the rest-task relationship is dependent on task load. In this study, we addressed these issues on 40 healthy control subjects using resting-state and task-driven [N-back working memory (WM) task] functional magnetic resonance imaging data collected in the same session. Using amplitude of low-frequency fluctuation (ALFF) as an index of intrinsic resting-state activity, we found that ALFF in the middle frontal gyrus and inferior/superior parietal lobules was positively correlated with WM task-evoked activation, while ALFF in the medial prefrontal cortex, posterior cingulate cortex, superior frontal gyrus, superior temporal gyrus, and fusiform gyrus was negatively correlated with WM task-evoked deactivation. Further, the relationship between the intrinsic resting-state activity and task-evoked activation in lateral/superior frontal gyri, inferior/superior parietal lobules, superior temporal gyrus, and midline regions was stronger at higher WM task loads. In addition, both resting-state activity and the task-evoked activation in the superior parietal lobule/precuneus were significantly correlated with the WM task behavioral performance, explaining similar portions of intersubject performance variance. Together, these findings suggest that intrinsic resting-state activity facilitates or is permissive of specific brain circuit engagement to perform a cognitive task, and that resting activity can predict subsequent task-evoked brain responses and behavioral performance. Copyright © 2012 Wiley Periodicals, Inc.

Distributed Patterns of Reactivation Predict Vividness of Recollection.

PubMed

St-Laurent, Marie; Abdi, Hervé; Buchsbaum, Bradley R

2015-10-01

According to the principle of reactivation, memory retrieval evokes patterns of brain activity that resemble those instantiated when an event was first experienced. Intuitively, one would expect neural reactivation to contribute to recollection (i.e., the vivid impression of reliving past events), but evidence of a direct relationship between the subjective quality of recollection and multiregional reactivation of item-specific neural patterns is lacking. The current study assessed this relationship using fMRI to measure brain activity as participants viewed and mentally replayed a set of short videos. We used multivoxel pattern analysis to train a classifier to identify individual videos based on brain activity evoked during perception and tested how accurately the classifier could distinguish among videos during mental replay. Classification accuracy correlated positively with memory vividness, indicating that the specificity of multivariate brain patterns observed during memory retrieval was related to the subjective quality of a memory. In addition, we identified a set of brain regions whose univariate activity during retrieval predicted both memory vividness and the strength of the classifier's prediction irrespective of the particular video that was retrieved. Our results establish distributed patterns of neural reactivation as a valid and objective marker of the quality of recollection.

Characterization and parameterization of aerosol cloud condensation nuclei activation under different pollution conditions

PubMed Central

Che, H. C.; Zhang, X. Y.; Wang, Y. Q.; Zhang, L.; Shen, X. J.; Zhang, Y. M.; Ma, Q. L.; Sun, J. Y.; Zhang, Y. W.; Wang, T. T.

2016-01-01

To better understand the cloud condensation nuclei (CCN) activation capacity of aerosol particles in different pollution conditions, a long-term field experiment was carried out at a regional GAW (Global Atmosphere Watch) station in the Yangtze River Delta area of China. The homogeneity of aerosol particles was the highest in clean weather, with the highest active fraction of all the weather types. For pollution with the same visibility, the residual aerosol particles in higher relative humidity weather conditions were more externally mixed and heterogeneous, with a lower hygroscopic capacity. The hygroscopic capacity (κ) of organic aerosols can be classified into 0.1 and 0.2 in different weather types. The particles at ~150 nm were easily activated in haze weather conditions. For CCN predictions, the bulk chemical composition method was closer to observations at low supersaturations (≤0.1%), whereas when the supersaturation was ≥0.2%, the size-resolved chemical composition method was more accurate. As for the mixing state of the aerosol particles, in haze, heavy haze, and severe haze weather conditions CCN predictions based on the internal mixing assumption were robust, whereas for other weather conditions, predictions based on the external mixing assumption were more accurate. PMID:27075947

Dust inflated accretion disc as the origin of the broad line region in active galactic nuclei

NASA Astrophysics Data System (ADS)

Baskin, Alexei; Laor, Ari

2018-02-01

The broad line region (BLR) in active galactic nuclei (AGNs) is composed of dense gas (˜1011 cm-3) on sub-pc scale, which absorbs about 30 per cent of the ionizing continuum. The outer size of the BLR is likely set by dust sublimation, and its density by the incident radiation pressure compression (RPC). But, what is the origin of this gas, and what sets its covering factor (CF)? Czerny & Hryniewicz (2011) suggested that the BLR is a failed dusty wind from the outer accretion disc. We explore the expected dust properties, and the implied BLR structure. We find that graphite grains sublimate only at T ≃ 2000 K at the predicted density of ˜1011 cm-3, and therefore large graphite grains (≥0.3 μm) survive down to the observed size of the BLR, RBLR. The dust opacity in the accretion disc atmosphere is ˜50 times larger than previously assumed, and leads to an inflated torus-like structure, with a predicted peak height at RBLR. The illuminated surface of this torus-like structure is a natural place for the BLR. The BLR CF is mostly set by the gas metallicity, the radiative accretion efficiency, a dynamic configuration and ablation by the incident optical-UV continuum. This model predicts that the BLR should extend inwards of RBLR to the disc radius where the surface temperature is ≃2000 K, which occurs at Rin ≃ 0.18RBLR. The value of Rin can be tested by reverberation mapping of the higher ionization lines, predicted by RPC to peak well inside RBLR. The dust inflated disc scenario can also be tested based on the predicted response of RBLR and the CF to changes in the AGN luminosity and accretion rate.

Two grave issues concerning the expected Tokai Earthquake

NASA Astrophysics Data System (ADS)

Mogi, K.

2004-08-01

The possibility of a great shallow earthquake (M 8) in the Tokai region, central Honshu, in the near future was pointed out by Mogi in 1969 and by the Coordinating Committee for Earthquake Prediction (CCEP), Japan (1970). In 1978, the government enacted the Large-Scale Earthquake Countermeasures Law and began to set up intensified observations in this region for short-term prediction of the expected Tokai earthquake. In this paper, two serious issues are pointed out, which may contribute to catastrophic effects in connection with the Tokai earthquake: 1. The danger of black-and-white predictions: According to the scenario based on the Large-Scale Earthquake Countermeasures Law, if abnormal crustal changes are observed, the Earthquake Assessment Committee (EAC) will determine whether or not there is an imminent danger. The findings are reported to the Prime Minister who decides whether to issue an official warning statement. Administrative policy clearly stipulates the measures to be taken in response to such a warning, and because the law presupposes the ability to predict a large earthquake accurately, there are drastic measures appropriate to the situation. The Tokai region is a densely populated region with high social and economic activity, and it is traversed by several vital transportation arteries. When a warning statement is issued, all transportation is to be halted. The Tokyo capital region would be cut off from the Nagoya and Osaka regions, and there would be a great impact on all of Japan. I (the former chairman of EAC) maintained that in view of the variety and complexity of precursory phenomena, it was inadvisable to attempt a black-and-white judgment as the basis for a "warning statement". I urged that the government adopt a "soft warning" system that acknowledges the uncertainty factor and that countermeasures be designed with that uncertainty in mind. 2. The danger of nuclear power plants in the focal region: Although the possibility of the occurrence of a great shallow earthquake in the Tokai region was pointed out by CCEP in 1970, soon after, plans for construction of a nuclear power plant started in this region. Since 1976, Hamaoka nuclear power plants (Units 1˜4) have been operating near the center of the expected focal region of the great Tokai earthquake, and Unit 5 is under construction. This is quite a dangerous situation.

Estimating the health benefits of planned public transit investments in Montreal.

PubMed

Tétreault, Louis-François; Eluru, Naveen; Hatzopoulou, Marianne; Morency, Patrick; Plante, Celine; Morency, Catherine; Reynaud, Frederic; Shekarrizfard, Maryam; Shamsunnahar, Yasmin; Faghih Imani, Ahmadreza; Drouin, Louis; Pelletier, Anne; Goudreau, Sophie; Tessier, Francois; Gauvin, Lise; Smargiassi, Audrey

2018-01-01

Since public transit infrastructure affects road traffic volumes and influences transportation mode choice, which in turn impacts health, it is important to estimate the alteration of the health burden linked with transit policies. We quantified the variation in health benefits and burden between a business as usual (BAU) and a public transit (PT) scenarios in 2031 (with 8 and 19 new subway and train stations) for the greater Montreal region. Using mode choice and traffic assignment models, we predicted the transportation mode choice and traffic assignment on the road network. Subsequently, we estimated the distance travelled in each municipality by mode, the minutes spent in active transportation, as well as traffic emissions. Thereafter we estimated the health burden attributed to air pollution and road traumas and the gains associated with active transportation for both the BAU and PT scenarios. We predicted a slight decrease of overall trips and kilometers travelled by car as well as an increase of active transportation for the PT in 2031 vs the BAU. Our analysis shows that new infrastructure will reduce the overall burden of transportation by 2.5 DALYs per 100,000 persons. This decrease is caused by the reduction of road traumas occurring in the inner suburbs and central Montreal region as well as gains in active transportation in the inner suburbs. Based on the results of our study, transportation planned public transit projects for Montreal are unlikely to reduce drastically the burden of disease attributable to road vehicles and infrastructures in the Montreal region. The impact of the planned transportation infrastructures seems to be very low and localized mainly in the areas where new public transit stations are planned. Copyright © 2017 Elsevier Inc. All rights reserved.

Impacts and socio-ecological feedbacks associated with regionalization of water supply in a suburban New England watershed

NASA Astrophysics Data System (ADS)

Wollheim, W. M.; Stewart, R. J.; Polsky, C.; Pontius, R.; Hopkinson, C.

2012-12-01

Suburban watersheds often rely on locally derived ecosystem services such as water supply, even as these services are threatened by existing land use and land-use change patterns. At some point, the ability of the watershed to provide such services may become impaired. Socio-ecological feedbacks are likely to emerge, leading to more active management of locally derived water provisioning services, or replacement of services generated locally with those from more distant locations. We applied a spatially distributed hydrological model to explore the impact of multiple interacting and spatially varying human activities, including feedbacks, on the hydrology of a suburban watershed in the Boston, MA, metropolitan area, the Ipswich R. watershed. We accounted for the role of impervious surfaces, lawns and lawn watering, septic systems, and water use, as well as several socio-ecological feedbacks evident in the region (water bans, regional import). The result of human activities on the landscape is that most of the river system is wetter than a hypothetical pristine condition (predicted mean basin runoff during summers of 0.65 mm per day in contemporary vs. 0.10 mm per day in pristine). However, water withdrawals along the large main stem river remove some of this excess, resulting in a reduced net effect of human activities at the large watershed scale (predicted mean basin runoff of 0.54 mm per day). Recent feedbacks in response to low flows have resulted in increasing importance of imported water supplies, removing local constraint to further development. Because suburban watersheds continue to rely on local ecosystem services, suburban watersheds may be useful model systems within which to study socio-ecological feedbacks.

Prefrontal inhibition of threat processing reduces working memory interference

PubMed Central

Clarke, Robert; Johnstone, Tom

2013-01-01

Bottom-up processes can interrupt ongoing cognitive processing in order to adaptively respond to emotional stimuli of high potential significance, such as those that threaten wellbeing. However it is vital that this interference can be modulated in certain contexts to focus on current tasks. Deficits in the ability to maintain the appropriate balance between cognitive and emotional demands can severely impact on day-to-day activities. This fMRI study examined this interaction between threat processing and cognition; 18 adult participants performed a visuospatial working memory (WM) task with two load conditions, in the presence and absence of anxiety induction by threat of electric shock. Threat of shock interfered with performance in the low cognitive load condition; however interference was eradicated under high load, consistent with engagement of emotion regulation mechanisms. Under low load the amygdala showed significant activation to threat of shock that was modulated by high cognitive load. A directed top-down control contrast identified two regions associated with top-down control; ventrolateral PFC and dorsal ACC. Dynamic causal modeling provided further evidence that under high cognitive load, top-down inhibition is exerted on the amygdala and its outputs to prefrontal regions. Additionally, we hypothesized that individual differences in a separate, non-emotional top-down control task would predict the recruitment of dorsal ACC and ventrolateral PFC during top-down control of threat. Consistent with this, performance on a separate dichotic listening task predicted dorsal ACC and ventrolateral PFC activation during high WM load under threat of shock, though activation in these regions did not directly correlate with WM performance. Together, the findings suggest that under high cognitive load and threat, top-down control is exerted by dACC and vlPFC to inhibit threat processing, thus enabling WM performance without threat-related interference. PMID:23750133

Decoding negative affect personality trait from patterns of brain activation to threat stimuli.

PubMed

Fernandes, Orlando; Portugal, Liana C L; Alves, Rita de Cássia S; Arruda-Sanchez, Tiago; Rao, Anil; Volchan, Eliane; Pereira, Mirtes; Oliveira, Letícia; Mourao-Miranda, Janaina

2017-01-15

Pattern recognition analysis (PRA) applied to functional magnetic resonance imaging (fMRI) has been used to decode cognitive processes and identify possible biomarkers for mental illness. In the present study, we investigated whether the positive affect (PA) or negative affect (NA) personality traits could be decoded from patterns of brain activation in response to a human threat using a healthy sample. fMRI data from 34 volunteers (15 women) were acquired during a simple motor task while the volunteers viewed a set of threat stimuli that were directed either toward them or away from them and matched neutral pictures. For each participant, contrast images from a General Linear Model (GLM) between the threat versus neutral stimuli defined the spatial patterns used as input to the regression model. We applied a multiple kernel learning (MKL) regression combining information from different brain regions hierarchically in a whole brain model to decode the NA and PA from patterns of brain activation in response to threat stimuli. The MKL model was able to decode NA but not PA from the contrast images between threat stimuli directed away versus neutral with a significance above chance. The correlation and the mean squared error (MSE) between predicted and actual NA were 0.52 (p-value=0.01) and 24.43 (p-value=0.01), respectively. The MKL pattern regression model identified a network with 37 regions that contributed to the predictions. Some of the regions were related to perception (e.g., occipital and temporal regions) while others were related to emotional evaluation (e.g., caudate and prefrontal regions). These results suggest that there was an interaction between the individuals' NA and the brain response to the threat stimuli directed away, which enabled the MKL model to decode NA from the brain patterns. To our knowledge, this is the first evidence that PRA can be used to decode a personality trait from patterns of brain activation during emotional contexts. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Regional-scale controls on the spatial activity of rockfalls (Turtmann Valley, Swiss Alps) - A multivariate modeling approach

NASA Astrophysics Data System (ADS)

Messenzehl, Karoline; Meyer, Hanna; Otto, Jan-Christoph; Hoffmann, Thomas; Dikau, Richard

2017-06-01

In mountain geosystems, rockfalls are among the most effective sediment transfer processes, reflected in the regional-scale distribution of talus slopes. However, the understanding of the key controlling factors seems to decrease with increasing spatial scale, due to emergent and complex system behavior and not least to recent methodological shortcomings in rockfall modeling research. In this study, we aim (i) to develop a new approach to identify major regional-scale rockfall controls and (ii) to quantify the relative importance of these controls. Using a talus slope inventory in the Turtmann Valley (Swiss Alps), we applied for the first time the decision-tree based random forest algorithm (RF) in combination with a principal component logistic regression (PCLR) to evaluate the spatial distribution of rockfall activity. This study presents new insights into the discussion on whether periglacial rockfall events are controlled more by topo-climatic, cryospheric, paraglacial or/and rock mechanical properties. Both models explain the spatial rockfall pattern very well, given the high areas under the Receiver Operating Characteristic (ROC) curves of > 0.83. Highest accuracy was obtained by the RF, correctly predicting 88% of the rockfall source areas. The RF appears to have a great potential in geomorphic research involving multicollinear data. The regional permafrost distribution, coupled to the bedrock curvature and valley topography, was detected to be the primary rockfall control. Rockfall source areas cluster within a low-radiation elevation belt (2900-3300 m a.s.l,) consistent with a permafrost probability of > 90%. The second most important factor is the time since deglaciation, reflected by the high abundance of rockfalls along recently deglaciated (< 100 years), north-facing slopes. However, our findings also indicate a strong rock mechanical control on the paraglacial rockfall activity, declining either exponentially or linearly since deglaciation. The study demonstrates the benefit of combined statistical approaches for predicting rockfall activity in deglaciated, permafrost-affected mountain valleys and highlights the complex interplay between rock mechanical, paraglacial and topo-climatic controls at the regional scale.

Computer-assisted determination of minimum energy conformations. 7: A pharmacophore model of the active region of the alpha2-adrenoceptor

NASA Astrophysics Data System (ADS)

Ashman, William P.; Mickiewicz, A. P.; Nelson, Todd M.

1992-09-01

Molecular modeling and computational chemistry techniques are used to analyze compounds in developing pharmacophores of biological receptors to use as templates in structure activity relationship studies and to design new chemicals having physiological activity of interest. In this study, the results of x-ray crystal analyses and PM3 semi-empirical molecular orbital conformational analyses are used to determine the three-dimensional representations of selected adrenergic compounds known to be agonists with the alpha2-adrenoceptor in achieving optimized geometries and electrostatic parameters. The alpha2-adrenergic agonists interact with the adrenergic system receptors to produce various increases or decreases in hemodynamic responses (i.e., hypertension, hypotension, and bradycardia) and sedation. A pharmacophore model of the active region of the alpha2-adrenoceptor is described based on the superimposition of common structural, electrostatic, and physicochemical features of the compounds. Using the model to predict compound adrenergic activity and to design alpha2-adrenergic compounds is discussed.

Multi-scale integration and predictability in resting state brain activity

PubMed Central

Kolchinsky, Artemy; van den Heuvel, Martijn P.; Griffa, Alessandra; Hagmann, Patric; Rocha, Luis M.; Sporns, Olaf; Goñi, Joaquín

2014-01-01

The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales. PMID:25104933

Role of the superior colliculus in choosing mixed-strategy saccades.

PubMed

Thevarajah, Dhushan; Mikulić, Areh; Dorris, Michael C

2009-02-18

Game theory outlines optimal response strategies during mixed-strategy competitions. The neural processes involved in choosing individual strategic actions, however, remain poorly understood. Here, we tested whether the superior colliculus (SC), a brain region critical for generating sensory-guided saccades, is also involved in choosing saccades under strategic conditions. Monkeys were free to choose either of two saccade targets as they competed against a computer opponent during the mixed-strategy game "matching pennies." The accuracy with which presaccadic SC activity predicted upcoming choice gradually increased in the time leading up to the saccade. Probing the SC with suprathreshold stimulation demonstrated that these evolving signals were functionally involved in preparing strategic saccades. Finally, subthreshold stimulation of the SC increased the likelihood that contralateral saccades were selected. Together, our results suggest that motor regions of the brain play an active role in choosing strategic actions rather than passively executing those prespecified by upstream executive regions.

Immediate memory consequences of the effect of emotion on attention to pictures.

PubMed

Talmi, Deborah; Anderson, Adam K; Riggs, Lily; Caplan, Jeremy B; Moscovitch, Morris

2008-03-01

Emotionally arousing stimuli are at once both highly attention grabbing and memorable. We examined whether emotional enhancement of memory (EEM) reflects an indirect effect of emotion on memory, mediated by enhanced attention to emotional items during encoding. We tested a critical prediction of the mediation hypothesis-that regions conjointly activated by emotion and attention would correlate with subsequent EEM. Participants were scanned with fMRI while they watched emotional or neutral pictures under instructions to attend to them a lot or a little, and were then given an immediate recognition test. A region in the left fusiform gyrus was activated by emotion, voluntary attention, and subsequent EEM. A functional network, different for each attention condition, connected this region and the amygdala, which was associated with emotion and EEM, but not with voluntary attention. These findings support an indirect cortical mediation account of immediate EEM that may complement a direct modulation model.

Immediate memory consequences of the effect of emotion on attention to pictures

PubMed Central

Talmi, Deborah; Anderson, Adam K.; Riggs, Lily; Caplan, Jeremy B.; Moscovitch, Morris

2008-01-01

Emotionally arousing stimuli are at once both highly attention grabbing and memorable. We examined whether emotional enhancement of memory (EEM) reflects an indirect effect of emotion on memory, mediated by enhanced attention to emotional items during encoding. We tested a critical prediction of the mediation hypothesis—that regions conjointly activated by emotion and attention would correlate with subsequent EEM. Participants were scanned with fMRI while they watched emotional or neutral pictures under instructions to attend to them a lot or a little, and were then given an immediate recognition test. A region in the left fusiform gyrus was activated by emotion, voluntary attention, and subsequent EEM. A functional network, different for each attention condition, connected this region and the amygdala, which was associated with emotion and EEM, but not with voluntary attention. These findings support an indirect cortical mediation account of immediate EEM that may complement a direct modulation model. PMID:18323572

Advances in Predicting Magnetic Fields on the Far Side of the Sun

NASA Astrophysics Data System (ADS)

Lindsey, C. A.

2016-12-01

Techniques in local solar seismology applied to observations of seismic oscillations in the Sun's near hemisphere allow us to map large magnetic regions in the Sun's far hemisphere. Seismic signatures are not nearly as sensitive to magnetic flux as observations in electromagnetic radiation. However, they clearly identify and locate the 400 or so largest active regions in a typical solar cycle, i.e., those of most concern for space-weather forecasting. By themselves, seismic observations are insensitive to magnetic polarity. However, the Hale polarity law offers tantalizing avenues for guessing polarity distributions from seismic signatures as they evolve. I will review what we presently know about the relationship between seismic signatures of active regions and their magnetic and radiative properties, and offer a preliminary assessment of the potential of far-side seismic maps for space-weather forecasting in the coming decade.

Comparative analysis of amino acid composition in the active site of nirk gene encoding copper-containing nitrite reductase (CuNiR) in bacterial spp.

PubMed

Adhikari, Utpal Kumar; Rahman, M Mizanur

2017-04-01

The nirk gene encoding the copper-containing nitrite reductase (CuNiR), a key catalytic enzyme in the environmental denitrification process that helps to produce nitric oxide from nitrite. The molecular mechanism of denitrification process is definitely complex and in this case a theoretical investigation has been conducted to know the sequence information and amino acid composition of the active site of CuNiR enzyme using various Bioinformatics tools. 10 Fasta formatted sequences were retrieved from the NCBI database and the domain and disordered regions identification and phylogenetic analyses were done on these sequences. The comparative modeling of protein was performed through Modeller 9v14 program and visualized by PyMOL tools. Validated protein models were deposited in the Protein Model Database (PMDB) (PMDB id: PM0080150 to PM0080159). Active sites of nirk encoding CuNiR enzyme were identified by Castp server. The PROCHECK showed significant scores for four protein models in the most favored regions of the Ramachandran plot. Active sites and cavities prediction exhibited that the amino acid, namely Glycine, Alanine, Histidine, Aspartic acid, Glutamic acid, Threonine, and Glutamine were common in four predicted protein models. The present in silico study anticipates that active site analyses result will pave the way for further research on the complex denitrification mechanism of the selected species in the experimental laboratory. Copyright © 2016. Published by Elsevier Ltd.

A neural model of valuation and information virality

PubMed Central

Baek, Elisa C.; O’Donnell, Matthew Brook; Kim, Hyun Suk; Cappella, Joseph N.

2017-01-01

Information sharing is an integral part of human interaction that serves to build social relationships and affects attitudes and behaviors in individuals and large groups. We present a unifying neurocognitive framework of mechanisms underlying information sharing at scale (virality). We argue that expectations regarding self-related and social consequences of sharing (e.g., in the form of potential for self-enhancement or social approval) are integrated into a domain-general value signal that encodes the value of sharing a piece of information. This value signal translates into population-level virality. In two studies (n = 41 and 39 participants), we tested these hypotheses using functional neuroimaging. Neural activity in response to 80 New York Times articles was observed in theory-driven regions of interest associated with value, self, and social cognitions. This activity then was linked to objectively logged population-level data encompassing n = 117,611 internet shares of the articles. In both studies, activity in neural regions associated with self-related and social cognition was indirectly related to population-level sharing through increased neural activation in the brain's value system. Neural activity further predicted population-level outcomes over and above the variance explained by article characteristics and commonly used self-report measures of sharing intentions. This parsimonious framework may help advance theory, improve predictive models, and inform new approaches to effective intervention. More broadly, these data shed light on the core functions of sharing—to express ourselves in positive ways and to strengthen our social bonds. PMID:28242678

Trends in Selective Hydrogen Peroxide Production on Transition Metal Surfaces from First Principles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rankin, Rees B.; Greeley, Jeffrey P.

2012-10-19

We present a comprehensive, Density Functional Theory-based analysis of the direct synthesis of hydrogen peroxide, H2O2, on twelve transition metal surfaces. We determine the full thermodynamics and selected kinetics of the reaction network on these metals, and we analyze these energetics with simple, microkinetically motivated rate theories to assess the activity and selectivity of hydrogen peroxide production on the surfaces of interest. By further exploiting Brønsted-Evans-Polanyi relationships and scaling relationships between the binding energies of different adsorbates, we express the results in the form of a two dimensional contour volcano plot, with the activity and selectivity being determined as functionsmore » of two independent descriptors, the atomic hydrogen and oxygen adsorption free energies. We identify both a region of maximum predicted catalytic activity, which is near Pt and Pd in descriptor space, and a region of selective hydrogen peroxide production, which includes Au. The optimal catalysts represent a compromise between activity and selectivity and are predicted to fall approximately between Au and Pd in descriptor space, providing a compact explanation for the experimentally known performance of Au-Pd alloys for hydrogen peroxide synthesis, and suggesting a target for future computational screening efforts to identify improved direct hydrogen peroxide synthesis catalysts. Related methods of combining activity and selectivity analysis into a single volcano plot may be applicable to, and useful for, other aqueous phase heterogeneous catalytic reactions where selectivity is a key catalytic criterion.« less

PET Measures of Endogenous Opioid Neurotransmission Predict Impulsiveness Traits in Humans

PubMed Central

Love, Tiffany M.; Stohler, Christian S.; Zubieta, Jon-Kar

2011-01-01

Objective The endogenous opioid system and μ-opioid receptors are known to interface environmental events, both positive (e.g., relevant emotional stimuli) and negative (e.g., stressors) with pertinent behavioral responses, regulating motivated behavior. Here we examined the degree to which trait impulsiveness, the tendency to act on cravings and urges rather than delaying gratification, is predicted by either baseline μ-opioid receptor availability or the response of this system to a standardized, experientially-matched stressor. Method Nineteen (19) young healthy male volunteers completed a personality questionnaire (NEO PI-R) and positron emission tomography scans with the μ-opioid receptor selective radiotracer [11C]carfentanil. Measures of receptor concentrations were obtained at rest and during the receipt of an experimentally maintained pain stressor of matched intensity between subjects. Baseline receptor levels and stress-induced activation of μ-opioid neurotransmission were compared between subjects scoring above and below the population median of the NEO impulsiveness subscale and the orthogonal dimension, deliberation, expected to interact with it. Results High impulsiveness and low deliberation scores were associated with significantly higher regional μ-opioid receptor concentrations and greater stress-induced endogenous opioid system activation. Effects were obtained in regions involved in motivated behavior and the effects of drugs of abuse: prefrontal and orbitofrontal cortex, anterior cingulate, thalamus, nucleus accumbens and basolateral amygdala. Mu-opioid receptor availability, and the magnitude of stress-induced endogenous opioid activation in these regions accounted for 21 to 49% of the variance in these personality traits. Conclusions Our data demonstrate that individual differences in the function of the endogenous μ-opioid system predicts personality traits that confer vulnerability or resiliency for risky behaviors, such as the predisposition to develop substance use disorders. These personality traits are also implicated in psychopathological states (e.g., personality disorders), where variations in the function of this neurotransmitter system may play a role as well. PMID:19805703

Higher Language Ability is Related to Angular Gyrus Activation Increase During Semantic Processing, Independent of Sentence Incongruency.

PubMed

Van Ettinger-Veenstra, Helene; McAllister, Anita; Lundberg, Peter; Karlsson, Thomas; Engström, Maria

2016-01-01

This study investigates the relation between individual language ability and neural semantic processing abilities. Our aim was to explore whether high-level language ability would correlate to decreased activation in language-specific regions or rather increased activation in supporting language regions during processing of sentences. Moreover, we were interested if observed neural activation patterns are modulated by semantic incongruency similarly to previously observed changes upon syntactic congruency modulation. We investigated 27 healthy adults with a sentence reading task-which tapped language comprehension and inference, and modulated sentence congruency-employing functional magnetic resonance imaging (fMRI). We assessed the relation between neural activation, congruency modulation, and test performance on a high-level language ability assessment with multiple regression analysis. Our results showed increased activation in the left-hemispheric angular gyrus extending to the temporal lobe related to high language ability. This effect was independent of semantic congruency, and no significant relation between language ability and incongruency modulation was observed. Furthermore, there was a significant increase of activation in the inferior frontal gyrus (IFG) bilaterally when the sentences were incongruent, indicating that processing incongruent sentences was more demanding than processing congruent sentences and required increased activation in language regions. The correlation of high-level language ability with increased rather than decreased activation in the left angular gyrus, a region specific for language processing, is opposed to what the neural efficiency hypothesis would predict. We can conclude that no evidence is found for an interaction between semantic congruency related brain activation and high-level language performance, even though the semantic incongruent condition shows to be more demanding and evoking more neural activation.

Higher Language Ability is Related to Angular Gyrus Activation Increase During Semantic Processing, Independent of Sentence Incongruency

PubMed Central

Van Ettinger-Veenstra, Helene; McAllister, Anita; Lundberg, Peter; Karlsson, Thomas; Engström, Maria

2016-01-01

This study investigates the relation between individual language ability and neural semantic processing abilities. Our aim was to explore whether high-level language ability would correlate to decreased activation in language-specific regions or rather increased activation in supporting language regions during processing of sentences. Moreover, we were interested if observed neural activation patterns are modulated by semantic incongruency similarly to previously observed changes upon syntactic congruency modulation. We investigated 27 healthy adults with a sentence reading task—which tapped language comprehension and inference, and modulated sentence congruency—employing functional magnetic resonance imaging (fMRI). We assessed the relation between neural activation, congruency modulation, and test performance on a high-level language ability assessment with multiple regression analysis. Our results showed increased activation in the left-hemispheric angular gyrus extending to the temporal lobe related to high language ability. This effect was independent of semantic congruency, and no significant relation between language ability and incongruency modulation was observed. Furthermore, there was a significant increase of activation in the inferior frontal gyrus (IFG) bilaterally when the sentences were incongruent, indicating that processing incongruent sentences was more demanding than processing congruent sentences and required increased activation in language regions. The correlation of high-level language ability with increased rather than decreased activation in the left angular gyrus, a region specific for language processing, is opposed to what the neural efficiency hypothesis would predict. We can conclude that no evidence is found for an interaction between semantic congruency related brain activation and high-level language performance, even though the semantic incongruent condition shows to be more demanding and evoking more neural activation. PMID:27014040

Statistical modelling predicts almost complete loss of major periglacial processes in Northern Europe by 2100.

PubMed

Aalto, Juha; Harrison, Stephan; Luoto, Miska

2017-09-11

The periglacial realm is a major part of the cryosphere, covering a quarter of Earth's land surface. Cryogenic land surface processes (LSPs) control landscape development, ecosystem functioning and climate through biogeochemical feedbacks, but their response to contemporary climate change is unclear. Here, by statistically modelling the current and future distributions of four major LSPs unique to periglacial regions at fine scale, we show fundamental changes in the periglacial climate realm are inevitable with future climate change. Even with the most optimistic CO 2 emissions scenario (Representative Concentration Pathway (RCP) 2.6) we predict a 72% reduction in the current periglacial climate realm by 2050 in our climatically sensitive northern Europe study area. These impacts are projected to be especially severe in high-latitude continental interiors. We further predict that by the end of the twenty-first century active periglacial LSPs will exist only at high elevations. These results forecast a future tipping point in the operation of cold-region LSP, and predict fundamental landscape-level modifications in ground conditions and related atmospheric feedbacks.Cryogenic land surface processes characterise the periglacial realm and control landscape development and ecosystem functioning. Here, via statistical modelling, the authors predict a 72% reduction of the periglacial realm in Northern Europe by 2050, and almost complete disappearance by 2100.

Mechanisms by which thrombolytic therapy results in nonuniform lysis and residual thrombus after reperfusion.

PubMed

Anand, S; Kudallur, V; Pitman, E B; Diamond, S L

1997-01-01

A transport-reaction model describing penetration of plasmin by diffusion and permeation into a dissolving fibrin gel was solved numerically to explore mechanisms that lead to the formation and growth of dissolution fingers through blood clots during thrombolytic therapy. Under conditions of fluid permeation driven by arterial pressures, small random spatial variations in the initial fibrin density within clots (+/-4 to 25% peak variations) were predicted by the simulation to result in dramatic dissolution fingers that grew in time. With in vitro experiments, video microscopy revealed that the shape of the proximal face of a fibrin gel, when deformed by pressure-driven permeation, led to lytic breakthrough in the center of the clot, consistent with model predictions of increased velocities in this region leading to cannulation. Computer simulation of lysis of fibrin retracted by platelets (where more permeable regions are expected in the middle of the clot due to retraction) predicted cannulation of the clot during thrombolysis. This residual, annular thrombus was predicted to lyse more slowly, because radial pressure gradients to drive inner clot permeation were quite small. In conjunction with kinetic models of systemic pharmacodynamics and plasminogen activation biochemistry, a two-dimensional transport-reaction model can facilitate the prediction of the time and causes of clot cannulation, poor reperfusion, and embolism during thrombolysis.

Fine-temporal forecasting of outbreak probability and severity: Ross River virus in Western Australia.

PubMed

Koolhof, I S; Bettiol, S; Carver, S

2017-10-01

Health warnings of mosquito-borne disease risk require forecasts that are accurate at fine-temporal resolutions (weekly scales); however, most forecasting is coarse (monthly). We use environmental and Ross River virus (RRV) surveillance to predict weekly outbreak probabilities and incidence spanning tropical, semi-arid, and Mediterranean regions of Western Australia (1991-2014). Hurdle and linear models were used to predict outbreak probabilities and incidence respectively, using time-lagged environmental variables. Forecast accuracy was assessed by model fit and cross-validation. Residual RRV notification data were also examined against mitigation expenditure for one site, Mandurah 2007-2014. Models were predictive of RRV activity, except at one site (Capel). Minimum temperature was an important predictor of RRV outbreaks and incidence at all predicted sites. Precipitation was more likely to cause outbreaks and greater incidence among tropical and semi-arid sites. While variable, mitigation expenditure coincided positively with increased RRV incidence (r 2 = 0·21). Our research demonstrates capacity to accurately predict mosquito-borne disease outbreaks and incidence at fine-temporal resolutions. We apply our findings, developing a user-friendly tool enabling managers to easily adopt this research to forecast region-specific RRV outbreaks and incidence. Approaches here may be of value to fine-scale forecasting of RRV in other areas of Australia, and other mosquito-borne diseases.

Structural and functional predictors of regional peak pressures under the foot during walking.

PubMed

Morag, E; Cavanagh, P R

1999-04-01

The objective of this study was to identify structural and functional factors which are predictors of peak pressure underneath the human foot during walking. Peak plantar pressure during walking and eight data sets of structural and functional measures were collected on 55 asymptomatic subjects between 20 and 70 yr. A best subset regression approach was used to establish models which predicted peak regional pressure under the foot. Potential predictor variables were chosen from physical characteristics, anthropometric data, passive range of motion (PROM), measurements from standardized weight bearing foot radiographs, mechanical properties of the plantar soft tissue, stride parameters, foot motion in 3D, and EMG during walking. Peak pressure values under the rearfoot, midfoot, MTH1, and hallux were measured. Heel pressure was a function of linear kinematics, longitudinal arch structure, thickness of plantar soft tissue, and age. Midfoot pressure prediction was dominated by arch structure, while MTH1 pressure was a function of radiographic measurements, talo-crural joint motion, and gastrocnemius activity. Hallux pressure was a function of structural measures and MTP1 joint motion. Foot structure and function predicted only approximately 50% of the variance in peak pressure, although the relative contributions in different anatomical regions varied dramatically. Structure was dominant in predicting peak pressure under the midfoot and MTH1, while both structure and function were important at the heel and hallux. The predictive models developed in this study give insight into potential etiological factors associated with elevated plantar pressure. They also provide direction for future studies designed to reduce elevated pressure in "at-risk" patients.

Effects of biotic feedback and harvest management on boreal forest fire activity under climate change.

PubMed

Krawchuk, Meg A; Cumming, Steve G

2011-01-01

Predictions of future fire activity over Canada's boreal forests have primarily been generated from climate data following assumptions that direct effects of weather will stand alone in contributing to changes in burning. However, this assumption needs explicit testing. First, areas recently burned can be less likely to burn again in the near term, and this endogenous regulation suggests the potential for self-limiting, negative biotic feedback to regional climate-driven increases in fire. Second, forest harvest is ongoing, and resulting changes in vegetation structure have been shown to affect fire activity. Consequently, we tested the assumption that fire activity will be driven by changes in fire weather without regulation by biotic feedback or regional harvest-driven changes in vegetation structure in the mixedwood boreal forest of Alberta, Canada, using a simulation experiment that includes the interaction of fire, stand dynamics, climate change, and clear cut harvest management. We found that climate change projected with fire weather indices calculated from the Canadian Regional Climate Model increased fire activity, as expected, and our simulations established evidence that the magnitude of regional increase in fire was sufficient to generate negative feedback to subsequent fire activity. We illustrate a 39% (1.39-fold) increase in fire initiation and 47% (1.47-fold) increase in area burned when climate and stand dynamics were included in simulations, yet 48% (1.48-fold) and 61% (1.61-fold) increases, respectively, when climate was considered alone. Thus, although biotic feedbacks reduced burned area estimates in important ways, they were secondary to the direct effect of climate on fire. We then show that ongoing harvest management in this region changed landscape composition in a way that led to reduced fire activity, even in the context of climate change. Although forest harvesting resulted in decreased regional fire activity when compared to unharvested conditions, forest composition and age structure was shifted substantially, illustrating a trade-off between management goals to minimize fire and conservation goals to emulate natural disturbance.

Genome-Wide Locations of Potential Epimutations Associated with Environmentally Induced Epigenetic Transgenerational Inheritance of Disease Using a Sequential Machine Learning Prediction Approach.

PubMed

Haque, M Muksitul; Holder, Lawrence B; Skinner, Michael K

2015-01-01

Environmentally induced epigenetic transgenerational inheritance of disease and phenotypic variation involves germline transmitted epimutations. The primary epimutations identified involve altered differential DNA methylation regions (DMRs). Different environmental toxicants have been shown to promote exposure (i.e., toxicant) specific signatures of germline epimutations. Analysis of genomic features associated with these epimutations identified low-density CpG regions (<3 CpG / 100bp) termed CpG deserts and a number of unique DNA sequence motifs. The rat genome was annotated for these and additional relevant features. The objective of the current study was to use a machine learning computational approach to predict all potential epimutations in the genome. A number of previously identified sperm epimutations were used as training sets. A novel machine learning approach using a sequential combination of Active Learning and Imbalance Class Learner analysis was developed. The transgenerational sperm epimutation analysis identified approximately 50K individual sites with a 1 kb mean size and 3,233 regions that had a minimum of three adjacent sites with a mean size of 3.5 kb. A select number of the most relevant genomic features were identified with the low density CpG deserts being a critical genomic feature of the features selected. A similar independent analysis with transgenerational somatic cell epimutation training sets identified a smaller number of 1,503 regions of genome-wide predicted sites and differences in genomic feature contributions. The predicted genome-wide germline (sperm) epimutations were found to be distinct from the predicted somatic cell epimutations. Validation of the genome-wide germline predicted sites used two recently identified transgenerational sperm epimutation signature sets from the pesticides dichlorodiphenyltrichloroethane (DDT) and methoxychlor (MXC) exposure lineage F3 generation. Analysis of this positive validation data set showed a 100% prediction accuracy for all the DDT-MXC sperm epimutations. Observations further elucidate the genomic features associated with transgenerational germline epimutations and identify a genome-wide set of potential epimutations that can be used to facilitate identification of epigenetic diagnostics for ancestral environmental exposures and disease susceptibility.

Mentalizing about emotion and its relationship to empathy.

PubMed

Hooker, Christine I; Verosky, Sara C; Germine, Laura T; Knight, Robert T; D'Esposito, Mark

2008-09-01

Mentalizing involves the ability to predict someone else's behavior based on their belief state. More advanced mentalizing skills involve integrating knowledge about beliefs with knowledge about the emotional impact of those beliefs. Recent research indicates that advanced mentalizing skills may be related to the capacity to empathize with others. However, it is not clear what aspect of mentalizing is most related to empathy. In this study, we used a novel, advanced mentalizing task to identify neural mechanisms involved in predicting a future emotional response based on a belief state. Subjects viewed social scenes in which one character had a False Belief and one character had a True Belief. In the primary condition, subjects were asked to predict what emotion the False Belief Character would feel if they had a full understanding about the situation. We found that neural regions related to both mentalizing and emotion were involved when predicting a future emotional response, including the superior temporal sulcus, medial prefrontal cortex, temporal poles, somatosensory related cortices (SRC), inferior frontal gyrus and thalamus. In addition, greater neural activity in primarily emotion-related regions, including right SRC and bilateral thalamus, when predicting emotional response was significantly correlated with more self-reported empathy. The findings suggest that predicting emotional response involves generating and using internal affective representations and that greater use of these affective representations when trying to understand the emotional experience of others is related to more empathy.

Intraseasonal variability of the West African monsoon and African easterly waves during boreal summer

NASA Astrophysics Data System (ADS)

Alaka, Ghassan J., Jr.

Substantial subseasonal variability in African easterly wave (AEW) activity and cyclogenesis frequency occurs in the main hurricane development region of the Atlantic during boreal summer. A complete understanding of intraseasonal variability in the Atlantic and west Africa during boreal summer requires analysis of how the Madden-Julian Oscillation (MJO) modulates the west African monsoon and consequently AEWs. Because the MJO is predictable a few weeks in advance, understanding how and why the MJO impacts the west African monsoon may have a profound influence on Atlantic tropical cyclone prediction. This study documents the MJO influence on the west African monsoon system during boreal summer using a variety of reanalysis and satellite datasets. This study aims to identify and explain the MJO teleconnection to the west African monsoon, and the processes that induce precipitation and AEW variability in this region. Intraseasonal west African and Atlantic convective anomalies on 30-90 day timescales are likely induced by equatorial Kelvin and Rossby waves generated in the Indian Ocean and west Pacific by the MJO. Previous studies have hypothesized that an area including the Darfur mountains and the Ethiopian highlands is an initiation region for AEWs. It is shown here that the initial MJO influence on precipitation and AEW activity in the African monsoon appears to occur in these regions, where eddy kinetic energy (EKE) anomalies first appear in advance of MJO-induced periods of enhanced and suppressed AEW activity. In the initiation region, upper tropospheric temperature anomalies are reduced, the atmosphere moistens by horizontal advection, and an eastward extension of the African easterly jet occurs in advance of the MJO wet phase of the African monsoon, when AEW activity is also enhanced. These factors all support strong precursor disturbances in the initiation region that seed the African easterly jet and contribute to downstream development of AEWs. Opposite behavior occurs in advance of the MJO dry phase. Moisture and eddy kinetic energy (EKE) budgets are examined to provide further insight as to how the MJO modulates and initiates precipitation and AEW variability in this region. In particular, meridional moisture advection anomalies foster moistening in the initiation region by anomalous flow acting across the mean moisture gradient. Additionally, positive (negative) upstream EKE tendency anomalies in advance of the MJO convective maximum (minimum) over tropical north Africa suggest wave growth (decay) near the entrance of the AEJ, while enhanced (suppressed) conversion of eddy available potential energy (EAPE) to EKE and barotropic conversion maintains downstream AEW growth (decay).

Track-pattern-based seasonal prediction model for intense tropical cyclone activities over the North Atlantic and the western North Pacific basins

NASA Astrophysics Data System (ADS)

Choi, W.; Ho, C. H.

2015-12-01

Intense tropical cyclones (TCs) accompanying heavy rainfall and destructive wind gusts sometimes cause incredible socio-economic damages in the regions near their landfall. This study aims to analyze intense TC activities in the North Atlantic (NA) and the western North Pacific (WNP) basins and develop their track propensity seasonal prediction model. Considering that the number of TCs in the NA basin is much smaller than that in the WNP basin, different intensity criteria are used; category 1 and above for NA and category 3 and above for WNP based on Saffir-Simpson hurricane wind scale. By using a fuzzy clustering method, intense TC tracks in the NA and the WNP basins are classified into two and three representative patterns, respectively. Each pattern shows empirical relationships with climate variabilities such as sea surface temperature distribution associated with El Niño/La Niña or Atlantic Meridional Mode, Pacific decadal oscillation, upper and low level zonal wind, and strength of subtropical high. The hybrid statistical-dynamical method has been used to develop the seasonal prediction model for each pattern based on statistical relationships between the intense TC activity and seasonal averaged key predictors. The model performance is statistically assessed by cross validation for the training period (1982-2013) and has been applied for the 2014 and 2015 prediction. This study suggests applicability of this model to real prediction work and provide bridgehead of attempt for intense TC prediction.