Explicitly integrating parameter, input, and structure uncertainties into Bayesian Neural Networks for probabilistic hydrologic forecasting

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

Zhang, Xuesong; Liang, Faming; Yu, Beibei

2011-11-09

Estimating uncertainty of hydrologic forecasting is valuable to water resources and other relevant decision making processes. Recently, Bayesian Neural Networks (BNNs) have been proved powerful tools for quantifying uncertainty of streamflow forecasting. In this study, we propose a Markov Chain Monte Carlo (MCMC) framework to incorporate the uncertainties associated with input, model structure, and parameter into BNNs. This framework allows the structure of the neural networks to change by removing or adding connections between neurons and enables scaling of input data by using rainfall multipliers. The results show that the new BNNs outperform the BNNs that only consider uncertainties associatedmore » with parameter and model structure. Critical evaluation of posterior distribution of neural network weights, number of effective connections, rainfall multipliers, and hyper-parameters show that the assumptions held in our BNNs are not well supported. Further understanding of characteristics of different uncertainty sources and including output error into the MCMC framework are expected to enhance the application of neural networks for uncertainty analysis of hydrologic forecasting.« less

Dissociable attentional and affective circuits in medication-naïve children with attention-deficit/hyperactivity disorder.

PubMed

Posner, Jonathan; Rauh, Virginia; Gruber, Allison; Gat, Inbal; Wang, Zhishun; Peterson, Bradley S

2013-07-30

Current neurocognitive models of attention-deficit/hyperactivity disorder (ADHD) suggest that neural circuits involving both attentional and affective processing make independent contributions to the phenomenology of the disorder. However, a clear dissociation of attentional and affective circuits and their behavioral correlates has yet to be shown in medication-naïve children with ADHD. Using resting-state functional connectivity MRI (rs-fcMRI) in a cohort of medication naïve children with (N=22) and without (N=20) ADHD, we demonstrate that children with ADHD have reduced connectivity in two neural circuits: one underlying executive attention (EA) and the other emotional regulation (ER). We also demonstrate a double dissociation between these two neural circuits and their behavioral correlates such that reduced connectivity in the EA circuit correlates with executive attention deficits but not with emotional lability, while on the other hand, reduced connectivity in the ER circuit correlates with emotional lability but not with executive attention deficits. These findings suggest potential avenues for future research such as examining treatment effects on these two neural circuits as well as the potential prognostic and developmental significance of disturbances in one circuit vs the other. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Dissociative states in dreams and brain chaos: implications for creative awareness

PubMed Central

Bob, Petr; Louchakova, Olga

2015-01-01

This article reviews recent findings indicating some common brain processes during dissociative states and dreaming with the aim to outline a perspective that neural chaotic states during dreaming can be closely related to dissociative states that may manifest in dreams scenery. These data are in agreement with various clinical findings that dissociated states can be projected into the “dream scenery” in REM sleep periods and dreams may represent their specific interactions that may uncover unusual psychological potential of creativity in psychotherapy, art, and scientific discoveries. PMID:26441729

Introduction to Papers from the 5th Workshop on Language Production: The Neural Bases of Language Production

ERIC Educational Resources Information Center

Rapp, Brenda; Miozzo, Michele

2011-01-01

The papers in this special issue of "Language and Cognitive Processing" on the neural bases of language production illustrate two general approaches in current cognitive neuroscience. One approach focuses on investigating cognitive issues, making use of the logic of associations/dissociations or the logic of neural markers as key investigative…

Executive-Attentional Uncertainty Responses by Rhesus Macaques ("Macaca mulatta")

ERIC Educational Resources Information Center

Smith, J. David; Coutinho, Mariana V. C.; Church, Barbara A.; Beran, Michael J.

2013-01-01

The uncertainty response has been influential in studies of human perception, and it is crucial in the growing research literature that explores animal metacognition. However, the uncertainty response's interpretation is still sharply debated. The authors sought to clarify this interpretation using the dissociative technique of cognitive loads…

Increased binding of 5-HT1A receptors in a dissociative amnesic patient after the recovery process.

PubMed

Kitamura, Soichiro; Yasuno, Fumihiko; Inoue, Makoto; Kosaka, Jun; Kiuchi, Kuniaki; Matsuoka, Kiwamu; Kishimoto, Toshifumi; Suhara, Tetsuya

2014-10-30

Dissociative amnesia is characterized by an inability to retrieve information already saved in memories. 5-HT has some role in neural regulatory control and may be related to the recovery from dissociative amnesia. To examine the role of 5-HT1A receptors in the recovery from dissociative amnesia, we performed two positron emission tomography (PET) scans on a 30-year-old patient of dissociative amnesia using [(11)C]WAY-100635, the first at amnesic state, and the second at the time he had recovered. Exploratory voxel-based analysis (VBA) was performed using SPM software. 5-HT1A BPND images were compared between the patient at amnesic and recovery states and healthy subjects (14 males, mean age 29.8 ± 6.45) with Jack-knife analysis. 5-HT1A receptor bindings of the patient at the recovery state were significantly higher than those of healthy subjects in the right superior and middle frontal cortex, left inferior frontal and orbitofrontal cortex and bilateral inferior temporal cortex. The increase in BPND values of recovery state was beyond 10% of those of amnesia state in these regions except in the right superior frontal cortex. We considered that neural regulatory control by the increase of 5-HT1A receptors in cortical regions played a role in the recovery from dissociative amnesia. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Six-dimensional quantum dynamics study for the dissociative adsorption of HCl on Au(111) surface

NASA Astrophysics Data System (ADS)

Liu, Tianhui; Fu, Bina; Zhang, Dong H.

2013-11-01

The six-dimensional quantum dynamics calculations for the dissociative chemisorption of HCl on Au(111) are carried out using the time-dependent wave-packet approach, based on an accurate PES which was recently developed by neural network fitting to density functional theory energy points. The influence of vibrational excitation and rotational orientation of HCl on the reactivity is investigated by calculating the exact six-dimensional dissociation probabilities, as well as the four-dimensional fixed-site dissociation probabilities. The vibrational excitation of HCl enhances the reactivity and the helicopter orientation yields higher dissociation probability than the cartwheel orientation. A new interesting site-averaged effect is found for the title molecule-surface system that one can essentially reproduce the six-dimensional dissociation probability by averaging the four-dimensional dissociation probabilities over 25 fixed sites.

Artificial neural network modelling of uncertainty in gamma-ray spectrometry

NASA Astrophysics Data System (ADS)

Dragović, S.; Onjia, A.; Stanković, S.; Aničin, I.; Bačić, G.

2005-03-01

An artificial neural network (ANN) model for the prediction of measuring uncertainties in gamma-ray spectrometry was developed and optimized. A three-layer feed-forward ANN with back-propagation learning algorithm was used to model uncertainties of measurement of activity levels of eight radionuclides ( 226Ra, 238U, 235U, 40K, 232Th, 134Cs, 137Cs and 7Be) in soil samples as a function of measurement time. It was shown that the neural network provides useful data even from small experimental databases. The performance of the optimized neural network was found to be very good, with correlation coefficients ( R2) between measured and predicted uncertainties ranging from 0.9050 to 0.9915. The correlation coefficients did not significantly deteriorate when the network was tested on samples with greatly different uranium-to-thorium ( 238U/ 232Th) ratios. The differences between measured and predicted uncertainties were not influenced by the absolute values of uncertainties of measured radionuclide activities. Once the ANN is trained, it could be employed in analyzing soil samples regardless of the 238U/ 232Th ratio. It was concluded that a considerable saving in time could be obtained using the trained neural network model for predicting the measurement times needed to attain the desired statistical accuracy.

[On the necessity to distinguishing judgment from subjective choice in the cognitive neuroscience of morality].

PubMed

Tassy, Sébastien

2011-10-01

Recently, cognitive neuroscience has shed new light on our understanding of the neural underpinning of humans' morality. These findings allow for a fundamental questioning and rethinking of the alleged dichotomy between reason and emotion, that has profoundly shaped both moral philosophy and moral psychology. Functional neuroimaging and neuropsychology studies have provided strong arguments favoring a dynamic and interdependent interaction between rational and emotional processes in the brain. Yet another fundamental issue remains largely unexplored: the dissociation between certain behaviours and the moral judgments that seem to precede them. The importance of this dissociation was highlighted in a study of psychopathic patients during which they preserved their moral judgments while frequently engaging in completely non moral behaviour. Such dissociation could result from the cognitive difference between an objective moral judgement with no personal consequence, and a subjective behavioural choice that has effective or potential personal consequences. Consequently, the results of moral dilemma experiments would differ widely depending whether they explore objective or subjective moral evaluations. That these evaluations involve two distinct neural processes should be taken into account when exploring the neural bases of human morality. © 2011 médecine/sciences – Inserm / SRMS.

Prediction and uncertainty in human Pavlovian to instrumental transfer.

PubMed

Trick, Leanne; Hogarth, Lee; Duka, Theodora

2011-05-01

Attentional capture and behavioral control by conditioned stimuli have been dissociated in animals. The current study assessed this dissociation in humans. Participants were trained on a Pavlovian schedule in which 3 visual stimuli, A, B, and C, predicted the occurrence of an aversive noise with 90%, 50%, or 10% probability, respectively. Participants then went on to separate instrumental training in which a key-press response canceled the aversive noise with a .5 probability on a variable interval schedule. Finally, in the transfer phase, the 3 Pavlovian stimuli were presented in this instrumental schedule and were no longer differentially predictive of the outcome. Observing times and gaze dwell time indexed attention to these stimuli in both training and transfer. Aware participants acquired veridical outcome expectancies in training--that is, A > B > C, and these expectancies persisted into transfer. Most important, the transfer effect accorded with these expectancies, A > B > C. By contrast, observing times accorded with uncertainty--that is, they showed B > A = C during training, and B < A = C in the transfer phase. Dwell time bias supported this association between attention and uncertainty, although these data showed a slightly more complicated pattern. Overall, the study suggests that transfer is linked to outcome prediction and is dissociated from attention to conditioned stimuli, which is linked to outcome uncertainty.

Memory repression: brain mechanisms underlying dissociative amnesia.

PubMed

Kikuchi, Hirokazu; Fujii, Toshikatsu; Abe, Nobuhito; Suzuki, Maki; Takagi, Masahito; Mugikura, Shunji; Takahashi, Shoki; Mori, Etsuro

2010-03-01

Dissociative amnesia usually follows a stressful event and cannot be attributable to explicit brain damage. It is thought to reflect a reversible deficit in memory retrieval probably due to memory repression. However, the neural mechanisms underlying this condition are not clear. We used fMRI to investigate neural activity associated with memory retrieval in two patients with dissociative amnesia. For each patient, three categories of face photographs and three categories of people's names corresponding to the photographs were prepared: those of "recognizable" high school friends who were acquainted with and recognizable to the patients, those of "unrecognizable" colleagues who were actually acquainted with but unrecognizable to the patients due to their memory impairments, and "control" distracters who were unacquainted with the patients. During fMRI, the patients were visually presented with these stimuli and asked to indicate whether they were personally acquainted with them. In the comparison of the unrecognizable condition with the recognizable condition, we found increased activity in the pFC and decreased activity in the hippocampus in both patients. After treatment for retrograde amnesia, the altered pattern of brain activation disappeared in one patient whose retrograde memories were recovered, whereas it remained unchanged in the other patient whose retrograde memories were not recovered. Our findings provide direct evidence that memory repression in dissociative amnesia is associated with an altered pattern of neural activity, and they suggest the possibility that the pFC has an important role in inhibiting the activity of the hippocampus in memory repression.

Dissociation of Subtraction and Multiplication in the Right Parietal Cortex: Evidence from Intraoperative Cortical Electrostimulation

ERIC Educational Resources Information Center

Yu, Xiaodan; Chen, Chuansheng; Pu, Song; Wu, Chenxing; Li, Yongnian; Jiang, Tao; Zhou, Xinlin

2011-01-01

Previous research has consistently shown that the left parietal cortex is critical for numerical processing, but the role of the right parietal lobe has been much less clear. This study used the intraoperative cortical electrical stimulation approach to investigate neural dissociation in the right parietal cortex for subtraction and…

Six-dimensional quantum dynamics study for the dissociative adsorption of HCl on Au(111) surface

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

Liu, Tianhui; Fu, Bina; Zhang, Dong H., E-mail: zhangdh@dicp.ac.cn

The six-dimensional quantum dynamics calculations for the dissociative chemisorption of HCl on Au(111) are carried out using the time-dependent wave-packet approach, based on an accurate PES which was recently developed by neural network fitting to density functional theory energy points. The influence of vibrational excitation and rotational orientation of HCl on the reactivity is investigated by calculating the exact six-dimensional dissociation probabilities, as well as the four-dimensional fixed-site dissociation probabilities. The vibrational excitation of HCl enhances the reactivity and the helicopter orientation yields higher dissociation probability than the cartwheel orientation. A new interesting site-averaged effect is found for the titlemore » molecule-surface system that one can essentially reproduce the six-dimensional dissociation probability by averaging the four-dimensional dissociation probabilities over 25 fixed sites.« less

Functional dissociations in top-down control dependent neural repetition priming.

PubMed

Klaver, Peter; Schnaidt, Malte; Fell, Jürgen; Ruhlmann, Jürgen; Elger, Christian E; Fernández, Guillén

2007-02-15

Little is known about the neural mechanisms underlying top-down control of repetition priming. Here, we use functional brain imaging to investigate these mechanisms. Study and repetition tasks used a natural/man-made forced choice task. In the study phase subjects were required to respond to either pictures or words that were presented superimposed on each other. In the repetition phase only words were presented that were new, previously attended or ignored, or picture names that were derived from previously attended or ignored pictures. Relative to new words we found repetition priming for previously attended words. Previously ignored words showed a reduced priming effect, and there was no significant priming for pictures repeated as picture names. Brain imaging data showed that neural priming of words in the left prefrontal cortex (LIPFC) and left fusiform gyrus (LOTC) was affected by attention, semantic compatibility of superimposed stimuli during study and cross-modal priming. Neural priming reduced for words in the LIPFC and for words and pictures in the LOTC if stimuli were previously ignored. Previously ignored words that were semantically incompatible with a superimposed picture during study induce increased neural priming compared to semantically compatible ignored words (LIPFC) and decreased neural priming of previously attended pictures (LOTC). In summary, top-down control induces dissociable effects on neural priming by attention, cross-modal priming and semantic compatibility in a way that was not evident from behavioral results.

Uncertainties in Parameters Estimated with Neural Networks: Application to Strong Gravitational Lensing

DOE PAGES

Perreault Levasseur, Laurence; Hezaveh, Yashar D.; Wechsler, Risa H.

2017-11-15

In Hezaveh et al. (2017) we showed that deep learning can be used for model parameter estimation and trained convolutional neural networks to determine the parameters of strong gravitational lensing systems. Here we demonstrate a method for obtaining the uncertainties of these parameters. We review the framework of variational inference to obtain approximate posteriors of Bayesian neural networks and apply it to a network trained to estimate the parameters of the Singular Isothermal Ellipsoid plus external shear and total flux magnification. We show that the method can capture the uncertainties due to different levels of noise in the input data,more » as well as training and architecture-related errors made by the network. To evaluate the accuracy of the resulting uncertainties, we calculate the coverage probabilities of marginalized distributions for each lensing parameter. By tuning a single hyperparameter, the dropout rate, we obtain coverage probabilities approximately equal to the confidence levels for which they were calculated, resulting in accurate and precise uncertainty estimates. Our results suggest that neural networks can be a fast alternative to Monte Carlo Markov Chains for parameter uncertainty estimation in many practical applications, allowing more than seven orders of magnitude improvement in speed.« less

Uncertainties in Parameters Estimated with Neural Networks: Application to Strong Gravitational Lensing

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

Perreault Levasseur, Laurence; Hezaveh, Yashar D.; Wechsler, Risa H.

In Hezaveh et al. (2017) we showed that deep learning can be used for model parameter estimation and trained convolutional neural networks to determine the parameters of strong gravitational lensing systems. Here we demonstrate a method for obtaining the uncertainties of these parameters. We review the framework of variational inference to obtain approximate posteriors of Bayesian neural networks and apply it to a network trained to estimate the parameters of the Singular Isothermal Ellipsoid plus external shear and total flux magnification. We show that the method can capture the uncertainties due to different levels of noise in the input data,more » as well as training and architecture-related errors made by the network. To evaluate the accuracy of the resulting uncertainties, we calculate the coverage probabilities of marginalized distributions for each lensing parameter. By tuning a single hyperparameter, the dropout rate, we obtain coverage probabilities approximately equal to the confidence levels for which they were calculated, resulting in accurate and precise uncertainty estimates. Our results suggest that neural networks can be a fast alternative to Monte Carlo Markov Chains for parameter uncertainty estimation in many practical applications, allowing more than seven orders of magnitude improvement in speed.« less

Dissociating sensory from decision processes in human perceptual decision making.

PubMed

Mostert, Pim; Kok, Peter; de Lange, Floris P

2015-12-15

A key question within systems neuroscience is how the brain translates physical stimulation into a behavioral response: perceptual decision making. To answer this question, it is important to dissociate the neural activity underlying the encoding of sensory information from the activity underlying the subsequent temporal integration into a decision variable. Here, we adopted a decoding approach to empirically assess this dissociation in human magnetoencephalography recordings. We used a functional localizer to identify the neural signature that reflects sensory-specific processes, and subsequently traced this signature while subjects were engaged in a perceptual decision making task. Our results revealed a temporal dissociation in which sensory processing was limited to an early time window and consistent with occipital areas, whereas decision-related processing became increasingly pronounced over time, and involved parietal and frontal areas. We found that the sensory processing accurately reflected the physical stimulus, irrespective of the eventual decision. Moreover, the sensory representation was stable and maintained over time when it was required for a subsequent decision, but unstable and variable over time when it was task-irrelevant. In contrast, decision-related activity displayed long-lasting sustained components. Together, our approach dissects neuro-anatomically and functionally distinct contributions to perceptual decisions.

Dissociating sensory from decision processes in human perceptual decision making

PubMed Central

Mostert, Pim; Kok, Peter; de Lange, Floris P.

2015-01-01

A key question within systems neuroscience is how the brain translates physical stimulation into a behavioral response: perceptual decision making. To answer this question, it is important to dissociate the neural activity underlying the encoding of sensory information from the activity underlying the subsequent temporal integration into a decision variable. Here, we adopted a decoding approach to empirically assess this dissociation in human magnetoencephalography recordings. We used a functional localizer to identify the neural signature that reflects sensory-specific processes, and subsequently traced this signature while subjects were engaged in a perceptual decision making task. Our results revealed a temporal dissociation in which sensory processing was limited to an early time window and consistent with occipital areas, whereas decision-related processing became increasingly pronounced over time, and involved parietal and frontal areas. We found that the sensory processing accurately reflected the physical stimulus, irrespective of the eventual decision. Moreover, the sensory representation was stable and maintained over time when it was required for a subsequent decision, but unstable and variable over time when it was task-irrelevant. In contrast, decision-related activity displayed long-lasting sustained components. Together, our approach dissects neuro-anatomically and functionally distinct contributions to perceptual decisions. PMID:26666393

Prediction and Uncertainty in Human Pavlovian to Instrumental Transfer

ERIC Educational Resources Information Center

Trick, Leanne; Hogarth, Lee; Duka, Theodora

2011-01-01

Attentional capture and behavioral control by conditioned stimuli have been dissociated in animals. The current study assessed this dissociation in humans. Participants were trained on a Pavlovian schedule in which 3 visual stimuli, A, B, and C, predicted the occurrence of an aversive noise with 90%, 50%, or 10% probability, respectively.…

Dissociable Patterns of Neural Activity during Response Inhibition in Depressed Adolescents with and without Suicidal Behavior

ERIC Educational Resources Information Center

Pan, Lisa A.; Batezati-Alves, Silvia C.; Almeida, Jorge R. C.; Segreti, AnnaMaria; Akkal, Dalila; Hassel, Stefanie; Lakdawala, Sara; Brent, David A.; Phillips, Mary L.

2011-01-01

Objectives: Impaired attentional control and behavioral control are implicated in adult suicidal behavior. Little is known about the functional integrity of neural circuitry supporting these processes in suicidal behavior in adolescence. Method: Functional magnetic resonance imaging was used in 15 adolescent suicide attempters with a history of…

pDeep: Predicting MS/MS Spectra of Peptides with Deep Learning.

PubMed

Zhou, Xie-Xuan; Zeng, Wen-Feng; Chi, Hao; Luo, Chunjie; Liu, Chao; Zhan, Jianfeng; He, Si-Min; Zhang, Zhifei

2017-12-05

In tandem mass spectrometry (MS/MS)-based proteomics, search engines rely on comparison between an experimental MS/MS spectrum and the theoretical spectra of the candidate peptides. Hence, accurate prediction of the theoretical spectra of peptides appears to be particularly important. Here, we present pDeep, a deep neural network-based model for the spectrum prediction of peptides. Using the bidirectional long short-term memory (BiLSTM), pDeep can predict higher-energy collisional dissociation, electron-transfer dissociation, and electron-transfer and higher-energy collision dissociation MS/MS spectra of peptides with >0.9 median Pearson correlation coefficients. Further, we showed that intermediate layer of the neural network could reveal physicochemical properties of amino acids, for example the similarities of fragmentation behaviors between amino acids. We also showed the potential of pDeep to distinguish extremely similar peptides (peptides that contain isobaric amino acids, for example, GG = N, AG = Q, or even I = L), which were very difficult to distinguish using traditional search engines.

The Dissociative Subtype of Post-traumatic Stress Disorder: Research Update on Clinical and Neurobiological Features.

PubMed

van Huijstee, Jytte; Vermetten, Eric

2017-10-21

Recently, a dissociative subtype of post-traumatic stress disorder (PTSD) has been included in the DSM-5. This review focuses on the clinical and neurobiological features that distinguish the dissociative subtype of PTSD from non-dissociative PTSD. Clinically, the dissociative subtype of PTSD is associated with high PTSD severity, predominance of derealization and depersonalization symptoms, a more significant history of early life trauma, and higher levels of comorbid psychiatric disorders. Furthermore, PTSD patients with dissociative symptoms exhibit different psychophysiological and neural responses to the recall of traumatic memories. While individuals with non-dissociative PTSD exhibit an increased heart rate, decreased activation of prefrontal regions, and increased activation of the amygdala in response to traumatic reminders, individuals with the dissociative subtype of PTSD show an opposite pattern. It has been proposed that dissociation is a regulatory strategy to restrain extreme arousal in PTSD through hyperinhibition of limbic regions. In this research update, promises and pitfalls in current research studies on the dissociative subtype of PTSD are listed. Inclusion of the dissociative subtype of PTSD in the DSM-5 stimulates research on the prevalence, symptomatology, and neurobiology of the dissociative subtype of PTSD and poses a challenge to improve treatment outcome in PTSD patients with dissociative symptoms.

Dissociation of the Neural Correlates of Visual and Auditory Contextual Encoding

ERIC Educational Resources Information Center

Gottlieb, Lauren J.; Uncapher, Melina R.; Rugg, Michael D.

2010-01-01

The present study contrasted the neural correlates of encoding item-context associations according to whether the contextual information was visual or auditory. Subjects (N = 20) underwent fMRI scanning while studying a series of visually presented pictures, each of which co-occurred with either a visually or an auditorily presented name. The task…

Neural Signatures of Number Processing in Human Infants: Evidence for Two Core Systems Underlying Numerical Cognition

ERIC Educational Resources Information Center

Hyde, Daniel C.; Spelke, Elizabeth S.

2011-01-01

Behavioral research suggests that two cognitive systems are at the foundations of numerical thinking: one for representing 1-3 objects in parallel and one for representing and comparing large, approximate numerical magnitudes. We tested for dissociable neural signatures of these systems in preverbal infants by recording event-related potentials…

Critical Neural Substrates for Correcting Unexpected Trajectory Errors and Learning from Them

ERIC Educational Resources Information Center

Mutha, Pratik K.; Sainburg, Robert L.; Haaland, Kathleen Y.

2011-01-01

Our proficiency at any skill is critically dependent on the ability to monitor our performance, correct errors and adapt subsequent movements so that errors are avoided in the future. In this study, we aimed to dissociate the neural substrates critical for correcting unexpected trajectory errors and learning to adapt future movements based on…

Associating Neural Alterations and Genotype in Autism and Fragile X Syndrome: Incorporating Perceptual Phenotypes in Causal Modeling

ERIC Educational Resources Information Center

Bertone, Armando; Hanck, Julie; Kogan, Cary; Chaudhuri, Avi; Cornish, Kim

2010-01-01

We have previously described (see companion paper, this issue) the utility of using perceptual signatures for defining and dissociating condition-specific neural functioning underlying early visual processes in autism and FXS. These perceptually-driven hypotheses are based on differential performance evidenced only at the earliest stages of visual…

Thought beyond language: neural dissociation of algebra and natural language.

PubMed

Monti, Martin M; Parsons, Lawrence M; Osherson, Daniel N

2012-08-01

A central question in cognitive science is whether natural language provides combinatorial operations that are essential to diverse domains of thought. In the study reported here, we addressed this issue by examining the role of linguistic mechanisms in forging the hierarchical structures of algebra. In a 3-T functional MRI experiment, we showed that processing of the syntax-like operations of algebra does not rely on the neural mechanisms of natural language. Our findings indicate that processing the syntax of language elicits the known substrate of linguistic competence, whereas algebraic operations recruit bilateral parietal brain regions previously implicated in the representation of magnitude. This double dissociation argues against the view that language provides the structure of thought across all cognitive domains.

Six-dimensional quantum dynamics study for the dissociative adsorption of DCl on Au(111) surface

NASA Astrophysics Data System (ADS)

Liu, Tianhui; Fu, Bina; Zhang, Dong H.

2014-04-01

We carried out six-dimensional quantum dynamics calculations for the dissociative adsorption of deuterium chloride (DCl) on Au(111) surface using the initial state-selected time-dependent wave packet approach. The four-dimensional dissociation probabilities are also obtained with the center of mass of DCl fixed at various sites. These calculations were all performed based on an accurate potential energy surface recently constructed by neural network fitting to density function theory energy points. The origin of the extremely small dissociation probability for DCl/HCl (v = 0, j = 0) fixed at the top site compared to other fixed sites is elucidated in this study. The influence of vibrational excitation and rotational orientation of DCl on the reactivity was investigated by calculating six-dimensional dissociation probabilities. The vibrational excitation of DCl enhances the reactivity substantially and the helicopter orientation yields higher dissociation probability than the cartwheel orientation. The site-averaged dissociation probability over 25 fixed sites obtained from four-dimensional quantum dynamics calculations can accurately reproduce the six-dimensional dissociation probability.

Six-dimensional quantum dynamics study for the dissociative adsorption of DCl on Au(111) surface

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

Liu, Tianhui; Fu, Bina, E-mail: bina@dicp.ac.cn, E-mail: zhangdh@dicp.ac.cn; Zhang, Dong H., E-mail: bina@dicp.ac.cn, E-mail: zhangdh@dicp.ac.cn

We carried out six-dimensional quantum dynamics calculations for the dissociative adsorption of deuterium chloride (DCl) on Au(111) surface using the initial state-selected time-dependent wave packet approach. The four-dimensional dissociation probabilities are also obtained with the center of mass of DCl fixed at various sites. These calculations were all performed based on an accurate potential energy surface recently constructed by neural network fitting to density function theory energy points. The origin of the extremely small dissociation probability for DCl/HCl (v = 0, j = 0) fixed at the top site compared to other fixed sites is elucidated in this study. The influence of vibrational excitationmore » and rotational orientation of DCl on the reactivity was investigated by calculating six-dimensional dissociation probabilities. The vibrational excitation of DCl enhances the reactivity substantially and the helicopter orientation yields higher dissociation probability than the cartwheel orientation. The site-averaged dissociation probability over 25 fixed sites obtained from four-dimensional quantum dynamics calculations can accurately reproduce the six-dimensional dissociation probability.« less

Dissociable neural response signatures for slow amplitude and frequency modulation in human auditory cortex.

PubMed

Henry, Molly J; Obleser, Jonas

2013-01-01

Natural auditory stimuli are characterized by slow fluctuations in amplitude and frequency. However, the degree to which the neural responses to slow amplitude modulation (AM) and frequency modulation (FM) are capable of conveying independent time-varying information, particularly with respect to speech communication, is unclear. In the current electroencephalography (EEG) study, participants listened to amplitude- and frequency-modulated narrow-band noises with a 3-Hz modulation rate, and the resulting neural responses were compared. Spectral analyses revealed similar spectral amplitude peaks for AM and FM at the stimulation frequency (3 Hz), but amplitude at the second harmonic frequency (6 Hz) was much higher for FM than for AM. Moreover, the phase delay of neural responses with respect to the full-band stimulus envelope was shorter for FM than for AM. Finally, the critical analysis involved classification of single trials as being in response to either AM or FM based on either phase or amplitude information. Time-varying phase, but not amplitude, was sufficient to accurately classify AM and FM stimuli based on single-trial neural responses. Taken together, the current results support the dissociable nature of cortical signatures of slow AM and FM. These cortical signatures potentially provide an efficient means to dissect simultaneously communicated slow temporal and spectral information in acoustic communication signals.

Dissociable Neural Response Signatures for Slow Amplitude and Frequency Modulation in Human Auditory Cortex

PubMed Central

Henry, Molly J.; Obleser, Jonas

2013-01-01

Natural auditory stimuli are characterized by slow fluctuations in amplitude and frequency. However, the degree to which the neural responses to slow amplitude modulation (AM) and frequency modulation (FM) are capable of conveying independent time-varying information, particularly with respect to speech communication, is unclear. In the current electroencephalography (EEG) study, participants listened to amplitude- and frequency-modulated narrow-band noises with a 3-Hz modulation rate, and the resulting neural responses were compared. Spectral analyses revealed similar spectral amplitude peaks for AM and FM at the stimulation frequency (3 Hz), but amplitude at the second harmonic frequency (6 Hz) was much higher for FM than for AM. Moreover, the phase delay of neural responses with respect to the full-band stimulus envelope was shorter for FM than for AM. Finally, the critical analysis involved classification of single trials as being in response to either AM or FM based on either phase or amplitude information. Time-varying phase, but not amplitude, was sufficient to accurately classify AM and FM stimuli based on single-trial neural responses. Taken together, the current results support the dissociable nature of cortical signatures of slow AM and FM. These cortical signatures potentially provide an efficient means to dissect simultaneously communicated slow temporal and spectral information in acoustic communication signals. PMID:24205309

Perceptual learning of degraded speech by minimizing prediction error.

PubMed

Sohoglu, Ediz; Davis, Matthew H

2016-03-22

Human perception is shaped by past experience on multiple timescales. Sudden and dramatic changes in perception occur when prior knowledge or expectations match stimulus content. These immediate effects contrast with the longer-term, more gradual improvements that are characteristic of perceptual learning. Despite extensive investigation of these two experience-dependent phenomena, there is considerable debate about whether they result from common or dissociable neural mechanisms. Here we test single- and dual-mechanism accounts of experience-dependent changes in perception using concurrent magnetoencephalographic and EEG recordings of neural responses evoked by degraded speech. When speech clarity was enhanced by prior knowledge obtained from matching text, we observed reduced neural activity in a peri-auditory region of the superior temporal gyrus (STG). Critically, longer-term improvements in the accuracy of speech recognition following perceptual learning resulted in reduced activity in a nearly identical STG region. Moreover, short-term neural changes caused by prior knowledge and longer-term neural changes arising from perceptual learning were correlated across subjects with the magnitude of learning-induced changes in recognition accuracy. These experience-dependent effects on neural processing could be dissociated from the neural effect of hearing physically clearer speech, which similarly enhanced perception but increased rather than decreased STG responses. Hence, the observed neural effects of prior knowledge and perceptual learning cannot be attributed to epiphenomenal changes in listening effort that accompany enhanced perception. Instead, our results support a predictive coding account of speech perception; computational simulations show how a single mechanism, minimization of prediction error, can drive immediate perceptual effects of prior knowledge and longer-term perceptual learning of degraded speech.

Perceptual learning of degraded speech by minimizing prediction error

PubMed Central

Sohoglu, Ediz

2016-01-01

Human perception is shaped by past experience on multiple timescales. Sudden and dramatic changes in perception occur when prior knowledge or expectations match stimulus content. These immediate effects contrast with the longer-term, more gradual improvements that are characteristic of perceptual learning. Despite extensive investigation of these two experience-dependent phenomena, there is considerable debate about whether they result from common or dissociable neural mechanisms. Here we test single- and dual-mechanism accounts of experience-dependent changes in perception using concurrent magnetoencephalographic and EEG recordings of neural responses evoked by degraded speech. When speech clarity was enhanced by prior knowledge obtained from matching text, we observed reduced neural activity in a peri-auditory region of the superior temporal gyrus (STG). Critically, longer-term improvements in the accuracy of speech recognition following perceptual learning resulted in reduced activity in a nearly identical STG region. Moreover, short-term neural changes caused by prior knowledge and longer-term neural changes arising from perceptual learning were correlated across subjects with the magnitude of learning-induced changes in recognition accuracy. These experience-dependent effects on neural processing could be dissociated from the neural effect of hearing physically clearer speech, which similarly enhanced perception but increased rather than decreased STG responses. Hence, the observed neural effects of prior knowledge and perceptual learning cannot be attributed to epiphenomenal changes in listening effort that accompany enhanced perception. Instead, our results support a predictive coding account of speech perception; computational simulations show how a single mechanism, minimization of prediction error, can drive immediate perceptual effects of prior knowledge and longer-term perceptual learning of degraded speech. PMID:26957596

Uncertainties in Parameters Estimated with Neural Networks: Application to Strong Gravitational Lensing

NASA Astrophysics Data System (ADS)

Perreault Levasseur, Laurence; Hezaveh, Yashar D.; Wechsler, Risa H.

2017-11-01

In Hezaveh et al. we showed that deep learning can be used for model parameter estimation and trained convolutional neural networks to determine the parameters of strong gravitational-lensing systems. Here we demonstrate a method for obtaining the uncertainties of these parameters. We review the framework of variational inference to obtain approximate posteriors of Bayesian neural networks and apply it to a network trained to estimate the parameters of the Singular Isothermal Ellipsoid plus external shear and total flux magnification. We show that the method can capture the uncertainties due to different levels of noise in the input data, as well as training and architecture-related errors made by the network. To evaluate the accuracy of the resulting uncertainties, we calculate the coverage probabilities of marginalized distributions for each lensing parameter. By tuning a single variational parameter, the dropout rate, we obtain coverage probabilities approximately equal to the confidence levels for which they were calculated, resulting in accurate and precise uncertainty estimates. Our results suggest that the application of approximate Bayesian neural networks to astrophysical modeling problems can be a fast alternative to Monte Carlo Markov Chains, allowing orders of magnitude improvement in speed.

Dissociating movement from movement timing in the rat primary motor cortex.

PubMed

Knudsen, Eric B; Powers, Marissa E; Moxon, Karen A

2014-11-19

Neural encoding of the passage of time to produce temporally precise movements remains an open question. Neurons in several brain regions across different experimental contexts encode estimates of temporal intervals by scaling their activity in proportion to the interval duration. In motor cortex the degree to which this scaled activity relies upon afferent feedback and is guided by motor output remains unclear. Using a neural reward paradigm to dissociate neural activity from motor output before and after complete spinal transection, we show that temporally scaled activity occurs in the rat hindlimb motor cortex in the absence of motor output and after transection. Context-dependent changes in the encoding are plastic, reversible, and re-established following injury. Therefore, in the absence of motor output and despite a loss of afferent feedback, thought necessary for timed movements, the rat motor cortex displays scaled activity during a broad range of temporally demanding tasks similar to that identified in other brain regions. Copyright © 2014 the authors 0270-6474/14/3415576-11$15.00/0.

Dissociable neural systems underwrite logical reasoning in the context of induced emotions with positive and negative valence.

PubMed

Smith, Kathleen W; Vartanian, Oshin; Goel, Vinod

2014-01-01

How emotions influence syllogistic reasoning is not well understood. fMRI was employed to investigate the effects of induced positive or negative emotion on syllogistic reasoning. Specifically, on a trial-by-trial basis participants were exposed to a positive, negative, or neutral picture, immediately prior to engagement in a reasoning task. After viewing and rating the valence and intensity of each picture, participants indicated by keypress whether or not the conclusion of the syllogism followed logically from the premises. The content of all syllogisms was neutral, and the influence of belief-bias was controlled for in the study design. Emotion did not affect reasoning performance, although there was a trend in the expected direction based on accuracy rates for the positive (63%) and negative (64%) versus neutral (70%) condition. Nevertheless, exposure to positive and negative pictures led to dissociable patterns of neural activation during reasoning. Therefore, the neural basis of deductive reasoning differs as a function of the valence of the context.

Dissociable Neural Systems Underwrite Logical Reasoning in the Context of Induced Emotions with Positive and Negative Valence

PubMed Central

Smith, Kathleen W.; Vartanian, Oshin; Goel, Vinod

2014-01-01

How emotions influence syllogistic reasoning is not well understood. fMRI was employed to investigate the effects of induced positive or negative emotion on syllogistic reasoning. Specifically, on a trial-by-trial basis participants were exposed to a positive, negative, or neutral picture, immediately prior to engagement in a reasoning task. After viewing and rating the valence and intensity of each picture, participants indicated by keypress whether or not the conclusion of the syllogism followed logically from the premises. The content of all syllogisms was neutral, and the influence of belief-bias was controlled for in the study design. Emotion did not affect reasoning performance, although there was a trend in the expected direction based on accuracy rates for the positive (63%) and negative (64%) versus neutral (70%) condition. Nevertheless, exposure to positive and negative pictures led to dissociable patterns of neural activation during reasoning. Therefore, the neural basis of deductive reasoning differs as a function of the valence of the context. PMID:25294997

Words, Hemispheres, and Dissociable Subsystems: The Effects of Exposure Duration, Case Alternation, Priming, and Continuity of Form on Word Recognition in the Left and Right Visual Fields

ERIC Educational Resources Information Center

Ellis, Andrew W.; Ansorge, Lydia; Lavidor, Michal

2007-01-01

Three experiments explore aspects of the dissociable neural subsystems theory of hemispheric specialisation proposed by Marsolek and colleagues, and in particular a study by [Deason, R. G., & Marsolek, C. J. (2005). A critical boundary to the left-hemisphere advantage in word processing. "Brain and Language," 92, 251-261]. Experiment 1A showed…

Dissociable Frontostriatal White Matter Connectivity Underlies Reward and Motor Impulsivity

PubMed Central

Hampton, William H.; Alm, Kylie H.; Venkatraman, Vinod; Nugiel, Tehila; Olson, Ingrid R.

2017-01-01

Dysfunction of cognitive control often leads to impulsive decision-making in clinical and healthy populations. Some research suggests that a generalized cognitive control mechanism underlies the ability to modulate various types of impulsive behavior, while other evidence suggests different forms of impulsivity are dissociable, and rely on distinct neural circuitry. Past research consistently implicates several brain regions, such as the striatum and portions of the prefrontal cortex, in impulsive behavior. However the ventral and dorsal striatum are distinct in regards to function and connectivity. Nascent evidence points to the importance of frontostriatal white matter connectivity in impulsivity, yet it remains unclear whether particular tracts relate to different control behaviors. Here we used probabilistic tractography of diffusion imaging data to relate ventral and dorsal frontostriatal connectivity to reward and motor impulsivity measures. We found a double dissociation such that individual differences in white matter connectivity between the ventral striatum and the ventromedial prefrontal cortex and dorsolateral prefrontal cortex was associated with reward impulsivity, as measured by delay discounting, whereas connectivity between dorsal striatum and supplementary motor area was associated with motor impulsivity, but not vice versa. Our findings suggest that (a) structural connectivity can is associated with a large amount of behavioral variation; (b) different types of impulsivity are driven by dissociable frontostriatal neural circuitry. PMID:28189592

Metabolic demands of neural-hemodynamic associated and disassociated areas in brain.

PubMed

Sanganahalli, Basavaraju G; Herman, Peter; Rothman, Douglas L; Blumenfeld, Hal; Hyder, Fahmeed

2016-10-01

Interpretation of regional blood oxygenation level-dependent (BOLD) responses in functional magnetic resonance imaging (fMRI) is contingent on whether local field potential (LFP) and multi-unit activity (MUA) is either dissociated or associated. To examine whether neural-hemodynamic associated and dissociated areas have different metabolic demands, we recorded sensory-evoked responses of BOLD signal, blood flow (CBF), and blood volume (CBV), which with calibrated fMRI provided oxidative metabolism (CMR O2 ) from rat's ventral posterolateral thalamic nucleus (VPL) and somatosensory forelimb cortex (S1 FL ) and compared these neuroimaging signals to neurophysiological recordings. MUA faithfully recorded evoked latency differences between VPL and S1 FL because evoked MUA in these regions were similar in magnitude. Since evoked LFP was significantly attenuated in VPL, we extracted the time courses of the weaker thalamic LFP to compare with the stronger cortical LFP using wavelet transform. BOLD and CBV responses were greater in S1 FL than in VPL, similar to LFP regional differences. CBF and CMR O2 responses were both comparably larger in S1 FL and VPL. Despite different levels of CBF-CMR O2 and LFP-MUA couplings in VPL and S1 FL , the CMR O2 was well matched with MUA in both regions. These results suggest that neural-hemodynamic associated and dissociated areas in VPL and S1 FL can have similar metabolic demands. © The Author(s) 2016.

Developmental dissociation in the neural responses to simple multiplication and subtraction problems

PubMed Central

Prado, Jérôme; Mutreja, Rachna; Booth, James R.

2014-01-01

Mastering single-digit arithmetic during school years is commonly thought to depend upon an increasing reliance on verbally memorized facts. An alternative model, however, posits that fluency in single-digit arithmetic might also be achieved via the increasing use of efficient calculation procedures. To test between these hypotheses, we used a cross-sectional design to measure the neural activity associated with single-digit subtraction and multiplication in 34 children from 2nd to 7th grade. The neural correlates of language and numerical processing were also identified in each child via localizer scans. Although multiplication and subtraction were undistinguishable in terms of behavior, we found a striking developmental dissociation in their neural correlates. First, we observed grade-related increases of activity for multiplication, but not for subtraction, in a language-related region of the left temporal cortex. Second, we found grade-related increases of activity for subtraction, but not for multiplication, in a region of the right parietal cortex involved in the procedural manipulation of numerical quantities. The present results suggest that fluency in simple arithmetic in children may be achieved by both increasing reliance on verbal retrieval and by greater use of efficient quantity-based procedures, depending on the operation. PMID:25089323

Developmental trajectory of neural specialization for letter and number visual processing.

PubMed

Park, Joonkoo; van den Berg, Berry; Chiang, Crystal; Woldorff, Marty G; Brannon, Elizabeth M

2018-05-01

Adult neuroimaging studies have demonstrated dissociable neural activation patterns in the visual cortex in response to letters (Latin alphabet) and numbers (Arabic numerals), which suggest a strong experiential influence of reading and mathematics on the human visual system. Here, developmental trajectories in the event-related potential (ERP) patterns evoked by visual processing of letters, numbers, and false fonts were examined in four different age groups (7-, 10-, 15-year-olds, and young adults). The 15-year-olds and adults showed greater neural sensitivity to letters over numbers in the left visual cortex and the reverse pattern in the right visual cortex, extending previous findings in adults to teenagers. In marked contrast, 7- and 10-year-olds did not show this dissociable neural pattern. Furthermore, the contrast of familiar stimuli (letters or numbers) versus unfamiliar ones (false fonts) showed stark ERP differences between the younger (7- and 10-year-olds) and the older (15-year-olds and adults) participants. These results suggest that both coarse (familiar versus unfamiliar) and fine (letters versus numbers) tuning for letters and numbers continue throughout childhood and early adolescence, demonstrating a profound impact of uniquely human cultural inventions on visual cognition and its development. © 2017 John Wiley & Sons Ltd.

Dissociative disorders in DSM-5.

PubMed

Spiegel, David; Loewenstein, Richard J; Lewis-Fernández, Roberto; Sar, Vedat; Simeon, Daphne; Vermetten, Eric; Cardeña, Etzel; Brown, Richard J; Dell, Paul F

2011-12-21

We present recommendations for revision of the diagnostic criteria for the Dissociative Disorders (DDs) for DSM-5. The periodic revision of the DSM provides an opportunity to revisit the assumptions underlying specific diagnoses and the empirical support, or lack of it, for the defining diagnostic criteria. This paper reviews clinical, phenomenological, epidemiological, cultural, and neurobiological data related to the DDs in order to generate an up-to-date, evidence-based set of DD diagnoses and diagnostic criteria for DSM-5. First, we review the definitions of dissociation and the differences between the definitions of dissociation and conceptualization of DDs in the DSM-IV-TR and the ICD-10, respectively. Also, we review more general conceptual issues in defining dissociation and dissociative disorders. Based on this review, we propose a revised definition of dissociation for DSM-5 and discuss the implications of this definition for understanding dissociative symptoms and disorders. We make the following recommendations for DSM-5: 1. Depersonalization Disorder (DPD) should include derealization symptoms as well. 2. Dissociative Fugue should become a subtype of Dissociative Amnesia (DA). 3. The diagnostic criteria for DID should be changed to emphasize the disruptive nature of the dissociation and amnesia for everyday as well as traumatic events. The experience of possession should be included in the definition of identity disruption. 4. Dissociative Trance Disorder should be included in the Unspecified Dissociative Disorder (UDD) category. There is a growing body of evidence linking the dissociative disorders to a trauma history, and to specific neural mechanisms. © 2011 Wiley Periodicals, Inc.

Dissociative disorders in DSM-5.

PubMed

Spiegel, David; Loewenstein, Richard J; Lewis-Fernández, Roberto; Sar, Vedat; Simeon, Daphne; Vermetten, Eric; Cardeña, Etzel; Dell, Paul F

2011-09-01

We present recommendations for revision of the diagnostic criteria for the Dissociative Disorders (DDs) for DSM-5. The periodic revision of the DSM provides an opportunity to revisit the assumptions underlying specific diagnoses and the empirical support, or lack of it, for the defining diagnostic criteria. This paper reviews clinical, phenomenological, epidemiological, cultural, and neurobiological data related to the DDs in order to generate an up-to-date, evidence-based set of DD diagnoses and diagnostic criteria for DSM-5. First, we review the definitions of dissociation and the differences between the definitions of dissociation and conceptualization of DDs in the DSM-IV-TR and the ICD-10, respectively. Also, we review more general conceptual issues in defining dissociation and dissociative disorders. Based on this review, we propose a revised definition of dissociation for DSM-5 and discuss the implications of this definition for understanding dissociative symptoms and disorders. We make the following recommendations for DSM-5: 1. Depersonalization Disorder (DPD) should derealization symptoms as well. 2. Dissociative Fugue should become a subtype of Dissociative Amnesia (DA). 3. The diagnostic criteria for DID should be changed to emphasize the disruptive nature of the dissociation and amnesia for everyday as well as traumatic events. The experience of possession should be included in the definition of identity disruption. 4. Should Dissociative Trance Disorder should be included in the Unspecified Dissociative Disorder (UDD) category. There is a growing body of evidence linking the dissociative disorders to a trauma history, and to specific neural mechanisms. © 2011 Wiley-Liss, Inc.

SPIDER OR NO SPIDER? NEURAL CORRELATES OF SUSTAINED AND PHASIC FEAR IN SPIDER PHOBIA.

PubMed

Münsterkötter, Anna Luisa; Notzon, Swantje; Redlich, Ronny; Grotegerd, Dominik; Dohm, Katharina; Arolt, Volker; Kugel, Harald; Zwanzger, Peter; Dannlowski, Udo

2015-09-01

Processes of phasic fear responses to threatening stimuli are thought to be distinct from sustained, anticipatory anxiety toward an unpredicted, potential threat. There is evidence for dissociable neural correlates of phasic fear and sustained anxiety. Whereas increased amygdala activity has been associated with phasic fear, sustained anxiety has been linked with activation of the bed nucleus of stria terminalis (BNST), anterior cingulate cortex (ACC), and the insula. So far, only a few studies have focused on the dissociation of neural processes related to both phasic and sustained fear in specific phobia. We suggested that first, conditions of phasic and sustained fear would involve different neural networks and, second, that overall neural activity would be enhanced in a sample of phobic compared to nonphobic participants. Pictures of spiders and neutral stimuli under conditions of either predicted (phasic) or unpredicted (sustained) fear were presented to 28 subjects with spider phobia and 28 nonphobic control subjects during functional magnetic resonance imaging (fMRI) scanning. Phobic patients revealed significantly higher amygdala activation than controls under conditions of phasic fear. Sustained fear processing was significantly related to activation in the insula and ACC, and phobic patients showed a stronger activation than controls of the BNST and the right ACC under conditions of sustained fear. Functional connectivity analysis revealed enhanced connectivity of the BNST and the amygdala in phobic subjects. Our findings support the idea of distinct neural correlates of phasic and sustained fear processes. Increased neural activity and functional connectivity in these networks might be crucial for the development and maintenance of anxiety disorders. © 2015 Wiley Periodicals, Inc.

Dissociable neural correlates of contour completion and contour representation in illusory contour perception.

PubMed

Wu, Xiang; He, Sheng; Bushara, Khalaf; Zeng, Feiyan; Liu, Ying; Zhang, Daren

2012-10-01

Object recognition occurs even when environmental information is incomplete. Illusory contours (ICs), in which a contour is perceived though the contour edges are incomplete, have been extensively studied as an example of such a visual completion phenomenon. Despite the neural activity in response to ICs in visual cortical areas from low (V1 and V2) to high (LOC: the lateral occipital cortex) levels, the details of the neural processing underlying IC perception are largely not clarified. For example, how do the visual areas function in IC perception and how do they interact to archive the coherent contour perception? IC perception involves the process of completing the local discrete contour edges (contour completion) and the process of representing the global completed contour information (contour representation). Here, functional magnetic resonance imaging was used to dissociate contour completion and contour representation by varying each in opposite directions. The results show that the neural activity was stronger to stimuli with more contour completion than to stimuli with more contour representation in V1 and V2, which was the reverse of that in the LOC. When inspecting the neural activity change across the visual pathway, the activation remained high for the stimuli with more contour completion and increased for the stimuli with more contour representation. These results suggest distinct neural correlates of contour completion and contour representation, and the possible collaboration between the two processes during IC perception, indicating a neural connection between the discrete retinal input and the coherent visual percept. Copyright © 2011 Wiley Periodicals, Inc.

A Double Dissociation between Anterior and Posterior Superior Temporal Gyrus for Processing Audiovisual Speech Demonstrated by Electrocorticography.

PubMed

Ozker, Muge; Schepers, Inga M; Magnotti, John F; Yoshor, Daniel; Beauchamp, Michael S

2017-06-01

Human speech can be comprehended using only auditory information from the talker's voice. However, comprehension is improved if the talker's face is visible, especially if the auditory information is degraded as occurs in noisy environments or with hearing loss. We explored the neural substrates of audiovisual speech perception using electrocorticography, direct recording of neural activity using electrodes implanted on the cortical surface. We observed a double dissociation in the responses to audiovisual speech with clear and noisy auditory component within the superior temporal gyrus (STG), a region long known to be important for speech perception. Anterior STG showed greater neural activity to audiovisual speech with clear auditory component, whereas posterior STG showed similar or greater neural activity to audiovisual speech in which the speech was replaced with speech-like noise. A distinct border between the two response patterns was observed, demarcated by a landmark corresponding to the posterior margin of Heschl's gyrus. To further investigate the computational roles of both regions, we considered Bayesian models of multisensory integration, which predict that combining the independent sources of information available from different modalities should reduce variability in the neural responses. We tested this prediction by measuring the variability of the neural responses to single audiovisual words. Posterior STG showed smaller variability than anterior STG during presentation of audiovisual speech with noisy auditory component. Taken together, these results suggest that posterior STG but not anterior STG is important for multisensory integration of noisy auditory and visual speech.

Dissociable neural modulation underlying lasting first impressions, changing your mind for the better, and changing it for the worse.

PubMed

Bhanji, Jamil P; Beer, Jennifer S

2013-05-29

Unattractive job candidates face a disadvantage when interviewing for a job. Employers' evaluations are colored by the candidate's physical attractiveness even when they take job interview performance into account. This example illustrates unexplored questions about the neural basis of social evaluation in humans. What neural regions support the lasting effects of initial impressions (even after getting to know someone)? How does the brain process information that changes our minds about someone? Job candidates' competence was evaluated from photographs and again after seeing snippets of job interviews. Left lateral orbitofrontal cortex modulation serves as a warning signal for initial reactions that ultimately undermine evaluations even when additional information is taken into account. The neural basis of changing one's mind about a candidate is not a simple matter of computing the amount of competence-affirming information in their job interview. Instead, seeing a candidate for the better is somewhat distinguishable at the neural level from seeing a candidate for the worse. Whereas amygdala modulation marks the extremity of evaluation change, favorable impression change additionally draws on parametric modulation of lateral prefrontal cortex and unfavorable impression change additionally draws on parametric modulation of medial prefrontal cortex, temporal cortex, and striatum. Investigating social evaluation as a dynamic process (rather than a one-time impression) paints a new picture of its neural basis and highlights the partially dissociable processes that contribute to changing your mind about someone for the better or the worse.

Neural network L1 adaptive control of MIMO systems with nonlinear uncertainty.

PubMed

Zhen, Hong-tao; Qi, Xiao-hui; Li, Jie; Tian, Qing-min

2014-01-01

An indirect adaptive controller is developed for a class of multiple-input multiple-output (MIMO) nonlinear systems with unknown uncertainties. This control system is comprised of an L 1 adaptive controller and an auxiliary neural network (NN) compensation controller. The L 1 adaptive controller has guaranteed transient response in addition to stable tracking. In this architecture, a low-pass filter is adopted to guarantee fast adaptive rate without generating high-frequency oscillations in control signals. The auxiliary compensation controller is designed to approximate the unknown nonlinear functions by MIMO RBF neural networks to suppress the influence of uncertainties. NN weights are tuned on-line with no prior training and the project operator ensures the weights bounded. The global stability of the closed-system is derived based on the Lyapunov function. Numerical simulations of an MIMO system coupled with nonlinear uncertainties are used to illustrate the practical potential of our theoretical results.

The dissociation between command following and communication in disorders of consciousness: an fMRI study in healthy subjects.

PubMed

Osborne, Natalie R; Owen, Adrian M; Fernández-Espejo, Davinia

2015-01-01

Neuroimaging studies have identified a subgroup of patients with a Disorder of Consciousness (DOC) who, while being behaviorally non-responsive, are nevertheless able to follow commands by modulating their brain activity in motor imagery (MI) tasks. These techniques have even allowed for binary communication in a small number of DOC patients. However, the majority of patients who can follow commands are unable to use their responses to communicate. A similar dissociation between present command following (CF) and absent communication abilities has been reported in overt behavioral assessments. However, the neural correlates of this dissociation in both overt and covert modalities are unknown. Here, we used functional magnetic resonance imaging (fMRI) to explore the neural mechanisms underlying CF and selection of responses for binary communication using either executed or imagined movements. Fifteen healthy participants executed or imagined two different types of arm movements that were either pre-determined by the experimenters (CF) or decided by them (action selection, AS). Action selection involved greater activity in high-level associative areas in frontal and parietal regions than CF. Additionally, motor execution (ME), as compared to MI, activated contralateral motor cortex, while the opposite contrast revealed activation in the ipsilateral sensorimotor cortex and the left inferior frontal gyrus. Importantly, there was no interaction between the task (CF/AS) and modality (MI/ME). Our results suggest that the neural processes involved in following a motor command or selecting between two motor actions are not dependent on how the response is expressed (via ME/MI). They also suggest a potential neural basis for the distinction in cognitive abilities seen in DOC patients.

The dissociation between command following and communication in disorders of consciousness: an fMRI study in healthy subjects

PubMed Central

Osborne, Natalie R.; Owen, Adrian M.; Fernández-Espejo, Davinia

2015-01-01

Neuroimaging studies have identified a subgroup of patients with a Disorder of Consciousness (DOC) who, while being behaviorally non-responsive, are nevertheless able to follow commands by modulating their brain activity in motor imagery (MI) tasks. These techniques have even allowed for binary communication in a small number of DOC patients. However, the majority of patients who can follow commands are unable to use their responses to communicate. A similar dissociation between present command following (CF) and absent communication abilities has been reported in overt behavioral assessments. However, the neural correlates of this dissociation in both overt and covert modalities are unknown. Here, we used functional magnetic resonance imaging (fMRI) to explore the neural mechanisms underlying CF and selection of responses for binary communication using either executed or imagined movements. Fifteen healthy participants executed or imagined two different types of arm movements that were either pre-determined by the experimenters (CF) or decided by them (action selection, AS). Action selection involved greater activity in high-level associative areas in frontal and parietal regions than CF. Additionally, motor execution (ME), as compared to MI, activated contralateral motor cortex, while the opposite contrast revealed activation in the ipsilateral sensorimotor cortex and the left inferior frontal gyrus. Importantly, there was no interaction between the task (CF/AS) and modality (MI/ME). Our results suggest that the neural processes involved in following a motor command or selecting between two motor actions are not dependent on how the response is expressed (via ME/MI). They also suggest a potential neural basis for the distinction in cognitive abilities seen in DOC patients. PMID:26441593

The neural representation of unexpected uncertainty during value-based decision making.

PubMed

Payzan-LeNestour, Elise; Dunne, Simon; Bossaerts, Peter; O'Doherty, John P

2013-07-10

Uncertainty is an inherent property of the environment and a central feature of models of decision-making and learning. Theoretical propositions suggest that one form, unexpected uncertainty, may be used to rapidly adapt to changes in the environment, while being influenced by two other forms: risk and estimation uncertainty. While previous studies have reported neural representations of estimation uncertainty and risk, relatively little is known about unexpected uncertainty. Here, participants performed a decision-making task while undergoing functional magnetic resonance imaging (fMRI), which, in combination with a Bayesian model-based analysis, enabled us to separately examine each form of uncertainty examined. We found representations of unexpected uncertainty in multiple cortical areas, as well as the noradrenergic brainstem nucleus locus coeruleus. Other unique cortical regions were found to encode risk, estimation uncertainty, and learning rate. Collectively, these findings support theoretical models in which several formally separable uncertainty computations determine the speed of learning. Copyright © 2013 Elsevier Inc. All rights reserved.

Robust stability for stochastic bidirectional associative memory neural networks with time delays

NASA Astrophysics Data System (ADS)

Shu, H. S.; Lv, Z. W.; Wei, G. L.

2008-02-01

In this paper, the asymptotic stability is considered for a class of uncertain stochastic bidirectional associative memory neural networks with time delays and parameter uncertainties. The delays are time-invariant and the uncertainties are norm-bounded that enter into all network parameters. The aim of this paper is to establish easily verifiable conditions under which the delayed neural network is robustly asymptotically stable in the mean square for all admissible parameter uncertainties. By employing a Lyapunov-Krasovskii functional and conducting the stochastic analysis, a linear matrix inequality matrix inequality (LMI) approach is developed to derive the stability criteria. The proposed criteria can be easily checked by the Matlab LMI toolbox. A numerical example is given to demonstrate the usefulness of the proposed criteria.

Statistically optimal perception and learning: from behavior to neural representations

PubMed Central

Fiser, József; Berkes, Pietro; Orbán, Gergő; Lengyel, Máté

2010-01-01

Human perception has recently been characterized as statistical inference based on noisy and ambiguous sensory inputs. Moreover, suitable neural representations of uncertainty have been identified that could underlie such probabilistic computations. In this review, we argue that learning an internal model of the sensory environment is another key aspect of the same statistical inference procedure and thus perception and learning need to be treated jointly. We review evidence for statistically optimal learning in humans and animals, and reevaluate possible neural representations of uncertainty based on their potential to support statistically optimal learning. We propose that spontaneous activity can have a functional role in such representations leading to a new, sampling-based, framework of how the cortex represents information and uncertainty. PMID:20153683

Dissociable frontostriatal white matter connectivity underlies reward and motor impulsivity.

PubMed

Hampton, William H; Alm, Kylie H; Venkatraman, Vinod; Nugiel, Tehila; Olson, Ingrid R

2017-04-15

Dysfunction of cognitive control often leads to impulsive decision-making in clinical and healthy populations. Some research suggests that a generalized cognitive control mechanism underlies the ability to modulate various types of impulsive behavior, while other evidence suggests different forms of impulsivity are dissociable, and rely on distinct neural circuitry. Past research consistently implicates several brain regions, such as the striatum and portions of the prefrontal cortex, in impulsive behavior. However the ventral and dorsal striatum are distinct in regards to function and connectivity. Nascent evidence points to the importance of frontostriatal white matter connectivity in impulsivity, yet it remains unclear whether particular tracts relate to different control behaviors. Here we used probabilistic tractography of diffusion imaging data to relate ventral and dorsal frontostriatal connectivity to reward and motor impulsivity measures. We found a double dissociation such that individual differences in white matter connectivity between the ventral striatum and the ventromedial prefrontal cortex and dorsolateral prefrontal cortex was associated with reward impulsivity, as measured by delay discounting, whereas connectivity between dorsal striatum and supplementary motor area was associated with motor impulsivity, but not vice versa. Our findings suggest that (a) structural connectivity can is associated with a large amount of behavioral variation; (b) different types of impulsivity are driven by dissociable frontostriatal neural circuitry. Copyright © 2017 Elsevier Inc. All rights reserved.

Dissociated neural basis of two behavioral hallmarks of holistic face processing: The whole-part effect and composite-face effect.

PubMed

Li, Jin; Huang, Lijie; Song, Yiying; Liu, Jia

2017-07-28

It has been long proposed that our extraordinary face recognition ability stems from holistic face processing. Two widely-used behavioral hallmarks of holistic face processing are the whole-part effect (WPE) and composite-face effect (CFE). However, it remains unknown whether these two effects reflect similar or different aspects of holistic face processing. Here we investigated this question by examining whether the WPE and CFE involved shared or distinct neural substrates in a large sample of participants (N=200). We found that the WPE and CFE showed hemispheric dissociation in the fusiform face area (FFA), that is, the WPE was correlated with face selectivity in the left FFA, while the CFE was correlated with face selectivity in the right FFA. Further, the correlation between the WPE and face selectivity was largely driven by the FFA response to faces, whereas the association between the CFE and face selectivity resulted from suppressed response to objects in the right FFA. Finally, we also observed dissociated correlation patterns of the WPE and CFE in other face-selective regions and across the whole brain. These results suggest that the WPE and CFE may reflect different aspects of holistic face processing, which shed new light on the behavioral dissociations of these two effects demonstrated in literature. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatiotemporal dissociation of brain activity underlying threat and reward in social anxiety disorder

PubMed Central

Ghane, Merage; Valdespino, Andrew; Coffman, Marika C.; Strege, Marlene V.; White, Susan W.; Ollendick, Thomas H.

2017-01-01

Abstract Social anxiety disorder (SAD) involves abnormalities in social motivation, which may be independent of well-documented differences in fear and arousal systems. Yet, the neurobiology underlying motivational difficulties in SAD is not well understood. The aim of the current study was to spatiotemporally dissociate reward circuitry dysfunction from alterations in fear and arousal-related neural activity during anticipation and notification of social and non-social reward and punishment. During fMRI acquisition, non-depressed adults with social anxiety disorder (SAD; N = 21) and age-, sex- and IQ-matched control subjects (N = 22) completed eight runs of an incentive delay task, alternating between social and monetary outcomes and interleaved in alternating order between gain and loss outcomes. Adults with SAD demonstrated significantly reduced neural activity in ventral striatum during the anticipation of positive but not negative social outcomes. No differences between the SAD and control groups were observed during anticipation of monetary gain or loss outcomes or during anticipation of negative social images. However, consistent with previous work, the SAD group demonstrated amygdala hyper-activity upon notification of negative social outcomes. Degraded anticipatory processing in bilateral ventral striatum in SAD was constrained exclusively to anticipation of positive social information and dissociable from the effects of negative social outcomes previously observed in the amygdala. Alterations in anticipation-related neural signals may represent a promising target for treatment that is not addressed by available evidence-based interventions, which focus primarily on fear extinction and habituation processes. PMID:27798252

Automatic and controlled components of judgment and decision making.

PubMed

Ferreira, Mario B; Garcia-Marques, Leonel; Sherman, Steven J; Sherman, Jeffrey W

2006-11-01

The categorization of inductive reasoning into largely automatic processes (heuristic reasoning) and controlled analytical processes (rule-based reasoning) put forward by dual-process approaches of judgment under uncertainty (e.g., K. E. Stanovich & R. F. West, 2000) has been primarily a matter of assumption with a scarcity of direct empirical findings supporting it. The present authors use the process dissociation procedure (L. L. Jacoby, 1991) to provide convergent evidence validating a dual-process perspective to judgment under uncertainty based on the independent contributions of heuristic and rule-based reasoning. Process dissociations based on experimental manipulation of variables were derived from the most relevant theoretical properties typically used to contrast the two forms of reasoning. These include processing goals (Experiment 1), cognitive resources (Experiment 2), priming (Experiment 3), and formal training (Experiment 4); the results consistently support the author's perspective. They conclude that judgment under uncertainty is neither an automatic nor a controlled process but that it reflects both processes, with each making independent contributions.

Recollection of episodic memory within the medial temporal lobe: behavioural dissociations from other types of memory.

PubMed

Easton, Alexander; Eacott, Madeline J

2010-12-31

In recent years there has been significant debate about whether there is a single medial temporal lobe memory system or dissociable systems for episodic and other types of declarative memory. In addition there has been a similar debate over the dissociability of recollection and familiarity based processes in recognition memory. Here we present evidence from recent work using episodic memory tasks in animals that allows us to explore these issues in more depth. We review studies that demonstrate triple dissociations within the medial temporal lobe, with only the hippocampal system being necessary for episodic memory. Similarly we review behavioural evidence for a dissociation in a task of episodic memory in rats where animals with lesions of the fornix are only impaired at recollection of the episodic memory, not recognition within the same trial. This work, then, supports recent models of dissociable neural systems within the medial temporal lobe but also raises questions for future investigation about the interactions of these medial temporal lobe memory systems with other structures. Copyright © 2009 Elsevier B.V. All rights reserved.

A Double Dissociation between Anterior and Posterior Superior Temporal Gyrus for Processing Audiovisual Speech Demonstrated by Electrocorticography

PubMed Central

Ozker, Muge; Schepers, Inga M.; Magnotti, John F.; Yoshor, Daniel; Beauchamp, Michael S.

2017-01-01

Human speech can be comprehended using only auditory information from the talker’s voice. However, comprehension is improved if the talker’s face is visible, especially if the auditory information is degraded as occurs in noisy environments or with hearing loss. We explored the neural substrates of audiovisual speech perception using electrocorticography, direct recording of neural activity using electrodes implanted on the cortical surface. We observed a double dissociation in the responses to audiovisual speech with clear and noisy auditory component within the superior temporal gyrus (STG), a region long known to be important for speech perception. Anterior STG showed greater neural activity to audiovisual speech with clear auditory component, whereas posterior STG showed similar or greater neural activity to audiovisual speech in which the speech was replaced with speech-like noise. A distinct border between the two response patterns was observed, demarcated by a landmark corresponding to the posterior margin of Heschl’s gyrus. To further investigate the computational roles of both regions, we considered Bayesian models of multisensory integration, which predict that combining the independent sources of information available from different modalities should reduce variability in the neural responses. We tested this prediction by measuring the variability of the neural responses to single audiovisual words. Posterior STG showed smaller variability than anterior STG during presentation of audiovisual speech with noisy auditory component. Taken together, these results suggest that posterior STG but not anterior STG is important for multisensory integration of noisy auditory and visual speech. PMID:28253074

Hemispheric association and dissociation of voice and speech information processing in stroke.

PubMed

Jones, Anna B; Farrall, Andrew J; Belin, Pascal; Pernet, Cyril R

2015-10-01

As we listen to someone speaking, we extract both linguistic and non-linguistic information. Knowing how these two sets of information are processed in the brain is fundamental for the general understanding of social communication, speech recognition and therapy of language impairments. We investigated the pattern of performances in phoneme versus gender categorization in left and right hemisphere stroke patients, and found an anatomo-functional dissociation in the right frontal cortex, establishing a new syndrome in voice discrimination abilities. In addition, phoneme and gender performances were most often associated than dissociated in the left hemisphere patients, suggesting a common neural underpinnings. Copyright © 2015 Elsevier Ltd. All rights reserved.

Native-language N400 and P600 predict dissociable language-learning abilities in adults

PubMed Central

Qi, Zhenghan; Beach, Sara D.; Finn, Amy S.; Minas, Jennifer; Goetz, Calvin; Chan, Brian; Gabrieli, John D.E.

2018-01-01

Language learning aptitude during adulthood varies markedly across individuals. An individual’s native-language ability has been associated with success in learning a new language as an adult. However, little is known about how native-language processing affects learning success and what neural markers of native-language processing, if any, are related to success in learning. We therefore related variation in electrophysiology during native-language processing to success in learning a novel artificial language. Event-related potentials (ERPs) were recorded while native English speakers judged the acceptability of English sentences prior to learning an artificial language. There was a trend towards a double dissociation between native-language ERPs and their relationships to novel syntax and vocabulary learning. Individuals who exhibited a greater N400 effect when processing English semantics showed better future learning of the artificial language overall. The N400 effect was related to syntax learning via its specific relationship to vocabulary learning. In contrast, the P600 effect size when processing English syntax predicted future syntax learning but not vocabulary learning. These findings show that distinct neural signatures of native-language processing relate to dissociable abilities for learning novel semantic and syntactic information. PMID:27737775

Neural mechanisms mediating degrees of strategic uncertainty.

PubMed

Nagel, Rosemarie; Brovelli, Andrea; Heinemann, Frank; Coricelli, Giorgio

2018-01-01

In social interactions, strategic uncertainty arises when the outcome of one's choice depends on the choices of others. An important question is whether strategic uncertainty can be resolved by assessing subjective probabilities to the counterparts' behavior, as if playing against nature, and thus transforming the strategic interaction into a risky (individual) situation. By means of functional magnetic resonance imaging with human participants we tested the hypothesis that choices under strategic uncertainty are supported by the neural circuits mediating choices under individual risk and deliberation in social settings (i.e. strategic thinking). Participants were confronted with risky lotteries and two types of coordination games requiring different degrees of strategic thinking of the kind 'I think that you think that I think etc.' We found that the brain network mediating risk during lotteries (anterior insula, dorsomedial prefrontal cortex and parietal cortex) is also engaged in the processing of strategic uncertainty in games. In social settings, activity in this network is modulated by the level of strategic thinking that is reflected in the activity of the dorsomedial and dorsolateral prefrontal cortex. These results suggest that strategic uncertainty is resolved by the interplay between the neural circuits mediating risk and higher order beliefs (i.e. beliefs about others' beliefs). © The Author(s) (2017). Published by Oxford University Press.

Neural mechanisms mediating degrees of strategic uncertainty

PubMed Central

Nagel, Rosemarie; Brovelli, Andrea; Heinemann, Frank

2018-01-01

Abstract In social interactions, strategic uncertainty arises when the outcome of one’s choice depends on the choices of others. An important question is whether strategic uncertainty can be resolved by assessing subjective probabilities to the counterparts’ behavior, as if playing against nature, and thus transforming the strategic interaction into a risky (individual) situation. By means of functional magnetic resonance imaging with human participants we tested the hypothesis that choices under strategic uncertainty are supported by the neural circuits mediating choices under individual risk and deliberation in social settings (i.e. strategic thinking). Participants were confronted with risky lotteries and two types of coordination games requiring different degrees of strategic thinking of the kind ‘I think that you think that I think etc.’ We found that the brain network mediating risk during lotteries (anterior insula, dorsomedial prefrontal cortex and parietal cortex) is also engaged in the processing of strategic uncertainty in games. In social settings, activity in this network is modulated by the level of strategic thinking that is reflected in the activity of the dorsomedial and dorsolateral prefrontal cortex. These results suggest that strategic uncertainty is resolved by the interplay between the neural circuits mediating risk and higher order beliefs (i.e. beliefs about others’ beliefs). PMID:29228378

What can individual differences reveal about face processing?

PubMed Central

Yovel, Galit; Wilmer, Jeremy B.; Duchaine, Brad

2014-01-01

Faces are probably the most widely studied visual stimulus. Most research on face processing has used a group-mean approach that averages behavioral or neural responses to faces across individuals and treats variance between individuals as noise. However, individual differences in face processing can provide valuable information that complements and extends findings from group-mean studies. Here we demonstrate that studies employing an individual differences approach—examining associations and dissociations across individuals—can answer fundamental questions about the way face processing operates. In particular these studies allow us to associate and dissociate the mechanisms involved in face processing, tie behavioral face processing mechanisms to neural mechanisms, link face processing to broader capacities and quantify developmental influences on face processing. The individual differences approach we illustrate here is a powerful method that should be further explored within the domain of face processing as well as fruitfully applied across the cognitive sciences. PMID:25191241

Signal recognition efficiencies of artificial neural-network pulse-shape discrimination in HPGe -decay searches

NASA Astrophysics Data System (ADS)

Caldwell, A.; Cossavella, F.; Majorovits, B.; Palioselitis, D.; Volynets, O.

2015-07-01

A pulse-shape discrimination method based on artificial neural networks was applied to pulses simulated for different background, signal and signal-like interactions inside a germanium detector. The simulated pulses were used to investigate variations of efficiencies as a function of used training set. It is verified that neural networks are well-suited to identify background pulses in true-coaxial high-purity germanium detectors. The systematic uncertainty on the signal recognition efficiency derived using signal-like evaluation samples from calibration measurements is estimated to be 5 %. This uncertainty is due to differences between signal and calibration samples.

Developmental Dissociation Between the Maturation of Procedural Memory and Declarative Memory

PubMed Central

Finn, Amy S.; Kalra, Priya B.; Goetz, Calvin; Leonard, Julia A.; Sheridan, Margaret A.; Gabrieli, John D. E.

2015-01-01

Declarative memory and procedural memory are known to be two fundamentally different kinds of memory that are dissociable in their psychological characteristics and measurement (explicit versus implicit) and in the neural systems that subserve each kind of memory. Declarative memory abilities are known to improve from childhood through young adulthood, but the developmental maturation of procedural memory is largely unknown. We compared 10-year-old children and young adults on measures of declarative memory, working memory capacity, and four measures of procedural memory that have been strongly dissociated from declarative memory (mirror tracing, rotary pursuit, probabilistic classification, and artificial grammar). Children had lesser declarative memory ability and lesser working memory capacity than the adults, but exhibited learning equivalent to adults on all four measures of procedural memory. Declarative and procedural memory are, therefore, developmentally dissociable, with procedural memory being adult-like by age 10 and declarative memory continuing to mature into young adulthood. PMID:26560675

No-Report Paradigms: Extracting the True Neural Correlates of Consciousness.

PubMed

Tsuchiya, Naotsugu; Wilke, Melanie; Frässle, Stefan; Lamme, Victor A F

2015-12-01

The goal of consciousness research is to reveal the neural basis of phenomenal experience. To study phenomenology, experimenters seem obliged to ask reports from the subjects to ascertain what they experience. However, we argue that the requirement of reports has biased the search for the neural correlates of consciousness over the past decades. More recent studies attempt to dissociate neural activity that gives rise to consciousness from the activity that enables the report; in particular, no-report paradigms have been utilized to study conscious experience in the full absence of any report. We discuss the advantages and disadvantages of report-based and no-report paradigms, and ask how these jointly bring us closer to understanding the true neural basis of consciousness. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Neural activity in superior parietal cortex during rule-based visual-motor transformations.

PubMed

Hawkins, Kara M; Sayegh, Patricia; Yan, Xiaogang; Crawford, J Douglas; Sergio, Lauren E

2013-03-01

Cognition allows for the use of different rule-based sensorimotor strategies, but the neural underpinnings of such strategies are poorly understood. The purpose of this study was to compare neural activity in the superior parietal lobule during a standard (direct interaction) reaching task, with two nonstandard (gaze and reach spatially incongruent) reaching tasks requiring the integration of rule-based information. Specifically, these nonstandard tasks involved dissociating the planes of reach and vision or rotating visual feedback by 180°. Single unit activity, gaze, and reach trajectories were recorded from two female Macaca mulattas. In all three conditions, we observed a temporal discharge pattern at the population level reflecting early reach planning and on-line reach monitoring. In the plane-dissociated task, we found a significant overall attenuation in the discharge rate of cells from deep recording sites, relative to standard reaching. We also found that cells modulated by reach direction tended to be significantly tuned either during the standard or the plane-dissociated task but rarely during both. In the standard versus feedback reversal comparison, we observed some cells that shifted their preferred direction by 180° between conditions, reflecting maintenance of directional tuning with respect to the reach goal. Our findings suggest that the superior parietal lobule plays an important role in processing information about the nonstandard nature of a task, which, through reciprocal connections with precentral motor areas, contributes to the accurate transformation of incongruent sensory inputs into an appropriate motor output. Such processing is crucial for the integration of rule-based information into a motor act.

A cGMP-applicable expansion method for aggregates of human neural stem and progenitor cells derived from pluripotent stem cells or fetal brain tissue.

PubMed

Shelley, Brandon C; Gowing, Geneviève; Svendsen, Clive N

2014-06-15

A cell expansion technique to amass large numbers of cells from a single specimen for research experiments and clinical trials would greatly benefit the stem cell community. Many current expansion methods are laborious and costly, and those involving complete dissociation may cause several stem and progenitor cell types to undergo differentiation or early senescence. To overcome these problems, we have developed an automated mechanical passaging method referred to as "chopping" that is simple and inexpensive. This technique avoids chemical or enzymatic dissociation into single cells and instead allows for the large-scale expansion of suspended, spheroid cultures that maintain constant cell/cell contact. The chopping method has primarily been used for fetal brain-derived neural progenitor cells or neurospheres, and has recently been published for use with neural stem cells derived from embryonic and induced pluripotent stem cells. The procedure involves seeding neurospheres onto a tissue culture Petri dish and subsequently passing a sharp, sterile blade through the cells effectively automating the tedious process of manually mechanically dissociating each sphere. Suspending cells in culture provides a favorable surface area-to-volume ratio; as over 500,000 cells can be grown within a single neurosphere of less than 0.5 mm in diameter. In one T175 flask, over 50 million cells can grow in suspension cultures compared to only 15 million in adherent cultures. Importantly, the chopping procedure has been used under current good manufacturing practice (cGMP), permitting mass quantity production of clinical-grade cell products.

Dissociable neural mechanisms underlying response-based and familiarity-based conflict in working memory.

PubMed

Nelson, James K; Reuter-Lorenz, Patricia A; Sylvester, Ching-Yune C; Jonides, John; Smith, Edward E

2003-09-16

Cognitive control requires the resolution of interference among competing and potentially conflicting representations. Such conflict can emerge at different points between stimulus input and response generation, with the net effect being that of compromising performance. The goal of this article was to dissociate the neural mechanisms underlying different sources of conflict to elucidate the architecture of the neural systems that implement cognitive control. By using functional magnetic resonance imaging and a verbal working memory task (item recognition), we examined brain activity related to two kinds of conflict with comparable behavioral consequences. In a trial of our item-recognition task, participants saw four letters, followed by a retention interval, and a probe letter that did or did not match one of the letters held in working memory (positive probe and negative probe, respectively). On some trials, conflict arose solely because of the current negative probe having a high familiarity, due to its membership in the immediately preceding trial's target set. On other trials, additional conflict arose because of the current negative probe having also been a positive probe on the immediately preceding trial, producing response-level conflict. Consistent with previous work, conflict due to high familiarity was associated with left prefrontal activation, but not with anterior cingulate activation. The response-conflict condition, when compared with high-familiarity conflict trials, was associated with anterior cingulate cortex activation, but with no additional left prefrontal activation. This double dissociation points to differing contributions of specific cortical areas to cognitive control, which are based on the source of conflict.

Dissociable neural representations of grammatical gender in Broca's area investigated by the combination of satiation and TMS.

PubMed

Cattaneo, Zaira; Devlin, Joseph T; Vecchi, Tomaso; Silvanto, Juha

2009-08-15

Along with meaning and form, words can be described on the basis of their grammatical properties. Grammatical gender is often used to investigate the latter as it is a grammatical property that is independent of meaning. The left inferior frontal gyrus (IFG) has been implicated in the encoding of grammatical gender, but its causal role in this process in neurologically normal observers has not been demonstrated. Here we combined verbal satiation with transcranial magnetic stimulation (TMS) to demonstrate that subpopulations of neurons within Broca's area respond preferentially to different classes of grammatical gender. Subjects were asked to classify Italian nouns into living and nonliving categories; half of these words were of masculine and the other half of feminine grammatical gender. Prior to each test block, a satiation paradigm (a phenomenon in which verbal repetition of a category name leads to a reduced access to that category) was used to modulate the initial state of the representations of either masculine or feminine noun categories. In the No TMS condition, subjects were slower in responding to exemplars to the satiated category relative to exemplars of the nonsatiated category, implying that the neural representations for different classes of grammatical gender are partly dissociable. The application of TMS over Broca's area removed the behavioral impact of verbal (grammatical) satiation, demonstrating the causal role of this region in the encoding of grammatical gender. These results show that the neural representations for different cases of a grammatical property within Broca's area are dissociable.

Spatiotemporal dissociation of brain activity underlying threat and reward in social anxiety disorder.

PubMed

A Richey, John; Ghane, Merage; Valdespino, Andrew; Coffman, Marika C; Strege, Marlene V; White, Susan W; Ollendick, Thomas H

2017-01-01

Social anxiety disorder (SAD) involves abnormalities in social motivation, which may be independent of well-documented differences in fear and arousal systems. Yet, the neurobiology underlying motivational difficulties in SAD is not well understood. The aim of the current study was to spatiotemporally dissociate reward circuitry dysfunction from alterations in fear and arousal-related neural activity during anticipation and notification of social and non-social reward and punishment. During fMRI acquisition, non-depressed adults with social anxiety disorder (SAD; N = 21) and age-, sex- and IQ-matched control subjects (N = 22) completed eight runs of an incentive delay task, alternating between social and monetary outcomes and interleaved in alternating order between gain and loss outcomes. Adults with SAD demonstrated significantly reduced neural activity in ventral striatum during the anticipation of positive but not negative social outcomes. No differences between the SAD and control groups were observed during anticipation of monetary gain or loss outcomes or during anticipation of negative social images. However, consistent with previous work, the SAD group demonstrated amygdala hyper-activity upon notification of negative social outcomes. Degraded anticipatory processing in bilateral ventral striatum in SAD was constrained exclusively to anticipation of positive social information and dissociable from the effects of negative social outcomes previously observed in the amygdala. Alterations in anticipation-related neural signals may represent a promising target for treatment that is not addressed by available evidence-based interventions, which focus primarily on fear extinction and habituation processes. © The Author (2016). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

An integrated theory of attention and decision making in visual signal detection.

PubMed

Smith, Philip L; Ratcliff, Roger

2009-04-01

The simplest attentional task, detecting a cued stimulus in an otherwise empty visual field, produces complex patterns of performance. Attentional cues interact with backward masks and with spatial uncertainty, and there is a dissociation in the effects of these variables on accuracy and on response time. A computational theory of performance in this task is described. The theory links visual encoding, masking, spatial attention, visual short-term memory (VSTM), and perceptual decision making in an integrated dynamic framework. The theory assumes that decisions are made by a diffusion process driven by a neurally plausible, shunting VSTM. The VSTM trace encodes the transient outputs of early visual filters in a durable form that is preserved for the time needed to make a decision. Attention increases the efficiency of VSTM encoding, either by increasing the rate of trace formation or by reducing the delay before trace formation begins. The theory provides a detailed, quantitative account of attentional effects in spatial cuing tasks at the level of response accuracy and the response time distributions. (c) 2009 APA, all rights reserved

Temporal dynamics of reward anticipation in the human brain.

PubMed

Zhang, Yuanyuan; Li, Qi; Wang, Zhao; Liu, Xun; Zheng, Ya

2017-09-01

Reward anticipation is a complex process including cue evaluation, motor preparation, and feedback anticipation. The present study investigated whether these psychological processes were dissociable on neural dynamics in terms of incentive valence and approach motivation. We recorded EEG when participants were performing a monetary incentive delay task, and found a cue-P3 during the cue-evaluation stage, a contingent negative variation (CNV) during the motor-preparation stage, and a stimulus-preceding negativity (SPN) during the feedback-anticipation stage. Critically, both the cue-P3 and SPN exhibited an enhanced sensitivity to gain versus loss anticipation, which was not observed for the CNV. Moreover, both the cue-P3 and SPN, instead of the CNV, for gain anticipation selectively predicted the participants' approach motivation as measured in a following effort expenditure for rewards task, particularly when reward uncertainty was maximal. Together, these results indicate that reward anticipation consists of several sub-stages, each with distinct functional significance, thus providing implications for neuropsychiatric diseases characterized by dysfunction in anticipatory reward processing. Copyright © 2017 Elsevier B.V. All rights reserved.

Formation of Neural Networks in 3D Scaffolds Fabricated by Means of Laser Microstereolithography.

PubMed

Vedunova, M V; Timashev, P S; Mishchenko, T A; Mitroshina, E V; Koroleva, A V; Chichkov, B N; Panchenko, V Ya; Bagratashvili, V N; Mukhina, I V

2016-08-01

We developed and tested new 3D scaffolds for neurotransplantation. Scaffolds of predetermined architectonic were prepared using microstereolithography technique. Scaffolds were highly biocompatible with the nervous tissue cells. In vitro studies showed that the material of fabricated scaffolds is not toxic for dissociated brain cells and promotes the formation of functional neural networks in the matrix. These results demonstrate the possibility of fabrication of tissue-engineering constructs for neurotransplantation based on created scaffolds.

New Passivity Criteria for Fuzzy Bam Neural Networks with Markovian Jumping Parameters and Time-Varying Delays

NASA Astrophysics Data System (ADS)

Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Thangaraj, P.

2013-02-01

This paper addresses the problem of passivity analysis issue for a class of fuzzy bidirectional associative memory (BAM) neural networks with Markovian jumping parameters and time varying delays. A set of sufficient conditions for the passiveness of the considered fuzzy BAM neural network model is derived in terms of linear matrix inequalities by using the delay fractioning technique together with the Lyapunov function approach. In addition, the uncertainties are inevitable in neural networks because of the existence of modeling errors and external disturbance. Further, this result is extended to study the robust passivity criteria for uncertain fuzzy BAM neural networks with time varying delays and uncertainties. These criteria are expressed in the form of linear matrix inequalities (LMIs), which can be efficiently solved via standard numerical software. Two numerical examples are provided to demonstrate the effectiveness of the obtained results.

Accounting for dissociation and photolysis: a review of the algal toxicity of triclosan.

PubMed

Roberts, Jayne; Price, Oliver R; Bettles, Nicola; Rendal, Cecilie; van Egmond, Roger

2014-11-01

Triclosan, an antimicrobial agent commonly used in down-the-drain consumer products, is toxic to freshwater microalgae. However, the rapid photolysis and pH-dependent dissociation of this compound may give rise to uncertainty in growth inhibition tests with freshwater microalgae, if these are not well characterized. Methods are presented to minimize these uncertainties by stabilizing pH with an organic buffering agent (Bis-Tris) and by the application of ultraviolet (UV) covers to remove UV wavelengths. Toxicity tests with these methods were in compliance with the validity criteria of the Organisation for Economic Co-operation and Development test 201, and no negative effects were seen in controls relative to the unmodified method. The methods were used for toxicity tests with triclosan at pH levels of 7.0, 8.0, and 8.5, yielding effective concentration, 10% values of 0.5 µg/L, 0.6 µg/L, and 12.1 µg/L, respectively. The observed change in toxicity with pH was proportional to the change in bioconcentration factor (BCF) as calculated using the cell model (a dynamic flux model based on the Fick-Nernst-Planck equations, in this case parameterized for an algal cell). Effect concentrations produced with the methods presented in the present study offer robust data on which to base risk assessment, and it is suggested that similar approaches be used to minimize uncertainty when other compounds that dissociate and photolyse are tested. © 2014 SETAC.

The dissociable neural dynamics of cognitive conflict and emotional conflict control: An ERP study.

PubMed

Xue, Song; Li, Yu; Kong, Xia; He, Qiaolin; Liu, Jia; Qiu, Jiang

2016-04-21

This study investigated differences in the neural time-course of cognitive conflict and emotional conflict control, using event-related potentials (ERPs). Although imaging studies have provided some evidence that distinct, dissociable neural systems underlie emotional and nonemotional conflict resolution, no ERP study has directly compared these two types of conflict. Therefore, the present study used a modified face-word Stroop task to explore the electrophysiological correlates of cognitive and emotional conflict control. The behavioral data showed that the difference in response time of congruency (incongruent condition minus the congruent condition) was larger in the cognitive conflict task than in the emotional conflict task, which indicated that cognitive conflict was stronger than the emotional conflict in the present tasks. Analysis of the ERP data revealed a main effect of task type on N2, which may be associated with top-down attention. The N450 results showed an interaction between cognitive and emotional conflict, which might be related to conflict detection. In addition, we found the incongruent condition elicited a larger SP than the congruent condition, which might be related to conflict resolution. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Neural priming in human frontal cortex: multiple forms of learning reduce demands on the prefrontal executive system.

PubMed

Race, Elizabeth A; Shanker, Shanti; Wagner, Anthony D

2009-09-01

Past experience is hypothesized to reduce computational demands in PFC by providing bottom-up predictive information that informs subsequent stimulus-action mapping. The present fMRI study measured cortical activity reductions ("neural priming"/"repetition suppression") during repeated stimulus classification to investigate the mechanisms through which learning from the past decreases demands on the prefrontal executive system. Manipulation of learning at three levels of representation-stimulus, decision, and response-revealed dissociable neural priming effects in distinct frontotemporal regions, supporting a multiprocess model of neural priming. Critically, three distinct patterns of neural priming were identified in lateral frontal cortex, indicating that frontal computational demands are reduced by three forms of learning: (a) cortical tuning of stimulus-specific representations, (b) retrieval of learned stimulus-decision mappings, and (c) retrieval of learned stimulus-response mappings. The topographic distribution of these neural priming effects suggests a rostrocaudal organization of executive function in lateral frontal cortex.

Egocentric virtual maze learning in adult survivors of childhood abuse with dissociative disorders: evidence from functional magnetic resonance imaging.

PubMed

Weniger, Godehard; Siemerkus, Jakob; Barke, Antonia; Lange, Claudia; Ruhleder, Mirjana; Sachsse, Ulrich; Schmidt-Samoa, Carsten; Dechent, Peter; Irle, Eva

2013-05-30

Present neuroimaging findings suggest two subtypes of trauma response, one characterized predominantly by hyperarousal and intrusions, and the other primarily by dissociative symptoms. The neural underpinnings of these two subtypes need to be better defined. Fourteen women with childhood abuse and the current diagnosis of dissociative amnesia or dissociative identity disorder but without posttraumatic stress disorder (PTSD) and 14 matched healthy comparison subjects underwent functional magnetic resonance imaging (fMRI) while finding their way in a virtual maze. The virtual maze presented a first-person view (egocentric), lacked any topographical landmarks and could be learned only by using egocentric navigation strategies. Participants with dissociative disorders (DD) were not impaired in learning the virtual maze when compared with controls, and showed a similar, although weaker, pattern of activity changes during egocentric learning when compared with controls. Stronger dissociative disorder severity of participants with DD was related to better virtual maze performance, and to stronger activity increase within the cingulate gyrus and the precuneus. Our results add to the present knowledge of preserved attentional and visuospatial mnemonic functioning in individuals with DD. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

The known unknowns: neural representation of second-order uncertainty, and ambiguity

PubMed Central

Bach, Dominik R.; Hulme, Oliver; Penny, William D.; Dolan, Raymond J.

2011-01-01

Predictions provided by action-outcome probabilities entail a degree of (first-order) uncertainty. However, these probabilities themselves can be imprecise and embody second-order uncertainty. Tracking second-order uncertainty is important for optimal decision making and reinforcement learning. Previous functional magnetic resonance imaging investigations of second-order uncertainty in humans have drawn on an economic concept of ambiguity, where action-outcome associations in a gamble are either known (unambiguous) or completely unknown (ambiguous). Here, we relaxed the constraints associated with a purely categorical concept of ambiguity and varied the second-order uncertainty of gambles continuously, quantified as entropy over second-order probabilities. We show that second-order uncertainty influences decisions in a pessimistic way by biasing second-order probabilities, and that second-order uncertainty is negatively correlated with posterior cingulate cortex activity. The category of ambiguous (compared to non-ambiguous) gambles also biased choice in a similar direction, but was associated with distinct activation of a posterior parietal cortical area; an activation that we show reflects a different computational mechanism. Our findings indicate that behavioural and neural responses to second-order uncertainty are distinct from those associated with ambiguity and may call for a reappraisal of previous data. PMID:21451019

Native-language N400 and P600 predict dissociable language-learning abilities in adults.

PubMed

Qi, Zhenghan; Beach, Sara D; Finn, Amy S; Minas, Jennifer; Goetz, Calvin; Chan, Brian; Gabrieli, John D E

2017-04-01

Language learning aptitude during adulthood varies markedly across individuals. An individual's native-language ability has been associated with success in learning a new language as an adult. However, little is known about how native-language processing affects learning success and what neural markers of native-language processing, if any, are related to success in learning. We therefore related variation in electrophysiology during native-language processing to success in learning a novel artificial language. Event-related potentials (ERPs) were recorded while native English speakers judged the acceptability of English sentences prior to learning an artificial language. There was a trend towards a double dissociation between native-language ERPs and their relationships to novel syntax and vocabulary learning. Individuals who exhibited a greater N400 effect when processing English semantics showed better future learning of the artificial language overall. The N400 effect was related to syntax learning via its specific relationship to vocabulary learning. In contrast, the P600 effect size when processing English syntax predicted future syntax learning but not vocabulary learning. These findings show that distinct neural signatures of native-language processing relate to dissociable abilities for learning novel semantic and syntactic information. Copyright © 2016 Elsevier Ltd. All rights reserved.

Shock Layer Radiation Modeling and Uncertainty for Mars Entry

NASA Technical Reports Server (NTRS)

Johnston, Christopher O.; Brandis, Aaron M.; Sutton, Kenneth

2012-01-01

A model for simulating nonequilibrium radiation from Mars entry shock layers is presented. A new chemical kinetic rate model is developed that provides good agreement with recent EAST and X2 shock tube radiation measurements. This model includes a CO dissociation rate that is a factor of 13 larger than the rate used widely in previous models. Uncertainties in the proposed rates are assessed along with uncertainties in translational-vibrational relaxation modeling parameters. The stagnation point radiative flux uncertainty due to these flowfield modeling parameter uncertainties is computed to vary from 50 to 200% for a range of free-stream conditions, with densities ranging from 5e-5 to 5e-4 kg/m3 and velocities ranging from of 6.3 to 7.7 km/s. These conditions cover the range of anticipated peak radiative heating conditions for proposed hypersonic inflatable aerodynamic decelerators (HIADs). Modeling parameters for the radiative spectrum are compiled along with a non-Boltzmann rate model for the dominant radiating molecules, CO, CN, and C2. A method for treating non-local absorption in the non-Boltzmann model is developed, which is shown to result in up to a 50% increase in the radiative flux through absorption by the CO 4th Positive band. The sensitivity of the radiative flux to the radiation modeling parameters is presented and the uncertainty for each parameter is assessed. The stagnation point radiative flux uncertainty due to these radiation modeling parameter uncertainties is computed to vary from 18 to 167% for the considered range of free-stream conditions. The total radiative flux uncertainty is computed as the root sum square of the flowfield and radiation parametric uncertainties, which results in total uncertainties ranging from 50 to 260%. The main contributors to these significant uncertainties are the CO dissociation rate and the CO heavy-particle excitation rates. Applying the baseline flowfield and radiation models developed in this work, the radiative heating for the Mars Pathfinder probe is predicted to be nearly 20 W/cm2. In contrast to previous studies, this value is shown to be significant relative to the convective heating.

Dynamic Sensor Tasking for Space Situational Awareness via Reinforcement Learning

NASA Astrophysics Data System (ADS)

Linares, R.; Furfaro, R.

2016-09-01

This paper studies the Sensor Management (SM) problem for optical Space Object (SO) tracking. The tasking problem is formulated as a Markov Decision Process (MDP) and solved using Reinforcement Learning (RL). The RL problem is solved using the actor-critic policy gradient approach. The actor provides a policy which is random over actions and given by a parametric probability density function (pdf). The critic evaluates the policy by calculating the estimated total reward or the value function for the problem. The parameters of the policy action pdf are optimized using gradients with respect to the reward function. Both the critic and the actor are modeled using deep neural networks (multi-layer neural networks). The policy neural network takes the current state as input and outputs probabilities for each possible action. This policy is random, and can be evaluated by sampling random actions using the probabilities determined by the policy neural network's outputs. The critic approximates the total reward using a neural network. The estimated total reward is used to approximate the gradient of the policy network with respect to the network parameters. This approach is used to find the non-myopic optimal policy for tasking optical sensors to estimate SO orbits. The reward function is based on reducing the uncertainty for the overall catalog to below a user specified uncertainty threshold. This work uses a 30 km total position error for the uncertainty threshold. This work provides the RL method with a negative reward as long as any SO has a total position error above the uncertainty threshold. This penalizes policies that take longer to achieve the desired accuracy. A positive reward is provided when all SOs are below the catalog uncertainty threshold. An optimal policy is sought that takes actions to achieve the desired catalog uncertainty in minimum time. This work trains the policy in simulation by letting it task a single sensor to "learn" from its performance. The proposed approach for the SM problem is tested in simulation and good performance is found using the actor-critic policy gradient method.

Dissociable Behavioral, Physiological and Neural Effects of Acute Glucose and Fructose Ingestion: A Pilot Study

PubMed Central

Schmidt, André; Zimak, Nina; Peterli, Ralph; Beglinger, Christoph; Borgwardt, Stefan

2015-01-01

Previous research has revealed that glucose and fructose ingestion differentially modulate release of satiation hormones. Recent studies have begun to elucidate brain-gut interactions with neuroimaging approaches such as magnetic resonance imaging (MRI), but the neural mechanism underlying different behavioral and physiological effects of glucose and fructose are unclear. In this paper, we have used resting state functional MRI to explore whether acute glucose and fructose ingestion also induced dissociable effects in the neural system. Using a cross-over, double-blind, placebo-controlled design, we compared resting state functional connectivity (rsFC) strengths within the basal ganglia/limbic network in 12 healthy lean males. Each subject was administered fructose, glucose and placebo on three separate occasions. Subsequent correlation analysis was used to examine relations between rsFC findings and plasma concentrations of satiation hormones and subjective feelings of appetite. Glucose ingestion induced significantly greater elevations in plasma glucose, insulin, GLP-1 and GIP, while feelings of fullness increased and prospective food consumption decreased relative to fructose. Furthermore, glucose increased rsFC of the left caudatus and putamen, precuneus and lingual gyrus more than fructose, whereas within the basal ganglia/limbic network, fructose increased rsFC of the left amygdala, left hippocampus, right parahippocampus, orbitofrontal cortex and precentral gyrus more than glucose. Moreover, compared to fructose, the increased rsFC after glucose positively correlated with the glucose-induced increase in insulin. Our findings suggest that glucose and fructose induce dissociable effects on rsFC within the basal ganglia/limbic network, which are probably mediated by different insulin levels. A larger study would be recommended in order to confirm these findings. PMID:26107810

Neural functional architecture and modulation during decision making under uncertainty in individuals with generalized anxiety disorder.

PubMed

Assaf, Michal; Rabany, Liron; Zertuche, Luis; Bragdon, Laura; Tolin, David; Goethe, John; Diefenbach, Gretchen

2018-06-21

Recent evidence suggests that repetitive transcranial magnetic stimulation (rTMS) might be effective in treating generalized anxiety disorder (GAD). Cognitive models of GAD highlight the role of intolerance of uncertainty (IU) in precipitating and maintaining worry, and it has been hypothesized that patients with GAD exhibit decision-making deficits under uncertain conditions. Improving understanding of the neural mechanisms underlying cognitive deficits associated with IU may lead to the identification of novel rTMS treatment targets and optimization of treatment parameters. The current report describes two interrelated studies designed to identify and verify a potential neural target for rTMS treatment of GAD. Study I explored the integrity of prefrontal cortex (PFC) and amygdala neural networks, which underlie decision making under conditions of uncertainty, in GAD. Individuals diagnosed with GAD (n = 31) and healthy controls (n = 20) completed a functional magnetic resonance imaging (fMRI) gambling task that manipulated uncertainty using high versus low error rates. In a subsequent randomized-controlled trial (Study II), a subset of the GAD sample (n = 16) completed the fMRI gambling task again after 30 sessions of active versus sham rTMS (1 Hz, right dorsolateral prefrontal cortex) to investigate the modulation of functional networks and symptoms. In Study I, participants with GAD demonstrated impairments in PFC-PFC and PFC-amygdala functional connectivity (FC) mostly during the high uncertainty condition. In Study II, one region of interest pair, dorsal anterior cingulate (ACC) - subgenual ACC, showed "normalization" of FC following active, but not sham, rTMS, and neural changes were associated with improvement in worry symptoms. These results outline a possible treatment mechanism of rTMS in GAD, and pave the way for future studies of treatment optimization. © 2018 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.

Boundedness and global robust stability analysis of delayed complex-valued neural networks with interval parameter uncertainties.

PubMed

Song, Qiankun; Yu, Qinqin; Zhao, Zhenjiang; Liu, Yurong; Alsaadi, Fuad E

2018-07-01

In this paper, the boundedness and robust stability for a class of delayed complex-valued neural networks with interval parameter uncertainties are investigated. By using Homomorphic mapping theorem, Lyapunov method and inequality techniques, sufficient condition to guarantee the boundedness of networks and the existence, uniqueness and global robust stability of equilibrium point is derived for the considered uncertain neural networks. The obtained robust stability criterion is expressed in complex-valued LMI, which can be calculated numerically using YALMIP with solver of SDPT3 in MATLAB. An example with simulations is supplied to show the applicability and advantages of the acquired result. Copyright © 2018 Elsevier Ltd. All rights reserved.

Neural dissociation of phonological and visual attention span disorders in developmental dyslexia: FMRI evidence from two case reports.

PubMed

Peyrin, C; Lallier, M; Démonet, J F; Pernet, C; Baciu, M; Le Bas, J F; Valdois, S

2012-03-01

A dissociation between phonological and visual attention (VA) span disorders has been reported in dyslexic children. This study investigates whether this cognitively-based dissociation has a neurobiological counterpart through the investigation of two cases of developmental dyslexia. LL showed a phonological disorder but preserved VA span whereas FG exhibited the reverse pattern. During a phonological rhyme judgement task, LL showed decreased activation of the left inferior frontal gyrus whereas this region was activated at the level of the controls in FG. Conversely, during a visual categorization task, FG demonstrated decreased activation of the parietal lobules whereas these regions were activated in LL as in the controls. These contrasted patterns of brain activation thus mirror the cognitive disorders' dissociation. These findings provide the first evidence for an association between distinct brain mechanisms and distinct cognitive deficits in developmental dyslexia, emphasizing the importance of taking into account the heterogeneity of the reading disorder. Copyright © 2012 Elsevier Inc. All rights reserved.

Developmental dissociation between the maturation of procedural memory and declarative memory.

PubMed

Finn, Amy S; Kalra, Priya B; Goetz, Calvin; Leonard, Julia A; Sheridan, Margaret A; Gabrieli, John D E

2016-02-01

Declarative memory and procedural memory are known to be two fundamentally different kinds of memory that are dissociable in their psychological characteristics and measurement (explicit vs. implicit) and in the neural systems that subserve each kind of memory. Declarative memory abilities are known to improve from childhood through young adulthood, but the developmental maturation of procedural memory is largely unknown. We compared 10-year-old children and young adults on measures of declarative memory and working memory capacity and on four measures of procedural memory that have been strongly dissociated from declarative memory (mirror tracing, rotary pursuit, probabilistic classification, and artificial grammar). Children had lesser declarative memory ability and lesser working memory capacity than adults, but children exhibited learning equivalent to adults on all four measures of procedural memory. Therefore, declarative memory and procedural memory are developmentally dissociable, with procedural memory being adult-like by age 10years and declarative memory continuing to mature into young adulthood. Copyright © 2015 Elsevier Inc. All rights reserved.

Passivity analysis for uncertain BAM neural networks with time delays and reaction-diffusions

NASA Astrophysics Data System (ADS)

Zhou, Jianping; Xu, Shengyuan; Shen, Hao; Zhang, Baoyong

2013-08-01

This article deals with the problem of passivity analysis for delayed reaction-diffusion bidirectional associative memory (BAM) neural networks with weight uncertainties. By using a new integral inequality, we first present a passivity condition for the nominal networks, and then extend the result to the case with linear fractional weight uncertainties. The proposed conditions are expressed in terms of linear matrix inequalities, and thus can be checked easily. Examples are provided to demonstrate the effectiveness of the proposed results.

Robust exponential stability of uncertain delayed neural networks with stochastic perturbation and impulse effects.

PubMed

Huang, Tingwen; Li, Chuandong; Duan, Shukai; Starzyk, Janusz A

2012-06-01

This paper focuses on the hybrid effects of parameter uncertainty, stochastic perturbation, and impulses on global stability of delayed neural networks. By using the Ito formula, Lyapunov function, and Halanay inequality, we established several mean-square stability criteria from which we can estimate the feasible bounds of impulses, provided that parameter uncertainty and stochastic perturbations are well-constrained. Moreover, the present method can also be applied to general differential systems with stochastic perturbation and impulses.

Instructed knowledge shapes feedback-driven aversive learning in striatum and orbitofrontal cortex, but not the amygdala

PubMed Central

Atlas, Lauren Y; Doll, Bradley B; Li, Jian; Daw, Nathaniel D; Phelps, Elizabeth A

2016-01-01

Socially-conveyed rules and instructions strongly shape expectations and emotions. Yet most neuroscientific studies of learning consider reinforcement history alone, irrespective of knowledge acquired through other means. We examined fear conditioning and reversal in humans to test whether instructed knowledge modulates the neural mechanisms of feedback-driven learning. One group was informed about contingencies and reversals. A second group learned only from reinforcement. We combined quantitative models with functional magnetic resonance imaging and found that instructions induced dissociations in the neural systems of aversive learning. Responses in striatum and orbitofrontal cortex updated with instructions and correlated with prefrontal responses to instructions. Amygdala responses were influenced by reinforcement similarly in both groups and did not update with instructions. Results extend work on instructed reward learning and reveal novel dissociations that have not been observed with punishments or rewards. Findings support theories of specialized threat-detection and may have implications for fear maintenance in anxiety. DOI: http://dx.doi.org/10.7554/eLife.15192.001 PMID:27171199

Dissociation of Subjectively Reported and Behaviorally Indexed Mind Wandering by EEG Rhythmic Activity

PubMed Central

Qin, Jungang; Perdoni, Christopher; He, Bin

2011-01-01

Inattention to current activity is ubiquitous in everyday situations. Mind wandering is an example of such a state, and its related brain areas have been examined in the literature. However, there is no clear evidence regarding neural rhythmic activities linked to mind wandering. Using a vigilance task with thought sampling and electroencephalography recording, the current study simultaneously examined neural oscillatory activities related to subjectively reported and behaviorally indexed mind wandering. By implementing time-frequency analysis, we found that subjectively reported mind wandering, relative to behaviorally indexed, showed increased gamma band activity at bilateral frontal-central areas. By means of beamformer source imaging, we found subjectively reported mind wandering within the gamma band to be characterized by increased activation in bilateral frontal cortices, supplemental motor area, paracentral cortex and right inferior temporal cortex in comparison to behaviorally indexed mind wandering. These findings dissociate subjectively reported and behaviorally indexed mind wandering and suggest that a higher degree of executive control processes are engaged in subjectively reported mind wandering. PMID:21915257

THE DYNAMICS OF MERGING CLUSTERS: A MONTE CARLO SOLUTION APPLIED TO THE BULLET AND MUSKET BALL CLUSTERS

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

Dawson, William A., E-mail: wadawson@ucdavis.edu

2013-08-01

Merging galaxy clusters have become one of the most important probes of dark matter, providing evidence for dark matter over modified gravity and even constraints on the dark matter self-interaction cross-section. To properly constrain the dark matter cross-section it is necessary to understand the dynamics of the merger, as the inferred cross-section is a function of both the velocity of the collision and the observed time since collision. While the best understanding of merging system dynamics comes from N-body simulations, these are computationally intensive and often explore only a limited volume of the merger phase space allowed by observed parametermore » uncertainty. Simple analytic models exist but the assumptions of these methods invalidate their results near the collision time, plus error propagation of the highly correlated merger parameters is unfeasible. To address these weaknesses I develop a Monte Carlo method to discern the properties of dissociative mergers and propagate the uncertainty of the measured cluster parameters in an accurate and Bayesian manner. I introduce this method, verify it against an existing hydrodynamic N-body simulation, and apply it to two known dissociative mergers: 1ES 0657-558 (Bullet Cluster) and DLSCL J0916.2+2951 (Musket Ball Cluster). I find that this method surpasses existing analytic models-providing accurate (10% level) dynamic parameter and uncertainty estimates throughout the merger history. This, coupled with minimal required a priori information (subcluster mass, redshift, and projected separation) and relatively fast computation ({approx}6 CPU hours), makes this method ideal for large samples of dissociative merging clusters.« less

Dissociation between Neural Signatures of Stimulus and Choice in Population Activity of Human V1 during Perceptual Decision-Making

PubMed Central

Choe, Kyoung Whan; Blake, Randolph

2014-01-01

Primary visual cortex (V1) forms the initial cortical representation of objects and events in our visual environment, and it distributes information about that representation to higher cortical areas within the visual hierarchy. Decades of work have established tight linkages between neural activity occurring in V1 and features comprising the retinal image, but it remains debatable how that activity relates to perceptual decisions. An actively debated question is the extent to which V1 responses determine, on a trial-by-trial basis, perceptual choices made by observers. By inspecting the population activity of V1 from human observers engaged in a difficult visual discrimination task, we tested one essential prediction of the deterministic view: choice-related activity, if it exists in V1, and stimulus-related activity should occur in the same neural ensemble of neurons at the same time. Our findings do not support this prediction: while cortical activity signifying the variability in choice behavior was indeed found in V1, that activity was dissociated from activity representing stimulus differences relevant to the task, being advanced in time and carried by a different neural ensemble. The spatiotemporal dynamics of population responses suggest that short-term priors, perhaps formed in higher cortical areas involved in perceptual inference, act to modulate V1 activity prior to stimulus onset without modifying subsequent activity that actually represents stimulus features within V1. PMID:24523561

Neural Correlates of Visual Short-term Memory Dissociate between Fragile and Working Memory Representations.

PubMed

Vandenbroucke, Annelinde R E; Sligte, Ilja G; de Vries, Jade G; Cohen, Michael X; Lamme, Victor A F

2015-12-01

Evidence is accumulating that the classic two-stage model of visual STM (VSTM), comprising iconic memory (IM) and visual working memory (WM), is incomplete. A third memory stage, termed fragile VSTM (FM), seems to exist in between IM and WM [Vandenbroucke, A. R. E., Sligte, I. G., & Lamme, V. A. F. Manipulations of attention dissociate fragile visual STM from visual working memory. Neuropsychologia, 49, 1559-1568, 2011; Sligte, I. G., Scholte, H. S., & Lamme, V. A. F. Are there multiple visual STM stores? PLoS One, 3, e1699, 2008]. Although FM can be distinguished from IM using behavioral and fMRI methods, the question remains whether FM is a weak expression of WM or a separate form of memory with its own neural signature. Here, we tested whether FM and WM in humans are supported by dissociable time-frequency features of EEG recordings. Participants performed a partial-report change detection task, from which individual differences in FM and WM capacity were estimated. These individual FM and WM capacities were correlated with time-frequency characteristics of the EEG signal before and during encoding and maintenance of the memory display. FM capacity showed negative alpha correlations over peri-occipital electrodes, whereas WM capacity was positively related, suggesting increased visual processing (lower alpha) to be related to FM capacity. Furthermore, FM capacity correlated with an increase in theta power over central electrodes during preparation and processing of the memory display, whereas WM did not. In addition to a difference in visual processing characteristics, a positive relation between gamma power and FM capacity was observed during both preparation and maintenance periods of the task. On the other hand, we observed that theta-gamma coupling was negatively correlated with FM capacity, whereas it was slightly positively correlated with WM. These data show clear differences in the neural substrates of FM versus WM and suggest that FM depends more on visual processing mechanisms compared with WM. This study thus provides novel evidence for a dissociation between different stages in VSTM.

Inferring pathological states in cortical neuron microcircuits.

PubMed

Rydzewski, Jakub; Nowak, Wieslaw; Nicosia, Giuseppe

2015-12-07

The brain activity is to a large extent determined by states of neural cortex microcircuits. Unfortunately, accuracy of results from neural circuits׳ mathematical models is often biased by the presence of uncertainties in underlying experimental data. Moreover, due to problems with uncertainties identification in a multidimensional parameters space, it is almost impossible to classify states of the neural cortex, which correspond to a particular set of the parameters. Here, we develop a complete methodology for determining uncertainties and the novel protocol for classifying all states in any neuroinformatic model. Further, we test this protocol on the mathematical, nonlinear model of such a microcircuit developed by Giugliano et al. (2008) and applied in the experimental data analysis of Huntington׳s disease. Up to now, the link between parameter domains in the mathematical model of Huntington׳s disease and the pathological states in cortical microcircuits has remained unclear. In this paper we precisely identify all the uncertainties, the most crucial input parameters and domains that drive the system into an unhealthy state. The scheme proposed here is general and can be easily applied to other mathematical models of biological phenomena. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural connectivity during reward expectation dissociates psychopathic criminals from non-criminal individuals with high impulsive/antisocial psychopathic traits

PubMed Central

von Borries, Katinka; Volman, Inge; Bulten, Berend Hendrik; Cools, Roshan; Verkes, Robbert-Jan

2016-01-01

Criminal behaviour poses a big challenge for society. A thorough understanding of the neurobiological mechanisms underlying criminality could optimize its prevention and management. Specifically,elucidating the neural mechanisms underpinning reward expectation might be pivotal to understanding criminal behaviour. So far no study has assessed reward expectation and its mechanisms in a criminal sample. To fill this gap, we assessed reward expectation in incarcerated, psychopathic criminals. We compared this group to two groups of non-criminal individuals: one with high levels and another with low levels of impulsive/antisocial traits. Functional magnetic resonance imaging was used to quantify neural responses to reward expectancy. Psychophysiological interaction analyses were performed to examine differences in functional connectivity patterns of reward-related regions. The data suggest that overt criminality is characterized, not by abnormal reward expectation per se, but rather by enhanced communication between reward-related striatal regions and frontal brain regions. We establish that incarcerated psychopathic criminals can be dissociated from non-criminal individuals with comparable impulsive/antisocial personality tendencies based on the degree to which reward-related brain regions interact with brain regions that control behaviour. The present results help us understand why some people act according to their impulsive/antisocial personality while others are able to behave adaptively despite reward-related urges. PMID:27217111

Functional dissociation of the left and right fusiform gyrus in self-face recognition.

PubMed

Ma, Yina; Han, Shihui

2012-10-01

It is well known that the fusiform gyrus is engaged in face perception, such as the processes of face familiarity and identity. However, the functional role of the fusiform gyrus in face processing related to high-level social cognition remains unclear. The current study assessed the functional role of individually defined fusiform face area (FFA) in the processing of self-face physical properties and self-face identity. We used functional magnetic resonance imaging to monitor neural responses to rapidly presented face stimuli drawn from morph continua between self-face (Morph 100%) and a gender-matched friend's face (Morph 0%) in a face recognition task. Contrasting Morph 100% versus Morph 60% that differed in self-face physical properties but were both recognized as the self uncovered neural activity sensitive to self-face physical properties in the left FFA. Contrasting Morphs 50% that were recognized as the self versus a friend on different trials revealed neural modulations associated with self-face identity in the right FFA. Moreover, the right FFA activity correlated with the frequency of recognizing Morphs 50% as the self. Our results provide evidence for functional dissociations of the left and right FFAs in the representations of self-face physical properties and self-face identity. Copyright © 2011 Wiley Periodicals, Inc.

Dissociable neural systems supporting knowledge about human character and appearance in ourselves and others.

PubMed

Moran, Joseph M; Lee, Su Mei; Gabrieli, John D E

2011-09-01

Functional neuroimaging has identified a neural system comprising posterior cingulate (pCC) and medial prefrontal (mPFC) cortices that appears to mediate self-referential thought. It is unclear whether the two components of this system mediate similar or different psychological processes, and how specific this system is for self relative to others. In an fMRI study, we compared brain responses for evaluation of character (e.g., honest) versus appearance (e.g., svelte) for oneself, one's mother (a close other), and President Bush (a distant other). There was a double dissociation between dorsal mPFC, which was more engaged for character than appearance judgments, and pCC, which was more engaged for appearance than character judgments. A ventral region of mPFC was engaged for judgments involving one's own character and appearance, and one's mother's character, but not her appearance. A follow-up behavioral study indicated that participants rate their own character and appearance, and their mother's character, but not her appearance, as important in their self-concept. This suggests that ventral mPFC activation reflects its role in processing information relevant to the self, but not limited to the self. Thus, specific neural systems mediate specific aspects of thinking about character and appearance in oneself and in others.

Robust model predictive control of nonlinear systems with unmodeled dynamics and bounded uncertainties based on neural networks.

PubMed

Yan, Zheng; Wang, Jun

2014-03-01

This paper presents a neural network approach to robust model predictive control (MPC) for constrained discrete-time nonlinear systems with unmodeled dynamics affected by bounded uncertainties. The exact nonlinear model of underlying process is not precisely known, but a partially known nominal model is available. This partially known nonlinear model is first decomposed to an affine term plus an unknown high-order term via Jacobian linearization. The linearization residue combined with unmodeled dynamics is then modeled using an extreme learning machine via supervised learning. The minimax methodology is exploited to deal with bounded uncertainties. The minimax optimization problem is reformulated as a convex minimization problem and is iteratively solved by a two-layer recurrent neural network. The proposed neurodynamic approach to nonlinear MPC improves the computational efficiency and sheds a light for real-time implementability of MPC technology. Simulation results are provided to substantiate the effectiveness and characteristics of the proposed approach.

Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

PubMed

Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

Application of Hierarchical Dissociated Neural Network in Closed-Loop Hybrid System Integrating Biological and Mechanical Intelligence

PubMed Central

Zhang, Bin; Wang, Yuechao; Li, Hongyi

2015-01-01

Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including ‘random’ and ‘4Q’ (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the ‘4Q’ cultures presented absolutely different activities, and the robot controlled by the ‘4Q’ network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems. PMID:25992579

Chaos control of the brushless direct current motor using adaptive dynamic surface control based on neural network with the minimum weights.

PubMed

Luo, Shaohua; Wu, Songli; Gao, Ruizhen

2015-07-01

This paper investigates chaos control for the brushless DC motor (BLDCM) system by adaptive dynamic surface approach based on neural network with the minimum weights. The BLDCM system contains parameter perturbation, chaotic behavior, and uncertainty. With the help of radial basis function (RBF) neural network to approximate the unknown nonlinear functions, the adaptive law is established to overcome uncertainty of the control gain. By introducing the RBF neural network and adaptive technology into the dynamic surface control design, a robust chaos control scheme is developed. It is proved that the proposed control approach can guarantee that all signals in the closed-loop system are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation results are provided to show that the proposed approach works well in suppressing chaos and parameter perturbation.

Chaos control of the brushless direct current motor using adaptive dynamic surface control based on neural network with the minimum weights

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

Luo, Shaohua; Department of Mechanical Engineering, Chongqing Aerospace Polytechnic, Chongqing, 400021; Wu, Songli

2015-07-15

This paper investigates chaos control for the brushless DC motor (BLDCM) system by adaptive dynamic surface approach based on neural network with the minimum weights. The BLDCM system contains parameter perturbation, chaotic behavior, and uncertainty. With the help of radial basis function (RBF) neural network to approximate the unknown nonlinear functions, the adaptive law is established to overcome uncertainty of the control gain. By introducing the RBF neural network and adaptive technology into the dynamic surface control design, a robust chaos control scheme is developed. It is proved that the proposed control approach can guarantee that all signals in themore » closed-loop system are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation results are provided to show that the proposed approach works well in suppressing chaos and parameter perturbation.« less

Posture-based processing in visual short-term memory for actions.

PubMed

Vicary, Staci A; Stevens, Catherine J

2014-01-01

Visual perception of human action involves both form and motion processing, which may rely on partially dissociable neural networks. If form and motion are dissociable during visual perception, then they may also be dissociable during their retention in visual short-term memory (VSTM). To elicit form-plus-motion and form-only processing of dance-like actions, individual action frames can be presented in the correct or incorrect order. The former appears coherent and should elicit action perception, engaging both form and motion pathways, whereas the latter appears incoherent and should elicit posture perception, engaging form pathways alone. It was hypothesized that, if form and motion are dissociable in VSTM, then recognition of static body posture should be better after viewing incoherent than after viewing coherent actions. However, as VSTM is capacity limited, posture-based encoding of actions may be ineffective with increased number of items or frames. Using a behavioural change detection task, recognition of a single test posture was significantly more likely after studying incoherent than after studying coherent stimuli. However, this effect only occurred for spans of two (but not three) items and for stimuli with five (but not nine) frames. As in perception, posture and motion are dissociable in VSTM.

Water dissociating on rigid Ni(100): A quantum dynamics study on a full-dimensional potential energy surface

NASA Astrophysics Data System (ADS)

Liu, Tianhui; Chen, Jun; Zhang, Zhaojun; Shen, Xiangjian; Fu, Bina; Zhang, Dong H.

2018-04-01

We constructed a nine-dimensional (9D) potential energy surface (PES) for the dissociative chemisorption of H2O on a rigid Ni(100) surface using the neural network method based on roughly 110 000 energies obtained from extensive density functional theory (DFT) calculations. The resulting PES is accurate and smooth, based on the small fitting errors and the good agreement between the fitted PES and the direct DFT calculations. Time dependent wave packet calculations also showed that the PES is very well converged with respect to the fitting procedure. The dissociation probabilities of H2O initially in the ground rovibrational state from 9D quantum dynamics calculations are quite different from the site-specific results from the seven-dimensional (7D) calculations, indicating the importance of full-dimensional quantum dynamics to quantitatively characterize this gas-surface reaction. It is found that the validity of the site-averaging approximation with exact potential holds well, where the site-averaging dissociation probability over 15 fixed impact sites obtained from 7D quantum dynamics calculations can accurately approximate the 9D dissociation probability for H2O in the ground rovibrational state.

Approach–Avoidance Processes Contribute to Dissociable Impacts of Risk and Loss on Choice

PubMed Central

Wright, Nicholas D.; Symmonds, Mkael; Hodgson, Karen; Fitzgerald, Thomas H. B.; Crawford, Bonni; Dolan, Raymond J.

2013-01-01

Value-based choices are influenced both by risk in potential outcomes and by whether outcomes reflect potential gains or losses. These variables are held to be related in a specific fashion, manifest in risk aversion for gains and risk seeking for losses. Instead, we hypothesized that there are independent impacts of risk and loss on choice such that, depending on context, subjects can show either risk aversion for gains and risk seeking for losses or the exact opposite. We demonstrate this independence in a gambling task, by selectively reversing a loss-induced effect (causing more gambling for gains than losses and the reverse) while leaving risk aversion unaffected. Consistent with these dissociable behavioral impacts of risk and loss, fMRI data revealed dissociable neural correlates of these variables, with parietal cortex tracking risk and orbitofrontal cortex and striatum tracking loss. Based on our neural data, we hypothesized that risk and loss influence action selection through approach–avoidance mechanisms, a hypothesis supported in an experiment in which we show valence and risk-dependent reaction time effects in line with this putative mechanism. We suggest that in the choice process risk and loss can independently engage approach–avoidance mechanisms. This can provide a novel explanation for how risk influences action selection and explains both classically described choice behavior as well as behavioral patterns not predicted by existing theory. PMID:22593069

The neural basis of body form and body action agnosia.

PubMed

Moro, Valentina; Urgesi, Cosimo; Pernigo, Simone; Lanteri, Paola; Pazzaglia, Mariella; Aglioti, Salvatore Maria

2008-10-23

Visual analysis of faces and nonfacial body stimuli brings about neural activity in different cortical areas. Moreover, processing body form and body action relies on distinct neural substrates. Although brain lesion studies show specific face processing deficits, neuropsychological evidence for defective recognition of nonfacial body parts is lacking. By combining psychophysics studies with lesion-mapping techniques, we found that lesions of ventromedial, occipitotemporal areas induce face and body recognition deficits while lesions involving extrastriate body area seem causatively associated with impaired recognition of body but not of face and object stimuli. We also found that body form and body action recognition deficits can be double dissociated and are causatively associated with lesions to extrastriate body area and ventral premotor cortex, respectively. Our study reports two category-specific visual deficits, called body form and body action agnosia, and highlights their neural underpinnings.

Dissociating Visual Form from Lexical Frequency Using Japanese

ERIC Educational Resources Information Center

Twomey, Tae; Duncan, Keith J. Kawabata; Hogan, John S.; Morita, Kenji; Umeda, Kazumasa; Sakai, Katsuyuki; Devlin, Joseph T.

2013-01-01

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,…

Aerial robot intelligent control method based on back-stepping

NASA Astrophysics Data System (ADS)

Zhou, Jian; Xue, Qian

2018-05-01

The aerial robot is characterized as strong nonlinearity, high coupling and parameter uncertainty, a self-adaptive back-stepping control method based on neural network is proposed in this paper. The uncertain part of the aerial robot model is compensated online by the neural network of Cerebellum Model Articulation Controller and robust control items are designed to overcome the uncertainty error of the system during online learning. At the same time, particle swarm algorithm is used to optimize and fix parameters so as to improve the dynamic performance, and control law is obtained by the recursion of back-stepping regression. Simulation results show that the designed control law has desired attitude tracking performance and good robustness in case of uncertainties and large errors in the model parameters.

Reduced amygdala reactivity and impaired working memory during dissociation in borderline personality disorder.

PubMed

Krause-Utz, Annegret; Winter, Dorina; Schriner, Friederike; Chiu, Chui-De; Lis, Stefanie; Spinhoven, Philip; Bohus, Martin; Schmahl, Christian; Elzinga, Bernet M

2018-06-01

Affective hyper-reactivity and impaired cognitive control of emotional material are core features of borderline personality disorder (BPD). A high percentage of individuals with BPD experience stress-related dissociation, including emotional numbing and memory disruptions. So far little is known about how dissociation influences the neural processing of emotional material in the context of a working memory task in BPD. We aimed to investigate whole-brain activity and amygdala functional connectivity (FC) during an Emotional Working Memory Task (EWMT) after dissociation induction in un-medicated BPD patients compared to healthy controls (HC). Using script-driven imagery, dissociation was induced in 17 patients ('BPD_D'), while 12 patients ('BPD_N') and 18 HC were exposed to neutral scripts during fMRI. Afterwards, participants performed the EWMT with neutral vs. negative IAPS pictures vs. no distractors. Main outcome measures were behavioral performance (reaction times, errors) and whole-brain activity during the EWMT. Psychophysiological interaction analysis was used to examine amygdala connectivity during emotional distraction. BPD patients after dissociation induction showed overall WM impairments, a deactivation in bilateral amygdala, and lower activity in left cuneus, lingual gyrus, and posterior cingulate than BPD_N, along with stronger left inferior frontal gyrus activity than HC. Furthermore, reduced amygdala FC with fusiform gyrus and stronger amygdala FC with right middle/superior temporal gyrus and left inferior parietal lobule was observed in BPD_D. Findings suggest that dissociation affects reactivity to emotionally salient material and WM. Altered activity in areas associated with emotion processing, memory, and self-referential processes may contribute to dissociative states in BPD.

Finite-time robust stabilization of uncertain delayed neural networks with discontinuous activations via delayed feedback control.

PubMed

Wang, Leimin; Shen, Yi; Sheng, Yin

2016-04-01

This paper is concerned with the finite-time robust stabilization of delayed neural networks (DNNs) in the presence of discontinuous activations and parameter uncertainties. By using the nonsmooth analysis and control theory, a delayed controller is designed to realize the finite-time robust stabilization of DNNs with discontinuous activations and parameter uncertainties, and the upper bound of the settling time functional for stabilization is estimated. Finally, two examples are provided to demonstrate the effectiveness of the theoretical results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Uncertainty and Anticipation in Anxiety

PubMed Central

Grupe, Dan W.; Nitschke, Jack B.

2014-01-01

Uncertainty about a possible future threat disrupts our ability to avoid it or to mitigate its negative impact, and thus results in anxiety. Here, we focus the broad literature on the neurobiology of anxiety through the lens of uncertainty. We identify five processes essential for adaptive anticipatory responses to future threat uncertainty, and propose that alterations to the neural instantiation of these processes results in maladaptive responses to uncertainty in pathological anxiety. This framework has the potential to advance the classification, diagnosis, and treatment of clinical anxiety. PMID:23783199

Neural-adaptive control of single-master-multiple-slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainties.

PubMed

Li, Zhijun; Su, Chun-Yi

2013-09-01

In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies.

A neural net approach to space vehicle guidance

NASA Technical Reports Server (NTRS)

Caglayan, Alper K.; Allen, Scott M.

1990-01-01

The space vehicle guidance problem is formulated using a neural network approach, and the appropriate neural net architecture for modeling optimum guidance trajectories is investigated. In particular, an investigation is made of the incorporation of prior knowledge about the characteristics of the optimal guidance solution into the neural network architecture. The online classification performance of the developed network is demonstrated using a synthesized network trained with a database of optimum guidance trajectories. Such a neural-network-based guidance approach can readily adapt to environment uncertainties such as those encountered by an AOTV during atmospheric maneuvers.

Sequential neural processes in abacus mental addition: an EEG and FMRI case study.

PubMed

Ku, Yixuan; Hong, Bo; Zhou, Wenjing; Bodner, Mark; Zhou, Yong-Di

2012-01-01

Abacus experts are able to mentally calculate multi-digit numbers rapidly. Some behavioral and neuroimaging studies have suggested a visuospatial and visuomotor strategy during abacus mental calculation. However, no study up to now has attempted to dissociate temporally the visuospatial neural process from the visuomotor neural process during abacus mental calculation. In the present study, an abacus expert performed the mental addition tasks (8-digit and 4-digit addends presented in visual or auditory modes) swiftly and accurately. The 100% correct rates in this expert's task performance were significantly higher than those of ordinary subjects performing 1-digit and 2-digit addition tasks. ERPs, EEG source localizations, and fMRI results taken together suggested visuospatial and visuomotor processes were sequentially arranged during the abacus mental addition with visual addends and could be dissociated from each other temporally. The visuospatial transformation of the numbers, in which the superior parietal lobule was most likely involved, might occur first (around 380 ms) after the onset of the stimuli. The visuomotor processing, in which the superior/middle frontal gyri were most likely involved, might occur later (around 440 ms). Meanwhile, fMRI results suggested that neural networks involved in the abacus mental addition with auditory stimuli were similar to those in the visual abacus mental addition. The most prominently activated brain areas in both conditions included the bilateral superior parietal lobules (BA 7) and bilateral middle frontal gyri (BA 6). These results suggest a supra-modal brain network in abacus mental addition, which may develop from normal mental calculation networks.

Widespread neural oscillations in the delta band dissociate rule convergence from rule divergence during creative idea generation.

PubMed

Boot, Nathalie; Baas, Matthijs; Mühlfeld, Elisabeth; de Dreu, Carsten K W; van Gaal, Simon

2017-09-01

Critical to creative cognition and performance is both the generation of multiple alternative solutions in response to open-ended problems (divergent thinking) and a series of cognitive operations that converges on the correct or best possible answer (convergent thinking). Although the neural underpinnings of divergent and convergent thinking are still poorly understood, several electroencephalography (EEG) studies point to differences in alpha-band oscillations between these thinking modes. We reason that, because most previous studies employed typical block designs, these pioneering findings may mainly reflect the more sustained aspects of creative processes that extend over longer time periods, and that still much is unknown about the faster-acting neural mechanisms that dissociate divergent from convergent thinking during idea generation. To this end, we developed a new event-related paradigm, in which we measured participants' tendency to implicitly follow a rule set by examples, versus breaking that rule, during the generation of novel names for specific categories (e.g., pasta, planets). This approach allowed us to compare the oscillatory dynamics of rule convergent and rule divergent idea generation and at the same time enabled us to measure spontaneous switching between these thinking modes on a trial-to-trial basis. We found that, relative to more systematic, rule convergent thinking, rule divergent thinking was associated with widespread decreases in delta band activity. Therefore, this study contributes to advancing our understanding of the neural underpinnings of creativity by addressing some methodological challenges that neuroscientific creativity research faces. Copyright © 2017 Elsevier Ltd. All rights reserved.

Neural correlates of humor detection and appreciation.

PubMed

Moran, Joseph M; Wig, Gagan S; Adams, Reginald B; Janata, Petr; Kelley, William M

2004-03-01

Humor is a uniquely human quality whose neural substrates remain enigmatic. The present report combined dynamic, real-life content and event-related functional magnetic resonance imaging (fMRI) to dissociate humor detection ("getting the joke") from humor appreciation (the affective experience of mirth). During scanning, subjects viewed full-length episodes of the television sitcoms Seinfeld or The Simpsons. Brain activity time-locked to humor detection moments revealed increases in left inferior frontal and posterior temporal cortices, whereas brain activity time-locked to moments of humor appreciation revealed increases in bilateral regions of insular cortex and the amygdala. These findings provide evidence that humor depends critically upon extant neural systems important for resolving incongruities (humor detection) and for the expression of affect (humor appreciation).

Dissociable effects of motivation and expectancy on conflict processing: an fMRI study.

PubMed

Soutschek, Alexander; Stelzel, Christine; Paschke, Lena; Walter, Henrik; Schubert, Torsten

2015-02-01

Previous studies suggest that both motivation and task difficulty expectations activate brain regions associated with cognitive control. However, it remains an open question whether motivational and cognitive determinants of control have similar or dissociable impacts on conflict processing on a neural level. The current study tested the effects of motivation and conflict expectancy on activity in regions related to processing of the target and the distractor information. Participants performed a picture-word interference task in which we manipulated the size of performance-dependent monetary rewards (level of motivation) and the ratio of congruent to incongruent trials within a block (level of conflict expectancy). Our results suggest that motivation improves conflict processing by facilitating task-relevant stimulus processing and task difficulty expectations mainly modulate the processing of distractor information. We conclude that motivation and conflict expectancy engage dissociable control strategies during conflict resolution.

Dissociating Stimulus-Set and Response-Set in the Context of Task-Set Switching

PubMed Central

Kieffaber, Paul D.; Kruschke, John K.; Cho, Raymond Y.; Walker, Philip M.; Hetrick, William P.

2014-01-01

The primary aim of the present research was to determine how stimulus-set and response-set components of task-set contribute to switch costs and conflict processing. Three experiments are described wherein participants completed an explicitly cued task-switching procedure. Experiment 1 established that task switches requiring a reconfiguration of both stimulus- and response-set incurred larger residual switch costs than task switches requiring the reconfiguration of stimulus-set alone. Between-task interference was also drastically reduced for response-set conflict compared with stimulus-set conflict. A second experiment replicated these findings and demonstrated that stimulus- and response-conflict have dissociable effects on the “decision time” and “motor time” components of total response time. Finally, a third experiment replicated Experiment 2 and demonstrated that the stimulus- and response- components of task switching and conflict processing elicit dissociable neural activity as evidence by event-related brain potentials. PMID:22984990

Representation of grammatical categories of words in the brain.

PubMed

Hillis, A E; Caramazza, A

1995-01-01

We report the performance of a patient who, as a consequence of left frontal and temporoparietal strokes, makes far more errors on nouns than on verbs in spoken output tasks, but makes far more errors on verbs than on nouns in written input tasks. This double dissociation within a single patient with respect to grammatical category provides evidence for the hypothesis that phonological and orthographic representations of nouns and verbs are processed by independent neural mechanisms. Furthermore, the opposite dissociation in the verbal output modality, an advantage for nouns over verbs in spoken tasks, by a different patient using the same stimuli has also been reported (Caramazza & Hillis, 1991). This double dissociation across patients on the same task indicates that results cannot be ascribed to "greater difficulty" with one type of stimulus, and provides further evidence for the view that grammatical category information is an important organizational principle of lexical knowledge in the brain.

Robust fixed-time synchronization of delayed Cohen-Grossberg neural networks.

PubMed

Wan, Ying; Cao, Jinde; Wen, Guanghui; Yu, Wenwu

2016-01-01

The fixed-time master-slave synchronization of Cohen-Grossberg neural networks with parameter uncertainties and time-varying delays is investigated. Compared with finite-time synchronization where the convergence time relies on the initial synchronization errors, the settling time of fixed-time synchronization can be adjusted to desired values regardless of initial conditions. Novel synchronization control strategy for the slave neural network is proposed. By utilizing the Filippov discontinuous theory and Lyapunov stability theory, some sufficient schemes are provided for selecting the control parameters to ensure synchronization with required convergence time and in the presence of parameter uncertainties. Corresponding criteria for tuning control inputs are also derived for the finite-time synchronization. Finally, two numerical examples are given to illustrate the validity of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Single neural adaptive controller and neural network identifier based on PSO algorithm for spherical actuators with 3D magnet array

NASA Astrophysics Data System (ADS)

Yan, Liang; Zhang, Lu; Zhu, Bo; Zhang, Jingying; Jiao, Zongxia

2017-10-01

Permanent magnet spherical actuator (PMSA) is a multi-variable featured and inter-axis coupled nonlinear system, which unavoidably compromises its motion control implementation. Uncertainties such as external load and friction torque of ball bearing and manufacturing errors also influence motion performance significantly. Therefore, the objective of this paper is to propose a controller based on a single neural adaptive (SNA) algorithm and a neural network (NN) identifier optimized with a particle swarm optimization (PSO) algorithm to improve the motion stability of PMSA with three-dimensional magnet arrays. The dynamic model and computed torque model are formulated for the spherical actuator, and a dynamic decoupling control algorithm is developed. By utilizing the global-optimization property of the PSO algorithm, the NN identifier is trained to avoid locally optimal solution and achieve high-precision compensations to uncertainties. The employment of the SNA controller helps to reduce the effect of compensation errors and convert the system to a stable one, even if there is difference between the compensations and uncertainties due to external disturbances. A simulation model is established, and experiments are conducted on the research prototype to validate the proposed control algorithm. The amplitude of the parameter perturbation is set to 5%, 10%, and 15%, respectively. The strong robustness of the proposed hybrid algorithm is validated by the abundant simulation data. It shows that the proposed algorithm can effectively compensate the influence of uncertainties and eliminate the effect of inter-axis couplings of the spherical actuator.

Dissociating 'what' and 'how' in visual form agnosia: a computational investigation.

PubMed

Vecera, S P

2002-01-01

Patients with visual form agnosia exhibit a profound impairment in shape perception (what an object is) coupled with intact visuomotor functions (how to act on an object), demonstrating a dissociation between visual perception and action. How can these patients act on objects that they cannot perceive? Although two explanations of this 'what-how' dissociation have been offered, each explanation has shortcomings. A 'pathway information' account of the 'what-how' dissociation is presented in this paper. This account hypothesizes that 'where' and 'how' tasks require less information than 'what' tasks, thereby allowing 'where/how' to remain relatively spared in the face of neurological damage. Simulations with a neural network model test the predictions of the pathway information account. Following damage to an input layer common to the 'what' and 'where/how' pathways, the model performs object identification more poorly than spatial localization. Thus, the model offers a parsimonious explanation of differential 'what-how' performance in visual form agnosia. The simulation results are discussed in terms of their implications for visual form agnosia and other neuropsychological syndromes.

Religious Fundamentalism Modulates Neural Responses to Error-Related Words: The Role of Motivation Toward Closure.

PubMed

Kossowska, Małgorzata; Szwed, Paulina; Wyczesany, Miroslaw; Czarnek, Gabriela; Wronka, Eligiusz

2018-01-01

Examining the relationship between brain activity and religious fundamentalism, this study explores whether fundamentalist religious beliefs increase responses to error-related words among participants intolerant to uncertainty (i.e., high in the need for closure) in comparison to those who have a high degree of toleration for uncertainty (i.e., those who are low in the need for closure). We examine a negative-going event-related brain potentials occurring 400 ms after stimulus onset (the N400) due to its well-understood association with the reactions to emotional conflict. Religious fundamentalism and tolerance of uncertainty were measured on self-report measures, and electroencephalographic neural reactivity was recorded as participants were performing an emotional Stroop task. In this task, participants read neutral words and words related to uncertainty, errors, and pondering, while being asked to name the color of the ink with which the word is written. The results confirm that among people who are intolerant of uncertainty (i.e., those high in the need for closure), religious fundamentalism is associated with an increased N400 on error-related words compared with people who tolerate uncertainty well (i.e., those low in the need for closure).

Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural fault tolerant control

NASA Astrophysics Data System (ADS)

Habibi, Hamed; Rahimi Nohooji, Hamed; Howard, Ian

2017-09-01

Power maximization has always been a practical consideration in wind turbines. The question of how to address optimal power capture, especially when the system dynamics are nonlinear and the actuators are subject to unknown faults, is significant. This paper studies the control methodology for variable-speed variable-pitch wind turbines including the effects of uncertain nonlinear dynamics, system fault uncertainties, and unknown external disturbances. The nonlinear model of the wind turbine is presented, and the problem of maximizing extracted energy is formulated by designing the optimal desired states. With the known system, a model-based nonlinear controller is designed; then, to handle uncertainties, the unknown nonlinearities of the wind turbine are estimated by utilizing radial basis function neural networks. The adaptive neural fault tolerant control is designed passively to be robust on model uncertainties, disturbances including wind speed and model noises, and completely unknown actuator faults including generator torque and pitch actuator torque. The Lyapunov direct method is employed to prove that the closed-loop system is uniformly bounded. Simulation studies are performed to verify the effectiveness of the proposed method.

Model-based choices involve prospective neural activity

PubMed Central

Doll, Bradley B.; Duncan, Katherine D.; Simon, Dylan A.; Shohamy, Daphna; Daw, Nathaniel D.

2015-01-01

Decisions may arise via “model-free” repetition of previously reinforced actions, or by “model-based” evaluation, which is widely thought to follow from prospective anticipation of action consequences using a learned map or model. While choices and neural correlates of decision variables sometimes reflect knowledge of their consequences, it remains unclear whether this actually arises from prospective evaluation. Using functional MRI and a sequential reward-learning task in which paths contained decodable object categories, we found that humans’ model-based choices were associated with neural signatures of future paths observed at decision time, suggesting a prospective mechanism for choice. Prospection also covaried with the degree of model-based influences on neural correlates of decision variables, and was inversely related to prediction error signals thought to underlie model-free learning. These results dissociate separate mechanisms underlying model-based and model-free evaluation and support the hypothesis that model-based influences on choices and neural decision variables result from prospection. PMID:25799041

Developmental Dissociation in the Neural Responses to Simple Multiplication and Subtraction Problems

ERIC Educational Resources Information Center

Prado, Jérôme; Mutreja, Rachna; Booth, James R.

2014-01-01

Mastering single-digit arithmetic during school years is commonly thought to depend upon an increasing reliance on verbally memorized facts. An alternative model, however, posits that fluency in single-digit arithmetic might also be achieved via the increasing use of efficient calculation procedures. To test between these hypotheses, we used a…

Explicit Pre-Training Instruction Does Not Improve Implicit Perceptual-Motor Sequence Learning

ERIC Educational Resources Information Center

Sanchez, Daniel J.; Reber, Paul J.

2013-01-01

Memory systems theory argues for separate neural systems supporting implicit and explicit memory in the human brain. Neuropsychological studies support this dissociation, but empirical studies of cognitively healthy participants generally observe that both kinds of memory are acquired to at least some extent, even in implicit learning tasks. A key…

Developmental Dyslexia in Chinese and English Populations: Dissociating the Effect of Dyslexia from Language Differences

ERIC Educational Resources Information Center

Hu, Wei; Lee, Hwee Ling; Zhang, Qiang; Liu, Tao; Geng, Li Bo; Seghier, Mohamed L.; Shakeshaft, Clare; Twomey, Tae; Green, David W.; Yang, Yi Ming; Price, Cathy J.

2010-01-01

Previous neuroimaging studies have suggested that developmental dyslexia has a different neural basis in Chinese and English populations because of known differences in the processing demands of the Chinese and English writing systems. Here, using functional magnetic resonance imaging, we provide the first direct statistically based investigation…

Neural mechanisms underlying urgent and evaluative behaviors: An fMRI study on the interaction of automatic and controlled processes.

PubMed

Megías, Alberto; Navas, Juan Francisco; Petrova, Dafina; Cándido, Antonio; Maldonado, Antonio; Garcia-Retamero, Rocio; Catena, Andrés

2015-08-01

Dual-process theories have dominated the study of risk perception and risk-taking over the last two decades. However, there is a lack of objective brain-level evidence supporting the two systems of processing in every-day risky behavior. To address this issue, we propose the dissociation between evaluative and urgent behaviors as evidence of dual processing in risky driving situations. Our findings show a dissociation of evaluative and urgent behavior both at the behavioral and neural level. fMRI data showed an increase of activation in areas implicated in motor programming, emotional processing, and visuomotor integration in urgent behavior compared to evaluative behavior. These results support a more automatic processing of risk in urgent tasks, relying mainly on heuristics and experiential appraisal. The urgent task, which is characterized by strong time pressure and the possibility for negative consequences among others factors, creates a suitable context for the experiential-affective system to guide the decision-making process. Moreover, we observed greater frontal activation in the urgent task, suggesting the participation of cognitive control in safe behaviors. The findings of this research are relevant for the study of the neural mechanisms underlying dual process models in risky perception and decision-making, especially because of their proximity to everyday activities. © 2015 Wiley Periodicals, Inc.

Separate Brain Circuits Support Integrative and Semantic Priming in the Human Language System.

PubMed

Feng, Gangyi; Chen, Qi; Zhu, Zude; Wang, Suiping

2016-07-01

Semantic priming is a crucial phenomenon to study the organization of semantic memory. A novel type of priming effect, integrative priming, has been identified behaviorally, whereby a prime word facilitates recognition of a target word when the 2 concepts can be combined to form a unitary representation. We used both functional and anatomical imaging approaches to investigate the neural substrates supporting such integrative priming, and compare them with those in semantic priming. Similar behavioral priming effects for both semantic (Bread-Cake) and integrative conditions (Cherry-Cake) were observed when compared with an unrelated condition. However, a clearly dissociated brain response was observed between these 2 types of priming. The semantic-priming effect was localized to the posterior superior temporal and middle temporal gyrus. In contrast, the integrative-priming effect localized to the left anterior inferior frontal gyrus and left anterior temporal cortices. Furthermore, fiber tractography showed that the integrative-priming regions were connected via uncinate fasciculus fiber bundle forming an integrative circuit, whereas the semantic-priming regions connected to the posterior frontal cortex via separated pathways. The results point to dissociable neural pathways underlying the 2 distinct types of priming, illuminating the neural circuitry organization of semantic representation and integration. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Uncertainty during Anticipation Modulates Neural Responses to Aversion in Human Insula and Amygdala

PubMed Central

Sarinopoulos, I.; Grupe, D. W.; Mackiewicz, K. L.; Herrington, J. D.; Lor, M.; Steege, E. E.

2010-01-01

Uncertainty about potential negative future outcomes can cause stress and is a central feature of anxiety disorders. The stress and anxiety associated with uncertain situations may lead individuals to overestimate the frequency with which uncertain cues are followed by negative outcomes, an example of covariation bias. Using functional magnetic resonance imaging, we found that uncertainty-related expectations modulated neural responses to aversion. Insula and amygdala responses to aversive pictures were larger after an uncertain cue (that preceded aversive or neutral pictures) than a certain cue (that always preceded aversive pictures). Anticipatory anterior cingulate cortex (ACC) activity elicited by the cues was inversely associated with the insula and amygdala responses to aversive pictures following the cues. Nearly 75% of subjects overestimated the frequency of aversive pictures following uncertain cues, and ACC and insula activity predicted this uncertainty-related covariation bias. Findings provide the first evidence of the brain mechanisms of covariation bias and highlight the temporal dynamics of ACC, insula, and amygdala recruitment for processing aversion in the context of uncertainty. PMID:19679543

Developing neuronal networks: Self-organized criticality predicts the future

NASA Astrophysics Data System (ADS)

Pu, Jiangbo; Gong, Hui; Li, Xiangning; Luo, Qingming

2013-01-01

Self-organized criticality emerged in neural activity is one of the key concepts to describe the formation and the function of developing neuronal networks. The relationship between critical dynamics and neural development is both theoretically and experimentally appealing. However, whereas it is well-known that cortical networks exhibit a rich repertoire of activity patterns at different stages during in vitro maturation, dynamical activity patterns through the entire neural development still remains unclear. Here we show that a series of metastable network states emerged in the developing and ``aging'' process of hippocampal networks cultured from dissociated rat neurons. The unidirectional sequence of state transitions could be only observed in networks showing power-law scaling of distributed neuronal avalanches. Our data suggest that self-organized criticality may guide spontaneous activity into a sequential succession of homeostatically-regulated transient patterns during development, which may help to predict the tendency of neural development at early ages in the future.

From sensation to perception: Using multivariate classification of visual illusions to identify neural correlates of conscious awareness in space and time.

PubMed

Hogendoorn, Hinze

2015-01-01

An important goal of cognitive neuroscience is understanding the neural underpinnings of conscious awareness. Although the low-level processing of sensory input is well understood in most modalities, it remains a challenge to understand how the brain translates such input into conscious awareness. Here, I argue that the application of multivariate pattern classification techniques to neuroimaging data acquired while observers experience perceptual illusions provides a unique way to dissociate sensory mechanisms from mechanisms underlying conscious awareness. Using this approach, it is possible to directly compare patterns of neural activity that correspond to the contents of awareness, independent from changes in sensory input, and to track these neural representations over time at high temporal resolution. I highlight five recent studies using this approach, and provide practical considerations and limitations for future implementations.

The Specialization of Function: Cognitive and Neural Perspectives

PubMed Central

Mahon, Bradford Z.; Cantlon, Jessica F.

2014-01-01

A unifying theme that cuts across all research areas and techniques in the cognitive and brain sciences is whether there is specialization of function at levels of processing that are ‘abstracted away’ from sensory inputs and motor outputs. Any theory that articulates claims about specialization of function in the mind/brain confronts the following types of interrelated questions, each of which carries with it certain theoretical commitments. What methods are appropriate for decomposing complex cognitive and neural processes into their constituent parts? How do cognitive processes map onto neural processes, and at what resolution are they related? What types of conclusions can be drawn about the structure of mind from dissociations observed at the neural level, and vice versa? The contributions that form this Special Issue of Cognitive Neuropsychology represent recent reflections on these and other issues from leading researchers in different areas of the cognitive and brain sciences. PMID:22185234

The Interplay between Uncertainty Monitoring and Working Memory: Can Metacognition Become Automatic?

PubMed Central

Coutinho, Mariana V. C.; Redford, Joshua S.; Church, Barbara A.; Zakrzewski, Alexandria C.; Couchman, Justin J.; Smith, J. David

2016-01-01

The uncertainty response has grounded the study of metacognition in nonhuman animals. Recent research has explored the processes supporting uncertainty monitoring in monkeys. It revealed that uncertainty responding in contrast to perceptual responding depends on significant working memory resources. The aim of the present study was to expand this research by examining whether uncertainty monitoring is also working memory demanding in humans. To explore this issue, human participants were tested with or without a cognitive load on a psychophysical discrimination task including either an uncertainty response (allowing the decline of difficult trials) or a middle-perceptual response (labeling the same intermediate trial levels). The results demonstrated that cognitive load reduced uncertainty responding, but increased middle responding. However, this dissociation between uncertainty and middle responding was only observed when participants either lacked training or had very little training with the uncertainty response. If more training was provided, the effect of load was small. These results suggest that uncertainty responding is resource demanding, but with sufficient training, human participants can respond to uncertainty either by using minimal working memory resources or effectively sharing resources. These results are discussed in relation to the literature on animal and human metacognition. PMID:25971878

Dual adaptive dynamic control of mobile robots using neural networks.

PubMed

Bugeja, Marvin K; Fabri, Simon G; Camilleri, Liberato

2009-02-01

This paper proposes two novel dual adaptive neural control schemes for the dynamic control of nonholonomic mobile robots. The two schemes are developed in discrete time, and the robot's nonlinear dynamic functions are assumed to be unknown. Gaussian radial basis function and sigmoidal multilayer perceptron neural networks are used for function approximation. In each scheme, the unknown network parameters are estimated stochastically in real time, and no preliminary offline neural network training is used. In contrast to other adaptive techniques hitherto proposed in the literature on mobile robots, the dual control laws presented in this paper do not rely on the heuristic certainty equivalence property but account for the uncertainty in the estimates. This results in a major improvement in tracking performance, despite the plant uncertainty and unmodeled dynamics. Monte Carlo simulation and statistical hypothesis testing are used to illustrate the effectiveness of the two proposed stochastic controllers as applied to the trajectory-tracking problem of a differentially driven wheeled mobile robot.

Functional (dissociative) retrograde amnesia.

PubMed

Markowitsch, H J; Staniloiu, A

2016-01-01

Retrograde amnesia is described as condition which can occur after direct brain damage, but which occurs more frequently as a result of a psychiatric illness. In order to understand the amnesic condition, content-based divisions of memory are defined. The measurement of retrograde memory is discussed and the dichotomy between "organic" and "psychogenic" retrograde amnesia is questioned. Briefly, brain damage-related etiologies of retrograde amnesia are mentioned. The major portion of the review is devoted to dissociative amnesia (also named psychogenic or functional amnesia) and to the discussion of an overlap between psychogenic and "brain organic" forms of amnesia. The "inability of access hypothesis" is proposed to account for most of both the organic and psychogenic (dissociative) patients with primarily retrograde amnesia. Questions such as why recovery from retrograde amnesia can occur in retrograde (dissociative) amnesia, and why long-term new learning of episodic-autobiographic episodes is possible, are addressed. It is concluded that research on retrograde amnesia research is still in its infancy, as the neural correlates of memory storage are still unknown. It is argued that the recollection of episodic-autobiographic episodes most likely involves frontotemporal regions of the right hemisphere, a region which appears to be hypometabolic in patients with dissociative amnesia. © 2016 Elsevier B.V. All rights reserved.

Subthreshold muscle twitches dissociate oscillatory neural signatures of conflicts from errors.

PubMed

Cohen, Michael X; van Gaal, Simon

2014-02-01

We investigated the neural systems underlying conflict detection and error monitoring during rapid online error correction/monitoring mechanisms. We combined data from four separate cognitive tasks and 64 subjects in which EEG and EMG (muscle activity from the thumb used to respond) were recorded. In typical neuroscience experiments, behavioral responses are classified as "error" or "correct"; however, closer inspection of our data revealed that correct responses were often accompanied by "partial errors" - a muscle twitch of the incorrect hand ("mixed correct trials," ~13% of the trials). We found that these muscle twitches dissociated conflicts from errors in time-frequency domain analyses of EEG data. In particular, both mixed-correct trials and full error trials were associated with enhanced theta-band power (4-9Hz) compared to correct trials. However, full errors were additionally associated with power and frontal-parietal synchrony in the delta band. Single-trial robust multiple regression analyses revealed a significant modulation of theta power as a function of partial error correction time, thus linking trial-to-trial fluctuations in power to conflict. Furthermore, single-trial correlation analyses revealed a qualitative dissociation between conflict and error processing, such that mixed correct trials were associated with positive theta-RT correlations whereas full error trials were associated with negative delta-RT correlations. These findings shed new light on the local and global network mechanisms of conflict monitoring and error detection, and their relationship to online action adjustment. © 2013.

Accounting for the dissociating properties of organic chemicals in LCIA: an uncertainty analysis applied to micropollutants in the assessment of freshwater ecotoxicity.

PubMed

Morais, Sérgio Alberto; Delerue-Matos, Cristina; Gabarrell, Xavier

2013-03-15

In life cycle impact assessment (LCIA) models, the sorption of the ionic fraction of dissociating organic chemicals is not adequately modeled because conventional non-polar partitioning models are applied. Therefore, high uncertainties are expected when modeling the mobility, as well as the bioavailability for uptake by exposed biota and degradation, of dissociating organic chemicals. Alternative regressions that account for the ionized fraction of a molecule to estimate fate parameters were applied to the USEtox model. The most sensitive model parameters in the estimation of ecotoxicological characterization factors (CFs) of micropollutants were evaluated by Monte Carlo analysis in both the default USEtox model and the alternative approach. Negligible differences of CFs values and 95% confidence limits between the two approaches were estimated for direct emissions to the freshwater compartment; however the default USEtox model overestimates CFs and the 95% confidence limits of basic compounds up to three orders and four orders of magnitude, respectively, relatively to the alternative approach for emissions to the agricultural soil compartment. For three emission scenarios, LCIA results show that the default USEtox model overestimates freshwater ecotoxicity impacts for the emission scenarios to agricultural soil by one order of magnitude, and larger confidence limits were estimated, relatively to the alternative approach. Copyright © 2013 Elsevier B.V. All rights reserved.

Estimation of uncertainty in pKa values determined by potentiometric titration.

PubMed

Koort, Eve; Herodes, Koit; Pihl, Viljar; Leito, Ivo

2004-06-01

A procedure is presented for estimation of uncertainty in measurement of the pK(a) of a weak acid by potentiometric titration. The procedure is based on the ISO GUM. The core of the procedure is a mathematical model that involves 40 input parameters. A novel approach is used for taking into account the purity of the acid, the impurities are not treated as inert compounds only, their possible acidic dissociation is also taken into account. Application to an example of practical pK(a) determination is presented. Altogether 67 different sources of uncertainty are identified and quantified within the example. The relative importance of different uncertainty sources is discussed. The most important source of uncertainty (with the experimental set-up of the example) is the uncertainty of pH measurement followed by the accuracy of the burette and the uncertainty of weighing. The procedure gives uncertainty separately for each point of the titration curve. The uncertainty depends on the amount of titrant added, being lowest in the central part of the titration curve. The possibilities of reducing the uncertainty and interpreting the drift of the pK(a) values obtained from the same curve are discussed.

Neural mechanisms of risky decision-making and reward response in adolescent onset cannabis use disorder.

PubMed

De Bellis, Michael D; Wang, Lihong; Bergman, Sara R; Yaxley, Richard H; Hooper, Stephen R; Huettel, Scott A

2013-11-01

Neural mechanisms of decision-making and reward response in adolescent cannabis use disorder (CUD) are underexplored. Three groups of male adolescents were studied: CUD in full remission (n=15); controls with psychopathology without substance use disorder history (n=23); and healthy controls (n=18). We investigated neural processing of decision-making and reward under conditions of varying risk and uncertainty with the Decision-Reward Uncertainty Task while participants were scanned using functional magnetic resonance imaging. Abstinent adolescents with CUD compared to controls with psychopathology showed hyperactivation in one cluster that spanned left superior parietal lobule/left lateral occipital cortex/precuneus while making risky decisions that involved uncertainty, and hypoactivation in left orbitofrontal cortex to rewarded outcomes compared to no-reward after making risky decisions. Post hoc region of interest analyses revealed that both control groups significantly differed from the CUD group (but not from each other) during both the decision-making and reward outcome phase of the Decision-Reward Uncertainty Task. In the CUD group, orbitofrontal activations to reward significantly and negatively correlated with total number of individual drug classes the CUD patients experimented with prior to treatment. CUD duration significantly and negatively correlated with orbitofrontal activations to no-reward. The adolescent CUD group demonstrated distinctly different activation patterns during risky decision-making and reward processing (after risky decision-making) compared to both the controls with psychopathology and healthy control groups. These findings suggest that neural differences in risky decision-making and reward processes are present in adolescent addiction, persist after remission from first CUD treatment, and may contribute to vulnerability for adolescent addiction. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Coding of level of ambiguity within neural systems mediating choice.

PubMed

Lopez-Paniagua, Dan; Seger, Carol A

2013-01-01

Data from previous neuroimaging studies exploring neural activity associated with uncertainty suggest varying levels of activation associated with changing degrees of uncertainty in neural regions that mediate choice behavior. The present study used a novel task that parametrically controlled the amount of information hidden from the subject; levels of uncertainty ranged from full ambiguity (no information about probability of winning) through multiple levels of partial ambiguity, to a condition of risk only (zero ambiguity with full knowledge of the probability of winning). A parametric analysis compared a linear model in which weighting increased as a function of level of ambiguity, and an inverted-U quadratic models in which partial ambiguity conditions were weighted most heavily. Overall we found that risk and all levels of ambiguity recruited a common "fronto-parietal-striatal" network including regions within the dorsolateral prefrontal cortex, intraparietal sulcus, and dorsal striatum. Activation was greatest across these regions and additional anterior and superior prefrontal regions for the quadratic function which most heavily weighs trials with partial ambiguity. These results suggest that the neural regions involved in decision processes do not merely track the absolute degree ambiguity or type of uncertainty (risk vs. ambiguity). Instead, recruitment of prefrontal regions may result from greater degree of difficulty in conditions of partial ambiguity: when information regarding reward probabilities important for decision making is hidden or not easily obtained the subject must engage in a search for tractable information. Additionally, this study identified regions of activity related to the valuation of potential gains associated with stimuli or options (including the orbitofrontal and medial prefrontal cortices and dorsal striatum) and related to winning (including orbitofrontal cortex and ventral striatum).

Coding of level of ambiguity within neural systems mediating choice

PubMed Central

Lopez-Paniagua, Dan; Seger, Carol A.

2013-01-01

Data from previous neuroimaging studies exploring neural activity associated with uncertainty suggest varying levels of activation associated with changing degrees of uncertainty in neural regions that mediate choice behavior. The present study used a novel task that parametrically controlled the amount of information hidden from the subject; levels of uncertainty ranged from full ambiguity (no information about probability of winning) through multiple levels of partial ambiguity, to a condition of risk only (zero ambiguity with full knowledge of the probability of winning). A parametric analysis compared a linear model in which weighting increased as a function of level of ambiguity, and an inverted-U quadratic models in which partial ambiguity conditions were weighted most heavily. Overall we found that risk and all levels of ambiguity recruited a common “fronto—parietal—striatal” network including regions within the dorsolateral prefrontal cortex, intraparietal sulcus, and dorsal striatum. Activation was greatest across these regions and additional anterior and superior prefrontal regions for the quadratic function which most heavily weighs trials with partial ambiguity. These results suggest that the neural regions involved in decision processes do not merely track the absolute degree ambiguity or type of uncertainty (risk vs. ambiguity). Instead, recruitment of prefrontal regions may result from greater degree of difficulty in conditions of partial ambiguity: when information regarding reward probabilities important for decision making is hidden or not easily obtained the subject must engage in a search for tractable information. Additionally, this study identified regions of activity related to the valuation of potential gains associated with stimuli or options (including the orbitofrontal and medial prefrontal cortices and dorsal striatum) and related to winning (including orbitofrontal cortex and ventral striatum). PMID:24367286

Adaptive Tracking Control for Robots With an Interneural Computing Scheme.

PubMed

Tsai, Feng-Sheng; Hsu, Sheng-Yi; Shih, Mau-Hsiang

2018-04-01

Adaptive tracking control of mobile robots requires the ability to follow a trajectory generated by a moving target. The conventional analysis of adaptive tracking uses energy minimization to study the convergence and robustness of the tracking error when the mobile robot follows a desired trajectory. However, in the case that the moving target generates trajectories with uncertainties, a common Lyapunov-like function for energy minimization may be extremely difficult to determine. Here, to solve the adaptive tracking problem with uncertainties, we wish to implement an interneural computing scheme in the design of a mobile robot for behavior-based navigation. The behavior-based navigation adopts an adaptive plan of behavior patterns learning from the uncertainties of the environment. The characteristic feature of the interneural computing scheme is the use of neural path pruning with rewards and punishment interacting with the environment. On this basis, the mobile robot can be exploited to change its coupling weights in paths of neural connections systematically, which can then inhibit or enhance the effect of flow elimination in the dynamics of the evolutionary neural network. Such dynamical flow translation ultimately leads to robust sensory-to-motor transformations adapting to the uncertainties of the environment. A simulation result shows that the mobile robot with the interneural computing scheme can perform fault-tolerant behavior of tracking by maintaining suitable behavior patterns at high frequency levels.

Making predictions in a changing world-inference, uncertainty, and learning.

PubMed

O'Reilly, Jill X

2013-01-01

To function effectively, brains need to make predictions about their environment based on past experience, i.e., they need to learn about their environment. The algorithms by which learning occurs are of interest to neuroscientists, both in their own right (because they exist in the brain) and as a tool to model participants' incomplete knowledge of task parameters and hence, to better understand their behavior. This review focusses on a particular challenge for learning algorithms-how to match the rate at which they learn to the rate of change in the environment, so that they use as much observed data as possible whilst disregarding irrelevant, old observations. To do this algorithms must evaluate whether the environment is changing. We discuss the concepts of likelihood, priors and transition functions, and how these relate to change detection. We review expected and estimation uncertainty, and how these relate to change detection and learning rate. Finally, we consider the neural correlates of uncertainty and learning. We argue that the neural correlates of uncertainty bear a resemblance to neural systems that are active when agents actively explore their environments, suggesting that the mechanisms by which the rate of learning is set may be subject to top down control (in circumstances when agents actively seek new information) as well as bottom up control (by observations that imply change in the environment).

Robust Neural Sliding Mode Control of Robot Manipulators

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

Nguyen Tran Hiep; Pham Thuong Cat

2009-03-05

This paper proposes a robust neural sliding mode control method for robot tracking problem to overcome the noises and large uncertainties in robot dynamics. The Lyapunov direct method has been used to prove the stability of the overall system. Simulation results are given to illustrate the applicability of the proposed method.

Neural network-based preprocessing to estimate the parameters of the X-ray emission of a single-temperature thermal plasma

NASA Astrophysics Data System (ADS)

Ichinohe, Y.; Yamada, S.; Miyazaki, N.; Saito, S.

2018-04-01

We present data preprocessing based on an artificial neural network to estimate the parameters of the X-ray emission spectra of a single-temperature thermal plasma. The method finds appropriate parameters close to the global optimum. The neural network is designed to learn the parameters of the thermal plasma (temperature, abundance, normalization and redshift) of the input spectra. After training using 9000 simulated X-ray spectra, the network has grown to predict all the unknown parameters with uncertainties of about a few per cent. The performance dependence on the network structure has been studied. We applied the neural network to an actual high-resolution spectrum obtained with Hitomi. The predicted plasma parameters agree with the known best-fitting parameters of the Perseus cluster within uncertainties of ≲10 per cent. The result shows that neural networks trained by simulated data might possibly be used to extract a feature built in the data. This would reduce human-intensive preprocessing costs before detailed spectral analysis, and would help us make the best use of the large quantities of spectral data that will be available in the coming decades.

Monthly water quality forecasting and uncertainty assessment via bootstrapped wavelet neural networks under missing data for Harbin, China.

PubMed

Wang, Yi; Zheng, Tong; Zhao, Ying; Jiang, Jiping; Wang, Yuanyuan; Guo, Liang; Wang, Peng

2013-12-01

In this paper, bootstrapped wavelet neural network (BWNN) was developed for predicting monthly ammonia nitrogen (NH(4+)-N) and dissolved oxygen (DO) in Harbin region, northeast of China. The Morlet wavelet basis function (WBF) was employed as a nonlinear activation function of traditional three-layer artificial neural network (ANN) structure. Prediction intervals (PI) were constructed according to the calculated uncertainties from the model structure and data noise. Performance of BWNN model was also compared with four different models: traditional ANN, WNN, bootstrapped ANN, and autoregressive integrated moving average model. The results showed that BWNN could handle the severely fluctuating and non-seasonal time series data of water quality, and it produced better performance than the other four models. The uncertainty from data noise was smaller than that from the model structure for NH(4+)-N; conversely, the uncertainty from data noise was larger for DO series. Besides, total uncertainties in the low-flow period were the biggest due to complicated processes during the freeze-up period of the Songhua River. Further, a data missing-refilling scheme was designed, and better performances of BWNNs for structural data missing (SD) were observed than incidental data missing (ID). For both ID and SD, temporal method was satisfactory for filling NH(4+)-N series, whereas spatial imputation was fit for DO series. This filling BWNN forecasting method was applied to other areas suffering "real" data missing, and the results demonstrated its efficiency. Thus, the methods introduced here will help managers to obtain informed decisions.

Neural Mechanisms of Attention

DTIC Science & Technology

1993-05-21

of Attention 39 The Element Superiority Effect : Attention? 46 Animal Models of Attention Deficit 47 Conditioned Attention Theory 50 2 ATTENTION AND...fails to obtain the necessary quantitative information about the effects of parametric manipulations on the dissociation, or the parametric results...neuroscience endeavor as described here. If simultaneously psychologists ignore the brain arid neuroscientists ignore the mind, no effective translation

Re-Evaluating Dissociations between Implicit and Explicit Category Learning: An Event-Related fMRI Study

ERIC Educational Resources Information Center

Gureckis, Todd M.; James, Thomas W.; Nosofsky, Robert M.

2011-01-01

Recent fMRI studies have found that distinct neural systems may mediate perceptual category learning under implicit and explicit learning conditions. In these previous studies, however, different stimulus-encoding processes may have been associated with implicit versus explicit learning. The present design was aimed at decoupling the influence of…

Dissociable Top-Down Anticipatory Neural States for Different Linguistic Dimensions

ERIC Educational Resources Information Center

Ruz, Maria; Nobre, Anna C.

2008-01-01

When preparing to perform a task, the brain settles into task-set states which are relevant for the selection of the appropriate task-rules and stimulus-response mappings. The way this selection takes place within the Language domain is not well understood. We used high-density electrophysiological recordings while participants were engaged in a…

Dissociative electron attachment to C{sub 2}F{sub 5} radicals

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

Haughey, Sean A.; Field, Thomas A.; Langer, Judith

Dissociative electron attachment to the reactive C{sub 2}F{sub 5} molecular radical has been investigated with two complimentary experimental methods; a single collision beam experiment and a new flowing afterglow Langmuir probe technique. The beam results show that F{sup -} is formed close to zero electron energy in dissociative electron attachment to C{sub 2}F{sub 5}. The afterglow measurements also show that F{sup -} is formed in collisions between electrons and C{sub 2}F{sub 5} molecules with rate constants of 3.7 Multiplication-Sign 10{sup -9} cm{sup 3} s{sup -1} to 4.7 Multiplication-Sign 10{sup -9} cm{sup 3} s{sup -1} at temperatures of 300-600 K. Themore » rate constant increases slowly with increasing temperature, but the rise observed is smaller than the experimental uncertainty of 35%.« less

Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting.

PubMed

Men, Zhongxian; Yee, Eugene; Lien, Fue-Sang; Yang, Zhiling; Liu, Yongqian

2014-01-01

Short-term wind speed and wind power forecasts (for a 72 h period) are obtained using a nonlinear autoregressive exogenous artificial neural network (ANN) methodology which incorporates either numerical weather prediction or high-resolution computational fluid dynamics wind field information as an exogenous input. An ensemble approach is used to combine the predictions from many candidate ANNs in order to provide improved forecasts for wind speed and power, along with the associated uncertainties in these forecasts. More specifically, the ensemble ANN is used to quantify the uncertainties arising from the network weight initialization and from the unknown structure of the ANN. All members forming the ensemble of neural networks were trained using an efficient particle swarm optimization algorithm. The results of the proposed methodology are validated using wind speed and wind power data obtained from an operational wind farm located in Northern China. The assessment demonstrates that this methodology for wind speed and power forecasting generally provides an improvement in predictive skills when compared to the practice of using an "optimal" weight vector from a single ANN while providing additional information in the form of prediction uncertainty bounds.

Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting

PubMed Central

Lien, Fue-Sang; Yang, Zhiling; Liu, Yongqian

2014-01-01

Short-term wind speed and wind power forecasts (for a 72 h period) are obtained using a nonlinear autoregressive exogenous artificial neural network (ANN) methodology which incorporates either numerical weather prediction or high-resolution computational fluid dynamics wind field information as an exogenous input. An ensemble approach is used to combine the predictions from many candidate ANNs in order to provide improved forecasts for wind speed and power, along with the associated uncertainties in these forecasts. More specifically, the ensemble ANN is used to quantify the uncertainties arising from the network weight initialization and from the unknown structure of the ANN. All members forming the ensemble of neural networks were trained using an efficient particle swarm optimization algorithm. The results of the proposed methodology are validated using wind speed and wind power data obtained from an operational wind farm located in Northern China. The assessment demonstrates that this methodology for wind speed and power forecasting generally provides an improvement in predictive skills when compared to the practice of using an “optimal” weight vector from a single ANN while providing additional information in the form of prediction uncertainty bounds. PMID:27382627

Implicit knowledge of visual uncertainty guides decisions with asymmetric outcomes.

PubMed

Whiteley, Louise; Sahani, Maneesh

2008-03-06

Perception is an "inverse problem," in which the state of the world must be inferred from the sensory neural activity that results. However, this inference is both ill-posed (Helmholtz, 1856; Marr, 1982) and corrupted by noise (Green & Swets, 1989), requiring the brain to compute perceptual beliefs under conditions of uncertainty. Here we show that human observers performing a simple visual choice task under an externally imposed loss function approach the optimal strategy, as defined by Bayesian probability and decision theory (Berger, 1985; Cox, 1961). In concert with earlier work, this suggests that observers possess a model of their internal uncertainty and can utilize this model in the neural computations that underlie their behavior (Knill & Pouget, 2004). In our experiment, optimal behavior requires that observers integrate the loss function with an estimate of their internal uncertainty rather than simply requiring that they use a modal estimate of the uncertain stimulus. Crucially, they approach optimal behavior even when denied the opportunity to learn adaptive decision strategies based on immediate feedback. Our data thus support the idea that flexible representations of uncertainty are pre-existing, widespread, and can be propagated to decision-making areas of the brain.

Neural-Network-Based Robust Optimal Tracking Control for MIMO Discrete-Time Systems With Unknown Uncertainty Using Adaptive Critic Design.

PubMed

Liu, Lei; Wang, Zhanshan; Zhang, Huaguang

2018-04-01

This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.

Oscillatory magnetic brain activity is related to dissociative symptoms and childhood adversities - A study in women with multiple trauma.

PubMed

Schalinski, I; Moran, J K; Elbert, T; Reindl, V; Wienbruch, C

2017-08-15

Individuals with trauma-related disorders are complex and heterogeneous; part of this complexity derives from additional psychopathology like dissociation as well as environmental adversities such as traumatic stress, experienced throughout the lifespan. Understanding the neurophysiological abnormalities in Post-traumatic stress disorder (PTSD) requires a simultaneous consideration of these factors. Resting state magnetoencephalography (MEG) recordings were obtained from 41 women with PTSD and comorbid depressive symptoms, and 16 healthy women. Oscillatory brain activity was extracted for five frequency bands and 11 source locations, and analyzed in relation to shutdown dissociation and adversity-related measures. Dissociative symptoms were related to increased delta and lowered beta power. Adversity-related measures modulated theta and alpha oscillatory power (in particular childhood sexual abuse) and differed between patients and controls. Findings are based on women with comorbid depressive symptoms and therefore may not be applicable for men or groups with other clinical profiles. In respect to childhood adversities, we had no reliable source for the early infancy. Trauma-related abnormalities in neural organization vary with both exposure to adversities as well as their potential to evoke ongoing shutdown responses. Copyright © 2017 Elsevier B.V. All rights reserved.

Dissociable neural representations of reinforcement and belief prediction errors underlie strategic learning

PubMed Central

Zhu, Lusha; Mathewson, Kyle E.; Hsu, Ming

2012-01-01

Decision-making in the presence of other competitive intelligent agents is fundamental for social and economic behavior. Such decisions require agents to behave strategically, where in addition to learning about the rewards and punishments available in the environment, they also need to anticipate and respond to actions of others competing for the same rewards. However, whereas we know much about strategic learning at both theoretical and behavioral levels, we know relatively little about the underlying neural mechanisms. Here, we show using a multi-strategy competitive learning paradigm that strategic choices can be characterized by extending the reinforcement learning (RL) framework to incorporate agents’ beliefs about the actions of their opponents. Furthermore, using this characterization to generate putative internal values, we used model-based functional magnetic resonance imaging to investigate neural computations underlying strategic learning. We found that the distinct notions of prediction errors derived from our computational model are processed in a partially overlapping but distinct set of brain regions. Specifically, we found that the RL prediction error was correlated with activity in the ventral striatum. In contrast, activity in the ventral striatum, as well as the rostral anterior cingulate (rACC), was correlated with a previously uncharacterized belief-based prediction error. Furthermore, activity in rACC reflected individual differences in degree of engagement in belief learning. These results suggest a model of strategic behavior where learning arises from interaction of dissociable reinforcement and belief-based inputs. PMID:22307594

Dissociable neural representations of reinforcement and belief prediction errors underlie strategic learning.

PubMed

Zhu, Lusha; Mathewson, Kyle E; Hsu, Ming

2012-01-31

Decision-making in the presence of other competitive intelligent agents is fundamental for social and economic behavior. Such decisions require agents to behave strategically, where in addition to learning about the rewards and punishments available in the environment, they also need to anticipate and respond to actions of others competing for the same rewards. However, whereas we know much about strategic learning at both theoretical and behavioral levels, we know relatively little about the underlying neural mechanisms. Here, we show using a multi-strategy competitive learning paradigm that strategic choices can be characterized by extending the reinforcement learning (RL) framework to incorporate agents' beliefs about the actions of their opponents. Furthermore, using this characterization to generate putative internal values, we used model-based functional magnetic resonance imaging to investigate neural computations underlying strategic learning. We found that the distinct notions of prediction errors derived from our computational model are processed in a partially overlapping but distinct set of brain regions. Specifically, we found that the RL prediction error was correlated with activity in the ventral striatum. In contrast, activity in the ventral striatum, as well as the rostral anterior cingulate (rACC), was correlated with a previously uncharacterized belief-based prediction error. Furthermore, activity in rACC reflected individual differences in degree of engagement in belief learning. These results suggest a model of strategic behavior where learning arises from interaction of dissociable reinforcement and belief-based inputs.

An electrophysiological dissociation of craving and stimulus-dependent attentional capture in smokers.

PubMed

Donohue, Sarah E; Woldorff, Marty G; Hopf, Jens-Max; Harris, Joseph A; Heinze, Hans-Jochen; Schoenfeld, Mircea A

2016-12-01

It has been suggested that over the course of an addiction, addiction-related stimuli become highly salient in the environment, thereby capturing an addict's attention. To assess these effects neurally in smokers, and how they interact with craving, we recorded electroencephalography (EEG) in two sessions: one in which participants had just smoked (non-craving), and one in which they had abstained from smoking for 3 h (craving). In both sessions, participants performed a visual-search task in which two colored squares were presented to the left and right of fixation, with one color being the target to which they should shift attention and discriminate the locations of two missing corners. Task-irrelevant images, both smoking-related and non-smoking-related, were embedded in both squares, enabling the shift of spatial attention to the target to be examined as a function of the addiction-related image being present or absent in the target, the distractor, or both. Behaviorally, participants were slower to respond to targets containing a smoking-related image. Furthermore, when the target contained a smoking-related image, the neural responses indicated that attention had been shifted less strongly to the target; when the distractor contained a smoking-related image, the shift of attention to the contralateral target was stronger. These effects occurred independently of craving and suggest that participants were actively avoiding the smoking-related images. Together, these results provide an electrophysiological dissociation between addiction-related visual-stimulus processing and the neural activity associated with craving.

Prospective Memory Impairments in Alzheimer's Disease and Behavioral Variant Frontotemporal Dementia: Clinical and Neural Correlates.

PubMed

Dermody, Nadene; Hornberger, Michael; Piguet, Olivier; Hodges, John R; Irish, Muireann

2016-01-01

Prospective memory (PM) refers to a future-oriented form of memory in which the individual must remember to execute an intended action either at a future point in time (Time-based) or in response to a specific event (Event-based). Lapses in PM are commonly exhibited in neurodegenerative disorders including Alzheimer's disease (AD) and frontotemporal dementia (FTD), however, the neurocognitive mechanisms driving these deficits remain unknown. To investigate the clinical and neural correlates of Time- and Event-based PM disruption in AD and the behavioral-variant FTD (bvFTD). Twelve AD, 12 bvFTD, and 12 healthy older Control participants completed a modified version of the Cambridge Prospective Memory test, which examines Time- and Event-based aspects of PM. All participants completed a standard neuropsychological assessment and underwent whole-brain structural MRI. AD and bvFTD patients displayed striking impairments across Time- and Event-based PM relative to Controls, however, Time-based PM was disproportionately affected in the AD group. Episodic memory dysfunction and hippocampal atrophy were found to correlate strongly with PM integrity in both patient groups, however, dissociable neural substrates were also evident for PM performance across dementia syndromes. Our study reveals the multifaceted nature of PM dysfunction in neurodegenerative disorders, and suggests common and dissociable neurocognitive mechanisms, which subtend these deficits in each patient group. Future studies of PM disturbance in dementia syndromes will be crucial for the development of successful interventions to improve functional independence in the patient's daily life.

Neural correlates of conventional and harm/welfare-based moral decision-making.

PubMed

White, Stuart F; Zhao, Hui; Leong, Kelly Kimiko; Smetana, Judith G; Nucci, Larry P; Blair, R James R

2017-12-01

The degree to which social norms are processed by a unitary system or dissociable systems remains debated. Much research on children's social-cognitive judgments has supported the distinction between "moral" (harm/welfare-based) and "conventional" norms. However, the extent to which these norms are processed by dissociable neural systems remains unclear. To address this issue, 23 healthy participants were scanned with functional magnetic resonance imaging (fMRI) while they rated the wrongness of harm/welfare-based and conventional transgressions and neutral vignettes. Activation significantly greater than the neutral vignette baseline was observed in regions implicated in decision-making regions including rostral/ventral medial frontal, anterior insula and dorsomedial frontal cortices when evaluating both harm/welfare-based and social-conventional transgressions. Greater activation when rating harm/welfare-based relative to social-conventional transgressions was seen through much of ACC and bilateral inferior frontal gyrus. Greater activation was observed in superior temporal gyrus, bilateral middle temporal gyrus, left PCC, and temporal-parietal junction when rating social-conventional transgressions relative to harm/welfare-based transgressions. These data suggest that decisions regarding the wrongness of actions, irrespective of whether they involve care/harm-based or conventional transgressions, recruit regions generally implicated in affect-based decision-making. However, there is neural differentiation between harm/welfare-based and conventional transgressions. This may reflect the particular importance of processing the intent of transgressors of conventional norms and perhaps the greater emotional content or salience of harm/welfare-based transgressions.

Based on interval type-2 fuzzy-neural network direct adaptive sliding mode control for SISO nonlinear systems

NASA Astrophysics Data System (ADS)

Lin, Tsung-Chih

2010-12-01

In this paper, a novel direct adaptive interval type-2 fuzzy-neural tracking control equipped with sliding mode and Lyapunov synthesis approach is proposed to handle the training data corrupted by noise or rule uncertainties for nonlinear SISO nonlinear systems involving external disturbances. By employing adaptive fuzzy-neural control theory, the update laws will be derived for approximating the uncertain nonlinear dynamical system. In the meantime, the sliding mode control method and the Lyapunov stability criterion are incorporated into the adaptive fuzzy-neural control scheme such that the derived controller is robust with respect to unmodeled dynamics, external disturbance and approximation errors. In comparison with conventional methods, the advocated approach not only guarantees closed-loop stability but also the output tracking error of the overall system will converge to zero asymptotically without prior knowledge on the upper bound of the lumped uncertainty. Furthermore, chattering effect of the control input will be substantially reduced by the proposed technique. To illustrate the performance of the proposed method, finally simulation example will be given.

Errors and conflict at the task level and the response level.

PubMed

Desmet, Charlotte; Fias, Wim; Hartstra, Egbert; Brass, Marcel

2011-01-26

In the last decade, research on error and conflict processing has become one of the most influential research areas in the domain of cognitive control. There is now converging evidence that a specific part of the posterior frontomedian cortex (pFMC), the rostral cingulate zone (RCZ), is crucially involved in the processing of errors and conflict. However, error-related research has focused primarily on a specific error type, namely, response errors. The aim of the present study was to investigate whether errors on the task level rely on the same neural and functional mechanisms. Here we report a dissociation of both error types in the pFMC: whereas response errors activate the RCZ, task errors activate the dorsal frontomedian cortex. Although this last region shows an overlap in activation for task and response errors on the group level, a closer inspection of the single-subject data is more in accordance with a functional anatomical dissociation. When investigating brain areas related to conflict on the task and response levels, a clear dissociation was perceived between areas associated with response conflict and with task conflict. Overall, our data support a dissociation between response and task levels of processing in the pFMC. In addition, we provide additional evidence for a dissociation between conflict and errors both at the response level and at the task level.

Applying Bayesian Neural Network to determine neutrino incoming direction in reactor neutrino experiments and supernova explosion location by scintillator detectors

NASA Astrophysics Data System (ADS)

Xu, W. W.; Xu, Y.; Meng, Y. X.; Wu, B.

2009-01-01

In the paper, it is discussed by using Monte-Carlo simulation that the Bayesian Neural Network (BNN) is applied to determine neutrino incoming direction in reactor neutrino experiments and supernova explosion location by scintillator detectors. As a result, compared to the method in ref. [1], the uncertainty on the measurement of the neutrino direction using BNN is significantly improved. The uncertainty on the measurement of the reactor neutrino direction is about 1.0° at the 68.3% C.L., and the one in the case of supernova neutrino is about 0.6° at the 68.3% C.L. . Compared to the method in ref. [1], the uncertainty attainable by using BNN reduces by a factor of about 20. And compared to the Super-Kamiokande experiment (SK), it reduces by a factor of about 8.

Neural Correlates of Expert Behavior During a Domain-Specific Attentional Cueing Task in Badminton Players.

PubMed

Wang, Chun-Hao; Tu, Kuo-Cheng

2017-06-01

The present study aimed to investigate the neural correlates associated with sports expertise during a domain-specific task in badminton players. We compared event-related potentials activity from collegiate male badminton players and a set of matched athletic controls when they performed a badminton-specific attentional cueing task in which the uncertainty and validity were manipulated. The data showed that, regardless of cue type, the badminton players had faster responses along with greater P3 amplitudes than the athletic controls on the task. Specifically, the contingent negative variation amplitude was smaller for the players than for the controls in the condition involving higher uncertainty. Such an effect, however, was absent in the condition with lower uncertainty. We conclude that expertise in sports is associated with proficient modulation of brain activity during cognitive and motor preparation, as well as response execution, when performing a task related to an individual's specific sport domain.

Adaptive dynamic surface control of flexible-joint robots using self-recurrent wavelet neural networks.

PubMed

Yoo, Sung Jin; Park, Jin Bae; Choi, Yoon Ho

2006-12-01

A new method for the robust control of flexible-joint (FJ) robots with model uncertainties in both robot dynamics and actuator dynamics is proposed. The proposed control system is a combination of the adaptive dynamic surface control (DSC) technique and the self-recurrent wavelet neural network (SRWNN). The adaptive DSC technique provides the ability to overcome the "explosion of complexity" problem in backstepping controllers. The SRWNNs are used to observe the arbitrary model uncertainties of FJ robots, and all their weights are trained online. From the Lyapunov stability analysis, their adaptation laws are induced, and the uniformly ultimately boundedness of all signals in a closed-loop adaptive system is proved. Finally, simulation results for a three-link FJ robot are utilized to validate the good position tracking performance and robustness against payload uncertainties and external disturbances of the proposed control system.

Adaptive neural network motion control for aircraft under uncertainty conditions

NASA Astrophysics Data System (ADS)

Efremov, A. V.; Tiaglik, M. S.; Tiumentsev, Yu V.

2018-02-01

We need to provide motion control of modern and advanced aircraft under diverse uncertainty conditions. This problem can be solved by using adaptive control laws. We carry out an analysis of the capabilities of these laws for such adaptive systems as MRAC (Model Reference Adaptive Control) and MPC (Model Predictive Control). In the case of a nonlinear control object, the most efficient solution to the adaptive control problem is the use of neural network technologies. These technologies are suitable for the development of both a control object model and a control law for the object. The approximate nature of the ANN model was taken into account by introducing additional compensating feedback into the control system. The capabilities of adaptive control laws under uncertainty in the source data are considered. We also conduct simulations to assess the contribution of adaptivity to the behavior of the system.

Biogrid--a microfluidic device for large-scale enzyme-free dissociation of stem cell aggregates.

PubMed

Wallman, Lars; Åkesson, Elisabet; Ceric, Dario; Andersson, Per Henrik; Day, Kelly; Hovatta, Outi; Falci, Scott; Laurell, Thomas; Sundström, Erik

2011-10-07

Culturing stem cells as free-floating aggregates in suspension facilitates large-scale production of cells in closed systems, for clinical use. To comply with GMP standards, the use of substances such as proteolytic enzymes should be avoided. Instead of enzymatic dissociation, the growing cell aggregates may be mechanically cut at passage, but available methods are not compatible with large-scale cell production and hence translation into the clinic becomes a severe bottle-neck. We have developed the Biogrid device, which consists of an array of micrometerscale knife edges, micro-fabricated in silicon, and a manifold in which the microgrid is placed across the central fluid channel. By connecting one side of the Biogrid to a syringe or a pump and the other side to the cell culture, the culture medium with suspended cell aggregates can be aspirated, forcing the aggregates through the microgrid, and ejected back to the cell culture container. Large aggregates are thereby dissociated into smaller fragments while small aggregates pass through the microgrid unaffected. As proof-of-concept, we demonstrate that the Biogrid device can be successfully used for repeated passage of human neural stem/progenitor cells cultured as so-called neurospheres, as well as for passage of suspension cultures of human embryonic stem cells. We also show that human neural stem/progenitor cells tolerate transient pressure changes far exceeding those that will occur in a fluidic system incorporating the Biogrid microgrids. Thus, by using the Biogrid device it is possible to mechanically passage large quantities of cells in suspension cultures in closed fluidic systems, without the use of proteolytic enzymes.

Associative and Strategic Components of Episodic Memory: A Life-Span Dissociation

ERIC Educational Resources Information Center

Shing, Yee Lee; Werkle-Bergner, Markus; Li, Shu-Chen; Lindenberger, Ulman

2008-01-01

The authors investigated the strategic component (i.e., elaboration and organization of episodic features) and the associative component (i.e., binding processes) of episodic memory and their interactions in 4 age groups (10-12, 13-15, 20-25, and 70-75 years of age). On the basis of behavioral and neural evidence, the authors hypothesized that the…

Using Perceptual Signatures to Define and Dissociate Condition-Specific Neural Etiology: Autism and Fragile X Syndrome as Model Conditions

ERIC Educational Resources Information Center

Bertone, Armando; Hanck, Julie; Kogan, Cary; Chaudhuri, Avi; Cornish, Kim

2010-01-01

The functional link between genetic alteration and behavioral end-state is rarely straightforward and never linear. Cases where neurodevlopmental conditions defined by a distinct genetic etiology share behavioral phenotypes are exemplary, as is the case for autism and Fragile X Syndrome (FXS). In this paper and its companion paper, we propose a…

Neural Dissociation in the Production of Lexical versus Classifier Signs in ASL: Distinct Patterns of Hemispheric Asymmetry

ERIC Educational Resources Information Center

Hickok, Gregory; Pickell, Herbert; Klima, Edward; Bellugi, Ursula

2009-01-01

We examine the hemispheric organization for the production of two classes of ASL signs, lexical signs and classifier signs. Previous work has found strong left hemisphere dominance for the production of lexical signs, but several authors have speculated that classifier signs may involve the right hemisphere to a greater degree because they can…

Individual Differences in Skilled Adult Readers Reveal Dissociable Patterns of Neural Activity Associated with Component Processes of Reading

ERIC Educational Resources Information Center

Welcome, Suzanne E.; Joanisse, Marc F.

2012-01-01

We used fMRI to examine patterns of brain activity associated with component processes of visual word recognition and their relationships to individual differences in reading skill. We manipulated both the judgments adults made on written stimuli and the characteristics of the stimuli. Phonological processing led to activation in left inferior…

Dissociation of verbal working memory system components using a delayed serial recall task.

PubMed

Chein, J M; Fiez, J A

2001-11-01

Functional magnetic resonance imaging (fMRI) was used to investigate the neural substrates of component processes in verbal working memory. Based on behavioral research using manipulations of verbal stimulus type to dissociate storage, rehearsal, and executive components of verbal working memory, we designed a delayed serial recall task requiring subjects to encode, maintain, and overtly recall sets of verbal items for which phonological similarity, articulatory length, and lexical status were manipulated. By using a task with temporally extended trials, we were able to exploit the temporal resolution afforded by fMRI to partially isolate neural contributions to encoding, maintenance, and retrieval stages of task performance. Several regions commonly associated with maintenance, including supplementary motor, premotor, and inferior frontal areas, were found to be active across all three trial stages. Additionally, we found that left inferior frontal and supplementary motor regions showed patterns of stimulus and temporal sensitivity implicating them in distinct aspects of articulatory rehearsal, while no regions showed a pattern of sensitivity consistent with a role in phonological storage. Regional modulation by task difficulty was further investigated as a measure of executive processing. We interpret our findings as they relate to notions about the cognitive architecture underlying verbal working memory performance.

Improving the accuracy of Density Functional Theory (DFT) calculation for homolysis bond dissociation energies of Y-NO bond: generalized regression neural network based on grey relational analysis and principal component analysis.

PubMed

Li, Hong Zhi; Tao, Wei; Gao, Ting; Li, Hui; Lu, Ying Hua; Su, Zhong Min

2011-01-01

We propose a generalized regression neural network (GRNN) approach based on grey relational analysis (GRA) and principal component analysis (PCA) (GP-GRNN) to improve the accuracy of density functional theory (DFT) calculation for homolysis bond dissociation energies (BDE) of Y-NO bond. As a demonstration, this combined quantum chemistry calculation with the GP-GRNN approach has been applied to evaluate the homolysis BDE of 92 Y-NO organic molecules. The results show that the ull-descriptor GRNN without GRA and PCA (F-GRNN) and with GRA (G-GRNN) approaches reduce the root-mean-square (RMS) of the calculated homolysis BDE of 92 organic molecules from 5.31 to 0.49 and 0.39 kcal mol(-1) for the B3LYP/6-31G (d) calculation. Then the newly developed GP-GRNN approach further reduces the RMS to 0.31 kcal mol(-1). Thus, the GP-GRNN correction on top of B3LYP/6-31G (d) can improve the accuracy of calculating the homolysis BDE in quantum chemistry and can predict homolysis BDE which cannot be obtained experimentally.

Neural Mechanisms Underlying Risk and Ambiguity Attitudes.

PubMed

Blankenstein, Neeltje E; Peper, Jiska S; Crone, Eveline A; van Duijvenvoorde, Anna C K

2017-11-01

Individual differences in attitudes to risk (a taste for risk, known probabilities) and ambiguity (a tolerance for uncertainty, unknown probabilities) differentially influence risky decision-making. However, it is not well understood whether risk and ambiguity are coded differently within individuals. Here, we tested whether individual differences in risk and ambiguity attitudes were reflected in distinct neural correlates during choice and outcome processing of risky and ambiguous gambles. To these ends, we developed a neuroimaging task in which participants ( n = 50) chose between a sure gain and a gamble, which was either risky or ambiguous, and presented decision outcomes (gains, no gains). From a separate task in which the amount, probability, and ambiguity level were varied, we estimated individuals' risk and ambiguity attitudes. Although there was pronounced neural overlap between risky and ambiguous gambling in a network typically related to decision-making under uncertainty, relatively more risk-seeking attitudes were associated with increased activation in valuation regions of the brain (medial and lateral OFC), whereas relatively more ambiguity-seeking attitudes were related to temporal cortex activation. In addition, although striatum activation was observed during reward processing irrespective of a prior risky or ambiguous gamble, reward processing after an ambiguous gamble resulted in enhanced dorsomedial PFC activation, possibly functioning as a general signal of uncertainty coding. These findings suggest that different neural mechanisms reflect individual differences in risk and ambiguity attitudes and that risk and ambiguity may impact overt risk-taking behavior in different ways.

Capturing the temporal evolution of choice across prefrontal cortex

PubMed Central

Hunt, Laurence T; Behrens, Timothy EJ; Hosokawa, Takayuki; Wallis, Jonathan D; Kennerley, Steven W

2015-01-01

Activity in prefrontal cortex (PFC) has been richly described using economic models of choice. Yet such descriptions fail to capture the dynamics of decision formation. Describing dynamic neural processes has proven challenging due to the problem of indexing the internal state of PFC and its trial-by-trial variation. Using primate neurophysiology and human magnetoencephalography, we here recover a single-trial index of PFC internal states from multiple simultaneously recorded PFC subregions. This index can explain the origins of neural representations of economic variables in PFC. It describes the relationship between neural dynamics and behaviour in both human and monkey PFC, directly bridging between human neuroimaging data and underlying neuronal activity. Moreover, it reveals a functionally dissociable interaction between orbitofrontal cortex, anterior cingulate cortex and dorsolateral PFC in guiding cost-benefit decisions. We cast our observations in terms of a recurrent neural network model of choice, providing formal links to mechanistic dynamical accounts of decision-making. DOI: http://dx.doi.org/10.7554/eLife.11945.001 PMID:26653139

Differential neural circuitry and self-interest in real vs hypothetical moral decisions

PubMed Central

Dalgleish, Tim; Thompson, Russell; Evans, Davy; Schweizer, Susanne; Mobbs, Dean

2012-01-01

Classic social psychology studies demonstrate that people can behave in ways that contradict their intentions—especially within the moral domain. We measured brain activity while subjects decided between financial self-benefit (earning money) and preventing physical harm (applying an electric shock) to a confederate under both real and hypothetical conditions. We found a shared neural network associated with empathic concern for both types of decisions. However, hypothetical and real moral decisions also recruited distinct neural circuitry: hypothetical moral decisions mapped closely onto the imagination network, while real moral decisions elicited activity in the bilateral amygdala and anterior cingulate—areas essential for social and affective processes. Moreover, during real moral decision-making, distinct regions of the prefrontal cortex (PFC) determined whether subjects make selfish or pro-social moral choices. Together, these results reveal not only differential neural mechanisms for real and hypothetical moral decisions but also that the nature of real moral decisions can be predicted by dissociable networks within the PFC. PMID:22711879

Neural-network hybrid control for antilock braking systems.

PubMed

Lin, Chih-Min; Hsu, C F

2003-01-01

The antilock braking systems are designed to maximize wheel traction by preventing the wheels from locking during braking, while also maintaining adequate vehicle steerability; however, the performance is often degraded under harsh road conditions. In this paper, a hybrid control system with a recurrent neural network (RNN) observer is developed for antilock braking systems. This hybrid control system is comprised of an ideal controller and a compensation controller. The ideal controller, containing an RNN uncertainty observer, is the principal controller; and the compensation controller is a compensator for the difference between the system uncertainty and the estimated uncertainty. Since for dynamic response the RNN has capabilities superior to the feedforward NN, it is utilized for the uncertainty observer. The Taylor linearization technique is employed to increase the learning ability of the RNN. In addition, the on-line parameter adaptation laws are derived based on a Lyapunov function, so the stability of the system can be guaranteed. Simulations are performed to demonstrate the effectiveness of the proposed NN hybrid control system for antilock braking control under various road conditions.

Application of neural network for real-time measurement of electrical resistivity in cold crucible

NASA Astrophysics Data System (ADS)

Votava, Pavel; Poznyak, Igor

2017-08-01

The article describes use of an Induction furnace with cold crucible as a tool for real-time measurement of a melted material electrical resistivity. The measurement is based on an inverse problem solution of a 2D mathematical model, possibly implementable in a microcontroller or a FPGA in a form of a neural network. The 2D mathematical model results has been provided as a training set for the neural network. At the end, the implementation results are discussed together with uncertainty of measurement, which is done by the neural network implementation itself.

Computational Evaluation of Cochlear Implant Surgery Outcomes Accounting for Uncertainty and Parameter Variability.

PubMed

Mangado, Nerea; Pons-Prats, Jordi; Coma, Martí; Mistrík, Pavel; Piella, Gemma; Ceresa, Mario; González Ballester, Miguel Á

2018-01-01

Cochlear implantation (CI) is a complex surgical procedure that restores hearing in patients with severe deafness. The successful outcome of the implanted device relies on a group of factors, some of them unpredictable or difficult to control. Uncertainties on the electrode array position and the electrical properties of the bone make it difficult to accurately compute the current propagation delivered by the implant and the resulting neural activation. In this context, we use uncertainty quantification methods to explore how these uncertainties propagate through all the stages of CI computational simulations. To this end, we employ an automatic framework, encompassing from the finite element generation of CI models to the assessment of the neural response induced by the implant stimulation. To estimate the confidence intervals of the simulated neural response, we propose two approaches. First, we encode the variability of the cochlear morphology among the population through a statistical shape model. This allows us to generate a population of virtual patients using Monte Carlo sampling and to assign to each of them a set of parameter values according to a statistical distribution. The framework is implemented and parallelized in a High Throughput Computing environment that enables to maximize the available computing resources. Secondly, we perform a patient-specific study to evaluate the computed neural response to seek the optimal post-implantation stimulus levels. Considering a single cochlear morphology, the uncertainty in tissue electrical resistivity and surgical insertion parameters is propagated using the Probabilistic Collocation method, which reduces the number of samples to evaluate. Results show that bone resistivity has the highest influence on CI outcomes. In conjunction with the variability of the cochlear length, worst outcomes are obtained for small cochleae with high resistivity values. However, the effect of the surgical insertion length on the CI outcomes could not be clearly observed, since its impact may be concealed by the other considered parameters. Whereas the Monte Carlo approach implies a high computational cost, Probabilistic Collocation presents a suitable trade-off between precision and computational time. Results suggest that the proposed framework has a great potential to help in both surgical planning decisions and in the audiological setting process.

An fMRI Examination of Developmental Differences in the Neural Correlates of Uncertainty and Decision-Making

ERIC Educational Resources Information Center

Krain, Amy L.; Hefton, Sara; Pine, Daniel S.; Ernst, Monique; Castellanos, F. Xavier; Klein, Rachel G.; Milham, Michael P.

2006-01-01

Background: Maturation of prefrontal circuits during adolescence contributes to the development of cognitive processes such as decision-making. Recent theories suggest that these neural changes also play a role in the shift from generalized anxiety disorder (GAD) to depression that often occurs during this developmental period. Cognitive models of…

Effects of Uncertainty on ERPs to Emotional Pictures Depend on Emotional Valence

PubMed Central

Lin, Huiyan; Jin, Hua; Liang, Jiafeng; Yin, Ruru; Liu, Ting; Wang, Yiwen

2015-01-01

Uncertainty about the emotional content of an upcoming event has found to modulate neural activity to the event before its occurrence. However, it is still under debate whether the uncertainty effects occur after the occurrence of the event. To address this issue, participants were asked to view emotional pictures that were shortly after a cue, which either indicated a certain emotion of the picture or not. Both certain and uncertain cues were used by neutral symbols. The anticipatory phase (i.e., inter-trial interval, ITI) between the cue and the picture was short to enhance the effects of uncertainty. In addition, we used positive and negative pictures that differed only in valence but not in arousal to investigate whether the uncertainty effect was dependent on emotional valence. Electroencephalography (EEG) was recorded during the presentation of the pictures. Event-related potential (ERP) results showed that negative pictures evoked smaller P2 and late LPP but larger N2 in the uncertain as compared to the certain condition; whereas we did not find the uncertainty effect in early LPP. For positive pictures, the early LPP was larger in the uncertain as compared to the certain condition; however, there were no uncertainty effects in some other ERP components (e.g., P2, N2, and late LPP). The findings suggest that uncertainty modulates neural activity to emotional pictures and this modulation is altered by the valence of the pictures, indicating that individuals alter the allocation of attentional resources toward uncertain emotional pictures dependently on the valence of the pictures. PMID:26733916

Dissociating Temporal Preparation Processes as a Function of the Inter-Trial Interval Duration

ERIC Educational Resources Information Center

Vallesi, Antonino; Lozano, Violeta N.; Correa, Angel

2013-01-01

Preparation over time is a ubiquitous capacity which implies decreasing uncertainty about when critical events will occur. This capacity is usually studied with the variable foreperiod paradigm, which consists in the random variation of the time interval (foreperiod) between a warning stimulus and a target. With this paradigm, response time (RT)…

An Integrated Theory of Attention and Decision Making in Visual Signal Detection

ERIC Educational Resources Information Center

Smith, Philip L.; Ratcliff, Roger

2009-01-01

The simplest attentional task, detecting a cued stimulus in an otherwise empty visual field, produces complex patterns of performance. Attentional cues interact with backward masks and with spatial uncertainty, and there is a dissociation in the effects of these variables on accuracy and on response time. A computational theory of performance in…

Recognition and Mental Manipulation of Body Parts Dissociate in Locked-In Syndrome

ERIC Educational Resources Information Center

Conson, Massimiliano; Pistoia, Francesca; Sara, Marco; Grossi, Dario; Trojano, Luigi

2010-01-01

Several lines of evidence demonstrate that the motor system is involved in motor simulation of actions, but some uncertainty exists about the consequences of lesions of descending motor pathways on mental imagery tasks. Moreover, recent findings suggest that the motor system could also have a role in recognition of body parts. To address these…

Performance assessment of low pressure nuclear thermal propulsion

NASA Technical Reports Server (NTRS)

Gerrish, H. P., Jr.; Doughty, G. E.

1993-01-01

A low pressure nuclear thermal propulsion (LPNTP) system, which takes advantage of hydrogen dissociation/recombination, was proposed as a means of increasing engine specific impulse (Isp). The effect of hydrogen dissociation/recombination on LPNTP Isp is examined. A two-dimensional computer model was used to show that the optimum chamber pressure is approximately 100 psia (at a chamber temperature of 3,000 K), with an Isp approximately 15 s higher than at 1,000 psia. At high chamber temperatures and low chamber pressures, the increase in Isp is due to both lower average molecular weights caused by dissociation and added kinetic energy from monatomic hydrogen recombination. Monatomic hydrogen recombination increases the Isp more then hydrogen dissociation. Variations in the mole fraction of monatomic hydrogen are similar to variations in static pressure along the axial nozzle position. Most recombination occurs close to the nozzle throat. Practical variations in nozzle geometry have minimal impact on recombination. Other models which can simulate a wider range of nozzle designs should be used in the future. The uncertainty of the hydrogen kinetic reaction rates at high temperatures (approximately 3,000 K) affects the accuracy of the analysis and should be verified with simple bench tests.

Incorporating Wind Power Forecast Uncertainties Into Stochastic Unit Commitment Using Neural Network-Based Prediction Intervals.

PubMed

Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

2015-09-01

Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-based prediction intervals (PIs) are implemented for forecast uncertainty quantification. Instead of a single level PI, wind power forecast uncertainties are represented in a list of PIs. These PIs are then decomposed into quantiles of wind power. A new scenario generation method is proposed to handle wind power forecast uncertainties. For each hour, an empirical cumulative distribution function (ECDF) is fitted to these quantile points. The Monte Carlo simulation method is used to generate scenarios from the ECDF. Then the wind power scenarios are incorporated into a stochastic security-constrained unit commitment (SCUC) model. The heuristic genetic algorithm is utilized to solve the stochastic SCUC problem. Five deterministic and four stochastic case studies incorporated with interval forecasts of wind power are implemented. The results of these cases are presented and discussed together. Generation costs, and the scheduled and real-time economic dispatch reserves of different unit commitment strategies are compared. The experimental results show that the stochastic model is more robust than deterministic ones and, thus, decreases the risk in system operations of smart grids.

Selective loss of verbal imagery.

PubMed

Mehta, Z; Newcombe, F

1996-05-01

This single case study of the ability to generate verbal and non-verbal imagery in a woman who sustained a gunshot wound to the brain reports a significant difficulty in generating images of word shapes but not a significant problem in generating object images. Further dissociation, however, was observed in her ability to generate images of living vs non-living material. She made more errors in imagery and factual information tasks for non-living items than for living items. This pattern contrasts with our previous report of the agnosic patient, M.S., who had severe difficulty in generating images of living material, whereas his ability to image the shape of words was comparable to that of normal control subjects. Furthermore, with regard to the generation of images of living compared with non-living material, M.S. shows more errors with living than nonliving items. In contrast, the present patient, S.M., made significantly more errors with non-living relative to living items. There appear to be two types of double dissociation which reinforce the growing evidence of dissociable impairments in the ability to generate images for different types of verbal and non-verbal material. Such dissociations, presumably related to sensory and cognitive processing demands, address the problem of the neural basis of imagery.

Dissociable contributions of the amygdala to the immediate and delayed effects of emotional arousal on memory.

PubMed

Schümann, Dirk; Sommer, Tobias

2018-06-01

Emotional arousal enhances memory encoding and consolidation leading to better immediate and delayed memory. Although the central noradrenergic system and the amygdala play critical roles in both effects of emotional arousal, we have recently shown that these effects are at least partly independent of each other, suggesting distinct underlying neural mechanisms. Here we aim to dissociate the neural substrates of both effects in 70 female participants using an emotional memory paradigm to investigate how neural activity, as measured by fMRI, and a polymorphism in the α 2B -noradrenoceptor vary for these effects. To also test whether the immediate and delayed effects of emotional arousal on memory are stable traits, we invited back participants who were a part of a large-scale behavioral memory study ∼3.5 yr ago. We replicated the low correlation of the immediate and delayed emotional enhancement of memory across participants ( r = 0.16) and observed, moreover, that only the delayed effect was, to some degree, stable over time ( r = 0.23). Bilateral amygdala activity, as well as its coupling with the visual cortex and the fusiform gyrus, was related to the preferential encoding of emotional stimuli, which is consistent with affect-biased attention. Moreover, the adrenoceptor genotype modulated the bilateral amygdala activity associated with this effect. The left amygdala and its coupling with the hippocampus was specifically associated with the more efficient consolidation of emotional stimuli, which is consistent with amygdalar modulation of hippocampal consolidation. © 2018 Schümann and Sommer; Published by Cold Spring Harbor Laboratory Press.

Isolating dividing neural and brain tumour cells for gene expression profiling.

PubMed

Endaya, Berwini; Cavanagh, Brenton; Alowaidi, Faisal; Walker, Tom; de Pennington, Nicholas; Ng, Jin-Ming A; Lam, Paula Y P; Mackay-Sim, Alan; Neuzil, Jiri; Meedeniya, Adrian C B

2016-01-15

The characterisation of dividing brain cells is fundamental for studies ranging from developmental and stem cell biology, to brain cancers. Whilst there is extensive anatomical data on these dividing cells, limited gene transcription data is available due to technical constraints. We focally isolated dividing cells whilst conserving RNA, from culture, primary neural tissue and xenografted glioma tumours, using a thymidine analogue that enables gene transcription analysis. 5-ethynyl-2-deoxyuridine labels the replicating DNA of dividing cells. Once labelled, cultured cells and tissues were dissociated, fluorescently tagged with a revised click chemistry technique and the dividing cells isolated using fluorescence-assisted cell sorting. RNA was extracted and analysed using real time PCR. Proliferation and maturation related gene expression in neurogenic tissues was demonstrated in acutely and 3 day old labelled cells, respectively. An elevated expression of marker and pathway genes was demonstrated in the dividing cells of xenografted brain tumours, with the non-dividing cells showing relatively low levels of expression. BrdU "immune-labelling", the most frequently used protocol for detecting cell proliferation, causes complete denaturation of RNA, precluding gene transcription analysis. This EdU labelling technique, maintained cell integrity during dissociation, minimized copper exposure during labelling and used a cell isolation protocol that avoided cell lysis, thus conserving RNA. The technique conserves RNA, enabling the definition of cell proliferation-related changes in gene transcription of neural and pathological brain cells in cells harvested immediately after division, or following a period of maturation. Copyright © 2015 Elsevier B.V. All rights reserved.

Dissociable identity- and modality-specific neural representations as revealed by cross-modal nonspatial inhibition of return.

PubMed

Chi, Yukai; Yue, Zhenzhu; Liu, Yupin; Mo, Lei; Chen, Qi

2014-08-01

There are ongoing debates on whether object concepts are coded as supramodal identity-based or modality-specific representations in the human brain. In this fMRI study, we adopted a cross-modal "prime-neutral cue-target" semantic priming paradigm, in which the prime-target relationship was manipulated along both the identity and the modality dimensions. The prime and the target could refer to either the same or different semantic identities, and could be delivered via either the same or different sensory modalities. By calculating the main effects and interactions of this 2 (identity cue validity: "Identity_Cued" vs. "Identity_Uncued") × 2 (modality cue validity: "Modality_Cued" vs. "Modality_Uncued") factorial design, we aimed at dissociating three neural networks involved in creating novel identity-specific representations independent of sensory modality, in creating modality-specific representations independent of semantic identity, and in evaluating changes of an object along both the identity and the modality dimensions, respectively. Our results suggested that bilateral lateral occipital cortex was involved in creating a new supramodal semantic representation irrespective of the input modality, left dorsal premotor cortex, and left intraparietal sulcus were involved in creating a new modality-specific representation irrespective of its semantic identity, and bilateral superior temporal sulcus was involved in creating a representation when the identity and modality properties were both cued or both uncued. In addition, right inferior frontal gyrus showed enhanced neural activity only when both the identity and the modality of the target were new, indicating its functional role in novelty detection. Copyright © 2014 Wiley Periodicals, Inc.

Decorrelated jet substructure tagging using adversarial neural networks

NASA Astrophysics Data System (ADS)

Shimmin, Chase; Sadowski, Peter; Baldi, Pierre; Weik, Edison; Whiteson, Daniel; Goul, Edward; Søgaard, Andreas

2017-10-01

We describe a strategy for constructing a neural network jet substructure tagger which powerfully discriminates boosted decay signals while remaining largely uncorrelated with the jet mass. This reduces the impact of systematic uncertainties in background modeling while enhancing signal purity, resulting in improved discovery significance relative to existing taggers. The network is trained using an adversarial strategy, resulting in a tagger that learns to balance classification accuracy with decorrelation. As a benchmark scenario, we consider the case where large-radius jets originating from a boosted resonance decay are discriminated from a background of nonresonant quark and gluon jets. We show that in the presence of systematic uncertainties on the background rate, our adversarially trained, decorrelated tagger considerably outperforms a conventionally trained neural network, despite having a slightly worse signal-background separation power. We generalize the adversarial training technique to include a parametric dependence on the signal hypothesis, training a single network that provides optimized, interpolatable decorrelated jet tagging across a continuous range of hypothetical resonance masses, after training on discrete choices of the signal mass.

Adaptive Neural Tracking Control for Switched High-Order Stochastic Nonlinear Systems.

PubMed

Zhao, Xudong; Wang, Xinyong; Zong, Guangdeng; Zheng, Xiaolong

2017-10-01

This paper deals with adaptive neural tracking control design for a class of switched high-order stochastic nonlinear systems with unknown uncertainties and arbitrary deterministic switching. The considered issues are: 1) completely unknown uncertainties; 2) stochastic disturbances; and 3) high-order nonstrict-feedback system structure. The considered mathematical models can represent many practical systems in the actual engineering. By adopting the approximation ability of neural networks, common stochastic Lyapunov function method together with adding an improved power integrator technique, an adaptive state feedback controller with multiple adaptive laws is systematically designed for the systems. Subsequently, a controller with only two adaptive laws is proposed to solve the problem of over parameterization. Under the designed controllers, all the signals in the closed-loop system are bounded-input bounded-output stable in probability, and the system output can almost surely track the target trajectory within a specified bounded error. Finally, simulation results are presented to show the effectiveness of the proposed approaches.

Vibration control of uncertain multiple launch rocket system using radial basis function neural network

NASA Astrophysics Data System (ADS)

Li, Bo; Rui, Xiaoting

2018-01-01

Poor dispersion characteristics of rockets due to the vibration of Multiple Launch Rocket System (MLRS) have always restricted the MLRS development for several decades. Vibration control is a key technique to improve the dispersion characteristics of rockets. For a mechanical system such as MLRS, the major difficulty in designing an appropriate control strategy that can achieve the desired vibration control performance is to guarantee the robustness and stability of the control system under the occurrence of uncertainties and nonlinearities. To approach this problem, a computed torque controller integrated with a radial basis function neural network is proposed to achieve the high-precision vibration control for MLRS. In this paper, the vibration response of a computed torque controlled MLRS is described. The azimuth and elevation mechanisms of the MLRS are driven by permanent magnet synchronous motors and supposed to be rigid. First, the dynamic model of motor-mechanism coupling system is established using Lagrange method and field-oriented control theory. Then, in order to deal with the nonlinearities, a computed torque controller is designed to control the vibration of the MLRS when it is firing a salvo of rockets. Furthermore, to compensate for the lumped uncertainty due to parametric variations and un-modeled dynamics in the design of the computed torque controller, a radial basis function neural network estimator is developed to adapt the uncertainty based on Lyapunov stability theory. Finally, the simulated results demonstrate the effectiveness of the proposed control system and show that the proposed controller is robust with regard to the uncertainty.

Dissociating retrieval success from incidental encoding activity during emotional memory retrieval, in the medial temporal lobe

PubMed Central

Shafer, Andrea T.; Dolcos, Florin

2014-01-01

The memory-enhancing effect of emotion has been linked to the engagement of emotion- and memory-related medial temporal lobe (MTL) regions (amygdala-AMY; hippocampus-HC; parahippocampus-PHC), during both encoding and retrieval. However, recognition tasks used to investigate the neural correlates of retrieval make it difficult to distinguish MTL engagement linked to retrieval success (RS) from that linked to incidental encoding success (ES) during retrieval. This issue has been investigated for retrieval of non-emotional memories, but not for emotional memory retrieval. To address this, we used event-related functional MRI in conjunction with an emotional distraction and two episodic memory tasks (one testing memory for distracter items and the other testing memory for new/lure items presented in the first memory task). This paradigm allowed for dissociation of MTL activity specifically linked to RS from that linked to both RS and incidental ES during retrieval. There were two novel findings regarding the neural correlates of emotional memory retrieval. First, greater emotional RS was identified bilaterally in AMY, HC, and PHC. However, AMY activity was most impacted when accounting for ES activity, as only RS activity in left AMY was dissociated from ES activity during retrieval, whereas portions of HC and PHC showing greater emotional RS were largely uninvolved in ES. Second, an earlier and more anteriorly spread response (left AMY and bilateral HC, PHC) was linked to greater emotional RS activity, whereas a later and more posteriorly localized response (right posterior PHC) was linked to greater neutral RS activity. These findings shed light on MTL mechanisms subserving the memory-enhancing effect of emotion at retrieval. PMID:24917798

Face Encoding and Recognition in the Human Brain

NASA Astrophysics Data System (ADS)

Haxby, James V.; Ungerleider, Leslie G.; Horwitz, Barry; Maisog, Jose Ma.; Rapoport, Stanley I.; Grady, Cheryl L.

1996-01-01

A dissociation between human neural systems that participate in the encoding and later recognition of new memories for faces was demonstrated by measuring memory task-related changes in regional cerebral blood flow with positron emission tomography. There was almost no overlap between the brain structures associated with these memory functions. A region in the right hippocampus and adjacent cortex was activated during memory encoding but not during recognition. The most striking finding in neocortex was the lateralization of prefrontal participation. Encoding activated left prefrontal cortex, whereas recognition activated right prefrontal cortex. These results indicate that the hippocampus and adjacent cortex participate in memory function primarily at the time of new memory encoding. Moreover, face recognition is not mediated simply by recapitulation of operations performed at the time of encoding but, rather, involves anatomically dissociable operations.

A new delay-independent condition for global robust stability of neural networks with time delays.

PubMed

Samli, Ruya

2015-06-01

This paper studies the problem of robust stability of dynamical neural networks with discrete time delays under the assumptions that the network parameters of the neural system are uncertain and norm-bounded, and the activation functions are slope-bounded. By employing the results of Lyapunov stability theory and matrix theory, new sufficient conditions for the existence, uniqueness and global asymptotic stability of the equilibrium point for delayed neural networks are presented. The results reported in this paper can be easily tested by checking some special properties of symmetric matrices associated with the parameter uncertainties of neural networks. We also present a numerical example to show the effectiveness of the proposed theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

fMRI functional connectivity of the periaqueductal gray in PTSD and its dissociative subtype.

PubMed

Harricharan, Sherain; Rabellino, Daniela; Frewen, Paul A; Densmore, Maria; Théberge, Jean; McKinnon, Margaret C; Schore, Allan N; Lanius, Ruth A

2016-12-01

Posttraumatic stress disorder (PTSD) is associated with hyperarousal and active fight or flight defensive responses. By contrast, the dissociative subtype of PTSD, characterized by depersonalization and derealization symptoms, is frequently accompanied by additional passive or submissive defensive responses associated with autonomic blunting. Here, the periaqueductal gray (PAG) plays a central role in defensive responses, where the dorsolateral (DL-PAG) and ventrolateral PAG (VL-PAG) are thought to mediate active and passive defensive responses, respectively. We examined PAG subregion (dorsolateral and ventrolateral) resting-state functional connectivity in three groups: PTSD patients without the dissociative subtype ( n  = 60); PTSD patients with the dissociative subtype ( n  = 37); and healthy controls ( n  = 40) using a seed-based approach via PickAtlas and SPM12. All PTSD patients showed extensive DL- and VL-PAG functional connectivity at rest with areas associated with emotional reactivity and defensive action as compared to controls ( n  = 40). Although all PTSD patients demonstrated DL-PAG functional connectivity with areas associated with initiation of active coping strategies and hyperarousal (e.g., dorsal anterior cingulate; anterior insula), only dissociative PTSD patients exhibited greater VL-PAG functional connectivity with brain regions linked to passive coping strategies and increased levels of depersonalization (e.g., temporoparietal junction; rolandic operculum). These findings suggest greater defensive posturing in PTSD patients even at rest and demonstrate that those with the dissociative subtype show unique patterns of PAG functional connectivity when compared to those without the subtype. Taken together, these findings represent an important first step toward identifying neural and behavioral targets for therapeutic interventions that address defensive strategies in trauma-related disorders.

Dissociations in cognitive memory: the syndrome of developmental amnesia.

PubMed

Vargha-Khadem, F; Gadian, D G; Mishkin, M

2001-09-29

The dearth of studies on amnesia in children has led to the assumption that when damage to the medial temporal lobe system occurs early in life, the compensatory capacity of the immature brain rescues memory functions. An alternative view is that such damage so interferes with the development of learning and memory that it results not in selective cognitive impairments but in general mental retardation. Data will be presented to counter both of these arguments. Results obtained from a series of 11 amnesic patients with a history of hypoxic ischaemic damage sustained perinatally or during childhood indicate that regardless of age at onset of hippocampal pathology, there is a pronounced dissociation between episodic memory, which is severely impaired, and semantic memory, which is relatively preserved. A second dissociation is characterized by markedly impaired recall and relatively spared recognition leading to a distinction between recollection-based versus familiarity-based judgements. These findings are discussed in terms of the locus and extent of neuropathology associated with hypoxic ischaemic damage, the neural basis of 'remembering' versus 'knowing', and a hierarchical model of cognitive memory.

The parietal cortex in sensemaking: the dissociation of multiple types of spatial information.

PubMed

Sun, Yanlong; Wang, Hongbin

2013-01-01

According to the data-frame theory, sensemaking is a macrocognitive process in which people try to make sense of or explain their observations by processing a number of explanatory structures called frames until the observations and frames become congruent. During the sensemaking process, the parietal cortex has been implicated in various cognitive tasks for the functions related to spatial and temporal information processing, mathematical thinking, and spatial attention. In particular, the parietal cortex plays important roles by extracting multiple representations of magnitudes at the early stages of perceptual analysis. By a series of neural network simulations, we demonstrate that the dissociation of different types of spatial information can start early with a rather similar structure (i.e., sensitivity on a common metric), but accurate representations require specific goal-directed top-down controls due to the interference in selective attention. Our results suggest that the roles of the parietal cortex rely on the hierarchical organization of multiple spatial representations and their interactions. The dissociation and interference between different types of spatial information are essentially the result of the competition at different levels of abstraction.

The Parietal Cortex in Sensemaking: The Dissociation of Multiple Types of Spatial Information

PubMed Central

Sun, Yanlong; Wang, Hongbin

2013-01-01

According to the data-frame theory, sensemaking is a macrocognitive process in which people try to make sense of or explain their observations by processing a number of explanatory structures called frames until the observations and frames become congruent. During the sensemaking process, the parietal cortex has been implicated in various cognitive tasks for the functions related to spatial and temporal information processing, mathematical thinking, and spatial attention. In particular, the parietal cortex plays important roles by extracting multiple representations of magnitudes at the early stages of perceptual analysis. By a series of neural network simulations, we demonstrate that the dissociation of different types of spatial information can start early with a rather similar structure (i.e., sensitivity on a common metric), but accurate representations require specific goal-directed top-down controls due to the interference in selective attention. Our results suggest that the roles of the parietal cortex rely on the hierarchical organization of multiple spatial representations and their interactions. The dissociation and interference between different types of spatial information are essentially the result of the competition at different levels of abstraction. PMID:23710165

Dissociation between morality and disgust: an event-related potential study.

PubMed

Yang, Qun; Li, An; Xiao, Xiao; Zhang, Ye; Tian, Xuehong

2014-10-01

This study explored the neural correlates of morality and disgust, particularly, how the mechanisms that mediate our avoidance of physically disgusting and morally abhorrent behaviors are neurologically dissociated during the time-course of processing. Twelve participants were asked to judge the acceptability of different types of behaviors, which varied in their level of moral wrongness and physical disgust, while event-related potentials (ERPs) were recorded. The main results showed that the two morally wrong conditions elicited greater amplitudes of P300-400 at frontal sites than the neutral condition and the physically disgusting, but not morally wrong, condition. The physically disgusting conditions (with and without moral content) elicited significantly more positive deflections in the 500-600 ms timeframe than the neutral condition at central-posterior sites. These findings indicate that our aversion to harmful substances in the physical environment and offensive behaviors in the social environment may be neurologically dissociable in the temporal dimension. Furthermore, the detection of moral violations may be processed earlier in time than that of physical disgust. Copyright © 2014 Elsevier B.V. All rights reserved.

The Impact of Anxiety-Inducing Distraction on Cognitive Performance: A Combined Brain Imaging and Personality Investigation

PubMed Central

Denkova, Ekaterina; Wong, Gloria; Dolcos, Sanda; Sung, Keen; Wang, Lihong; Coupland, Nicholas; Dolcos, Florin

2010-01-01

Background Previous investigations revealed that the impact of task-irrelevant emotional distraction on ongoing goal-oriented cognitive processing is linked to opposite patterns of activation in emotional and perceptual vs. cognitive control/executive brain regions. However, little is known about the role of individual variations in these responses. The present study investigated the effect of trait anxiety on the neural responses mediating the impact of transient anxiety-inducing task-irrelevant distraction on cognitive performance, and on the neural correlates of coping with such distraction. We investigated whether activity in the brain regions sensitive to emotional distraction would show dissociable patterns of co-variation with measures indexing individual variations in trait anxiety and cognitive performance. Methodology/Principal Findings Event-related fMRI data, recorded while healthy female participants performed a delayed-response working memory (WM) task with distraction, were investigated in conjunction with behavioural measures that assessed individual variations in both trait anxiety and WM performance. Consistent with increased sensitivity to emotional cues in high anxiety, specific perceptual areas (fusiform gyrus - FG) exhibited increased activity that was positively correlated with trait anxiety and negatively correlated with WM performance, whereas specific executive regions (right lateral prefrontal cortex - PFC) exhibited decreased activity that was negatively correlated with trait anxiety. The study also identified a role of the medial and left lateral PFC in coping with distraction, as opposed to reflecting a detrimental impact of emotional distraction. Conclusions These findings provide initial evidence concerning the neural mechanisms sensitive to individual variations in trait anxiety and WM performance, which dissociate the detrimental impact of emotion distraction and the engagement of mechanisms to cope with distracting emotions. Our study sheds light on the neural correlates of emotion-cognition interactions in normal behaviour, which has implications for understanding factors that may influence susceptibility to affective disorders, in general, and to anxiety disorders, in particular. PMID:21152391

Uncertainty and Cognitive Control

PubMed Central

Mushtaq, Faisal; Bland, Amy R.; Schaefer, Alexandre

2011-01-01

A growing trend of neuroimaging, behavioral, and computational research has investigated the topic of outcome uncertainty in decision-making. Although evidence to date indicates that humans are very effective in learning to adapt to uncertain situations, the nature of the specific cognitive processes involved in the adaptation to uncertainty are still a matter of debate. In this article, we reviewed evidence suggesting that cognitive control processes are at the heart of uncertainty in decision-making contexts. Available evidence suggests that: (1) There is a strong conceptual overlap between the constructs of uncertainty and cognitive control; (2) There is a remarkable overlap between the neural networks associated with uncertainty and the brain networks subserving cognitive control; (3) The perception and estimation of uncertainty might play a key role in monitoring processes and the evaluation of the “need for control”; (4) Potential interactions between uncertainty and cognitive control might play a significant role in several affective disorders. PMID:22007181

Face Aftereffects Indicate Dissociable, but Not Distinct, Coding of Male and Female Faces

ERIC Educational Resources Information Center

Jaquet, Emma; Rhodes, Gillian

2008-01-01

It has been claimed that exposure to distorted faces of one sex induces perceptual aftereffects for test faces that are of the same sex, but not for test faces of the other sex (A. C. Little, L. M. DeBruine, & B. C. Jones, 2005). This result suggests that male and female faces have separate neural coding. Given the high degree of visual similarity…

Three-dimensional micro-electrode array for recording dissociated neuronal cultures.

PubMed

Musick, Katherine; Khatami, David; Wheeler, Bruce C

2009-07-21

This work demonstrates the design, fabrication, packaging, characterization, and functionality of an electrically and fluidically active three-dimensional micro-electrode array (3D MEA) for use with neuronal cell cultures. The successful function of the device implies that this basic concept-construction of a 3D array with a layered approach-can be utilized as the basis for a new family of neural electrode arrays. The 3D MEA prototype consists of a stack of individually patterned thin films that form a cell chamber conducive to maintaining and recording the electrical activity of a long-term three-dimensional network of rat cortical neurons. Silicon electrode layers contain a polymer grid for neural branching, growth, and network formation. Along the walls of these electrode layers lie exposed gold electrodes which permit recording and stimulation of the neuronal electrical activity. Silicone elastomer micro-fluidic layers provide a means for loading dissociated neurons into the structure and serve as the artificial vasculature for nutrient supply and aeration. The fluidic layers also serve as insulation for the micro-electrodes. Cells have been shown to survive in the 3D MEA for up to 28 days, with spontaneous and evoked electrical recordings performed in that time. The micro-fluidic capability was demonstrated by flowing in the drug tetrotodoxin to influence the activity of the culture.

A temporal dissociation of subliminal versus supraliminal fear perception: an event-related potential study.

PubMed

Liddell, Belinda J; Williams, Leanne M; Rathjen, Jennifer; Shevrin, Howard; Gordon, Evian

2004-04-01

Current theories of emotion suggest that threat-related stimuli are first processed via an automatically engaged neural mechanism, which occurs outside conscious awareness. This mechanism operates in conjunction with a slower and more comprehensive process that allows a detailed evaluation of the potentially harmful stimulus (LeDoux, 1998). We drew on the Halgren and Marinkovic (1995) model to examine these processes using event-related potentials (ERPs) within a backward masking paradigm. Stimuli used were faces with fear and neutral (as baseline control) expressions, presented above (supraliminal) and below (subliminal) the threshold for conscious detection. ERP data revealed a double dissociation for the supraliminal versus subliminal perception of fear. In the subliminal condition, responses to the perception of fear stimuli were enhanced relative to neutral for the N2 "excitatory" component, which is thought to represent orienting and automatic aspects of face processing. By contrast, supraliminal perception of fear was associated with relatively enhanced responses for the late P3 "inhibitory" component, implicated in the integration of emotional processes. These findings provide evidence in support of Halgren and Marinkovic's temporal model of emotion processing, and indicate that the neural mechanisms for appraising signals of threat may be initiated, not only automatically, but also without the need for conscious detection of these signals.

Attending to the present: mindfulness meditation reveals distinct neural modes of self-reference

PubMed Central

Farb, Norman A. S.; Segal, Zindel V.; Mayberg, Helen; Bean, Jim; McKeon, Deborah; Fatima, Zainab

2007-01-01

It has long been theorised that there are two temporally distinct forms of self-reference: extended self-reference linking experiences across time, and momentary self-reference centred on the present. To characterise these two aspects of awareness, we used functional magnetic resonance imaging (fMRI) to examine monitoring of enduring traits (’narrative’ focus, NF) or momentary experience (’experiential’ focus, EF) in both novice participants and those having attended an 8 week course in mindfulness meditation, a program that trains individuals to develop focused attention on the present. In novices, EF yielded focal reductions in self-referential cortical midline regions (medial prefrontal cortex, mPFC) associated with NF. In trained participants, EF resulted in more marked and pervasive reductions in the mPFC, and increased engagement of a right lateralised network, comprising the lateral PFC and viscerosomatic areas such as the insula, secondary somatosensory cortex and inferior parietal lobule. Functional connectivity analyses further demonstrated a strong coupling between the right insula and the mPFC in novices that was uncoupled in the mindfulness group. These results suggest a fundamental neural dissociation between two distinct forms of self-awareness that are habitually integrated but can be dissociated through attentional training: the self across time and in the present moment. PMID:18985137

Hearing Scenes: A Neuromagnetic Signature of Auditory Source and Reverberant Space Separation

PubMed Central

Oliva, Aude

2017-01-01

Abstract Perceiving the geometry of surrounding space is a multisensory process, crucial to contextualizing object perception and guiding navigation behavior. Humans can make judgments about surrounding spaces from reverberation cues, caused by sounds reflecting off multiple interior surfaces. However, it remains unclear how the brain represents reverberant spaces separately from sound sources. Here, we report separable neural signatures of auditory space and source perception during magnetoencephalography (MEG) recording as subjects listened to brief sounds convolved with monaural room impulse responses (RIRs). The decoding signature of sound sources began at 57 ms after stimulus onset and peaked at 130 ms, while space decoding started at 138 ms and peaked at 386 ms. Importantly, these neuromagnetic responses were readily dissociable in form and time: while sound source decoding exhibited an early and transient response, the neural signature of space was sustained and independent of the original source that produced it. The reverberant space response was robust to variations in sound source, and vice versa, indicating a generalized response not tied to specific source-space combinations. These results provide the first neuromagnetic evidence for robust, dissociable auditory source and reverberant space representations in the human brain and reveal the temporal dynamics of how auditory scene analysis extracts percepts from complex naturalistic auditory signals. PMID:28451630

Occipital Alpha and Gamma Oscillations Support Complementary Mechanisms for Processing Stimulus Value Associations.

PubMed

Marshall, Tom R; den Boer, Sebastiaan; Cools, Roshan; Jensen, Ole; Fallon, Sean James; Zumer, Johanna M

2018-01-01

Selective attention is reflected neurally in changes in the power of posterior neural oscillations in the alpha (8-12 Hz) and gamma (40-100 Hz) bands. Although a neural mechanism that allows relevant information to be selectively processed has its advantages, it may lead to lucrative or dangerous information going unnoticed. Neural systems are also in place for processing rewarding and punishing information. Here, we examine the interaction between selective attention (left vs. right) and stimulus's learned value associations (neutral, punished, or rewarded) and how they compete for control of posterior neural oscillations. We found that both attention and stimulus-value associations influenced neural oscillations. Whereas selective attention had comparable effects on alpha and gamma oscillations, value associations had dissociable effects on these neural markers of attention. Salient targets (associated with positive and negative outcomes) hijacked changes in alpha power-increasing hemispheric alpha lateralization when salient targets were attended, decreasing it when they were being ignored. In contrast, hemispheric gamma-band lateralization was specifically abolished by negative distractors. Source analysis indicated occipital generators of both attentional and value effects. Thus, posterior cortical oscillations support both the ability to selectively attend while at the same time retaining the ability to remain sensitive to valuable features in the environment. Moreover, the versatility of our attentional system to respond separately to salient from merely positively valued stimuli appears to be carried out by separate neural processes reflected in different frequency bands.

Delineating the Neural Signatures of Tracking Spatial Position and Working Memory during Attentive Tracking

PubMed Central

Drew, Trafton; Horowitz, Todd S.; Wolfe, Jeremy M.; Vogel, Edward K.

2015-01-01

In the attentive tracking task, observers track multiple objects as they move independently and unpredictably among visually identical distractors. Although a number of models of attentive tracking implicate visual working memory as the mechanism responsible for representing target locations, no study has ever directly compared the neural mechanisms of the two tasks. In the current set of experiments, we used electrophysiological recordings to delineate similarities and differences between the neural processing involved in working memory and attentive tracking. We found that the contralateral electrophysiological response to the two tasks was similarly sensitive to the number of items attended in both tasks but that there was also a unique contralateral negativity related to the process of monitoring target position during tracking. This signal was absent for periods of time during tracking tasks when objects briefly stopped moving. These results provide evidence that, during attentive tracking, the process of tracking target locations elicits an electrophysiological response that is distinct and dissociable from neural measures of the number of items being attended. PMID:21228175

Experimental study of iron-chloride complexing in hydrothermal fluids

USGS Publications Warehouse

Fein, J.B.; Hemley, J.J.; d'Angelo, W. M.; Komninou, A.; Sverjensky, D.A.

1992-01-01

Mineral assemblage solubilities were measured in cold-seal pressure vessels as a function of pressure, temperature, and potassium chloride concentration in order to determine the nature and thermodynamic properties of iron-chloride complexes under hydrothermal conditions. The assemblage pyritepyrrhotite-magnetite was used to buffer f{hook}S2 and f{hook}O2, and K+ H+ ratios were buffered at reasonable geologic values using the assemblage potassium feldspar-muscovite (or andalusite)-quartz. The pressure-temperature ranges were 0.5-2.0 kbar and 300-600??C, and initial fluid compositions ranged from 0.01-2.0 molal KCl. With all other factors constant, the concentration of iron in solution increases with increasing temperature, with decreasing pressure, and with increasing total potassium chloride concentration. Changes in iron concentrations as a function of KCl concentration, in conjunction with charge balance, mass action, and mass balance constraints on the system, place constraints on the stoichiometry of the important iron-chloride complexes under each of the experimental conditions. Using least-squared linear regression fits to determine these slopes, the calculations yield values for the average ligand numbers that are in the range 1.2-1.9, with uncertainties ranging from ??0.1-0.6 at the several PT conditions considered. The slopes of the regressed fits to the data suggest that both FeCl+ and FeCl20 are important in the experimental fluids, with FeCl20 becoming dominant at the higher temperatures. Theoretical calculations, however, indicate that FeCl+ does not contribute significantly to the solubility. Because of the large uncertainties associated with some of the calculated average ligand numbers, we base our data analysis on the theoretical calculations. A statistical analysis is applied to the solubility data in order to determine the values and uncertainties of the dissociation constant for FeCl20 that best fit the data at each of the experimental pressures and temperatures. The calculated stability of FeCl20 increases with increasing temperature and total chloride concentration, and with decreasing pressure. The values of the dissociation constant of FeCl20that are calculated in this study are in moderately good agreement with FeCl20dissociation constants from other studies of iron-chloride complexing in supercritical fluids. Differences are likely due to different assumptions made concerning activity coefficients of aqueous species. Log kd values for full dissociation of FeCl20 at 0.5 kbar-300??C-and at 1 kbar-400, 500, and 600??C, respectively-are -3.75 ?? 0.40, -6.25 ?? 0.10, -9.19 ?? 0.44, and -13.29 ?? 0.09. ?? 1992.

Feature-based and object-based attention orientation during short-term memory maintenance.

PubMed

Ku, Yixuan

2015-12-01

Top-down attention biases the short-term memory (STM) processing at multiple stages. Orienting attention during the maintenance period of STM by a retrospective cue (retro-cue) strengthens the representation of the cued item and improves the subsequent STM performance. In a recent article, Backer et al. (Backer KC, Binns MA, Alain C. J Neurosci 35: 1307-1318, 2015) extended these findings from the visual to the auditory domain and combined electroencephalography to dissociate neural mechanisms underlying feature-based and object-based attention orientation. Both event-related potentials and neural oscillations explained the behavioral benefits of retro-cues and favored the theory that feature-based and object-based attention orientation were independent. Copyright © 2015 the American Physiological Society.

Damage to the ventromedial prefrontal cortex reduces interpersonal disgust.

PubMed

Ciaramelli, Elisa; Sperotto, Rebecca G; Mattioli, Flavia; di Pellegrino, Giuseppe

2013-02-01

Disgust for contaminating objects (core disgust), immoral behaviors (moral disgust) and unsavory others (interpersonal disgust), have been assumed to be closely related. It is not clear, however, whether different forms of disgust are mediated by overlapping or specific neural substrates. We report that 10 patients with damage to the ventromedial prefrontal cortex (vmPFC) avoided behaviors that normally elicit interpersonal disgust (e.g. using the scarf of a busker) less frequently than healthy and brain-damaged controls, whereas they avoided core and moral disgust elicitors at normal rates. These results indicate that different forms of disgust are dissociated neurally. We propose that the vmPFC is causally (and selectively) involved in mediating interpersonal disgust, shaping patterns of social avoidance and approach.

Damage to the ventromedial prefrontal cortex reduces interpersonal disgust

PubMed Central

Ciaramelli, Elisa; Sperotto, Rebecca G.; Mattioli, Flavia

2013-01-01

Disgust for contaminating objects (core disgust), immoral behaviors (moral disgust) and unsavory others (interpersonal disgust), have been assumed to be closely related. It is not clear, however, whether different forms of disgust are mediated by overlapping or specific neural substrates. We report that 10 patients with damage to the ventromedial prefrontal cortex (vmPFC) avoided behaviors that normally elicit interpersonal disgust (e.g. using the scarf of a busker) less frequently than healthy and brain-damaged controls, whereas they avoided core and moral disgust elicitors at normal rates. These results indicate that different forms of disgust are dissociated neurally. We propose that the vmPFC is causally (and selectively) involved in mediating interpersonal disgust, shaping patterns of social avoidance and approach. PMID:22842816

A causal role for right frontopolar cortex in directed, but not random, exploration

PubMed Central

Zajkowski, Wojciech K; Kossut, Malgorzata

2017-01-01

The explore-exploit dilemma occurs anytime we must choose between exploring unknown options for information and exploiting known resources for reward. Previous work suggests that people use two different strategies to solve the explore-exploit dilemma: directed exploration, driven by information seeking, and random exploration, driven by decision noise. Here, we show that these two strategies rely on different neural systems. Using transcranial magnetic stimulation to inhibit the right frontopolar cortex, we were able to selectively inhibit directed exploration while leaving random exploration intact. This suggests a causal role for right frontopolar cortex in directed, but not random, exploration and that directed and random exploration rely on (at least partially) dissociable neural systems. PMID:28914605

Unique insula subregion resting-state functional connectivity with amygdala complexes in posttraumatic stress disorder and its dissociative subtype.

PubMed

Nicholson, Andrew A; Sapru, Iman; Densmore, Maria; Frewen, Paul A; Neufeld, Richard W J; Théberge, Jean; McKinnon, Margaret C; Lanius, Ruth A

2016-04-30

The insula and amygdala are implicated in the pathophysiology of posttraumatic stress disorder (PTSD), where both have been shown to be hyper/hypoactive in non-dissociative (PTSD-DS) and dissociative subtype (PTSD+DS) PTSD patients, respectively, during symptom provocation. However, the functional connectivity between individual insula subregions and the amygdala has not been investigated in persons with PTSD, with or without the dissociative subtype. We examined insula subregion (anterior, mid, and posterior) functional connectivity with the bilateral amygdala using a region-of-interest seed-based approach via PickAtlas and SPM8. Resting-state fMRI was conducted with (n=61) PTSD patients (n=44 PTSD-DS; n=17 PTSD+DS), and (n=40) age-matched healthy controls. When compared to controls, the PTSD-DS group displayed increased insula connectivity (bilateral anterior, bilateral mid, and left posterior) to basolateral amygdala clusters in both hemispheres, and the PTSD+DS group displayed increased insula connectivity (bilateral anterior, left mid, and left posterior) to the left basolateral amygdala complex. Moreover, as compared to PTSD-DS, increased insula subregion connectivity (bilateral anterior, left mid, and right posterior) to the left basolateral amygdala was found in PTSD+DS. Depersonalization/derealization symptoms and PTSD symptom severity correlated with insula subregion connectivity to the basolateral amygdala within PTSD patients. This study is an important first step in elucidating patterns of neural connectivity associated with unique symptoms of arousal/interoception, emotional processing, and awareness of bodily states, in PTSD and its dissociative subtype. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A recurrent neural-network-based sensor and actuator fault detection and isolation for nonlinear systems with application to the satellite's attitude control subsystem.

PubMed

Talebi, H A; Khorasani, K; Tafazoli, S

2009-01-01

This paper presents a robust fault detection and isolation (FDI) scheme for a general class of nonlinear systems using a neural-network-based observer strategy. Both actuator and sensor faults are considered. The nonlinear system considered is subject to both state and sensor uncertainties and disturbances. Two recurrent neural networks are employed to identify general unknown actuator and sensor faults, respectively. The neural network weights are updated according to a modified backpropagation scheme. Unlike many previous methods developed in the literature, our proposed FDI scheme does not rely on availability of full state measurements. The stability of the overall FDI scheme in presence of unknown sensor and actuator faults as well as plant and sensor noise and uncertainties is shown by using the Lyapunov's direct method. The stability analysis developed requires no restrictive assumptions on the system and/or the FDI algorithm. Magnetorquer-type actuators and magnetometer-type sensors that are commonly employed in the attitude control subsystem (ACS) of low-Earth orbit (LEO) satellites for attitude determination and control are considered in our case studies. The effectiveness and capabilities of our proposed fault diagnosis strategy are demonstrated and validated through extensive simulation studies.

Dissociated effects of anticipating smoking versus monetary reward in the caudate as a function of smoking abstinence.

PubMed

Sweitzer, Maggie M; Geier, Charles F; Joel, Danielle L; McGurrin, Patrick; Denlinger, Rachel L; Forbes, Erika E; Donny, Eric C

2014-11-01

Theories of addiction suggest that chronic smoking may be associated with both hypersensitivity to smoking and related cues and hyposensitivity to alternative reinforcers. However, neural responses to smoking and nonsmoking rewards are rarely evaluated within the same paradigm, leaving the extent to which both processes operate simultaneously uncertain. Behavioral evidence and theoretical models suggest that dysregulated reward processing may be more pronounced during deprivation from nicotine, but neuroimaging evidence on the effects of deprivation on reward processing is limited. The current study examined the impact of deprivation from smoking on neural processing of both smoking and monetary rewards. Two separate functional magnetic resonance imaging scans were performed in 38 daily smokers, one after smoking without restriction and one following 24 hours of abstinence. A rewarded guessing task was conducted during each scan to evaluate striatal blood oxygen level-dependent response during anticipation of both smoking and monetary rewards. A significant reward type by abstinence interaction was observed in the bilateral caudate and medial prefrontal cortex during reward anticipation. The blood oxygen level-dependent response to anticipation of smoking reward was significantly higher and anticipation of monetary rewards was significantly lower during abstinence compared with nonabstinence. Attenuation of monetary reward-related activation during abstinence was significantly correlated with abstinence-induced increases in craving and withdrawal. These results provide the first direct evidence of dissociated effects of smoking versus monetary rewards as a function of abstinence. The findings suggest an important neural pathway that may underlie the choice to smoke in lieu of alternative reinforcement during a quit attempt. © 2013 Society of Biological Psychiatry Published by Society of Biological Psychiatry All rights reserved.

Common and Dissociable Neural Activity After Mindfulness-Based Stress Reduction and Relaxation Response Programs.

PubMed

Sevinc, Gunes; Hölzel, Britta K; Hashmi, Javeria; Greenberg, Jonathan; McCallister, Adrienne; Treadway, Michael; Schneider, Marissa L; Dusek, Jeffery A; Carmody, James; Lazar, Sara W

2018-06-01

We investigated common and dissociable neural and psychological correlates of two widely used meditation-based stress reduction programs. Participants were randomized to the Relaxation Response (RR; n = 18; 56% female) or the Mindfulness-Based Stress Reduction (MBSR; n = 16; 56% female) programs. Both programs use a "bodyscan" meditation; however, the RR program explicitly emphasizes physical relaxation during this practice, whereas the MBSR program emphasizes mindful awareness with no explicit relaxation instructions. After the programs, neural activity during the respective meditation was investigated using functional magnetic resonance imaging. Both programs were associated with reduced stress (for RR, from 14.1 ± 6.6 to 11.3 ± 5.5 [Cohen's d = 0.50; for MBSR, from 17.7 ± 5.7 to 11.9 ± 5.0 [Cohen's d = 1.02]). Conjunction analyses revealed functional coupling between ventromedial prefrontal regions and supplementary motor areas (p < .001). The disjunction analysis indicated that the RR bodyscan was associated with stronger functional connectivity of the right inferior frontal gyrus-an important hub of intentional inhibition and control-with supplementary motor areas (p < .001, family-wise error [FWE] rate corrected). The MBSR program was uniquely associated with improvements in self-compassion and rumination, and the within-group analysis of MBSR bodyscan revealed significant functional connectivity of the right anterior insula-an important hub of sensory awareness and salience-with pregenual anterior cingulate during bodyscan meditation compared with rest (p = .03, FWE corrected). The bodyscan exercises in each program were associated with both overlapping and differential functional coupling patterns, which were consistent with each program's theoretical foundation. These results may have implications for the differential effects of these programs for the treatment of diverse conditions.

Opposite brain emotion-regulation patterns in identity states of dissociative identity disorder: a PET study and neurobiological model.

PubMed

Reinders, Antje A T S; Willemsen, Antoon T M; den Boer, Johan A; Vos, Herry P J; Veltman, Dick J; Loewenstein, Richard J

2014-09-30

Imaging studies in posttraumatic stress disorder (PTSD) have shown differing neural network patterns between hypo-aroused/dissociative and hyper-aroused subtypes. Since dissociative identity disorder (DID) involves different emotional states, this study tests whether DID fits aspects of the differing brain-activation patterns in PTSD. While brain activation was monitored using positron emission tomography, DID individuals (n=11) and matched DID-simulating healthy controls (n=16) underwent an autobiographic script-driven imagery paradigm in a hypo-aroused and a hyper-aroused identity state. Results were consistent with those previously found in the two PTSD subtypes for the rostral/dorsal anterior cingulate, the prefrontal cortex, and the amygdala and insula, respectively. Furthermore, the dissociative identity state uniquely activated the posterior association areas and the parahippocampal gyri, whereas the hyper-aroused identity state uniquely activated the caudate nucleus. Therefore, we proposed an extended PTSD-based neurobiological model for emotion modulation in DID: the hypo-aroused identity state activates the prefrontal cortex, cingulate, posterior association areas and parahippocampal gyri, thereby overmodulating emotion regulation; the hyper-aroused identity state activates the amygdala and insula as well as the dorsal striatum, thereby undermodulating emotion regulation. This confirms the notion that DID is related to PTSD as hypo-aroused and hyper-arousal states in DID and PTSD are similar. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Neural network modeling and an uncertainty analysis in Bayesian framework: A case study from the KTB borehole site

NASA Astrophysics Data System (ADS)

Maiti, Saumen; Tiwari, Ram Krishna

2010-10-01

A new probabilistic approach based on the concept of Bayesian neural network (BNN) learning theory is proposed for decoding litho-facies boundaries from well-log data. We show that how a multi-layer-perceptron neural network model can be employed in Bayesian framework to classify changes in litho-log successions. The method is then applied to the German Continental Deep Drilling Program (KTB) well-log data for classification and uncertainty estimation in the litho-facies boundaries. In this framework, a posteriori distribution of network parameter is estimated via the principle of Bayesian probabilistic theory, and an objective function is minimized following the scaled conjugate gradient optimization scheme. For the model development, we inflict a suitable criterion, which provides probabilistic information by emulating different combinations of synthetic data. Uncertainty in the relationship between the data and the model space is appropriately taken care by assuming a Gaussian a priori distribution of networks parameters (e.g., synaptic weights and biases). Prior to applying the new method to the real KTB data, we tested the proposed method on synthetic examples to examine the sensitivity of neural network hyperparameters in prediction. Within this framework, we examine stability and efficiency of this new probabilistic approach using different kinds of synthetic data assorted with different level of correlated noise. Our data analysis suggests that the designed network topology based on the Bayesian paradigm is steady up to nearly 40% correlated noise; however, adding more noise (˜50% or more) degrades the results. We perform uncertainty analyses on training, validation, and test data sets with and devoid of intrinsic noise by making the Gaussian approximation of the a posteriori distribution about the peak model. We present a standard deviation error-map at the network output corresponding to the three types of the litho-facies present over the entire litho-section of the KTB. The comparisons of maximum a posteriori geological sections constructed here, based on the maximum a posteriori probability distribution, with the available geological information and the existing geophysical findings suggest that the BNN results reveal some additional finer details in the KTB borehole data at certain depths, which appears to be of some geological significance. We also demonstrate that the proposed BNN approach is superior to the conventional artificial neural network in terms of both avoiding "over-fitting" and aiding uncertainty estimation, which are vital for meaningful interpretation of geophysical records. Our analyses demonstrate that the BNN-based approach renders a robust means for the classification of complex changes in the litho-facies successions and thus could provide a useful guide for understanding the crustal inhomogeneity and the structural discontinuity in many other tectonically complex regions.

The application of immune genetic algorithm in main steam temperature of PID control of BP network

NASA Astrophysics Data System (ADS)

Li, Han; Zhen-yu, Zhang

In order to overcome the uncertainties, large delay, large inertia and nonlinear property of the main steam temperature controlled object in the power plant, a neural network intelligent PID control system based on immune genetic algorithm and BP neural network is designed. Using the immune genetic algorithm global search optimization ability and good convergence, optimize the weights of the neural network, meanwhile adjusting PID parameters using BP network. The simulation result shows that the system is superior to conventional PID control system in the control of quality and robustness.

Neural Correlates of Biased Responses: The Negative Method Effect in the Rosenberg Self-Esteem Scale Is Associated with Right Amygdala Volume.

PubMed

Wang, Yinan; Kong, Feng; Huang, Lijie; Liu, Jia

2016-10-01

Self-esteem is a widely studied construct in psychology that is typically measured by the Rosenberg Self-Esteem Scale (RSES). However, a series of cross-sectional and longitudinal studies have suggested that a simple and widely used unidimensional factor model does not provide an adequate explanation of RSES responses due to method effects. To identify the neural correlates of the method effect, we sought to determine whether and how method effects were associated with the RSES and investigate the neural basis of these effects. Two hundred and eighty Chinese college students (130 males; mean age = 22.64 years) completed the RSES and underwent magnetic resonance imaging (MRI). Behaviorally, method effects were linked to both positively and negatively worded items in the RSES. Neurally, the right amygdala volume negatively correlated with the negative method factor, while the hippocampal volume positively correlated with the general self-esteem factor in the RSES. The neural dissociation between the general self-esteem factor and negative method factor suggests that there are different neural mechanisms underlying them. The amygdala is involved in modulating negative affectivity; therefore, the current study sheds light on the nature of method effects that are related to self-report with a mix of positively and negatively worded items. © 2015 Wiley Periodicals, Inc.

Neural Signatures of Controlled and Automatic Retrieval Processes in Memory-based Decision-making.

PubMed

Khader, Patrick H; Pachur, Thorsten; Weber, Lilian A E; Jost, Kerstin

2016-01-01

Decision-making often requires retrieval from memory. Drawing on the neural ACT-R theory [Anderson, J. R., Fincham, J. M., Qin, Y., & Stocco, A. A central circuit of the mind. Trends in Cognitive Sciences, 12, 136-143, 2008] and other neural models of memory, we delineated the neural signatures of two fundamental retrieval aspects during decision-making: automatic and controlled activation of memory representations. To disentangle these processes, we combined a paradigm developed to examine neural correlates of selective and sequential memory retrieval in decision-making with a manipulation of associative fan (i.e., the decision options were associated with one, two, or three attributes). The results show that both the automatic activation of all attributes associated with a decision option and the controlled sequential retrieval of specific attributes can be traced in material-specific brain areas. Moreover, the two facets of memory retrieval were associated with distinct activation patterns within the frontoparietal network: The dorsolateral prefrontal cortex was found to reflect increasing retrieval effort during both automatic and controlled activation of attributes. In contrast, the superior parietal cortex only responded to controlled retrieval, arguably reflecting the sequential updating of attribute information in working memory. This dissociation in activation pattern is consistent with ACT-R and constitutes an important step toward a neural model of the retrieval dynamics involved in memory-based decision-making.

Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics.

PubMed

Tong, Shaocheng; Wang, Tong; Li, Yongming; Zhang, Huaguang

2014-06-01

This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.

Reliability assessment of serviceability performance of braced retaining walls using a neural network approach

NASA Astrophysics Data System (ADS)

Goh, A. T. C.; Kulhawy, F. H.

2005-05-01

In urban environments, one major concern with deep excavations in soft clay is the potentially large ground deformations in and around the excavation. Excessive movements can damage adjacent buildings and utilities. There are many uncertainties associated with the calculation of the ultimate or serviceability performance of a braced excavation system. These include the variabilities of the loadings, geotechnical soil properties, and engineering and geometrical properties of the wall. A risk-based approach to serviceability performance failure is necessary to incorporate systematically the uncertainties associated with the various design parameters. This paper demonstrates the use of an integrated neural network-reliability method to assess the risk of serviceability failure through the calculation of the reliability index. By first performing a series of parametric studies using the finite element method and then approximating the non-linear limit state surface (the boundary separating the safe and failure domains) through a neural network model, the reliability index can be determined with the aid of a spreadsheet. Two illustrative examples are presented to show how the serviceability performance for braced excavation problems can be assessed using the reliability index.

Beyond Stimulus Cues and Reinforcement Signals: A New Approach to Animal Metacognition

PubMed Central

Couchman, Justin J.; Coutinho, Mariana V. C.; Beran, Michael J.; Smith, J. David

2010-01-01

Some metacognition paradigms for nonhuman animals encourage the alternative explanation that animals avoid difficult trials based only on reinforcement history and stimulus aversion. To explore this possibility, we placed humans and monkeys in successive uncertainty-monitoring tasks that were qualitatively different, eliminating many associative cues that might support transfer across tasks. In addition, task transfer occurred under conditions of deferred and rearranged feedback—both species completed blocks of trials followed by summary feedback. This ensured that animals received no trial-by-trial reinforcement. Despite distancing performance from associative cues, humans and monkeys still made adaptive uncertainty responses by declining the most difficult trials. These findings suggest that monkeys’ uncertainty responses could represent a higher-level, decisional process of cognitive monitoring, though that process need not involve full self-awareness or consciousness. The dissociation of performance from reinforcement has theoretical implications concerning the status of reinforcement as the critical binding force in animal learning. PMID:20836592

Neural effects of methylphenidate and nicotine during smooth pursuit eye movements.

PubMed

Kasparbauer, Anna-Maria; Meyhöfer, Inga; Steffens, Maria; Weber, Bernd; Aydin, Merve; Kumari, Veena; Hurlemann, Rene; Ettinger, Ulrich

2016-11-01

Nicotine and methylphenidate are putative cognitive enhancers in healthy and patient populations. Although they stimulate different neurotransmitter systems, they have been shown to enhance performance on overlapping measures of attention. So far, there has been no direct comparison of the effects of these two stimulants on behavioural performance or brain function in healthy humans. Here, we directly compare the two compounds using a well-established oculomotor biomarker in order to explore common and distinct behavioural and neural effects. Eighty-two healthy male non-smokers performed a smooth pursuit eye movement task while lying in an fMRI scanner. In a between-subjects, double-blind design, subjects either received placebo (placebo patch and capsule), nicotine (7mg nicotine patch and placebo capsule), or methylphenidate (placebo patch and 40mg methylphenidate capsule). There were no significant drug effects on behavioural measures. At the neural level, methylphenidate elicited higher activation in left frontal eye field compared to nicotine, with an intermediate response under placebo. The reduced activation of task-related regions under nicotine could be associated with more efficient neural processing, while increased hemodynamic response under methylphenidate is interpretable as enhanced processing of task-relevant networks. Together, these findings suggest dissociable neural effects of these putative cognitive enhancers. Copyright © 2016 Elsevier Inc. All rights reserved.

Neural Correlates of Consumer Buying Motivations: A 7T functional Magnetic Resonance Imaging (fMRI) Study

PubMed Central

Goodman, Adam M.; Wang, Yun; Kwon, Wi-Suk; Byun, Sang-Eun; Katz, Jeffrey S.; Deshpande, Gopikrishna

2017-01-01

Consumer buying motivations can be distinguished into three categories: functional, experiential, or symbolic motivations (Keller, 1993). Although prior neuroimaging studies have examined the neural substrates which enable these motivations, direct comparisons between these three types of consumer motivations have yet to be made. In the current study, we used 7 Tesla (7T) functional magnetic resonance imaging (fMRI) to assess the neural correlates of each motivation by instructing participants to view common consumer goods while emphasizing either functional, experiential, or symbolic values of these products. The results demonstrated mostly consistent activations between symbolic and experiential motivations. Although, these motivations differed in that symbolic motivation was associated with medial frontal gyrus (MFG) activation, whereas experiential motivation was associated with posterior cingulate cortex (PCC) activation. Functional motivation was associated with dorsolateral prefrontal cortex (DLPFC) activation, as compared to other motivations. These findings provide a neural basis for how symbolic and experiential motivations may be similar, yet different in subtle ways. Furthermore, the dissociation of functional motivation within the DLPFC supports the notion that this motivation relies on executive function processes relatively more than hedonic motivation. These findings provide a better understanding of the underlying neural functioning which may contribute to poor self-control choices. PMID:28959182

Neural Substrates of Spontaneous Musical Performance: An fMRI Study of Jazz Improvisation

PubMed Central

Limb, Charles J.; Braun, Allen R.

2008-01-01

To investigate the neural substrates that underlie spontaneous musical performance, we examined improvisation in professional jazz pianists using functional MRI. By employing two paradigms that differed widely in musical complexity, we found that improvisation (compared to production of over-learned musical sequences) was consistently characterized by a dissociated pattern of activity in the prefrontal cortex: extensive deactivation of dorsolateral prefrontal and lateral orbital regions with focal activation of the medial prefrontal (frontal polar) cortex. Such a pattern may reflect a combination of psychological processes required for spontaneous improvisation, in which internally motivated, stimulus-independent behaviors unfold in the absence of central processes that typically mediate self-monitoring and conscious volitional control of ongoing performance. Changes in prefrontal activity during improvisation were accompanied by widespread activation of neocortical sensorimotor areas (that mediate the organization and execution of musical performance) as well as deactivation of limbic structures (that regulate motivation and emotional tone). This distributed neural pattern may provide a cognitive context that enables the emergence of spontaneous creative activity. PMID:18301756

Neural substrates of spontaneous musical performance: an FMRI study of jazz improvisation.

PubMed

Limb, Charles J; Braun, Allen R

2008-02-27

To investigate the neural substrates that underlie spontaneous musical performance, we examined improvisation in professional jazz pianists using functional MRI. By employing two paradigms that differed widely in musical complexity, we found that improvisation (compared to production of over-learned musical sequences) was consistently characterized by a dissociated pattern of activity in the prefrontal cortex: extensive deactivation of dorsolateral prefrontal and lateral orbital regions with focal activation of the medial prefrontal (frontal polar) cortex. Such a pattern may reflect a combination of psychological processes required for spontaneous improvisation, in which internally motivated, stimulus-independent behaviors unfold in the absence of central processes that typically mediate self-monitoring and conscious volitional control of ongoing performance. Changes in prefrontal activity during improvisation were accompanied by widespread activation of neocortical sensorimotor areas (that mediate the organization and execution of musical performance) as well as deactivation of limbic structures (that regulate motivation and emotional tone). This distributed neural pattern may provide a cognitive context that enables the emergence of spontaneous creative activity.

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

Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior

PubMed Central

Greene, Michelle R; Baldassano, Christopher; Fei-Fei, Li; Beck, Diane M; Baker, Chris I

2018-01-01

Inherent correlations between visual and semantic features in real-world scenes make it difficult to determine how different scene properties contribute to neural representations. Here, we assessed the contributions of multiple properties to scene representation by partitioning the variance explained in human behavioral and brain measurements by three feature models whose inter-correlations were minimized a priori through stimulus preselection. Behavioral assessments of scene similarity reflected unique contributions from a functional feature model indicating potential actions in scenes as well as high-level visual features from a deep neural network (DNN). In contrast, similarity of cortical responses in scene-selective areas was uniquely explained by mid- and high-level DNN features only, while an object label model did not contribute uniquely to either domain. The striking dissociation between functional and DNN features in their contribution to behavioral and brain representations of scenes indicates that scene-selective cortex represents only a subset of behaviorally relevant scene information. PMID:29513219

Distinct contributions of functional and deep neural network features to representational similarity of scenes in human brain and behavior.

PubMed

Groen, Iris Ia; Greene, Michelle R; Baldassano, Christopher; Fei-Fei, Li; Beck, Diane M; Baker, Chris I

2018-03-07

Inherent correlations between visual and semantic features in real-world scenes make it difficult to determine how different scene properties contribute to neural representations. Here, we assessed the contributions of multiple properties to scene representation by partitioning the variance explained in human behavioral and brain measurements by three feature models whose inter-correlations were minimized a priori through stimulus preselection. Behavioral assessments of scene similarity reflected unique contributions from a functional feature model indicating potential actions in scenes as well as high-level visual features from a deep neural network (DNN). In contrast, similarity of cortical responses in scene-selective areas was uniquely explained by mid- and high-level DNN features only, while an object label model did not contribute uniquely to either domain. The striking dissociation between functional and DNN features in their contribution to behavioral and brain representations of scenes indicates that scene-selective cortex represents only a subset of behaviorally relevant scene information.

Nucleus Accumbens Mediates Relative Motivation for Rewards in the Absence of Choice

PubMed Central

Clithero, John A.; Reeck, Crystal; Carter, R. McKell; Smith, David V.; Huettel, Scott A.

2011-01-01

To dissociate a choice from its antecedent neural states, motivation associated with the expected outcome must be captured in the absence of choice. Yet, the neural mechanisms that mediate behavioral idiosyncrasies in motivation, particularly with regard to complex economic preferences, are rarely examined in situations without overt decisions. We employed functional magnetic resonance imaging in a large sample of participants while they anticipated earning rewards from two different modalities: monetary and candy rewards. An index for relative motivation toward different reward types was constructed using reaction times to the target for earning rewards. Activation in the nucleus accumbens (NAcc) and anterior insula (aINS) predicted individual variation in relative motivation between our reward modalities. NAcc activation, however, mediated the effects of aINS, indicating the NAcc is the likely source of this relative weighting. These results demonstrate that neural idiosyncrasies in reward efficacy exist even in the absence of explicit choices, and extend the role of NAcc as a critical brain region for such choice-free motivation. PMID:21941472

Age-related delay in visual and auditory evoked responses is mediated by white- and grey-matter differences.

PubMed

Price, D; Tyler, L K; Neto Henriques, R; Campbell, K L; Williams, N; Treder, M S; Taylor, J R; Henson, R N A

2017-06-09

Slowing is a common feature of ageing, yet a direct relationship between neural slowing and brain atrophy is yet to be established in healthy humans. We combine magnetoencephalographic (MEG) measures of neural processing speed with magnetic resonance imaging (MRI) measures of white and grey matter in a large population-derived cohort to investigate the relationship between age-related structural differences and visual evoked field (VEF) and auditory evoked field (AEF) delay across two different tasks. Here we use a novel technique to show that VEFs exhibit a constant delay, whereas AEFs exhibit delay that accumulates over time. White-matter (WM) microstructure in the optic radiation partially mediates visual delay, suggesting increased transmission time, whereas grey matter (GM) in auditory cortex partially mediates auditory delay, suggesting less efficient local processing. Our results demonstrate that age has dissociable effects on neural processing speed, and that these effects relate to different types of brain atrophy.

Age-related delay in visual and auditory evoked responses is mediated by white- and grey-matter differences

PubMed Central

Price, D.; Tyler, L. K.; Neto Henriques, R.; Campbell, K. L.; Williams, N.; Treder, M.S.; Taylor, J. R.; Brayne, Carol; Bullmore, Edward T.; Calder, Andrew C.; Cusack, Rhodri; Dalgleish, Tim; Duncan, John; Matthews, Fiona E.; Marslen-Wilson, William D.; Rowe, James B.; Shafto, Meredith A.; Cheung, Teresa; Davis, Simon; Geerligs, Linda; Kievit, Rogier; McCarrey, Anna; Mustafa, Abdur; Samu, David; Tsvetanov, Kamen A.; van Belle, Janna; Bates, Lauren; Emery, Tina; Erzinglioglu, Sharon; Gadie, Andrew; Gerbase, Sofia; Georgieva, Stanimira; Hanley, Claire; Parkin, Beth; Troy, David; Auer, Tibor; Correia, Marta; Gao, Lu; Green, Emma; Allen, Jodie; Amery, Gillian; Amunts, Liana; Barcroft, Anne; Castle, Amanda; Dias, Cheryl; Dowrick, Jonathan; Fair, Melissa; Fisher, Hayley; Goulding, Anna; Grewal, Adarsh; Hale, Geoff; Hilton, Andrew; Johnson, Frances; Johnston, Patricia; Kavanagh-Williamson, Thea; Kwasniewska, Magdalena; McMinn, Alison; Norman, Kim; Penrose, Jessica; Roby, Fiona; Rowland, Diane; Sargeant, John; Squire, Maggie; Stevens, Beth; Stoddart, Aldabra; Stone, Cheryl; Thompson, Tracy; Yazlik, Ozlem; Barnes, Dan; Dixon, Marie; Hillman, Jaya; Mitchell, Joanne; Villis, Laura; Henson, R. N. A.

2017-01-01

Slowing is a common feature of ageing, yet a direct relationship between neural slowing and brain atrophy is yet to be established in healthy humans. We combine magnetoencephalographic (MEG) measures of neural processing speed with magnetic resonance imaging (MRI) measures of white and grey matter in a large population-derived cohort to investigate the relationship between age-related structural differences and visual evoked field (VEF) and auditory evoked field (AEF) delay across two different tasks. Here we use a novel technique to show that VEFs exhibit a constant delay, whereas AEFs exhibit delay that accumulates over time. White-matter (WM) microstructure in the optic radiation partially mediates visual delay, suggesting increased transmission time, whereas grey matter (GM) in auditory cortex partially mediates auditory delay, suggesting less efficient local processing. Our results demonstrate that age has dissociable effects on neural processing speed, and that these effects relate to different types of brain atrophy. PMID:28598417

The neural basis of metacognitive ability

PubMed Central

Fleming, Stephen M.; Dolan, Raymond J.

2012-01-01

Ability in various cognitive domains is often assessed by measuring task performance, such as the accuracy of a perceptual categorization. A similar analysis can be applied to metacognitive reports about a task to quantify the degree to which an individual is aware of his or her success or failure. Here, we review the psychological and neural underpinnings of metacognitive accuracy, drawing on research in memory and decision-making. These data show that metacognitive accuracy is dissociable from task performance and varies across individuals. Convergent evidence indicates that the function of the rostral and dorsal aspect of the lateral prefrontal cortex (PFC) is important for the accuracy of retrospective judgements of performance. In contrast, prospective judgements of performance may depend upon medial PFC. We close with a discussion of how metacognitive processes relate to concepts of cognitive control, and propose a neural synthesis in which dorsolateral and anterior prefrontal cortical subregions interact with interoceptive cortices (cingulate and insula) to promote accurate judgements of performance. PMID:22492751

Liking, wanting, and the incentive-sensitization theory of addiction.

PubMed

Berridge, Kent C; Robinson, Terry E

2016-11-01

Rewards are both "liked" and "wanted," and those 2 words seem almost interchangeable. However, the brain circuitry that mediates the psychological process of "wanting" a particular reward is dissociable from circuitry that mediates the degree to which it is "liked." Incentive salience or "wanting," a form of motivation, is generated by large and robust neural systems that include mesolimbic dopamine. By comparison, "liking," or the actual pleasurable impact of reward consumption, is mediated by smaller and fragile neural systems, and is not dependent on dopamine. The incentive-sensitization theory posits the essence of drug addiction to be excessive amplification specifically of psychological "wanting," especially triggered by cues, without necessarily an amplification of "liking." This is because of long-lasting changes in dopamine-related motivation systems of susceptible individuals, called "neural sensitization." A quarter-century after its proposal, evidence has continued to grow in support the incentive-sensitization theory. Further, its scope is now expanding to include diverse behavioral addictions and other psychopathologies. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Liking, Wanting and the Incentive-Sensitization Theory of Addiction

PubMed Central

Berridge, Kent C.; Robinson, Terry E.

2016-01-01

Rewards are both ‘liked’ and ‘wanted’, and those two words seem almost interchangeable. However, the brain circuitry that mediates the psychological process of ‘wanting’ a particular reward is dissociable from circuitry that mediates the degree to which it is ‘liked’. Incentive salience or ‘wanting’, a form of motivation, is generated by large and robust neural systems that include mesolimbic dopamine. By comparison, ‘liking’, or the actual pleasurable impact of reward consumption, is mediated by smaller and fragile neural systems, and is not dependent on dopamine. The incentive-sensitization theory posits the essence of drug addiction to be excessive amplification specifically of psychological ‘wanting’, especially triggered by cues, without necessarily an amplification of ‘liking’. This is due to long-lasting changes in dopamine-related motivation systems of susceptible individuals, called neural sensitization. A quarter-century after its proposal, evidence has continued to grow in support the incentive-sensitization theory. Further, its scope is now expanding to include diverse behavioral addictions and other psychopathologies. PMID:27977239

Adaptive output feedback control of flexible-joint robots using neural networks: dynamic surface design approach.

PubMed

Yoo, Sung Jin; Park, Jin Bae; Choi, Yoon Ho

2008-10-01

In this paper, we propose a new robust output feedback control approach for flexible-joint electrically driven (FJED) robots via the observer dynamic surface design technique. The proposed method only requires position measurements of the FJED robots. To estimate the link and actuator velocity information of the FJED robots with model uncertainties, we develop an adaptive observer using self-recurrent wavelet neural networks (SRWNNs). The SRWNNs are used to approximate model uncertainties in both robot (link) dynamics and actuator dynamics, and all their weights are trained online. Based on the designed observer, the link position tracking controller using the estimated states is induced from the dynamic surface design procedure. Therefore, the proposed controller can be designed more simply than the observer backstepping controller. From the Lyapunov stability analysis, it is shown that all signals in a closed-loop adaptive system are uniformly ultimately bounded. Finally, the simulation results on a three-link FJED robot are presented to validate the good position tracking performance and robustness of the proposed control system against payload uncertainties and external disturbances.

The fidelity of Kepler eclipsing binary parameters inferred by the neural network

NASA Astrophysics Data System (ADS)

Holanda, N.; da Silva, J. R. P.

2018-04-01

This work aims to test the fidelity and efficiency of obtaining automatic orbital elements of eclipsing binary systems, from light curves using neural network models. We selected a random sample with 78 systems, from over 1400 eclipsing binary detached obtained from the Kepler Eclipsing Binaries Catalog, processed using the neural network approach. The orbital parameters of the sample systems were measured applying the traditional method of light curve adjustment with uncertainties calculated by the bootstrap method, employing the JKTEBOP code. These estimated parameters were compared with those obtained by the neural network approach for the same systems. The results reveal a good agreement between techniques for the sum of the fractional radii and moderate agreement for e cos ω and e sin ω, but orbital inclination is clearly underestimated in neural network tests.

The fidelity of Kepler eclipsing binary parameters inferred by the neural network

NASA Astrophysics Data System (ADS)

Holanda, N.; da Silva, J. R. P.

2018-07-01

This work aims to test the fidelity and efficiency of obtaining automatic orbital elements of eclipsing binary systems, from light curves using neural network models. We selected a random sample with 78 systems, from over 1400 detached eclipsing binaries obtained from the Kepler Eclipsing Binaries Catalog, processed using the neural network approach. The orbital parameters of the sample systems were measured applying the traditional method of light-curve adjustment with uncertainties calculated by the bootstrap method, employing the JKTEBOP code. These estimated parameters were compared with those obtained by the neural network approach for the same systems. The results reveal a good agreement between techniques for the sum of the fractional radii and moderate agreement for e cosω and e sinω, but orbital inclination is clearly underestimated in neural network tests.

Neural network-based adaptive dynamic surface control for permanent magnet synchronous motors.

PubMed

Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Chen, Bing; Lin, Chong

2015-03-01

This brief considers the problem of neural networks (NNs)-based adaptive dynamic surface control (DSC) for permanent magnet synchronous motors (PMSMs) with parameter uncertainties and load torque disturbance. First, NNs are used to approximate the unknown and nonlinear functions of PMSM drive system and a novel adaptive DSC is constructed to avoid the explosion of complexity in the backstepping design. Next, under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced to only one, and the designed neural controllers structure is much simpler than some existing results in literature, which can guarantee that the tracking error converges to a small neighborhood of the origin. Then, simulations are given to illustrate the effectiveness and potential of the new design technique.

Neural Network Control of a Magnetically Suspended Rotor System

NASA Technical Reports Server (NTRS)

Choi, Benjamin; Brown, Gerald; Johnson, Dexter

1997-01-01

Abstract Magnetic bearings offer significant advantages because of their noncontact operation, which can reduce maintenance. Higher speeds, no friction, no lubrication, weight reduction, precise position control, and active damping make them far superior to conventional contact bearings. However, there are technical barriers that limit the application of this technology in industry. One of them is the need for a nonlinear controller that can overcome the system nonlinearity and uncertainty inherent in magnetic bearings. This paper discusses the use of a neural network as a nonlinear controller that circumvents system nonlinearity. A neural network controller was well trained and successfully demonstrated on a small magnetic bearing rig. This work demonstrated the feasibility of using a neural network to control nonlinear magnetic bearings and systems with unknown dynamics.

Encoding-related brain activity dissociates between the recollective processes underlying successful recall and recognition: a subsequent-memory study.

PubMed

Sadeh, Talya; Maril, Anat; Goshen-Gottstein, Yonatan

2012-07-01

The subsequent-memory (SM) paradigm uncovers brain mechanisms that are associated with mnemonic activity during encoding by measuring participants' neural activity during encoding and classifying the encoding trials according to performance in the subsequent retrieval phase. The majority of these studies have converged on the notion that the mechanism supporting recognition is mediated by familiarity and recollection. The process of recollection is often assumed to be a recall-like process, implying that the active search for the memory trace is similar, if not identical, for recall and recognition. Here we challenge this assumption and hypothesize - based on previous findings obtained in our lab - that the recollective processes underlying recall and recognition might show dissociative patterns of encoding-related brain activity. To this end, our design controlled for familiarity, thereby focusing on contextual, recollective processes. We found evidence for dissociative neurocognitive encoding mechanisms supporting subsequent-recall and subsequent-recognition. Specifically, the contrast of subsequent-recognition versus subsequent-recall revealed activation in the Parahippocampal cortex (PHc) and the posterior hippocampus--regions associated with contextual processing. Implications of our findings and their relation to current cognitive models of recollection are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Dissociating motivation from reward in human striatal activity.

PubMed

Miller, Eric M; Shankar, Maya U; Knutson, Brian; McClure, Samuel M

2014-05-01

Neural activity in the striatum has consistently been shown to scale with the value of anticipated rewards. As a result, it is common across a number of neuroscientific subdiscliplines to associate activation in the striatum with anticipation of a rewarding outcome or a positive emotional state. However, most studies have failed to dissociate expected value from the motivation associated with seeking a reward. Although motivation generally scales positively with increases in potential reward, there are circumstances in which this linkage does not apply. The current study dissociates value-related activation from that induced by motivation alone by employing a task in which motivation increased as anticipated reward decreased. This design reverses the typical relationship between motivation and reward, allowing us to differentially investigate fMRI BOLD responses that scale with each. We report that activity scaled differently with value and motivation across the striatum. Specifically, responses in the caudate and putamen increased with motivation, whereas nucleus accumbens activity increased with expected reward. Consistent with this, self-report ratings indicated a positive association between caudate and putamen activity and arousal, whereas activity in the nucleus accumbens was more associated with liking. We conclude that there exist regional limits on inferring reward expectation from striatal activation.

Lesions of the fornix and anterior thalamic nuclei dissociate different aspects of hippocampal-dependent spatial learning: implications for the neural basis of scene learning.

PubMed

Aggleton, John P; Poirier, Guillaume L; Aggleton, Hugh S; Vann, Seralynne D; Pearce, John M

2009-06-01

The present study used 2 different discrimination tasks designed to isolate distinct components of visuospatial learning: structural learning and geometric learning. Structural learning refers to the ability to learn the precise combination of stimulus identity with stimulus location. Rats with anterior thalamic lesions and fornix lesions were unimpaired on a configural learning task in which the rats learned 3 concurrent mirror-image discriminations (structural learning). Indeed, both lesions led to facilitated learning. In contrast, anterior thalamic lesions impaired the geometric discrimination (e.g., swim to the corner with the short wall to the right of the long wall). Finally, both the fornix and anterior thalamic lesions severely impaired T-maze alternation, a task that taxes an array of spatial strategies including allocentric learning. This pattern of dissociations and double dissociations highlights how distinct classes of spatial learning rely on different systems, even though they may converge on the hippocampus. Consequently, the findings suggest that structural learning is heavily dependent on cortico-hippocampal interactions. In contrast, subcortical inputs (such as those from the anterior thalamus) contribute to geometric learning. Copyright (c) 2009 APA, all rights reserved.

Dissociating Motivation from Reward in Human Striatal Activity

PubMed Central

Miller, Eric M.; Shankar, Maya U.; Knutson, Brian; McClure, Samuel M.

2018-01-01

Neural activity in the striatum has consistently been shown to scale with the value of anticipated rewards. As a result, it is common across a number of neuroscientific subdiscliplines to associate activation in the striatum with anticipation of a rewarding outcome or a positive emotional state. However, most studies have failed to dissociate expected value from the motivation associated with seeking a reward. Although motivation generally scales positively with increases in potential reward, there are circumstances in which this linkage does not apply. The current study dissociates value-related activation from that induced by motivation alone by employing a task in which motivation increased as anticipated reward decreased. This design reverses the typical relationship between motivation and reward, allowing us to differentially investigate fMRI BOLD responses that scale with each. We report that activity scaled differently with value and motivation across the striatum. Specifically, responses in the caudate and putamen increased with motivation, whereas nucleus accumbens activity increased with expected reward. Consistent with this, self-report ratings indicated a positive association between caudate and putamen activity and arousal, whereas activity in the nucleus accumbens was more associated with liking. We conclude that there exist regional limits on inferring reward expectation from striatal activation. PMID:24345173

A computational framework for the study of confidence in humans and animals

PubMed Central

Kepecs, Adam; Mainen, Zachary F.

2012-01-01

Confidence judgements, self-assessments about the quality of a subject's knowledge, are considered a central example of metacognition. Prima facie, introspection and self-report appear the only way to access the subjective sense of confidence or uncertainty. Contrary to this notion, overt behavioural measures can be used to study confidence judgements by animals trained in decision-making tasks with perceptual or mnemonic uncertainty. Here, we suggest that a computational approach can clarify the issues involved in interpreting these tasks and provide a much needed springboard for advancing the scientific understanding of confidence. We first review relevant theories of probabilistic inference and decision-making. We then critically discuss behavioural tasks employed to measure confidence in animals and show how quantitative models can help to constrain the computational strategies underlying confidence-reporting behaviours. In our view, post-decision wagering tasks with continuous measures of confidence appear to offer the best available metrics of confidence. Since behavioural reports alone provide a limited window into mechanism, we argue that progress calls for measuring the neural representations and identifying the computations underlying confidence reports. We present a case study using such a computational approach to study the neural correlates of decision confidence in rats. This work shows that confidence assessments may be considered higher order, but can be generated using elementary neural computations that are available to a wide range of species. Finally, we discuss the relationship of confidence judgements to the wider behavioural uses of confidence and uncertainty. PMID:22492750

Dissociation of visual associative and motor learning in Drosophila at the flight simulator.

PubMed

Wang, Shunpeng; Li, Yan; Feng, Chunhua; Guo, Aike

2003-08-29

Ever since operant conditioning was studied experimentally, the relationship between associative learning and possible motor learning has become controversial. Although motor learning and its underlying neural substrates have been extensively studied in mammals, it is still poorly understood in invertebrates. The visual discriminative avoidance paradigm of Drosophila at the flight simulator has been widely used to study the flies' visual associative learning and related functions, but it has not been used to study the motor learning process. In this study, newly-designed data analysis was employed to examine the flies' solitary behavioural variable that was recorded at the flight simulator-yaw torque. Analysis was conducted to explore torque distributions of both wild-type and mutant flies in conditioning, with the following results: (1) Wild-type Canton-S flies had motor learning performance in conditioning, which was proved by modifications of the animal's behavioural mode in conditioning. (2) Repetition of training improved the motor learning performance of wild-type Canton-S flies. (3) Although mutant dunce(1) flies were defective in visual associative learning, they showed essentially normal motor learning performance in terms of yaw torque distribution in conditioning. Finally, we tentatively proposed that both visual associative learning and motor learning were involved in the visual operant conditioning of Drosophila at the flight simulator, that the two learning forms could be dissociated and they might have different neural bases.

How the brain predicts people's behavior in relation to rules and desires. Evidence of a medio-prefrontal dissociation.

PubMed

Corradi-Dell'Acqua, Corrado; Turri, Francesco; Kaufmann, Laurence; Clément, Fabrice; Schwartz, Sophie

2015-09-01

Forming and updating impressions about others is critical in everyday life and engages portions of the dorsomedial prefrontal cortex (dMPFC), the posterior cingulate cortex (PCC) and the amygdala. Some of these activations are attributed to "mentalizing" functions necessary to represent people's mental states, such as beliefs or desires. Evolutionary psychology and developmental studies, however, suggest that interpersonal inferences can also be obtained through the aid of deontic heuristics, which dictate what must (or must not) be done in given circumstances. We used fMRI and asked 18 participants to predict whether unknown characters would follow their desires or obey external rules. Participants had no means, at the beginning, to make accurate predictions, but slowly learned (throughout the experiment) each character's behavioral profile. We isolated brain regions whose activity changed during the experiment, as a neural signature of impression updating: whereas dMPFC was progressively more involved in predicting characters' behavior in relation to their desires, the medial orbitofrontal cortex and the amygdala were progressively more recruited in predicting rule-based behavior. Our data provide evidence of a neural dissociation between deontic inference and theory-of-mind (ToM), and support a differentiation of orbital and dorsal prefrontal cortex in terms of low- and high-level social cognition. Copyright © 2015 Elsevier Ltd. All rights reserved.

Visual extinction in relation to visuospatial neglect after right-hemispheric stroke: quantitative assessment and statistical lesion-symptom mapping.

PubMed

Vossel, S; Eschenbeck, P; Weiss, P H; Weidner, R; Saliger, J; Karbe, H; Fink, G R

2011-08-01

Visual neglect and extinction are two common neurological syndromes in patients with right-hemispheric brain damage. Whether and how these two syndromes are associated or share common neural substrates is still a matter of debate. To address these issues, the authors investigated 56 patients with right-hemispheric stroke with a novel diagnostic test to detect extinction and neglect. In this computerised task, subjects had to respond to target stimuli in uni- and bilateral stimulation conditions with detection probabilities being assessed. A cluster-analytical approach identified 18 patients with neglect and 13 patients with extinction. Statistical lesion-symptom mapping analyses with measures for extinction and neglect were performed. Extinction and neglect co-occurred in a subset of patients but were also observed independently from each other, thereby constituting a double dissociation. Lesions within the right inferior parietal cortex were significantly associated with the severity of visual extinction. Visuospatial neglect was related to damage of fronto-parietal brain regions, with parieto-occipital areas affecting line bisection and dorsal fronto-parietal areas affecting cancellation task performance, respectively. Quantifying lesion-induced symptoms with this novel paradigm shows that extinction and neglect are dissociable syndromes in patients with right-hemispheric stroke. Furthermore, extinction and neglect can be related to differential neural substrates, with extinction being related to focal brain damage within the right inferior parietal cortex.

Dissociable Brain Signatures of Choice Conflict and Immediate Reward Preferences in Alcohol Use Disorders

PubMed Central

Amlung, Michael; Sweet, Lawrence H.; Acker, John; Brown, Courtney L.; MacKillop, James

2013-01-01

Impulsive delayed reward discounting (DRD) is an important behavioral process in alcohol use disorders (AUDs), reflecting incapacity to delay gratification. Recent work in neuroeconomics has begun to unravel the neural mechanisms supporting DRD, but applications of neuroeconomics in relation to AUDs have been limited. This study examined the neural mechanisms of DRD preferences in AUDs, with emphasis on dissociating activation patterns based on DRD choice type and level of cognitive conflict. Heavy drinking adult males with (n = 13) and without (n = 12) a diagnosis of an AUD completed a monetary DRD task during a functional magnetic resonance imaging scan. Participant responses were coded based on choice type (impulsive vs. restrained) and level of cognitive conflict (easy vs. hard). AUD+ participants exhibited significantly more impulsive DRD decision-making. Significant activation during DRD was found in several decision-making regions, including dorsolateral prefrontal cortex (DLPFC), insula, posterior parietal cortex (PPC), and posterior cingulate. An axis of cognitive conflict was also observed, with hard choices associated with anterior cingulate cortex and easy choices associated with activation in supplementary motor area. AUD+ individuals exhibited significant hyperactivity in regions associated with cognitive control (DLPFC) and prospective thought (PPC) and exhibited less task-related deactivation of areas associated with the brain's default network during DRD decisions. This study provides further clarification of the brain systems supporting DRD in general and in relation to AUDs. PMID:23231650

Permutation invariant potential energy surfaces for polyatomic reactions using atomistic neural networks

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

Kolb, Brian; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139; Zhao, Bin

2016-06-14

The applicability and accuracy of the Behler-Parrinello atomistic neural network method for fitting reactive potential energy surfaces is critically examined in three systems, H + H{sub 2} → H{sub 2} + H, H + H{sub 2}O → H{sub 2} + OH, and H + CH{sub 4} → H{sub 2} + CH{sub 3}. A pragmatic Monte Carlo method is proposed to make efficient choice of the atom-centered mapping functions. The accuracy of the potential energy surfaces is not only tested by fitting errors but also validated by direct comparison in dynamically important regions and by quantum scattering calculations. Our results suggestmore » this method is both accurate and efficient in representing multidimensional potential energy surfaces even when dissociation continua are involved.« less

Distinct spatial frequency sensitivities for processing faces and emotional expressions.

PubMed

Vuilleumier, Patrik; Armony, Jorge L; Driver, Jon; Dolan, Raymond J

2003-06-01

High and low spatial frequency information in visual images is processed by distinct neural channels. Using event-related functional magnetic resonance imaging (fMRI) in humans, we show dissociable roles of such visual channels for processing faces and emotional fearful expressions. Neural responses in fusiform cortex, and effects of repeating the same face identity upon fusiform activity, were greater with intact or high-spatial-frequency face stimuli than with low-frequency faces, regardless of emotional expression. In contrast, amygdala responses to fearful expressions were greater for intact or low-frequency faces than for high-frequency faces. An activation of pulvinar and superior colliculus by fearful expressions occurred specifically with low-frequency faces, suggesting that these subcortical pathways may provide coarse fear-related inputs to the amygdala.

Differential involvement of left prefrontal cortex in inductive and deductive reasoning.

PubMed

Goel, Vinod; Dolan, Raymond J

2004-10-01

While inductive and deductive reasoning are considered distinct logical and psychological processes, little is known about their respective neural basis. To address this issue we scanned 16 subjects with fMRI, using an event-related design, while they engaged in inductive and deductive reasoning tasks. Both types of reasoning were characterized by activation of left lateral prefrontal and bilateral dorsal frontal, parietal, and occipital cortices. Neural responses unique to each type of reasoning determined from the Reasoning Type (deduction and induction) by Task (reasoning and baseline) interaction indicated greater involvement of left inferior frontal gyrus (BA 44) in deduction than induction, while left dorsolateral (BA 8/9) prefrontal gyrus showed greater activity during induction than deduction. This pattern suggests a dissociation within prefrontal cortex for deductive and inductive reasoning.

Aberrant occipital dynamics differentiate HIV-infected patients with and without cognitive impairment.

PubMed

Wiesman, Alex I; O'Neill, Jennifer; Mills, Mackenzie S; Robertson, Kevin R; Fox, Howard S; Swindells, Susan; Wilson, Tony W

2018-06-01

Combination antiretroviral therapies have revolutionized the treatment of HIV infection, and many patients now enjoy a lifespan equal to that of the general population. However, HIV-associated neurocognitive disorders (HAND) remain a major health concern, with between 30% and 70% of all HIV-infected patients developing cognitive impairments during their life time. One important feature of HAND is visuo-perceptual deficits, but the systems-level neural dynamics underlying these impairments are poorly understood. In the current study, we use magnetoencephalography and advanced time series analyses to examine these neural dynamics during a visuospatial processing task in a group of HIV-infected patients without HAND (n = 25), patients with HAND (n = 18), and a group of demographically-matched uninfected controls (n = 24). All participants completed a thorough neuropsychological assessment, and underwent magnetoencephalography and structural MRI protocols. In agreement with previous studies, patients with HAND performed significantly worse than HIV-infected patients without HAND and controls on the cognitive task, in terms of increased reaction time and decreased accuracy. Our magnetoencephalography results demonstrated that both spontaneous and neural oscillatory activity within the occipital cortices were affected by HIV infection, and that these patterns predicted behavioural performance (i.e. accuracy) on the task. Specifically, spontaneous neural activity in the alpha (8-16 Hz) and gamma (52-70 Hz) bands during the prestimulus baseline period, as well as oscillatory theta responses (4-8 Hz) during task performance were aberrant in HIV-infected patients, with both spontaneous alpha and oscillatory theta activity significantly predicting accuracy on the task and neuropsychological performance outside of the magnetoencephalography scanner. Importantly, these rhythmic patterns of population-level neural activity also distinguished patients by HAND status, such that spontaneous alpha activity in patients with HAND was elevated relative to HIV-infected patients without HAND and controls. In contrast, HIV-infected patients with and without HAND had increased spontaneous gamma compared to controls. Finally, there was a stepwise decrease in oscillatory theta activity as a function of disease severity, such that the response diminished from controls to patients without HAND to patients with HAND. Interestingly, the strength of the relationship between this theta response and accuracy also dissociated patient groups in a similar manner (controls > HIV with no HAND > HIV with HAND), indicating a reduced coupling between neurophysiology and behaviour in HIV-infected patients. This study provides the first neuroimaging evidence of a dissociation between HIV-infected patients with and without HAND, and these findings shed new light on the neural bases of cognitive impairment in HIV infection.

Decoding the Charitable Brain: Empathy, Perspective Taking, and Attention Shifts Differentially Predict Altruistic Giving.

PubMed

Tusche, Anita; Böckler, Anne; Kanske, Philipp; Trautwein, Fynn-Mathis; Singer, Tania

2016-04-27

Altruistic behavior varies considerably across people and decision contexts. The relevant computational and motivational mechanisms that underlie its heterogeneity, however, are poorly understood. Using a charitable giving task together with multivariate decoding techniques, we identified three distinct psychological mechanisms underlying altruistic decision-making (empathy, perspective taking, and attentional reorienting) and linked them to dissociable neural computations. Neural responses in the anterior insula (AI) (but not temporoparietal junction [TPJ]) encoded trial-wise empathy for beneficiaries, whereas the TPJ (but not AI) predicted the degree of perspective taking. Importantly, the relative influence of both socio-cognitive processes differed across individuals: participants whose donation behavior was heavily influenced by affective empathy exhibited higher predictive accuracies for generosity in AI, whereas those who strongly relied on cognitive perspective taking showed improved predictions of generous donations in TPJ. Furthermore, subject-specific contributions of both processes for donations were reflected in participants' empathy and perspective taking responses in a separate fMRI task (EmpaToM), suggesting that process-specific inputs into altruistic choices may reflect participants' general propensity to either empathize or mentalize. Finally, using independent attention task data, we identified shared neural codes for attentional reorienting and generous donations in the posterior superior temporal sulcus, suggesting that domain-general attention shifts also contribute to generous behavior (but not in TPJ or AI). Overall, our findings demonstrate highly specific roles of AI for affective empathy and TPJ for cognitive perspective taking as precursors of prosocial behavior and suggest that these discrete routes of social cognition differentially drive intraindividual and interindividual differences in altruistic behavior. Human societies depend on the altruistic behavior of their members, but teasing apart its underlying motivations and neural mechanisms poses a serious challenge. Using multivariate decoding techniques, we delineated three distinct processes for altruistic decision-making (affective empathy, cognitive perspective taking, and domain-general attention shifts), linked them to dissociable neural computations, and identified their relative influence across individuals. Distinguishing process-specific computations both behaviorally and neurally is crucial for developing complete theoretical and neuroscientific accounts of altruistic behavior and more effective means of increasing it. Moreover, information on the relative influence of subprocesses across individuals and its link to people's more general propensity to engage empathy or perspective taking can inform training programs to increase prosociality, considering their "fit" with different individuals. Copyright © 2016 the authors 0270-6474/16/364719-14$15.00/0.

Dynamic changes in neural circuit topology following mild mechanical injury in vitro.

PubMed

Patel, Tapan P; Ventre, Scott C; Meaney, David F

2012-01-01

Despite its enormous incidence, mild traumatic brain injury is not well understood. One aspect that needs more definition is how the mechanical energy during injury affects neural circuit function. Recent developments in cellular imaging probes provide an opportunity to assess the dynamic state of neural networks with single-cell resolution. In this article, we developed imaging methods to assess the state of dissociated cortical networks exposed to mild injury. We estimated the imaging conditions needed to achieve accurate measures of network properties, and applied these methodologies to evaluate if mild mechanical injury to cortical neurons produces graded changes to either spontaneous network activity or altered network topology. We found that modest injury produced a transient increase in calcium activity that dissipated within 1 h after injury. Alternatively, moderate mechanical injury produced immediate disruption in network synchrony, loss in excitatory tone, and increased modular topology. A calcium-activated neutral protease (calpain) was a key intermediary in these changes; blocking calpain activation restored the network nearly completely to its pre-injury state. Together, these findings show a more complex change in neural circuit behavior than previously reported for mild mechanical injury, and highlight at least one important early mechanism responsible for these changes.

Visuospatial Asymmetries Arise from Differences in the Onset Time of Perceptual Evidence Accumulation.

PubMed

Newman, Daniel P; Loughnane, Gerard M; Kelly, Simon P; O'Connell, Redmond G; Bellgrove, Mark A

2017-03-22

Healthy subjects tend to exhibit a bias of visual attention whereby left hemifield stimuli are processed more quickly and accurately than stimuli appearing in the right hemifield. It has long been held that this phenomenon arises from the dominant role of the right cerebral hemisphere in regulating attention. However, methods that would enable more precise understanding of the mechanisms underpinning visuospatial bias have remained elusive. We sought to finely trace the temporal evolution of spatial biases by leveraging a novel bilateral dot motion detection paradigm. In combination with electroencephalography, this paradigm enables researchers to isolate discrete neural signals reflecting the key neural processes needed for making these detection decisions. These include signals for spatial attention, early target selection, evidence accumulation, and motor preparation. Using this method, we established that three key neural markers accounted for unique between-subject variation in visuospatial bias: hemispheric asymmetry in posterior α power measured before target onset, which is related to the distribution of preparatory attention across the visual field; asymmetry in the peak latency of the early N2c target-selection signal; and, finally, asymmetry in the onset time of the subsequent neural evidence-accumulation process with earlier onsets for left hemifield targets. Our development of a single paradigm to dissociate distinct processing components that track the temporal evolution of spatial biases not only advances our understanding of the neural mechanisms underpinning normal visuospatial attention bias, but may also in the future aid differential diagnoses in disorders of spatial attention. SIGNIFICANCE STATEMENT The significance of this research is twofold. First, it shows that individual differences in how humans direct their attention between left and right space reflects physiological differences in how early the brain starts to accumulate evidence for the existence of a visual target. Second, the novel methods developed here may have particular relevance to disorders of attention, such as unilateral spatial neglect. In the case of spatial neglect, pathological inattention to left space could have multiple underlying causes, including biased attention, impaired decision formation, or a motor deficit related to one side of space. Our development of a single paradigm to dissociate each of these components may aid in supporting more precise differential diagnosis in such heterogeneous disorders. Copyright © 2017 the authors 0270-6474/17/373378-08$15.00/0.

Dissociating Normal Aging from Alzheimer’s Disease: A View from Cognitive Neuroscience

PubMed Central

Toepper, Max

2017-01-01

Both normal aging and Alzheimer’s disease (AD) are associated with changes in cognition, grey and white matter volume, white matter integrity, neural activation, functional connectivity, and neurotransmission. Obviously, all of these changes are more pronounced in AD and proceed faster providing the basis for an AD diagnosis. Since these differences are quantitative, however, it was hypothesized that AD might simply reflect an accelerated aging process. The present article highlights the different neurocognitive changes associated with normal aging and AD and shows that, next to quantitative differences, there are multiple qualitative differences as well. These differences comprise different neurocognitive dissociations as different cognitive deficit profiles, different weights of grey and white matter atrophy, and different gradients of structural decline. These qualitative differences clearly indicate that AD cannot be simply described as accelerated aging process but on the contrary represents a solid entity. PMID:28269778

Preserved processing of musical structure in a person with agrammatic aphasia.

PubMed

Slevc, L Robert; Faroqi-Shah, Yasmeen; Saxena, Sadhvi; Okada, Brooke M

2016-12-01

Evidence for shared processing of structure (or syntax) in language and in music conflicts with neuropsychological dissociations between the two. However, while harmonic structural processing can be impaired in patients with spared linguistic syntactic abilities (Peretz, I. (1993). Auditory atonalia for melodies. Cognitive Neuropsychology, 10, 21-56. doi:10.1080/02643299308253455), evidence for the opposite dissociation-preserved harmonic processing despite agrammatism-is largely lacking. Here, we report one such case: HV, a former musician with Broca's aphasia and agrammatic speech, was impaired in making linguistic, but not musical, acceptability judgments. Similarly, she showed no sensitivity to linguistic structure, but normal sensitivity to musical structure, in implicit priming tasks. To our knowledge, this is the first non-anecdotal report of a patient with agrammatic aphasia demonstrating preserved harmonic processing abilities, supporting claims that aspects of musical and linguistic structure rely on distinct neural mechanisms.

Dissociating Medial Temporal and Striatal Memory Systems With a Same/Different Matching Task: Evidence for Two Neural Systems in Human Recognition.

PubMed

Sinha, Neha; Glass, Arnold Lewis

2017-01-01

The medial temporal lobe and striatum have both been implicated as brain substrates of memory and learning. Here, we show dissociation between these two memory systems using a same/different matching task, in which subjects judged whether four-letter strings were the same or different. Different RT was determined by the left-to-right location of the first letter different between the study and test string, consistent with a left-to-right comparison of the study and test strings, terminating when a difference was found. This comparison process results in same responses being slower than different responses. Nevertheless, same responses were faster than different responses. Same responses were associated with hippocampus activation. Different responses were associated with both caudate and hippocampus activation. These findings are consistent with the dual-system hypothesis of mammalian memory and extend the model to human visual recognition.

Multivoxel neurofeedback selectively modulates confidence without changing perceptual performance

PubMed Central

Cortese, Aurelio; Amano, Kaoru; Koizumi, Ai; Kawato, Mitsuo; Lau, Hakwan

2016-01-01

A central controversy in metacognition studies concerns whether subjective confidence directly reflects the reliability of perceptual or cognitive processes, as suggested by normative models based on the assumption that neural computations are generally optimal. This view enjoys popularity in the computational and animal literatures, but it has also been suggested that confidence may depend on a late-stage estimation dissociable from perceptual processes. Yet, at least in humans, experimental tools have lacked the power to resolve these issues convincingly. Here, we overcome this difficulty by using the recently developed method of decoded neurofeedback (DecNef) to systematically manipulate multivoxel correlates of confidence in a frontoparietal network. Here we report that bi-directional changes in confidence do not affect perceptual accuracy. Further psychophysical analyses rule out accounts based on simple shifts in reporting strategy. Our results provide clear neuroscientific evidence for the systematic dissociation between confidence and perceptual performance, and thereby challenge current theoretical thinking. PMID:27976739

The basal ganglia is necessary for learning spectral, but not temporal features of birdsong

PubMed Central

Ali, Farhan; Fantana, Antoniu L.; Burak, Yoram; Ölveczky, Bence P.

2013-01-01

Executing a motor skill requires the brain to control which muscles to activate at what times. How these aspects of control - motor implementation and timing - are acquired, and whether the learning processes underlying them differ, is not well understood. To address this we used a reinforcement learning paradigm to independently manipulate both spectral and temporal features of birdsong, a complex learned motor sequence, while recording and perturbing activity in underlying circuits. Our results uncovered a striking dissociation in how neural circuits underlie learning in the two domains. The basal ganglia was required for modifying spectral, but not temporal structure. This functional dissociation extended to the descending motor pathway, where recordings from a premotor cortex analogue nucleus reflected changes to temporal, but not spectral structure. Our results reveal a strategy in which the nervous system employs different and largely independent circuits to learn distinct aspects of a motor skill. PMID:24075977

The dissociable effects of punishment and reward on motor learning.

PubMed

Galea, Joseph M; Mallia, Elizabeth; Rothwell, John; Diedrichsen, Jörn

2015-04-01

A common assumption regarding error-based motor learning (motor adaptation) in humans is that its underlying mechanism is automatic and insensitive to reward- or punishment-based feedback. Contrary to this hypothesis, we show in a double dissociation that the two have independent effects on the learning and retention components of motor adaptation. Negative feedback, whether graded or binary, accelerated learning. While it was not necessary for the negative feedback to be coupled to monetary loss, it had to be clearly related to the actual performance on the preceding movement. Positive feedback did not speed up learning, but it increased retention of the motor memory when performance feedback was withdrawn. These findings reinforce the view that independent mechanisms underpin learning and retention in motor adaptation, reject the assumption that motor adaptation is independent of motivational feedback, and raise new questions regarding the neural basis of negative and positive motivational feedback in motor learning.

Clinical characteristics and brain PET findings in 3 cases of dissociative amnesia: disproportionate retrograde deficit and posterior middle temporal gyrus hypometabolism.

PubMed

Thomas-Antérion, C; Dubas, F; Decousus, M; Jeanguillaume, C; Guedj, E

2014-10-01

Precipitated by psychological stress, dissociative amnesia occurs in the absence of identifiable brain damage. Its clinical characteristics and functional neural basis are still a matter of controversy. In the present paper, we report 3 cases of retrograde autobiographical amnesia, characterized by an acute onset concomitant with emotional/neurological precipitants. We present 2 cases of dissociative amnesia with fugue (cases 1 and 2), and one case of focal dissociative amnesia after a minor head trauma (case 3). The individual case histories and neuropsychological characteristics are reported, as well as the whole-brain voxel-based 18FDG-PET metabolic findings obtained at group-level in comparison to 15 healthy subjects. All patients suffered from autobiographical memory loss, in the absence of structural lesion. They had no significant impairment of anterograde memory or of executive function. Impairment of autobiographical memory was complete for two of the three patients, with loss of personal identity (cases 1 and 2). A clinical recovery was found for the two patients in whom follow-up was available (cases 2 and 3). Voxel-based group analysis highlighted a metabolic impairment of the right posterior middle temporal gyrus. 18FDG-PET was repeated in case 3, and showed a complete functional brain recovery. The situation of dissociative amnesia with disproportionate retrograde amnesia is clinically heterogeneous between individuals. Our findings may suggest that impairment of high-level integration of visual and/or emotional information processing involving dysfunction of the right posterior middle temporal gyrus could reduce triggering of multi-modal visual memory traces, thus impeding reactivation of aversive memories. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Imagining the future: The core episodic simulation network dissociates as a function of timecourse and the amount of simulated information

PubMed Central

Thakral, Preston P.; Benoit, Roland G.; Schacter, Daniel L.

2017-01-01

Neuroimaging data indicate that episodic memory (i.e., remembering specific past experiences) and episodic simulation (i.e., imagining specific future experiences) are associated with enhanced activity in a common set of neural regions, often referred to as the core network. This network comprises the hippocampus, parahippocampal cortex, lateral and medial parietal cortex, lateral temporal cortex, and medial prefrontal cortex. Evidence for a core network has been taken as support for the idea that episodic memory and episodic simulation are supported by common processes. Much remains to be learned about how specific core network regions contribute to specific aspects of episodic simulation. Prior neuroimaging studies of episodic memory indicate that certain regions within the core network are differentially sensitive to the amount of information recollected (e.g., the left lateral parietal cortex). In addition, certain core network regions dissociate as a function of their timecourse of engagement during episodic memory (e.g., transient activity in the posterior hippocampus and sustained activity in the left lateral parietal cortex). In the current study, we assessed whether similar dissociations could be observed during episodic simulation. We found that the left lateral parietal cortex modulates as a function of the amount of simulated details. Of particular interest, while the hippocampus was insensitive to the amount of simulated details, we observed a temporal dissociation within the hippocampus: transient activity occurred in relatively posterior portions of the hippocampus and sustained activity occurred in anterior portions. Because the posterior hippocampal and lateral parietal findings parallel those observed previously during episodic memory, the present results add to the evidence that episodic memory and episodic simulation are supported by common processes. Critically, the present study also provides evidence that regions within the core network support dissociable processes. PMID:28324695

Dissociative part-dependent resting-state activity in dissociative identity disorder: a controlled FMRI perfusion study.

PubMed

Schlumpf, Yolanda R; Reinders, Antje A T S; Nijenhuis, Ellert R S; Luechinger, Roger; van Osch, Matthias J P; Jäncke, Lutz

2014-01-01

In accordance with the Theory of Structural Dissociation of the Personality (TSDP), studies of dissociative identity disorder (DID) have documented that two prototypical dissociative subsystems of the personality, the "Emotional Part" (EP) and the "Apparently Normal Part" (ANP), have different biopsychosocial reactions to supraliminal and subliminal trauma-related cues and that these reactions cannot be mimicked by fantasy prone healthy controls nor by actors. Arterial spin labeling perfusion MRI was used to test the hypotheses that ANP and EP in DID have different perfusion patterns in response to rest instructions, and that perfusion is different in actors who were instructed to simulate ANP and EP. In a follow-up study, regional cerebral blood flow of DID patients was compared with the activation pattern of healthy non-simulating controls. Compared to EP, ANP showed elevated perfusion in bilateral thalamus. Compared to ANP, EP had increased perfusion in the dorsomedial prefrontal cortex, primary somatosensory cortex, and motor-related areas. Perfusion patterns for simulated ANP and EP were different. Fitting their reported role-play strategies, the actors activated brain structures involved in visual mental imagery and empathizing feelings. The follow-up study demonstrated elevated perfusion in the left temporal lobe in DID patients, whereas non-simulating healthy controls had increased activity in areas which mediate the mental construction of past and future episodic events. DID involves dissociative part-dependent resting-state differences. Compared to ANP, EP activated brain structures involved in self-referencing and sensorimotor actions more. Actors had different perfusion patterns compared to genuine ANP and EP. Comparisons of neural activity for individuals with DID and non-DID simulating controls suggest that the resting-state features of ANP and EP in DID are not due to imagination. The findings are consistent with TSDP and inconsistent with the idea that DID is caused by suggestion, fantasy proneness, and role-playing.

Dissociative Part-Dependent Resting-State Activity in Dissociative Identity Disorder: A Controlled fMRI Perfusion Study

PubMed Central

Schlumpf, Yolanda R.; Reinders, Antje A. T. S.; Nijenhuis, Ellert R. S.; Luechinger, Roger; van Osch, Matthias J. P.; Jäncke, Lutz

2014-01-01

Background In accordance with the Theory of Structural Dissociation of the Personality (TSDP), studies of dissociative identity disorder (DID) have documented that two prototypical dissociative subsystems of the personality, the “Emotional Part” (EP) and the “Apparently Normal Part” (ANP), have different biopsychosocial reactions to supraliminal and subliminal trauma-related cues and that these reactions cannot be mimicked by fantasy prone healthy controls nor by actors. Methods Arterial spin labeling perfusion MRI was used to test the hypotheses that ANP and EP in DID have different perfusion patterns in response to rest instructions, and that perfusion is different in actors who were instructed to simulate ANP and EP. In a follow-up study, regional cerebral blood flow of DID patients was compared with the activation pattern of healthy non-simulating controls. Results Compared to EP, ANP showed elevated perfusion in bilateral thalamus. Compared to ANP, EP had increased perfusion in the dorsomedial prefrontal cortex, primary somatosensory cortex, and motor-related areas. Perfusion patterns for simulated ANP and EP were different. Fitting their reported role-play strategies, the actors activated brain structures involved in visual mental imagery and empathizing feelings. The follow-up study demonstrated elevated perfusion in the left temporal lobe in DID patients, whereas non-simulating healthy controls had increased activity in areas which mediate the mental construction of past and future episodic events. Conclusion DID involves dissociative part-dependent resting-state differences. Compared to ANP, EP activated brain structures involved in self-referencing and sensorimotor actions more. Actors had different perfusion patterns compared to genuine ANP and EP. Comparisons of neural activity for individuals with DID and non-DID simulating controls suggest that the resting-state features of ANP and EP in DID are not due to imagination. The findings are consistent with TSDP and inconsistent with the idea that DID is caused by suggestion, fantasy proneness, and role-playing. PMID:24922512

Neural networks: A simulation technique under uncertainty conditions

NASA Technical Reports Server (NTRS)

Mcallister, M. Luisa Nicosia

1992-01-01

This paper proposes a new definition of fuzzy graphs and shows how transmission through a graph with linguistic expressions as labels provides an easy computational tool. These labels are represented by modified Kauffmann Fuzzy numbers.

Genetic reprogramming of human amniotic cells with episomal vectors: neural rosettes as sentinels in candidate selection for validation assays.

PubMed

Wilson, Patricia G; Payne, Tiffany

2014-01-01

The promise of genetic reprogramming has prompted initiatives to develop banks of induced pluripotent stem cells (iPSCs) from diverse sources. Sentinel assays for pluripotency could maximize available resources for generating iPSCs. Neural rosettes represent a primitive neural tissue that is unique to differentiating PSCs and commonly used to identify derivative neural/stem progenitors. Here, neural rosettes were used as a sentinel assay for pluripotency in selection of candidates to advance to validation assays. Candidate iPSCs were generated from independent populations of amniotic cells with episomal vectors. Phase imaging of living back up cultures showed neural rosettes in 2 of the 5 candidate populations. Rosettes were immunopositive for the Sox1, Sox2, Pax6 and Pax7 transcription factors that govern neural development in the earliest stage of development and for the Isl1/2 and Otx2 transcription factors that are expressed in the dorsal and ventral domains, respectively, of the neural tube in vivo. Dissociation of rosettes produced cultures of differentiation competent neural/stem progenitors that generated immature neurons that were immunopositive for βIII-tubulin and glia that were immunopositive for GFAP. Subsequent validation assays of selected candidates showed induced expression of endogenous pluripotency genes, epigenetic modification of chromatin and formation of teratomas in immunodeficient mice that contained derivatives of the 3 embryonic germ layers. Validated lines were vector-free and maintained a normal karyotype for more than 60 passages. The credibility of rosette assembly as a sentinel assay for PSCs is supported by coordinate loss of nuclear-localized pluripotency factors Oct4 and Nanog in neural rosettes that emerge spontaneously in cultures of self-renewing validated lines. Taken together, these findings demonstrate value in neural rosettes as sentinels for pluripotency and selection of promising candidates for advance to validation assays.

Genetic reprogramming of human amniotic cells with episomal vectors: neural rosettes as sentinels in candidate selection for validation assays

PubMed Central

Payne, Tiffany

2014-01-01

The promise of genetic reprogramming has prompted initiatives to develop banks of induced pluripotent stem cells (iPSCs) from diverse sources. Sentinel assays for pluripotency could maximize available resources for generating iPSCs. Neural rosettes represent a primitive neural tissue that is unique to differentiating PSCs and commonly used to identify derivative neural/stem progenitors. Here, neural rosettes were used as a sentinel assay for pluripotency in selection of candidates to advance to validation assays. Candidate iPSCs were generated from independent populations of amniotic cells with episomal vectors. Phase imaging of living back up cultures showed neural rosettes in 2 of the 5 candidate populations. Rosettes were immunopositive for the Sox1, Sox2, Pax6 and Pax7 transcription factors that govern neural development in the earliest stage of development and for the Isl1/2 and Otx2 transcription factors that are expressed in the dorsal and ventral domains, respectively, of the neural tube in vivo. Dissociation of rosettes produced cultures of differentiation competent neural/stem progenitors that generated immature neurons that were immunopositive for βIII-tubulin and glia that were immunopositive for GFAP. Subsequent validation assays of selected candidates showed induced expression of endogenous pluripotency genes, epigenetic modification of chromatin and formation of teratomas in immunodeficient mice that contained derivatives of the 3 embryonic germ layers. Validated lines were vector-free and maintained a normal karyotype for more than 60 passages. The credibility of rosette assembly as a sentinel assay for PSCs is supported by coordinate loss of nuclear-localized pluripotency factors Oct4 and Nanog in neural rosettes that emerge spontaneously in cultures of self-renewing validated lines. Taken together, these findings demonstrate value in neural rosettes as sentinels for pluripotency and selection of promising candidates for advance to validation assays. PMID:25426336

Rare Neural Correlations Implement Robotic Conditioning with Delayed Rewards and Disturbances

PubMed Central

Soltoggio, Andrea; Lemme, Andre; Reinhart, Felix; Steil, Jochen J.

2013-01-01

Neural conditioning associates cues and actions with following rewards. The environments in which robots operate, however, are pervaded by a variety of disturbing stimuli and uncertain timing. In particular, variable reward delays make it difficult to reconstruct which previous actions are responsible for following rewards. Such an uncertainty is handled by biological neural networks, but represents a challenge for computational models, suggesting the lack of a satisfactory theory for robotic neural conditioning. The present study demonstrates the use of rare neural correlations in making correct associations between rewards and previous cues or actions. Rare correlations are functional in selecting sparse synapses to be eligible for later weight updates if a reward occurs. The repetition of this process singles out the associating and reward-triggering pathways, and thereby copes with distal rewards. The neural network displays macro-level classical and operant conditioning, which is demonstrated in an interactive real-life human-robot interaction. The proposed mechanism models realistic conditioning in humans and animals and implements similar behaviors in neuro-robotic platforms. PMID:23565092

Dissociated roles of the parietal and frontal cortices in the scope and control of attention during visual working memory.

PubMed

Li, Siyao; Cai, Ying; Liu, Jing; Li, Dawei; Feng, Zifang; Chen, Chuansheng; Xue, Gui

2017-04-01

Mounting evidence suggests that multiple mechanisms underlie working memory capacity. Using transcranial direct current stimulation (tDCS), the current study aimed to provide causal evidence for the neural dissociation of two mechanisms underlying visual working memory (WM) capacity, namely, the scope and control of attention. A change detection task with distractors was used, where a number of colored bars (i.e., two red bars, four red bars, or two red plus two blue bars) were presented on both sides (Experiment 1) or the center (Experiment 2) of the screen for 100ms, and participants were instructed to remember the red bars and to ignore the blue bars (in both Experiments), as well as to ignore the stimuli on the un-cued side (Experiment 1 only). In both experiments, participants finished three sessions of the task after 15min of 1.5mA anodal tDCS administered on the right prefrontal cortex (PFC), the right posterior parietal cortex (PPC), and the primary visual cortex (VC), respectively. The VC stimulation served as an active control condition. We found that compared to stimulation on the VC, stimulation on the right PPC specifically increased the visual WM capacity under the no-distractor condition (i.e., 4 red bars), whereas stimulation on the right PFC specifically increased the visual WM capacity under the distractor condition (i.e., 2 red bars plus 2 blue bars). These results suggest that the PPC and PFC are involved in the scope and control of attention, respectively. We further showed that compared to central presentation of the stimuli (Experiment 2), bilateral presentation of the stimuli (on both sides of the fixation in Experiment 1) led to an additional demand for attention control. Our results emphasize the dissociated roles of the frontal and parietal lobes in visual WM capacity, and provide a deeper understanding of the neural mechanisms of WM. Copyright © 2017 Elsevier Inc. All rights reserved.

Getting a grip on reality: Grasping movements directed to real objects and images rely on dissociable neural representations.

PubMed

Freud, Erez; Macdonald, Scott N; Chen, Juan; Quinlan, Derek J; Goodale, Melvyn A; Culham, Jody C

2018-01-01

In the current era of touchscreen technology, humans commonly execute visually guided actions directed to two-dimensional (2D) images of objects. Although real, three-dimensional (3D), objects and images of the same objects share high degree of visual similarity, they differ fundamentally in the actions that can be performed on them. Indeed, previous behavioral studies have suggested that simulated grasping of images relies on different representations than actual grasping of real 3D objects. Yet the neural underpinnings of this phenomena have not been investigated. Here we used functional magnetic resonance imaging (fMRI) to investigate how brain activation patterns differed for grasping and reaching actions directed toward real 3D objects compared to images. Multivoxel Pattern Analysis (MVPA) revealed that the left anterior intraparietal sulcus (aIPS), a key region for visually guided grasping, discriminates between both the format in which objects were presented (real/image) and the motor task performed on them (grasping/reaching). Interestingly, during action planning, the representations of real 3D objects versus images differed more for grasping movements than reaching movements, likely because grasping real 3D objects involves fine-grained planning and anticipation of the consequences of a real interaction. Importantly, this dissociation was evident in the planning phase, before movement initiation, and was not found in any other regions, including motor and somatosensory cortices. This suggests that the dissociable representations in the left aIPS were not based on haptic, motor or proprioceptive feedback. Together, these findings provide novel evidence that actions, particularly grasping, are affected by the realness of the target objects during planning, perhaps because real targets require a more elaborate forward model based on visual cues to predict the consequences of real manipulation. Copyright © 2017 Elsevier Ltd. All rights reserved.

Mind the Gap: Two Dissociable Mechanisms of Temporal Processing in the Auditory System

PubMed Central

Anderson, Lucy A.

2016-01-01

High temporal acuity of auditory processing underlies perception of speech and other rapidly varying sounds. A common measure of auditory temporal acuity in humans is the threshold for detection of brief gaps in noise. Gap-detection deficits, observed in developmental disorders, are considered evidence for “sluggish” auditory processing. Here we show, in a mouse model of gap-detection deficits, that auditory brain sensitivity to brief gaps in noise can be impaired even without a general loss of central auditory temporal acuity. Extracellular recordings in three different subdivisions of the auditory thalamus in anesthetized mice revealed a stimulus-specific, subdivision-specific deficit in thalamic sensitivity to brief gaps in noise in experimental animals relative to controls. Neural responses to brief gaps in noise were reduced, but responses to other rapidly changing stimuli unaffected, in lemniscal and nonlemniscal (but not polysensory) subdivisions of the medial geniculate body. Through experiments and modeling, we demonstrate that the observed deficits in thalamic sensitivity to brief gaps in noise arise from reduced neural population activity following noise offsets, but not onsets. These results reveal dissociable sound-onset-sensitive and sound-offset-sensitive channels underlying auditory temporal processing, and suggest that gap-detection deficits can arise from specific impairment of the sound-offset-sensitive channel. SIGNIFICANCE STATEMENT The experimental and modeling results reported here suggest a new hypothesis regarding the mechanisms of temporal processing in the auditory system. Using a mouse model of auditory temporal processing deficits, we demonstrate the existence of specific abnormalities in auditory thalamic activity following sound offsets, but not sound onsets. These results reveal dissociable sound-onset-sensitive and sound-offset-sensitive mechanisms underlying auditory processing of temporally varying sounds. Furthermore, the findings suggest that auditory temporal processing deficits, such as impairments in gap-in-noise detection, could arise from reduced brain sensitivity to sound offsets alone. PMID:26865621

Food restriction dissociates sexual motivation, sexual performance, and the rewarding consequences of copulation in female Syrian hamsters

PubMed Central

Klingerman, Candice M.; Patel, Anand; Hedges, Valerie L.; Meisel, Robert L.; Schneider, Jill E.

2012-01-01

Animals can switch their behavioral priorities from ingestive to sex behaviors to optimize reproductive success in environments where energy fluctuates. We hypothesized that energy availability differentially affects the appetitive (motivation), consummatory (performance), and learned (rewarding) components of behavior. In Experiment 1, appetitive and consummatory aspects of sex behavior were dissociated in the majority of female Syrian hamsters restricted to 75% of their ad libitum food intake for 11 days. Food restriction significantly inhibited vaginal scent marking, decreased the preference for spending time with male hamsters vs. spending time with food, and increased food hoarding with no significant effect on consummatory behaviors such as the incidence of lordosis or food intake. In Experiments 2 and 3, we attempted to use a similar level of food restriction to dissociate sexual appetite from sexual reward. In hamsters, formation of a conditioned place preference (CPP) for copulatory reward is reflected in increased nucleus accumbens (NAc) neural activation, measured as immunocytochemical staining for c-Fos, the protein product of the immediate-early gene, c-fos. In Experiment 2, neural activation increased 1 h after copulation in the NAc core and shell, and did not differ significantly between 10-day food-restricted and ad libitum-fed females in any brain area examined. In Experiment 3, females were either food-restricted or fed ad libitum over 8-30 days of conditioning with copulatory stimuli. Food-restricted females showed significantly fewer appetitive behaviors, but no difference in formation of a CPP compared to females fed ad libitum. Together these data are consistent with the idea that mild levels of food restriction that inhibit appetitive behaviors fail to attenuate consummatory behaviors and the rewarding consequences of copulation. Thus, appetitive sex behaviors are, at least partially, neuroanatomically and behaviorally distinct from both consummatory behaviors and copulatory reward. PMID:21600244

A Hybrid Neural Network-Genetic Algorithm Technique for Aircraft Engine Performance Diagnostics

NASA Technical Reports Server (NTRS)

Kobayashi, Takahisa; Simon, Donald L.

2001-01-01

In this paper, a model-based diagnostic method, which utilizes Neural Networks and Genetic Algorithms, is investigated. Neural networks are applied to estimate the engine internal health, and Genetic Algorithms are applied for sensor bias detection and estimation. This hybrid approach takes advantage of the nonlinear estimation capability provided by neural networks while improving the robustness to measurement uncertainty through the application of Genetic Algorithms. The hybrid diagnostic technique also has the ability to rank multiple potential solutions for a given set of anomalous sensor measurements in order to reduce false alarms and missed detections. The performance of the hybrid diagnostic technique is evaluated through some case studies derived from a turbofan engine simulation. The results show this approach is promising for reliable diagnostics of aircraft engines.

Uncertainty analysis of neural network based flood forecasting models: An ensemble based approach for constructing prediction interval

NASA Astrophysics Data System (ADS)

Kasiviswanathan, K.; Sudheer, K.

2013-05-01

Artificial neural network (ANN) based hydrologic models have gained lot of attention among water resources engineers and scientists, owing to their potential for accurate prediction of flood flows as compared to conceptual or physics based hydrologic models. The ANN approximates the non-linear functional relationship between the complex hydrologic variables in arriving at the river flow forecast values. Despite a large number of applications, there is still some criticism that ANN's point prediction lacks in reliability since the uncertainty of predictions are not quantified, and it limits its use in practical applications. A major concern in application of traditional uncertainty analysis techniques on neural network framework is its parallel computing architecture with large degrees of freedom, which makes the uncertainty assessment a challenging task. Very limited studies have considered assessment of predictive uncertainty of ANN based hydrologic models. In this study, a novel method is proposed that help construct the prediction interval of ANN flood forecasting model during calibration itself. The method is designed to have two stages of optimization during calibration: at stage 1, the ANN model is trained with genetic algorithm (GA) to obtain optimal set of weights and biases vector, and during stage 2, the optimal variability of ANN parameters (obtained in stage 1) is identified so as to create an ensemble of predictions. During the 2nd stage, the optimization is performed with multiple objectives, (i) minimum residual variance for the ensemble mean, (ii) maximum measured data points to fall within the estimated prediction interval and (iii) minimum width of prediction interval. The method is illustrated using a real world case study of an Indian basin. The method was able to produce an ensemble that has an average prediction interval width of 23.03 m3/s, with 97.17% of the total validation data points (measured) lying within the interval. The derived prediction interval for a selected hydrograph in the validation data set is presented in Fig 1. It is noted that most of the observed flows lie within the constructed prediction interval, and therefore provides information about the uncertainty of the prediction. One specific advantage of the method is that when ensemble mean value is considered as a forecast, the peak flows are predicted with improved accuracy by this method compared to traditional single point forecasted ANNs. Fig. 1 Prediction Interval for selected hydrograph

Functional Roles of Neural Preparatory Processes in a Cued Stroop Task Revealed by Linking Electrophysiology with Behavioral Performance.

PubMed

Wang, Chao; Ding, Mingzhou; Kluger, Benzi M

2015-01-01

It is well established that cuing facilitates behavioral performance and that different aspects of instructional cues evoke specific neural preparatory processes in cued task-switching paradigms. To deduce the functional role of these neural preparatory processes the majority of studies vary aspects of the experimental paradigm and describe how these variations alter markers of neural preparatory processes. Although these studies provide important insights, they also have notable limitations, particularly in terms of understanding the causal or functional relationship of neural markers to cognitive and behavioral processes. In this study, we sought to address these limitations and uncover the functional roles of neural processes by examining how variability in the amplitude of neural preparatory processes predicts behavioral performance to subsequent stimuli. To achieve this objective 16 young adults were recruited to perform a cued Stroop task while their brain activity was measured using high-density electroencephalography. Four temporally overlapping but functionally and topographically distinct cue-triggered event related potentials (ERPs) were identified: 1) A left-frontotemporal negativity (250-700 ms) that was positively associated with word-reading performance; 2) a midline-frontal negativity (450-800 ms) that was positively associated with color-naming and incongruent performance; 3) a left-frontal negativity (450-800 ms) that was positively associated with switch trial performance; and 4) a centroparietal positivity (450-800 ms) that was positively associated with performance for almost all trial types. These results suggest that at least four dissociable cognitive processes are evoked by instructional cues in the present task, including: 1) domain-specific task facilitation; 2) switch-specific task-set reconfiguration; 3) preparation for response conflict; and 4) proactive attentional control. Examining the relationship between ERPs and behavioral performance provides a functional link between neural markers and the cognitive processes they index.

Modeling Uncertainties in EEG Microstates: Analysis of Real and Imagined Motor Movements Using Probabilistic Clustering-Driven Training of Probabilistic Neural Networks.

PubMed

Dinov, Martin; Leech, Robert

2017-01-01

Part of the process of EEG microstate estimation involves clustering EEG channel data at the global field power (GFP) maxima, very commonly using a modified K-means approach. Clustering has also been done deterministically, despite there being uncertainties in multiple stages of the microstate analysis, including the GFP peak definition, the clustering itself and in the post-clustering assignment of microstates back onto the EEG timecourse of interest. We perform a fully probabilistic microstate clustering and labeling, to account for these sources of uncertainty using the closest probabilistic analog to KM called Fuzzy C-means (FCM). We train softmax multi-layer perceptrons (MLPs) using the KM and FCM-inferred cluster assignments as target labels, to then allow for probabilistic labeling of the full EEG data instead of the usual correlation-based deterministic microstate label assignment typically used. We assess the merits of the probabilistic analysis vs. the deterministic approaches in EEG data recorded while participants perform real or imagined motor movements from a publicly available data set of 109 subjects. Though FCM group template maps that are almost topographically identical to KM were found, there is considerable uncertainty in the subsequent assignment of microstate labels. In general, imagined motor movements are less predictable on a time point-by-time point basis, possibly reflecting the more exploratory nature of the brain state during imagined, compared to during real motor movements. We find that some relationships may be more evident using FCM than using KM and propose that future microstate analysis should preferably be performed probabilistically rather than deterministically, especially in situations such as with brain computer interfaces, where both training and applying models of microstates need to account for uncertainty. Probabilistic neural network-driven microstate assignment has a number of advantages that we have discussed, which are likely to be further developed and exploited in future studies. In conclusion, probabilistic clustering and a probabilistic neural network-driven approach to microstate analysis is likely to better model and reveal details and the variability hidden in current deterministic and binarized microstate assignment and analyses.

Modeling Uncertainties in EEG Microstates: Analysis of Real and Imagined Motor Movements Using Probabilistic Clustering-Driven Training of Probabilistic Neural Networks

PubMed Central

Dinov, Martin; Leech, Robert

2017-01-01

Part of the process of EEG microstate estimation involves clustering EEG channel data at the global field power (GFP) maxima, very commonly using a modified K-means approach. Clustering has also been done deterministically, despite there being uncertainties in multiple stages of the microstate analysis, including the GFP peak definition, the clustering itself and in the post-clustering assignment of microstates back onto the EEG timecourse of interest. We perform a fully probabilistic microstate clustering and labeling, to account for these sources of uncertainty using the closest probabilistic analog to KM called Fuzzy C-means (FCM). We train softmax multi-layer perceptrons (MLPs) using the KM and FCM-inferred cluster assignments as target labels, to then allow for probabilistic labeling of the full EEG data instead of the usual correlation-based deterministic microstate label assignment typically used. We assess the merits of the probabilistic analysis vs. the deterministic approaches in EEG data recorded while participants perform real or imagined motor movements from a publicly available data set of 109 subjects. Though FCM group template maps that are almost topographically identical to KM were found, there is considerable uncertainty in the subsequent assignment of microstate labels. In general, imagined motor movements are less predictable on a time point-by-time point basis, possibly reflecting the more exploratory nature of the brain state during imagined, compared to during real motor movements. We find that some relationships may be more evident using FCM than using KM and propose that future microstate analysis should preferably be performed probabilistically rather than deterministically, especially in situations such as with brain computer interfaces, where both training and applying models of microstates need to account for uncertainty. Probabilistic neural network-driven microstate assignment has a number of advantages that we have discussed, which are likely to be further developed and exploited in future studies. In conclusion, probabilistic clustering and a probabilistic neural network-driven approach to microstate analysis is likely to better model and reveal details and the variability hidden in current deterministic and binarized microstate assignment and analyses. PMID:29163110

Neural network-based sliding mode control for atmospheric-actuated spacecraft formation using switching strategy

NASA Astrophysics Data System (ADS)

Sun, Ran; Wang, Jihe; Zhang, Dexin; Shao, Xiaowei

2018-02-01

This paper presents an adaptive neural networks-based control method for spacecraft formation with coupled translational and rotational dynamics using only aerodynamic forces. It is assumed that each spacecraft is equipped with several large flat plates. A coupled orbit-attitude dynamic model is considered based on the specific configuration of atmospheric-based actuators. For this model, a neural network-based adaptive sliding mode controller is implemented, accounting for system uncertainties and external perturbations. To avoid invalidation of the neural networks destroying stability of the system, a switching control strategy is proposed which combines an adaptive neural networks controller dominating in its active region and an adaptive sliding mode controller outside the neural active region. An optimal process is developed to determine the control commands for the plates system. The stability of the closed-loop system is proved by a Lyapunov-based method. Comparative results through numerical simulations illustrate the effectiveness of executing attitude control while maintaining the relative motion, and higher control accuracy can be achieved by using the proposed neural-based switching control scheme than using only adaptive sliding mode controller.

A novel method for improving the accuracy of coordinate transformation in multiple measurement systems

NASA Astrophysics Data System (ADS)

Liu, W. L.; Li, Y. W.

2017-09-01

Large-scale dimensional metrology usually requires a combination of multiple measurement systems, such as laser tracking, total station, laser scanning, coordinate measuring arm and video photogrammetry, etc. Often, the results from different measurement systems must be combined to provide useful results. The coordinate transformation is used to unify coordinate frames in combination; however, coordinate transformation uncertainties directly affect the accuracy of the final measurement results. In this paper, a novel method is proposed for improving the accuracy of coordinate transformation, combining the advantages of the best-fit least-square and radial basis function (RBF) neural networks. First of all, the configuration of coordinate transformation is introduced and a transformation matrix containing seven variables is obtained. Second, the 3D uncertainty of the transformation model and the residual error variable vector are established based on the best-fit least-square. Finally, in order to optimize the uncertainty of the developed seven-variable transformation model, we used the RBF neural network to identify the uncertainty of the dynamic, and unstructured, owing to its great ability to approximate any nonlinear function to the designed accuracy. Intensive experimental studies were conducted to check the validity of the theoretical results. The results show that the mean error of coordinate transformation decreased from 0.078 mm to 0.054 mm after using this method in contrast with the GUM method.

Proceedings of the NASA Conference on Space Telerobotics, volume 1

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo (Editor); Seraji, Homayoun (Editor)

1989-01-01

The theme of the Conference was man-machine collaboration in space. Topics addressed include: redundant manipulators; man-machine systems; telerobot architecture; remote sensing and planning; navigation; neural networks; fundamental AI research; and reasoning under uncertainty.

Impact of Noise on a Dynamical System: Prediction and Uncertainties from a Swarm-Optimized Neural Network

PubMed Central

López-Caraballo, C. H.; Lazzús, J. A.; Salfate, I.; Rojas, P.; Rivera, M.; Palma-Chilla, L.

2015-01-01

An artificial neural network (ANN) based on particle swarm optimization (PSO) was developed for the time series prediction. The hybrid ANN+PSO algorithm was applied on Mackey-Glass chaotic time series in the short-term x(t + 6). The performance prediction was evaluated and compared with other studies available in the literature. Also, we presented properties of the dynamical system via the study of chaotic behaviour obtained from the predicted time series. Next, the hybrid ANN+PSO algorithm was complemented with a Gaussian stochastic procedure (called stochastic hybrid ANN+PSO) in order to obtain a new estimator of the predictions, which also allowed us to compute the uncertainties of predictions for noisy Mackey-Glass chaotic time series. Thus, we studied the impact of noise for several cases with a white noise level (σ N) from 0.01 to 0.1. PMID:26351449

Impact of Noise on a Dynamical System: Prediction and Uncertainties from a Swarm-Optimized Neural Network.

PubMed

López-Caraballo, C H; Lazzús, J A; Salfate, I; Rojas, P; Rivera, M; Palma-Chilla, L

2015-01-01

An artificial neural network (ANN) based on particle swarm optimization (PSO) was developed for the time series prediction. The hybrid ANN+PSO algorithm was applied on Mackey-Glass chaotic time series in the short-term x(t + 6). The performance prediction was evaluated and compared with other studies available in the literature. Also, we presented properties of the dynamical system via the study of chaotic behaviour obtained from the predicted time series. Next, the hybrid ANN+PSO algorithm was complemented with a Gaussian stochastic procedure (called stochastic hybrid ANN+PSO) in order to obtain a new estimator of the predictions, which also allowed us to compute the uncertainties of predictions for noisy Mackey-Glass chaotic time series. Thus, we studied the impact of noise for several cases with a white noise level (σ(N)) from 0.01 to 0.1.

The Effect of Agmatine on Expression of IL-1β and TLX Which Promotes Neuronal Differentiation in Lipopolysaccharide-Treated Neural Progenitors.

PubMed

Song, Juhyun; Kumar, Bokara Kiran; Kang, Somang; Park, Kyung Ah; Lee, Won Taek; Lee, Jong Eun

2013-12-01

Differentiation of neural progenitor cells (NPCs) is important for protecting neural cells and brain tissue during inflammation. Interleukin-1 beta (IL-1β) is the most common pro- inflammatory cytokine in brain inflammation, and increased IL-1β levels can decrease the proliferation of NPCs. We aimed to investigate whether agmatine (Agm), a primary polyamine that protects neural cells, could trigger differentiation of NPCs by activating IL-1β in vitro. The cortex of ICR mouse embryos (E14) was dissociated to culture NPCs. NPCs were stimulated by lipopolysaccharide (LPS). After 6 days, protein expression of stem cell markers and differentiation signal factors was confirmed by using western blot analysis. Also, immunocytochemistry was used to confirm the cell fate. Agm treatment activated NPC differentiation significantly more than in the control group, which was evident by the increased expression of a neuronal marker, MAP2, in the LPS-induced, Agm-treated group. Differentiation of LPS-induced, Agm-treated NPCs was regulated by the MAPK pathway and is thought to be related to IL-1β activation and decreased expression of TLX, a transcription factor that regulates NPC differentiation. Our results reveal that Agm can promote NPC differentiation to neural stem cells by modulating IL-1β expression under inflammatory condition, and they suggest that Agm may be a novel therapeutic strategy for neuroinflammatory diseases.

The ugly truth: negative gossip about celebrities and positive gossip about self entertain people in different ways.

PubMed

Peng, Xiaozhe; Li, You; Wang, Pengfei; Mo, Lei; Chen, Qi

2015-01-01

In contrast to abstract trait words which describe people's general personality, gossip is about personal affairs of others. Although neural correlates underlying processing self-related trait words have been well documented, it remains poorly understood how the human brain processes gossip. In the present fMRI study, participants were instructed to rate their online emotional states upon hearing positive and negative gossip about celebrities, themselves, and their best friends. Explicit behavioral ratings suggested that participants were happier to hear positive gossip and more annoyed to hear negative gossip about themselves than about celebrities and best friends. At the neural level, dissociated neural networks were involved in processing the positive gossip about self and the negative gossip about celebrities. On the one hand, the superior medial prefrontal cortex responded not only to self-related gossip but also to moral transgressions, and neural activity in the orbital prefrontal cortex increased linearly with pleasure ratings on positive gossip about self. On the other hand, although participants' ratings did not show they were particularly happy on hearing negative gossip about celebrities, the significantly enhanced neural activity in the reward system suggested that they were indeed amused. Moreover, via enhanced functional connectivity, the prefrontal executive control network was involved in regulating the reward system by giving explicit pleasure ratings according to social norm compliance, rather than natural true feelings.

Neural network uncertainty assessment using Bayesian statistics: a remote sensing application

NASA Technical Reports Server (NTRS)

Aires, F.; Prigent, C.; Rossow, W. B.

2004-01-01

Neural network (NN) techniques have proved successful for many regression problems, in particular for remote sensing; however, uncertainty estimates are rarely provided. In this article, a Bayesian technique to evaluate uncertainties of the NN parameters (i.e., synaptic weights) is first presented. In contrast to more traditional approaches based on point estimation of the NN weights, we assess uncertainties on such estimates to monitor the robustness of the NN model. These theoretical developments are illustrated by applying them to the problem of retrieving surface skin temperature, microwave surface emissivities, and integrated water vapor content from a combined analysis of satellite microwave and infrared observations over land. The weight uncertainty estimates are then used to compute analytically the uncertainties in the network outputs (i.e., error bars and correlation structure of these errors). Such quantities are very important for evaluating any application of an NN model. The uncertainties on the NN Jacobians are then considered in the third part of this article. Used for regression fitting, NN models can be used effectively to represent highly nonlinear, multivariate functions. In this situation, most emphasis is put on estimating the output errors, but almost no attention has been given to errors associated with the internal structure of the regression model. The complex structure of dependency inside the NN is the essence of the model, and assessing its quality, coherency, and physical character makes all the difference between a blackbox model with small output errors and a reliable, robust, and physically coherent model. Such dependency structures are described to the first order by the NN Jacobians: they indicate the sensitivity of one output with respect to the inputs of the model for given input data. We use a Monte Carlo integration procedure to estimate the robustness of the NN Jacobians. A regularization strategy based on principal component analysis is proposed to suppress the multicollinearities in order to make these Jacobians robust and physically meaningful.

Neural correlates of risk taking in violent criminal offenders characterized by emotional hypo- and hyper-reactivity.

PubMed

Prehn, Kristin; Schlagenhauf, Florian; Schulze, Lars; Berger, Christoph; Vohs, Knut; Fleischer, Monika; Hauenstein, Karlheinz; Keiper, Peter; Domes, Gregor; Herpertz, Sabine C

2013-01-01

Recent approaches suggest that emotional reactivity can be used to differentiate between subgroups of individuals who are at risk for showing elevated levels of aggression and violence. In this study, we examined how emotion governs decision making within two subgroups of antisocial criminal offenders with either emotional hypo- or hyper-reactivity compared with healthy, noncriminal controls. Offenders were recruited from high-security forensic treatment facilities and penal institutions and underwent functional magnetic resonance imaging during a financial decision-making task. In this task, participants were required to choose between low-risk (bonds) and high-risk alternatives (stocks). Bonds were always the safe choice; stocks could win or lose, with a varying degree of uncertainty. We found that emotionally hypo-reactive offenders differed most from healthy controls by showing diminished neural activation in the rostral anterior cingulate cortex in response to uncertainty as well as decreased activity in the prefrontal cortex when trying to regulate their behavior accordingly (i.e., when consistently choosing "safe alternatives"). Hence, the data indicate that emotionally hypo-reactive offenders (with psychopathic traits) constitute a special subgroup within antisocial offenders characterized in particular by a limited capacity to emotionally represent uncertainty and to anticipate punishment.

Structural reliability calculation method based on the dual neural network and direct integration method.

PubMed

Li, Haibin; He, Yun; Nie, Xiaobo

2018-01-01

Structural reliability analysis under uncertainty is paid wide attention by engineers and scholars due to reflecting the structural characteristics and the bearing actual situation. The direct integration method, started from the definition of reliability theory, is easy to be understood, but there are still mathematics difficulties in the calculation of multiple integrals. Therefore, a dual neural network method is proposed for calculating multiple integrals in this paper. Dual neural network consists of two neural networks. The neural network A is used to learn the integrand function, and the neural network B is used to simulate the original function. According to the derivative relationships between the network output and the network input, the neural network B is derived from the neural network A. On this basis, the performance function of normalization is employed in the proposed method to overcome the difficulty of multiple integrations and to improve the accuracy for reliability calculations. The comparisons between the proposed method and Monte Carlo simulation method, Hasofer-Lind method, the mean value first-order second moment method have demonstrated that the proposed method is an efficient and accurate reliability method for structural reliability problems.

Optogenetic Control of Cells and Circuits

PubMed Central

Miesenböck, Gero

2013-01-01

The absorption of light by bound or diffusible chromophores causes conformational rearrangements in natural and artificial photoreceptor proteins. These rearrangements are coupled to the opening or closing of ion transport pathways, the association or dissociation of binding partners, the enhancement or suppression of catalytic activity, or the transcription or repression of genetic information. Illumination of cells, tissues, or organisms engineered genetically to express photoreceptor proteins can thus be used to perturb biochemical and electrical signaling with exquisite cellular and molecular specificity. First demonstrated in 2002, this principle of optogenetic control has had a profound impact on neuroscience, where it provides a direct and stringent means of probing the organization of neural circuits and of identifying the neural substrates of behavior. The impact of optogenetic control is also beginning to be felt in other areas of cell and organismal biology. PMID:21819234

Adaptive Neural Networks Decentralized FTC Design for Nonstrict-Feedback Nonlinear Interconnected Large-Scale Systems Against Actuator Faults.

PubMed

Li, Yongming; Tong, Shaocheng

The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.

Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model

PubMed Central

Li, Yuzhe; Nakae, Ken; Ishii, Shin; Naoki, Honda

2016-01-01

Uncertainty of fear conditioning is crucial for the acquisition and extinction of fear memory. Fear memory acquired through partial pairings of a conditioned stimulus (CS) and an unconditioned stimulus (US) is more resistant to extinction than that acquired through full pairings; this effect is known as the partial reinforcement extinction effect (PREE). Although the PREE has been explained by psychological theories, the neural mechanisms underlying the PREE remain largely unclear. Here, we developed a neural circuit model based on three distinct types of neurons (fear, persistent and extinction neurons) in the amygdala and medial prefrontal cortex (mPFC). In the model, the fear, persistent and extinction neurons encode predictions of net severity, of unconditioned stimulus (US) intensity, and of net safety, respectively. Our simulation successfully reproduces the PREE. We revealed that unpredictability of the US during extinction was represented by the combined responses of the three types of neurons, which are critical for the PREE. In addition, we extended the model to include amygdala subregions and the mPFC to address a recent finding that the ventral mPFC (vmPFC) is required for consolidating extinction memory but not for memory retrieval. Furthermore, model simulations led us to propose a novel procedure to enhance extinction learning through re-conditioning with a stronger US; strengthened fear memory up-regulates the extinction neuron, which, in turn, further inhibits the fear neuron during re-extinction. Thus, our models increased the understanding of the functional roles of the amygdala and vmPFC in the processing of uncertainty in fear conditioning and extinction. PMID:27617747

Uncertainty-Dependent Extinction of Fear Memory in an Amygdala-mPFC Neural Circuit Model.

PubMed

Li, Yuzhe; Nakae, Ken; Ishii, Shin; Naoki, Honda

2016-09-01

Uncertainty of fear conditioning is crucial for the acquisition and extinction of fear memory. Fear memory acquired through partial pairings of a conditioned stimulus (CS) and an unconditioned stimulus (US) is more resistant to extinction than that acquired through full pairings; this effect is known as the partial reinforcement extinction effect (PREE). Although the PREE has been explained by psychological theories, the neural mechanisms underlying the PREE remain largely unclear. Here, we developed a neural circuit model based on three distinct types of neurons (fear, persistent and extinction neurons) in the amygdala and medial prefrontal cortex (mPFC). In the model, the fear, persistent and extinction neurons encode predictions of net severity, of unconditioned stimulus (US) intensity, and of net safety, respectively. Our simulation successfully reproduces the PREE. We revealed that unpredictability of the US during extinction was represented by the combined responses of the three types of neurons, which are critical for the PREE. In addition, we extended the model to include amygdala subregions and the mPFC to address a recent finding that the ventral mPFC (vmPFC) is required for consolidating extinction memory but not for memory retrieval. Furthermore, model simulations led us to propose a novel procedure to enhance extinction learning through re-conditioning with a stronger US; strengthened fear memory up-regulates the extinction neuron, which, in turn, further inhibits the fear neuron during re-extinction. Thus, our models increased the understanding of the functional roles of the amygdala and vmPFC in the processing of uncertainty in fear conditioning and extinction.

I think therefore I am: Rest-related prefrontal cortex neural activity is involved in generating the sense of self.

PubMed

Gruberger, M; Levkovitz, Y; Hendler, T; Harel, E V; Harari, H; Ben Simon, E; Sharon, H; Zangen, A

2015-05-01

The sense of self has always been a major focus in the psychophysical debate. It has been argued that this complex ongoing internal sense cannot be explained by any physical measure and therefore substantiates a mind-body differentiation. Recently, however, neuro-imaging studies have associated self-referential spontaneous thought, a core-element of the ongoing sense of self, with synchronous neural activations during rest in the medial prefrontal cortex (PFC), as well as the medial and lateral parietal cortices. By applying deep transcranial magnetic stimulation (TMS) over human PFC before rest, we disrupted activity in this neural circuitry thereby inducing reports of lowered self-awareness and strong feelings of dissociation. This effect was not found with standard or sham TMS, or when stimulation was followed by a task instead of rest. These findings demonstrate for the first time a critical, causal role of intact rest-related PFC activity patterns in enabling integrated, enduring, self-referential mental processing. Copyright © 2015 Elsevier Inc. All rights reserved.

Neural evidence of motivational conflict between social values.

PubMed

Leszkowicz, Emilia; Linden, David E J; Maio, Gregory R; Ihssen, Niklas

2017-10-01

Motivational interdependence is an organizing principle in Schwartz's circumplex model of social values, which has received abundant cross-cultural support. We used fMRI to test whether motivational relations between social values predict different brain responses in a situation of choice between values. We hypothesized that differences in brain responses would become evident when the more important value had to be selected in pairs of congruent (e.g., wealth and success) as opposed to incongruent (e.g., curiosity and stability) values as they are described in Schwartz's model, because the former serve mutually facilitating motives, whereas the latter serve mutually inhibiting motives. Consistent with the model, choosing between congruent values led to longer response times and more activation in conflict-related brain regions (e.g., the supplementary motor area, dorsolateral prefrontal cortex) than selecting between incongruent values. These results provide novel neural evidence supporting the circumplex model's predictions about motivational interdependence between social values. In particular, our results show that the neural networks underlying social values are organized in a way that allows activation patterns related to motivational similarity between congruent values to be dissociated from those related to incongruent values.

The Language–Number Interface in the Brain: A Complex Parametric Study of Quantifiers and Quantities

PubMed Central

Heim, Stefan; Amunts, Katrin; Drai, Dan; Eickhoff, Simon B.; Hautvast, Sarah; Grodzinsky, Yosef

2011-01-01

The neural bases for numerosity and language are of perennial interest. In monkeys, neural separation of numerical Estimation and numerical Comparison has been demonstrated. As linguistic and numerical knowledge can only be compared in humans, we used a new fMRI paradigm in an attempt to dissociate Estimation from Comparison, and at the same time uncover the neural relation between numerosity and language. We used complex stimuli: images depicting a proportion between quantities of blue and yellow circles were coupled with sentences containing quantifiers that described them (e.g., “most/few of the circles are yellow”). Participants verified sentences against images. Both Estimation and Comparison recruited adjacent, partially overlapping bi-hemispheric fronto-parietal regions. Additional semantic analysis of positive vs. negative quantifiers involving the interpretation of quantity and numerosity specifically recruited left area 45. The anatomical proximity between numerosity regions and those involved in semantic analysis points to subtle links between the number system and language. Results fortify the homology of Estimation and Comparison between humans and monkeys. PMID:22470338

A fast flexible ink-jet printing method for patterning dissociated neurons in culture.

PubMed

Sanjana, Neville E; Fuller, Sawyer B

2004-07-30

We present a new technique that uses a custom-built ink-jet printer to fabricate precise micropatterns of cell adhesion materials for neural cell culture. Other work in neural cell patterning has employed photolithography or "soft lithographic" techniques such as micro-stamping, but such approaches are limited by their use of an un-alterable master pattern such as a mask or stamp master and can be resource-intensive. In contrast, ink-jet printing, used in low-cost desktop printers, patterns material by depositing microscopic droplets under robotic control in a programmable and inexpensive manner. We report the use of ink-jet printing to fabricate neuron-adhesive patterns such as islands and other shapes using poly(ethylene) glycol as the cell-repulsive material and a collagen/poly-D-lysine (PDL) mixture as the cell-adhesive material. We show that dissociated rat hippocampal neurons and glia grown at low densities on such patterns retain strong pattern adherence for over 25 days. The patterned neurons are comparable to control, un-patterned cells in electrophysiological properties and in immunocytochemical measurements of synaptic density and inhibitory cell distributions. We suggest that an inexpensive desktop printer may be an accessible tool for making micro-island cultures and other basic patterns. We also suggest that ink-jet printing may be extended to a range of developmental neuroscience studies, given its ability to more easily layer materials, build substrate-bound gradients, construct out-of-plane structure, and deposit sources of diffusible factors. Copyright 2004 Elsevier B.V.

Dissociating maternal responses to sad and happy facial expressions of their own child: An fMRI study.

PubMed

Kluczniok, Dorothea; Hindi Attar, Catherine; Stein, Jenny; Poppinga, Sina; Fydrich, Thomas; Jaite, Charlotte; Kappel, Viola; Brunner, Romuald; Herpertz, Sabine C; Boedeker, Katja; Bermpohl, Felix

2017-01-01

Maternal sensitive behavior depends on recognizing one's own child's affective states. The present study investigated distinct and overlapping neural responses of mothers to sad and happy facial expressions of their own child (in comparison to facial expressions of an unfamiliar child). We used functional MRI to measure dissociable and overlapping activation patterns in 27 healthy mothers in response to happy, neutral and sad facial expressions of their own school-aged child and a gender- and age-matched unfamiliar child. To investigate differential activation to sad compared to happy faces of one's own child, we used interaction contrasts. During the scan, mothers had to indicate the affect of the presented face. After scanning, they were asked to rate the perceived emotional arousal and valence levels for each face using a 7-point Likert-scale (adapted SAM version). While viewing their own child's sad faces, mothers showed activation in the amygdala and anterior cingulate cortex whereas happy facial expressions of the own child elicited activation in the hippocampus. Conjoint activation in response to one's own child happy and sad expressions was found in the insula and the superior temporal gyrus. Maternal brain activations differed depending on the child's affective state. Sad faces of the own child activated areas commonly associated with a threat detection network, whereas happy faces activated reward related brain areas. Overlapping activation was found in empathy related networks. These distinct neural activation patterns might facilitate sensitive maternal behavior.

Dissociable brain signatures of choice conflict and immediate reward preferences in alcohol use disorders.

PubMed

Amlung, Michael; Sweet, Lawrence H; Acker, John; Brown, Courtney L; MacKillop, James

2014-07-01

Impulsive delayed reward discounting (DRD) is an important behavioral process in alcohol use disorders (AUDs), reflecting incapacity to delay gratification. Recent work in neuroeconomics has begun to unravel the neural mechanisms supporting DRD, but applications of neuroeconomics in relation to AUDs have been limited. This study examined the neural mechanisms of DRD preferences in AUDs, with emphasis on dissociating activation patterns based on DRD choice type and level of cognitive conflict. Heavy drinking adult men with (n = 13) and without (n = 12) a diagnosis of an AUD completed a monetary DRD task during a functional magnetic resonance imaging scan. Participant responses were coded based on choice type (impulsive versus restrained) and level of cognitive conflict (easy versus hard). AUD+ participants exhibited significantly more impulsive DRD decision-making. Significant activation during DRD was found in several decision-making regions, including dorsolateral prefrontal cortex (DLPFC), insula, posterior parietal cortex (PPC), and posterior cingulate. An axis of cognitive conflict was also observed, with hard choices associated with anterior cingulate cortex and easy choices associated with activation in supplementary motor area. AUD+ individuals exhibited significant hyperactivity in regions associated with cognitive control (DLPFC) and prospective thought (PPC) and exhibited less task-related deactivation of areas associated with the brain's default network during DRD decisions. This study provides further clarification of the brain systems supporting DRD in general and in relation to AUDs. © 2012 The Authors, Addiction Biology © 2012 Society for the Study of Addiction.

Possible origin of the discrepancy in Peierls stresses of fcc metals: First-principles simulations of dislocation mobility in aluminum

NASA Astrophysics Data System (ADS)

Shin, Ilgyou; Carter, Emily A.

2013-08-01

Dislocation motion governs the strength and ductility of metals, and the Peierls stress (σp) quantifies dislocation mobility. σp measurements carry substantial uncertainty in face-centered cubic (fcc) metals, and σp values can differ by up to two orders of magnitude. We perform first-principles simulations based on orbital-free density functional theory (OFDFT) to calculate the most accurate currently possible σp for the motion of (1)/(2)<110>111 dislocations in fcc Al. We predict the σps of screw and edge dislocations (dissociated in their equilibrium state) to be 1.9×10-4G and 4.9×10-5G, respectively (G is the shear modulus). These values fall within the range of measurements from mechanical deformation tests (10-4-10-5G). OFDFT also finds a new metastable structure for a screw dislocation not seen in earlier simulations, in which a dislocation core on the glide plane does not dissociate into partials. The corresponding σp for this undissociated dislocation is predicted to be 1.1×10-2G, which agrees with typical Bordoni peak measurements (10-2-10-3G). The calculated σps for dissociated and undissociated screw dislocations differ by two orders of magnitude. The presence of undissociated, as well as dissociated, screw dislocations may resolve the decades-long mystery in fcc metals regarding the two orders of magnitude discrepancy in σp measurements.

Modulation of task demands suggests that semantic processing interferes with the formation of episodic associations

PubMed Central

Long, Nicole M.; Kahana, Michael J.

2016-01-01

Although episodic and semantic memory share overlapping neural mechanisms, it remains unclear how our pre-existing semantic associations modulate the formation of new, episodic associations. When freely recalling recently studied words, people rely on both episodic and semantic associations, shown through temporal and semantic clustering of responses. We asked whether orienting participants toward semantic associations interferes with or facilitates the formation of episodic associations. We compared electroencephalographic (EEG) activity recorded during the encoding of subsequently recalled words that were either temporally or semantically clustered. Participants studied words with or without a concurrent semantic orienting task. We identified a neural signature of successful episodic association formation whereby high frequency EEG activity (HFA, 44 – 100 Hz) overlying left prefrontal regions increased for subsequently temporally clustered words, but only for those words studied without a concurrent semantic orienting task. To confirm that this disruption in the formation of episodic associations was driven by increased semantic processing, we measured the neural correlates of subsequent semantic clustering. We found that HFA increased for subsequently semantically clustered words only for lists with a concurrent semantic orienting task. This dissociation suggests that increased semantic processing of studied items interferes with the neural processes that support the formation of novel episodic associations. PMID:27617775

Modulation of task demands suggests that semantic processing interferes with the formation of episodic associations.

PubMed

Long, Nicole M; Kahana, Michael J

2017-02-01

Although episodic and semantic memory share overlapping neural mechanisms, it remains unclear how our pre-existing semantic associations modulate the formation of new, episodic associations. When freely recalling recently studied words, people rely on both episodic and semantic associations, shown through temporal and semantic clustering of responses. We asked whether orienting participants toward semantic associations interferes with or facilitates the formation of episodic associations. We compared electroencephalographic (EEG) activity recorded during the encoding of subsequently recalled words that were either temporally or semantically clustered. Participants studied words with or without a concurrent semantic orienting task. We identified a neural signature of successful episodic association formation whereby high-frequency EEG activity (HFA, 44-100 Hz) overlying left prefrontal regions increased for subsequently temporally clustered words, but only for those words studied without a concurrent semantic orienting task. To confirm that this disruption in the formation of episodic associations was driven by increased semantic processing, we measured the neural correlates of subsequent semantic clustering. We found that HFA increased for subsequently semantically clustered words only for lists with a concurrent semantic orienting task. This dissociation suggests that increased semantic processing of studied items interferes with the neural processes that support the formation of novel episodic associations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A Goal Direction Signal in the Human Entorhinal/Subicular Region

PubMed Central

Chadwick, Martin J.; Jolly, Amy E.J.; Amos, Doran P.; Hassabis, Demis; Spiers, Hugo J.

2015-01-01

Summary Navigating to a safe place, such as a home or nest, is a fundamental behavior for all complex animals. Determining the direction to such goals is a crucial first step in navigation. Surprisingly, little is known about how or where in the brain this “goal direction signal” is represented. In mammals, “head-direction cells” are thought to support this process, but despite 30 years of research, no evidence for a goal direction representation has been reported [1, 2]. Here, we used fMRI to record neural activity while participants made goal direction judgments based on a previously learned virtual environment. We applied multivoxel pattern analysis [3–5] to these data and found that the human entorhinal/subicular region contains a neural representation of intended goal direction. Furthermore, the neural pattern expressed for a given goal direction matched the pattern expressed when simply facing that same direction. This suggests the existence of a shared neural representation of both goal and facing direction. We argue that this reflects a mechanism based on head-direction populations that simulate future goal directions during route planning [6]. Our data further revealed that the strength of direction information predicts performance. Finally, we found a dissociation between this geocentric information in the entorhinal/subicular region and egocentric direction information in the precuneus. PMID:25532898

Illuminating the conceptual structure of the space of moral violations with searchlight representational similarity analysis.

PubMed

Wasserman, E A; Chakroff, A; Saxe, R; Young, L

2017-10-01

Characterizing how representations of moral violations are organized, cognitively and neurally, is central to understanding how people conceive and judge them. Past work has identified brain regions that represent morally relevant features and distinguish moral domains, but has not yet advanced a broader account of where and on what basis neural representations of moral violations are organized. With searchlight representational similarity analysis, we investigate where category membership drives similarity in neural patterns during moral judgment of violations from two key moral domains: Harm and Purity. Representations converge across domains in a network of regions resembling the mentalizing network. However, Harm and Purity violation representations respectively converge in different regions: precuneus (PC) and left inferior frontal gyrus (LIFG). Examining substructure within moral domains, Harm violations converge in PC regardless of subdomain (physical harms, psychological harms), while Purity subdomains (pathogen-related violations, sex-related violations) converge in distinct sets of regions - mirroring a dissociation observed in principal-component analysis of behavioral data. Further, we find initial evidence for representation of morally relevant features within these two domain-encoding regions. The present analyses offer a case study for understanding how organization within the complex conceptual space of moral violations is reflected in the organization of neural patterns across the cortex. Copyright © 2017 Elsevier Inc. All rights reserved.

Memory modulation across neural systems: intra-amygdala glucose reverses deficits caused by intraseptal morphine on a spatial task but not on an aversive task.

PubMed

McNay, E C; Gold, P E

1998-05-15

Based largely on dissociations of the effects of different lesions on learning and memory, memories for different attributes appear to be organized in independent neural systems. Results obtained with direct injections of drugs into one brain region at a time support a similar conclusion. The present experiments investigated the effects of simultaneous pharmacological manipulation of two neural systems, the amygdala and the septohippocampal system, to examine possible interactions of memory modulation across systems. Morphine injected into the medial septum impaired memory both for avoidance training and during spontaneous alternation. When glucose was concomitantly administered to the amygdala, glucose reversed the morphine-induced deficits in memory during alternation but not for avoidance training. These results suggest that the amygdala is involved in modulation of spatial memory processes and that direct injections of memory-modulating drugs into the amygdala do not always modulate memory for aversive events. These findings are contrary to predictions from the findings of lesion studies and of studies using direct injections of drugs into single brain areas. Thus, the independence of neural systems responsible for processing different classes of memory is less clear than implied by studies using lesions or injections of drugs into single brain areas.

Hierarchical Bayesian Model Averaging for Non-Uniqueness and Uncertainty Analysis of Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Fijani, E.; Chitsazan, N.; Nadiri, A.; Tsai, F. T.; Asghari Moghaddam, A.

2012-12-01

Artificial Neural Networks (ANNs) have been widely used to estimate concentration of chemicals in groundwater systems. However, estimation uncertainty is rarely discussed in the literature. Uncertainty in ANN output stems from three sources: ANN inputs, ANN parameters (weights and biases), and ANN structures. Uncertainty in ANN inputs may come from input data selection and/or input data error. ANN parameters are naturally uncertain because they are maximum-likelihood estimated. ANN structure is also uncertain because there is no unique ANN model given a specific case. Therefore, multiple plausible AI models are generally resulted for a study. One might ask why good models have to be ignored in favor of the best model in traditional estimation. What is the ANN estimation variance? How do the variances from different ANN models accumulate to the total estimation variance? To answer these questions we propose a Hierarchical Bayesian Model Averaging (HBMA) framework. Instead of choosing one ANN model (the best ANN model) for estimation, HBMA averages outputs of all plausible ANN models. The model weights are based on the evidence of data. Therefore, the HBMA avoids overconfidence on the single best ANN model. In addition, HBMA is able to analyze uncertainty propagation through aggregation of ANN models in a hierarchy framework. This method is applied for estimation of fluoride concentration in the Poldasht plain and the Bazargan plain in Iran. Unusually high fluoride concentration in the Poldasht and Bazargan plains has caused negative effects on the public health. Management of this anomaly requires estimation of fluoride concentration distribution in the area. The results show that the HBMA provides a knowledge-decision-based framework that facilitates analyzing and quantifying ANN estimation uncertainties from different sources. In addition HBMA allows comparative evaluation of the realizations for each source of uncertainty by segregating the uncertainty sources in a hierarchical framework. Fluoride concentration estimation using the HBMA method shows better agreement to the observation data in the test step because they are not based on a single model with a non-dominate weights.

Insights in spatio-temporal characterization of human fetal neural stem cells.

PubMed

Martín-Ibáñez, Raquel; Guardia, Inés; Pardo, Mónica; Herranz, Cristina; Zietlow, Rike; Vinh, Ngoc-Nga; Rosser, Anne; Canals, Josep M

2017-05-01

Primary human fetal cells have been used in clinical trials of cell replacement therapy for the treatment of neurodegenerative disorders such as Huntington's disease (HD). However, human fetal primary cells are scarce and difficult to work with and so a renewable source of cells is sought. Human fetal neural stem cells (hfNSCs) can be generated from human fetal tissue, but little is known about the differences between hfNSCs obtained from different developmental stages and brain areas. In the present work we characterized hfNSCs, grown as neurospheres, obtained from three developmental stages: 4-5, 6-7 and 8-9weeks post conception (wpc) and four brain areas: forebrain, cortex, whole ganglionic eminence (WGE) and cerebellum. We observed that, as fetal brain development proceeds, the number of neural precursors is diminished and post-mitotic cells are increased. In turn, primary cells obtained from older embryos are more sensitive to the dissociation process, their viability is diminished and they present lower proliferation ratios compared to younger embryos. However, independently of the developmental stage of derivation proliferation ratios were very low in all cases. Improvements in the expansion rates were achieved by mechanical, instead of enzymatic, dissociation of neurospheres but not by changes in the seeding densities. Regardless of the developmental stage, neurosphere cultures presented large variability in the viability and proliferation rates during the initial 3-4 passages, but stabilized achieving significant expansion rates at passage 5 to 6. This was true also for all brain regions except cerebellar derived cultures that did not expand. Interestingly, the brain region of hfNSC derivation influences the expansion potential, being forebrain, cortex and WGE derived cells the most expandable compared to cerebellar. Short term expansion partially compromised the regional identity of cortical but not WGE cultures. Nevertheless, both expanded cultures were multipotent and kept the ability to differentiate to region specific mature neuronal phenotypes. Copyright © 2017 Elsevier Inc. All rights reserved.

Double dissociation in the neural substrates of acute opiate dependence as measured by withdrawal-potentiated startle.

PubMed

Harris, A C; Atkinson, D M; Aase, D M; Gewirtz, J C

2006-01-01

The basolateral amygdala and portions of the "extended" amygdala (i.e. central nucleus of the amygdala, bed nucleus of the stria terminalis and shell of the nucleus accumbens) have been implicated in the aversive aspects of withdrawal from chronic opiate administration. Given that similar withdrawal signs are observed following a single opiate exposure, these structures may also play a role in "acute opiate dependence." In the current study, drug-naïve rats underwent naloxone-precipitated withdrawal from acute morphine (10 mg/kg) exposure on two successive days. On either the first or second day of testing, the basolateral amygdala, central nucleus of the amygdala, bed nucleus of the stria terminalis, or nucleus accumbens was temporarily inactivated immediately prior to naloxone injection by microinfusion of the glutamatergic alpha-amino-3-hydroxy-5-methyl-4-isoxazole proprionic acid receptor antagonist 1,2,3,4-tetrahydro-6-nitro-2,3-dioxo-benzo(f)quinoxaline-7-sulfonamide (3 microg/0.5 microl). On the first day, inactivation of the basolateral amygdala, central nucleus of the amygdala, or bed nucleus of the stria terminalis, but not the nucleus accumbens blocked withdrawal-potentiated startle, a behavioral measure of the anxiogenic effects of withdrawal. On the second day, inactivation of the nucleus accumbens, but not the basolateral amygdala, central nucleus of the amygdala, or bed nucleus of the stria terminalis disrupted the withdrawal effect. Effects of structural inactivations on withdrawal-potentiated startle were not influenced by differences in withdrawal severity on the two days of testing. A fear-potentiated startle procedure provided functional confirmation of correct cannulae placement in basolateral amygdale- and central nucleus of the amygdala-implanted animals. Our findings indicate a double dissociation in the neural substrates of withdrawal-potentiated startle following a first versus second morphine exposure, and may reflect a reorganization of the neural circuitry underlying the expression of withdrawal-induced negative affect during the earliest stages of opiate dependence.

A promising tool to achieve chemical accuracy for density functional theory calculations on Y-NO homolysis bond dissociation energies.

PubMed

Li, Hong Zhi; Hu, Li Hong; Tao, Wei; Gao, Ting; Li, Hui; Lu, Ying Hua; Su, Zhong Min

2012-01-01

A DFT-SOFM-RBFNN method is proposed to improve the accuracy of DFT calculations on Y-NO (Y = C, N, O, S) homolysis bond dissociation energies (BDE) by combining density functional theory (DFT) and artificial intelligence/machine learning methods, which consist of self-organizing feature mapping neural networks (SOFMNN) and radial basis function neural networks (RBFNN). A descriptor refinement step including SOFMNN clustering analysis and correlation analysis is implemented. The SOFMNN clustering analysis is applied to classify descriptors, and the representative descriptors in the groups are selected as neural network inputs according to their closeness to the experimental values through correlation analysis. Redundant descriptors and intuitively biased choices of descriptors can be avoided by this newly introduced step. Using RBFNN calculation with the selected descriptors, chemical accuracy (≤1 kcal·mol(-1)) is achieved for all 92 calculated organic Y-NO homolysis BDE calculated by DFT-B3LYP, and the mean absolute deviations (MADs) of the B3LYP/6-31G(d) and B3LYP/STO-3G methods are reduced from 4.45 and 10.53 kcal·mol(-1) to 0.15 and 0.18 kcal·mol(-1), respectively. The improved results for the minimal basis set STO-3G reach the same accuracy as those of 6-31G(d), and thus B3LYP calculation with the minimal basis set is recommended to be used for minimizing the computational cost and to expand the applications to large molecular systems. Further extrapolation tests are performed with six molecules (two containing Si-NO bonds and two containing fluorine), and the accuracy of the tests was within 1 kcal·mol(-1). This study shows that DFT-SOFM-RBFNN is an efficient and highly accurate method for Y-NO homolysis BDE. The method may be used as a tool to design new NO carrier molecules.

A Promising Tool to Achieve Chemical Accuracy for Density Functional Theory Calculations on Y-NO Homolysis Bond Dissociation Energies

PubMed Central

Li, Hong Zhi; Hu, Li Hong; Tao, Wei; Gao, Ting; Li, Hui; Lu, Ying Hua; Su, Zhong Min

2012-01-01

A DFT-SOFM-RBFNN method is proposed to improve the accuracy of DFT calculations on Y-NO (Y = C, N, O, S) homolysis bond dissociation energies (BDE) by combining density functional theory (DFT) and artificial intelligence/machine learning methods, which consist of self-organizing feature mapping neural networks (SOFMNN) and radial basis function neural networks (RBFNN). A descriptor refinement step including SOFMNN clustering analysis and correlation analysis is implemented. The SOFMNN clustering analysis is applied to classify descriptors, and the representative descriptors in the groups are selected as neural network inputs according to their closeness to the experimental values through correlation analysis. Redundant descriptors and intuitively biased choices of descriptors can be avoided by this newly introduced step. Using RBFNN calculation with the selected descriptors, chemical accuracy (≤1 kcal·mol−1) is achieved for all 92 calculated organic Y-NO homolysis BDE calculated by DFT-B3LYP, and the mean absolute deviations (MADs) of the B3LYP/6-31G(d) and B3LYP/STO-3G methods are reduced from 4.45 and 10.53 kcal·mol−1 to 0.15 and 0.18 kcal·mol−1, respectively. The improved results for the minimal basis set STO-3G reach the same accuracy as those of 6-31G(d), and thus B3LYP calculation with the minimal basis set is recommended to be used for minimizing the computational cost and to expand the applications to large molecular systems. Further extrapolation tests are performed with six molecules (two containing Si-NO bonds and two containing fluorine), and the accuracy of the tests was within 1 kcal·mol−1. This study shows that DFT-SOFM-RBFNN is an efficient and highly accurate method for Y-NO homolysis BDE. The method may be used as a tool to design new NO carrier molecules. PMID:22942689

A Neuropsychological Approach to Understanding Risk-Taking for Potential Gains and Losses

PubMed Central

Levin, Irwin P.; Xue, Gui; Weller, Joshua A.; Reimann, Martin; Lauriola, Marco; Bechara, Antoine

2012-01-01

Affective neuroscience has helped guide research and theory development in judgment and decision-making by revealing the role of emotional processes in choice behavior, especially when risk is involved. Evidence is emerging that qualitatively and quantitatively different processes may be involved in risky decision-making for gains and losses. We start by reviewing behavioral work by Kahneman and Tversky (1979) and others, which shows that risk-taking differs for potential gains and potential losses. We then turn to the literature in decision neuroscience to support the gain versus loss distinction. Relying in part on data from a new task that separates risky decision-making for gains and losses, we test a neural model that assigns unique mechanisms for risky decision-making involving potential losses. Included are studies using patients with lesions to brain areas specified as important in the model and studies with healthy individuals whose brains are scanned to reveal activation in these and other areas during risky decision-making. In some cases, there is evidence that gains and losses are processed in different regions of the brain, while in other cases the same region appears to process risk in a different manner for gains and losses. At a more general level, we provide strong support for the notion that decisions involving risk-taking for gains and decisions involving risk-taking for losses represent different psychological processes. At a deeper level, we present mounting evidence that different neural structures play different roles in guiding risky choices in these different domains. Some structures are differentially activated by risky gains and risky losses while others respond uniquely in one domain or the other. Taken together, these studies support a clear functional dissociation between risk-taking for gains and risk-taking for losses, and further dissociation at the neural level. PMID:22347161

Molecular dynamics investigations of ozone on an ab initio potential energy surface with the utilization of pattern-recognition neural network for accurate determination of product formation.

PubMed

Le, Hung M; Dinh, Thach S; Le, Hieu V

2011-10-13

The singlet-triplet transformation and molecular dissociation of ozone (O(3)) gas is investigated by performing quasi-classical molecular dynamics (MD) simulations on an ab initio potential energy surface (PES) with visible and near-infrared excitations. MP4(SDQ) level of theory with the 6-311g(2d,2p) basis set is executed for three different electronic spin states (singlet, triplet, and quintet). In order to simplify the potential energy function, an approximation is adopted by ignoring the spin-orbit coupling and allowing the molecule to switch favorably and instantaneously to the spin state that is more energetically stable (lowest in energy among the three spin states). This assumption has previously been utilized to study the SiO(2) system as reported by Agrawal et al. (J. Chem. Phys. 2006, 124 (13), 134306). The use of such assumption in this study probably makes the upper limits of computed rate coefficients the true rate coefficients. The global PES for ozone is constructed by fitting 5906 ab initio data points using a 60-neuron two-layer feed-forward neural network. The mean-absolute error and root-mean-squared error of this fit are 0.0446 eV (1.03 kcal/mol) and 0.0756 eV (1.74 kcal/mol), respectively, which reveal very good fitting accuracy. The parameter coefficients of the global PES are reported in this paper. In order to identify the spin state with high confidence, we propose the use of a pattern-recognition neural network, which is trained to predict the spin state of a given configuration (with a prediction accuracy being 95.6% on a set of testing data points). To enhance the prediction effectiveness, a buffer series of five points are validated to confirm the spin state during the MD process to gain better confidence. Quasi-classical MD simulations from 1.2 to 2.4 eV of total internal energy (including zero-point energy) result in rate coefficients of singlet-triplet transformation in the range of 0.027 ps(-1) to 1.21 ps(-1). Also, we find very low dissociation probability up to 2.4 eV of internal energy during the investigating period (5 ps), which suggests that dissociation does not occur directly from the singlet ground-state, but it involves the excited triplet-state as an intermediate step and requires more reaction time to occur.

High-order tracking differentiator based adaptive neural control of a flexible air-breathing hypersonic vehicle subject to actuators constraints.

PubMed

Bu, Xiangwei; Wu, Xiaoyan; Tian, Mingyan; Huang, Jiaqi; Zhang, Rui; Ma, Zhen

2015-09-01

In this paper, an adaptive neural controller is exploited for a constrained flexible air-breathing hypersonic vehicle (FAHV) based on high-order tracking differentiator (HTD). By utilizing functional decomposition methodology, the dynamic model is reasonably decomposed into the respective velocity subsystem and altitude subsystem. For the velocity subsystem, a dynamic inversion based neural controller is constructed. By introducing the HTD to adaptively estimate the newly defined states generated in the process of model transformation, a novel neural based altitude controller that is quite simpler than the ones derived from back-stepping is addressed based on the normal output-feedback form instead of the strict-feedback formulation. Based on minimal-learning parameter scheme, only two neural networks with two adaptive parameters are needed for neural approximation. Especially, a novel auxiliary system is explored to deal with the problem of control inputs constraints. Finally, simulation results are presented to test the effectiveness of the proposed control strategy in the presence of system uncertainties and actuators constraints. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Fact or factitious? A psychobiological study of authentic and simulated dissociative identity states.

PubMed

Reinders, A A T S; Reinders, A A T Simone; Willemsen, Antoon T M; Vos, Herry P J; den Boer, Johan A; Nijenhuis, Ellert R S

2012-01-01

Dissociative identity disorder (DID) is a disputed psychiatric disorder. Research findings and clinical observations suggest that DID involves an authentic mental disorder related to factors such as traumatization and disrupted attachment. A competing view indicates that DID is due to fantasy proneness, suggestibility, suggestion, and role-playing. Here we examine whether dissociative identity state-dependent psychobiological features in DID can be induced in high or low fantasy prone individuals by instructed and motivated role-playing, and suggestion. DID patients, high fantasy prone and low fantasy prone controls were studied in two different types of identity states (neutral and trauma-related) in an autobiographical memory script-driven (neutral or trauma-related) imagery paradigm. The controls were instructed to enact the two DID identity states. Twenty-nine subjects participated in the study: 11 patients with DID, 10 high fantasy prone DID simulating controls, and 8 low fantasy prone DID simulating controls. Autonomic and subjective reactions were obtained. Differences in psychophysiological and neural activation patterns were found between the DID patients and both high and low fantasy prone controls. That is, the identity states in DID were not convincingly enacted by DID simulating controls. Thus, important differences regarding regional cerebral bloodflow and psychophysiological responses for different types of identity states in patients with DID were upheld after controlling for DID simulation. The findings are at odds with the idea that differences among different types of dissociative identity states in DID can be explained by high fantasy proneness, motivated role-enactment, and suggestion. They indicate that DID does not have a sociocultural (e.g., iatrogenic) origin.

Natural Memory Beyond the Storage Model: Repression, Trauma, and the Construction of a Personal Past

PubMed Central

Axmacher, Nikolai; Do Lam, Anne T. A.; Kessler, Henrik; Fell, Juergen

2010-01-01

Naturally occurring memory processes show features which are difficult to investigate by conventional cognitive neuroscience paradigms. Distortions of memory for problematic contents are described both by psychoanalysis (internal conflicts) and research on post-traumatic stress disorder (PTSD; external traumata). Typically, declarative memory for these contents is impaired – possibly due to repression in the case of internal conflicts or due to dissociation in the case of external traumata – but they continue to exert an unconscious pathological influence: neurotic symptoms or psychosomatic disorders after repression or flashbacks and intrusions in PTSD after dissociation. Several experimental paradigms aim at investigating repression in healthy control subjects. We argue that these paradigms do not adequately operationalize the clinical process of repression, because they rely on an intentional inhibition of random stimuli (suppression). Furthermore, these paradigms ignore that memory distortions due to repression or dissociation are most accurately characterized by a lack of self-referential processing, resulting in an impaired integration of these contents into the self. This aspect of repression and dissociation cannot be captured by the concept of memory as a storage device which is usually employed in the cognitive neurosciences. It can only be assessed within the framework of a constructivist memory concept, according to which successful memory involves a reconstruction of experiences such that they fit into a representation of the self. We suggest several experimental paradigms that allow for the investigation of the neural correlates of repressed memories and trauma-induced memory distortions based on a constructivist memory concept. PMID:21151366

Electromagnetic Dissociation of Uranium in Heavy Ion Collisions at 120 Mev/a

NASA Astrophysics Data System (ADS)

Justice, Marvin Lealon

The heavy-ion induced electromagnetic dissociation (EMD) of a 120 MeV/A ^{238}U beam incident on five targets (^9Be, ^{27}Al, ^ {nat}Cu, ^{nat} Ag, and ^{nat}U) has been studied experimentally. Electromagnetic dissociation at this beam energy is essentially a two step process involving the excitation of a giant resonance followed by particle decay. At 120 MeV/A there is predicted to be a significant contribution (~25%) of the giant quadrupole resonance to the EMD cross sections. The specific exit channel which was looked at was projectile fission. The two fission fragments were detected in coincidence by an array of solid-state DeltaE-E detectors, allowing the charges of the fragments to be determined to within +/- .5 units. The events were sorted on the basis of the sums of the fragments' charges, acceptance corrections were applied, and total cross sections for the most peripheral events (i.e. those leading to charge sums of approximately 92) were determined. Electromagnetic fission at the beam energy of this experiment always leads to a true charge sum of 92. Due to the imperfect resolution of the detectors, charge sums of 91 and 93 were included in order to account for all of the electromagnetic fission events. The experimentally observed cross sections are due to nuclear interaction processes as well as electromagnetic processes. Under the conditions of this experiment, the cross sections for the beryllium target are almost entirely due to nuclear processes. The nuclear cross sections for the other four targets were determined by extrapolation from the beryllium data using a geometrical scaling model. After subtraction of the nuclear cross sections, the resulting electromagnetic cross sections are compared to theoretical calculations based on the equivalent photon approximation. Systematic uncertainties associated with the normalization of the data make quantitative comparisons with theory difficult, however. The systematic uncertainties are discussed and suggestions for improving the experiment are given.

Robust adaptive backstepping neural networks control for spacecraft rendezvous and docking with input saturation.

PubMed

Xia, Kewei; Huo, Wei

2016-05-01

This paper presents a robust adaptive neural networks control strategy for spacecraft rendezvous and docking with the coupled position and attitude dynamics under input saturation. Backstepping technique is applied to design a relative attitude controller and a relative position controller, respectively. The dynamics uncertainties are approximated by radial basis function neural networks (RBFNNs). A novel switching controller consists of an adaptive neural networks controller dominating in its active region combined with an extra robust controller to avoid invalidation of the RBFNNs destroying stability of the system outside the neural active region. An auxiliary signal is introduced to compensate the input saturation with anti-windup technique, and a command filter is employed to approximate derivative of the virtual control in the backstepping procedure. Globally uniformly ultimately bounded of the relative states is proved via Lyapunov theory. Simulation example demonstrates effectiveness of the proposed control scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Containment control of networked autonomous underwater vehicles: A predictor-based neural DSC design.

PubMed

Peng, Zhouhua; Wang, Dan; Wang, Wei; Liu, Lu

2015-11-01

This paper investigates the containment control problem of networked autonomous underwater vehicles in the presence of model uncertainty and unknown ocean disturbances. A predictor-based neural dynamic surface control design method is presented to develop the distributed adaptive containment controllers, under which the trajectories of follower vehicles nearly converge to the dynamic convex hull spanned by multiple reference trajectories over a directed network. Prediction errors, rather than tracking errors, are used to update the neural adaptation laws, which are independent of the tracking error dynamics, resulting in two time-scales to govern the entire system. The stability property of the closed-loop network is established via Lyapunov analysis, and transient property is quantified in terms of L2 norms of the derivatives of neural weights, which are shown to be smaller than the classical neural dynamic surface control approach. Comparative studies are given to show the substantial improvements of the proposed new method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Robustness analysis of uncertain dynamical neural networks with multiple time delays.

PubMed

Senan, Sibel

2015-10-01

This paper studies the problem of global robust asymptotic stability of the equilibrium point for the class of dynamical neural networks with multiple time delays with respect to the class of slope-bounded activation functions and in the presence of the uncertainties of system parameters of the considered neural network model. By using an appropriate Lyapunov functional and exploiting the properties of the homeomorphism mapping theorem, we derive a new sufficient condition for the existence, uniqueness and global robust asymptotic stability of the equilibrium point for the class of neural networks with multiple time delays. The obtained stability condition basically relies on testing some relationships imposed on the interconnection matrices of the neural system, which can be easily verified by using some certain properties of matrices. An instructive numerical example is also given to illustrate the applicability of our result and show the advantages of this new condition over the previously reported corresponding results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Overcoming rule-based rigidity and connectionist limitations through massively-parallel case-based reasoning

NASA Technical Reports Server (NTRS)

Barnden, John; Srinivas, Kankanahalli

1990-01-01

Symbol manipulation as used in traditional Artificial Intelligence has been criticized by neural net researchers for being excessively inflexible and sequential. On the other hand, the application of neural net techniques to the types of high-level cognitive processing studied in traditional artificial intelligence presents major problems as well. A promising way out of this impasse is to build neural net models that accomplish massively parallel case-based reasoning. Case-based reasoning, which has received much attention recently, is essentially the same as analogy-based reasoning, and avoids many of the problems leveled at traditional artificial intelligence. Further problems are avoided by doing many strands of case-based reasoning in parallel, and by implementing the whole system as a neural net. In addition, such a system provides an approach to some aspects of the problems of noise, uncertainty and novelty in reasoning systems. The current neural net system (Conposit), which performs standard rule-based reasoning, is being modified into a massively parallel case-based reasoning version.

Neural correlates of auditory short-term memory in rostral superior temporal cortex

PubMed Central

Scott, Brian H.; Mishkin, Mortimer; Yin, Pingbo

2014-01-01

Summary Background Auditory short-term memory (STM) in the monkey is less robust than visual STM and may depend on a retained sensory trace, which is likely to reside in the higher-order cortical areas of the auditory ventral stream. Results We recorded from the rostral superior temporal cortex as monkeys performed serial auditory delayed-match-to-sample (DMS). A subset of neurons exhibited modulations of their firing rate during the delay between sounds, during the sensory response, or both. This distributed subpopulation carried a predominantly sensory signal modulated by the mnemonic context of the stimulus. Excitatory and suppressive effects on match responses were dissociable in their timing, and in their resistance to sounds intervening between the sample and match. Conclusions Like the monkeys’ behavioral performance, these neuronal effects differ from those reported in the same species during visual DMS, suggesting different neural mechanisms for retaining dynamic sounds and static images in STM. PMID:25456448

Neuropsychology of aging, past, present and future: Contributions of Morris Moscovitch.

PubMed

Reuter-Lorenz, Patricia A; Cooke, Katherine A

2016-09-01

In this review we provide a broad overview of major trends in the cognitive neuroscience of aging and illustrate their roots in the pioneering ideas and discoveries of Morris Moscovitch and his close collaborators, especially Gordon Winocur. These trends include an on-going focus on the specific and dissociable contributions of medial temporal and frontal lobe processes to cognitive aging, especially in the memory domain, the role of individual variability stemming from different patterns of underlying neural decline, the possibility of compensatory neural and cognitive influences that alter the expression of neurobiological aging, and the investigation of lifestyle and psychosocial factors that affect plasticity and may contribute to the rate and level of neurocognitive decline. These prescient ideas, evident in the early work of Moscovitch and Winocur, continue to drive on-going research efforts in the cognitive neuroscience of aging. Copyright © 2016 Elsevier Ltd. All rights reserved.

Sight and blindness in the same person: Gating in the visual system.

PubMed

Strasburger, Hans; Waldvogel, Bruno

2015-12-01

We present the case of a patient having dissociative identity disorder (DID) who-after 15 years of misdiagnosed cortical blindness--step-by-step regained sight during psychotherapeutic treatment. At first only a few personality states regained vision whereas others remained blind. This could be confirmed by electrophysiological measurement, in which visual evoked potentials (VEPs) were absent in the blind personality states but were normal and stable in the seeing states. A switch between these states could happen within seconds. We assume a top-down modulation of activity in the primary visual pathway as a neural basis of such psychogenic blindness, possibly at the level of the thalamus. VEPs therefore do not allow separating psychogenic blindness from organic disruption of the visual pathway. In summary, psychogenic blindness seems to suppress visual information at an early neural stage. © 2015 The Institute of Psychology, Chinese Academy of Sciences and Wiley Publishing Asia Pty Ltd.

Neural Correlates of Lyrical Improvisation: An fMRI Study of Freestyle Rap

PubMed Central

Liu, Siyuan; Chow, Ho Ming; Xu, Yisheng; Erkkinen, Michael G.; Swett, Katherine E.; Eagle, Michael W.; Rizik-Baer, Daniel A.; Braun, Allen R.

2012-01-01

The neural correlates of creativity are poorly understood. Freestyle rap provides a unique opportunity to study spontaneous lyrical improvisation, a multidimensional form of creativity at the interface of music and language. Here we use functional magnetic resonance imaging to characterize this process. Task contrast analyses indicate that improvised performance is characterized by dissociated activity in medial and dorsolateral prefrontal cortices, providing a context in which stimulus-independent behaviors may unfold in the absence of conscious monitoring and volitional control. Connectivity analyses reveal widespread improvisation-related correlations between medial prefrontal, cingulate motor, perisylvian cortices and amygdala, suggesting the emergence of a network linking motivation, language, affect and movement. Lyrical improvisation appears to be characterized by altered relationships between regions coupling intention and action, in which conventional executive control may be bypassed and motor control directed by cingulate motor mechanisms. These functional reorganizations may facilitate the initial improvisatory phase of creative behavior. PMID:23155479

Neural correlates of lyrical improvisation: an FMRI study of freestyle rap.

PubMed

Liu, Siyuan; Chow, Ho Ming; Xu, Yisheng; Erkkinen, Michael G; Swett, Katherine E; Eagle, Michael W; Rizik-Baer, Daniel A; Braun, Allen R

2012-01-01

The neural correlates of creativity are poorly understood. Freestyle rap provides a unique opportunity to study spontaneous lyrical improvisation, a multidimensional form of creativity at the interface of music and language. Here we use functional magnetic resonance imaging to characterize this process. Task contrast analyses indicate that improvised performance is characterized by dissociated activity in medial and dorsolateral prefrontal cortices, providing a context in which stimulus-independent behaviors may unfold in the absence of conscious monitoring and volitional control. Connectivity analyses reveal widespread improvisation-related correlations between medial prefrontal, cingulate motor, perisylvian cortices and amygdala, suggesting the emergence of a network linking motivation, language, affect and movement. Lyrical improvisation appears to be characterized by altered relationships between regions coupling intention and action, in which conventional executive control may be bypassed and motor control directed by cingulate motor mechanisms. These functional reorganizations may facilitate the initial improvisatory phase of creative behavior.

Breathlessness, fatigue and the respiratory muscles.

PubMed

Mioxham, John; Jolley, Caroline

2009-10-01

Breathlessness is a common symptom in respiratory, cardiovascular and malignant disease. It reduces exercise tolerance and mobility, and is an important determinant of quality of life. The multifactorial nature of the symptom often presents difficulties in understanding why individual patients are breathless, and how breathlessness should best be palliated, especially in advanced disease. However, insights into the neurophysiological factors underlying the symptom can be gained by considering the balance between the load on, and capacity of, the respiratory muscles and increased neural respiratory drive, reflecting increased respiratory effort. Mismatch between efferent neural respiratory drive and afferent feedback, reflecting the degree of neuromechanical dissociation, is also important. This paper describes mechanisms by which ventilatory load, capacity and drive may be affected by disease, and how these can be measured physiologically. The schema presented also provides a framework for understanding the mechanisms by which interventions that relieve breathlessness may have their effect.

Habit formation.

PubMed

Smith, Kyle S; Graybiel, Ann M

2016-03-01

Habits, both good ones and bad ones, are pervasive in animal behavior. Important frameworks have been developed to understand habits through psychological and neurobiological studies. This work has given us a rich understanding of brain networks that promote habits, and has also helped us to understand what constitutes a habitual behavior as opposed to a behavior that is more flexible and prospective. Mounting evidence from studies using neural recording methods suggests that habit formation is not a simple process. We review this evidence and take the position that habits could be sculpted from multiple dissociable changes in neural activity. These changes occur across multiple brain regions and even within single brain regions. This strategy of classifying components of a habit based on different brain signals provides a potentially useful new way to conceive of disorders that involve overly fixed behaviors as arising from different potential dysfunctions within the brain's habit network.

Habit formation

PubMed Central

Smith, Kyle S.; Graybiel, Ann M.

2016-01-01

Habits, both good ones and bad ones, are pervasive in animal behavior. Important frameworks have been developed to understand habits through psychological and neurobiological studies. This work has given us a rich understanding of brain networks that promote habits, and has also helped us to understand what constitutes a habitual behavior as opposed to a behavior that is more flexible and prospective. Mounting evidence from studies using neural recording methods suggests that habit formation is not a simple process. We review this evidence and take the position that habits could be sculpted from multiple dissociable changes in neural activity. These changes occur across multiple brain regions and even within single brain regions. This strategy of classifying components of a habit based on different brain signals provides a potentially useful new way to conceive of disorders that involve overly fixed behaviors as arising from different potential dysfunctions within the brain's habit network. PMID:27069378

The neural correlates of visual self-recognition.

PubMed

Devue, Christel; Brédart, Serge

2011-03-01

This paper presents a review of studies that were aimed at determining which brain regions are recruited during visual self-recognition, with a particular focus on self-face recognition. A complex bilateral network, involving frontal, parietal and occipital areas, appears to be associated with self-face recognition, with a particularly high implication of the right hemisphere. Results indicate that it remains difficult to determine which specific cognitive operation is reflected by each recruited brain area, in part due to the variability of used control stimuli and experimental tasks. A synthesis of the interpretations provided by previous studies is presented. The relevance of using self-recognition as an indicator of self-awareness is discussed. We argue that a major aim of future research in the field should be to identify more clearly the cognitive operations induced by the perception of the self-face, and search for dissociations between neural correlates and cognitive components. Copyright © 2010 Elsevier Inc. All rights reserved.

Dissociable intrinsic functional networks support noun-object and verb-action processing.

PubMed

Yang, Huichao; Lin, Qixiang; Han, Zaizhu; Li, Hongyu; Song, Luping; Chen, Lingjuan; He, Yong; Bi, Yanchao

2017-12-01

The processing mechanism of verbs-actions and nouns-objects is a central topic of language research, with robust evidence for behavioral dissociation. The neural basis for these two major word and/or conceptual classes, however, remains controversial. Two experiments were conducted to study this question from the network perspective. Experiment 1 found that nodes of the same class, obtained through task-evoked brain imaging meta-analyses, were more strongly connected with each other than nodes of different classes during resting-state, forming segregated network modules. Experiment 2 examined the behavioral relevance of these intrinsic networks using data from 88 brain-damaged patients, finding that across patients the relative strength of functional connectivity of the two networks significantly correlated with the noun-object vs. verb-action relative behavioral performances. In summary, we found that verbs-actions and nouns-objects are supported by separable intrinsic functional networks and that the integrity of such networks accounts for the relative noun-object- and verb-action-selective deficits. Copyright © 2017 Elsevier Inc. All rights reserved.

Selective increase of intention-based economic decisions by noninvasive brain stimulation to the dorsolateral prefrontal cortex.

PubMed

Nihonsugi, Tsuyoshi; Ihara, Aya; Haruno, Masahiko

2015-02-25

The intention behind another's action and the impact of the outcome are major determinants of human economic behavior. It is poorly understood, however, whether the two systems share a core neural computation. Here, we investigated whether the two systems are causally dissociable in the brain by integrating computational modeling, functional magnetic resonance imaging, and transcranial direct current stimulation experiments in a newly developed trust game task. We show not only that right dorsolateral prefrontal cortex (DLPFC) activity is correlated with intention-based economic decisions and that ventral striatum and amygdala activity are correlated with outcome-based decisions, but also that stimulation to the DLPFC selectively enhances intention-based decisions. These findings suggest that the right DLPFC is involved in the implementation of intention-based decisions in the processing of cooperative decisions. This causal dissociation of cortical and subcortical backgrounds may indicate evolutionary and developmental differences in the two decision systems. Copyright © 2015 the authors 0270-6474/15/53412-08$15.00/0.

Dissociable parietal regions facilitate successful retrieval of recently learned and personally familiar information.

PubMed

Elman, Jeremy A; Cohn-Sheehy, Brendan I; Shimamura, Arthur P

2013-03-01

In fMRI analyses, the posterior parietal cortex (PPC) is particularly active during the successful retrieval of episodic memory. To delineate the neural correlates of episodic retrieval more succinctly, we compared retrieval of recently learned spatial locations (photographs of buildings) with retrieval of previously familiar locations (photographs of familiar campus buildings). Episodic retrieval of recently learned locations activated a circumscribed region within the ventral PPC (anterior angular gyrus and adjacent regions in the supramarginal gyrus) as well as medial PPC regions (posterior cingulated gyrus and posterior precuneus). Retrieval of familiar locations activated more posterior regions in the ventral PPC (posterior angular gyrus, LOC) and more anterior regions in the medial PPC (anterior precuneus and retrosplenial cortex). These dissociable effects define more precisely PPC regions involved in the retrieval of recent, contextually bound information as opposed to regions involved in other processes, such as visual imagery, scene reconstruction, and self-referential processing. Copyright © 2012 Elsevier Ltd. All rights reserved.

Dissociable prefrontal brain systems for attention and emotion

NASA Astrophysics Data System (ADS)

Yamasaki, Hiroshi; Labar, Kevin S.; McCarthy, Gregory

2002-08-01

The prefrontal cortex has been implicated in a variety of attentional, executive, and mnemonic mental operations, yet its functional organization is still highly debated. The present study used functional MRI to determine whether attentional and emotional functions are segregated into dissociable prefrontal networks in the human brain. Subjects discriminated infrequent and irregularly presented attentional targets (circles) from frequent standards (squares) while novel distracting scenes, parametrically varied for emotional arousal, were intermittently presented. Targets differentially activated middle frontal gyrus, posterior parietal cortex, and posterior cingulate gyrus. Novel distracters activated inferior frontal gyrus, amygdala, and fusiform gyrus, with significantly stronger activation evoked by the emotional scenes. The anterior cingulate gyrus was the only brain region with equivalent responses to attentional and emotional stimuli. These results show that attentional and emotional functions are segregated into parallel dorsal and ventral streams that extend into prefrontal cortex and are integrated in the anterior cingulate. These findings may have implications for understanding the neural dynamics underlying emotional distractibility on attentional tasks in affective disorders. novelty | prefrontal cortex | amygdala | cingulate gyrus

Modality and morphology: what we write may not be what we say.

PubMed

Rapp, Brenda; Fischer-Baum, Simon; Miozzo, Michele

2015-06-01

Written language is an evolutionarily recent human invention; consequently, its neural substrates cannot be determined by the genetic code. How, then, does the brain incorporate skills of this type? One possibility is that written language is dependent on evolutionarily older skills, such as spoken language; another is that dedicated substrates develop with expertise. If written language does depend on spoken language, then acquired deficits of spoken and written language should necessarily co-occur. Alternatively, if at least some substrates are dedicated to written language, such deficits may doubly dissociate. We report on 5 individuals with aphasia, documenting a double dissociation in which the production of affixes (e.g., the -ing in jumping) is disrupted in writing but not speaking or vice versa. The findings reveal that written- and spoken-language systems are considerably independent from the standpoint of morpho-orthographic operations. Understanding this independence of the orthographic system in adults has implications for the education and rehabilitation of people with written-language deficits. © The Author(s) 2015.

Anxiety dissociates the adaptive functions of sensory and motor response enhancements to social threats

PubMed Central

El Zein, Marwa; Wyart, Valentin; Grèzes, Julie

2015-01-01

Efficient detection and reaction to negative signals in the environment is essential for survival. In social situations, these signals are often ambiguous and can imply different levels of threat for the observer, thereby making their recognition susceptible to contextual cues – such as gaze direction when judging facial displays of emotion. However, the mechanisms underlying such contextual effects remain poorly understood. By computational modeling of human behavior and electrical brain activity, we demonstrate that gaze direction enhances the perceptual sensitivity to threat-signaling emotions – anger paired with direct gaze, and fear paired with averted gaze. This effect arises simultaneously in ventral face-selective and dorsal motor cortices at 200 ms following face presentation, dissociates across individuals as a function of anxiety, and does not reflect increased attention to threat-signaling emotions. These findings reveal that threat tunes neural processing in fast, selective, yet attention-independent fashion in sensory and motor systems, for different adaptive purposes. DOI: http://dx.doi.org/10.7554/eLife.10274.001 PMID:26712157

Using Hypnotic Suggestion to Model Loss of Control and Awareness of Movements: An Exploratory fMRI Study

PubMed Central

Oakley, David A.; Bell, Vaughan; Koppel, Cristina; Mehta, Mitul A.; Halligan, Peter W.

2013-01-01

The feeling of voluntary control and awareness of movement is fundamental to our notions of selfhood and responsibility for actions, yet can be lost in neuropsychiatric syndromes (e.g. delusions of control, non-epileptic seizures) and culturally influenced dissociative states (e.g. attributions of spirit possession). The brain processes involved remain poorly understood. We used suggestion and functional magnetic resonance imaging (fMRI) to investigate loss of control and awareness of right hand movements in 15 highly hypnotically suggestible subjects. Loss of perceived control of movements was associated with reduced connectivity between supplementary motor area (SMA) and motor regions. Reduced awareness of involuntary movements was associated with less activation in parietal cortices (BA 7, BA 40) and insula. Collectively these results suggest that the sense of voluntary control of movement may critically depend on the functional coupling of SMA with motor systems, and provide a potential neural basis for the narrowing of awareness reported in pathological and culturally influenced dissociative phenomena. PMID:24205198

Dog experts' brains distinguish socially relevant body postures similarly in dogs and humans.

PubMed

Kujala, Miiamaaria V; Kujala, Jan; Carlson, Synnöve; Hari, Riitta

2012-01-01

We read conspecifics' social cues effortlessly, but little is known about our abilities to understand social gestures of other species. To investigate the neural underpinnings of such skills, we used functional magnetic resonance imaging to study the brain activity of experts and non-experts of dog behavior while they observed humans or dogs either interacting with, or facing away from a conspecific. The posterior superior temporal sulcus (pSTS) of both subject groups dissociated humans facing toward each other from humans facing away, and in dog experts, a distinction also occurred for dogs facing toward vs. away in a bilateral area extending from the pSTS to the inferior temporo-occipital cortex: the dissociation of dog behavior was significantly stronger in expert than control group. Furthermore, the control group had stronger pSTS responses to humans than dogs facing toward a conspecific, whereas in dog experts, the responses were of similar magnitude. These findings suggest that dog experts' brains distinguish socially relevant body postures similarly in dogs and humans.

RBF neural network based PI pitch controller for a class of 5-MW wind turbines using particle swarm optimization algorithm.

PubMed

Poultangari, Iman; Shahnazi, Reza; Sheikhan, Mansour

2012-09-01

In order to control the pitch angle of blades in wind turbines, commonly the proportional and integral (PI) controller due to its simplicity and industrial usability is employed. The neural networks and evolutionary algorithms are tools that provide a suitable ground to determine the optimal PI gains. In this paper, a radial basis function (RBF) neural network based PI controller is proposed for collective pitch control (CPC) of a 5-MW wind turbine. In order to provide an optimal dataset to train the RBF neural network, particle swarm optimization (PSO) evolutionary algorithm is used. The proposed method does not need the complexities, nonlinearities and uncertainties of the system under control. The simulation results show that the proposed controller has satisfactory performance. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

Novel prescribed performance neural control of a flexible air-breathing hypersonic vehicle with unknown initial errors.

PubMed

Bu, Xiangwei; Wu, Xiaoyan; Zhu, Fujing; Huang, Jiaqi; Ma, Zhen; Zhang, Rui

2015-11-01

A novel prescribed performance neural controller with unknown initial errors is addressed for the longitudinal dynamic model of a flexible air-breathing hypersonic vehicle (FAHV) subject to parametric uncertainties. Different from traditional prescribed performance control (PPC) requiring that the initial errors have to be known accurately, this paper investigates the tracking control without accurate initial errors via exploiting a new performance function. A combined neural back-stepping and minimal learning parameter (MLP) technology is employed for exploring a prescribed performance controller that provides robust tracking of velocity and altitude reference trajectories. The highlight is that the transient performance of velocity and altitude tracking errors is satisfactory and the computational load of neural approximation is low. Finally, numerical simulation results from a nonlinear FAHV model demonstrate the efficacy of the proposed strategy. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Dissociative part-dependent biopsychosocial reactions to backward masked angry and neutral faces: An fMRI study of dissociative identity disorder.

PubMed

Schlumpf, Yolanda R; Nijenhuis, Ellert R S; Chalavi, Sima; Weder, Ekaterina V; Zimmermann, Eva; Luechinger, Roger; La Marca, Roberto; Reinders, A A T Simone; Jäncke, Lutz

2013-01-01

The Theory of Structural Dissociation of the Personality (TSDP) proposes that dissociative identity disorder (DID) patients are fixed in traumatic memories as "Emotional Parts" (EP), but mentally avoid these as "Apparently Normal Parts" of the personality (ANP). We tested the hypotheses that ANP and EP have different biopsychosocial reactions to subliminally presented angry and neutral faces, and that actors instructed and motivated to simulate ANP and EP react differently. Women with DID and matched healthy female actors (CON) were as ANP and EP (DIDanp, DIDep, CONanp, CONep) consecutively exposed to masked neutral and angry faces. Their brain activation was monitored using functional magnetic resonance imaging. The black-and-white dotted masks preceding and following the faces each had a centered colored dot, but in a different color. Participants were instructed to immediately press a button after a perceived color change. State anxiety was assessed after each run using the STAI-S. Final statistical analyses were conducted on 11 DID patients and 15 controls for differences in neural activity, and 13 DID patients and 15 controls for differences in behavior and psychometric measures. Differences between ANP and EP in DID patients and between DID and CON in the two dissociative parts of the personality were generally larger for neutral than for angry faces. The longest reaction times (RTs) existed for DIDep when exposed to neutral faces. Compared to DIDanp, DIDep was associated with more activation of the parahippocampal gyrus. Following neutral faces and compared to CONep, DIDep had more activation in the brainstem, face-sensitive regions, and motor-related areas. DIDanp showed a decreased activity all over the brain in the neutral and angry face condition. There were neither significant within differences nor significant between group differences in state anxiety. CON was not able to simulate genuine ANP and EP biopsychosocially. DID patients have dissociative part-dependent biopsychosocial reactions to masked neutral and angry faces. As EP, they are overactivated, and as ANP underactivated. The findings support TSDP. Major clinical implications are discussed.

Dissociative part-dependent biopsychosocial reactions to backward masked angry and neutral faces: An fMRI study of dissociative identity disorder☆

PubMed Central

Schlumpf, Yolanda R.; Nijenhuis, Ellert R.S.; Chalavi, Sima; Weder, Ekaterina V.; Zimmermann, Eva; Luechinger, Roger; La Marca, Roberto; Reinders, A.A.T. Simone; Jäncke, Lutz

2013-01-01

Objective The Theory of Structural Dissociation of the Personality (TSDP) proposes that dissociative identity disorder (DID) patients are fixed in traumatic memories as “Emotional Parts” (EP), but mentally avoid these as “Apparently Normal Parts” of the personality (ANP). We tested the hypotheses that ANP and EP have different biopsychosocial reactions to subliminally presented angry and neutral faces, and that actors instructed and motivated to simulate ANP and EP react differently. Methods Women with DID and matched healthy female actors (CON) were as ANP and EP (DIDanp, DIDep, CONanp, CONep) consecutively exposed to masked neutral and angry faces. Their brain activation was monitored using functional magnetic resonance imaging. The black-and-white dotted masks preceding and following the faces each had a centered colored dot, but in a different color. Participants were instructed to immediately press a button after a perceived color change. State anxiety was assessed after each run using the STAI-S. Final statistical analyses were conducted on 11 DID patients and 15 controls for differences in neural activity, and 13 DID patients and 15 controls for differences in behavior and psychometric measures. Results Differences between ANP and EP in DID patients and between DID and CON in the two dissociative parts of the personality were generally larger for neutral than for angry faces. The longest reaction times (RTs) existed for DIDep when exposed to neutral faces. Compared to DIDanp, DIDep was associated with more activation of the parahippocampal gyrus. Following neutral faces and compared to CONep, DIDep had more activation in the brainstem, face-sensitive regions, and motor-related areas. DIDanp showed a decreased activity all over the brain in the neutral and angry face condition. There were neither significant within differences nor significant between group differences in state anxiety. CON was not able to simulate genuine ANP and EP biopsychosocially. Conclusions DID patients have dissociative part-dependent biopsychosocial reactions to masked neutral and angry faces. As EP, they are overactivated, and as ANP underactivated. The findings support TSDP. Major clinical implications are discussed. PMID:24179849

A Non-linear Predictive Model of Borderline Personality Disorder Based on Multilayer Perceptron.

PubMed

Maldonato, Nelson M; Sperandeo, Raffaele; Moretto, Enrico; Dell'Orco, Silvia

2018-01-01

Borderline Personality Disorder is a serious mental disease, classified in Cluster B of DSM IV-TR personality disorders. People with this syndrome presents an anamnesis of traumatic experiences and shows dissociative symptoms. Since not all subjects who have been victims of trauma develop a Borderline Personality Disorder, the emergence of this serious disease seems to have the fragility of character as a predisposing condition. Infect, numerous studies show that subjects positive for diagnosis of Borderline Personality Disorder had scores extremely high or extremely low to some temperamental dimensions (harm Avoidance and reward dependence) and character dimensions (cooperativeness and self directedness). In a sample of 602 subjects, who have had consecutive access to an Outpatient Mental Health Service, it was evaluated the presence of Borderline Personality Disorder using the semi-structured interview for the DSM IV-TR personality disorders. In this population we assessed the presence of dissociative symptoms with the Dissociative Experiences Scale and the personality traits with the Temperament and Character Inventory developed by Cloninger. To assess the weight and the predictive value of these psychopathological dimensions in relation to the Borderline Personality Disorder diagnosis, a neural network statistical model called "multilayer perceptron," was implemented. This model was developed with a dichotomous dependent variable, consisting in the presence or absence of the diagnosis of borderline personality disorder and with five covariates. The first one is the taxonomic subscale of dissociative experience scale, the others are temperamental and characterial traits: Novelty-Seeking, Harm-Avoidance, Self-Directedness and Cooperativeness. The statistical model, that results satisfactory, showed a significance capacity (89%) to predict the presence of borderline personality disorder. Furthermore, the dissociative symptoms seem to have a greater influence than the character traits in the borderline personality disorder e disease. In conclusion, the results seem to indicate that to borderline personality disorder development, contribute both psychic factors, such as temperament and character traits, and environmental factors, such as traumatic events capable of producing dissociative symptoms. These factors interact in a nonlinear way in producing maladaptive behaviors typical of this disorder.

Frontotemporal lobar degeneration and social behaviour: Dissociation between the knowledge of its consequences and its conceptual meaning.

PubMed

Zahn, Roland; Green, Sophie; Beaumont, Helen; Burns, Alistair; Moll, Jorge; Caine, Diana; Gerhard, Alexander; Hoffman, Paul; Shaw, Benjamin; Grafman, Jordan; Lambon Ralph, Matthew A

2017-08-01

Inappropriate social behaviour is an early symptom of frontotemporal lobar degeneration (FTLD) in both behavioural variant frontotemporal dementia (bvFTD) and semantic dementia (SD) subtypes. Knowledge of social behaviour is essential for appropriate social conduct. The superior anterior temporal lobe (ATL) has been identified as one key neural component for the conceptual knowledge of social behaviour, but it is unknown whether this is dissociable from knowledge of the consequences of social behaviour. Here, we used a newly-developed test of knowledge about long-term and short-term consequences of social behaviour to investigate its impairment in patients with FTLD relative to a previously-developed test of social conceptual knowledge. We included 19 healthy elderly control participants and 19 consecutive patients with features of bvFTD or SD and defined dissociations as performance differences between tasks for each patient (Bonferroni-corrected p < .05). Knowledge of long-term consequences was selectively impaired relative to short-term consequences in five patients and the reverse dissociation occurred in one patient. Six patients showed a selective impairment of social concepts relative to long-term consequences with the reverse dissociation occurring in one patient. These results corroborate the hypothesis that knowledge of long-term consequences of social behaviour is dissociable from knowledge of short-term consequences, as well as of social conceptual knowledge. Confirming our hypothesis, we found that patients with more marked grey matter (GM) volume loss in frontopolar relative to right superior ATL regions of interest exhibited poorer knowledge of the long-term consequences of social behaviour relative to the knowledge of its conceptual meaning and vice versa (n = 15). These findings support the hypothesis that frontopolar and ATL regions represent distinct aspects of social knowledge. This suggests that rather than being unable to suppress urges to behave inappropriately, FTLD patients often lose the knowledge of what appropriate social behaviour is and can therefore not be expected to behave accordingly. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

Hierarchical modeling of molecular energies using a deep neural network

NASA Astrophysics Data System (ADS)

Lubbers, Nicholas; Smith, Justin S.; Barros, Kipton

2018-06-01

We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion, HIP-NN decomposes properties, such as energy, as a sum over hierarchical terms. These terms are generated from a neural network—a composition of many nonlinear transformations—acting on a representation of the molecule. HIP-NN achieves the state-of-the-art performance on a dataset of 131k ground state organic molecules and predicts energies with 0.26 kcal/mol mean absolute error. With minimal tuning, our model is also competitive on a dataset of molecular dynamics trajectories. In addition to enabling accurate energy predictions, the hierarchical structure of HIP-NN helps to identify regions of model uncertainty.

[Modulation of Metacognition with Decoded Neurofeedback].

PubMed

Koizumi, Ai; Cortese, Aurelio; Amano, Kaoru; Kawato, Mitsuo; Lau, Hakwan

2017-12-01

Humans often assess their confidence in their own perception, e.g., feeling "confident" or "certain" of having seen a friend, or feeling "uncertain" about whether the phone rang. The neural mechanism underlying the metacognitive function that reflects subjective perception still remains under debate. We have previously used decoded neurofeedback (DecNef) to demonstrate that manipulating the multivoxel activation patterns in the frontoparietal network modulates perceptual confidence without affecting perceptual performance. The results provided clear evidence for a dissociation between perceptual confidence and performance and suggested a distinct role of the frontoparietal network in metacognition.

Neural correlates of sexual cue reactivity in individuals with and without compulsive sexual behaviours.

PubMed

Voon, Valerie; Mole, Thomas B; Banca, Paula; Porter, Laura; Morris, Laurel; Mitchell, Simon; Lapa, Tatyana R; Karr, Judy; Harrison, Neil A; Potenza, Marc N; Irvine, Michael

2014-01-01

Although compulsive sexual behaviour (CSB) has been conceptualized as a "behavioural" addiction and common or overlapping neural circuits may govern the processing of natural and drug rewards, little is known regarding the responses to sexually explicit materials in individuals with and without CSB. Here, the processing of cues of varying sexual content was assessed in individuals with and without CSB, focusing on neural regions identified in prior studies of drug-cue reactivity. 19 CSB subjects and 19 healthy volunteers were assessed using functional MRI comparing sexually explicit videos with non-sexual exciting videos. Ratings of sexual desire and liking were obtained. Relative to healthy volunteers, CSB subjects had greater desire but similar liking scores in response to the sexually explicit videos. Exposure to sexually explicit cues in CSB compared to non-CSB subjects was associated with activation of the dorsal anterior cingulate, ventral striatum and amygdala. Functional connectivity of the dorsal anterior cingulate-ventral striatum-amygdala network was associated with subjective sexual desire (but not liking) to a greater degree in CSB relative to non-CSB subjects. The dissociation between desire or wanting and liking is consistent with theories of incentive motivation underlying CSB as in drug addictions. Neural differences in the processing of sexual-cue reactivity were identified in CSB subjects in regions previously implicated in drug-cue reactivity studies. The greater engagement of corticostriatal limbic circuitry in CSB following exposure to sexual cues suggests neural mechanisms underlying CSB and potential biological targets for interventions.

Neural Correlates of Sexual Cue Reactivity in Individuals with and without Compulsive Sexual Behaviours

PubMed Central

Voon, Valerie; Mole, Thomas B.; Banca, Paula; Porter, Laura; Morris, Laurel; Mitchell, Simon; Lapa, Tatyana R.; Karr, Judy; Harrison, Neil A.; Potenza, Marc N.; Irvine, Michael

2014-01-01

Although compulsive sexual behaviour (CSB) has been conceptualized as a “behavioural” addiction and common or overlapping neural circuits may govern the processing of natural and drug rewards, little is known regarding the responses to sexually explicit materials in individuals with and without CSB. Here, the processing of cues of varying sexual content was assessed in individuals with and without CSB, focusing on neural regions identified in prior studies of drug-cue reactivity. 19 CSB subjects and 19 healthy volunteers were assessed using functional MRI comparing sexually explicit videos with non-sexual exciting videos. Ratings of sexual desire and liking were obtained. Relative to healthy volunteers, CSB subjects had greater desire but similar liking scores in response to the sexually explicit videos. Exposure to sexually explicit cues in CSB compared to non-CSB subjects was associated with activation of the dorsal anterior cingulate, ventral striatum and amygdala. Functional connectivity of the dorsal anterior cingulate-ventral striatum-amygdala network was associated with subjective sexual desire (but not liking) to a greater degree in CSB relative to non-CSB subjects. The dissociation between desire or wanting and liking is consistent with theories of incentive motivation underlying CSB as in drug addictions. Neural differences in the processing of sexual-cue reactivity were identified in CSB subjects in regions previously implicated in drug-cue reactivity studies. The greater engagement of corticostriatal limbic circuitry in CSB following exposure to sexual cues suggests neural mechanisms underlying CSB and potential biological targets for interventions. PMID:25013940

Very High Resolution Tree Cover Mapping for Continental United States using Deep Convolutional Neural Networks

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Kalia, Subodh; Li, Shuang; Michaelis, Andrew; Nemani, Ramakrishna R.; Saatchi, Sassan A

2017-01-01

Uncertainties in input land cover estimates contribute to a significant bias in modeled above ground biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

Short-term load and wind power forecasting using neural network-based prediction intervals.

PubMed

Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

2014-02-01

Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

Human pursuance of equality hinges on mental processes of projecting oneself into the perspectives of others and into future situations.

PubMed

Takesue, Hirofumi; Miyauchi, Carlos Makoto; Sakaiya, Shiro; Fan, Hongwei; Matsuda, Tetsuya; Kato, Junko

2017-07-19

In the pursuance of equality, behavioural scientists disagree about distinct motivators, that is, consideration of others and prospective calculation for oneself. However, accumulating data suggest that these motivators may share a common process in the brain whereby perspectives and events that did not arise in the immediate environment are conceived. To examine this, we devised a game imitating a real decision-making situation regarding redistribution among income classes in a welfare state. The neural correlates of redistributive decisions were examined under contrasting conditions, with and without uncertainty, which affects support for equality in society. The dorsal anterior cingulate cortex (dACC) and the caudate nucleus were activated by equality decisions with uncertainty but by selfless decisions without uncertainty. Activation was also correlated with subjective values. Activation in both the dACC and the caudate nucleus was associated with the attitude to prefer accordance with others, whereas activation in the caudate nucleus reflected that the expected reward involved the prospective calculation of relative income. The neural correlates suggest that consideration of others and prospective calculation for oneself may underlie the support for equality. Projecting oneself into the perspective of others and into prospective future situations may underpin the pursuance of equality.

Very High Resolution Tree Cover Mapping for Continental United States using Deep Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Ganguly, S.; Kalia, S.; Li, S.; Michaelis, A.; Nemani, R. R.; Saatchi, S.

2017-12-01

Uncertainties in input land cover estimates contribute to a significant bias in modeled above gound biomass (AGB) and carbon estimates from satellite-derived data. The resolution of most currently used passive remote sensing products is not sufficient to capture tree canopy cover of less than ca. 10-20 percent, limiting their utility to estimate canopy cover and AGB for trees outside of forest land. In our study, we created a first of its kind Continental United States (CONUS) tree cover map at a spatial resolution of 1-m for the 2010-2012 epoch using the USDA NAIP imagery to address the present uncertainties in AGB estimates. The process involves different tasks including data acquisition/ingestion to pre-processing and running a state-of-art encoder-decoder based deep convolutional neural network (CNN) algorithm for automatically generating a tree/non-tree map for almost a quarter million scenes. The entire processing chain including generation of the largest open source existing aerial/satellite image training database was performed at the NEX supercomputing and storage facility. We believe the resulting forest cover product will substantially contribute to filling the gaps in ongoing carbon and ecological monitoring research and help quantifying the errors and uncertainties in derived products.

Sensory Optimization by Stochastic Tuning

PubMed Central

Jurica, Peter; Gepshtein, Sergei; Tyukin, Ivan; van Leeuwen, Cees

2013-01-01

Individually, visual neurons are each selective for several aspects of stimulation, such as stimulus location, frequency content, and speed. Collectively, the neurons implement the visual system’s preferential sensitivity to some stimuli over others, manifested in behavioral sensitivity functions. We ask how the individual neurons are coordinated to optimize visual sensitivity. We model synaptic plasticity in a generic neural circuit, and find that stochastic changes in strengths of synaptic connections entail fluctuations in parameters of neural receptive fields. The fluctuations correlate with uncertainty of sensory measurement in individual neurons: the higher the uncertainty the larger the amplitude of fluctuation. We show that this simple relationship is sufficient for the stochastic fluctuations to steer sensitivities of neurons toward a characteristic distribution, from which follows a sensitivity function observed in human psychophysics, and which is predicted by a theory of optimal allocation of receptive fields. The optimal allocation arises in our simulations without supervision or feedback about system performance and independently of coupling between neurons, making the system highly adaptive and sensitive to prevailing stimulation. PMID:24219849

Neural network-based position synchronised internal force control scheme for cooperative manipulator system

NASA Astrophysics Data System (ADS)

Wang, Jin; Xu, Fan; Lu, GuoDong

2017-09-01

More complex problems of simultaneous position and internal force control occur with cooperative manipulator systems than that of a single one. In the presence of unwanted parametric and modelling uncertainties as well as external disturbances, a decentralised position synchronised force control scheme is proposed. With a feedforward neural network estimating engine, a precise model of the system dynamics is not required. Unlike conventional cooperative or synchronised controllers, virtual position and virtual synchronisation errors are introduced for internal force tracking control and task space position synchronisation. Meanwhile joint space synchronisation and force measurement are unnecessary. Together with simulation studies and analysis, the position and the internal force errors are shown to asymptotically converge to zero. Moreover, the controller exhibits different characteristics with selected synchronisation factors. Under certain settings, it can deal with temporary cooperation by an intelligent retreat mechanism, where less internal force would occur and rigid collision can be avoided. Using a Lyapunov stability approach, the controller is proven to be robust in face of the aforementioned uncertainties.

Functional Roles of Neural Preparatory Processes in a Cued Stroop Task Revealed by Linking Electrophysiology with Behavioral Performance

PubMed Central

Wang, Chao; Ding, Mingzhou; Kluger, Benzi M.

2015-01-01

It is well established that cuing facilitates behavioral performance and that different aspects of instructional cues evoke specific neural preparatory processes in cued task-switching paradigms. To deduce the functional role of these neural preparatory processes the majority of studies vary aspects of the experimental paradigm and describe how these variations alter markers of neural preparatory processes. Although these studies provide important insights, they also have notable limitations, particularly in terms of understanding the causal or functional relationship of neural markers to cognitive and behavioral processes. In this study, we sought to address these limitations and uncover the functional roles of neural processes by examining how variability in the amplitude of neural preparatory processes predicts behavioral performance to subsequent stimuli. To achieve this objective 16 young adults were recruited to perform a cued Stroop task while their brain activity was measured using high-density electroencephalography. Four temporally overlapping but functionally and topographically distinct cue-triggered event related potentials (ERPs) were identified: 1) A left-frontotemporal negativity (250-700 ms) that was positively associated with word-reading performance; 2) a midline-frontal negativity (450-800 ms) that was positively associated with color-naming and incongruent performance; 3) a left-frontal negativity (450-800 ms) that was positively associated with switch trial performance; and 4) a centroparietal positivity (450-800 ms) that was positively associated with performance for almost all trial types. These results suggest that at least four dissociable cognitive processes are evoked by instructional cues in the present task, including: 1) domain-specific task facilitation; 2) switch-specific task-set reconfiguration; 3) preparation for response conflict; and 4) proactive attentional control. Examining the relationship between ERPs and behavioral performance provides a functional link between neural markers and the cognitive processes they index. PMID:26230662

Validating neural-network refinements of nuclear mass models

NASA Astrophysics Data System (ADS)

Utama, R.; Piekarewicz, J.

2018-01-01

Background: Nuclear astrophysics centers on the role of nuclear physics in the cosmos. In particular, nuclear masses at the limits of stability are critical in the development of stellar structure and the origin of the elements. Purpose: We aim to test and validate the predictions of recently refined nuclear mass models against the newly published AME2016 compilation. Methods: The basic paradigm underlining the recently refined nuclear mass models is based on existing state-of-the-art models that are subsequently refined through the training of an artificial neural network. Bayesian inference is used to determine the parameters of the neural network so that statistical uncertainties are provided for all model predictions. Results: We observe a significant improvement in the Bayesian neural network (BNN) predictions relative to the corresponding "bare" models when compared to the nearly 50 new masses reported in the AME2016 compilation. Further, AME2016 estimates for the handful of impactful isotopes in the determination of r -process abundances are found to be in fairly good agreement with our theoretical predictions. Indeed, the BNN-improved Duflo-Zuker model predicts a root-mean-square deviation relative to experiment of σrms≃400 keV. Conclusions: Given the excellent performance of the BNN refinement in confronting the recently published AME2016 compilation, we are confident of its critical role in our quest for mass models of the highest quality. Moreover, as uncertainty quantification is at the core of the BNN approach, the improved mass models are in a unique position to identify those nuclei that will have the strongest impact in resolving some of the outstanding questions in nuclear astrophysics.

Dissociations of cognitive inhibition, response inhibition, and emotional interference: Voxelwise ALE meta-analyses of fMRI studies.

PubMed

Hung, Yuwen; Gaillard, Schuyler L; Yarmak, Pavel; Arsalidou, Marie

2018-06-19

Inhibitory control is the stopping of a mental process with or without intention, conceptualized as mental suppression of competing information because of limited cognitive capacity. Inhibitory control dysfunction is a core characteristic of many major psychiatric disorders. Inhibition is generally thought to involve the prefrontal cortex; however, a single inhibitory mechanism is insufficient for interpreting the heterogeneous nature of human cognition. It remains unclear whether different dimensions of inhibitory processes-specifically cognitive inhibition, response inhibition, and emotional interference-rely on dissociated neural systems. We conducted systematic meta-analyses of fMRI studies in the BrainMap database supplemented by PubMed using whole-brain activation likelihood estimation. A total of 66 study experiments including 1,447 participants and 987 foci revealed that while the left anterior insula was concordant in all inhibitory dimensions, cognitive inhibition reliably activated specific dorsal frontal inhibitory system, engaging dorsal anterior cingulate, dorsolateral prefrontal cortex, and parietal areas, whereas emotional interference reliably implicated a ventral inhibitory system, involving the ventral surface of the inferior frontal gyrus and the amygdala. Response inhibition showed concordant clusters in the fronto-striatal system, including the dorsal anterior cingulate region and extended supplementary motor areas, the dorsal and ventral lateral prefrontal cortex, basal ganglia, midbrain regions, and parietal regions. We provide an empirically derived dimensional model of inhibition characterizing neural systems underlying different aspects of inhibitory mechanisms. This study offers a fundamental framework to advance current understanding of inhibition and provides new insights for future clinical research into disorders with different types of inhibition-related dysfunctions. © 2018 Wiley Periodicals, Inc.

Experience-Dependent Hemispheric Specialization of Letters and Numbers is Revealed in Early Visual Processing

PubMed Central

Park, Joonkoo; Chiang, Crystal; Brannon, Elizabeth M.; Woldorff, Marty G.

2014-01-01

Recent functional magnetic resonance imaging research has demonstrated that letters and numbers are preferentially processed in distinct regions and hemispheres in the visual cortex. In particular, the left visual cortex preferentially processes letters compared to numbers, while the right visual cortex preferentially processes numbers compared to letters. Because letters and numbers are cultural inventions and are otherwise physically arbitrary, such a double dissociation is strong evidence for experiential effects on neural architecture. Here, we use the high temporal resolution of event-related potentials (ERPs) to investigate the temporal dynamics of the neural dissociation between letters and numbers. We show that the divergence between ERP traces to letters and numbers emerges very early in processing. Letters evoked greater N1 waves (latencies 140–170 ms) than did numbers over left occipital channels, while numbers evoked greater N1s than letters over the right, suggesting letters and numbers are preferentially processed in opposite hemispheres early in visual encoding. Moreover, strings of letters, but not single letters, elicited greater P2 ERP waves, (starting around 250 ms) than numbers did over the left hemisphere, suggesting that the visual cortex is tuned to selectively process combinations of letters, but not numbers, further along in the visual processing stream. Additionally, the processing of both of these culturally defined stimulus types differentiated from similar but unfamiliar visual stimulus forms (false fonts) even earlier in the processing stream (the P1 at 100 ms). These findings imply major cortical specialization processes within the visual system driven by experience with reading and mathematics. PMID:24669789

Experience-dependent hemispheric specialization of letters and numbers is revealed in early visual processing.

PubMed

Park, Joonkoo; Chiang, Crystal; Brannon, Elizabeth M; Woldorff, Marty G

2014-10-01

Recent fMRI research has demonstrated that letters and numbers are preferentially processed in distinct regions and hemispheres in the visual cortex. In particular, the left visual cortex preferentially processes letters compared with numbers, whereas the right visual cortex preferentially processes numbers compared with letters. Because letters and numbers are cultural inventions and are otherwise physically arbitrary, such a double dissociation is strong evidence for experiential effects on neural architecture. Here, we use the high temporal resolution of ERPs to investigate the temporal dynamics of the neural dissociation between letters and numbers. We show that the divergence between ERP traces to letters and numbers emerges very early in processing. Letters evoked greater N1 waves (latencies 140-170 msec) than did numbers over left occipital channels, whereas numbers evoked greater N1s than letters over the right, suggesting letters and numbers are preferentially processed in opposite hemispheres early in visual encoding. Moreover, strings of letters, but not single letters, elicited greater P2 ERP waves (starting around 250 msec) than numbers did over the left hemisphere, suggesting that the visual cortex is tuned to selectively process combinations of letters, but not numbers, further along in the visual processing stream. Additionally, the processing of both of these culturally defined stimulus types differentiated from similar but unfamiliar visual stimulus forms (false fonts) even earlier in the processing stream (the P1 at 100 msec). These findings imply major cortical specialization processes within the visual system driven by experience with reading and mathematics.

Neural correlates of self-deception and impression-management.

PubMed

Farrow, Tom F D; Burgess, Jenny; Wilkinson, Iain D; Hunter, Michael D

2015-01-01

Self-deception and impression-management comprise two types of deceptive, but generally socially acceptable behaviours, which are common in everyday life as well as being present in a number of psychiatric disorders. We sought to establish and dissociate the 'normal' brain substrates of self-deception and impression-management. Twenty healthy participants underwent fMRI scanning at 3T whilst completing the 'Balanced Inventory of Desirable Responding' test under two conditions: 'fake good', giving the most desirable impression possible and 'fake bad' giving an undesirable impression. Impression-management scores were more malleable to manipulation via 'faking' than self-deception scores. Response times to self-deception questions and 'fake bad' instructions were significantly longer than to impression-management questions and 'fake good' instructions respectively. Self-deception and impression-management manipulation and 'faking bad' were associated with activation of medial prefrontal cortex (mPFC) and left ventrolateral prefrontal cortex (vlPFC). Impression-management manipulation was additionally associated with activation of left dorsolateral prefrontal cortex and left posterior middle temporal gyrus. 'Faking bad' was additionally associated with activation of right vlPFC, left temporo-parietal junction and right cerebellum. There were no supra-threshold activations associated with 'faking good'. Our neuroimaging data suggest that manipulating self-deception and impression-management and more specifically 'faking bad' engages a common network comprising mPFC and left vlPFC. Shorter response times and lack of dissociable neural activations suggests that 'faking good', particularly when it comes to impression-management, may be our most practiced 'default' mode. Copyright © 2014 Elsevier Ltd. All rights reserved.

Dissociating maternal responses to sad and happy facial expressions of their own child: An fMRI study

PubMed Central

Hindi Attar, Catherine; Stein, Jenny; Poppinga, Sina; Fydrich, Thomas; Jaite, Charlotte; Kappel, Viola; Brunner, Romuald; Herpertz, Sabine C.; Boedeker, Katja; Bermpohl, Felix

2017-01-01

Background Maternal sensitive behavior depends on recognizing one’s own child’s affective states. The present study investigated distinct and overlapping neural responses of mothers to sad and happy facial expressions of their own child (in comparison to facial expressions of an unfamiliar child). Methods We used functional MRI to measure dissociable and overlapping activation patterns in 27 healthy mothers in response to happy, neutral and sad facial expressions of their own school-aged child and a gender- and age-matched unfamiliar child. To investigate differential activation to sad compared to happy faces of one’s own child, we used interaction contrasts. During the scan, mothers had to indicate the affect of the presented face. After scanning, they were asked to rate the perceived emotional arousal and valence levels for each face using a 7-point Likert-scale (adapted SAM version). Results While viewing their own child’s sad faces, mothers showed activation in the amygdala and anterior cingulate cortex whereas happy facial expressions of the own child elicited activation in the hippocampus. Conjoint activation in response to one’s own child happy and sad expressions was found in the insula and the superior temporal gyrus. Conclusions Maternal brain activations differed depending on the child’s affective state. Sad faces of the own child activated areas commonly associated with a threat detection network, whereas happy faces activated reward related brain areas. Overlapping activation was found in empathy related networks. These distinct neural activation patterns might facilitate sensitive maternal behavior. PMID:28806742

Functional Organization of the Parahippocampal Cortex: Dissociable Roles for Context Representations and the Perception of Visual Scenes.

PubMed

Baumann, Oliver; Mattingley, Jason B

2016-02-24

The human parahippocampal cortex has been ascribed central roles in both visuospatial and mnemonic processes. More specifically, evidence suggests that the parahippocampal cortex subserves both the perceptual analysis of scene layouts as well as the retrieval of associative contextual memories. It remains unclear, however, whether these two functional roles can be dissociated within the parahippocampal cortex anatomically. Here, we provide evidence for a dissociation between neural activation patterns associated with visuospatial analysis of scenes and contextual mnemonic processing along the parahippocampal longitudinal axis. We used fMRI to measure parahippocampal responses while participants engaged in a task that required them to judge the contextual relatedness of scene and object pairs, which were presented either as words or pictures. Results from combined factorial and conjunction analyses indicated that the posterior section of parahippocampal cortex is driven predominantly by judgments associated with pictorial scene analysis, whereas its anterior section is more active during contextual judgments regardless of stimulus category (scenes vs objects) or modality (word vs picture). Activation maxima associated with visuospatial and mnemonic processes were spatially segregated, providing support for the existence of functionally distinct subregions along the parahippocampal longitudinal axis and suggesting that, in humans, the parahippocampal cortex serves as a functional interface between perception and memory systems. Copyright © 2016 the authors 0270-6474/16/362536-07$15.00/0.

Double dissociation between rules and memory in music: an event-related potential study.

PubMed

Miranda, Robbin A; Ullman, Michael T

2007-11-01

Language and music share a number of characteristics. Crucially, both domains depend on both rules and memorized representations. Double dissociations between the neurocognition of rule-governed and memory-based knowledge have been found in language but not music. Here, the neural bases of both of these aspects of music were examined with an event-related potential (ERP) study of note violations in melodies. Rule-only violations consisted of out-of-key deviant notes that violated tonal harmony rules in novel (unfamiliar) melodies. Memory-only violations consisted of in-key deviant notes in familiar well-known melodies; these notes followed musical rules but deviated from the actual melodies. Finally, out-of-key notes in familiar well-known melodies constituted violations of both rules and memory. All three conditions were presented, within-subjects, to healthy young adults, half musicians and half non-musicians. The results revealed a double dissociation, independent of musical training, between rules and memory: both rule violation conditions, but not the memory-only violations, elicited an early, somewhat right-lateralized anterior-central negativity (ERAN), consistent with previous studies of rule violations in music, and analogous to the early left-lateralized anterior negativities elicited by rule violations in language. In contrast, both memory violation conditions, but not the rule-only violation, elicited a posterior negativity that might be characterized as an N400, an ERP component that depends, at least in part, on the processing of representations stored in long-term memory, both in language and in other domains. The results suggest that the neurocognitive rule/memory dissociation extends from language to music, further strengthening the similarities between the two domains.

Fact or Factitious? A Psychobiological Study of Authentic and Simulated Dissociative Identity States

PubMed Central

Simone Reinders, A. A. T.; Willemsen, Antoon T. M.; Vos, Herry P. J.; den Boer, Johan A.; Nijenhuis, Ellert R. S.

2012-01-01

Background Dissociative identity disorder (DID) is a disputed psychiatric disorder. Research findings and clinical observations suggest that DID involves an authentic mental disorder related to factors such as traumatization and disrupted attachment. A competing view indicates that DID is due to fantasy proneness, suggestibility, suggestion, and role-playing. Here we examine whether dissociative identity state-dependent psychobiological features in DID can be induced in high or low fantasy prone individuals by instructed and motivated role-playing, and suggestion. Methodology/Principal Findings DID patients, high fantasy prone and low fantasy prone controls were studied in two different types of identity states (neutral and trauma-related) in an autobiographical memory script-driven (neutral or trauma-related) imagery paradigm. The controls were instructed to enact the two DID identity states. Twenty-nine subjects participated in the study: 11 patients with DID, 10 high fantasy prone DID simulating controls, and 8 low fantasy prone DID simulating controls. Autonomic and subjective reactions were obtained. Differences in psychophysiological and neural activation patterns were found between the DID patients and both high and low fantasy prone controls. That is, the identity states in DID were not convincingly enacted by DID simulating controls. Thus, important differences regarding regional cerebral bloodflow and psychophysiological responses for different types of identity states in patients with DID were upheld after controlling for DID simulation. Conclusions/Significance The findings are at odds with the idea that differences among different types of dissociative identity states in DID can be explained by high fantasy proneness, motivated role-enactment, and suggestion. They indicate that DID does not have a sociocultural (e.g., iatrogenic) origin. PMID:22768068

Double dissociation between rules and memory in music: An event-related potential study

PubMed Central

Miranda, Robbin A.; Ullman, Michael T.

2007-01-01

Language and music share a number of characteristics. Crucially, both domains depend on both rules and memorized representations. Double dissociations between the neurocognition of rule-governed and memory-based knowledge have been found in language but not music. Here, the neural bases of both of these aspects of music were examined with an event-related potential (ERP) study of note violations in melodies. Rule-only violations consisted of out-of-key deviant notes that violated tonal harmony rules in novel (unfamiliar) melodies. Memory-only violations consisted of in-key deviant notes in familiar well-known melodies; these notes followed musical rules but deviated from the actual melodies. Finally, out-of-key notes in familiar well-known melodies constituted violations of both rules and memory. All three conditions were presented, within-subjects, to healthy young adults, half musicians and half non-musicians. The results revealed a double dissociation, independent of musical training, between rules and memory: both rule violation conditions, but not the memory-only violations, elicited an early, somewhat right-lateralized anterior-central negativity (ERAN), consistent with previous studies of rule violations in music, and analogous to the early left-lateralized anterior negativities elicited by rule violations in language. In contrast, both memory violation conditions, but not the rule-only violation, elicited a posterior negativity that might be characterized as an N400, an ERP component that depends, at least in part, on the processing of representations stored in long-term memory, both in language and in other domains. The results suggest that the neurocognitive rule/memory dissociation extends from language to music, further strengthening the similarities between the two domains. PMID:17855126

Disruption of visual awareness during the attentional blink is reflected by selective disruption of late-stage neural processing

PubMed Central

Harris, Joseph A.; McMahon, Alex R.; Woldorff, Marty G.

2015-01-01

Any information represented in the brain holds the potential to influence behavior. It is therefore of broad interest to determine the extent and quality of neural processing of stimulus input that occurs with and without awareness. The attentional blink is a useful tool for dissociating neural and behavioral measures of perceptual visual processing across conditions of awareness. The extent of higher-order visual information beyond basic sensory signaling that is processed during the attentional blink remains controversial. To determine what neural processing at the level of visual-object identification occurs in the absence of awareness, electrophysiological responses to images of faces and houses were recorded both within and outside of the attentional blink period during a rapid serial visual presentation (RSVP) stream. Electrophysiological results were sorted according to behavioral performance (correctly identified targets versus missed targets) within these blink and non-blink periods. An early index of face-specific processing (the N170, 140–220 ms post-stimulus) was observed regardless of whether the subject demonstrated awareness of the stimulus, whereas a later face-specific effect with the same topographic distribution (500–700 ms post-stimulus) was only seen for accurate behavioral discrimination of the stimulus content. The present findings suggest a multi-stage process of object-category processing, with only the later phase being associated with explicit visual awareness. PMID:23859644

Transient and sustained neural responses to death-related linguistic cues

PubMed Central

Shi, Zhenhao

2013-01-01

Recent research showed that perception of death-related vs death-unrelated linguistic cues produced increased frontoparietal activity but decreased insular activity. This study investigated (i) whether the increased frontoparietal and decreased insular activities are, respectively, associated with transient trial-specific processes of death-related linguistic cues and sustained death-related thought during death-relevance judgments on linguistic cues and (ii) whether the neural activity underlying death-related thought can predict individuals’ dispositional death anxiety. Participants were presented with death-related/unrelated words, life-related/unrelated words, and negative-valence/neutral words in separate sessions. Participants were scanned using functional magnetic resonance imaging while performing death-relevance, life-relevance, and valence judgments on the words, respectively. The contrast of death-related vs death-unrelated words during death-relevance judgments revealed transient increased activity in the left inferior parietal lobule, the right frontal eye field, and the right superior parietal lobule. The contrast of death-relevance judgments vs life-relevance/valence judgments showed decreased activity in the bilateral insula. The sustained insular activity was correlated with dispositional death anxiety, but only in those with weak transient frontoparietal responses to death-related words. Our results dissociate the transient and sustained neural responses to death-related linguistic cues and suggest that the combination of the transient and sustained neural activities can predict dispositional death anxiety. PMID:22422804

Neural dissociation of food- and money-related reward processing using an abstract incentive delay task.

PubMed

Simon, Joe J; Skunde, Mandy; Wu, Mudan; Schnell, Knut; Herpertz, Sabine C; Bendszus, Martin; Herzog, Wolfgang; Friederich, Hans-Christoph

2015-08-01

Food is an innate reward stimulus related to energy homeostasis and survival, whereas money is considered a more general reward stimulus that gains a rewarding value through learning experiences. Although the underlying neural processing for both modalities of reward has been investigated independently from one another, a more detailed investigation of neural similarities and/or differences between food and monetary reward is still missing. Here, we investigated the neural processing of food compared with monetary-related rewards in 27 healthy, normal-weight women using functional magnetic resonance imaging. We developed a task distinguishing between the anticipation and the receipt of either abstract food or monetary reward. Both tasks activated the ventral striatum during the expectation of a reward. Compared with money, greater food-related activations were observed in prefrontal, parietal and central midline structures during the anticipation and lateral orbitofrontal cortex (lOFC) during the receipt of food reward. Furthermore, during the receipt of food reward, brain activation in the secondary taste cortex was positively related to the body mass index. These results indicate that food-dependent activations encompass to a greater extent brain regions involved in self-control and self-reflection during the anticipation and phylogenetically older parts of the lOFC during the receipt of reward. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Using Expectancy Theory to quantitatively dissociate the neural representation of motivation from its influential factors in the human brain: An fMRI study.

PubMed

Kohli, Akshay; Blitzer, David N; Lefco, Ray W; Barter, Joseph W; Haynes, M Ryan; Colalillo, Sam A; Ly, Martina; Zink, Caroline F

2018-05-08

Researchers have yet to apply a formal operationalized theory of motivation to neurobiology that would more accurately and precisely define neural activity underlying motivation. We overcome this challenge with the novel application of the Expectancy Theory of Motivation to human fMRI to identify brain activity that explicitly reflects motivation. Expectancy Theory quantitatively describes how individual constructs determine motivation by defining motivation force as the product of three variables: expectancy - belief that effort will better performance; instrumentality - belief that successful performance leads to particular outcome, and valence - outcome desirability. Here, we manipulated information conveyed by reward-predicting cues such that relative cue-evoked activity patterns could be statistically mapped to individual Expectancy Theory variables. The variable associated with activity in any voxel is only reported if it replicated between two groups of healthy participants. We found signals in midbrain, ventral striatum, sensorimotor cortex, and visual cortex that specifically map to motivation itself, rather than other factors. This is important because, for the first time, it empirically clarifies approach motivation neural signals during reward anticipation. It also highlights the effectiveness of the application of Expectancy Theory to neurobiology to more precisely and accurately probe motivation neural correlates than has been achievable previously. Copyright © 2018 Elsevier Inc. All rights reserved.

Functional reorganisation in chronic pain and neural correlates of pain sensitisation: A coordinate based meta-analysis of 266 cutaneous pain fMRI studies.

PubMed

Tanasescu, Radu; Cottam, William J; Condon, Laura; Tench, Christopher R; Auer, Dorothee P

2016-09-01

Maladaptive mechanisms of pain processing in chronic pain conditions (CP) are poorly understood. We used coordinate based meta-analysis of 266 fMRI pain studies to study functional brain reorganisation in CP and experimental models of hyperalgesia. The pattern of nociceptive brain activation was similar in CP, hyperalgesia and normalgesia in controls. However, elevated likelihood of activation was detected in the left putamen, left frontal gyrus and right insula in CP comparing stimuli of the most painful vs. other site. Meta-analysis of contrast maps showed no difference between CP, controls, mood conditions. In contrast, experimental hyperalgesia induced stronger activation in the bilateral insula, left cingulate and right frontal gyrus. Activation likelihood maps support a shared neural pain signature of cutaneous nociception in CP and controls. We also present a double dissociation between neural correlates of transient and persistent pain sensitisation with general increased activation intensity but unchanged pattern in experimental hyperalgesia and, by contrast, focally increased activation likelihood, but unchanged intensity, in CP when stimulated at the most painful body part. Copyright © 2016. Published by Elsevier Ltd.

Brain oscillatory substrates of visual short-term memory capacity.

PubMed

Sauseng, Paul; Klimesch, Wolfgang; Heise, Kirstin F; Gruber, Walter R; Holz, Elisa; Karim, Ahmed A; Glennon, Mark; Gerloff, Christian; Birbaumer, Niels; Hummel, Friedhelm C

2009-11-17

The amount of information that can be stored in visual short-term memory is strictly limited to about four items. Therefore, memory capacity relies not only on the successful retention of relevant information but also on efficient suppression of distracting information, visual attention, and executive functions. However, completely separable neural signatures for these memory capacity-limiting factors remain to be identified. Because of its functional diversity, oscillatory brain activity may offer a utile solution. In the present study, we show that capacity-determining mechanisms, namely retention of relevant information and suppression of distracting information, are based on neural substrates independent of each other: the successful maintenance of relevant material in short-term memory is associated with cross-frequency phase synchronization between theta (rhythmical neural activity around 5 Hz) and gamma (> 50 Hz) oscillations at posterior parietal recording sites. On the other hand, electroencephalographic alpha activity (around 10 Hz) predicts memory capacity based on efficient suppression of irrelevant information in short-term memory. Moreover, repetitive transcranial magnetic stimulation at alpha frequency can modulate short-term memory capacity by influencing the ability to suppress distracting information. Taken together, the current study provides evidence for a double dissociation of brain oscillatory correlates of visual short-term memory capacity.

Roman Catholic beliefs produce characteristic neural responses to moral dilemmas

PubMed Central

Flexas, Albert; de Miguel, Pedro; Cela-Conde, Camilo J.; Munar, Enric

2014-01-01

This study provides exploratory evidence about how behavioral and neural responses to standard moral dilemmas are influenced by religious belief. Eleven Catholics and 13 Atheists (all female) judged 48 moral dilemmas. Differential neural activity between the two groups was found in precuneus and in prefrontal, frontal and temporal regions. Furthermore, a double dissociation showed that Catholics recruited different areas for deontological (precuneus; temporoparietal junction) and utilitarian moral judgments [dorsolateral prefrontal cortex (DLPFC); temporal poles], whereas Atheists did not (superior parietal gyrus for both types of judgment). Finally, we tested how both groups responded to personal and impersonal moral dilemmas: Catholics showed enhanced activity in DLPFC and posterior cingulate cortex during utilitarian moral judgments to impersonal moral dilemmas and enhanced responses in anterior cingulate cortex and superior temporal sulcus during deontological moral judgments to personal moral dilemmas. Our results indicate that moral judgment can be influenced by an acquired set of norms and conventions transmitted through religious indoctrination and practice. Catholic individuals may hold enhanced awareness of the incommensurability between two unequivocal doctrines of the Catholic belief set, triggered explicitly in a moral dilemma: help and care in all circumstances—but thou shalt not kill. PMID:23160812

Neural correlates of novelty and appropriateness processing in externally induced constraint relaxation.

PubMed

Huang, Furong; Tang, Shuang; Sun, Pei; Luo, Jing

2018-05-15

Novelty and appropriateness are considered the two fundamental features of creative thinking, including insight problem solving, which can be performed through chunk decomposition and constraint relaxation. Based on a previous study that separated the neural bases of novelty and appropriateness in chunk decomposition, in this study, we used event-related functional magnetic resonance imaging (fMRI) to further dissociate these mechanisms in constraint relaxation. Participants were guided to mentally represent the method of problem solving according to the externally provided solutions that were elaborately prepared in advance and systematically varied in their novelty and appropriateness for the given problem situation. The results showed that novelty processing was completed by the temporoparietal junction (TPJ) and regions in the executive system (dorsolateral prefrontal cortex [DLPFC]), whereas appropriateness processing was completed by the TPJ and regions in the episodic memory (hippocampus), emotion (amygdala), and reward systems (orbitofrontal cortex [OFC]). These results likely indicate that appropriateness processing can result in a more memorable and richer experience than novelty processing in constraint relaxation. The shared and distinct neural mechanisms of the features of novelty and appropriateness in constraint relaxation are discussed, enriching the representation of the change theory of insight. Copyright © 2018 Elsevier Inc. All rights reserved.

Altered brain response for semantic knowledge in Alzheimer's disease.

PubMed

Wierenga, Christina E; Stricker, Nikki H; McCauley, Ashley; Simmons, Alan; Jak, Amy J; Chang, Yu-Ling; Nation, Daniel A; Bangen, Katherine J; Salmon, David P; Bondi, Mark W

2011-02-01

Word retrieval deficits are common in Alzheimer's disease (AD) and are thought to reflect a degradation of semantic memory. Yet, the nature of semantic deterioration in AD and the underlying neural correlates of these semantic memory changes remain largely unknown. We examined the semantic memory impairment in AD by investigating the neural correlates of category knowledge (e.g., living vs. nonliving) and featural processing (global vs. local visual information). During event-related fMRI, 10 adults diagnosed with mild AD and 22 cognitively normal (CN) older adults named aloud items from three categories for which processing of specific visual features has previously been dissociated from categorical features. Results showed widespread group differences in the categorical representation of semantic knowledge in several language-related brain areas. For example, the right inferior frontal gyrus showed selective brain response for nonliving items in the CN group but living items in the AD group. Additionally, the AD group showed increased brain response for word retrieval irrespective of category in Broca's homologue in the right hemisphere and rostral cingulate cortex bilaterally, which suggests greater recruitment of frontally mediated neural compensatory mechanisms in the face of semantic alteration. Copyright © 2010 Elsevier Ltd. All rights reserved.

Roman Catholic beliefs produce characteristic neural responses to moral dilemmas.

PubMed

Christensen, Julia F; Flexas, Albert; de Miguel, Pedro; Cela-Conde, Camilo J; Munar, Enric

2014-02-01

This study provides exploratory evidence about how behavioral and neural responses to standard moral dilemmas are influenced by religious belief. Eleven Catholics and 13 Atheists (all female) judged 48 moral dilemmas. Differential neural activity between the two groups was found in precuneus and in prefrontal, frontal and temporal regions. Furthermore, a double dissociation showed that Catholics recruited different areas for deontological (precuneus; temporoparietal junction) and utilitarian moral judgments [dorsolateral prefrontal cortex (DLPFC); temporal poles], whereas Atheists did not (superior parietal gyrus for both types of judgment). Finally, we tested how both groups responded to personal and impersonal moral dilemmas: Catholics showed enhanced activity in DLPFC and posterior cingulate cortex during utilitarian moral judgments to impersonal moral dilemmas and enhanced responses in anterior cingulate cortex and superior temporal sulcus during deontological moral judgments to personal moral dilemmas. Our results indicate that moral judgment can be influenced by an acquired set of norms and conventions transmitted through religious indoctrination and practice. Catholic individuals may hold enhanced awareness of the incommensurability between two unequivocal doctrines of the Catholic belief set, triggered explicitly in a moral dilemma: help and care in all circumstances-but thou shalt not kill.

Cultured Cortical Neurons Can Perform Blind Source Separation According to the Free-Energy Principle

PubMed Central

Isomura, Takuya; Kotani, Kiyoshi; Jimbo, Yasuhiko

2015-01-01

Blind source separation is the computation underlying the cocktail party effect––a partygoer can distinguish a particular talker’s voice from the ambient noise. Early studies indicated that the brain might use blind source separation as a signal processing strategy for sensory perception and numerous mathematical models have been proposed; however, it remains unclear how the neural networks extract particular sources from a complex mixture of inputs. We discovered that neurons in cultures of dissociated rat cortical cells could learn to represent particular sources while filtering out other signals. Specifically, the distinct classes of neurons in the culture learned to respond to the distinct sources after repeating training stimulation. Moreover, the neural network structures changed to reduce free energy, as predicted by the free-energy principle, a candidate unified theory of learning and memory, and by Jaynes’ principle of maximum entropy. This implicit learning can only be explained by some form of Hebbian plasticity. These results are the first in vitro (as opposed to in silico) demonstration of neural networks performing blind source separation, and the first formal demonstration of neuronal self-organization under the free energy principle. PMID:26690814

Adaptive Neural Network Based Control of Noncanonical Nonlinear Systems.

PubMed

Zhang, Yanjun; Tao, Gang; Chen, Mou

2016-09-01

This paper presents a new study on the adaptive neural network-based control of a class of noncanonical nonlinear systems with large parametric uncertainties. Unlike commonly studied canonical form nonlinear systems whose neural network approximation system models have explicit relative degree structures, which can directly be used to derive parameterized controllers for adaptation, noncanonical form nonlinear systems usually do not have explicit relative degrees, and thus their approximation system models are also in noncanonical forms. It is well-known that the adaptive control of noncanonical form nonlinear systems involves the parameterization of system dynamics. As demonstrated in this paper, it is also the case for noncanonical neural network approximation system models. Effective control of such systems is an open research problem, especially in the presence of uncertain parameters. This paper shows that it is necessary to reparameterize such neural network system models for adaptive control design, and that such reparameterization can be realized using a relative degree formulation, a concept yet to be studied for general neural network system models. This paper then derives the parameterized controllers that guarantee closed-loop stability and asymptotic output tracking for noncanonical form neural network system models. An illustrative example is presented with the simulation results to demonstrate the control design procedure, and to verify the effectiveness of such a new design method.

Sensory cortical response to uncertainty and low salience during recognition of affective cues in musical intervals.

PubMed

Bravo, Fernando; Cross, Ian; Stamatakis, Emmanuel Andreas; Rohrmeier, Martin

2017-01-01

Previous neuroimaging studies have shown an increased sensory cortical response (i.e., heightened weight on sensory evidence) under higher levels of predictive uncertainty. The signal enhancement theory proposes that attention improves the quality of the stimulus representation, and therefore reduces uncertainty by increasing the gain of the sensory signal. The present study employed functional magnetic resonance imaging (fMRI) to investigate the neural correlates for ambiguous valence inferences signaled by auditory information within an emotion recognition paradigm. Participants categorized sound stimuli of three distinct levels of consonance/dissonance controlled by interval content. Separate behavioural and neuroscientific experiments were conducted. Behavioural results revealed that, compared with the consonance condition (perfect fourths, fifths and octaves) and the strong dissonance condition (minor/major seconds and tritones), the intermediate dissonance condition (minor thirds) was the most ambiguous, least salient and more cognitively demanding category (slowest reaction times). The neuroscientific findings were consistent with a heightened weight on sensory evidence whilst participants were evaluating intermediate dissonances, which was reflected in an increased neural response of the right Heschl's gyrus. The results support previous studies that have observed enhanced precision of sensory evidence whilst participants attempted to represent and respond to higher degrees of uncertainty, and converge with evidence showing preferential processing of complex spectral information in the right primary auditory cortex. These findings are discussed with respect to music-theoretical concepts and recent Bayesian models of perception, which have proposed that attention may heighten the weight of information coming from sensory channels to stimulate learning about unknown predictive relationships.

Sensory cortical response to uncertainty and low salience during recognition of affective cues in musical intervals

PubMed Central

Cross, Ian; Stamatakis, Emmanuel Andreas; Rohrmeier, Martin

2017-01-01

Previous neuroimaging studies have shown an increased sensory cortical response (i.e., heightened weight on sensory evidence) under higher levels of predictive uncertainty. The signal enhancement theory proposes that attention improves the quality of the stimulus representation, and therefore reduces uncertainty by increasing the gain of the sensory signal. The present study employed functional magnetic resonance imaging (fMRI) to investigate the neural correlates for ambiguous valence inferences signaled by auditory information within an emotion recognition paradigm. Participants categorized sound stimuli of three distinct levels of consonance/dissonance controlled by interval content. Separate behavioural and neuroscientific experiments were conducted. Behavioural results revealed that, compared with the consonance condition (perfect fourths, fifths and octaves) and the strong dissonance condition (minor/major seconds and tritones), the intermediate dissonance condition (minor thirds) was the most ambiguous, least salient and more cognitively demanding category (slowest reaction times). The neuroscientific findings were consistent with a heightened weight on sensory evidence whilst participants were evaluating intermediate dissonances, which was reflected in an increased neural response of the right Heschl’s gyrus. The results support previous studies that have observed enhanced precision of sensory evidence whilst participants attempted to represent and respond to higher degrees of uncertainty, and converge with evidence showing preferential processing of complex spectral information in the right primary auditory cortex. These findings are discussed with respect to music-theoretical concepts and recent Bayesian models of perception, which have proposed that attention may heighten the weight of information coming from sensory channels to stimulate learning about unknown predictive relationships. PMID:28422990

Uncertainty increases neural indices of attention in obsessive-compulsive disorder.

PubMed

Dieterich, Raoul; Endrass, Tanja; Kathmann, Norbert

2017-11-01

Patients with obsessive-compulsive disorder (OCD) experience abnormally high levels of uncertainty, and unpredictability is evaluated negatively and not well tolerated. The current study examined neural correlates of attentional processing in response to experimentally induced uncertainty in OCD. Twenty-four OCD patients and 24 healthy controls performed a task where neutral and negative pictures were preceded by a cue, either being predictive (certain condition) or nonpredictive (uncertain condition) of subsequent picture valence. We examined prepicture anticipatory attention through α (∼8-12 Hz) suppression, and attentional allocation during picture presentation with the P1, N1, P2, N2, and late positive potential (LPP) of the event-related potential. Additionally, we tested how clinical measures related to these attentional markers. Subjectively, patients overestimated the frequency of negative pictures after nonpredictive cues. Patients, but not controls, showed upper α(10-12 Hz) suppression after nonpredictive and predictive negative cues relative to predictive neutral cues. Only patients showed increased P2 and decreased N2 amplitudes for pictures after nonpredictive cues, and, whereas both groups showed increased LPP amplitudes for pictures after nonpredictive cues, this modulation was more pronounced in OCD during the early LPP (<1,000 ms). In patients, P2 and LPP amplitudes for negative pictures were associated positively with anxiety and negatively with depression. These results suggest that OCD patients process anticipation of inevitable and potential threat similarly and highlight the substantial motivational impact of uncertain events to OCD patients. Finally, the correlation with anxiety implies that anxiety represents the source of hypervigilance during uncertainty resolution. © 2017 Wiley Periodicals, Inc.

Recursive Bayesian recurrent neural networks for time-series modeling.

PubMed

Mirikitani, Derrick T; Nikolaev, Nikolay

2010-02-01

This paper develops a probabilistic approach to recursive second-order training of recurrent neural networks (RNNs) for improved time-series modeling. A general recursive Bayesian Levenberg-Marquardt algorithm is derived to sequentially update the weights and the covariance (Hessian) matrix. The main strengths of the approach are a principled handling of the regularization hyperparameters that leads to better generalization, and stable numerical performance. The framework involves the adaptation of a noise hyperparameter and local weight prior hyperparameters, which represent the noise in the data and the uncertainties in the model parameters. Experimental investigations using artificial and real-world data sets show that RNNs equipped with the proposed approach outperform standard real-time recurrent learning and extended Kalman training algorithms for recurrent networks, as well as other contemporary nonlinear neural models, on time-series modeling.

Neural network robust tracking control with adaptive critic framework for uncertain nonlinear systems.

PubMed

Wang, Ding; Liu, Derong; Zhang, Yun; Li, Hongyi

2018-01-01

In this paper, we aim to tackle the neural robust tracking control problem for a class of nonlinear systems using the adaptive critic technique. The main contribution is that a neural-network-based robust tracking control scheme is established for nonlinear systems involving matched uncertainties. The augmented system considering the tracking error and the reference trajectory is formulated and then addressed under adaptive critic optimal control formulation, where the initial stabilizing controller is not needed. The approximate control law is derived via solving the Hamilton-Jacobi-Bellman equation related to the nominal augmented system, followed by closed-loop stability analysis. The robust tracking control performance is guaranteed theoretically via Lyapunov approach and also verified through simulation illustration. Copyright © 2017 Elsevier Ltd. All rights reserved.

Sleep deprivation alters choice strategy without altering uncertainty or loss aversion preferences

PubMed Central

Mullette-Gillman, O'Dhaniel A.; Kurnianingsih, Yoanna A.; Liu, Jean C. J.

2015-01-01

Sleep deprivation alters decision making; however, it is unclear what specific cognitive processes are modified to drive altered choices. In this manuscript, we examined how one night of total sleep deprivation (TSD) alters economic decision making. We specifically examined changes in uncertainty preferences dissociably from changes in the strategy with which participants engage with presented choice information. With high test-retest reliability, we show that TSD does not alter uncertainty preferences or loss aversion. Rather, TSD alters the information the participants rely upon to make their choices. Utilizing a choice strategy metric which contrasts the influence of maximizing and satisficing information on choice behavior, we find that TSD alters the relative reliance on maximizing information and satisficing information, in the gains domain. This alteration is the result of participants both decreasing their reliance on cognitively-complex maximizing information and a concomitant increase in the use of readily-available satisficing information. TSD did not result in a decrease in overall information use in either domain. These results show that sleep deprivation alters decision making by altering the informational strategies that participants employ, without altering their preferences. PMID:26500479

Determination of the amount of gas adsorption on SiO2/Si(100) surfaces to realize precise mass measurement

NASA Astrophysics Data System (ADS)

Mizushima, S.

2004-06-01

The adsorption isotherms on SiO2/Si(100) surfaces were measured using a vacuum mass comparator. Samples with a surface area difference of 816.6 cm2 were used for the measurement, and a substitution weighing method was adopted to reduce the uncertainty due to the drift and non-linearity of the indication of the mass comparator. We measured adsorption isotherms of water vapour on the SiO2/Si(100) surfaces outgassed at a temperature of 500 °C and found that dissociative adsorption caused an irreversible increase of 0.028 µg cm-2 with an uncertainty of 0.004 µg cm-2 (k = 1). We also found that the physical adsorption of water molecules on hydroxylated surfaces had a monolayer capacity of 0.004 µg cm-2 with an uncertainty of 0.002 µg cm-2 (k = 1). In addition, the adsorption isotherms for ethanol vapour and n-octane vapour, which were different from water vapour in adsorption properties, were measured and analysed.

Neural Imaging Using Single-Photon Avalanche Diodes

PubMed Central

Karami, Mohammad Azim; Ansarian, Misagh

2017-01-01

Introduction: This paper analyses the ability of single-photon avalanche diodes (SPADs) for neural imaging. The current trend in the production of SPADs moves toward the minimum dark count rate (DCR) and maximum photon detection probability (PDP). Moreover, the jitter response which is the main measurement characteristic for the timing uncertainty is progressing. Methods: The neural imaging process using SPADs can be performed by means of florescence lifetime imaging (FLIM), time correlated single-photon counting (TCSPC), positron emission tomography (PET), and single-photon emission computed tomography (SPECT). Results: This trend will result in more precise neural imaging cameras. While achieving low DCR SPADs is difficult in deep submicron technologies because of using higher doping profiles, higher PDPs are reported in green and blue part of light. Furthermore, the number of pixels integrated in the same chip is increasing with the technology progress which can result in the higher resolution of imaging. Conclusion: This study proposes implemented SPADs in Deep-submicron technologies to be used in neural imaging cameras, due to the small size pixels and higher timing accuracies. PMID:28446946

Neural network analysis of Charpy transition temperature of irradiated low-activation martensitic steels

NASA Astrophysics Data System (ADS)

Cottrell, G. A.; Kemp, R.; Bhadeshia, H. K. D. H.; Odette, G. R.; Yamamoto, T.

2007-08-01

We have constructed a Bayesian neural network model that predicts the change, due to neutron irradiation, of the Charpy ductile-brittle transition temperature (ΔDBTT) of low-activation martensitic steels given a set of multi-dimensional published data with doses <100 displacements per atom (dpa). Results show the high significance of irradiation temperature and (dpa) 1/2 in determining ΔDBTT. Sparse data regions were identified by the size of the modelling uncertainties, indicating areas where further experimental data are needed. The method has promise for selecting and ranking experiments on future irradiation materials test facilities.

INDIRECT INTELLIGENT SLIDING MODE CONTROL OF A SHAPE MEMORY ALLOY ACTUATED FLEXIBLE BEAM USING HYSTERETIC RECURRENT NEURAL NETWORKS.

PubMed

Hannen, Jennifer C; Crews, John H; Buckner, Gregory D

2012-08-01

This paper introduces an indirect intelligent sliding mode controller (IISMC) for shape memory alloy (SMA) actuators, specifically a flexible beam deflected by a single offset SMA tendon. The controller manipulates applied voltage, which alters SMA tendon temperature to track reference bending angles. A hysteretic recurrent neural network (HRNN) captures the nonlinear, hysteretic relationship between SMA temperature and bending angle. The variable structure control strategy provides robustness to model uncertainties and parameter variations, while effectively compensating for system nonlinearities, achieving superior tracking compared to an optimized PI controller.

Dissociative Photoionization of the Elusive Vinoxy Radical.

PubMed

Adams, Jonathan D; Scrape, Preston G; Lee, Shih-Huang; Butler, Laurie J

2017-08-24

These experiments report the dissociative photoionization of vinoxy radicals to m/z = 15 and 29. In a crossed laser-molecular beam scattering apparatus, we induce C-Cl bond fission in 2-chloroacetaldehyde by photoexcitation at 157 nm. Our velocity measurements, combined with conservation of angular momentum, show that 21% of the C-Cl photofission events form vinoxy radicals that are stable to subsequent dissociation to CH 3 + CO or H + ketene. Photoionization of these stable vinoxy radicals, identified by their velocities, which are momentum-matched with the higher-kinetic-energy Cl atom photofragments, shows that the vinoxy radicals dissociatively photoionize to give signal at m/z = 15 and 29. We calibrated the partial photoionization cross section of vinoxy to CH 3 + relative to the bandwidth-averaged photoionization cross section of the Cl atom at 13.68 eV to put the partial photoionization cross sections on an absolute scale. The resulting bandwidth-averaged partial cross sections are 0.63 and 1.3 Mb at 10.5 and 11.44 eV, respectively. These values are consistent with the upper limit to the cross section estimated from a study by Savee et al. on the O( 3 P) + propene bimolecular reaction. We note that the uncertainty in these values is primarily dependent on the signal attributed to C-Cl primary photofission in the m/z = 35 (Cl + ) time-of-flight data. While the value is a rough estimate, the bandwidth-averaged partial photoionization cross section of vinoxy to HCO + calculated from the signal at m/z = 29 at 11.53 eV is approximately half that of vinoxy to CH 3 + . We also present critical points on the potential energy surface of the vinoxy cation calculated at the G4//B3LYP/6-311++G(3df,2p) level of theory to support the observation of dissociative ionization of vinoxy to both CH 3 + and HCO + .

A Monte Carlo Sensitivity Analysis of CF2 and CF Radical Densities in a c-C4F8 Plasma

NASA Technical Reports Server (NTRS)

Bose, Deepak; Rauf, Shahid; Hash, D. B.; Govindan, T. R.; Meyyappan, M.

2004-01-01

A Monte Carlo sensitivity analysis is used to build a plasma chemistry model for octacyclofluorobutane (c-C4F8) which is commonly used in dielectric etch. Experimental data are used both quantitatively and quantitatively to analyze the gas phase and gas surface reactions for neutral radical chemistry. The sensitivity data of the resulting model identifies a few critical gas phase and surface aided reactions that account for most of the uncertainty in the CF2 and CF radical densities. Electron impact dissociation of small radicals (CF2 and CF) and their surface recombination reactions are found to be the rate-limiting steps in the neutral radical chemistry. The relative rates for these electron impact dissociation and surface recombination reactions are also suggested. The resulting mechanism is able to explain the measurements of CF2 and CF densities available in the literature and also their hollow spatial density profiles.

A Measurement of the proton-proton inelastic scattering cross-section at center off mass energy = 7 TeV with the ATLAS detector at the LHC

NASA Astrophysics Data System (ADS)

Tompkins, Lauren Alexandra

The first measurement of the inelastic cross-section for proton-proton collisions at a center of mass energy of 7 TeV using the ATLAS detector at the Large Hadron Collider is presented. From a dataset corresponding to an integrated luminosity of 20 inverse microbarns, events are selected by requiring activity in scintillation counters mounted in the forward region of the ATLAS detector. An inelastic cross-section of 60.1 +/- 2.1 millibarns is measured for the subset of events visible to the scintillation counters. The uncertainty includes the statistical and systematic uncertainty on the measurement. The visible events satisfy xi > 5 x 10 -6, where xi=MX 2/s is calculated from the invariant mass, MX, of hadrons selected using the largest rapidity gap in the event. For diffractive events this corresponds to requiring at least one of the dissociation masses to be larger than 15.7~GeV. Using an extrapolation dependent on the model for the differential diffractive mass distribution, an inelastic cross-section of 69.1 +/- 2.4 (exp) +/- 6.9 (extr) millibarns is determined, where (exp) indicates the experimental uncertainties and (extr) indicates the uncertainty due to the extrapolation from the limited xi-range to the full inelastic cross-section.

Connectivity in the human brain dissociates entropy and complexity of auditory inputs☆

PubMed Central

Nastase, Samuel A.; Iacovella, Vittorio; Davis, Ben; Hasson, Uri

2015-01-01

Complex systems are described according to two central dimensions: (a) the randomness of their output, quantified via entropy; and (b) their complexity, which reflects the organization of a system's generators. Whereas some approaches hold that complexity can be reduced to uncertainty or entropy, an axiom of complexity science is that signals with very high or very low entropy are generated by relatively non-complex systems, while complex systems typically generate outputs with entropy peaking between these two extremes. In understanding their environment, individuals would benefit from coding for both input entropy and complexity; entropy indexes uncertainty and can inform probabilistic coding strategies, whereas complexity reflects a concise and abstract representation of the underlying environmental configuration, which can serve independent purposes, e.g., as a template for generalization and rapid comparisons between environments. Using functional neuroimaging, we demonstrate that, in response to passively processed auditory inputs, functional integration patterns in the human brain track both the entropy and complexity of the auditory signal. Connectivity between several brain regions scaled monotonically with input entropy, suggesting sensitivity to uncertainty, whereas connectivity between other regions tracked entropy in a convex manner consistent with sensitivity to input complexity. These findings suggest that the human brain simultaneously tracks the uncertainty of sensory data and effectively models their environmental generators. PMID:25536493

Neural control of magnetic suspension systems

NASA Technical Reports Server (NTRS)

Gray, W. Steven

1993-01-01

The purpose of this research program is to design, build and test (in cooperation with NASA personnel from the NASA Langley Research Center) neural controllers for two different small air-gap magnetic suspension systems. The general objective of the program is to study neural network architectures for the purpose of control in an experimental setting and to demonstrate the feasibility of the concept. The specific objectives of the research program are: (1) to demonstrate through simulation and experimentation the feasibility of using neural controllers to stabilize a nonlinear magnetic suspension system; (2) to investigate through simulation and experimentation the performance of neural controllers designs under various types of parametric and nonparametric uncertainty; (3) to investigate through simulation and experimentation various types of neural architectures for real-time control with respect to performance and complexity; and (4) to benchmark in an experimental setting the performance of neural controllers against other types of existing linear and nonlinear compensator designs. To date, the first one-dimensional, small air-gap magnetic suspension system has been built, tested and delivered to the NASA Langley Research Center. The device is currently being stabilized with a digital linear phase-lead controller. The neural controller hardware is under construction. Two different neural network paradigms are under consideration, one based on hidden layer feedforward networks trained via back propagation and one based on using Gaussian radial basis functions trained by analytical methods related to stability conditions. Some advanced nonlinear control algorithms using feedback linearization and sliding mode control are in simulation studies.

Searching for Cross-diagnostic Convergence: Neural Mechanisms Governing Excitation and Inhibition Balance in Schizophrenia and Autism Spectrum Disorders

PubMed Central

Foss-Feig, Jennifer H.; Adkinson, Brendan D.; Ji, Jie Lisa; Yang, Genevieve; Srihari, Vinod H.; McPartland, James C.; Krystal, John H.; Murray, John D.; Anticevic, Alan

2017-01-01

Recent theoretical accounts have proposed excitation (E) and inhibition (I) imbalance as a possible mechanistic, network-level hypothesis underlying neural and behavioral dysfunction across neurodevelopmental disorders, particularly autism spectrum disorder (ASD) and schizophrenia (SCZ). These two disorders share some overlap in their clinical presentation as well as convergence in their underlying genes and neurobiology. However, there are also clear points of dissociation in terms of phenotypes and putatively affected neural circuitry. Here we highlight emerging work from the clinical neuroscience literature examining neural correlates of E/I imbalance across children and adults with ASD and adults with both chronic and early-course SCZ. We discuss findings from diverse neuroimaging studies across distinct modalities, conducted with EEG, MEG, 1H-MRS, and fMRI, including effects observed both during task and at rest. Throughout this review we discuss points of convergence and divergence in the ASD and SCZ literature, with a focus on disruptions in neural E/I balance. We also consider these findings in relation to predictions generated by theoretical neuroscience, particularly computational models predicting E/I imbalance across disorders. Finally, we discuss how human non-invasive neuroimaging can benefit from pharmacological challenge studies to reveal mechanisms in ASD and SCZ. Collectively, we attempt to shed light on shared and divergent neuroimaging effects across disorders with the goal of informing future research examining the mechanisms underlying the E/I imbalance hypothesis across neurodevelopmental disorders. We posit that such translational efforts are vital to facilitate development of neurobiologically informed treatment strategies across neuropsychiatric conditions. PMID:28434615

Distinct Neural Activity Associated with Focused-Attention Meditation and Loving-Kindness Meditation

PubMed Central

Lee, Tatia M. C.; Leung, Mei-Kei; Hou, Wai-Kai; Tang, Joey C. Y.; Yin, Jing; So, Kwok-Fai; Lee, Chack-Fan; Chan, Chetwyn C. H.

2012-01-01

This study examined the dissociable neural effects of ānāpānasati (focused-attention meditation, FAM) and mettā (loving-kindness meditation, LKM) on BOLD signals during cognitive (continuous performance test, CPT) and affective (emotion-processing task, EPT, in which participants viewed affective pictures) processing. Twenty-two male Chinese expert meditators (11 FAM experts, 11 LKM experts) and 22 male Chinese novice meditators (11 FAM novices, 11 LKM novices) had their brain activity monitored by a 3T MRI scanner while performing the cognitive and affective tasks in both meditation and baseline states. We examined the interaction between state (meditation vs. baseline) and expertise (expert vs. novice) separately during LKM and FAM, using a conjunction approach to reveal common regions sensitive to the expert meditative state. Additionally, exclusive masking techniques revealed distinct interactions between state and group during LKM and FAM. Specifically, we demonstrated that the practice of FAM was associated with expertise-related behavioral improvements and neural activation differences in attention task performance. However, the effect of state LKM meditation did not carry over to attention task performance. On the other hand, both FAM and LKM practice appeared to affect the neural responses to affective pictures. For viewing sad faces, the regions activated for FAM practitioners were consistent with attention-related processing; whereas responses of LKM experts to sad pictures were more in line with differentiating emotional contagion from compassion/emotional regulation processes. Our findings provide the first report of distinct neural activity associated with forms of meditation during sustained attention and emotion processing. PMID:22905090

Shindigs, brunches, and rodeos: the neural basis of event words.

PubMed

Bedny, Marina; Dravida, Swethasri; Saxe, Rebecca

2014-09-01

Events (e.g., "running" or "eating") constitute a basic type within human cognition and human language. We asked whether thinking about events, as compared to other conceptual categories, depends on partially independent neural circuits. Indirect evidence for this hypothesis comes from previous studies showing elevated posterior temporal responses to verbs, which typically label events. Neural responses to verbs could, however, be driven either by their grammatical or by their semantic properties. In the present experiment, we separated the effects of grammatical class (verb vs. noun) and semantic category (event vs. object) by measuring neural responses to event nouns (e.g., "the hurricane"). Participants rated the semantic relatedness of event nouns, as well as of two categories of object nouns-animals (e.g., "the alligator") and plants (e.g., "the acorn")-and three categories of verbs-manner of motion (e.g., "to roll"), emission (e.g., "to sparkle"), and perception (e.g., "to gaze"). As has previously been observed, we found larger responses to verbs than to object nouns in the left posterior middle (LMTG) and superior (LSTG) temporal gyri. Crucially, we also found that the LMTG responds more to event than to object nouns. These data suggest that part of the posterior lateral temporal response to verbs is driven by their semantic properties. By contrast, a more superior region, at the junction of the temporal and parietal cortices, responded more to verbs than to all nouns, irrespective of their semantic category. We concluded that the neural mechanisms engaged when thinking about event and object categories are partially dissociable.

Disruption of Boundary Encoding During Sensorimotor Sequence Learning: An MEG Study.

PubMed

Michail, Georgios; Nikulin, Vadim V; Curio, Gabriel; Maess, Burkhard; Herrojo Ruiz, María

2018-01-01

Music performance relies on the ability to learn and execute actions and their associated sounds. The process of learning these auditory-motor contingencies depends on the proper encoding of the serial order of the actions and sounds. Among the different serial positions of a behavioral sequence, the first and last (boundary) elements are particularly relevant. Animal and patient studies have demonstrated a specific neural representation for boundary elements in prefrontal cortical regions and in the basal ganglia, highlighting the relevance of their proper encoding. The neural mechanisms underlying the encoding of sequence boundaries in the general human population remain, however, largely unknown. In this study, we examined how alterations of auditory feedback, introduced at different ordinal positions (boundary or within-sequence element), affect the neural and behavioral responses during sensorimotor sequence learning. Analysing the neuromagnetic signals from 20 participants while they performed short piano sequences under the occasional effect of altered feedback (AF), we found that at around 150-200 ms post-keystroke, the neural activities in the dorsolateral prefrontal cortex (DLPFC) and supplementary motor area (SMA) were dissociated for boundary and within-sequence elements. Furthermore, the behavioral data demonstrated that feedback alterations on boundaries led to greater performance costs, such as more errors in the subsequent keystrokes. These findings jointly support the idea that the proper encoding of boundaries is critical in acquiring sensorimotor sequences. They also provide evidence for the involvement of a distinct neural circuitry in humans including prefrontal and higher-order motor areas during the encoding of the different classes of serial order.

Dissociable Neural Mechanisms Underlying the Modulation of Pain and Anxiety? An fMRI Pilot Study

PubMed Central

Moseley, Graham Lorimer; Berna, Chantal; Ploner, Markus; Tracey, Irene

2014-01-01

The down-regulation of pain through beliefs is commonly discussed as a form of emotion regulation. In line with this interpretation, the analgesic effect has been shown to co-occur with reduced anxiety and increased activity in the ventrolateral prefrontal cortex (VLPFC), which is a key region of emotion regulation. This link between pain and anxiety modulation raises the question whether the two effects are rooted in the same neural mechanism. In this pilot fMRI study, we compared the neural basis of the analgesic and anxiolytic effect of two types of threat modulation: a “behavioral control” paradigm, which involves the ability to terminate a noxious stimulus, and a “safety signaling” paradigm, which involves visual cues that signal the threat (or absence of threat) that a subsequent noxious stimulus might be of unusually high intensity. Analgesia was paralleled by VLPFC activity during behavioral control. Safety signaling engaged elements of the descending pain control system, including the rostral anterior cingulate cortex that showed increased functional connectivity with the periaqueductal gray and VLPFC. Anxiety reduction, in contrast, scaled with dorsolateral prefrontal cortex activation during behavioral control but had no distinct neural signature during safety signaling. Our pilot data therefore suggest that analgesic and anxiolytic effects are instantiated in distinguishable neural mechanisms and differ between distinct stress- and pain-modulatory approaches, supporting the recent notion of multiple pathways subserving top-down modulation of the pain experience. Additional studies in larger cohorts are needed to follow up on these preliminary findings. PMID:25502237

Two takes on the social brain: a comparison of theory of mind tasks.

PubMed

Gobbini, Maria Ida; Koralek, Aaron C; Bryan, Ronald E; Montgomery, Kimberly J; Haxby, James V

2007-11-01

We compared two tasks that are widely used in research on mentalizing--false belief stories and animations of rigid geometric shapes that depict social interactions--to investigate whether the neural systems that mediate the representation of others' mental states are consistent across these tasks. Whereas false belief stories activated primarily the anterior paracingulate cortex (APC), the posterior cingulate cortex/precuneus (PCC/PC), and the temporo-parietal junction (TPJ)--components of the distributed neural system for theory of mind (ToM)--the social animations activated an extensive region along nearly the full extent of the superior temporal sulcus, including a locus in the posterior superior temporal sulcus (pSTS), as well as the frontal operculum and inferior parietal lobule (IPL)--components of the distributed neural system for action understanding--and the fusiform gyrus. These results suggest that the representation of covert mental states that may predict behavior and the representation of intentions that are implied by perceived actions involve distinct neural systems. These results show that the TPJ and the pSTS play dissociable roles in mentalizing and are parts of different distributed neural systems. Because the social animations do not depict articulated body movements, these results also highlight that the perception of the kinematics of actions is not necessary to activate the mirror neuron system, suggesting that this system plays a general role in the representation of intentions and goals of actions. Furthermore, these results suggest that the fusiform gyrus plays a general role in the representation of visual stimuli that signify agency, independent of visual form.

Attention Alters Neural Responses to Evocative Faces in Behaviorally Inhibited Adolescents

PubMed Central

Pérez-Edgar, Koraly; Roberson-Nay, Roxann; Hardin, Michael G.; Poeth, Kaitlin; Guyer, Amanda E.; Nelson, Eric E.; McClure, Erin B.; Henderson, Heather A.; Fox, Nathan A.; Pine, Daniel S.; Ernst, Monique

2007-01-01

Behavioral inhibition (BI) is a risk factor for anxiety disorders. While the two constructs bear behavioral similarities, previous work has not extended these parallels to the neural level. This study examined amygdala reactivity during a task previously used with clinically anxious adolescents. Adolescents were selected for enduring patterns of BI or non-inhibition (BN). We examined amygdala response to evocative emotion faces in BI (N=10, mean 12.8 years) and BN (N=17, mean 12.5 years) adolescents while systematically manipulating attention. Analyses focused on amygdala response during subjective ratings of internal fear (constrained attention) and passive viewing (unconstrained attention) during the presentation of emotion faces (Happy, Angry, Fearful, and Neutral). BI adolescents, relative to BN adolescents, showed exaggerated amygdala response during subjective fear ratings and deactivation during passive viewing, across all emotion faces. In addition, the BI group showed an abnormally high amygdala response to a task condition marked by novelty and uncertainty (i.e., rating fear state to a Happy face). Perturbations in amygdala function are evident in adolescents temperamentally at risk for anxiety. Attention state alters the underlying pattern of neural processing, potentially mediating the observed behavioral patterns across development. BI adolescents also show a heightened sensitivity to novelty and uncertainty, which has been linked to anxiety. These patterns of reactivity may help sustain early temperamental biases over time and contribute to the observed relation between BI and anxiety. PMID:17376704

Planar imaging of OH density distributions in a supersonic combustion tunnel

NASA Technical Reports Server (NTRS)

Quagliaroli, T. M.; Laufer, G.; Krauss, R. H.; Mcdaniel, J. C., Jr.

1993-01-01

Images of absolute OH number density were obtained using planar laser-induced fluorescence (PLIF) in a supersonic H2-air combustion tunnel. A tunable KrF excimer laser was used to excite the Q2(11) ro-vibronic line. Calibration of the PLIF images was obtained by referencing the signal measured in the flame to that obtained by the excitation of OH produced by thermal dissociation of H2O in an atmospheric furnace. Measurement errors due to uncertainty in internal furnace atmospheric conditions and image temperature correction are estimated.

Indirect adaptive fuzzy wavelet neural network with self- recurrent consequent part for AC servo system.

PubMed

Hou, Runmin; Wang, Li; Gao, Qiang; Hou, Yuanglong; Wang, Chao

2017-09-01

This paper proposes a novel indirect adaptive fuzzy wavelet neural network (IAFWNN) to control the nonlinearity, wide variations in loads, time-variation and uncertain disturbance of the ac servo system. In the proposed approach, the self-recurrent wavelet neural network (SRWNN) is employed to construct an adaptive self-recurrent consequent part for each fuzzy rule of TSK fuzzy model. For the IAFWNN controller, the online learning algorithm is based on back propagation (BP) algorithm. Moreover, an improved particle swarm optimization (IPSO) is used to adapt the learning rate. The aid of an adaptive SRWNN identifier offers the real-time gradient information to the adaptive fuzzy wavelet neural controller to overcome the impact of parameter variations, load disturbances and other uncertainties effectively, and has a good dynamic. The asymptotical stability of the system is guaranteed by using the Lyapunov method. The result of the simulation and the prototype test prove that the proposed are effective and suitable. Copyright © 2017. Published by Elsevier Ltd.

Online Recorded Data-Based Composite Neural Control of Strict-Feedback Systems With Application to Hypersonic Flight Dynamics.

PubMed

Xu, Bin; Yang, Daipeng; Shi, Zhongke; Pan, Yongping; Chen, Badong; Sun, Fuchun

2017-09-25

This paper investigates the online recorded data-based composite neural control of uncertain strict-feedback systems using the backstepping framework. In each step of the virtual control design, neural network (NN) is employed for uncertainty approximation. In previous works, most designs are directly toward system stability ignoring the fact how the NN is working as an approximator. In this paper, to enhance the learning ability, a novel prediction error signal is constructed to provide additional correction information for NN weight update using online recorded data. In this way, the neural approximation precision is highly improved, and the convergence speed can be faster. Furthermore, the sliding mode differentiator is employed to approximate the derivative of the virtual control signal, and thus, the complex analysis of the backstepping design can be avoided. The closed-loop stability is rigorously established, and the boundedness of the tracking error can be guaranteed. Through simulation of hypersonic flight dynamics, the proposed approach exhibits better tracking performance.

A program for the Bayesian Neural Network in the ROOT framework

NASA Astrophysics Data System (ADS)

Zhong, Jiahang; Huang, Run-Sheng; Lee, Shih-Chang

2011-12-01

We present a Bayesian Neural Network algorithm implemented in the TMVA package (Hoecker et al., 2007 [1]), within the ROOT framework (Brun and Rademakers, 1997 [2]). Comparing to the conventional utilization of Neural Network as discriminator, this new implementation has more advantages as a non-parametric regression tool, particularly for fitting probabilities. It provides functionalities including cost function selection, complexity control and uncertainty estimation. An example of such application in High Energy Physics is shown. The algorithm is available with ROOT release later than 5.29. Program summaryProgram title: TMVA-BNN Catalogue identifier: AEJX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: BSD license No. of lines in distributed program, including test data, etc.: 5094 No. of bytes in distributed program, including test data, etc.: 1,320,987 Distribution format: tar.gz Programming language: C++ Computer: Any computer system or cluster with C++ compiler and UNIX-like operating system Operating system: Most UNIX/Linux systems. The application programs were thoroughly tested under Fedora and Scientific Linux CERN. Classification: 11.9 External routines: ROOT package version 5.29 or higher ( http://root.cern.ch) Nature of problem: Non-parametric fitting of multivariate distributions Solution method: An implementation of Neural Network following the Bayesian statistical interpretation. Uses Laplace approximation for the Bayesian marginalizations. Provides the functionalities of automatic complexity control and uncertainty estimation. Running time: Time consumption for the training depends substantially on the size of input sample, the NN topology, the number of training iterations, etc. For the example in this manuscript, about 7 min was used on a PC/Linux with 2.0 GHz processors.

Frontal Theta Reflects Uncertainty and Unexpectedness during Exploration and Exploitation

PubMed Central

Figueroa, Christina M.; Cohen, Michael X; Frank, Michael J.

2012-01-01

In order to understand the exploitation/exploration trade-off in reinforcement learning, previous theoretical and empirical accounts have suggested that increased uncertainty may precede the decision to explore an alternative option. To date, the neural mechanisms that support the strategic application of uncertainty-driven exploration remain underspecified. In this study, electroencephalography (EEG) was used to assess trial-to-trial dynamics relevant to exploration and exploitation. Theta-band activities over middle and lateral frontal areas have previously been implicated in EEG studies of reinforcement learning and strategic control. It was hypothesized that these areas may interact during top-down strategic behavioral control involved in exploratory choices. Here, we used a dynamic reward–learning task and an associated mathematical model that predicted individual response times. This reinforcement-learning model generated value-based prediction errors and trial-by-trial estimates of exploration as a function of uncertainty. Mid-frontal theta power correlated with unsigned prediction error, although negative prediction errors had greater power overall. Trial-to-trial variations in response-locked frontal theta were linearly related to relative uncertainty and were larger in individuals who used uncertainty to guide exploration. This finding suggests that theta-band activities reflect prefrontal-directed strategic control during exploratory choices. PMID:22120491

Peripheral dysgraphia: dissociations of lowercase from uppercase letters and of print from cursive writing.

PubMed

Ingles, Janet L; Fisk, John D; Fleetwood, Ian; Burrell, Steven; Darvesh, Sultan

2014-03-01

Clinical analyses of patients with acquired dysgraphia provide unique opportunities to understand the cognitive and neural organization of written language production. We report J.B., a 50-year-old woman with peripheral dysgraphia who had prominent dissociations in her ability to write in lowercase versus uppercase and print versus cursive. We gave J.B. a series of tasks that evaluated her skills at writing uppercase and lowercase print and cursive, spelling aloud and in writing, writing numbers and symbols, and visual letter recognition and imagery. She was impaired in printing letters, with lowercase more affected than uppercase, but her cursive writing was relatively intact. This pattern was consistent across letter, word, and nonword writing tasks. She was unimpaired on tasks assessing her visual recognition and imagery of lowercase and uppercase letters. Her writing of numbers was preserved. J.B.'s handwriting disorder was accompanied by a central phonological dysgraphia. Our findings indicate functional independence of graphomotor programs for print and cursive letter styles and for letters and numbers. We discuss the relationship between peripheral and central writing disorders.

Dissociations of subliminal and supraliminal self-face from other-face processing: behavioral and ERP evidence.

PubMed

Geng, Haiyan; Zhang, Shen; Li, Qi; Tao, Ran; Xu, Shan

2012-10-01

Self-related information has been found to be processed more quickly and accurately in studies with supraliminal self-stimuli and traditional paradigms such as masked priming. We conducted two experiments to investigate whether subliminal self-face processing enjoys this advantage and the neural correlates of processing self-faces at both subliminal and supraliminal levels. We found that self-faces were quicker than famous-other faces to gain dominance against dynamic noise patterns during prolonged interocular suppression to enter awareness (Experiment 1). Meanwhile, subliminal contrast of self- and famous-other face processing was reflected in a reduced early vertex positive potential (VPP) component, whereas supraliminal self-other face differentiation was reflected in an enhanced N170, as well as a more positive late component (300-580ms, Experiment 2) to the self-face. The clear dissociations of self- and other-face processing found across our two experiments validate the self advantage. Our findings also contribute to understandings of the mechanisms underlying self-face processing at different levels of awareness. Copyright © 2012 Elsevier Ltd. All rights reserved.

Dog Experts' Brains Distinguish Socially Relevant Body Postures Similarly in Dogs and Humans

PubMed Central

Kujala, Miiamaaria V.; Kujala, Jan; Carlson, Synnöve; Hari, Riitta

2012-01-01

We read conspecifics' social cues effortlessly, but little is known about our abilities to understand social gestures of other species. To investigate the neural underpinnings of such skills, we used functional magnetic resonance imaging to study the brain activity of experts and non-experts of dog behavior while they observed humans or dogs either interacting with, or facing away from a conspecific. The posterior superior temporal sulcus (pSTS) of both subject groups dissociated humans facing toward each other from humans facing away, and in dog experts, a distinction also occurred for dogs facing toward vs. away in a bilateral area extending from the pSTS to the inferior temporo-occipital cortex: the dissociation of dog behavior was significantly stronger in expert than control group. Furthermore, the control group had stronger pSTS responses to humans than dogs facing toward a conspecific, whereas in dog experts, the responses were of similar magnitude. These findings suggest that dog experts' brains distinguish socially relevant body postures similarly in dogs and humans. PMID:22720054

Dissociable roles of medial and lateral PFC in rule learning.

PubMed

Cao, Bihua; Li, Wei; Li, Fuhong; Li, Hong

2016-11-01

Although the neural basis of rule learning is of great interest to cognitive neuroscientists, the pattern of transient brain activation during rule discovery remains to be investigated. In this study, we measured event-related functional magnetic resonance imaging (fMRI) during distinct phases of rule learning. Twenty-one healthy human volunteers were presented with a series of cards, each containing a clock-like display of 12 circles numbered sequentially. Participants were instructed that a fictitious animal would move from one circle to another either in a regular pattern (according to a rule hidden in consecutive trials) or randomly. Participants were then asked to judge whether a given step followed a rule. While the rule-search phase evoked more activation in the posterior lateral prefrontal cortex (LPFC), the rule-following phase caused stronger activation in the anterior medial prefrontal cortex (MPFC). Importantly, the intermediate phase, the rule-discovery phase evoked more activations in MPFC and dorsal anterior cingulate cortex (dACC) than rule search, and more activations in LPFC than rule following. Therefore, we can conclude that the medial and lateral PFC have dissociable contributions in rule learning.

Bilinguals at the "cocktail party": dissociable neural activity in auditory-linguistic brain regions reveals neurobiological basis for nonnative listeners' speech-in-noise recognition deficits.

PubMed

Bidelman, Gavin M; Dexter, Lauren

2015-04-01

We examined a consistent deficit observed in bilinguals: poorer speech-in-noise (SIN) comprehension for their nonnative language. We recorded neuroelectric mismatch potentials in mono- and bi-lingual listeners in response to contrastive speech sounds in noise. Behaviorally, late bilinguals required ∼10dB more favorable signal-to-noise ratios to match monolinguals' SIN abilities. Source analysis of cortical activity demonstrated monotonic increase in response latency with noise in superior temporal gyrus (STG) for both groups, suggesting parallel degradation of speech representations in auditory cortex. Contrastively, we found differential speech encoding between groups within inferior frontal gyrus (IFG)-adjacent to Broca's area-where noise delays observed in nonnative listeners were offset in monolinguals. Notably, brain-behavior correspondences double dissociated between language groups: STG activation predicted bilinguals' SIN, whereas IFG activation predicted monolinguals' performance. We infer higher-order brain areas act compensatorily to enhance impoverished sensory representations but only when degraded speech recruits linguistic brain mechanisms downstream from initial auditory-sensory inputs. Copyright © 2015 Elsevier Inc. All rights reserved.

Effects of measurement unobservability on neural extended Kalman filter tracking

NASA Astrophysics Data System (ADS)

Stubberud, Stephen C.; Kramer, Kathleen A.

2009-05-01

An important component of tracking fusion systems is the ability to fuse various sensors into a coherent picture of the scene. When multiple sensor systems are being used in an operational setting, the types of data vary. A significant but often overlooked concern of multiple sensors is the incorporation of measurements that are unobservable. An unobservable measurement is one that may provide information about the state, but cannot recreate a full target state. A line of bearing measurement, for example, cannot provide complete position information. Often, such measurements come from passive sensors such as a passive sonar array or an electronic surveillance measure (ESM) system. Unobservable measurements will, over time, result in the measurement uncertainty to grow without bound. While some tracking implementations have triggers to protect against the detrimental effects, many maneuver tracking algorithms avoid discussing this implementation issue. One maneuver tracking technique is the neural extended Kalman filter (NEKF). The NEKF is an adaptive estimation algorithm that estimates the target track as it trains a neural network on line to reduce the error between the a priori target motion model and the actual target dynamics. The weights of neural network are trained in a similar method to the state estimation/parameter estimation Kalman filter techniques. The NEKF has been shown to improve target tracking accuracy through maneuvers and has been use to predict target behavior using the new model that consists of the a priori model and the neural network. The key to the on-line adaptation of the NEKF is the fact that the neural network is trained using the same residuals as the Kalman filter for the tracker. The neural network weights are treated as augmented states to the target track. Through the state-coupling function, the weights are coupled to the target states. Thus, if the measurements cause the states of the target track to be unobservable, then the weights of the neural network have unobservable modes as well. In recent analysis, the NEKF was shown to have a significantly larger growth in the eigenvalues of the error covariance matrix than the standard EKF tracker when the measurements were purely bearings-only. This caused detrimental effects to the ability of the NEKF to model the target dynamics. In this work, the analysis is expanded to determine the detrimental effects of bearings-only measurements of various uncertainties on the performance of the NEKF when these unobservable measurements are interlaced with completely observable measurements. This analysis provides the ability to put implementation limitations on the NEKF when bearings-only sensors are present.

Neural Correlates of Sequence Learning with Stochastic Feedback

ERIC Educational Resources Information Center

Averbeck, Bruno B.; Kilner, James; Frith, Christopher D.

2011-01-01

Although much is known about decision making under uncertainty when only a single step is required in the decision process, less is known about sequential decision making. We carried out a stochastic sequence learning task in which subjects had to use noisy feedback to learn sequences of button presses. We compared flat and hierarchical behavioral…

Differential Effects of Insular and Ventromedial Prefrontal Cortex Lesions on Risky Decision-Making

ERIC Educational Resources Information Center

Clark, L.; Bechara, A.; Damasio, H.; Aitken, M. R. F.; Sahakian, B. J.; Robbins, T. W.

2008-01-01

The ventromedial prefrontal cortex (vmPFC) and insular cortex are implicated in distributed neural circuitry that supports emotional decision-making. Previous studies of patients with vmPFC lesions have focused primarily on decision-making under uncertainty, when outcome probabilities are ambiguous (e.g. the Iowa Gambling Task). It remains unclear…

Sensory optimization by stochastic tuning.

PubMed

Jurica, Peter; Gepshtein, Sergei; Tyukin, Ivan; van Leeuwen, Cees

2013-10-01

Individually, visual neurons are each selective for several aspects of stimulation, such as stimulus location, frequency content, and speed. Collectively, the neurons implement the visual system's preferential sensitivity to some stimuli over others, manifested in behavioral sensitivity functions. We ask how the individual neurons are coordinated to optimize visual sensitivity. We model synaptic plasticity in a generic neural circuit and find that stochastic changes in strengths of synaptic connections entail fluctuations in parameters of neural receptive fields. The fluctuations correlate with uncertainty of sensory measurement in individual neurons: The higher the uncertainty the larger the amplitude of fluctuation. We show that this simple relationship is sufficient for the stochastic fluctuations to steer sensitivities of neurons toward a characteristic distribution, from which follows a sensitivity function observed in human psychophysics and which is predicted by a theory of optimal allocation of receptive fields. The optimal allocation arises in our simulations without supervision or feedback about system performance and independently of coupling between neurons, making the system highly adaptive and sensitive to prevailing stimulation. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Mixed H ∞ and Passive Projective Synchronization for Fractional Order Memristor-Based Neural Networks with Time-Delay and Parameter Uncertainty

NASA Astrophysics Data System (ADS)

Song, Xiao-Na; Song, Shuai; Tejado Balsera, Inés; Liu, Lei-Po

2017-10-01

This paper investigates the mixed H ∞ and passive projective synchronization problem for fractional-order (FO) memristor-based neural networks. Our aim is to design a controller such that, though the unavoidable phenomena of time-delay and parameter uncertainty are fully considered, the resulting closed-loop system is asymptotically stable with a mixed H ∞ and passive performance level. By combining active and adaptive control methods, a novel hybrid control strategy is designed, which can guarantee the robust stability of the closed-loop system and also ensure a mixed H ∞ and passive performance level. Via the application of FO Lyapunov stability theory, the projective synchronization conditions are addressed in terms of linear matrix inequality techniques. Finally, two simulation examples are given to illustrate the effectiveness of the proposed method. Supported by National Natural Science Foundation of China under Grant Nos. U1604146, U1404610, 61473115, 61203047, Science and Technology Research Project in Henan Province under Grant Nos. 152102210273, 162102410024, and Foundation for the University Technological Innovative Talents of Henan Province under Grant No. 18HASTIT019

Intelligent robust tracking control for a class of uncertain strict-feedback nonlinear systems.

PubMed

Chang, Yeong-Chan

2009-02-01

This paper addresses the problem of designing robust tracking controls for a large class of strict-feedback nonlinear systems involving plant uncertainties and external disturbances. The input and virtual input weighting matrices are perturbed by bounded time-varying uncertainties. An adaptive fuzzy-based (or neural-network-based) dynamic feedback tracking controller will be developed such that all the states and signals of the closed-loop system are bounded and the trajectory tracking error should be as small as possible. First, the adaptive approximators with linearly parameterized models are designed, and a partitioned procedure with respect to the developed adaptive approximators is proposed such that the implementation of the fuzzy (or neural network) basis functions depends only on the state variables but does not depend on the tuning approximation parameters. Furthermore, we extend to design the nonlinearly parameterized adaptive approximators. Consequently, the intelligent robust tracking control schemes developed in this paper possess the properties of computational simplicity and easy implementation. Finally, simulation examples are presented to demonstrate the effectiveness of the proposed control algorithms.

Deconstructing risk: Separable encoding of variance and skewness in the brain

PubMed Central

Symmonds, Mkael; Wright, Nicholas D.; Bach, Dominik R.; Dolan, Raymond J.

2011-01-01

Risky choice entails a need to appraise all possible outcomes and integrate this information with individual risk preference. Risk is frequently quantified solely by statistical variance of outcomes, but here we provide evidence that individuals’ choice behaviour is sensitive to both dispersion (variance) and asymmetry (skewness) of outcomes. Using a novel behavioural paradigm in humans, we independently manipulated these ‘summary statistics’ while scanning subjects with fMRI. We show that a behavioural sensitivity to variance and skewness is mirrored in neuroanatomically dissociable representations of these quantities, with parietal cortex showing sensitivity to the former and prefrontal cortex and ventral striatum to the latter. Furthermore, integration of these objective risk metrics with subjective risk preference is expressed in a subject-specific coupling between neural activity and choice behaviour in anterior insula. Our findings show that risk is neither monolithic from a behavioural nor neural perspective and its decomposition is evident both in distinct behavioural preferences and in segregated underlying brain representations. PMID:21763444

Monitoring and control of amygdala neurofeedback involves distributed information processing in the human brain.

PubMed

Paret, Christian; Zähringer, Jenny; Ruf, Matthias; Gerchen, Martin Fungisai; Mall, Stephanie; Hendler, Talma; Schmahl, Christian; Ende, Gabriele

2018-03-30

Brain-computer interfaces provide conscious access to neural activity by means of brain-derived feedback ("neurofeedback"). An individual's abilities to monitor and control feedback are two necessary processes for effective neurofeedback therapy, yet their underlying functional neuroanatomy is still being debated. In this study, healthy subjects received visual feedback from their amygdala response to negative pictures. Activation and functional connectivity were analyzed to disentangle the role of brain regions in different processes. Feedback monitoring was mapped to the thalamus, ventromedial prefrontal cortex (vmPFC), ventral striatum (VS), and rostral PFC. The VS responded to feedback corresponding to instructions while rPFC activity differentiated between conditions and predicted amygdala regulation. Control involved the lateral PFC, anterior cingulate, and insula. Monitoring and control activity overlapped in the VS and thalamus. Extending current neural models of neurofeedback, this study introduces monitoring and control of feedback as anatomically dissociated processes, and suggests their important role in voluntary neuromodulation. © 2018 Wiley Periodicals, Inc.

Fluid and flexible minds: Intelligence reflects synchrony in the brain’s intrinsic network architecture

PubMed Central

Ferguson, Michael A.; Anderson, Jeffrey S.; Spreng, R. Nathan

2017-01-01

Human intelligence has been conceptualized as a complex system of dissociable cognitive processes, yet studies investigating the neural basis of intelligence have typically emphasized the contributions of discrete brain regions or, more recently, of specific networks of functionally connected regions. Here we take a broader, systems perspective in order to investigate whether intelligence is an emergent property of synchrony within the brain’s intrinsic network architecture. Using a large sample of resting-state fMRI and cognitive data (n = 830), we report that the synchrony of functional interactions within and across distributed brain networks reliably predicts fluid and flexible intellectual functioning. By adopting a whole-brain, systems-level approach, we were able to reliably predict individual differences in human intelligence by characterizing features of the brain’s intrinsic network architecture. These findings hold promise for the eventual development of neural markers to predict changes in intellectual function that are associated with neurodevelopment, normal aging, and brain disease.

Distinct Sources of Deterministic and Stochastic Components of Action Timing Decisions in Rodent Frontal Cortex.

PubMed

Murakami, Masayoshi; Shteingart, Hanan; Loewenstein, Yonatan; Mainen, Zachary F

2017-05-17

The selection and timing of actions are subject to determinate influences such as sensory cues and internal state as well as to effectively stochastic variability. Although stochastic choice mechanisms are assumed by many theoretical models, their origin and mechanisms remain poorly understood. Here we investigated this issue by studying how neural circuits in the frontal cortex determine action timing in rats performing a waiting task. Electrophysiological recordings from two regions necessary for this behavior, medial prefrontal cortex (mPFC) and secondary motor cortex (M2), revealed an unexpected functional dissociation. Both areas encoded deterministic biases in action timing, but only M2 neurons reflected stochastic trial-by-trial fluctuations. This differential coding was reflected in distinct timescales of neural dynamics in the two frontal cortical areas. These results suggest a two-stage model in which stochastic components of action timing decisions are injected by circuits downstream of those carrying deterministic bias signals. Copyright © 2017 Elsevier Inc. All rights reserved.

Distinct Neural Circuits Support Transient and Sustained Processes in Prospective Memory and Working Memory

PubMed Central

West, Robert; Braver, Todd

2009-01-01

Current theories are divided as to whether prospective memory (PM) involves primarily sustained processes such as strategic monitoring, or transient processes such as the retrieval of intentions from memory when a relevant cue is encountered. The current study examined the neural correlates of PM using a functional magnetic resonance imaging design that allows for the decomposition of brain activity into sustained and transient components. Performance of the PM task was primarily associated with sustained responses in a network including anterior prefrontal cortex (lateral Brodmann area 10), and these responses were dissociable from sustained responses associated with active maintenance in working memory. Additionally, the sustained responses in anterior prefrontal cortex correlated with faster response times for prospective responses. Prospective cues also elicited selective transient activity in a region of interest along the right middle temporal gyrus. The results support the conclusion that both sustained and transient processes contribute to efficient PM and provide novel constraints on the functional role of anterior PFC in higher-order cognition. PMID:18854581

Neural components of topographical representation

PubMed Central

Aguirre, Geoffrey K.; Zarahn, Eric; D’Esposito, Mark

1998-01-01

Studies of patients with focal brain damage suggest that topographical representation is subserved by dissociable neural subcomponents. This article offers a condensed review of the literature of “topographical disorientation” and describes several functional MRI studies designed to test hypotheses generated by that review. Three hypotheses are considered: (i) The parahippocampal cortex is critically involved in the acquisition of exocentric spatial information in humans; (ii) separable, posterior, dorsal, and ventral cortical regions subserve the perception and long term representation of position and identity, respectively, of landmarks; and (iii) there is a distinct area of the ventral occipitotemporal cortex that responds maximally to building stimuli and may play a role in the perception of salient landmarks. We conclude with a discussion of the inferential limitations of neuroimaging and lesion studies. It is proposed that combining these two approaches allows for inferences regarding the computational involvement of a neuroanatomical substrate in a given cognitive process although neither method can strictly support this conclusion alone. PMID:9448249

Direct cortical stimulation of inferior frontal cortex disrupts both speech and music production in highly trained musicians.

PubMed

Leonard, Matthew K; Desai, Maansi; Hungate, Dylan; Cai, Ruofan; Singhal, Nilika S; Knowlton, Robert C; Chang, Edward F

2018-05-22

Music and speech are human-specific behaviours that share numerous properties, including the fine motor skills required to produce them. Given these similarities, previous work has suggested that music and speech may at least partially share neural substrates. To date, much of this work has focused on perception, and has not investigated the neural basis of production, particularly in trained musicians. Here, we report two rare cases of musicians undergoing neurosurgical procedures, where it was possible to directly stimulate the left hemisphere cortex during speech and piano/guitar music production tasks. We found that stimulation to left inferior frontal cortex, including pars opercularis and ventral pre-central gyrus, caused slowing and arrest for both speech and music, and note sequence errors for music. Stimulation to posterior superior temporal cortex only caused production errors during speech. These results demonstrate partially dissociable networks underlying speech and music production, with a shared substrate in frontal regions.

Task relevance modulates the behavioural and neural effects of sensory predictions

PubMed Central

Friston, Karl J.; Nobre, Anna C.

2017-01-01

The brain is thought to generate internal predictions to optimize behaviour. However, it is unclear whether predictions signalling is an automatic brain function or depends on task demands. Here, we manipulated the spatial/temporal predictability of visual targets, and the relevance of spatial/temporal information provided by auditory cues. We used magnetoencephalography (MEG) to measure participants’ brain activity during task performance. Task relevance modulated the influence of predictions on behaviour: spatial/temporal predictability improved spatial/temporal discrimination accuracy, but not vice versa. To explain these effects, we used behavioural responses to estimate subjective predictions under an ideal-observer model. Model-based time-series of predictions and prediction errors (PEs) were associated with dissociable neural responses: predictions correlated with cue-induced beta-band activity in auditory regions and alpha-band activity in visual regions, while stimulus-bound PEs correlated with gamma-band activity in posterior regions. Crucially, task relevance modulated these spectral correlates, suggesting that current goals influence PE and prediction signalling. PMID:29206225

Hypothalamic Circuits for Predation and Evasion.

PubMed

Li, Yi; Zeng, Jiawei; Zhang, Juen; Yue, Chenyu; Zhong, Weixin; Liu, Zhixiang; Feng, Qiru; Luo, Minmin

2018-02-21

The interactions between predator and prey represent some of the most dramatic events in nature and constitute a matter of life and death for both sides. The hypothalamus has been implicated in driving predation and evasion; however, the exact hypothalamic neural circuits underlying these behaviors remain poorly defined. Here, we demonstrate that inhibitory and excitatory projections from the mouse lateral hypothalamus (LH) to the periaqueductal gray (PAG) in the midbrain drive, respectively, predation and evasion. LH GABA neurons were activated during predation. Optogenetically stimulating PAG-projecting LH GABA neurons drove strong predatory attack, and inhibiting these cells reversibly blocked predation. In contrast, LH glutamate neurons were activated during evasion. Stimulating PAG-projecting LH glutamate neurons drove evasion and inhibiting them impeded predictive evasion. Therefore, the seemingly opposite behaviors of predation and evasion are tightly regulated by two dissociable modular command systems within a single neural projection from the LH to the PAG. VIDEO ABSTRACT. Copyright © 2018 Elsevier Inc. All rights reserved.

Dissecting out conscious and unconscious memory (sub)processes within the human medial temporal lobe.

PubMed

Grunwald, T; Pezer, N; Münte, T F; Kurthen, M; Lehnertz, K; Van Roost, D; Fernández, G; Kutas, M; Elger, C E

2003-11-01

The human medial temporal lobe (MTL) system mediates memories that can be consciously recollected. However, the specific natures of the individual contributions of its various subregions to conscious memory processes remain equivocal. Here we show a functional dissociation between the hippocampus proper and the parahippocampal region in conscious and unconscious memory as revealed by invasive recordings of limbic event-related brain potentials recorded during explicit and implicit word recognition: Only hippocampal and not parahippocampal neural activity exhibits a sensitivity to the implicit versus explicit nature of the recognition memory task. Moreover, only within the hippocampus proper do the neural responses to repeated words differ not only from those to new words but also from each other as a function of recognition success. By contrast parahippocampal (rhinal) responses are sensitive to repetition independent of conscious recognition. These findings thus demonstrate that it is the hippocampus proper among the MTL structures that is specifically engaged during conscious memory processes.

Neural correlates of auditory short-term memory in rostral superior temporal cortex.

PubMed

Scott, Brian H; Mishkin, Mortimer; Yin, Pingbo

2014-12-01

Auditory short-term memory (STM) in the monkey is less robust than visual STM and may depend on a retained sensory trace, which is likely to reside in the higher-order cortical areas of the auditory ventral stream. We recorded from the rostral superior temporal cortex as monkeys performed serial auditory delayed match-to-sample (DMS). A subset of neurons exhibited modulations of their firing rate during the delay between sounds, during the sensory response, or during both. This distributed subpopulation carried a predominantly sensory signal modulated by the mnemonic context of the stimulus. Excitatory and suppressive effects on match responses were dissociable in their timing and in their resistance to sounds intervening between the sample and match. Like the monkeys' behavioral performance, these neuronal effects differ from those reported in the same species during visual DMS, suggesting different neural mechanisms for retaining dynamic sounds and static images in STM. Copyright © 2014 Elsevier Ltd. All rights reserved.

Common and dissociable neural correlates associated with component processes of inductive reasoning.

PubMed

Jia, Xiuqin; Liang, Peipeng; Lu, Jie; Yang, Yanhui; Zhong, Ning; Li, Kuncheng

2011-06-15

The ability to draw numerical inductive reasoning requires two key cognitive processes, identification and extrapolation. This study aimed to identify the neural correlates of both component processes of numerical inductive reasoning using event-related fMRI. Three kinds of tasks: rule induction (RI), rule induction and application (RIA), and perceptual judgment (Jud) were solved by twenty right-handed adults. Our results found that the left superior parietal lobule (SPL) extending into the precuneus and left dorsolateral prefrontal cortex (DLPFC) were commonly recruited in the two components. It was also observed that the fronto-parietal network was more specific to identification, whereas the striatal-thalamic network was more specific to extrapolation. The findings suggest that numerical inductive reasoning is mediated by the coordination of multiple brain areas including the prefrontal, parietal, and subcortical regions, of which some are more specific to demands on only one of these two component processes, whereas others are sensitive to both. Copyright © 2011 Elsevier Inc. All rights reserved.

Is Order the Defining Feature of Magnitude Representation? An ERP Study on Learning Numerical Magnitude and Spatial Order of Artificial Symbols

PubMed Central

Zhao, Hui; Chen, Chuansheng; Zhang, Hongchuan; Zhou, Xinlin; Mei, Leilei; Chen, Chunhui; Chen, Lan; Cao, Zhongyu; Dong, Qi

2012-01-01

Using an artificial-number learning paradigm and the ERP technique, the present study investigated neural mechanisms involved in the learning of magnitude and spatial order. 54 college students were divided into 2 groups matched in age, gender, and school major. One group was asked to learn the associations between magnitude (dot patterns) and the meaningless Gibson symbols, and the other group learned the associations between spatial order (horizontal positions on the screen) and the same set of symbols. Results revealed differentiated neural mechanisms underlying the learning processes of symbolic magnitude and spatial order. Compared to magnitude learning, spatial-order learning showed a later and reversed distance effect. Furthermore, an analysis of the order-priming effect showed that order was not inherent to the learning of magnitude. Results of this study showed a dissociation between magnitude and order, which supports the numerosity code hypothesis of mental representations of magnitude. PMID:23185363

Readers select a comprehension mode independent of pronoun: Evidence from fMRI during narrative comprehension.

PubMed

Hartung, Franziska; Hagoort, Peter; Willems, Roel M

2017-07-01

Perspective is a crucial feature for communicating about events. Yet it is unclear how linguistically encoded perspective relates to cognitive perspective taking. Here, we tested the effect of perspective taking with short literary stories. Participants listened to stories with 1st or 3rd person pronouns referring to the protagonist, while undergoing fMRI. When comparing action events with 1st and 3rd person pronouns, we found no evidence for a neural dissociation depending on the pronoun. A split sample approach based on the self-reported experience of perspective taking revealed 3 comprehension preferences. One group showed a strong 1st person preference, another a strong 3rd person preference, while a third group engaged in 1st and 3rd person perspective taking simultaneously. Comparing brain activations of the groups revealed different neural networks. Our results suggest that comprehension is perspective dependent, but not on the perspective suggested by the text, but on the reader's (situational) preference. Copyright © 2017 Elsevier Inc. All rights reserved.

A new upper bound for the norm of interval matrices with application to robust stability analysis of delayed neural networks.

PubMed

Faydasicok, Ozlem; Arik, Sabri

2013-08-01

The main problem with the analysis of robust stability of neural networks is to find the upper bound norm for the intervalized interconnection matrices of neural networks. In the previous literature, the major three upper bound norms for the intervalized interconnection matrices have been reported and they have been successfully applied to derive new sufficient conditions for robust stability of delayed neural networks. One of the main contributions of this paper will be the derivation of a new upper bound for the norm of the intervalized interconnection matrices of neural networks. Then, by exploiting this new upper bound norm of interval matrices and using stability theory of Lyapunov functionals and the theory of homomorphic mapping, we will obtain new sufficient conditions for the existence, uniqueness and global asymptotic stability of the equilibrium point for the class of neural networks with discrete time delays under parameter uncertainties and with respect to continuous and slope-bounded activation functions. The results obtained in this paper will be shown to be new and they can be considered alternative results to previously published corresponding results. We also give some illustrative and comparative numerical examples to demonstrate the effectiveness and applicability of the proposed robust stability condition. Copyright © 2013 Elsevier Ltd. All rights reserved.

Neural and Neural Gray-Box Modeling for Entry Temperature Prediction in a Hot Strip Mill

NASA Astrophysics Data System (ADS)

Barrios, José Angel; Torres-Alvarado, Miguel; Cavazos, Alberto; Leduc, Luis

2011-10-01

In hot strip mills, initial controller set points have to be calculated before the steel bar enters the mill. Calculations rely on the good knowledge of rolling variables. Measurements are available only after the bar has entered the mill, and therefore they have to be estimated. Estimation of process variables, particularly that of temperature, is of crucial importance for the bar front section to fulfill quality requirements, and the same must be performed in the shortest possible time to preserve heat. Currently, temperature estimation is performed by physical modeling; however, it is highly affected by measurement uncertainties, variations in the incoming bar conditions, and final product changes. In order to overcome these problems, artificial intelligence techniques such as artificial neural networks and fuzzy logic have been proposed. In this article, neural network-based systems, including neural-based Gray-Box models, are applied to estimate scale breaker entry temperature, given its importance, and their performance is compared to that of the physical model used in plant. Several neural systems and several neural-based Gray-Box models are designed and tested with real data. Taking advantage of the flexibility of neural networks for input incorporation, several factors which are believed to have influence on the process are also tested. The systems proposed in this study were proven to have better performance indexes and hence better prediction capabilities than the physical models currently used in plant.

Pupil dilation signals uncertainty and surprise in a learning gambling task.

PubMed

Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

2013-01-01

Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes' feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans.

Pupil dilation signals uncertainty and surprise in a learning gambling task

PubMed Central

Lavín, Claudio; San Martín, René; Rosales Jubal, Eduardo

2014-01-01

Pupil dilation under constant illumination is a physiological marker where modulation is related to several cognitive functions involved in daily decision making. There is evidence for a role of pupil dilation change during decision-making tasks associated with uncertainty, reward-prediction errors and surprise. However, while some work suggests that pupil dilation is mainly modulated by reward predictions, others point out that this marker is related to uncertainty signaling and surprise. Supporting the latter hypothesis, the neural substrate of this marker is related to noradrenaline (NA) activity which has been also related to uncertainty signaling. In this work we aimed to test whether pupil dilation is a marker for uncertainty and surprise in a learning task. We recorded pupil dilation responses in 10 participants performing the Iowa Gambling Task (IGT), a decision-making task that requires learning and constant monitoring of outcomes’ feedback, which are important variables within the traditional study of human decision making. Results showed that pupil dilation changes were modulated by learned uncertainty and surprise regardless of feedback magnitudes. Interestingly, greater pupil dilation changes were found during positive feedback (PF) presentation when there was lower uncertainty about a future negative feedback (NF); and by surprise during NF presentation. These results support the hypothesis that pupil dilation is a marker of learned uncertainty, and may be used as a marker of NA activity facing unfamiliar situations in humans. PMID:24427126

Neurobiological dissociation of retrieval and reconsolidation of cocaine-associated memory

PubMed Central

Otis, James M.; Dashew, Kidane B.; Mueller, Devin

2013-01-01

Drug use is provoked by the presentation of drug-associated cues, even following long periods of abstinence. Disruption of these learned associations would therefore limit relapse susceptibility. Drug-associated memories are susceptible to long-term disruption during retrieval and shortly after, during memory reconsolidation. Recent evidence reveals that retrieval and reconsolidation are dependent on β-adrenergic receptor (β-AR) activation. Despite this, whether retrieval and reconsolidation are dependent on identical or distinct neural mechanisms is unknown. The prelimbic medial prefrontal cortex (PL-mPFC) and basolateral amygdala (BLA) have been implicated in the expression and reconsolidation of associative memories. Therefore, we investigated the necessity of β-AR activation within the PL-mPFC and BLA for cocaine-associated memory retrieval and reconsolidation in rats. Before or immediately after a cocaine-induced conditioned place preference (CPP) retrieval trial, β-AR antagonists were infused into the PL-mPFC or BLA, followed by daily testing. PL-mPFC infusions before, but not after, a CPP trial disrupted CPP memory retrieval and induced a persistent deficit in retrieval during subsequent trials. In contrast, BLA β-AR blockade had no effect on initial CPP memory retrieval, but prevented CPP expression during subsequent trials indicative of reconsolidation disruption. Our results reveal a distinct dissociation between the neural mechanisms required for cocaine-associated memory retrieval and reconsolidation. Using patch-clamp electrophysiology, we also show that application of a β-AR antagonist prevents NE-induced potentiation of PL-mPFC pyramidal and GABAergic neuronal excitability. Thus, targeted β-AR blockade could induce long-term deficits in drug-associated memory retrieval by reducing neuronal excitability, providing a novel method of preventing cue-elicited drug seeking and relapse. PMID:23325262

Developmental dyslexia in Chinese and English populations: dissociating the effect of dyslexia from language differences

PubMed Central

Hu, Wei; Lee, Hwee Ling; Zhang, Qiang; Liu, Tao; Geng, Li Bo; Seghier, Mohamed L.; Shakeshaft, Clare; Twomey, Tae; Green, David W.; Yang, Yi Ming

2010-01-01

Previous neuroimaging studies have suggested that developmental dyslexia has a different neural basis in Chinese and English populations because of known differences in the processing demands of the Chinese and English writing systems. Here, using functional magnetic resonance imaging, we provide the first direct statistically based investigation into how the effect of dyslexia on brain activation is influenced by the Chinese and English writing systems. Brain activation for semantic decisions on written words was compared in English dyslexics, Chinese dyslexics, English normal readers and Chinese normal readers, while controlling for all other experimental parameters. By investigating the effects of dyslexia and language in one study, we show common activation in Chinese and English dyslexics despite different activation in Chinese versus English normal readers. The effect of dyslexia in both languages was observed as less than normal activation in the left angular gyrus and in left middle frontal, posterior temporal and occipitotemporal regions. Differences in Chinese and English normal reading were observed as increased activation for Chinese relative to English in the left inferior frontal sulcus; and increased activation for English relative to Chinese in the left posterior superior temporal sulcus. These cultural differences were not observed in dyslexics who activated both left inferior frontal sulcus and left posterior superior temporal sulcus, consistent with the use of culturally independent strategies when reading is less efficient. By dissociating the effect of dyslexia from differences in Chinese and English normal reading, our results reconcile brain activation results with a substantial body of behavioural studies showing commonalities in the cognitive manifestation of dyslexia in Chinese and English populations. They also demonstrate the influence of cognitive ability and learning environment on a common neural system for reading. PMID:20488886

Developmental dyslexia in Chinese and English populations: dissociating the effect of dyslexia from language differences.

PubMed

Hu, Wei; Lee, Hwee Ling; Zhang, Qiang; Liu, Tao; Geng, Li Bo; Seghier, Mohamed L; Shakeshaft, Clare; Twomey, Tae; Green, David W; Yang, Yi Ming; Price, Cathy J

2010-06-01

Previous neuroimaging studies have suggested that developmental dyslexia has a different neural basis in Chinese and English populations because of known differences in the processing demands of the Chinese and English writing systems. Here, using functional magnetic resonance imaging, we provide the first direct statistically based investigation into how the effect of dyslexia on brain activation is influenced by the Chinese and English writing systems. Brain activation for semantic decisions on written words was compared in English dyslexics, Chinese dyslexics, English normal readers and Chinese normal readers, while controlling for all other experimental parameters. By investigating the effects of dyslexia and language in one study, we show common activation in Chinese and English dyslexics despite different activation in Chinese versus English normal readers. The effect of dyslexia in both languages was observed as less than normal activation in the left angular gyrus and in left middle frontal, posterior temporal and occipitotemporal regions. Differences in Chinese and English normal reading were observed as increased activation for Chinese relative to English in the left inferior frontal sulcus; and increased activation for English relative to Chinese in the left posterior superior temporal sulcus. These cultural differences were not observed in dyslexics who activated both left inferior frontal sulcus and left posterior superior temporal sulcus, consistent with the use of culturally independent strategies when reading is less efficient. By dissociating the effect of dyslexia from differences in Chinese and English normal reading, our results reconcile brain activation results with a substantial body of behavioural studies showing commonalities in the cognitive manifestation of dyslexia in Chinese and English populations. They also demonstrate the influence of cognitive ability and learning environment on a common neural system for reading.

Neural correlates of confidence during item recognition and source memory retrieval: evidence for both dual-process and strength memory theories.

PubMed

Hayes, Scott M; Buchler, Norbou; Stokes, Jared; Kragel, James; Cabeza, Roberto

2011-12-01

Although the medial-temporal lobes (MTL), PFC, and parietal cortex are considered primary nodes in the episodic memory network, there is much debate regarding the contributions of MTL, PFC, and parietal subregions to recollection versus familiarity (dual-process theory) and the feasibility of accounts on the basis of a single memory strength process (strength theory). To investigate these issues, the current fMRI study measured activity during retrieval of memories that differed quantitatively in terms of strength (high vs. low-confidence trials) and qualitatively in terms of recollection versus familiarity (source vs. item memory tasks). Support for each theory varied depending on which node of the episodic memory network was considered. Results from MTL best fit a dual-process account, as a dissociation was found between a right hippocampal region showing high-confidence activity during the source memory task and bilateral rhinal regions showing high-confidence activity during the item memory task. Within PFC, several left-lateralized regions showed greater activity for source than item memory, consistent with recollective orienting, whereas a right-lateralized ventrolateral area showed low-confidence activity in both tasks, consistent with monitoring processes. Parietal findings were generally consistent with strength theory, with dorsal areas showing low-confidence activity and ventral areas showing high-confidence activity in both tasks. This dissociation fits with an attentional account of parietal functions during episodic retrieval. The results suggest that both dual-process and strength theories are partly correct, highlighting the need for an integrated model that links to more general cognitive theories to account for observed neural activity during episodic memory retrieval.

The role of the P3 and CNV components in voluntary and automatic temporal orienting: A high spatial-resolution ERP study.

PubMed

Mento, Giovanni

2017-12-01

A main distinction has been proposed between voluntary and automatic mechanisms underlying temporal orienting (TO) of selective attention. Voluntary TO implies the endogenous directing of attention induced by symbolic cues. Conversely, automatic TO is exogenously instantiated by the physical properties of stimuli. A well-known example of automatic TO is sequential effects (SEs), which refer to the adjustments in participants' behavioral performance as a function of the trial-by-trial sequential distribution of the foreperiod between two stimuli. In this study a group of healthy adults underwent a cued reaction time task purposely designed to assess both voluntary and automatic TO. During the task, both post-cue and post-target event-related potentials (ERPs) were recorded by means of a high spatial resolution EEG system. In the results of the post-cue analysis, the P3a and P3b were identified as two distinct ERP markers showing distinguishable spatiotemporal features and reflecting automatic and voluntary a priori expectancy generation, respectively. The brain source reconstruction further revealed that distinct cortical circuits supported these two temporally dissociable components. Namely, the voluntary P3b was supported by a left sensorimotor network, while the automatic P3a was generated by a more distributed frontoparietal circuit. Additionally, post-cue contingent negative variation (CNV) and post-target P3 modulations were observed as common markers of voluntary and automatic expectancy implementation and response selection, although partially dissociable neural networks subserved these two mechanisms. Overall, these results provide new electrophysiological evidence suggesting that distinct neural substrates can be recruited depending on the voluntary or automatic cognitive nature of the cognitive mechanisms subserving TO. Copyright © 2017 Elsevier Ltd. All rights reserved.

Single-base-pair discrimination of terminal mismatches by using oligonucleotide microarrays and neural network analyses

NASA Technical Reports Server (NTRS)

Urakawa, Hidetoshi; Noble, Peter A.; El Fantroussi, Said; Kelly, John J.; Stahl, David A.

2002-01-01

The effects of single-base-pair near-terminal and terminal mismatches on the dissociation temperature (T(d)) and signal intensity of short DNA duplexes were determined by using oligonucleotide microarrays and neural network (NN) analyses. Two perfect-match probes and 29 probes having a single-base-pair mismatch at positions 1 to 5 from the 5' terminus of the probe were designed to target one of two short sequences representing 16S rRNA. Nonequilibrium dissociation rates (i.e., melting profiles) of all probe-target duplexes were determined simultaneously. Analysis of variance revealed that position of the mismatch, type of mismatch, and formamide concentration significantly affected the T(d) and signal intensity. Increasing the concentration of formamide in the washing buffer decreased the T(d) and signal intensity, and it decreased the variability of the signal. Although T(d)s of probe-target duplexes with mismatches in the first or second position were not significantly different from one another, duplexes with mismatches in the third to fifth positions had significantly lower T(d)s than those with mismatches in the first or second position. The trained NNs predicted the T(d) with high accuracies (R(2) = 0.93). However, the NNs predicted the signal intensity only moderately accurately (R(2) = 0.67), presumably due to increased noise in the signal intensity at low formamide concentrations. Sensitivity analysis revealed that the concentration of formamide explained most (75%) of the variability in T(d)s, followed by position of the mismatch (19%) and type of mismatch (6%). The results suggest that position of the mismatch at or near the 5' terminus plays a greater role in determining the T(d) and signal intensity of duplexes than the type of mismatch.

Neural Correlates of Confidence during Item Recognition and Source Memory Retrieval: Evidence for Both Dual-process and Strength Memory Theories

PubMed Central

Hayes, Scott M.; Buchler, Norbou; Stokes, Jared; Kragel, James; Cabeza, Roberto

2012-01-01

Although the medial-temporal lobes (MTL), PFC, and parietal cortex are considered primary nodes in the episodic memory network, there is much debate regarding the contributions of MTL, PFC, and parietal subregions to recollection versus familiarity (dual-process theory) and the feasibility of accounts on the basis of a single memory strength process (strength theory). To investigate these issues, the current fMRI study measured activity during retrieval of memories that differed quantitatively in terms of strength (high vs. low-confidence trials) and qualitatively in terms of recollection versus familiarity (source vs. item memory tasks). Support for each theory varied depending on which node of the episodic memory network was considered. Results from MTL best fit a dual-process account, as a dissociation was found between a right hippocampal region showing high-confidence activity during the source memory task and bilateral rhinal regions showing high-confidence activity during the item memory task. Within PFC, several left-lateralized regions showed greater activity for source than item memory, consistent with recollective orienting, whereas a right-lateralized ventrolateral area showed low-confidence activity in both tasks, consistent with monitoring processes. Parietal findings were generally consistent with strength theory, with dorsal areas showing low-confidence activity and ventral areas showing high-confidence activity in both tasks. This dissociation fits with an attentional account of parietal functions during episodic retrieval. The results suggest that both dual-process and strength theories are partly correct, highlighting the need for an integrated model that links to more general cognitive theories to account for observed neural activity during episodic memory retrieval. PMID:21736454

Neurobiological dissociation of retrieval and reconsolidation of cocaine-associated memory.

PubMed

Otis, James M; Dashew, Kidane B; Mueller, Devin

2013-01-16

Drug use is provoked by the presentation of drug-associated cues, even following long periods of abstinence. Disruption of these learned associations would therefore limit relapse susceptibility. Drug-associated memories are susceptible to long-term disruption during retrieval and shortly after, during memory reconsolidation. Recent evidence reveals that retrieval and reconsolidation are dependent on β-adrenergic receptor (β-AR) activation. Despite this, whether retrieval and reconsolidation are dependent on identical or distinct neural mechanisms is unknown. The prelimbic medial prefrontal cortex (PL-mPFC) and basolateral amygdala (BLA) have been implicated in the expression and reconsolidation of associative memories. Therefore, we investigated the necessity of β-AR activation within the PL-mPFC and BLA for cocaine-associated memory retrieval and reconsolidation in rats. Before or immediately after a cocaine-induced conditioned place preference (CPP) retrieval trial, β-AR antagonists were infused into the PL-mPFC or BLA, followed by daily testing. PL-mPFC infusions before, but not after, a CPP trial disrupted CPP memory retrieval and induced a persistent deficit in retrieval during subsequent trials. In contrast, BLA β-AR blockade had no effect on initial CPP memory retrieval, but prevented CPP expression during subsequent trials indicative of reconsolidation disruption. Our results reveal a distinct dissociation between the neural mechanisms required for cocaine-associated memory retrieval and reconsolidation. Using patch-clamp electrophysiology, we also show that application of a β-AR antagonist prevents norepinephrine-induced potentiation of PL-mPFC pyramidal cell and γ-aminobutyric-acid (GABA) interneuron excitability. Thus, targeted β-AR blockade could induce long-term deficits in drug-associated memory retrieval by reducing neuronal excitability, providing a novel method of preventing cue-elicited drug seeking and relapse.

Dissociation between neural and vascular responses to sympathetic stimulation : contribution of local adrenergic receptor function

NASA Technical Reports Server (NTRS)

Jacob, G.; Costa, F.; Shannon, J.; Robertson, D.; Biaggioni, I.

2000-01-01

Sympathetic activation produced by various stimuli, eg, mental stress or handgrip, evokes regional vascular responses that are often nonhomogeneous. This phenomenon is believed to be the consequence of the recruitment of differential central neural pathways or of a sympathetically mediated vasodilation. The purpose of this study was to determine whether a similar heterogeneous response occurs with cold pressor stimulation and to test the hypothesis that local differences in adrenergic receptor function could be in part responsible for this diversity. In 8 healthy subjects, local norepinephrine spillover and blood flow were measured in arms and legs at baseline and during sympathetic stimulation induced by baroreflex mechanisms (nitroprusside infusion) or cold pressor stimulation. At baseline, legs had higher vascular resistance (27+/-5 versus 17+/-2 U, P=0.05) despite lower norepinephrine spillover (0.28+/-0.04 versus 0.4+/-0.05 mg. min(-1). dL(-1), P=0.03). Norepinephrine spillover increased similarly in both arms and legs during nitroprusside infusion and cold pressor stimulation. On the other hand, during cold stimulation, vascular resistance increased in arms but not in legs (20+/-9% versus -7+/-4%, P=0.03). Increasing doses of isoproterenol and phenylephrine were infused intra-arterially in arms and legs to estimate beta-mediated vasodilation and alpha-induced vasoconstriction, respectively. beta-Mediated vasodilation was significantly lower in legs compared with arms. Thus, we report a dissociation between norepinephrine spillover and vascular responses to cold stress in lower limbs characterized by a paradoxical decrease in local resistance despite increases in sympathetic activity. The differences observed in adrenergic receptor responses cannot explain this phenomenon.

Highly Efficient Differentiation and Enrichment of Spinal Motor Neurons Derived from Human and Monkey Embryonic Stem Cells

PubMed Central

Wada, Tamaki; Honda, Makoto; Minami, Itsunari; Tooi, Norie; Amagai, Yuji; Nakatsuji, Norio; Aiba, Kazuhiro

2009-01-01

Background There are no cures or efficacious treatments for severe motor neuron diseases. It is extremely difficult to obtain naïve spinal motor neurons (sMNs) from human tissues for research due to both technical and ethical reasons. Human embryonic stem cells (hESCs) are alternative sources. Several methods for MN differentiation have been reported. However, efficient production of naïve sMNs and culture cost were not taken into consideration in most of the methods. Methods/Principal Findings We aimed to establish protocols for efficient production and enrichment of sMNs derived from pluripotent stem cells. Nestin+ neural stem cell (NSC) clusters were induced by Noggin or a small molecule inhibitor of BMP signaling. After dissociation of NSC clusters, neurospheres were formed in a floating culture containing FGF2. The number of NSCs in neurospheres could be expanded more than 30-fold via several passages. More than 33% of HB9+ sMN progenitor cells were observed after differentiation of dissociated neurospheres by all-trans retinoic acid (ATRA) and a Shh agonist for another week on monolayer culture. HB9+ sMN progenitor cells were enriched by gradient centrifugation up to 80% purity. These HB9+ cells differentiated into electrophysiologically functional cells and formed synapses with myotubes during a few weeks after ATRA/SAG treatment. Conclusions and Significance The series of procedures we established here, namely neural induction, NSC expansion, sMN differentiation and sMN purification, can provide large quantities of naïve sMNs derived from human and monkey pluripotent stem cells. Using small molecule reagents, reduction of culture cost could be achieved. PMID:19701462

The Effects of Sleep Deprivation on Dissociable Prototype Learning Systems

PubMed Central

Maddox, W. Todd; Glass, Brian D.; Zeithamova, Dagmar; Savarie, Zachary R.; Bowen, Christopher; Matthews, Michael D.; Schnyer, David M.

2011-01-01

Background: The cognitive neural underpinnings of prototype learning are becoming clear. Evidence points to 2 different neural systems, depending on the learning parameters. A/not-A (AN) prototype learning is mediated by posterior brain regions that are involved in early perceptual learning, whereas A/B (AB) is mediated by frontal and medial temporal lobe regions. Study Objectives: To investigate the effects of sleep deprivation on AN and AB prototype learning and to use established prototype models to provide insights into the cognitive-processing locus of sleep-deprivation deficits. Design: Participants performed an AN and an AB prototype learning task twice, separated by a 24-hour period, with or without sleep between testing sessions. Participants: Eighteen West Point cadets participated in the sleep-deprivation group, and 17 West Point cadets participated in a control group. Measurements and Results: Sleep deprivation led to an AN, but not an AB, performance deficit. Prototype model analyses indicated that the AN deficit was due to changes in attentional focus and a decrease in confidence that is reflected in an increased bias to respond non-A. Conclusions: The findings suggest that AN, but not AB, prototype learning is affected by sleep deprivation. Prototype model analyses support the notion that the effect of sleep deprivation on AN is consistent with lapses in attentional focus that are more detrimental to AN than to AB. This finding adds to a growing body of work that suggests that different performance changes associated with sleep deprivation can be attributed to a common mechanism of changes in simple attention and vigilance. Citation: Maddox WT; Glass BD; Zeithamova D; Savarie ZR; Bowen C; Matthews MD; Schnyer DM. The effects of sleep deprivation on dissociable prototype learning systems. SLEEP 2011;34(3):253-260. PMID:21358842

Application of Adaptive Autopilot Designs for an Unmanned Aerial Vehicle

NASA Technical Reports Server (NTRS)

Shin, Yoonghyun; Calise, Anthony J.; Motter, Mark A.

2005-01-01

This paper summarizes the application of two adaptive approaches to autopilot design, and presents an evaluation and comparison of the two approaches in simulation for an unmanned aerial vehicle. One approach employs two-stage dynamic inversion and the other employs feedback dynamic inversions based on a command augmentation system. Both are augmented with neural network based adaptive elements. The approaches permit adaptation to both parametric uncertainty and unmodeled dynamics, and incorporate a method that permits adaptation during periods of control saturation. Simulation results for an FQM-117B radio controlled miniature aerial vehicle are presented to illustrate the performance of the neural network based adaptation.

Adaptive neural network backstepping control for a class of uncertain fractional-order chaotic systems with unknown backlash-like hysteresis

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

Wu, Yimin; Lv, Hui, E-mail: lvhui207@gmail.com

In this paper, we consider the control problem of a class of uncertain fractional-order chaotic systems preceded by unknown backlash-like hysteresis nonlinearities based on backstepping control algorithm. We model the hysteresis by using a differential equation. Based on the fractional Lyapunov stability criterion and the backstepping algorithm procedures, an adaptive neural network controller is driven. No knowledge of the upper bound of the disturbance and system uncertainty is required in our controller, and the asymptotical convergence of the tracking error can be guaranteed. Finally, we give two simulation examples to confirm our theoretical results.

Receptive amusia: evidence for cross-hemispheric neural networks underlying music processing strategies.

PubMed

Schuppert, M; Münte, T F; Wieringa, B M; Altenmüller, E

2000-03-01

Perceptual musical functions were investigated in patients suffering from unilateral cerebrovascular cortical lesions. Using MIDI (Musical Instrument Digital Interface) technique, a standardized short test battery was established that covers local (analytical) as well as global perceptual mechanisms. These represent the principal cognitive strategies in melodic and temporal musical information processing (local, interval and rhythm; global, contour and metre). Of the participating brain-damaged patients, a total of 69% presented with post-lesional impairments in music perception. Left-hemisphere-damaged patients showed significant deficits in the discrimination of local as well as global structures in both melodic and temporal information processing. Right-hemisphere-damaged patients also revealed an overall impairment of music perception, reaching significance in the temporal conditions. Detailed analysis outlined a hierarchical organization, with an initial right-hemisphere recognition of contour and metre followed by identification of interval and rhythm via left-hemisphere subsystems. Patterns of dissociated and associated melodic and temporal deficits indicate autonomous, yet partially integrated neural subsystems underlying the processing of melodic and temporal stimuli. In conclusion, these data contradict a strong hemispheric specificity for music perception, but indicate cross-hemisphere, fragmented neural substrates underlying local and global musical information processing in the melodic and temporal dimensions. Due to the diverse profiles of neuropsychological deficits revealed in earlier investigations as well as in this study, individual aspects of musicality and musical behaviour very likely contribute to the definite formation of these widely distributed neural networks.

Neural Basis of Self and Other Representation in Autism: An fMRI Study of Self-Face Recognition

PubMed Central

Uddin, Lucina Q.; Davies, Mari S.; Scott, Ashley A.; Zaidel, Eran; Bookheimer, Susan Y.; Iacoboni, Marco; Dapretto, Mirella

2008-01-01

Background Autism is a developmental disorder characterized by decreased interest and engagement in social interactions and by enhanced self-focus. While previous theoretical approaches to understanding autism have emphasized social impairments and altered interpersonal interactions, there is a recent shift towards understanding the nature of the representation of the self in individuals with autism spectrum disorders (ASD). Still, the neural mechanisms subserving self-representations in ASD are relatively unexplored. Methodology/Principal Findings We used event-related fMRI to investigate brain responsiveness to images of the subjects' own face and to faces of others. Children with ASD and typically developing (TD) children viewed randomly presented digital morphs between their own face and a gender-matched other face, and made “self/other” judgments. Both groups of children activated a right premotor/prefrontal system when identifying images containing a greater percentage of the self face. However, while TD children showed activation of this system during both self- and other-processing, children with ASD only recruited this system while viewing images containing mostly their own face. Conclusions/Significance This functional dissociation between the representation of self versus others points to a potential neural substrate for the characteristic self-focus and decreased social understanding exhibited by these individuals, and suggests that individuals with ASD lack the shared neural representations for self and others that TD children and adults possess and may use to understand others. PMID:18958161

The neural processing of moral sensitivity to issues of justice and care.

PubMed

Robertson, Diana; Snarey, John; Ousley, Opal; Harenski, Keith; DuBois Bowman, F; Gilkey, Rick; Kilts, Clinton

2007-03-02

The empirical and theoretical consideration of ethical decision making has focused on the process of moral judgment; however, a precondition to judgment is moral sensitivity, the ability to detect and evaluate moral issues [Rest, J. R. (1984). The major components of morality. In W. Kurtines & J. Gewirtz (Eds.), Morality, moral behaviour, and moral development (pp. 24-38). New York, NY: Wiley]. Using functional magnetic resonance imaging (fMRI) and contextually standardized, real life moral issues, we demonstrate that sensitivity to moral issues is associated with activation of the polar medial prefrontal cortex, dorsal posterior cingulate cortex, and posterior superior temporal sulcus (STS). These activations suggest that moral sensitivity is related to access to knowledge unique to one's self, supported by autobiographical memory retrieval and social perspective taking. We also assessed whether sensitivity to rule-based or "justice" moral issues versus social situational or "care" moral issues is associated with dissociable neural processing events. Sensitivity to justice issues was associated with greater activation of the left intraparietal sulcus, whereas sensitivity to care issues was associated with greater activation of the ventral posterior cingulate cortex, ventromedial and dorsolateral prefrontal cortex, and thalamus. These results suggest a role for access to self histories and identities and social perspectives in sensitivity to moral issues, provide neural representations of the subcomponent process of moral sensitivity originally proposed by Rest, and support differing neural information processing for the interpretive recognition of justice and care moral issues.

Neural dissociations in attitude strength: Distinct regions of cingulate cortex track ambivalence and certainty.

PubMed

Luttrell, Andrew; Stillman, Paul E; Hasinski, Adam E; Cunningham, William A

2016-04-01

People's behaviors are often guided by valenced responses to objects in the environment. Beyond positive and negative evaluations, attitudes research has documented the importance of attitude strength--qualities of an attitude that enhance or attenuate its impact and durability. Although neuroscience research has extensively investigated valence, little work exists on other related variables like metacognitive judgments about one's attitudes. It remains unclear, then, whether the various indicators of attitude strength represent a single underlying neural process or whether they reflect independent processes. To examine this, we used functional MRI (fMRI) to identify the neural correlates of attitude strength. Specifically, we focus on ambivalence and certainty, which represent metacognitive judgments that people can make about their evaluations. Although often correlated, prior neuroscience research suggests that these 2 attributes may have distinct neural underpinnings. We investigate this by having participants make evaluative judgments of visually presented words while undergoing fMRI. After scanning, participants rated the degree of ambivalence and certainty they felt regarding their attitudes toward each word. We found that these 2 judgments corresponded to distinct brain regions' activity during the process of evaluation. Ambivalence corresponded to activation in anterior cingulate cortex, dorsomedial prefrontal cortex, and posterior cingulate cortex. Certainty, however, corresponded to activation in unique areas of the precuneus/posterior cingulate cortex. These results support a model treating ambivalence and certainty as distinct, though related, attitude strength variables, and we discuss implications for both attitudes and neuroscience research. (c) 2016 APA, all rights reserved).

Less is More: Neural Activity During Very Brief and Clearly Visible Exposure to Phobic Stimuli

PubMed Central

Siegel, Paul; Warren, Richard; Wang, Zhishun; Yang, Jie; Cohen, Don; Anderson, Jason F.; Murray, Lilly; Peterson, Bradley S.

2017-01-01

Research on automatic processes in emotion has focused almost exclusively on the provocation of fear responses. We have shown, in contrast, that the repeated presentation of masked feared images reduces avoidance of a live tarantula by spider-phobic participants. We investigated the neural basis for these adaptive effects of masked exposure. We identified 21 spider-phobic and 21 control participants using a psychiatric interview, fear questionnaire, and approach behavior towards a live tarantula. They received each of three conditions: (1) very brief exposure (VBE) to masked images of spiders; (2) clearly visible exposure (CVE) to spiders; and (3) masked images of flowers (control). Only VBE to masked spiders generated neural activity more strongly in phobic than in control participants, within subcortical fear, attention, higher-order language, and vision systems. Counter-intuitively, CVE to the same spiders generated stronger neural activity in control rather than phobic participants within these and other systems. VBE activated regions that support fear processing in phobic participants without causing them to experience fear consciously. CVE, by contrast, deactivated regions supporting fear regulation and caused phobic participants to experience fear. Activations by CVE to spiders correlated with fear ratings - explicit fear. Activations by VBE to masked spiders correlated with color-naming interference of spider words – implicit fear. These multiple dissociations between the effects of VBE and CVE to spiders suggest that limiting awareness of exposure to phobic stimuli through visual masking paradoxically facilitates their processing, while simultaneously minimizing the experience of fear. PMID:28165171

The cerebellum and decision making under uncertainty.

PubMed

Blackwood, Nigel; Ffytche, Dominic; Simmons, Andrew; Bentall, Richard; Murray, Robin; Howard, Robert

2004-06-01

This study aimed to identify the neural basis of probabilistic reasoning, a type of inductive inference that aids decision making under conditions of uncertainty. Eight normal subjects performed two separate two-alternative-choice tasks (the balls in a bottle and personality survey tasks) while undergoing functional magnetic resonance imaging (fMRI). The experimental conditions within each task were chosen so that they differed only in their requirement to make a decision under conditions of uncertainty (probabilistic reasoning and frequency determination required) or under conditions of certainty (frequency determination required). The same visual stimuli and motor responses were used in the experimental conditions. We provide evidence that the neo-cerebellum, in conjunction with the premotor cortex, inferior parietal lobule and medial occipital cortex, mediates the probabilistic inferences that guide decision making under uncertainty. We hypothesise that the neo-cerebellum constructs internal working models of uncertain events in the external world, and that such probabilistic models subserve the predictive capacity central to induction. Copyright 2004 Elsevier B.V.

Money talks: neural substrate of modulation of fairness by monetary incentives

PubMed Central

Zhou, Yuan; Wang, Yun; Rao, Li-Lin; Yang, Liu-Qing; Li, Shu

2014-01-01

A unique feature of the human species is compliance with social norms, e.g., fairness, even though this normative decision means curbing self-interest. However, sometimes people prefer to pursue wealth at the expense of moral goodness. Specifically, deviations from a fairness-related normative choice have been observed in the presence of a high monetary incentive. The neural mechanism underlying this deviation from the fairness-related normative choice has yet to be determined. In order to address this issue, using functional magnetic resonance imaging we employed an ultimatum game (UG) paradigm in which fairness and a proposed monetary amount were orthogonally varied. We found evidence for a significant modulation by the proposed amount on fairness in the right lateral prefrontal cortex (PFC) and the bilateral insular cortices. Additionally, the insular subregions showed dissociable modulation patterns. Inter-individual differences in the modulation effects in the left inferior frontal gyrus (IFG) accounted for inter-individual differences in the behavioral modulation effect as measured by the rejection rate, supporting the concept that the PFC plays a critical role in making fairness-related normative decisions in a social interaction condition. Our findings provide neural evidence for the modulation of fairness by monetary incentives as well as accounting for inter-individual differences. PMID:24834034

Neural Correlates of Racial Ingroup Bias in Observing Computer-Animated Social Encounters.

PubMed

Katsumi, Yuta; Dolcos, Sanda

2017-01-01

Despite evidence for the role of group membership in the neural correlates of social cognition, the mechanisms associated with processing non-verbal behaviors displayed by racially ingroup vs. outgroup members remain unclear. Here, 20 Caucasian participants underwent fMRI recording while observing social encounters with ingroup and outgroup characters displaying dynamic and static non-verbal behaviors. Dynamic behaviors included approach and avoidance behaviors, preceded or not by a handshake; both dynamic and static behaviors were followed by participants' ratings. Behaviorally, participants showed bias toward their ingroup members, demonstrated by faster/slower reaction times for evaluating ingroup static/approach behaviors, respectively. At the neural level, despite overall similar responses in the action observation network to ingroup and outgroup encounters, the medial prefrontal cortex showed dissociable activation, possibly reflecting spontaneous processing of ingroup static behaviors and positive evaluations of ingroup approach behaviors. The anterior cingulate and superior frontal cortices also showed sensitivity to race, reflected in coordinated and reduced activation for observing ingroup static behaviors. Finally, the posterior superior temporal sulcus showed uniquely increased activity to observing ingroup handshakes. These findings shed light on the mechanisms of racial ingroup bias in observing social encounters, and have implications for understanding factors related to successful interactions with individuals from diverse backgrounds.

Dissociating neural markers of stimulus memorability and subjective recognition during episodic retrieval.

PubMed

Bainbridge, Wilma A; Rissman, Jesse

2018-06-06

While much of memory research takes an observer-centric focus looking at participant performance, recent work has pinpointed important item-centric effects on memory, or how intrinsically memorable a given stimulus is. However, little is known about the neural correlates of memorability during memory retrieval, or how such correlates relate to subjective memory behavior. Here, stimuli and blood-oxygen-level dependent data from a prior functional magnetic resonance imaging (fMRI) study were reanalyzed using a memorability-based framework. In that study, sixteen participants studied 200 novel face images and were scanned while making recognition memory judgments on those faces, interspersed with 200 unstudied faces. In the current investigation, memorability scores for those stimuli were obtained through an online crowd-sourced (N = 740) continuous recognition test that measured each image's corrected recognition rate. Representational similarity analyses were conducted across the brain to identify regions wherein neural pattern similarity tracked item-specific effects (stimulus memorability) versus observer-specific effects (individual memory performance). We find two non-overlapping sets of regions, with memorability-related information predominantly represented within ventral and medial temporal regions and memory retrieval outcome-related information within fronto-parietal regions. These memorability-based effects persist regardless of image history, implying that coding of stimulus memorability may be a continuous and automatic perceptual process.

Neural Representations of Natural and Scrambled Movies Progressively Change from Rat Striate to Temporal Cortex

PubMed Central

Vinken, Kasper; Van den Bergh, Gert; Vermaercke, Ben; Op de Beeck, Hans P.

2016-01-01

In recent years, the rodent has come forward as a candidate model for investigating higher level visual abilities such as object vision. This view has been backed up substantially by evidence from behavioral studies that show rats can be trained to express visual object recognition and categorization capabilities. However, almost no studies have investigated the functional properties of rodent extrastriate visual cortex using stimuli that target object vision, leaving a gap compared with the primate literature. Therefore, we recorded single-neuron responses along a proposed ventral pathway in rat visual cortex to investigate hallmarks of primate neural object representations such as preference for intact versus scrambled stimuli and category-selectivity. We presented natural movies containing a rat or no rat as well as their phase-scrambled versions. Population analyses showed increased dissociation in representations of natural versus scrambled stimuli along the targeted stream, but without a clear preference for natural stimuli. Along the measured cortical hierarchy the neural response seemed to be driven increasingly by features that are not V1-like and destroyed by phase-scrambling. However, there was no evidence for category selectivity for the rat versus nonrat distinction. Together, these findings provide insights about differences and commonalities between rodent and primate visual cortex. PMID:27146315

Online neural monitoring of statistical learning

PubMed Central

Batterink, Laura J.; Paller, Ken A.

2017-01-01

The extraction of patterns in the environment plays a critical role in many types of human learning, from motor skills to language acquisition. This process is known as statistical learning. Here we propose that statistical learning has two dissociable components: (1) perceptual binding of individual stimulus units into integrated composites and (2) storing those integrated representations for later use. Statistical learning is typically assessed using post-learning tasks, such that the two components are conflated. Our goal was to characterize the online perceptual component of statistical learning. Participants were exposed to a structured stream of repeating trisyllabic nonsense words and a random syllable stream. Online learning was indexed by an EEG-based measure that quantified neural entrainment at the frequency of the repeating words relative to that of individual syllables. Statistical learning was subsequently assessed using conventional measures in an explicit rating task and a reaction-time task. In the structured stream, neural entrainment to trisyllabic words was higher than in the random stream, increased as a function of exposure to track the progression of learning, and predicted performance on the RT task. These results demonstrate that monitoring this critical component of learning via rhythmic EEG entrainment reveals a gradual acquisition of knowledge whereby novel stimulus sequences are transformed into familiar composites. This online perceptual transformation is a critical component of learning. PMID:28324696

Enhanced neural responses to rule violation in children with autism: a comparison to social exclusion.

PubMed

Bolling, Danielle Z; Pitskel, Naomi B; Deen, Ben; Crowley, Michael J; McPartland, James C; Kaiser, Martha D; Wyk, Brent C Vander; Wu, Jia; Mayes, Linda C; Pelphrey, Kevin A

2011-07-01

The present study aimed to explore the neural correlates of two characteristic deficits in autism spectrum disorders (ASD); social impairment and restricted, repetitive behavior patterns. To this end, we used comparable experiences of social exclusion and rule violation to probe potentially atypical neural networks in ASD. In children and adolescents with and without ASD, we used the interactive ball-toss game (Cyberball) to elicit social exclusion and a comparable game (Cybershape) to elicit a non-exclusive rule violation. Using functional magnetic resonance imaging (fMRI), we identified group differences in brain responses to social exclusion and rule violation. Though both groups reported equal distress following exclusion, the right insula and ventral anterior cingulate cortex were hypoactive during exclusion in children with ASD. In rule violation, right insula and dorsal prefrontal cortex were hyperactive in ASD. Right insula showed a dissociation in activation; it was hypoactive to social exclusion and hyperactive to rule violation in the ASD group. Further probed, different regions of right insula were modulated in each game, highlighting differences in regional specificity for which subsequent analyses revealed differences in patterns of functional connectivity. These results demonstrate neurobiological differences in processing social exclusion and rule violation in children with ASD.

Neural bases of prospective memory: a meta-analysis and the "Attention to Delayed Intention" (AtoDI) model.

PubMed

Cona, Giorgia; Scarpazza, Cristina; Sartori, Giuseppe; Moscovitch, Morris; Bisiacchi, Patrizia Silvia

2015-05-01

Remembering to realize delayed intentions is a multi-phase process, labelled as prospective memory (PM), and involves a plurality of neural networks. The present study utilized the activation likelihood estimation method of meta-analysis to provide a complete overview of the brain regions that are consistently activated in each PM phase. We formulated the 'Attention to Delayed Intention' (AtoDI) model to explain the neural dissociation found between intention maintenance and retrieval phases. The dorsal frontoparietal network is involved mainly in the maintenance phase and seems to mediate the strategic monitoring processes, such as the allocation of top-down attention both towards external stimuli, to monitor for the occurrence of the PM cues, and to internal memory contents, to maintain the intention active in memory. The ventral frontoparietal network is recruited in the retrieval phase and might subserve the bottom-up attention captured externally by the PM cues and, internally, by the intention stored in memory. Together with other brain regions (i.e., insula and posterior cingulate cortex), the ventral frontoparietal network would support the spontaneous retrieval processes. The functional contribution of the anterior prefrontal cortex is discussed extensively for each PM phase. Copyright © 2015 Elsevier Ltd. All rights reserved.

Neural Correlates of Explicit Social Judgments on Vocal Stimuli

PubMed Central

Hensel, Lukas; Bzdok, Danilo; Müller, Veronika I.; Zilles, Karl; Eickhoff, Simon B.

2015-01-01

Functional neuroimaging research on the neural basis of social evaluation has traditionally focused on face perception paradigms. Thus, little is known about the neurobiology of social evaluation processes based on auditory cues, such as voices. To investigate the top-down effects of social trait judgments on voices, hemodynamic responses of 44 healthy participants were measured during social trait (trustworthiness [TR] and attractiveness [AT]), emotional (happiness, HA), and cognitive (age, AG) voice judgments. Relative to HA and AG judgments, TR and AT judgments both engaged the bilateral inferior parietal cortex (IPC; area PGa) and the dorsomedial prefrontal cortex (dmPFC) extending into the perigenual anterior cingulate cortex. This dmPFC activation overlapped with previously reported areas specifically involved in social judgments on ‘faces.’ Moreover, social trait judgments were expected to share neural correlates with emotional HA and cognitive AG judgments. Comparison of effects pertaining to social, social–emotional, and social–cognitive appraisal processes revealed a dissociation of the left IPC into 3 functional subregions assigned to distinct cytoarchitectonic subdivisions. In total, the dmPFC is proposed to assume a central role in social attribution processes across sensory qualities. In social judgments on voices, IPC activity shifts from rostral processing of more emotional judgment facets to caudal processing of more cognitive judgment facets. PMID:24243619

Unity and diversity of executive functions: Individual differences as a window on cognitive structure.

PubMed

Friedman, Naomi P; Miyake, Akira

2017-01-01

Executive functions (EFs) are high-level cognitive processes, often associated with the frontal lobes, that control lower level processes in the service of goal-directed behavior. They include abilities such as response inhibition, interference control, working memory updating, and set shifting. EFs show a general pattern of shared but distinct functions, a pattern described as "unity and diversity". We review studies of EF unity and diversity at the behavioral and genetic levels, focusing on studies of normal individual differences and what they reveal about the functional organization of these cognitive abilities. In particular, we review evidence that across multiple ages and populations, commonly studied EFs (a) are robustly correlated but separable when measured with latent variables; (b) are not the same as general intelligence or g; (c) are highly heritable at the latent level and seemingly also highly polygenic; and (d) activate both common and specific neural areas and can be linked to individual differences in neural activation, volume, and connectivity. We highlight how considering individual differences at the behavioral and neural levels can add considerable insight to the investigation of the functional organization of the brain, and conclude with some key points about individual differences to consider when interpreting neuropsychological patterns of dissociation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Dissociating neural variability related to stimulus quality and response times in perceptual decision-making.

PubMed

Bode, Stefan; Bennett, Daniel; Sewell, David K; Paton, Bryan; Egan, Gary F; Smith, Philip L; Murawski, Carsten

2018-03-01

According to sequential sampling models, perceptual decision-making is based on accumulation of noisy evidence towards a decision threshold. The speed with which a decision is reached is determined by both the quality of incoming sensory information and random trial-by-trial variability in the encoded stimulus representations. To investigate those decision dynamics at the neural level, participants made perceptual decisions while functional magnetic resonance imaging (fMRI) was conducted. On each trial, participants judged whether an image presented under conditions of high, medium, or low visual noise showed a piano or a chair. Higher stimulus quality (lower visual noise) was associated with increased activation in bilateral medial occipito-temporal cortex and ventral striatum. Lower stimulus quality was related to stronger activation in posterior parietal cortex (PPC) and dorsolateral prefrontal cortex (DLPFC). When stimulus quality was fixed, faster response times were associated with a positive parametric modulation of activation in medial prefrontal and orbitofrontal cortex, while slower response times were again related to more activation in PPC, DLPFC and insula. Our results suggest that distinct neural networks were sensitive to the quality of stimulus information, and to trial-to-trial variability in the encoded stimulus representations, but that reaching a decision was a consequence of their joint activity. Copyright © 2018 Elsevier Ltd. All rights reserved.

Neural Correlates of Racial Ingroup Bias in Observing Computer-Animated Social Encounters

PubMed Central

Katsumi, Yuta; Dolcos, Sanda

2018-01-01

Despite evidence for the role of group membership in the neural correlates of social cognition, the mechanisms associated with processing non-verbal behaviors displayed by racially ingroup vs. outgroup members remain unclear. Here, 20 Caucasian participants underwent fMRI recording while observing social encounters with ingroup and outgroup characters displaying dynamic and static non-verbal behaviors. Dynamic behaviors included approach and avoidance behaviors, preceded or not by a handshake; both dynamic and static behaviors were followed by participants’ ratings. Behaviorally, participants showed bias toward their ingroup members, demonstrated by faster/slower reaction times for evaluating ingroup static/approach behaviors, respectively. At the neural level, despite overall similar responses in the action observation network to ingroup and outgroup encounters, the medial prefrontal cortex showed dissociable activation, possibly reflecting spontaneous processing of ingroup static behaviors and positive evaluations of ingroup approach behaviors. The anterior cingulate and superior frontal cortices also showed sensitivity to race, reflected in coordinated and reduced activation for observing ingroup static behaviors. Finally, the posterior superior temporal sulcus showed uniquely increased activity to observing ingroup handshakes. These findings shed light on the mechanisms of racial ingroup bias in observing social encounters, and have implications for understanding factors related to successful interactions with individuals from diverse backgrounds. PMID:29354042

Deconstruction of spatial integrity in visual stimulus detected by modulation of synchronized activity in cat visual cortex.

PubMed

Zhou, Zhiyi; Bernard, Melanie R; Bonds, A B

2008-04-02

Spatiotemporal relationships among contour segments can influence synchronization of neural responses in the primary visual cortex. We performed a systematic study to dissociate the impact of spatial and temporal factors in the signaling of contour integration via synchrony. In addition, we characterized the temporal evolution of this process to clarify potential underlying mechanisms. With a 10 x 10 microelectrode array, we recorded the simultaneous activity of multiple cells in the cat primary visual cortex while stimulating with drifting sine-wave gratings. We preserved temporal integrity and systematically degraded spatial integrity of the sine-wave gratings by adding spatial noise. Neural synchronization was analyzed in the time and frequency domains by conducting cross-correlation and coherence analyses. The general association between neural spike trains depends strongly on spatial integrity, with coherence in the gamma band (35-70 Hz) showing greater sensitivity to the change of spatial structure than other frequency bands. Analysis of the temporal dynamics of synchronization in both time and frequency domains suggests that spike timing synchronization is triggered nearly instantaneously by coherent structure in the stimuli, whereas frequency-specific oscillatory components develop more slowly, presumably through network interactions. Our results suggest that, whereas temporal integrity is required for the generation of synchrony, spatial integrity is critical in triggering subsequent gamma band synchronization.

The importance of actions and the worth of an object: dissociable neural systems representing core value and economic value.

PubMed

Brosch, Tobias; Coppin, Géraldine; Schwartz, Sophie; Sander, David

2012-06-01

Neuroeconomic research has delineated neural regions involved in the computation of value, referring to a currency for concrete choices and decisions ('economic value'). Research in psychology and sociology, on the other hand, uses the term 'value' to describe motivational constructs that guide choices and behaviors across situations ('core value'). As a first step towards an integration of these literatures, we compared the neural regions computing economic value and core value. Replicating previous work, economic value computations activated a network centered on medial orbitofrontal cortex. Core value computations activated medial prefrontal cortex, a region involved in the processing of self-relevant information and dorsal striatum, involved in action selection. Core value ratings correlated with activity in precuneus and anterior prefrontal cortex, potentially reflecting the degree to which a core value is perceived as internalized part of one's self-concept. Distributed activation pattern in insula and ACC allowed differentiating individual core value types. These patterns may represent evaluation profiles reflecting prototypical fundamental concerns expressed in the core value types. Our findings suggest mechanisms by which core values, as motivationally important long-term goals anchored in the self-schema, may have the behavioral power to drive decisions and behaviors in the absence of immediately rewarding behavioral options.

[Investigation of neural stem cell-derived donor contribution in the inner ear following blastocyst injection].

PubMed

Volkenstein, S; Brors, D; Hansen, S; Mlynski, R; Dinger, T C; Müller, A M; Dazert, S

2008-03-01

Utilising the enormous proliferation and multi-lineage differentiation potentials of somatic stem cells represents a possible therapeutical strategy for diseases of non-regenerative tissues like the inner ear. In the current study, the possibility of murine neural stem cells to contribute to the developing inner ear following blastocyst injection was investigated. Fetal brain-derived neural stem cells from the embryonic day 14 cortex of male mice were isolated and expanded for four weeks in neurobasal media supplemented with bFGF and EGF. Neural stem cells of male animals were harvested, injected into blastocysts and the blastocysts were transferred into pseudo-pregnant foster animals. Each blastocyst was injected with 5-15 microspheres growing from single cell suspension from neurospheres dissociated the day before. The resulting mice were investigated six months POST PARTUM for the presence of donor cells. Brainstem evoked response audiometry (BERA) was performed in six animals. To visualize donor cells Lac-Z staining was performed on sliced cochleas of two animals. In addition, the cochleas of four female animals were isolated and genomic DNA of the entire cochlea was analyzed for donor contribution by Y-chromosome-specific PCR. All animals had normal thresholds in brainstem evoked response audiometry. The male-specific PCR product indicating the presence of male donor cells were detected in the cochleas of three of the four female animals investigated. In two animals, male donor cells were detected unilateral, in one animal bilateral. The results suggest that descendants of neural stem cells are detectable in the inner ear after injection into blastocysts and possess the ability to integrate into the developing inner ear without obvious loss in hearing function.

Computerised working memory based cognitive remediation therapy does not affect Reading the Mind in the Eyes test performance or neural activity during a Facial Emotion Recognition test in psychosis.

PubMed

Mothersill, David; Dillon, Rachael; Hargreaves, April; Castorina, Marco; Furey, Emilia; Fagan, Andrew J; Meaney, James F; Fitzmaurice, Brian; Hallahan, Brian; McDonald, Colm; Wykes, Til; Corvin, Aiden; Robertson, Ian H; Donohoe, Gary

2018-05-27

Working memory based cognitive remediation therapy (CT) for psychosis has recently been associated with broad improvements in performance on untrained tasks measuring working memory, episodic memory and IQ, and changes in associated brain regions. However, it is unclear if these improvements transfer to the domain of social cognition and neural activity related to performance on social cognitive tasks. We examined performance on the Reading the Mind in the Eyes test (Eyes test) in a large sample of participants with psychosis who underwent working memory based CT (N = 43) compared to a Control Group of participants with psychosis (N = 35). In a subset of this sample, we used functional magnetic resonance imaging (fMRI) to examine changes in neural activity during a facial emotion recognition task in participants who underwent CT (N = 15) compared to a Control Group (N = 15). No significant effects of CT were observed on Eyes test performance or on neural activity during facial emotion recognition, either at p<0.05 family-wise error, or at a p<0.001 uncorrected threshold, within a priori social cognitive regions of interest. This study suggests that working memory based CT does not significantly impact an aspect of social cognition which was measured behaviourally and neurally. It provides further evidence that deficits in the ability to decode mental state from facial expressions are dissociable from working memory deficits, and suggests that future CT programs should target social cognition in addition to working memory for the purposes of further enhancing social function. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Searching for Cross-Diagnostic Convergence: Neural Mechanisms Governing Excitation and Inhibition Balance in Schizophrenia and Autism Spectrum Disorders.

PubMed

Foss-Feig, Jennifer H; Adkinson, Brendan D; Ji, Jie Lisa; Yang, Genevieve; Srihari, Vinod H; McPartland, James C; Krystal, John H; Murray, John D; Anticevic, Alan

2017-05-15

Recent theoretical accounts have proposed excitation and inhibition (E/I) imbalance as a possible mechanistic, network-level hypothesis underlying neural and behavioral dysfunction across neurodevelopmental disorders, particularly autism spectrum disorder (ASD) and schizophrenia (SCZ). These two disorders share some overlap in their clinical presentation as well as convergence in their underlying genes and neurobiology. However, there are also clear points of dissociation in terms of phenotypes and putatively affected neural circuitry. We highlight emerging work from the clinical neuroscience literature examining neural correlates of E/I imbalance across children and adults with ASD and adults with both chronic and early-course SCZ. We discuss findings from diverse neuroimaging studies across distinct modalities, conducted with electroencephalography, magnetoencephalography, proton magnetic resonance spectroscopy, and functional magnetic resonance imaging, including effects observed both during task and at rest. Throughout this review, we discuss points of convergence and divergence in the ASD and SCZ literature, with a focus on disruptions in neural E/I balance. We also consider these findings in relation to predictions generated by theoretical neuroscience, particularly computational models predicting E/I imbalance across disorders. Finally, we discuss how human noninvasive neuroimaging can benefit from pharmacological challenge studies to reveal mechanisms in ASD and SCZ. Collectively, we attempt to shed light on shared and divergent neuroimaging effects across disorders with the goal of informing future research examining the mechanisms underlying the E/I imbalance hypothesis across neurodevelopmental disorders. We posit that such translational efforts are vital to facilitate development of neurobiologically informed treatment strategies across neuropsychiatric conditions. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Folic Acid Food Fortification—Its History, Effect, Concerns, and Future Directions

PubMed Central

Crider, Krista S.; Bailey, Lynn B.; Berry, Robert J.

2011-01-01

Periconceptional intake of folic acid is known to reduce a woman’s risk of having an infant affected by a neural tube birth defect (NTD). National programs to mandate fortification of food with folic acid have reduced the prevalence of NTDs worldwide. Uncertainty surrounding possible unintended consequences has led to concerns about higher folic acid intake and food fortification programs. This uncertainty emphasizes the need to continually monitor fortification programs for accurate measures of their effect and the ability to address concerns as they arise. This review highlights the history, effect, concerns, and future directions of folic acid food fortification programs. PMID:22254102