Temporally diverse firing patterns in olfactory receptor neurons underlie spatiotemporal neural codes for odors

PubMed Central

Raman, Baranidharan; Joseph, Joby; Tang, Jeff; Stopfer, Mark

2010-01-01

Odorants are represented as spatiotemporal patterns of spikes in neurons of the antennal lobe (AL, insects) and olfactory bulb (OB, vertebrates). These response patterns have been thought to arise primarily from interactions within the AL/OB, an idea supported, in part, by the assumption that olfactory receptor neurons (ORNs) respond to odorants with simple firing patterns. However, activating the AL directly with simple pulses of current evoked responses in AL neurons that were much less diverse, complex, and enduring than responses elicited by odorants. Similarly, models of the AL driven by simplistic inputs generated relatively simple output. How then are dynamic neural codes for odors generated? Consistent with recent results from several other species, our recordings from locust ORNs showed a great diversity of temporal structure. Further, we found that, viewed as a population, many response features of ORNs were remarkably similar to those observed within the AL. Using a set of computational models constrained by our electrophysiological recordings, we found that the temporal heterogeneity of responses of ORNs critically underlies the generation of spatiotemporal odor codes in the AL. A test then performed in vivo confirmed that, given temporally homogeneous input, the AL cannot create diverse spatiotemporal patterns on its own; however, given temporally heterogeneous input, the AL generated realistic firing patterns. Finally, given the temporally structured input provided by ORNs, we clarified several separate, additional contributions of the AL to olfactory information processing. Thus, our results demonstrate the origin and subsequent reformatting of spatiotemporal neural codes for odors. PMID:20147528

Holocene forest dynamics in central and western Mediterranean: periodicity, spatio-temporal patterns and climate influence.

PubMed

Di Rita, Federico; Fletcher, William J; Aranbarri, Josu; Margaritelli, Giulia; Lirer, Fabrizio; Magri, Donatella

2018-06-12

It is well-known that the Holocene exhibits a millennial-scale climate variability. However, its periodicity, spatio-temporal patterns and underlying processes are not fully deciphered yet. Here we focus on the central and western Mediterranean. We show that recurrent forest declines from the Gulf of Gaeta (central Tyrrhenian Sea) reveal a 1860-yr periodicity, consistent with a ca. 1800-yr climate fluctuation induced by large-scale changes in climate modes, linked to solar activity and/or AMOC intensity. We show that recurrent forest declines and dry events are also recorded in several pollen and palaeohydrological proxy-records in the south-central Mediterranean. We found coeval events also in several palaeohydrological records from the south-western Mediterranean, which however show generally wet climate conditions, indicating a spatio-temporal hydrological pattern opposite to the south-central Mediterranean and suggesting that different expressions of climate modes occurred in the two regions at the same time. We propose that these opposite hydroclimate regimes point to a complex interplay of the prevailing or predominant phases of NAO-like circulation, East Atlantic pattern, and extension and location of the North African anticyclone. At a larger geographical scale, displacements of the ITCZ, modulated by solar activity and/or AMOC intensity, may have also indirectly influenced the observed pattern.

The spatiotemporal pattern of Src activation at lipid rafts revealed by diffusion-corrected FRET imaging.

PubMed

Lu, Shaoying; Ouyang, Mingxing; Seong, Jihye; Zhang, Jin; Chien, Shu; Wang, Yingxiao

2008-07-25

Genetically encoded biosensors based on fluorescence resonance energy transfer (FRET) have been widely applied to visualize the molecular activity in live cells with high spatiotemporal resolution. However, the rapid diffusion of biosensor proteins hinders a precise reconstruction of the actual molecular activation map. Based on fluorescence recovery after photobleaching (FRAP) experiments, we have developed a finite element (FE) method to analyze, simulate, and subtract the diffusion effect of mobile biosensors. This method has been applied to analyze the mobility of Src FRET biosensors engineered to reside at different subcompartments in live cells. The results indicate that the Src biosensor located in the cytoplasm moves 4-8 folds faster (0.93+/-0.06 microm(2)/sec) than those anchored on different compartments in plasma membrane (at lipid raft: 0.11+/-0.01 microm(2)/sec and outside: 0.18+/-0.02 microm(2)/sec). The mobility of biosensor at lipid rafts is slower than that outside of lipid rafts and is dominated by two-dimensional diffusion. When this diffusion effect was subtracted from the FRET ratio images, high Src activity at lipid rafts was observed at clustered regions proximal to the cell periphery, which remained relatively stationary upon epidermal growth factor (EGF) stimulation. This result suggests that EGF induced a Src activation at lipid rafts with well-coordinated spatiotemporal patterns. Our FE-based method also provides an integrated platform of image analysis for studying molecular mobility and reconstructing the spatiotemporal activation maps of signaling molecules in live cells.

DNA-Demethylase Regulated Genes Show Methylation-Independent Spatiotemporal Expression Patterns

PubMed Central

Schumann, Ulrike; Lee, Joanne; Kazan, Kemal; Ayliffe, Michael; Wang, Ming-Bo

2017-01-01

Recent research has indicated that a subset of defense-related genes is downregulated in the Arabidopsis DNA demethylase triple mutant rdd (ros1 dml2 dml3) resulting in increased susceptibility to the fungal pathogen Fusarium oxysporum. In rdd plants these downregulated genes contain hypermethylated transposable element sequences (TE) in their promoters, suggesting that this methylation represses gene expression in the mutant and that these sequences are actively demethylated in wild-type plants to maintain gene expression. In this study, the tissue-specific and pathogen-inducible expression patterns of rdd-downregulated genes were investigated and the individual role of ROS1, DML2, and DML3 demethylases in these spatiotemporal regulation patterns was determined. Large differences in defense gene expression were observed between pathogen-infected and uninfected tissues and between root and shoot tissues in both WT and rdd plants, however, only subtle changes in promoter TE methylation patterns occurred. Therefore, while TE hypermethylation caused decreased gene expression in rdd plants it did not dramatically effect spatiotemporal gene regulation, suggesting that this latter regulation is largely methylation independent. Analysis of ros1-3, dml2-1, and dml3-1 single gene mutant lines showed that promoter TE hypermethylation and defense-related gene repression was predominantly, but not exclusively, due to loss of ROS1 activity. These data demonstrate that DNA demethylation of TE sequences, largely by ROS1, promotes defense-related gene expression but does not control spatiotemporal expression in Arabidopsis. Summary: Ros1-mediated DNA demethylation of promoter transposable elements is essential for activation of defense-related gene expression in response to fungal infection in Arabidopsis thaliana. PMID:28894455

Spatio-temporal Organization During Ventricular Fibrillation in the Human Heart.

PubMed

Robson, Jinny; Aram, Parham; Nash, Martyn P; Bradley, Chris P; Hayward, Martin; Paterson, David J; Taggart, Peter; Clayton, Richard H; Kadirkamanathan, Visakan

2018-06-01

In this paper, we present a novel approach to quantify the spatio-temporal organization of electrical activation during human ventricular fibrillation (VF). We propose three different methods based on correlation analysis, graph theoretical measures and hierarchical clustering. Using the proposed approach, we quantified the level of spatio-temporal organization during three episodes of VF in ten patients, recorded using multi-electrode epicardial recordings with 30 s coronary perfusion, 150 s global myocardial ischaemia and 30 s reflow. Our findings show a steady decline in spatio-temporal organization from the onset of VF with coronary perfusion. We observed transient increases in spatio-temporal organization during global myocardial ischaemia. However, the decline in spatio-temporal organization continued during reflow. Our results were consistent across all patients, and were consistent with the numbers of phase singularities. Our findings show that the complex spatio-temporal patterns can be studied using complex network analysis.

Mining patterns in persistent surveillance systems with smart query and visual analytics

NASA Astrophysics Data System (ADS)

Habibi, Mohammad S.; Shirkhodaie, Amir

2013-05-01

In Persistent Surveillance Systems (PSS) the ability to detect and characterize events geospatially help take pre-emptive steps to counter adversary's actions. Interactive Visual Analytic (VA) model offers this platform for pattern investigation and reasoning to comprehend and/or predict such occurrences. The need for identifying and offsetting these threats requires collecting information from diverse sources, which brings with it increasingly abstract data. These abstract semantic data have a degree of inherent uncertainty and imprecision, and require a method for their filtration before being processed further. In this paper, we have introduced an approach based on Vector Space Modeling (VSM) technique for classification of spatiotemporal sequential patterns of group activities. The feature vectors consist of an array of attributes extracted from generated sensors semantic annotated messages. To facilitate proper similarity matching and detection of time-varying spatiotemporal patterns, a Temporal-Dynamic Time Warping (DTW) method with Gaussian Mixture Model (GMM) for Expectation Maximization (EM) is introduced. DTW is intended for detection of event patterns from neighborhood-proximity semantic frames derived from established ontology. GMM with EM, on the other hand, is employed as a Bayesian probabilistic model to estimated probability of events associated with a detected spatiotemporal pattern. In this paper, we present a new visual analytic tool for testing and evaluation group activities detected under this control scheme. Experimental results demonstrate the effectiveness of proposed approach for discovery and matching of subsequences within sequentially generated patterns space of our experiments.

Composite catalyst surfaces: Effect of inert and active heterogeneities on pattern formation

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

Baer, M.; Bangia, A.K.; Kevrekidis, I.G.

1996-12-05

Spatiotemporal dynamics in reaction-diffusion systems can be altered through the properties (reactivity, diffusivity) of the medium in which they occur. We construct active heterogeneous media (composite catalytic surfaces with inert as well as active illusions) using microelectronics fabrication techniques and study the spatiotemporal dynamics of heterogeneous catalytic reactions on these catalysts. In parallel, we perform simulations as well as numerical stability and bifurcation analysis of these patterns using mechanistic models. At the limit of large heterogeneity `grain size` (compared to the wavelength of spontaneously arising structures) the interaction patterns with inert or active boundaries dominates (e.g., pinning, transmission, and boundarymore » breakup of spirals, interaction of pulses with corners, `pacemaker` effects). At the opposite limit of very small or very finely distributed heterogeneity, effective behavior is observed (slight modulation of pulses, nearly uniform oscillations, effective spirals). Some representative studies of transitions between the two limits are presented. 48 refs., 11 figs.« less

Instabilities and spatiotemporal patterns behind predator invasions with nonlocal prey competition.

PubMed

Merchant, Sandra M; Nagata, Wayne

2011-12-01

We study the influence of nonlocal intraspecies prey competition on the spatiotemporal patterns arising behind predator invasions in two oscillatory reaction-diffusion integro-differential models. We use three common types of integral kernels as well as develop a caricature system, to describe the influence of the standard deviation and kurtosis of the kernel function on the patterns observed. We find that nonlocal competition can destabilize the spatially homogeneous state behind the invasion and lead to the formation of complex spatiotemporal patterns, including stationary spatially periodic patterns, wave trains and irregular spatiotemporal oscillations. In addition, the caricature system illustrates how large standard deviation and low kurtosis facilitate the formation of these spatiotemporal patterns. This suggests that nonlocal competition may be an important mechanism underlying spatial pattern formation, particularly in systems where the competition between individuals varies over space in a platykurtic manner. Copyright © 2011 Elsevier Inc. All rights reserved.

Spatiotemporal relations of primary sensorimotor and secondary motor activation patterns mapped by NIR imaging

PubMed Central

Khan, Bilal; Chand, Pankaj; Alexandrakis, George

2011-01-01

Functional near infrared (fNIR) imaging was used to identify spatiotemporal relations between spatially distinct cortical regions activated during various hand and arm motion protocols. Imaging was performed over a field of view (FOV, 12 x 8.4 cm) including the secondary motor, primary sensorimotor, and the posterior parietal cortices over a single brain hemisphere. This is a more extended FOV than typically used in current fNIR studies. Three subjects performed four motor tasks that induced activation over this extended FOV. The tasks included card flipping (pronation and supination) that, to our knowledge, has not been performed in previous functional magnetic resonance imaging (fMRI) or fNIR studies. An earlier rise and a longer duration of the hemodynamic activation response were found in tasks requiring increased physical or mental effort. Additionally, analysis of activation images by cluster component analysis (CCA) demonstrated that cortical regions can be grouped into clusters, which can be adjacent or distant from each other, that have similar temporal activation patterns depending on whether the performed motor task is guided by visual or tactile feedback. These analyses highlight the future potential of fNIR imaging to tackle clinically relevant questions regarding the spatiotemporal relations between different sensorimotor cortex regions, e.g. ones involved in the rehabilitation response to motor impairments. PMID:22162826

Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA.

PubMed

Cao, Xiaodong; MacNaughton, Piers; Deng, Zhengyi; Yin, Jie; Zhang, Xi; Allen, Joseph G

2018-02-02

Twitter provides a rich database of spatiotemporal information about users who broadcast their real-time opinions, sentiment, and activities. In this paper, we sought to investigate the holistic influence of land use and time period on public sentiment. A total of 880,937 tweets posted by 26,060 active users were collected across Massachusetts (MA), USA, through 31 November 2012 to 3 June 2013. The IBM Watson Alchemy API (application program interface) was employed to quantify the sentiment scores conveyed by tweets on a large scale. Then we statistically analyzed the sentiment scores across different spaces and times. A multivariate linear mixed-effects model was used to quantify the fixed effects of land use and the time period on the variations in sentiment scores, considering the clustering effect of users. The results exposed clear spatiotemporal patterns of users' sentiment. Higher sentiment scores were mainly observed in the commercial and public areas, during the noon/evening and on weekends. Our findings suggest that social media outputs can be used to better understand the spatial and temporal patterns of public happiness and well-being in cities and regions.

Using Twitter to Better Understand the Spatiotemporal Patterns of Public Sentiment: A Case Study in Massachusetts, USA

PubMed Central

MacNaughton, Piers; Deng, Zhengyi; Yin, Jie; Zhang, Xi; Allen, Joseph G.

2018-01-01

Twitter provides a rich database of spatiotemporal information about users who broadcast their real-time opinions, sentiment, and activities. In this paper, we sought to investigate the holistic influence of land use and time period on public sentiment. A total of 880,937 tweets posted by 26,060 active users were collected across Massachusetts (MA), USA, through 31 November 2012 to 3 June 2013. The IBM Watson Alchemy API (application program interface) was employed to quantify the sentiment scores conveyed by tweets on a large scale. Then we statistically analyzed the sentiment scores across different spaces and times. A multivariate linear mixed-effects model was used to quantify the fixed effects of land use and the time period on the variations in sentiment scores, considering the clustering effect of users. The results exposed clear spatiotemporal patterns of users’ sentiment. Higher sentiment scores were mainly observed in the commercial and public areas, during the noon/evening and on weekends. Our findings suggest that social media outputs can be used to better understand the spatial and temporal patterns of public happiness and well-being in cities and regions. PMID:29393869

Stability Switches, Hopf Bifurcations, and Spatio-temporal Patterns in a Delayed Neural Model with Bidirectional Coupling

NASA Astrophysics Data System (ADS)

Song, Yongli; Zhang, Tonghua; Tadé, Moses O.

2009-12-01

The dynamical behavior of a delayed neural network with bi-directional coupling is investigated by taking the delay as the bifurcating parameter. Some parameter regions are given for conditional/absolute stability and Hopf bifurcations by using the theory of functional differential equations. As the propagation time delay in the coupling varies, stability switches for the trivial solution are found. Conditions ensuring the stability and direction of the Hopf bifurcation are determined by applying the normal form theory and the center manifold theorem. We also discuss the spatio-temporal patterns of bifurcating periodic oscillations by using the symmetric bifurcation theory of delay differential equations combined with representation theory of Lie groups. In particular, we obtain that the spatio-temporal patterns of bifurcating periodic oscillations will alternate according to the change of the propagation time delay in the coupling, i.e., different ranges of delays correspond to different patterns of neural activities. Numerical simulations are given to illustrate the obtained results and show the existence of bursts in some interval of the time for large enough delay.

Dynamical Properties of Transient Spatio-Temporal Patterns in Bacterial Colony of Proteus mirabilis

NASA Astrophysics Data System (ADS)

Watanabe, Kazuhiko; Wakita, Jun-ichi; Itoh, Hiroto; Shimada, Hirotoshi; Kurosu, Sayuri; Ikeda, Takemasa; Yamazaki, Yoshihiro; Matsuyama, Tohey; Matsushita, Mitsugu

2002-02-01

Spatio-temporal patterns emerged inside a colony of bacterial species Proteus mirabilis on the surface of nutrient-rich semisolid agar medium have been investigated. We observed various patterns composed of the following basic types: propagating stripe, propagating stripe with fixed dislocation, expanding and shrinking target, and rotating spiral. The remarkable point is that the pattern changes immediately when we alter the position for observation, but it returns to the original if we restore the observing position within a few minutes. We further investigated mesoscopic and microscopic properties of the spatio-temporal patterns. It turned out that whenever the spatio-temporal patterns are observed in a colony, the areas are composed of two superimposed monolayers of elongated bacterial cells. In each area they are aligned almost parallel with each other like a two-dimensional nematic liquid crystal, and move collectively and independently of another layer. It has been found that the observed spatio-temporal patterns are explained as the moiré effect.

Understanding spatio-temporal strategies of adult zebrafish exploration in the open field test.

PubMed

Stewart, Adam Michael; Gaikwad, Siddharth; Kyzar, Evan; Kalueff, Allan V

2012-04-27

Zebrafish (Danio rerio) are emerging as a useful model organism for neuroscience research. Mounting evidence suggests that various traditional rodent paradigms may be adapted for testing zebrafish behavior. The open field test is a popular rodent test of novelty exploration, recently applied to zebrafish research. To better understand fish novelty behavior, we exposed adult zebrafish to two different open field arenas for 30 min, assessing the amount and temporal patterning of their exploration. While (similar to rodents) zebrafish scale their locomotory activity depending on the size of the tank, the temporal patterning of their activity was independent of arena size. These observations strikingly parallel similar rodent behaviors, suggesting that spatio-temporal strategies of animal exploration may be evolutionarily conserved across vertebrate species. In addition, we found interesting oscillations in zebrafish exploration, with the per-minute distribution of their horizontal activity demonstrating sinusoidal-like patterns. While such patterning is not reported for rodents and other higher vertebrates, a nonlinear regression analysis confirmed the oscillation patterning of all assessed zebrafish behavioral endpoints in both open field arenas, revealing a potentially important aspect of novelty exploration in lower vertebrates. Copyright © 2012 Elsevier B.V. All rights reserved.

Spatiotemporal Patterns Produced by Bacteria

NASA Astrophysics Data System (ADS)

Shimada, Yuji; Nakahara, Akio; Matsushita, Mitsugu; Matsuyama, Tohey

1995-06-01

Spatiotemporal patterns formed by a bacterial colony of Proteus mirabilis on an agar plate were observed. About half or one hour after the colony spread over the entire surface of the agar medium in a petridish, various patterns including target and spiral patterns appeared. They are very similar to those seen in other dissipative systems, such as chemical oscillations and electrohydrodynamic convective systems. Microscopic observations revealed that the collective motion of bacterial cells is responsible for the formation of these spatiotemporal patterns.

Spatio-Temporal Characteristics of Resident Trip Based on Poi and OD Data of Float CAR in Beijing

NASA Astrophysics Data System (ADS)

Mou, N.; Li, J.; Zhang, L.; Liu, W.; Xu, Y.

2017-09-01

Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according to the characteristics of the taxi trajectory data distributed along the road network, it takes the Voronoi generated by the road nodes as the research unit. This paper proposes a hybrid clustering method - based on grid density, which is used to cluster the OD (origin and destination) data of taxi at different times. Then combining with the POI data of Beijing, this research calculated the density of the POI data in the clustering results, and analyzed the relationship between the activities of residents in different periods and the functional types of the region. The final results showed that the residents were mainly commuting on weekdays. And it found that the distribution of travel density showed a concentric circle of the characteristics, focusing on residential areas and work areas. The results of cluster analysis and POI analysis showed that the residents' travel had experienced the process of "spatial relative dispersion - spatial aggregation - spatial relative dispersion" in one day.

Magnetoencephalography with temporal spread imaging to visualize propagation of epileptic activity.

PubMed

Shibata, Sumiya; Matsuhashi, Masao; Kunieda, Takeharu; Yamao, Yukihiro; Inano, Rika; Kikuchi, Takayuki; Imamura, Hisaji; Takaya, Shigetoshi; Matsumoto, Riki; Ikeda, Akio; Takahashi, Ryosuke; Mima, Tatsuya; Fukuyama, Hidenao; Mikuni, Nobuhiro; Miyamoto, Susumu

2017-05-01

We describe temporal spread imaging (TSI) that can identify the spatiotemporal pattern of epileptic activity using Magnetoencephalography (MEG). A three-dimensional grid of voxels covering the brain is created. The array-gain minimum-variance spatial filter is applied to an interictal spike to estimate the magnitude of the source and the time (Ta) when the magnitude exceeds a predefined threshold at each voxel. This calculation is performed through all spikes. Each voxel has the mean Ta () and spike number (N sp ), which is the number of spikes whose source exceeds the threshold. Then, a random resampling method is used to determine the cutoff value of N sp for the statistically reproducible pattern of the activity. Finally, all the voxels where the source exceeds the threshold reproducibly shown on the MRI with a color scale representing . Four patients with intractable mesial temporal lobe epilepsy (MTLE) were analyzed. In three patients, the common pattern of the overlap between the propagation and the hypometabolism shown by fluorodeoxyglucose-positron emission tomography (FDG-PET) was identified. TSI can visualize statistically reproducible patterns of the temporal and spatial spread of epileptic activity. TSI can assess the statistical significance of the spatiotemporal pattern based on its reproducibility. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Optically triggering spatiotemporally confined GPCR activity in a cell and programming neurite initiation and extension

PubMed Central

Karunarathne, W. K. Ajith; Giri, Lopamudra; Kalyanaraman, Vani; Gautam, N.

2013-01-01

G-protein–coupled receptor (GPCR) activity gradients evoke important cell behavior but there is a dearth of methods to induce such asymmetric signaling in a cell. Here we achieved reversible, rapidly switchable patterns of spatiotemporally restricted GPCR activity in a single cell. We recruited properties of nonrhodopsin opsins—rapid deactivation, distinct spectral tuning, and resistance to bleaching—to activate native Gi, Gq, or Gs signaling in selected regions of a cell. Optical inputs were designed to spatiotemporally control levels of second messengers, IP3, phosphatidylinositol (3,4,5)-triphosphate, and cAMP in a cell. Spectrally selective imaging was accomplished to simultaneously monitor optically evoked molecular and cellular response dynamics. We show that localized optical activation of an opsin-based trigger can induce neurite initiation, phosphatidylinositol (3,4,5)-triphosphate increase, and actin remodeling. Serial optical inputs to neurite tips can refashion early neuron differentiation. Methods here can be widely applied to program GPCR-mediated cell behaviors. PMID:23479634

The Link between Microbial Diversity and Nitrogen Cycling in Marine Sediments Is Modulated by Macrofaunal Bioturbation

PubMed Central

Yazdani Foshtomi, Maryam; Braeckman, Ulrike; Derycke, Sofie; Sapp, Melanie; Van Gansbeke, Dirk; Sabbe, Koen; Willems, Anne; Vincx, Magda; Vanaverbeke, Jan

2015-01-01

Objectives The marine benthic nitrogen cycle is affected by both the presence and activity of macrofauna and the diversity of N-cycling microbes. However, integrated research simultaneously investigating macrofauna, microbes and N-cycling is lacking. We investigated spatio-temporal patterns in microbial community composition and diversity, macrofaunal abundance and their sediment reworking activity, and N-cycling in seven subtidal stations in the Southern North Sea. Spatio-Temporal Patterns of the Microbial Communities Our results indicated that bacteria (total and β-AOB) showed more spatio-temporal variation than archaea (total and AOA) as sedimentation of organic matter and the subsequent changes in the environment had a stronger impact on their community composition and diversity indices in our study area. However, spatio-temporal patterns of total bacterial and β-AOB communities were different and related to the availability of ammonium for the autotrophic β-AOB. Highest bacterial richness and diversity were observed in June at the timing of the phytoplankton bloom deposition, while richness of β-AOB as well as AOA peaked in September. Total archaeal community showed no temporal variation in diversity indices. Macrofauna, Microbes and the Benthic N-Cycle Distance based linear models revealed that, independent from the effect of grain size and the quality and quantity of sediment organic matter, nitrification and N-mineralization were affected by respectively the diversity of metabolically active β-AOB and AOA, and the total bacteria, near the sediment-water interface. Separate models demonstrated a significant and independent effect of macrofaunal activities on community composition and richness of total bacteria, and diversity indices of metabolically active AOA. Diversity of β-AOB was significantly affected by macrofaunal abundance. Our results support the link between microbial biodiversity and ecosystem functioning in marine sediments, and provided broad correlative support for the hypothesis that this relationship is modulated by macrofaunal activity. We hypothesized that the latter effect can be explained by their bioturbating and bio-irrigating activities, increasing the spatial complexity of the biogeochemical environment. PMID:26102286

Mining spatiotemporal patterns of urban dwellers from taxi trajectory data

NASA Astrophysics Data System (ADS)

Mao, Feng; Ji, Minhe; Liu, Ting

2016-06-01

With the widespread adoption of locationaware technology, obtaining long-sequence, massive and high-accuracy spatiotemporal trajectory data of individuals has become increasingly popular in various geographic studies. Trajectory data of taxis, one of the most widely used inner-city travel modes, contain rich information about both road network traffic and travel behavior of passengers. Such data can be used to study the microscopic activity patterns of individuals as well as the macro system of urban spatial structures. This paper focuses on trajectories obtained from GPS-enabled taxis and their applications for mining urban commuting patterns. A novel approach is proposed to discover spatiotemporal patterns of household travel from the taxi trajectory dataset with a large number of point locations. The approach involves three critical steps: spatial clustering of taxi origin-destination (OD) based on urban traffic grids to discover potentially meaningful places, identifying threshold values from statistics of the OD clusters to extract urban jobs-housing structures, and visualization of analytic results to understand the spatial distribution and temporal trends of the revealed urban structures and implied household commuting behavior. A case study with a taxi trajectory dataset in Shanghai, China is presented to demonstrate and evaluate the proposed method.

HOTS: A Hierarchy of Event-Based Time-Surfaces for Pattern Recognition.

PubMed

Lagorce, Xavier; Orchard, Garrick; Galluppi, Francesco; Shi, Bertram E; Benosman, Ryad B

2017-07-01

This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.This paper describes novel event-based spatio-temporal features called time-surfaces and how they can be used to create a hierarchical event-based pattern recognition architecture. Unlike existing hierarchical architectures for pattern recognition, the presented model relies on a time oriented approach to extract spatio-temporal features from the asynchronously acquired dynamics of a visual scene. These dynamics are acquired using biologically inspired frameless asynchronous event-driven vision sensors. Similarly to cortical structures, subsequent layers in our hierarchy extract increasingly abstract features using increasingly large spatio-temporal windows. The central concept is to use the rich temporal information provided by events to create contexts in the form of time-surfaces which represent the recent temporal activity within a local spatial neighborhood. We demonstrate that this concept can robustly be used at all stages of an event-based hierarchical model. First layer feature units operate on groups of pixels, while subsequent layer feature units operate on the output of lower level feature units. We report results on a previously published 36 class character recognition task and a four class canonical dynamic card pip task, achieving near 100 percent accuracy on each. We introduce a new seven class moving face recognition task, achieving 79 percent accuracy.

Comparison of spatiotemporal cortical activation pattern during visual perception of Korean, English, Chinese words: an event-related potential study.

PubMed

Kim, Kyung Hwan; Kim, Ja Hyun

2006-02-20

The aim of this study was to compare spatiotemporal cortical activation patterns during the visual perception of Korean, English, and Chinese words. The comparison of these three languages offers an opportunity to study the effect of written forms on cortical processing of visually presented words, because of partial similarity/difference among words of these languages, and the familiarity of native Koreans with these three languages at the word level. Single-character words and pictograms were excluded from the stimuli in order to activate neuronal circuitries that are involved only in word perception. Since a variety of cerebral processes are sequentially evoked during visual word perception, a high-temporal resolution is required and thus we utilized event-related potential (ERP) obtained from high-density electroencephalograms. The differences and similarities observed from statistical analyses of ERP amplitudes, the correlation between ERP amplitudes and response times, and the patterns of current source density, appear to be in line with demands of visual and semantic analysis resulting from the characteristics of each language, and the expected task difficulties for native Korean subjects.

Neural Sequence Generation Using Spatiotemporal Patterns of Inhibition.

PubMed

Cannon, Jonathan; Kopell, Nancy; Gardner, Timothy; Markowitz, Jeffrey

2015-11-01

Stereotyped sequences of neural activity are thought to underlie reproducible behaviors and cognitive processes ranging from memory recall to arm movement. One of the most prominent theoretical models of neural sequence generation is the synfire chain, in which pulses of synchronized spiking activity propagate robustly along a chain of cells connected by highly redundant feedforward excitation. But recent experimental observations in the avian song production pathway during song generation have shown excitatory activity interacting strongly with the firing patterns of inhibitory neurons, suggesting a process of sequence generation more complex than feedforward excitation. Here we propose a model of sequence generation inspired by these observations in which a pulse travels along a spatially recurrent excitatory chain, passing repeatedly through zones of local feedback inhibition. In this model, synchrony and robust timing are maintained not through redundant excitatory connections, but rather through the interaction between the pulse and the spatiotemporal pattern of inhibition that it creates as it circulates the network. These results suggest that spatially and temporally structured inhibition may play a key role in sequence generation.

Propagating wave and irregular dynamics: Spatiotemporal patterns of cholinergic theta oscillations in neocortex, in vitro

PubMed Central

Bao, Weili; Wu, Jian-young

2010-01-01

Neocortical “theta” oscillation (5- 12 Hz) has been observed in animals and human subjects but little is known about how the oscillation is organized in the cortical intrinsic networks. Here we use voltage-sensitive dye and optical imaging to study a carbachol/bicuculline induced theta (~8 Hz) oscillation in rat neocortical slices. The imaging has large signal-to-noise ratio, allowing us to map the phase distribution over the neocortical tissue during the oscillation. The oscillation was organized as spontaneous epochs and each epoch was composed of a “first spike”, a “regular” period (with relatively stable frequency and amplitude) and an “irregular” period (with variable frequency and amplitude) of oscillations. During each cycle of the regular oscillation one wave of activation propagated horizontally (parallel to the cortical lamina) across the cortical section at a velocity of ~50 mm/sec. Vertically the activity was synchronized through all cortical layers. This pattern of one propagating wave associated with one oscillation cycle was seen during all the regular cycles. The oscillation frequency varied noticeably at two neighboring horizontal locations (330 μm apart), suggesting that the oscillation is locally organized and each local oscillator is about equal or less than 300 μm wide horizontally. During irregular oscillations the spatiotemporal patterns were complex and sometimes the vertical synchronization decomposed, suggesting a de-coupling among local oscillators. Our data suggested that neocortical theta oscillation is sustained by multiple local oscillators. The coupling regime among the oscillators may determine the spatiotemporal pattern and switching between propagating waves and irregular patterns. PMID:12612003

Optogenetically induced spatiotemporal gamma oscillations and neuronal spiking activity in primate motor cortex.

PubMed

Lu, Yao; Truccolo, Wilson; Wagner, Fabien B; Vargas-Irwin, Carlos E; Ozden, Ilker; Zimmermann, Jonas B; May, Travis; Agha, Naubahar S; Wang, Jing; Nurmikko, Arto V

2015-06-01

Transient gamma-band (40-80 Hz) spatiotemporal patterns are hypothesized to play important roles in cortical function. Here we report the direct observation of gamma oscillations as spatiotemporal waves induced by targeted optogenetic stimulation, recorded by intracortical multichannel extracellular techniques in macaque monkeys during their awake resting states. Microelectrode arrays integrating an optical fiber at their center were chronically implanted in primary motor (M1) and ventral premotor (PMv) cortices of two subjects. Targeted brain tissue was transduced with the red-shifted opsin C1V1(T/T). Constant (1-s square pulses) and ramp stimulation induced narrowband gamma oscillations during awake resting states. Recordings across 95 microelectrodes (4 × 4-mm array) enabled us to track the transient gamma spatiotemporal patterns manifested, e.g., as concentric expanding and spiral waves. Gamma oscillations were induced well beyond the light stimulation volume, via network interactions at distal electrode sites, depending on optical power. Despite stimulation-related modulation in spiking rates, neuronal spiking remained highly asynchronous during induced gamma oscillations. In one subject we examined stimulation effects during preparation and execution of a motor task and observed that movement execution largely attenuated optically induced gamma oscillations. Our findings demonstrate that, beyond previously reported induced gamma activity under periodic drive, a prolonged constant stimulus above a certain threshold may carry primate motor cortex network dynamics into gamma oscillations, likely via a Hopf bifurcation. More broadly, the experimental capability in combining microelectrode array recordings and optogenetic stimulation provides an important approach for probing spatiotemporal dynamics in primate cortical networks during various physiological and behavioral conditions.

Optogenetically induced spatiotemporal gamma oscillations and neuronal spiking activity in primate motor cortex

PubMed Central

Lu, Yao; Truccolo, Wilson; Wagner, Fabien B.; Vargas-Irwin, Carlos E.; Ozden, Ilker; Zimmermann, Jonas B.; May, Travis; Agha, Naubahar S.; Wang, Jing

2015-01-01

Transient gamma-band (40–80 Hz) spatiotemporal patterns are hypothesized to play important roles in cortical function. Here we report the direct observation of gamma oscillations as spatiotemporal waves induced by targeted optogenetic stimulation, recorded by intracortical multichannel extracellular techniques in macaque monkeys during their awake resting states. Microelectrode arrays integrating an optical fiber at their center were chronically implanted in primary motor (M1) and ventral premotor (PMv) cortices of two subjects. Targeted brain tissue was transduced with the red-shifted opsin C1V1(T/T). Constant (1-s square pulses) and ramp stimulation induced narrowband gamma oscillations during awake resting states. Recordings across 95 microelectrodes (4 × 4-mm array) enabled us to track the transient gamma spatiotemporal patterns manifested, e.g., as concentric expanding and spiral waves. Gamma oscillations were induced well beyond the light stimulation volume, via network interactions at distal electrode sites, depending on optical power. Despite stimulation-related modulation in spiking rates, neuronal spiking remained highly asynchronous during induced gamma oscillations. In one subject we examined stimulation effects during preparation and execution of a motor task and observed that movement execution largely attenuated optically induced gamma oscillations. Our findings demonstrate that, beyond previously reported induced gamma activity under periodic drive, a prolonged constant stimulus above a certain threshold may carry primate motor cortex network dynamics into gamma oscillations, likely via a Hopf bifurcation. More broadly, the experimental capability in combining microelectrode array recordings and optogenetic stimulation provides an important approach for probing spatiotemporal dynamics in primate cortical networks during various physiological and behavioral conditions. PMID:25761956

Methods, caveats and the future of large-scale microelectrode recordings in the non-human primate

PubMed Central

Dotson, Nicholas M.; Goodell, Baldwin; Salazar, Rodrigo F.; Hoffman, Steven J.; Gray, Charles M.

2015-01-01

Cognitive processes play out on massive brain-wide networks, which produce widely distributed patterns of activity. Capturing these activity patterns requires tools that are able to simultaneously measure activity from many distributed sites with high spatiotemporal resolution. Unfortunately, current techniques with adequate coverage do not provide the requisite spatiotemporal resolution. Large-scale microelectrode recording devices, with dozens to hundreds of microelectrodes capable of simultaneously recording from nearly as many cortical and subcortical areas, provide a potential way to minimize these tradeoffs. However, placing hundreds of microelectrodes into a behaving animal is a highly risky and technically challenging endeavor that has only been pursued by a few groups. Recording activity from multiple electrodes simultaneously also introduces several statistical and conceptual dilemmas, such as the multiple comparisons problem and the uncontrolled stimulus response problem. In this perspective article, we discuss some of the techniques that we, and others, have developed for collecting and analyzing large-scale data sets, and address the future of this emerging field. PMID:26578906

Biophysics of object segmentation in a collision-detecting neuron

PubMed Central

Dewell, Richard Burkett

2018-01-01

Collision avoidance is critical for survival, including in humans, and many species possess visual neurons exquisitely sensitive to objects approaching on a collision course. Here, we demonstrate that a collision-detecting neuron can detect the spatial coherence of a simulated impending object, thereby carrying out a computation akin to object segmentation critical for proper escape behavior. At the cellular level, object segmentation relies on a precise selection of the spatiotemporal pattern of synaptic inputs by dendritic membrane potential-activated channels. One channel type linked to dendritic computations in many neural systems, the hyperpolarization-activated cation channel, HCN, plays a central role in this computation. Pharmacological block of HCN channels abolishes the neuron's spatial selectivity and impairs the generation of visually guided escape behaviors, making it directly relevant to survival. Additionally, our results suggest that the interaction of HCN and inactivating K+ channels within active dendrites produces neuronal and behavioral object specificity by discriminating between complex spatiotemporal synaptic activation patterns. PMID:29667927

Extreme brain events: Higher-order statistics of brain resting activity and its relation with structural connectivity

NASA Astrophysics Data System (ADS)

Amor, T. A.; Russo, R.; Diez, I.; Bharath, P.; Zirovich, M.; Stramaglia, S.; Cortes, J. M.; de Arcangelis, L.; Chialvo, D. R.

2015-09-01

The brain exhibits a wide variety of spatiotemporal patterns of neuronal activity recorded using functional magnetic resonance imaging as the so-called blood-oxygenated-level-dependent (BOLD) signal. An active area of work includes efforts to best describe the plethora of these patterns evolving continuously in the brain. Here we explore the third-moment statistics of the brain BOLD signals in the resting state as a proxy to capture extreme BOLD events. We find that the brain signal exhibits typically nonzero skewness, with positive values for cortical regions and negative values for subcortical regions. Furthermore, the combined analysis of structural and functional connectivity demonstrates that relatively more connected regions exhibit activity with high negative skewness. Overall, these results highlight the relevance of recent results emphasizing that the spatiotemporal location of the relatively large-amplitude events in the BOLD time series contains relevant information to reproduce a number of features of the brain dynamics during resting state in health and disease.

Arabidopsis roots and shoots show distinct temporal adaptation patterns toward nitrogen starvation.

PubMed

Krapp, Anne; Berthomé, Richard; Orsel, Mathilde; Mercey-Boutet, Stéphanie; Yu, Agnes; Castaings, Loren; Elftieh, Samira; Major, Hilary; Renou, Jean-Pierre; Daniel-Vedele, Françoise

2011-11-01

Nitrogen (N) is an essential macronutrient for plants. N levels in soil vary widely, and plants have developed strategies to cope with N deficiency. However, the regulation of these adaptive responses and the coordinating signals that underlie them are still poorly understood. The aim of this study was to characterize N starvation in adult Arabidopsis (Arabidopsis thaliana) plants in a spatiotemporal manner by an integrative, multilevel global approach analyzing growth, metabolites, enzyme activities, and transcript levels. We determined that the remobilization of N and carbon compounds to the growing roots occurred long before the internal N stores became depleted. A global metabolite analysis by gas chromatography-mass spectrometry revealed organ-specific differences in the metabolic adaptation to complete N starvation, for example, for several tricarboxylic acid cycle intermediates, but also for carbohydrates, secondary products, and phosphate. The activities of central N metabolism enzymes and the capacity for nitrate uptake adapted to N starvation by favoring N remobilization and by increasing the high-affinity nitrate uptake capacity after long-term starvation. Changes in the transcriptome confirmed earlier studies and added a new dimension by revealing specific spatiotemporal patterns and several unknown N starvation-regulated genes, including new predicted small RNA genes. No global correlation between metabolites, enzyme activities, and transcripts was evident. However, this multilevel spatiotemporal global study revealed numerous new patterns of adaptation mechanisms to N starvation. In the context of a sustainable agriculture, this work will give new insight for the production of crops with increased N use efficiency.

The Central Italy Seismic Sequence (2016): Spatial Patterns and Dynamic Fingerprints

NASA Astrophysics Data System (ADS)

Suteanu, Cristian; Liucci, Luisa; Melelli, Laura

2018-01-01

The paper investigates spatio-temporal aspects of the seismic sequence that started in Central Italy (Amatrice, Lazio region) in August 2016, causing hundreds of fatalities and producing major damage to settlements. On one hand, scaling properties of the landscape topography are identified and related to geomorphological processes, supporting the identification of preferential spatial directions in tectonic activity and confirming the role of the past tectonic periods and ongoing processes with respect to the driving of the geomorphological evolution of the area. On the other hand, relations between the spatio-temporal evolution of the sequence and the seismogenic fault systems are studied. The dynamic fingerprints of seismicity are established with the help of events thread analysis (ETA), which characterizes anisotropy in spatio-temporal earthquake patterns. ETA confirms the fact that the direction of the seismogenic normal fault-oriented (N)NW-(S)SE is characterized by persistent seismic activity. More importantly, it also highlights the role of the pre-existing compressive structures, Neogenic thrust and transpressive regional fronts, with a trend-oriented (N)NE-(S)SW, in the stress transfer. Both the fractal features of the topographic surface and the dynamic fingerprint of the recent seismic sequence point to the hypothesis of an active interaction between the Quaternary fault systems and the pre-existing compressional structures.

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons.

PubMed

Ma, Ying; Shaik, Mohammed A; Kozberg, Mariel G; Kim, Sharon H; Portes, Jacob P; Timerman, Dmitriy; Hillman, Elizabeth M C

2016-12-27

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI.

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

PubMed Central

Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Portes, Jacob P.; Timerman, Dmitriy

2016-01-01

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (<0.04 Hz) hemodynamic fluctuations that were not well-predicted by local Thy1-GCaMP recordings. These results support that resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. PMID:27974609

Data Flow Analysis and Visualization for Spatiotemporal Statistical Data without Trajectory Information.

PubMed

Kim, Seokyeon; Jeong, Seongmin; Woo, Insoo; Jang, Yun; Maciejewski, Ross; Ebert, David S

2018-03-01

Geographic visualization research has focused on a variety of techniques to represent and explore spatiotemporal data. The goal of those techniques is to enable users to explore events and interactions over space and time in order to facilitate the discovery of patterns, anomalies and relationships within the data. However, it is difficult to extract and visualize data flow patterns over time for non-directional statistical data without trajectory information. In this work, we develop a novel flow analysis technique to extract, represent, and analyze flow maps of non-directional spatiotemporal data unaccompanied by trajectory information. We estimate a continuous distribution of these events over space and time, and extract flow fields for spatial and temporal changes utilizing a gravity model. Then, we visualize the spatiotemporal patterns in the data by employing flow visualization techniques. The user is presented with temporal trends of geo-referenced discrete events on a map. As such, overall spatiotemporal data flow patterns help users analyze geo-referenced temporal events, such as disease outbreaks, crime patterns, etc. To validate our model, we discard the trajectory information in an origin-destination dataset and apply our technique to the data and compare the derived trajectories and the original. Finally, we present spatiotemporal trend analysis for statistical datasets including twitter data, maritime search and rescue events, and syndromic surveillance.

Learning-automaton-based online discovery and tracking of spatiotemporal event patterns.

PubMed

Yazidi, Anis; Granmo, Ole-Christoffer; Oommen, B John

2013-06-01

Discovering and tracking of spatiotemporal patterns in noisy sequences of events are difficult tasks that have become increasingly pertinent due to recent advances in ubiquitous computing, such as community-based social networking applications. The core activities for applications of this class include the sharing and notification of events, and the importance and usefulness of these functionalities increase as event sharing expands into larger areas of one's life. Ironically, instead of being helpful, an excessive number of event notifications can quickly render the functionality of event sharing to be obtrusive. Indeed, any notification of events that provides redundant information to the application/user can be seen to be an unnecessary distraction. In this paper, we introduce a new scheme for discovering and tracking noisy spatiotemporal event patterns, with the purpose of suppressing reoccurring patterns, while discerning novel events. Our scheme is based on maintaining a collection of hypotheses, each one conjecturing a specific spatiotemporal event pattern. A dedicated learning automaton (LA)--the spatiotemporal pattern LA (STPLA)--is associated with each hypothesis. By processing events as they unfold, we attempt to infer the correctness of each hypothesis through a real-time guided random walk. Consequently, the scheme that we present is computationally efficient, with a minimal memory footprint. Furthermore, it is ergodic, allowing adaptation. Empirical results involving extensive simulations demonstrate the superior convergence and adaptation speed of STPLA, as well as an ability to operate successfully with noise, including both the erroneous inclusion and omission of events. An empirical comparison study was performed and confirms the superiority of our scheme compared to a similar state-of-the-art approach. In particular, the robustness of the STPLA to inclusion as well as to omission noise constitutes a unique property compared to other related approaches. In addition, the results included, which involve the so-called " presence sharing" application, are both promising and, in our opinion, impressive. It is thus our opinion that the proposed STPLA scheme is, in general, ideal for improving the usefulness of event notification and sharing systems, since it is capable of significantly, robustly, and adaptively suppressing redundant information.

Hysteresis, neural avalanches, and critical behavior near a first-order transition of a spiking neural network

NASA Astrophysics Data System (ADS)

Scarpetta, Silvia; Apicella, Ilenia; Minati, Ludovico; de Candia, Antonio

2018-06-01

Many experimental results, both in vivo and in vitro, support the idea that the brain cortex operates near a critical point and at the same time works as a reservoir of precise spatiotemporal patterns. However, the mechanism at the basis of these observations is still not clear. In this paper we introduce a model which combines both these features, showing that scale-free avalanches are the signature of a system posed near the spinodal line of a first-order transition, with many spatiotemporal patterns stored as dynamical metastable attractors. Specifically, we studied a network of leaky integrate-and-fire neurons whose connections are the result of the learning of multiple spatiotemporal dynamical patterns, each with a randomly chosen ordering of the neurons. We found that the network shows a first-order transition between a low-spiking-rate disordered state (down), and a high-rate state characterized by the emergence of collective activity and the replay of one of the stored patterns (up). The transition is characterized by hysteresis, or alternation of up and down states, depending on the lifetime of the metastable states. In both cases, critical features and neural avalanches are observed. Notably, critical phenomena occur at the edge of a discontinuous phase transition, as recently observed in a network of glow lamps.

Precise Spatiotemporal Control of Optogenetic Activation Using an Acousto-Optic Device

PubMed Central

Guo, Yanmeng; Song, Peipei; Zhang, Xiaohui; Zeng, Shaoqun; Wang, Zuoren

2011-01-01

Light activation and inactivation of neurons by optogenetic techniques has emerged as an important tool for studying neural circuit function. To achieve a high resolution, new methods are being developed to selectively manipulate the activity of individual neurons. Here, we report that the combination of an acousto-optic device (AOD) and single-photon laser was used to achieve rapid and precise spatiotemporal control of light stimulation at multiple points in a neural circuit with millisecond time resolution. The performance of this system in activating ChIEF expressed on HEK 293 cells as well as cultured neurons was first evaluated, and the laser stimulation patterns were optimized. Next, the spatiotemporally selective manipulation of multiple neurons was achieved in a precise manner. Finally, we demonstrated the versatility of this high-resolution method in dissecting neural circuits both in the mouse cortical slice and the Drosophila brain in vivo. Taken together, our results show that the combination of AOD-assisted laser stimulation and optogenetic tools provides a flexible solution for manipulating neuronal activity at high efficiency and with high temporal precision. PMID:22174813

Mining Spatiotemporal Patterns of the Elder's Daily Movement

NASA Astrophysics Data System (ADS)

Chen, C. R.; Chen, C. F.; Liu, M. E.; Tsai, S. J.; Son, N. T.; Kinh, L. V.

2016-06-01

With rapid developments in wearable device technology, a vast amount of spatiotemporal data, such as people's movement and physical activities, are generated. Information derived from the data reveals important knowledge that can contribute a long-term care and psychological assessment of the elders' living condition especially in long-term care institutions. This study aims to develop a method to investigate the spatial-temporal movement patterns of the elders with their outdoor trajectory information. To achieve the goal, GPS based location data of the elderly subjects from long-term care institutions are collected and analysed with geographic information system (GIS). A GIS statistical model is developed to mine the elderly subjects' spatiotemporal patterns with the location data and represent their daily movement pattern at particular time. The proposed method first finds the meaningful trajectory and extracts the frequent patterns from the time-stamp location data. Then, a density-based clustering method is used to identify the major moving range and the gather/stay hotspot in both spatial and temporal dimensions. The preliminary results indicate that the major moving area of the elderly people encompasses their dorm and has a short moving distance who often stay in the same site. Subjects' outdoor appearance are corresponded to their life routine. The results can be useful for understanding elders' social network construction, risky area identification and medical care monitoring.

A neuronal model of a global workspace in effortful cognitive tasks.

PubMed

Dehaene, S; Kerszberg, M; Changeux, J P

1998-11-24

A minimal hypothesis is proposed concerning the brain processes underlying effortful tasks. It distinguishes two main computational spaces: a unique global workspace composed of distributed and heavily interconnected neurons with long-range axons, and a set of specialized and modular perceptual, motor, memory, evaluative, and attentional processors. Workspace neurons are mobilized in effortful tasks for which the specialized processors do not suffice. They selectively mobilize or suppress, through descending connections, the contribution of specific processor neurons. In the course of task performance, workspace neurons become spontaneously coactivated, forming discrete though variable spatio-temporal patterns subject to modulation by vigilance signals and to selection by reward signals. A computer simulation of the Stroop task shows workspace activation to increase during acquisition of a novel task, effortful execution, and after errors. We outline predictions for spatio-temporal activation patterns during brain imaging, particularly about the contribution of dorsolateral prefrontal cortex and anterior cingulate to the workspace.

Multi-Spatiotemporal Patterns of Residential Burglary Crimes in Chicago: 2006-2016

NASA Astrophysics Data System (ADS)

Luo, J.

2017-10-01

This research attempts to explore the patterns of burglary crimes at multi-spatiotemporal scales in Chicago between 2006 and 2016. Two spatial scales are investigated that are census block and police beat area. At each spatial scale, three temporal scales are integrated to make spatiotemporal slices: hourly scale with two-hour time step from 12:00am to the end of the day; daily scale with one-day step from Sunday to Saturday within a week; monthly scale with one-month step from January to December. A total of six types of spatiotemporal slices will be created as the base for the analysis. Burglary crimes are spatiotemporally aggregated to spatiotemporal slices based on where and when they occurred. For each type of spatiotemporal slices with burglary occurrences integrated, spatiotemporal neighborhood will be defined and managed in a spatiotemporal matrix. Hot-spot analysis will identify spatiotemporal clusters of each type of spatiotemporal slices. Spatiotemporal trend analysis is conducted to indicate how the clusters shift in space and time. The analysis results will provide helpful information for better target policing and crime prevention policy such as police patrol scheduling regarding times and places covered.

An evaluation of space time cube representation of spatiotemporal patterns.

PubMed

Kristensson, Per Ola; Dahlbäck, Nils; Anundi, Daniel; Björnstad, Marius; Gillberg, Hanna; Haraldsson, Jonas; Mårtensson, Ingrid; Nordvall, Mathias; Ståhl, Josefine

2009-01-01

Space time cube representation is an information visualization technique where spatiotemporal data points are mapped into a cube. Information visualization researchers have previously argued that space time cube representation is beneficial in revealing complex spatiotemporal patterns in a data set to users. The argument is based on the fact that both time and spatial information are displayed simultaneously to users, an effect difficult to achieve in other representations. However, to our knowledge the actual usefulness of space time cube representation in conveying complex spatiotemporal patterns to users has not been empirically validated. To fill this gap, we report on a between-subjects experiment comparing novice users' error rates and response times when answering a set of questions using either space time cube or a baseline 2D representation. For some simple questions, the error rates were lower when using the baseline representation. For complex questions where the participants needed an overall understanding of the spatiotemporal structure of the data set, the space time cube representation resulted in on average twice as fast response times with no difference in error rates compared to the baseline. These results provide an empirical foundation for the hypothesis that space time cube representation benefits users analyzing complex spatiotemporal patterns.

Spiral wave classification using normalized compression distance: Towards atrial tissue spatiotemporal electrophysiological behavior characterization.

PubMed

Alagoz, Celal; Guez, Allon; Cohen, Andrew; Bullinga, John R

2015-08-01

Analysis of electrical activation patterns such as re-entries during atrial fibrillation (Afib) is crucial in understanding arrhythmic mechanisms and assessment of diagnostic measures. Spiral waves are a phenomena that provide intuitive basis for re-entries occurring in cardiac tissue. Distinct spiral wave behaviors such as stable spiral waves, meandering spiral waves, and spiral wave break-up may have distinct electrogram manifestations on a mapping catheter. Hence, it is desirable to have an automated classification of spiral wave behavior based on catheter recordings for a qualitative characterization of spatiotemporal electrophysiological activity on atrial tissue. In this study, we propose a method for classification of spatiotemporal characteristics of simulated atrial activation patterns in terms of distinct spiral wave behaviors during Afib using two different techniques: normalized compressed distance (NCD) and normalized FFT (NFFTD). We use a phenomenological model for cardiac electrical propagation to produce various simulated spiral wave behaviors on a 2D grid and labeled them as stable, meandering, or breakup. By mimicking commonly used catheter types, a star shaped and a circular shaped both of which do the local readings from atrial wall, monopolar and bipolar intracardiac electrograms are simulated. Virtual catheters are positioned at different locations on the grid. The classification performance for different catheter locations, types and for monopolar or bipolar readings were also compared. We observed that the performance for each case differed slightly. However, we found that NCD performance is superior to NFFTD. Through the simulation study, we showed the theoretical validation of the proposed method. Our findings suggest that a qualitative wavefront activation pattern can be assessed during Afib without the need for highly invasive mapping techniques such as multisite simultaneous electrogram recordings.

Mapping child maltreatment risk: a 12-year spatio-temporal analysis of neighborhood influences.

PubMed

Gracia, Enrique; López-Quílez, Antonio; Marco, Miriam; Lila, Marisol

2017-10-18

'Place' matters in understanding prevalence variations and inequalities in child maltreatment risk. However, most studies examining ecological variations in child maltreatment risk fail to take into account the implications of the spatial and temporal dimensions of neighborhoods. In this study, we conduct a high-resolution small-area study to analyze the influence of neighborhood characteristics on the spatio-temporal epidemiology of child maltreatment risk. We conducted a 12-year (2004-2015) small-area Bayesian spatio-temporal epidemiological study with all families with child maltreatment protection measures in the city of Valencia, Spain. As neighborhood units, we used 552 census block groups. Cases were geocoded using the family address. Neighborhood-level characteristics analyzed included three indicators of neighborhood disadvantage-neighborhood economic status, neighborhood education level, and levels of policing activity-, immigrant concentration, and residential instability. Bayesian spatio-temporal modelling and disease mapping methods were used to provide area-specific risk estimations. Results from a spatio-temporal autoregressive model showed that neighborhoods with low levels of economic and educational status, with high levels of policing activity, and high immigrant concentration had higher levels of substantiated child maltreatment risk. Disease mapping methods were used to analyze areas of excess risk. Results showed chronic spatial patterns of high child maltreatment risk during the years analyzed, as well as stability over time in areas of low risk. Areas with increased or decreased child maltreatment risk over the years were also observed. A spatio-temporal epidemiological approach to study the geographical patterns, trends over time, and the contextual determinants of child maltreatment risk can provide a useful method to inform policy and action. This method can offer a more accurate description of the problem, and help to inform more localized prevention and intervention strategies. This new approach can also contribute to an improved epidemiological surveillance system to detect ecological variations in risk, and to assess the effectiveness of the initiatives to reduce this risk.

Increased spatial granularity of left brain activation and unique age/gender signatures: a 4D frequency domain approach to cerebral lateralization at rest.

PubMed

Agcaoglu, O; Miller, R; Mayer, A R; Hugdahl, K; Calhoun, V D

2016-12-01

Cerebral lateralization is a well-studied topic. However, most of the research to date in functional magnetic resonance imaging (fMRI) has been carried out on hemodynamic fluctuations of voxels, networks, or regions of interest (ROIs). For example, cerebral differences can be revealed by comparing the temporal activation of an ROI in one hemisphere with the corresponding homotopic region in the other hemisphere. While this approach can reveal significant information about cerebral organization, it does not provide information about the full spatiotemporal organization of the hemispheres. The cerebral differences revealed in literature suggest that hemispheres have different spatiotemporal organization in the resting state. In this study, we evaluate cerebral lateralization in the 4D spatiotemporal frequency domain to compare the hemispheres in the context of general activation patterns at different spatial and temporal scales. We use a gender-balanced resting fMRI dataset comprising over 600 healthy subjects ranging in age from 12 to 71, that have previously been studied with a network specific voxel-wise and global analysis of lateralization (Agcaoglu, et al. NeuroImage, 2014). Our analysis elucidates significant differences in the spatiotemporal organization of brain activity between hemispheres, and generally more spatiotemporal fluctuation in the left hemisphere especially in the high spatial frequency bands, and more power in the right hemisphere in the low and middle spatial frequencies. Importantly, the identified effects are not visible in the context of a typical assessment of voxelwise, regional, or even global laterality, thus our study highlights the value of 4D spatiotemporal frequency domain analyses as a complementary and powerful tool for studying brain function.

Neural feedback for instantaneous spatiotemporal modulation of afferent pathways in bi-directional brain-machine interfaces.

PubMed

Liu, Jianbo; Khalil, Hassan K; Oweiss, Karim G

2011-10-01

In bi-directional brain-machine interfaces (BMIs), precisely controlling the delivery of microstimulation, both in space and in time, is critical to continuously modulate the neural activity patterns that carry information about the state of the brain-actuated device to sensory areas in the brain. In this paper, we investigate the use of neural feedback to control the spatiotemporal firing patterns of neural ensembles in a model of the thalamocortical pathway. Control of pyramidal (PY) cells in the primary somatosensory cortex (S1) is achieved based on microstimulation of thalamic relay cells through multiple-input multiple-output (MIMO) feedback controllers. This closed loop feedback control mechanism is achieved by simultaneously varying the stimulation parameters across multiple stimulation electrodes in the thalamic circuit based on continuous monitoring of the difference between reference patterns and the evoked responses of the cortical PY cells. We demonstrate that it is feasible to achieve a desired level of performance by controlling the firing activity pattern of a few "key" neural elements in the network. Our results suggest that neural feedback could be an effective method to facilitate the delivery of information to the cortex to substitute lost sensory inputs in cortically controlled BMIs.

Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities.

PubMed

Frelat, Romain; Lindegren, Martin; Denker, Tim Spaanheden; Floeter, Jens; Fock, Heino O; Sguotti, Camilla; Stäbler, Moritz; Otto, Saskia A; Möllmann, Christian

2017-01-01

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs.

Spatiotemporal dynamics of a digital phase-locked loop based coupled map lattice system

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

Banerjee, Tanmoy, E-mail: tbanerjee@phys.buruniv.ac.in; Paul, Bishwajit; Sarkar, B. C.

2014-03-15

We explore the spatiotemporal dynamics of a coupled map lattice (CML) system, which is realized with a one dimensional array of locally coupled digital phase-locked loops (DPLLs). DPLL is a nonlinear feedback-controlled system widely used as an important building block of electronic communication systems. We derive the phase-error equation of the spatially extended system of coupled DPLLs, which resembles a form of the equation of a CML system. We carry out stability analysis for the synchronized homogeneous solutions using the circulant matrix formalism. It is shown through extensive numerical simulations that with the variation of nonlinearity parameter and coupling strengthmore » the system shows transitions among several generic features of spatiotemporal dynamics, viz., synchronized fixed point solution, frozen random pattern, pattern selection, spatiotemporal intermittency, and fully developed spatiotemporal chaos. We quantify the spatiotemporal dynamics using quantitative measures like average quadratic deviation and spatial correlation function. We emphasize that instead of using an idealized model of CML, which is usually employed to observe the spatiotemporal behaviors, we consider a real world physical system and establish the existence of spatiotemporal chaos and other patterns in this system. We also discuss the importance of the present study in engineering application like removal of clock-skew in parallel processors.« less

Spatiotemporal dynamics of a digital phase-locked loop based coupled map lattice system.

PubMed

Banerjee, Tanmoy; Paul, Bishwajit; Sarkar, B C

2014-03-01

We explore the spatiotemporal dynamics of a coupled map lattice (CML) system, which is realized with a one dimensional array of locally coupled digital phase-locked loops (DPLLs). DPLL is a nonlinear feedback-controlled system widely used as an important building block of electronic communication systems. We derive the phase-error equation of the spatially extended system of coupled DPLLs, which resembles a form of the equation of a CML system. We carry out stability analysis for the synchronized homogeneous solutions using the circulant matrix formalism. It is shown through extensive numerical simulations that with the variation of nonlinearity parameter and coupling strength the system shows transitions among several generic features of spatiotemporal dynamics, viz., synchronized fixed point solution, frozen random pattern, pattern selection, spatiotemporal intermittency, and fully developed spatiotemporal chaos. We quantify the spatiotemporal dynamics using quantitative measures like average quadratic deviation and spatial correlation function. We emphasize that instead of using an idealized model of CML, which is usually employed to observe the spatiotemporal behaviors, we consider a real world physical system and establish the existence of spatiotemporal chaos and other patterns in this system. We also discuss the importance of the present study in engineering application like removal of clock-skew in parallel processors.

Spatiotemporal dynamics of a digital phase-locked loop based coupled map lattice system

NASA Astrophysics Data System (ADS)

Banerjee, Tanmoy; Paul, Bishwajit; Sarkar, B. C.

2014-03-01

We explore the spatiotemporal dynamics of a coupled map lattice (CML) system, which is realized with a one dimensional array of locally coupled digital phase-locked loops (DPLLs). DPLL is a nonlinear feedback-controlled system widely used as an important building block of electronic communication systems. We derive the phase-error equation of the spatially extended system of coupled DPLLs, which resembles a form of the equation of a CML system. We carry out stability analysis for the synchronized homogeneous solutions using the circulant matrix formalism. It is shown through extensive numerical simulations that with the variation of nonlinearity parameter and coupling strength the system shows transitions among several generic features of spatiotemporal dynamics, viz., synchronized fixed point solution, frozen random pattern, pattern selection, spatiotemporal intermittency, and fully developed spatiotemporal chaos. We quantify the spatiotemporal dynamics using quantitative measures like average quadratic deviation and spatial correlation function. We emphasize that instead of using an idealized model of CML, which is usually employed to observe the spatiotemporal behaviors, we consider a real world physical system and establish the existence of spatiotemporal chaos and other patterns in this system. We also discuss the importance of the present study in engineering application like removal of clock-skew in parallel processors.

Mining continuous activity patterns from animal trajectory data

USGS Publications Warehouse

Wang, Y.; Luo, Ze; Baoping, Yan; Takekawa, John Y.; Prosser, Diann J.; Newman, Scott H.

2014-01-01

The increasing availability of animal tracking data brings us opportunities and challenges to intuitively understand the mechanisms of animal activities. In this paper, we aim to discover animal movement patterns from animal trajectory data. In particular, we propose a notion of continuous activity pattern as the concise representation of underlying similar spatio-temporal movements, and develop an extension and refinement framework to discover the patterns. We first preprocess the trajectories into significant semantic locations with time property. Then, we apply a projection-based approach to generate candidate patterns and refine them to generate true patterns. A sequence graph structure and a simple and effective processing strategy is further developed to reduce the computational overhead. The proposed approaches are extensively validated on both real GPS datasets and large synthetic datasets.

Spontaneous and electrically modulated spatiotemporal dynamics of the neocortical slow oscillation and associated local fast activity.

PubMed

Greenberg, Anastasia; Dickson, Clayton T

2013-12-01

The neocortical slow oscillation (SO; ~1Hz) of non-REM sleep and anesthesia reflects synchronized network activity composed of alternating active and silent (ON/OFF) phases at the local network and cellular level. The SO itself shows self-organized spatiotemporal dynamics as it appears to originate at unique foci on each cycle and then propagates across the cortical surface. During sleep, this rhythm is relevant for neuroplastic processes mediating memory consolidation especially since its enhancement by slow, rhythmic electrical fields improves subsequent recall. However, the neurobiological mechanism by which spontaneous or enhanced SO activity might operate on memory traces is unknown. Here we show a series of original results, using cycle to cycle tracking across multiple neocortical sites in urethane anesthetized rats: The spontaneous spatiotemporal dynamics of the SO are complex, showing interfering propagation patterns in the anterior-to-posterior plane. These patterns compete for expression and tend to alternate following phase resets that take place during the silent OFF phase of the SO. Applying sinusoidal electrical field stimulation to the anterior pole of the cerebral cortex progressively entrained local field, gamma, and multi-unit activity at all sites, while disrupting the coordination of endogenous SO activity. Field stimulation also biased propagation in the anterior-to-posterior direction and more notably, enhanced the long-range gamma synchrony between cortical regions. These results are the first to show that changes to slow wave dynamics cause enhancements in high frequency cortico-cortical communication and provide mechanistic clues into how the SO is relevant for sleep-dependent memory consolidation. © 2013.

Immature Spinal Locomotor Output in Children with Cerebral Palsy.

PubMed

Cappellini, Germana; Ivanenko, Yury P; Martino, Giovanni; MacLellan, Michael J; Sacco, Annalisa; Morelli, Daniela; Lacquaniti, Francesco

2016-01-01

Detailed descriptions of gait impairments have been reported in cerebral palsy (CP), but it is still unclear how maturation of the spinal motoneuron output is affected. Spatiotemporal alpha-motoneuron activation during walking can be assessed by mapping the electromyographic activity profiles from several, simultaneously recorded muscles onto the anatomical rostrocaudal location of the motoneuron pools in the spinal cord, and by means of factor analysis of the muscle activity profiles. Here, we analyzed gait kinematics and EMG activity of 11 pairs of bilateral muscles with lumbosacral innervation in 35 children with CP (19 diplegic, 16 hemiplegic, 2-12 years) and 33 typically developing (TD) children (1-12 years). TD children showed a progressive reduction of EMG burst durations and a gradual reorganization of the spatiotemporal motoneuron output with increasing age. By contrast, children with CP showed very limited age-related changes of EMG durations and motoneuron output, as well as of limb intersegmental coordination and foot trajectory control (on both sides for diplegic children and the affected side for hemiplegic children). Factorization of the EMG signals revealed a comparable structure of the motor output in children with CP and TD children, but significantly wider temporal activation patterns in children with CP, resembling the patterns of much younger TD infants. A similar picture emerged when considering the spatiotemporal maps of alpha-motoneuron activation. Overall, the results are consistent with the idea that early injuries to developing motor regions of the brain substantially affect the maturation of the spinal locomotor output and consequently the future locomotor behavior.

Immature Spinal Locomotor Output in Children with Cerebral Palsy

PubMed Central

Cappellini, Germana; Ivanenko, Yury P.; Martino, Giovanni; MacLellan, Michael J.; Sacco, Annalisa; Morelli, Daniela; Lacquaniti, Francesco

2016-01-01

Detailed descriptions of gait impairments have been reported in cerebral palsy (CP), but it is still unclear how maturation of the spinal motoneuron output is affected. Spatiotemporal alpha-motoneuron activation during walking can be assessed by mapping the electromyographic activity profiles from several, simultaneously recorded muscles onto the anatomical rostrocaudal location of the motoneuron pools in the spinal cord, and by means of factor analysis of the muscle activity profiles. Here, we analyzed gait kinematics and EMG activity of 11 pairs of bilateral muscles with lumbosacral innervation in 35 children with CP (19 diplegic, 16 hemiplegic, 2–12 years) and 33 typically developing (TD) children (1–12 years). TD children showed a progressive reduction of EMG burst durations and a gradual reorganization of the spatiotemporal motoneuron output with increasing age. By contrast, children with CP showed very limited age-related changes of EMG durations and motoneuron output, as well as of limb intersegmental coordination and foot trajectory control (on both sides for diplegic children and the affected side for hemiplegic children). Factorization of the EMG signals revealed a comparable structure of the motor output in children with CP and TD children, but significantly wider temporal activation patterns in children with CP, resembling the patterns of much younger TD infants. A similar picture emerged when considering the spatiotemporal maps of alpha-motoneuron activation. Overall, the results are consistent with the idea that early injuries to developing motor regions of the brain substantially affect the maturation of the spinal locomotor output and consequently the future locomotor behavior. PMID:27826251

Neuromusculoskeletal models based on the muscle synergy hypothesis for the investigation of adaptive motor control in locomotion via sensory-motor coordination.

PubMed

Aoi, Shinya; Funato, Tetsuro

2016-03-01

Humans and animals walk adaptively in diverse situations by skillfully manipulating their complicated and redundant musculoskeletal systems. From an analysis of measured electromyographic (EMG) data, it appears that despite complicated spatiotemporal properties, muscle activation patterns can be explained by a low dimensional spatiotemporal structure. More specifically, they can be accounted for by the combination of a small number of basic activation patterns. The basic patterns and distribution weights indicate temporal and spatial structures, respectively, and the weights show the muscle sets that are activated synchronously. In addition, various locomotor behaviors have similar low dimensional structures and major differences appear in the basic patterns. These analysis results suggest that neural systems use muscle group combinations to solve motor control redundancy problems (muscle synergy hypothesis) and manipulate those basic patterns to create various locomotor functions. However, it remains unclear how the neural system controls such muscle groups and basic patterns through neuromechanical interactions in order to achieve adaptive locomotor behavior. This paper reviews simulation studies that explored adaptive motor control in locomotion via sensory-motor coordination using neuromusculoskeletal models based on the muscle synergy hypothesis. Herein, the neural mechanism in motor control related to the muscle synergy for adaptive locomotion and a potential muscle synergy analysis method including neuromusculoskeletal modeling for motor impairments and rehabilitation are discussed. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Diode probes for spatiotemporal optical control of multiple neurons in freely moving animals

PubMed Central

Koos, Tibor; Buzsáki, György

2012-01-01

Neuronal control with high temporal precision is possible with optogenetics, yet currently available methods do not enable to control independently multiple locations in the brains of freely moving animals. Here, we describe a diode-probe system that allows real-time and location-specific control of neuronal activity at multiple sites. Manipulation of neuronal activity in arbitrary spatiotemporal patterns is achieved by means of an optoelectronic array, manufactured by attaching multiple diode-fiber assemblies to high-density silicon probes or wire tetrodes and implanted into the brains of animals that are expressing light-responsive opsins. Each diode can be controlled separately, allowing localized light stimulation of neuronal activators and silencers in any temporal configuration and concurrent recording of the stimulated neurons. Because the only connections to the animals are via a highly flexible wire cable, unimpeded behavior is allowed for circuit monitoring and multisite perturbations in the intact brain. The capacity of the system to generate unique neural activity patterns facilitates multisite manipulation of neural circuits in a closed-loop manner and opens the door to addressing novel questions. PMID:22496529

Spatiotemporal pattern in somitogenesis: a non-Turing scenario with wave propagation.

PubMed

Nagahara, Hiroki; Ma, Yue; Takenaka, Yoshiko; Kageyama, Ryoichiro; Yoshikawa, Kenichi

2009-08-01

Living organisms maintain their lives under far-from-equilibrium conditions by creating a rich variety of spatiotemporal structures in a self-organized manner, such as temporal rhythms, switching phenomena, and development of the body. In this paper, we focus on the dynamical process of morphogens in somitogenesis in mice where propagation of the gene expression level plays an essential role in creating the spatially periodic patterns of the vertebral columns. We present a simple discrete reaction-diffusion model which includes neighboring interaction through an activator, but not diffusion of an inhibitor. We can produce stationary periodic patterns by introducing the effect of spatial discreteness to the field. Based on the present model, we discuss the underlying physical principles that are independent of the details of biomolecular reactions. We also discuss the framework of spatial discreteness based on the reaction-diffusion model in relation to a cellular array, by comparison with an actual experimental observation.

Rich do not rise early: spatio-temporal patterns in the mobility networks of different socio-economic classes

PubMed Central

Hurtado, Rafael G.; Floría, Luis Mario

2016-01-01

We analyse the urban mobility in the cities of Medellín and Manizales (Colombia). Each city is represented by six mobility networks, each one encoding the origin-destination trips performed by a subset of the population corresponding to a particular socio-economic status. The nodes of each network are the different urban locations whereas links account for the existence of a trip between two different areas of the city. We study the main structural properties of these mobility networks by focusing on their spatio-temporal patterns. Our goal is to relate these patterns with the partition into six socio-economic compartments of these two societies. Our results show that spatial and temporal patterns vary across these socio-economic groups. In particular, the two datasets show that as wealth increases the early-morning activity is delayed, the midday peak becomes smoother and the spatial distribution of trips becomes more localized. PMID:27853531

Distinct spatiotemporal activity in principal neurons of the mouse olfactory bulb in anesthetized and awake states

PubMed Central

Blauvelt, David G.; Sato, Tomokazu F.; Wienisch, Martin; Murthy, Venkatesh N.

2013-01-01

The acquisition of olfactory information and its early processing in mammals are modulated by brain states through sniffing behavior and neural feedback. We imaged the spatiotemporal pattern of odor-evoked activity in a population of output neurons (mitral/tufted cells, MTCs) in the olfactory bulb (OB) of head-restrained mice expressing a genetically-encoded calcium indicator. The temporal dynamics of MTC population activity were relatively simple in anesthetized animals, but were highly variable in awake animals. However, the apparently irregular activity in awake animals could be predicted well using sniff timing measured externally, or inferred through fluctuations in the global responses of MTC population even without explicit knowledge of sniff times. The overall spatial pattern of activity was conserved across states, but odor responses had a diffuse spatial component in anesthetized mice that was less prominent during wakefulness. Multi-photon microscopy indicated that MTC lateral dendrites were the likely source of spatially disperse responses in the anesthetized animal. Our data demonstrate that the temporal and spatial dynamics of MTCs can be significantly modulated by behavioral state, and that the ensemble activity of MTCs can provide information about sniff timing to downstream circuits to help decode odor responses. PMID:23543674

Group-level spatio-temporal pattern recovery in MEG decoding using multi-task joint feature learning.

PubMed

Kia, Seyed Mostafa; Pedregosa, Fabian; Blumenthal, Anna; Passerini, Andrea

2017-06-15

The use of machine learning models to discriminate between patterns of neural activity has become in recent years a standard analysis approach in neuroimaging studies. Whenever these models are linear, the estimated parameters can be visualized in the form of brain maps which can aid in understanding how brain activity in space and time underlies a cognitive function. However, the recovered brain maps often suffer from lack of interpretability, especially in group analysis of multi-subject data. To facilitate the application of brain decoding in group-level analysis, we present an application of multi-task joint feature learning for group-level multivariate pattern recovery in single-trial magnetoencephalography (MEG) decoding. The proposed method allows for recovering sparse yet consistent patterns across different subjects, and therefore enhances the interpretability of the decoding model. Our experimental results demonstrate that the mutli-task joint feature learning framework is capable of recovering more meaningful patterns of varying spatio-temporally distributed brain activity across individuals while still maintaining excellent generalization performance. We compare the performance of the multi-task joint feature learning in terms of generalization, reproducibility, and quality of pattern recovery against traditional single-subject and pooling approaches on both simulated and real MEG datasets. These results can facilitate the usage of brain decoding for the characterization of fine-level distinctive patterns in group-level inference. Considering the importance of group-level analysis, the proposed approach can provide a methodological shift towards more interpretable brain decoding models. Copyright © 2017 Elsevier B.V. All rights reserved.

Can you escape the beat? Modelling spatiotemporal biodegradation dynamics during periodic disturbances

NASA Astrophysics Data System (ADS)

König, Sara; Worrich, Anja; Wick, Lukas Y.; Miltner, Anja; Kästner, Matthias; Thullner, Martin; Centler, Florian; Banitz, Thomas; Frank, Karin

2016-04-01

Biodegradation of organic compounds in soil is an important microbial ecosystem service. Soil ecosystems are constantly exposed to disturbances of different spatial configurations and frequencies, challenging their ability to recover the biodegradation function. Thus, the response to these disturbances is crucial for the soil systems' biodegradation performance. The influence of spatial aspects of the disturbance regimes on long-term biodegradation dynamics under periodic disturbances has not been examined, yet. We applied a numerical simulation model considering bacterial growth, degradation, and dispersal to analyze the spatiotemporal biodegradation dynamics under disturbances occuring with different frequencies and with different spatial configurations. We found biodegradation performance decreasing in response to periodic disturbances but on average approaching a new quasi steady state. This mean performance of the disturbed systems increases with both, the interval length between disturbance events and the fragmentation of the spatial disturbance patterns. A detailed spatiotemporal analysis of degradation activity reveals that under highly fragmented disturbance patterns, biodegradation still takes place in the entire disturbed area. For moderately fragmented disturbance patterns, parts of the disturbed area become completely inactive. However, areas with high degradation activity emerge at the interface between disturbed and undisturbed areas, allowing the systems to maintain a relatively high degradation performance. Further decreasing the disturbance patterns' fragmentation, fewer interfaces between disturbed and undisturbed area and, thus, fewer active habitats occur, which reduces biodegradation performances. In additional simulations, we found that bacterial dispersal networks, as for example provided by fungal hyphae, usually increase the areas of high degradation activity and, thus, the biodegradation performance in presence of periodic disturbances. However, for some specific regimes with highly fragmented disturbance patterns, dispersal networks can in turn decrease the biodegradation performance. Our results show that spatial aspects of the periodic disturbance regime influence the biodegradation dynamics, indicating the relevance of spatial processes for functional stability. The level of connectivity between disturbed and undisturbed areas is crucial for the local and global dynamics of the ecosystem service biodegradation. Networks enhancing bacterial dispersal may often, but not always, increase the functional stability.

Cortical Activation Patterns Evoked by Temporally Asymmetric Sounds and Their Modulation by Learning

PubMed Central

Horikawa, Junsei

2017-01-01

When complex sounds are reversed in time, the original and reversed versions are perceived differently in spectral and temporal dimensions despite their identical duration and long-term spectrum-power profiles. Spatiotemporal activation patterns evoked by temporally asymmetric sound pairs demonstrate how the temporal envelope determines the readout of the spectrum. We examined the patterns of activation evoked by a temporally asymmetric sound pair in the primary auditory field (AI) of anesthetized guinea pigs and determined how discrimination training modified these patterns. Optical imaging using a voltage-sensitive dye revealed that a forward ramped-down natural sound (F) consistently evoked much stronger responses than its time-reversed, ramped-up counterpart (revF). The spatiotemporal maximum peak (maxP) of F-evoked activation was always greater than that of revF-evoked activation, and these maxPs were significantly separated within the AI. Although discrimination training did not affect the absolute magnitude of these maxPs, the revF-to-F ratio of the activation peaks calculated at the location where hemispheres were maximally activated (i.e., F-evoked maxP) was significantly smaller in the trained group. The F-evoked activation propagated across the AI along the temporal axis to the ventroanterior belt field (VA), with the local activation peak within the VA being significantly larger in the trained than in the naïve group. These results suggest that the innate network is more responsive to natural sounds of ramped-down envelopes than their time-reversed, unnatural sounds. The VA belt field activation might play an important role in emotional learning of sounds through its connections with amygdala. PMID:28451640

a Three-Step Spatial-Temporal Clustering Method for Human Activity Pattern Analysis

NASA Astrophysics Data System (ADS)

Huang, W.; Li, S.; Xu, S.

2016-06-01

How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time) to four dimensions (space, time and semantics). More specifically, not only a location and time that people stay and spend are collected, but also what people "say" for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The results show that the approximate 55% spatiotemporal clusters distributed in different locations can be eventually grouped as the same type of clusters with consideration of semantic aspect.

Spatiotemporal Patterns in a Predator-Prey Model with Cross-Diffusion Effect

NASA Astrophysics Data System (ADS)

Sambath, M.; Balachandran, K.; Guin, L. N.

The present research deals with the emergence of spatiotemporal patterns of a two-dimensional (2D) continuous predator-prey system with cross-diffusion effect. First, we work out the critical lines of Hopf and Turing bifurcations of the current model system in a 2D spatial domain by means of bifurcation theory. More specifically, the exact Turing region is specified in a two-parameter space. In effect, by choosing the cross-diffusion coefficient as one of the momentous parameter, we demonstrate that the model system undergoes a sequence of spatiotemporal patterns in a homogeneous environment through diffusion-driven instability. Our results via numerical simulation authenticate that cross-diffusion be able to create stationary patterns which enrich the findings of pattern formation in an ecosystem.

Modelling and formation of spatiotemporal patterns of fractional predation system in subdiffusion and superdiffusion scenarios

NASA Astrophysics Data System (ADS)

Owolabi, Kolade M.; Atangana, Abdon

2018-02-01

This paper primarily focused on the question of how population diffusion can affect the formation of the spatial patterns in the spatial fraction predator-prey system by Turing mechanisms. Our numerical findings assert that modeling by fractional reaction-diffusion equations should be considered as an appropriate tool for studying the fundamental mechanisms of complex spatiotemporal dynamics. We observe that pure Hopf instability gives rise to the formation of spiral patterns in 2D and pure Turing instability destroys the spiral pattern and results to the formation of chaotic or spatiotemporal spatial patterns. Existence and permanence of the species is also guaranteed with the 3D simulations at some instances of time for subdiffusive and superdiffusive scenarios.

Mimicking muscle activity with electrical stimulation

NASA Astrophysics Data System (ADS)

Johnson, Lise A.; Fuglevand, Andrew J.

2011-02-01

Functional electrical stimulation is a rehabilitation technology that can restore some degree of motor function in individuals who have sustained a spinal cord injury or stroke. One way to identify the spatio-temporal patterns of muscle stimulation needed to elicit complex upper limb movements is to use electromyographic (EMG) activity recorded from able-bodied subjects as a template for electrical stimulation. However, this requires a transfer function to convert the recorded (or predicted) EMG signals into an appropriate pattern of electrical stimulation. Here we develop a generalized transfer function that maps EMG activity into a stimulation pattern that modulates muscle output by varying both the pulse frequency and the pulse amplitude. We show that the stimulation patterns produced by this transfer function mimic the active state measured by EMG insofar as they reproduce with good fidelity the complex patterns of joint torque and joint displacement.

Representation of Muscle Synergies in the Primate Brain.

PubMed

Overduin, Simon A; d'Avella, Andrea; Roh, Jinsook; Carmena, Jose M; Bizzi, Emilio

2015-09-16

Evidence suggests that the CNS uses motor primitives to simplify movement control, but whether it actually stores primitives instead of computing solutions on the fly to satisfy task demands is a controversial and still-unanswered possibility. Also in contention is whether these primitives take the form of time-invariant muscle coactivations ("spatial" synergies) or time-varying muscle commands ("spatiotemporal" synergies). Here, we examined forelimb muscle patterns and motor cortical spiking data in rhesus macaques (Macaca mulatta) handling objects of variable shape and size. From these data, we extracted both spatiotemporal and spatial synergies using non-negative decomposition. Each spatiotemporal synergy represents a sequence of muscular or neural activations that appeared to recur frequently during the animals' behavior. Key features of the spatiotemporal synergies (including their dimensionality, timing, and amplitude modulation) were independently observed in the muscular and neural data. In addition, both at the muscular and neural levels, these spatiotemporal synergies could be readily reconstructed as sequential activations of spatial synergies (a subset of those extracted independently from the task data), suggestive of a hierarchical relationship between the two levels of synergies. The possibility that motor cortex may execute even complex skill using spatiotemporal synergies has novel implications for the design of neuroprosthetic devices, which could gain computational efficiency by adopting the discrete and low-dimensional control that these primitives imply. We studied the motor cortical and forearm muscular activity of rhesus macaques (Macaca mulatta) as they reached, grasped, and carried objects of varied shape and size. We applied non-negative matrix factorization separately to the cortical and muscular data to reduce their dimensionality to a smaller set of time-varying "spatiotemporal" synergies. Each synergy represents a sequence of cortical or muscular activity that recurred frequently during the animals' behavior. Salient features of the synergies (including their dimensionality, timing, and amplitude modulation) were observed at both the cortical and muscular levels. The possibility that the brain may execute even complex behaviors using spatiotemporal synergies has implications for neuroprosthetic algorithm design, which could become more computationally efficient by adopting the discrete and low-dimensional control that they afford. Copyright © 2015 the authors 0270-6474/15/3512615-10$15.00/0.

Method for detecting the signature of noise-induced structures in spatiotemporal data sets: an application to excitable media

NASA Astrophysics Data System (ADS)

Huett, Marc-Thorsten

2003-05-01

We formulate mathematical tools for analyzing spatiotemporal data sets. The tools are based on nearest-neighbor considerations similar to cellular automata. One of the analysis tools allows for reconstructing the noise intensity in a data set and is an appropriate method for detecting a variety of noise-induced phenomena in spatiotemporal data. The functioning of these methods is illustrated on sample data generated with the forest fire model and with networks of nonlinear oscillators. It is seen that these methods allow the characterization of spatiotemporal stochastic resonance (STSR) in experimental data. Application of these tools to biological spatiotemporal patterns is discussed. For one specific example, the slime mold Dictyostelium discoideum, it is seen, how transitions between different patterns are clearly marked by changes in the spatiotemporal observables.

Similarity-Based Fusion of MEG and fMRI Reveals Spatio-Temporal Dynamics in Human Cortex During Visual Object Recognition

PubMed Central

Cichy, Radoslaw Martin; Pantazis, Dimitrios; Oliva, Aude

2016-01-01

Every human cognitive function, such as visual object recognition, is realized in a complex spatio-temporal activity pattern in the brain. Current brain imaging techniques in isolation cannot resolve the brain's spatio-temporal dynamics, because they provide either high spatial or temporal resolution but not both. To overcome this limitation, we developed an integration approach that uses representational similarities to combine measurements of magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) to yield a spatially and temporally integrated characterization of neuronal activation. Applying this approach to 2 independent MEG–fMRI data sets, we observed that neural activity first emerged in the occipital pole at 50–80 ms, before spreading rapidly and progressively in the anterior direction along the ventral and dorsal visual streams. Further region-of-interest analyses established that dorsal and ventral regions showed MEG–fMRI correspondence in representations later than early visual cortex. Together, these results provide a novel and comprehensive, spatio-temporally resolved view of the rapid neural dynamics during the first few hundred milliseconds of object vision. They further demonstrate the feasibility of spatially unbiased representational similarity-based fusion of MEG and fMRI, promising new insights into how the brain computes complex cognitive functions. PMID:27235099

Climate-mediated spatiotemporal variability in terrestrial productivity across Europe

NASA Astrophysics Data System (ADS)

Wu, X.; Babst, F.; Ciais, P.; Frank, D.; Reichstein, M.; Wattenbach, M.; Zang, C.; Mahecha, M. D.

2014-06-01

Quantifying the interannual variability (IAV) of the terrestrial ecosystem productivity and its sensitivity to climate is crucial for improving carbon budget predictions. In this context it is necessary to disentangle the influence of climate from impacts of other mechanisms underlying the spatiotemporal patterns of IAV of the ecosystem productivity. In this study we investigated the spatiotemporal patterns of IAV of historical observations of European crop yields in tandem with a set of climate variables. We further evaluated if relevant remote-sensing retrievals of NDVI (normalized difference vegetation index) and FAPAR (fraction of absorbed photosynthetically active radiation) depict a similar behaviour. Our results reveal distinct spatial patterns in the IAV of the analysed proxies linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions in both crop yield and remote-sensing observations. Our results further indicate that variations in the water balance during the active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity-related variables in temperate Europe. Overall, we observe a temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe during the 1975-2009 period. In the same regions, a simultaneous increase in the IAV of water availability was detected. These findings suggest intricate responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become potentially more sensitive to changes in water availability in the dry regions in Europe. The changing sensitivity of terrestrial productivity accompanied by the changing IAV of climate is expected to impact carbon stocks and the net carbon balance of European ecosystems.

Mining moving object trajectories in location-based services for spatio-temporal database update

NASA Astrophysics Data System (ADS)

Guo, Danhuai; Cui, Weihong

2008-10-01

Advances in wireless transmission and mobile technology applied to LBS (Location-based Services) flood us with amounts of moving objects data. Vast amounts of gathered data from position sensors of mobile phones, PDAs, or vehicles hide interesting and valuable knowledge and describe the behavior of moving objects. The correlation between temporal moving patterns of moving objects and geo-feature spatio-temporal attribute was ignored, and the value of spatio-temporal trajectory data was not fully exploited too. Urban expanding or frequent town plan change bring about a large amount of outdated or imprecise data in spatial database of LBS, and they cannot be updated timely and efficiently by manual processing. In this paper we introduce a data mining approach to movement pattern extraction of moving objects, build a model to describe the relationship between movement patterns of LBS mobile objects and their environment, and put up with a spatio-temporal database update strategy in LBS database based on trajectories spatiotemporal mining. Experimental evaluation reveals excellent performance of the proposed model and strategy. Our original contribution include formulation of model of interaction between trajectory and its environment, design of spatio-temporal database update strategy based on moving objects data mining, and the experimental application of spatio-temporal database update by mining moving objects trajectories.

Temporal relationship between the 2000 Miyake-Kozu seismovolcanic activity and the 2000 Tokai slow-slip event

NASA Astrophysics Data System (ADS)

Kawamura, Masashi; Yamaoka, Koshun

2009-02-01

We investigated the temporal relationship between the two events, namely, the seismovolcanic activity near the Miyakejima and Kozushima islands and the slow-slip event along the plate boundary in the Tokai district. The islands are located on the east of Tokai, and the Tokai slow-slip event was discovered immediately after the large crustal deformation caused by the volcanic activity in the Miyakejima-Kozushima regions ceased. However, the order of occurrence of these events is still controversial and its recognition will help us to understand the tectonic processes of the central part of Japan, where many volcanic and seismic activities occur. For this purpose, we applied the statistical approach (Kawamura, M., Yamaoka, K., 2006. Spatiotemporal characteristics of the displacement field revealed with principal component analysis and the mode-rotation technique, Tectonophys., 419, 55-73), which consists of principal component analysis (PCA) and a mode rotation procedure, to the displacement field provided by the nationwide GPS network (GEONET) in order to obtain the characteristic structures of spatiotemporal crustal deformation caused by the above two events. We divided the time period of analysis into two sections (namely, June 26, 1999 to June 25, 2000 and June 26, 2000 to June 25, 2002) by the day when the magma intrusion occurred beneath the Miyakejima volcano on June 26, 2000. The spatial and temporal modes for the first time period did not indicate any significant spatiotemporal patterns corresponding to the two events. This indicates the absence of episodic crustal deformations during this time period. On the contrary, the modes for the latter time period included the changes caused by these events. The two major modes included the spatiotemporal structures of the first and latter half periods of the Miyake-Kozu seismovolcanic activity. The characteristic pattern of the crustal deformation corresponding to the Tokai slow-slip event was found in the fourth mode, which was prominent after the beginning of the Miyake-Kozu seismovolcanic activity. From these results, we conclude that the crustal deformation caused by the Tokai slow-slip event did not start before the Miyake-Kozu seismovolcanic activity.

Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities

PubMed Central

Lindegren, Martin; Denker, Tim Spaanheden; Floeter, Jens; Fock, Heino O.; Sguotti, Camilla; Stäbler, Moritz; Otto, Saskia A.; Möllmann, Christian

2017-01-01

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs. PMID:29136658

A model for optimizing file access patterns using spatio-temporal parallelism

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

Boonthanome, Nouanesengsy; Patchett, John; Geveci, Berk

2013-01-01

For many years now, I/O read time has been recognized as the primary bottleneck for parallel visualization and analysis of large-scale data. In this paper, we introduce a model that can estimate the read time for a file stored in a parallel filesystem when given the file access pattern. Read times ultimately depend on how the file is stored and the access pattern used to read the file. The file access pattern will be dictated by the type of parallel decomposition used. We employ spatio-temporal parallelism, which combines both spatial and temporal parallelism, to provide greater flexibility to possible filemore » access patterns. Using our model, we were able to configure the spatio-temporal parallelism to design optimized read access patterns that resulted in a speedup factor of approximately 400 over traditional file access patterns.« less

Region-specific network plasticity in simulated and living cortical networks: comparison of the center of activity trajectory (CAT) with other statistics

NASA Astrophysics Data System (ADS)

Chao, Zenas C.; Bakkum, Douglas J.; Potter, Steve M.

2007-09-01

Electrically interfaced cortical networks cultured in vitro can be used as a model for studying the network mechanisms of learning and memory. Lasting changes in functional connectivity have been difficult to detect with extracellular multi-electrode arrays using standard firing rate statistics. We used both simulated and living networks to compare the ability of various statistics to quantify functional plasticity at the network level. Using a simulated integrate-and-fire neural network, we compared five established statistical methods to one of our own design, called center of activity trajectory (CAT). CAT, which depicts dynamics of the location-weighted average of spatiotemporal patterns of action potentials across the physical space of the neuronal circuitry, was the most sensitive statistic for detecting tetanus-induced plasticity in both simulated and living networks. By reducing the dimensionality of multi-unit data while still including spatial information, CAT allows efficient real-time computation of spatiotemporal activity patterns. Thus, CAT will be useful for studies in vivo or in vitro in which the locations of recording sites on multi-electrode probes are important.

Protein Tyrosine Phosphatase-PEST and β8 Integrin Regulate Spatiotemporal Patterns of RhoGDI1 Activation in Migrating Cells

PubMed Central

Lee, Hye Shin; Cheerathodi, Mujeeburahiman; Chaki, Sankar P.; Reyes, Steve B.; Zheng, Yanhua; Lu, Zhimin; Paidassi, Helena; DerMardirossian, Celine; Lacy-Hulbert, Adam; Rivera, Gonzalo M.

2015-01-01

Directional cell motility is essential for normal development and physiology, although how motile cells spatiotemporally activate signaling events remains largely unknown. Here, we have characterized an adhesion and signaling unit comprised of protein tyrosine phosphatase (PTP)-PEST and the extracellular matrix (ECM) adhesion receptor β8 integrin that plays essential roles in directional cell motility. β8 integrin and PTP-PEST form protein complexes at the leading edge of migrating cells and balance patterns of Rac1 and Cdc42 signaling by controlling the subcellular localization and phosphorylation status of Rho GDP dissociation inhibitor 1 (RhoGDI1). Translocation of Src-phosphorylated RhoGDI1 to the cell's leading edge promotes local activation of Rac1 and Cdc42, whereas dephosphorylation of RhoGDI1 by integrin-bound PTP-PEST promotes RhoGDI1 release from the membrane and sequestration of inactive Rac1/Cdc42 in the cytoplasm. Collectively, these data reveal a finely tuned regulatory mechanism for controlling signaling events at the leading edge of directionally migrating cells. PMID:25666508

Predictability of spatio-temporal patterns in a lattice of coupled FitzHugh–Nagumo oscillators

PubMed Central

Grace, Miriam; Hütt, Marc-Thorsten

2013-01-01

In many biological systems, variability of the components can be expected to outrank statistical fluctuations in the shaping of self-organized patterns. In pioneering work in the late 1990s, it was hypothesized that a drift of cellular parameters (along a ‘developmental path’), together with differences in cell properties (‘desynchronization’ of cells on the developmental path) can establish self-organized spatio-temporal patterns (in their example, spiral waves of cAMP in a colony of Dictyostelium discoideum cells) starting from a homogeneous state. Here, we embed a generic model of an excitable medium, a lattice of diffusively coupled FitzHugh–Nagumo oscillators, into a developmental-path framework. In this minimal model of spiral wave generation, we can now study the predictability of spatio-temporal patterns from cell properties as a function of desynchronization (or ‘spread’) of cells along the developmental path and the drift speed of cell properties on the path. As a function of drift speed and desynchronization, we observe systematically different routes towards fully established patterns, as well as strikingly different correlations between cell properties and pattern features. We show that the predictability of spatio-temporal patterns from cell properties contains important information on the pattern formation process as well as on the underlying dynamical system. PMID:23349439

Spatiotemporal neuromodulation therapies engaging muscle synergies improve motor control after spinal cord injury

PubMed Central

Wenger, Nikolaus; Moraud, Eduardo Martin; Gandar, Jerome; Musienko, Pavel; Capogrosso, Marco; Baud, Laetitia; Le Goff, Camille G.; Barraud, Quentin; Pavlova, Natalia; Dominici, Nadia; Minev, Ivan R.; Asboth, Leonie; Hirsch, Arthur; Duis, Simone; Kreider, Julie; Mortera, Andrea; Haverbeck, Oliver; Kraus, Silvio; Schmitz, Felix; DiGiovanna, Jack; van den Brand, Rubia; Bloch, Jocelyne; Detemple, Peter; Lacour, Stéphanie P.; Bézard, Erwan; Micera, Silvestro; Courtine, Grégoire

2016-01-01

Electrical neuromodulation of lumbar segments improves motor control after spinal cord injury in animal models and humans. However, the physiological principles underlying the effect of this intervention remain poorly understood, which has limited this therapeutic approach to continuous stimulation applied to restricted spinal cord locations. Here, we developed novel stimulation protocols that reproduce the natural dynamics of motoneuron activation during locomotion. For this, we computed the spatiotemporal activation pattern of muscle synergies during locomotion in healthy rats. Computer simulations identified optimal electrode locations to target each synergy through the recruitment of proprioceptive feedback circuits. This framework steered the design of spatially selective spinal implants and real–time control software that modulate extensor versus flexor synergies with precise temporal resolution. Spatiotemporal neuromodulation therapies improved gait quality, weight–bearing capacities, endurance and skilled locomotion in multiple rodent models of spinal cord injury. These new concepts are directly translatable to strategies to improve motor control in humans. PMID:26779815

Abnormal early dynamic individual patterns of functional networks in low gamma band for depression recognition.

PubMed

Bi, Kun; Chattun, Mahammad Ridwan; Liu, Xiaoxue; Wang, Qiang; Tian, Shui; Zhang, Siqi; Lu, Qing; Yao, Zhijian

2018-06-13

The functional networks are associated with emotional processing in depression. The mapping of dynamic spatio-temporal brain networks is used to explore individual performance during early negative emotional processing. However, the dysfunctions of functional networks in low gamma band and their discriminative potentialities during early period of emotional face processing remain to be explored. Functional brain networks were constructed from the MEG recordings of 54 depressed patients and 54 controls in low gamma band (30-48 Hz). Dynamic connectivity regression (DCR) algorithm analyzed the individual change points of time series in response to emotional stimuli and constructed individualized spatio-temporal patterns. The nodal characteristics of patterns were calculated and fed into support vector machine (SVM). Performance of the classification algorithm in low gamma band was validated by dynamic topological characteristics of individual patterns in comparison to alpha and beta band. The best discrimination accuracy of individual spatio-temporal patterns was 91.01% in low gamma band. Individual temporal patterns had better results compared to group-averaged temporal patterns in all bands. The most important discriminative networks included affective network (AN) and fronto-parietal network (FPN) in low gamma band. The sample size is relatively small. High gamma band was not considered. The abnormal dynamic functional networks in low gamma band during early emotion processing enabled depression recognition. The individual information processing is crucial in the discovery of abnormal spatio-temporal patterns in depression during early negative emotional processing. Individual spatio-temporal patterns may reflect the real dynamic function of subjects while group-averaged data may neglect some individual information. Copyright © 2018. Published by Elsevier B.V.

Automated detection of qualitative spatio-temporal features in electrocardiac activation maps.

PubMed

Ironi, Liliana; Tentoni, Stefania

2007-02-01

This paper describes a piece of work aiming at the realization of a tool for the automated interpretation of electrocardiac maps. Such maps can capture a number of electrical conduction pathologies, such as arrhytmia, that can be missed by the analysis of traditional electrocardiograms. But, their introduction into the clinical practice is still far away as their interpretation requires skills that belongs to very few experts. Then, an automated interpretation tool would bridge the gap between the established research outcome and clinical practice with a consequent great impact on health care. Qualitative spatial reasoning can play a crucial role in the identification of spatio-temporal patterns and salient features that characterize the heart electrical activity. We adopted the spatial aggregation (SA) conceptual framework and an interplay of numerical and qualitative information to extract features from epicardial maps, and to make them available for reasoning tasks. Our focus is on epicardial activation isochrone maps as they are a synthetic representation of spatio-temporal aspects of the propagation of the electrical excitation. We provide a computational SA-based methodology to extract, from 3D epicardial data gathered over time, (1) the excitation wavefront structure, and (2) the salient features that characterize wavefront propagation and visually correspond to specific geometric objects. The proposed methodology provides a robust and efficient way to identify salient pieces of information in activation time maps. The hierarchical structure of the abstracted geometric objects, crucial in capturing the prominent information, facilitates the definition of general rules necessary to infer the correlation between pathophysiological patterns and wavefront structure and propagation.

Spatiotemporal analysis of dengue fever in Nepal from 2010 to 2014.

PubMed

Acharya, Bipin Kumar; Cao, ChunXiang; Lakes, Tobia; Chen, Wei; Naeem, Shahid

2016-08-22

Due to recent emergence, dengue is becoming one of the major public health problems in Nepal. The numbers of reported dengue cases in general and the area with reported dengue cases are both continuously increasing in recent years. However, spatiotemporal patterns and clusters of dengue have not been investigated yet. This study aims to fill this gap by analyzing spatiotemporal patterns based on monthly surveillance data aggregated at district. Dengue cases from 2010 to 2014 at district level were collected from the Nepal government's health and mapping agencies respectively. GeoDa software was used to map crude incidence, excess hazard and spatially smoothed incidence. Cluster analysis was performed in SaTScan software to explore spatiotemporal clusters of dengue during the above-mentioned time period. Spatiotemporal distribution of dengue fever in Nepal from 2010 to 2014 was mapped at district level in terms of crude incidence, excess risk and spatially smoothed incidence. Results show that the distribution of dengue fever was not random but clustered in space and time. Chitwan district was identified as the most likely cluster and Jhapa district was the first secondary cluster in both spatial and spatiotemporal scan. July to September of 2010 was identified as a significant temporal cluster. This study assessed and mapped for the first time the spatiotemporal pattern of dengue fever in Nepal. Two districts namely Chitwan and Jhapa were found highly affected by dengue fever. The current study also demonstrated the importance of geospatial approach in epidemiological research. The initial result on dengue patterns and risk of this study may assist institutions and policy makers to develop better preventive strategies.

Emergent dynamics of spatio-temporal chaos in a heterogeneous excitable medium.

PubMed

Bittihn, Philip; Berg, Sebastian; Parlitz, Ulrich; Luther, Stefan

2017-09-01

Self-organized activation patterns in excitable media such as spiral waves and spatio-temporal chaos underlie dangerous cardiac arrhythmias. While the interaction of single spiral waves with different types of heterogeneity has been studied extensively, the effect of heterogeneity on fully developed spatio-temporal chaos remains poorly understood. We investigate how the complexity and stability properties of spatio-temporal chaos in the Bär-Eiswirth model of excitable media depend on the heterogeneity of the underlying medium. We employ different measures characterizing the chaoticity of the system and find that the spatial arrangement of multiple discrete lower excitability regions has a strong impact on the complexity of the dynamics. Varying the number, shape, and spatial arrangement of the heterogeneities, we observe strong emergent effects ranging from increases in chaoticity to the complete cessation of chaos, contrasting the expectation from the homogeneous behavior. The implications of our findings for the development and treatment of arrhythmias in the heterogeneous cardiac muscle are discussed.

Emergent dynamics of spatio-temporal chaos in a heterogeneous excitable medium

NASA Astrophysics Data System (ADS)

Bittihn, Philip; Berg, Sebastian; Parlitz, Ulrich; Luther, Stefan

2017-09-01

Self-organized activation patterns in excitable media such as spiral waves and spatio-temporal chaos underlie dangerous cardiac arrhythmias. While the interaction of single spiral waves with different types of heterogeneity has been studied extensively, the effect of heterogeneity on fully developed spatio-temporal chaos remains poorly understood. We investigate how the complexity and stability properties of spatio-temporal chaos in the Bär-Eiswirth model of excitable media depend on the heterogeneity of the underlying medium. We employ different measures characterizing the chaoticity of the system and find that the spatial arrangement of multiple discrete lower excitability regions has a strong impact on the complexity of the dynamics. Varying the number, shape, and spatial arrangement of the heterogeneities, we observe strong emergent effects ranging from increases in chaoticity to the complete cessation of chaos, contrasting the expectation from the homogeneous behavior. The implications of our findings for the development and treatment of arrhythmias in the heterogeneous cardiac muscle are discussed.

Cortical Entropy, Mutual Information and Scale-Free Dynamics in Waking Mice.

PubMed

Fagerholm, Erik D; Scott, Gregory; Shew, Woodrow L; Song, Chenchen; Leech, Robert; Knöpfel, Thomas; Sharp, David J

2016-10-01

Some neural circuits operate with simple dynamics characterized by one or a few well-defined spatiotemporal scales (e.g. central pattern generators). In contrast, cortical neuronal networks often exhibit richer activity patterns in which all spatiotemporal scales are represented. Such "scale-free" cortical dynamics manifest as cascades of activity with cascade sizes that are distributed according to a power-law. Theory and in vitro experiments suggest that information transmission among cortical circuits is optimized by scale-free dynamics. In vivo tests of this hypothesis have been limited by experimental techniques with insufficient spatial coverage and resolution, i.e., restricted access to a wide range of scales. We overcame these limitations by using genetically encoded voltage imaging to track neural activity in layer 2/3 pyramidal cells across the cortex in mice. As mice recovered from anesthesia, we observed three changes: (a) cortical information capacity increased, (b) information transmission among cortical regions increased and (c) neural activity became scale-free. Our results demonstrate that both information capacity and information transmission are maximized in the awake state in cortical regions with scale-free network dynamics. © The Author 2016. Published by Oxford University Press.

Spatio-temporal analysis of irregular vocal fold oscillations: Biphonation due to desynchronization of spatial modes

NASA Astrophysics Data System (ADS)

Neubauer, Jürgen; Mergell, Patrick; Eysholdt, Ulrich; Herzel, Hanspeter

2001-12-01

This report is on direct observation and modal analysis of irregular spatio-temporal vibration patterns of vocal fold pathologies in vivo. The observed oscillation patterns are described quantitatively with multiline kymograms, spectral analysis, and spatio-temporal plots. The complex spatio-temporal vibration patterns are decomposed by empirical orthogonal functions into independent vibratory modes. It is shown quantitatively that biphonation can be induced either by left-right asymmetry or by desynchronized anterior-posterior vibratory modes, and the term ``AP (anterior-posterior) biphonation'' is introduced. The presented phonation examples show that for normal phonation the first two modes sufficiently explain the glottal dynamics. The spatio-temporal oscillation pattern associated with biphonation due to left-right asymmetry can be explained by the first three modes. Higher-order modes are required to describe the pattern for biphonation induced by anterior-posterior vibrations. Spatial irregularity is quantified by an entropy measure, which is significantly higher for irregular phonation than for normal phonation. Two asymmetry measures are introduced: the left-right asymmetry and the anterior-posterior asymmetry, as the ratios of the fundamental frequencies of left and right vocal fold and of anterior-posterior modes, respectively. These quantities clearly differentiate between left-right biphonation and anterior-posterior biphonation. This paper proposes methods to analyze quantitatively irregular vocal fold contour patterns in vivo and complements previous findings of desynchronization of vibration modes in computer modes and in in vitro experiments.

Spatio-temporal Dynamics of Audiovisual Speech Processing

PubMed Central

Bernstein, Lynne E.; Auer, Edward T.; Wagner, Michael; Ponton, Curtis W.

2007-01-01

The cortical processing of auditory-alone, visual-alone, and audiovisual speech information is temporally and spatially distributed, and functional magnetic resonance imaging (fMRI) cannot adequately resolve its temporal dynamics. In order to investigate a hypothesized spatio-temporal organization for audiovisual speech processing circuits, event-related potentials (ERPs) were recorded using electroencephalography (EEG). Stimuli were congruent audiovisual /bα/, incongruent auditory /bα/ synchronized with visual /gα/, auditory-only /bα/, and visual-only /bα/ and /gα/. Current density reconstructions (CDRs) of the ERP data were computed across the latency interval of 50-250 milliseconds. The CDRs demonstrated complex spatio-temporal activation patterns that differed across stimulus conditions. The hypothesized circuit that was investigated here comprised initial integration of audiovisual speech by the middle superior temporal sulcus (STS), followed by recruitment of the intraparietal sulcus (IPS), followed by activation of Broca's area (Miller and d'Esposito, 2005). The importance of spatio-temporally sensitive measures in evaluating processing pathways was demonstrated. Results showed, strikingly, early (< 100 msec) and simultaneous activations in areas of the supramarginal and angular gyrus (SMG/AG), the IPS, the inferior frontal gyrus, and the dorsolateral prefrontal cortex. Also, emergent left hemisphere SMG/AG activation, not predicted based on the unisensory stimulus conditions was observed at approximately 160 to 220 msec. The STS was neither the earliest nor most prominent activation site, although it is frequently considered the sine qua non of audiovisual speech integration. As discussed here, the relatively late activity of the SMG/AG solely under audiovisual conditions is a possible candidate audiovisual speech integration response. PMID:17920933

Spatiotemporal Patterns and Predictability of Cyberattacks

PubMed Central

Chen, Yu-Zhong; Huang, Zi-Gang; Xu, Shouhuai; Lai, Ying-Cheng

2015-01-01

A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term “spatio” refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack “fingerprints” and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches. PMID:25992837

Spatiotemporal patterns and predictability of cyberattacks.

PubMed

Chen, Yu-Zhong; Huang, Zi-Gang; Xu, Shouhuai; Lai, Ying-Cheng

2015-01-01

A relatively unexplored issue in cybersecurity science and engineering is whether there exist intrinsic patterns of cyberattacks. Conventional wisdom favors absence of such patterns due to the overwhelming complexity of the modern cyberspace. Surprisingly, through a detailed analysis of an extensive data set that records the time-dependent frequencies of attacks over a relatively wide range of consecutive IP addresses, we successfully uncover intrinsic spatiotemporal patterns underlying cyberattacks, where the term "spatio" refers to the IP address space. In particular, we focus on analyzing macroscopic properties of the attack traffic flows and identify two main patterns with distinct spatiotemporal characteristics: deterministic and stochastic. Strikingly, there are very few sets of major attackers committing almost all the attacks, since their attack "fingerprints" and target selection scheme can be unequivocally identified according to the very limited number of unique spatiotemporal characteristics, each of which only exists on a consecutive IP region and differs significantly from the others. We utilize a number of quantitative measures, including the flux-fluctuation law, the Markov state transition probability matrix, and predictability measures, to characterize the attack patterns in a comprehensive manner. A general finding is that the attack patterns possess high degrees of predictability, potentially paving the way to anticipating and, consequently, mitigating or even preventing large-scale cyberattacks using macroscopic approaches.

Evaluation of urban sprawl and urban landscape pattern in a rapidly developing region.

PubMed

Lv, Zhi-Qiang; Dai, Fu-Qiang; Sun, Cheng

2012-10-01

Urban sprawl is a worldwide phenomenon happening particularly in rapidly developing regions. A study on the spatiotemporal characteristics of urban sprawl and urban pattern is useful for the sustainable management of land management and urban land planning. The present research explores the spatiotemporal dynamics of urban sprawl in the context of a rapid urbanization process in a booming economic region of southern China from 1979 to 2005. Three urban sprawl types are distinguished by analyzing overlaid urban area maps of two adjacent study years which originated from the interpretation of remote sensed images and vector land use maps. Landscape metrics are used to analyze the spatiotemporal pattern of urban sprawl for each study period. Study results show that urban areas have expanded dramatically, and the spatiotemporal landscape pattern configured by the three sprawl types changed obviously. The different sprawl type patterns in five study periods have transformed significantly, with their proportions altered both in terms of quantity and of location. The present research proves that urban sprawl quantification and pattern analysis can provide a clear perspective of the urbanization process during a long time period. Particularly, the present study on urban sprawl and sprawl patterns can be used by land use and urban planners.

4-dimensional functional profiling in the convulsant-treated larval zebrafish brain.

PubMed

Winter, Matthew J; Windell, Dylan; Metz, Jeremy; Matthews, Peter; Pinion, Joe; Brown, Jonathan T; Hetheridge, Malcolm J; Ball, Jonathan S; Owen, Stewart F; Redfern, Will S; Moger, Julian; Randall, Andrew D; Tyler, Charles R

2017-07-26

Functional neuroimaging, using genetically-encoded Ca 2+ sensors in larval zebrafish, offers a powerful combination of high spatiotemporal resolution and higher vertebrate relevance for quantitative neuropharmacological profiling. Here we use zebrafish larvae with pan-neuronal expression of GCaMP6s, combined with light sheet microscopy and a novel image processing pipeline, for the 4D profiling of chemoconvulsant action in multiple brain regions. In untreated larvae, regions associated with autonomic functionality, sensory processing and stress-responsiveness, consistently exhibited elevated spontaneous activity. The application of drugs targeting different convulsant mechanisms (4-Aminopyridine, Pentylenetetrazole, Pilocarpine and Strychnine) resulted in distinct spatiotemporal patterns of activity. These activity patterns showed some interesting parallels with what is known of the distribution of their respective molecular targets, but crucially also revealed system-wide neural circuit responses to stimulation or suppression. Drug concentration-response curves of neural activity were identified in a number of anatomically-defined zebrafish brain regions, and in vivo larval electrophysiology, also conducted in 4dpf larvae, provided additional measures of neural activity. Our quantification of network-wide chemoconvulsant drug activity in the whole zebrafish brain illustrates the power of this approach for neuropharmacological profiling in applications ranging from accelerating studies of drug safety and efficacy, to identifying pharmacologically-altered networks in zebrafish models of human neurological disorders.

A spatiotemporal profile of visual system activation revealed by current source density analysis in the awake macaque.

PubMed

Schroeder, C E; Mehta, A D; Givre, S J

1998-01-01

We investigated the spatiotemporal activation pattern, produced by one visual stimulus, across cerebral cortical regions in awake monkeys. Laminar profiles of postsynaptic potentials and action potentials were indexed with current source density (CSD) and multiunit activity profiles respectively. Locally, we found contrasting activation profiles in dorsal and ventral stream areas. The former, like V1 and V2, exhibit a 'feedforward' profile, with excitation beginning at the depth of Lamina 4, followed by activation of the extragranular laminae. The latter often displayed a multilaminar/columnar profile, with initial responses distributed across the laminae and reflecting modulation rather than excitation; CSD components were accompanied by either no changes or by suppression of action potentials. System-wide, response latencies indicated a large dorsal/ventral stream latency advantage, which generalizes across a wide range of methods. This predicts a specific temporal ordering of dorsal and ventral stream components of visual analysis, as well as specific patterns of dorsal-ventral stream interaction. Our findings support a hierarchical model of cortical organization that combines serial and parallel elements. Critical in such a model is the recognition that processing within a location typically entails multiple temporal components or 'waves' of activity, driven by input conveyed over heterogeneous pathways from the retina.

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE.

PubMed

Quaglio, Pietro; Yegenoglu, Alper; Torre, Emiliano; Endres, Dominik M; Grün, Sonja

2017-01-01

Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons). In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST). We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE) analysis.

Distributional patterns in an insect community inhabiting a sandy beach of Uruguay

NASA Astrophysics Data System (ADS)

Mourglia, Virginia; González-Vainer, Patricia; Defeo, Omar

2015-12-01

Most studies of sandy beach macrofauna have been restricted to semiterrestrial species and do not include insects when providing species richness and abundance estimates. Particularly, spatio-temporal patterns of community structure of the entomofauna inhabiting these ecosystems have been scarcely documented. This study assessed spatio-temporal distributional patterns of the night active entomofauna on a beach-dune system of Uruguay, including variations in species richness, abundance and diversity, and their relationship with environmental factors. A deconstructive taxonomic analysis was also performed, considering richness and abundance patterns separately for the most abundant insect Orders (Hymenoptera and Coleoptera) to better understand the factors which drive their patterns. We found clear temporal and across-shore patterns in the insect community inhabiting a land-ocean interface, which matched spatiotemporal variations in the environment. Abundance and species richness were highest in spring and summer, concurrently with high temperatures and low values of sediment moisture and compaction. Multivariate ordinations showed two well-defined species groups, which separated summer, autumn and spring samples from winter ones. Generalized Linear Models allowed us to describe a clear segregation in space of the most important orders of the insect community, with specific preferences for the terrestrial (Hymenoptera) and beach (Coleoptera) fringes. Hymenoptera preferred the dune zone, characterized by high elevation and low sand moisture and compaction levels, whereas Coleoptera preferred gentle slopes and fine and humid sands of the beach. Our results suggest that beach and dune ecosystems operate as two separate components in regard to their physical and biological features. The high values of species richness and abundance of insects reveal that this group has a more significant ecological role than that originally considered so far in sandy beach ecology.

Detection and Evaluation of Spatio-Temporal Spike Patterns in Massively Parallel Spike Train Data with SPADE

PubMed Central

Quaglio, Pietro; Yegenoglu, Alper; Torre, Emiliano; Endres, Dominik M.; Grün, Sonja

2017-01-01

Repeated, precise sequences of spikes are largely considered a signature of activation of cell assemblies. These repeated sequences are commonly known under the name of spatio-temporal patterns (STPs). STPs are hypothesized to play a role in the communication of information in the computational process operated by the cerebral cortex. A variety of statistical methods for the detection of STPs have been developed and applied to electrophysiological recordings, but such methods scale poorly with the current size of available parallel spike train recordings (more than 100 neurons). In this work, we introduce a novel method capable of overcoming the computational and statistical limits of existing analysis techniques in detecting repeating STPs within massively parallel spike trains (MPST). We employ advanced data mining techniques to efficiently extract repeating sequences of spikes from the data. Then, we introduce and compare two alternative approaches to distinguish statistically significant patterns from chance sequences. The first approach uses a measure known as conceptual stability, of which we investigate a computationally cheap approximation for applications to such large data sets. The second approach is based on the evaluation of pattern statistical significance. In particular, we provide an extension to STPs of a method we recently introduced for the evaluation of statistical significance of synchronous spike patterns. The performance of the two approaches is evaluated in terms of computational load and statistical power on a variety of artificial data sets that replicate specific features of experimental data. Both methods provide an effective and robust procedure for detection of STPs in MPST data. The method based on significance evaluation shows the best overall performance, although at a higher computational cost. We name the novel procedure the spatio-temporal Spike PAttern Detection and Evaluation (SPADE) analysis. PMID:28596729

Regulation of Spatiotemporal Patterns by Biological Variability: General Principles and Applications to Dictyostelium discoideum

PubMed Central

Grace, Miriam; Hütt, Marc-Thorsten

2015-01-01

Spatiotemporal patterns often emerge from local interactions in a self-organizing fashion. In biology, the resulting patterns are also subject to the influence of the systematic differences between the system’s constituents (biological variability). This regulation of spatiotemporal patterns by biological variability is the topic of our review. We discuss several examples of correlations between cell properties and the self-organized spatiotemporal patterns, together with their relevance for biology. Our guiding, illustrative example will be spiral waves of cAMP in a colony of Dictyostelium discoideum cells. Analogous processes take place in diverse situations (such as cardiac tissue, where spiral waves occur in potentially fatal ventricular fibrillation) so a deeper understanding of this additional layer of self-organized pattern formation would be beneficial to a wide range of applications. One of the most striking differences between pattern-forming systems in physics or chemistry and those in biology is the potential importance of variability. In the former, system components are essentially identical with random fluctuations determining the details of the self-organization process and the resulting patterns. In biology, due to variability, the properties of potentially very few cells can have a driving influence on the resulting asymptotic collective state of the colony. Variability is one means of implementing a few-element control on the collective mode. Regulatory architectures, parameters of signaling cascades, and properties of structure formation processes can be "reverse-engineered" from observed spatiotemporal patterns, as different types of regulation and forms of interactions between the constituents can lead to markedly different correlations. The power of this biology-inspired view of pattern formation lies in building a bridge between two scales: the patterns as a collective state of a very large number of cells on the one hand, and the internal parameters of the single cells on the other. PMID:26562406

Microscale Spatiotemporal Dynamics during Neocortical Propagation of Human Focal Seizures

PubMed Central

Wagner, Fabien B.; Eskandar, Emad N.; Cosgrove, G. Rees; Madsen, Joseph R.; Blum, Andrew S.; Potter, N. Stevenson; Hochberg, Leigh R.; Cash, Sydney S.; Truccolo, Wilson

2015-01-01

Some of the most clinically consequential aspects of focal epilepsy, e.g. loss of consciousness, arise from the generalization or propagation of seizures through local and large-scale neocortical networks. Yet, the dynamics of such neocortical propagation remain poorly understood. Here, we studied the microdynamics of focal seizure propagation in neocortical patches (4 × 4 mm) recorded via high-density microelectrode arrays (MEAs) implanted in people with pharmacologically resistant epilepsy. Our main findings are threefold: (1) A newly developed stage segmentation method, applied to local field potentials (LFPs) and multi-unit activity (MUA), revealed a succession of discrete seizure stages, each lasting several seconds. These different stages showed characteristic evolutions in overall activity and spatial patterns, which were relatively consistent across seizures within each of the 5 patients studied. Interestingly, segmented seizure stages based on LFPs or MUA showed a dissociation of their spatiotemporal dynamics, likely reflecting different contributions of non-local synaptic inputs and local network activity. (2) As previously reported, some of the seizures showed a peak in MUA that happened several seconds after local seizure onset and slowly propagated across the MEA. However, other seizures had a more complex structure characterized by, for example, several MUA peaks, more consistent with the succession of discrete stages than the slow propagation of a simple wavefront of increased MUA. In both cases, nevertheless, seizures characterized by spike-wave discharges (SWDs, ~ 2–3Hz) eventually evolved into patterns of phase-locked MUA and LFPs. (3) Individual SWDs or gamma oscillation cycles (25–60 Hz), characteristic of two different types of recorded seizures, tended to propagate with varying degrees of directionality, directions of propagation and speeds, depending on the identified seizure stage. However, no clear relationship was observed between the MUA peak onset time (in seizures where such peak onset occurred) and changes in MUA or LFP propagation patterns. Overall, our findings indicate that the recruitment of neocortical territories into ictal activity undergo complex spatiotemporal dynamics evolving in slow discrete states, which are consistent across seizures within each patient. Furthermore, ictal states at finer spatiotemporal scales (individual SWDs or gamma oscillations) are organized by slower time-scale network dynamics evolving through these discrete stages. PMID:26279211

Finding Spatio-Temporal Patterns in Large Sensor Datasets

ERIC Educational Resources Information Center

McGuire, Michael Patrick

2010-01-01

Spatial or temporal data mining tasks are performed in the context of the relevant space, defined by a spatial neighborhood, and the relevant time period, defined by a specific time interval. Furthermore, when mining large spatio-temporal datasets, interesting patterns typically emerge where the dataset is most dynamic. This dissertation is…

Fire, native species, and soil resource interactions influence the spatio-temporal invasion pattern of Bromus tectorum

Treesearch

Michael J. Gundale; Steve Sutherland; Thomas H. DeLuca; others

2008-01-01

Bromus tectorum (cheatgrass) is an invasive annual that occupies perennial grass and shrub communities throughout the western United States. Bromus tectorum exhibits an intriguing spatio-temporal pattern of invasion in low elevation ponderosa pine Pinus ponderosa/bunchgrass communities in western Montana where it...

Calculating foraging area using gloal navigation satellite system (GNSS) technology

USDA-ARS?s Scientific Manuscript database

Adjusting stocking rate to changing forage conditions is a critical part of pro-active range management. In general stocking rate approaches tend to assume more optimal landscape use patterns than will actually occur. Today we can monitor spatio-temporal landscape use on a 24/7 basis using animals...

Monitoring the trajectory of urban nighttime light hotspots using a Gaussian volume model

NASA Astrophysics Data System (ADS)

Zheng, Qiming; Jiang, Ruowei; Wang, Ke; Huang, Lingyan; Ye, Ziran; Gan, Muye; Ji, Biyong

2018-03-01

Urban nighttime light hotspot is an ideal representation of the spatial heterogeneity of human activities within a city, which is sensitive to regional urban expansion pattern. However, most of previous studies related to nighttime light imageries focused on extracting urban extent, leaving the spatial variation of radiance intensity insufficiently explored. With the help of global radiance calibrated DMSP-OLS datasets (NTLgrc), we proposed an innovative framework to explore the spatio-temporal trajectory of polycentric urban nighttime light hotspots. Firstly, NTLgrc was inter-annually calibrated to improve the consistency. Secondly, multi-resolution segmentation and region-growing SVM classification were employed to remove blooming effect and to extract potential clusters. At last, the urban hotspots were identified by a Gaussian volume model, and the resulting parameters were used to quantitatively depict hotspot features (i.e., intensity, morphology and centroid dynamics). The result shows that our framework successfully captures hotspots in polycentric urban area, whose Ra2 are over 0.9. Meanwhile, the spatio-temporal dynamics of the hotspot features intuitively reveal the impact of the regional urban growth pattern and planning strategies on human activities. Compared to previous studies, our framework is more robust and offers an effective way to describe hotspot pattern. Also, it provides a more comprehensive and spatial-explicit understanding regarding the interaction between urbanization pattern and human activities. Our findings are expected to be beneficial to governors in term of sustainable urban planning and decision making.

Mapping the spatio-temporal structure of motor cortical LFP and spiking activities during reach-to-grasp movements

PubMed Central

Riehle, Alexa; Wirtssohn, Sarah; Grün, Sonja; Brochier, Thomas

2013-01-01

Grasping an object involves shaping the hand and fingers in relation to the object’s physical properties. Following object contact, it also requires a fine adjustment of grasp forces for secure manipulation. Earlier studies suggest that the control of hand shaping and grasp force involve partially segregated motor cortical networks. However, it is still unclear how information originating from these networks is processed and integrated. We addressed this issue by analyzing massively parallel signals from population measures (local field potentials, LFPs) and single neuron spiking activities recorded simultaneously during a delayed reach-to-grasp task, by using a 100-electrode array chronically implanted in monkey motor cortex. Motor cortical LFPs exhibit a large multi-component movement-related potential (MRP) around movement onset. Here, we show that the peak amplitude of each MRP component and its latency with respect to movement onset vary along the cortical surface covered by the array. Using a comparative mapping approach, we suggest that the spatio-temporal structure of the MRP reflects the complex physical properties of the reach-to-grasp movement. In addition, we explored how the spatio-temporal structure of the MRP relates to two other measures of neuronal activity: the temporal profile of single neuron spiking activity at each electrode site and the somatosensory receptive field properties of single neuron activities. We observe that the spatial representations of LFP and spiking activities overlap extensively and relate to the spatial distribution of proximal and distal representations of the upper limb. Altogether, these data show that, in motor cortex, a precise spatio-temporal pattern of activation is involved for the control of reach-to-grasp movements and provide some new insight about the functional organization of motor cortex during reaching and object manipulation. PMID:23543888

Oscillations and patterns in a model of simultaneous CO and C2H2 oxidation and NO(x) reduction in a cross-flow reactor.

PubMed

Hadač, Otto; Kohout, Martin; Havlica, Jaromír; Schreiber, Igor

2015-03-07

A model describing simultaneous catalytic oxidation of CO and C2H2 and reduction of NOx in a cross-flow tubular reactor is explored with the aim of relating spatiotemporal patterns to specific pathways in the mechanism. For that purpose, a detailed mechanism proposed for three-way catalytic converters is split into two subsystems, (i) simultaneous oxidation of CO and C2H2, and (ii) oxidation of CO combined with NOx reduction. The ability of these two subsystems to display mechanism-specific dynamical effects is studied initially by neglecting transport phenomena and applying stoichiometric network and bifurcation analyses. We obtain inlet temperature - inlet oxygen concentration bifurcation diagrams, where each region possessing specific dynamics - oscillatory, bistable and excitable - is associated with a dominant reaction pathway. Next, the spatiotemporal behaviour due to reaction kinetics combined with transport processes is studied. The observed spatiotemporal patterns include phase waves, travelling fronts, pulse waves and spatiotemporal chaos. Although these types of pattern occur generally when the kinetic scheme possesses autocatalysis, we find that some of their properties depend on the underlying dominant reaction pathway. The relation of patterns to specific reaction pathways is discussed.

Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs.

PubMed

Lee, Sungjun; Lim, Junseok; Park, Jonghun; Kim, Kwanho

2016-01-23

Due to the recent explosive growth of location-aware services based on mobile devices, predicting the next places of a user is of increasing importance to enable proactive information services. In this paper, we introduce a data-driven framework that aims to predict the user's next places using his/her past visiting patterns analyzed from mobile device logs. Specifically, the notion of the spatiotemporal-periodic (STP) pattern is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail level of location for each individual. Subsequently, we present algorithms that extract the STP patterns from a user's past visiting behaviors and predict the next places based on the patterns. The experiment results obtained by using a real-world dataset show that the proposed methods are more effective in predicting the user's next places than the previous approaches considered in most cases.

Synchronization and spatiotemporal patterns in coupled phase oscillators on a weighted planar network

NASA Astrophysics Data System (ADS)

Kagawa, Yuki; Takamatsu, Atsuko

2009-04-01

To reveal the relation between network structures found in two-dimensional biological systems, such as protoplasmic tube networks in the plasmodium of true slime mold, and spatiotemporal oscillation patterns emerged on the networks, we constructed coupled phase oscillators on weighted planar networks and investigated their dynamics. Results showed that the distribution of edge weights in the networks strongly affects (i) the propensity for global synchronization and (ii) emerging ratios of oscillation patterns, such as traveling and concentric waves, even if the total weight is fixed. In-phase locking, traveling wave, and concentric wave patterns were, respectively, observed most frequently in uniformly weighted, center weighted treelike, and periphery weighted ring-shaped networks. Controlling the global spatiotemporal patterns with the weight distribution given by the local weighting (coupling) rules might be useful in biological network systems including the plasmodial networks and neural networks in the brain.

Chimera states in networks of logistic maps with hierarchical connectivities

NASA Astrophysics Data System (ADS)

zur Bonsen, Alexander; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

2018-04-01

Chimera states are complex spatiotemporal patterns consisting of coexisting domains of coherence and incoherence. We study networks of nonlocally coupled logistic maps and analyze systematically how the dilution of the network links influences the appearance of chimera patterns. The network connectivities are constructed using an iterative Cantor algorithm to generate fractal (hierarchical) connectivities. Increasing the hierarchical level of iteration, we compare the resulting spatiotemporal patterns. We demonstrate that a high clustering coefficient and symmetry of the base pattern promotes chimera states, and asymmetric connectivities result in complex nested chimera patterns.

Spatio-Temporal Brain Mapping of Motion-Onset VEPs Combined with fMRI and Retinotopic Maps

PubMed Central

Pitzalis, Sabrina; Strappini, Francesca; De Gasperis, Marco; Bultrini, Alessandro; Di Russo, Francesco

2012-01-01

Neuroimaging studies have identified several motion-sensitive visual areas in the human brain, but the time course of their activation cannot be measured with these techniques. In the present study, we combined electrophysiological and neuroimaging methods (including retinotopic brain mapping) to determine the spatio-temporal profile of motion-onset visual evoked potentials for slow and fast motion stimuli and to localize its neural generators. We found that cortical activity initiates in the primary visual area (V1) for slow stimuli, peaking 100 ms after the onset of motion. Subsequently, activity in the mid-temporal motion-sensitive areas, MT+, peaked at 120 ms, followed by peaks in activity in the more dorsal area, V3A, at 160 ms and the lateral occipital complex at 180 ms. Approximately 250 ms after stimulus onset, activity fast motion stimuli was predominant in area V6 along the parieto-occipital sulcus. Finally, at 350 ms (100 ms after the motion offset) brain activity was visible again in area V1. For fast motion stimuli, the spatio-temporal brain pattern was similar, except that the first activity was detected at 70 ms in area MT+. Comparing functional magnetic resonance data for slow vs. fast motion, we found signs of slow-fast motion stimulus topography along the posterior brain in at least three cortical regions (MT+, V3A and LOR). PMID:22558222

Lateral Membrane Waves Constitute a Universal Dynamic Pattern of Motile Cells

NASA Astrophysics Data System (ADS)

Döbereiner, Hans-Günther; Dubin-Thaler, Benjamin J.; Hofman, Jake M.; Xenias, Harry S.; Sims, Tasha N.; Giannone, Grégory; Dustin, Michael L.; Wiggins, Chris H.; Sheetz, Michael P.

2006-07-01

We have monitored active movements of the cell circumference on specifically coated substrates for a variety of cells including mouse embryonic fibroblasts and T cells, as well as wing disk cells from fruit flies. Despite having different functions and being from multiple phyla, these cell types share a common spatiotemporal pattern in their normal membrane velocity; we show that protrusion and retraction events are organized in lateral waves along the cell membrane. These wave patterns indicate both spatial and temporal long-range periodic correlations of the actomyosin gel.

Discrete simulations of spatio-temporal dynamics of small water bodies under varied stream flow discharges

NASA Astrophysics Data System (ADS)

Daya Sagar, B. S.

2005-01-01

Spatio-temporal patterns of small water bodies (SWBs) under the influence of temporally varied stream flow discharge are simulated in discrete space by employing geomorphologically realistic expansion and contraction transformations. Cascades of expansion-contraction are systematically performed by synchronizing them with stream flow discharge simulated via the logistic map. Templates with definite characteristic information are defined from stream flow discharge pattern as the basis to model the spatio-temporal organization of randomly situated surface water bodies of various sizes and shapes. These spatio-temporal patterns under varied parameters (λs) controlling stream flow discharge patterns are characterized by estimating their fractal dimensions. At various λs, nonlinear control parameters, we show the union of boundaries of water bodies that traverse the water body and non-water body spaces as geomorphic attractors. The computed fractal dimensions of these attractors are 1.58, 1.53, 1.78, 1.76, 1.84, and 1.90, respectively, at λs of 1, 2, 3, 3.46, 3.57, and 3.99. These values are in line with general visual observations.

Time-course analysis of the neuroanatomical correlates of sexual arousal evoked by erotic video stimuli in healthy males.

PubMed

Sundaram, Thirunavukkarasu; Jeong, Gwang-Woo; Kim, Tae-Hoon; Kim, Gwang-Won; Baek, Han-Su; Kang, Heoung-Keun

2010-01-01

To assess the dynamic activations of the key brain areas associated with the time-course of the sexual arousal evoked by visual sexual stimuli in healthy male subjects. Fourteen right-handed heterosexual male volunteers participated in this study. Alternatively combined rest period and erotic video visual stimulation were used according to the standard block design. In order to illustrate and quantify the spatiotemporal activation patterns of the key brain regions, the activation period was divided into three different stages as the EARLY, MID and LATE stages. For the group result (p < 0.05), when comparing the MID stage with the EARLY stage, a significant increase of the brain activation was observed in the areas that included the inferior frontal gyrus, the supplementary motor area, the hippocampus, the head of the caudate nucleus, the midbrain, the superior occipital gyrus and the fusiform gyrus. At the same time, when comparing the EARLY stage with the MID stage, the putamen, the globus pallidus, the pons, the thalamus, the hypothalamus, the lingual gyrus and the cuneus yielded significantly increased activations. When comparing the LATE stage with the MID stage, all the above mentioned brain regions showed elevated activations except the hippocampus. Our results illustrate the spatiotemporal activation patterns of the key brain regions across the three stages of visual sexual arousal.

Time-Course Analysis of the Neuroanatomical Correlates of Sexual Arousal Evoked by Erotic Video Stimuli in Healthy Males

PubMed Central

Sundaram, Thirunavukkarasu; Kim, Tae-Hoon; Kim, Gwang-Won; Baek, Han-Su; Kang, Heoung-Keun

2010-01-01

Objective To assess the dynamic activations of the key brain areas associated with the time-course of the sexual arousal evoked by visual sexual stimuli in healthy male subjects. Materials and Methods Fourteen right-handed heterosexual male volunteers participated in this study. Alternatively combined rest period and erotic video visual stimulation were used according to the standard block design. In order to illustrate and quantify the spatiotemporal activation patterns of the key brain regions, the activation period was divided into three different stages as the EARLY, MID and LATE stages. Results For the group result (p < 0.05), when comparing the MID stage with the EARLY stage, a significant increase of the brain activation was observed in the areas that included the inferior frontal gyrus, the supplementary motor area, the hippocampus, the head of the caudate nucleus, the midbrain, the superior occipital gyrus and the fusiform gyrus. At the same time, when comparing the EARLY stage with the MID stage, the putamen, the globus pallidus, the pons, the thalamus, the hypothalamus, the lingual gyrus and the cuneus yielded significantly increased activations. When comparing the LATE stage with the MID stage, all the above mentioned brain regions showed elevated activations except the hippocampus. Conclusion Our results illustrate the spatiotemporal activation patterns of the key brain regions across the three stages of visual sexual arousal. PMID:20461181

An analysis of current source density profiles activated by local stimulation in the mouse auditory cortex in vitro.

PubMed

Yamamura, Daiki; Sano, Ayaka; Tateno, Takashi

2017-03-15

To examine local network properties of the mouse auditory cortex in vitro, we recorded extracellular spatiotemporal laminar profiles driven by short electric local stimulation on a planar multielectrode array substrate. The recorded local field potentials were subsequently evaluated using current source density (CSD) analysis to identify sources and sinks. Current sinks are thought to be an indicator of net synaptic current in the small volume of cortex surrounding the recording site. Thus, CSD analysis combined with multielectrode arrays enabled us to compare mean synaptic activity in response to small current stimuli on a layer-by-layer basis. We also used senescence-accelerated mice (SAM), some strains of which show earlier onset of age-related hearing loss, to examine the characteristic spatiotemporal CSD profiles stimulated by electrodes in specific cortical layers. Thus, the CSD patterns were classified into several clusters based on stimulation sites in the cortical layers. We also found some differences in CSD patterns between the two SAM strains in terms of aging according to principle component analysis with dimension reduction. For simultaneous two-site stimulation, we modeled the obtained CSD profiles as a linear superposition of the CSD profiles to individual single-site stimulation. The model analysis indicated the nonlinearity of spatiotemporal integration over stimulus-driven activity in a layer-specific manner. Finally, on the basis of these results, we discuss the auditory cortex local network properties and the effects of aging on these mouse strains. Copyright © 2017 Elsevier B.V. All rights reserved.

Combined ICA-LORETA analysis of mismatch negativity.

PubMed

Marco-Pallarés, J; Grau, C; Ruffini, G

2005-04-01

A major challenge for neuroscience is to map accurately the spatiotemporal patterns of activity of the large neuronal populations that are believed to underlie computing in the human brain. To study a specific example, we selected the mismatch negativity (MMN) brain wave (an event-related potential, ERP) because it gives an electrophysiological index of a "primitive intelligence" capable of detecting changes, even abstract ones, in a regular auditory pattern. ERPs have a temporal resolution of milliseconds but appear to result from mixed neuronal contributions whose spatial location is not fully understood. Thus, it is important to separate these sources in space and time. To tackle this problem, a two-step approach was designed combining the independent component analysis (ICA) and low-resolution tomography (LORETA) algorithms. Here we implement this approach to analyze the subsecond spatiotemporal dynamics of MMN cerebral sources using trial-by-trial experimental data. We show evidence that a cerebral computation mechanism underlies MMN. This mechanism is mediated by the orchestrated activity of several spatially distributed brain sources located in the temporal, frontal, and parietal areas, which activate at distinct time intervals and are grouped in six main statistically independent components.

Spatiotemporal chaos involving wave instability.

PubMed

Berenstein, Igal; Carballido-Landeira, Jorge

2017-01-01

In this paper, we investigate pattern formation in a model of a reaction confined in a microemulsion, in a regime where both Turing and wave instability occur. In one-dimensional systems, the pattern corresponds to spatiotemporal intermittency where the behavior of the systems alternates in both time and space between stationary Turing patterns and traveling waves. In two-dimensional systems, the behavior initially may correspond to Turing patterns, which then turn into wave patterns. The resulting pattern also corresponds to a chaotic state, where the system alternates in both space and time between standing wave patterns and traveling waves, and the local dynamics may show vanishing amplitude of the variables.

Spatiotemporal chaos involving wave instability

NASA Astrophysics Data System (ADS)

Berenstein, Igal; Carballido-Landeira, Jorge

2017-01-01

In this paper, we investigate pattern formation in a model of a reaction confined in a microemulsion, in a regime where both Turing and wave instability occur. In one-dimensional systems, the pattern corresponds to spatiotemporal intermittency where the behavior of the systems alternates in both time and space between stationary Turing patterns and traveling waves. In two-dimensional systems, the behavior initially may correspond to Turing patterns, which then turn into wave patterns. The resulting pattern also corresponds to a chaotic state, where the system alternates in both space and time between standing wave patterns and traveling waves, and the local dynamics may show vanishing amplitude of the variables.

The Link between Microbial Diversity and Nitrogen Cycling in Marine Sediments Is Modulated by Macrofaunal Bioturbation.

PubMed

Yazdani Foshtomi, Maryam; Braeckman, Ulrike; Derycke, Sofie; Sapp, Melanie; Van Gansbeke, Dirk; Sabbe, Koen; Willems, Anne; Vincx, Magda; Vanaverbeke, Jan

2015-01-01

The marine benthic nitrogen cycle is affected by both the presence and activity of macrofauna and the diversity of N-cycling microbes. However, integrated research simultaneously investigating macrofauna, microbes and N-cycling is lacking. We investigated spatio-temporal patterns in microbial community composition and diversity, macrofaunal abundance and their sediment reworking activity, and N-cycling in seven subtidal stations in the Southern North Sea. Our results indicated that bacteria (total and β-AOB) showed more spatio-temporal variation than archaea (total and AOA) as sedimentation of organic matter and the subsequent changes in the environment had a stronger impact on their community composition and diversity indices in our study area. However, spatio-temporal patterns of total bacterial and β-AOB communities were different and related to the availability of ammonium for the autotrophic β-AOB. Highest bacterial richness and diversity were observed in June at the timing of the phytoplankton bloom deposition, while richness of β-AOB as well as AOA peaked in September. Total archaeal community showed no temporal variation in diversity indices. Distance based linear models revealed that, independent from the effect of grain size and the quality and quantity of sediment organic matter, nitrification and N-mineralization were affected by respectively the diversity of metabolically active β-AOB and AOA, and the total bacteria, near the sediment-water interface. Separate models demonstrated a significant and independent effect of macrofaunal activities on community composition and richness of total bacteria, and diversity indices of metabolically active AOA. Diversity of β-AOB was significantly affected by macrofaunal abundance. Our results support the link between microbial biodiversity and ecosystem functioning in marine sediments, and provided broad correlative support for the hypothesis that this relationship is modulated by macrofaunal activity. We hypothesized that the latter effect can be explained by their bioturbating and bio-irrigating activities, increasing the spatial complexity of the biogeochemical environment.

Spatio-temporal variation in stream water chemistry in a tropical urban watershed

Treesearch

A. Ramirez; K.G. Rosas; A.E. Lugo; O.M. Ramos-Gonzalez

2014-01-01

Urban activities and related infrastructure alter the natural patterns of stream physical and chemical conditions. According to the Urban Stream Syndrome, streams draining urban landscapes are characterized by high concentrations of nutrients and ions, and might have elevated water temperatures and variable oxygen concentrations. Here, we report temporal and spatial...

Visual Circuit Development Requires Patterned Activity Mediated by Retinal Acetylcholine Receptors

PubMed Central

Burbridge, Timothy J.; Xu, Hong-Ping; Ackman, James B.; Ge, Xinxin; Zhang, Yueyi; Ye, Mei-Jun; Zhou, Z. Jimmy; Xu, Jian; Contractor, Anis; Crair, Michael C.

2014-01-01

SUMMARY The elaboration of nascent synaptic connections into highly ordered neural circuits is an integral feature of the developing vertebrate nervous system. In sensory systems, patterned spontaneous activity before the onset of sensation is thought to influence this process, but this conclusion remains controversial largely due to the inherent difficulty recording neural activity in early development. Here, we describe novel genetic and pharmacological manipulations of spontaneous retinal activity, assayed in vivo, that demonstrate a causal link between retinal waves and visual circuit refinement. We also report a de-coupling of downstream activity in retinorecipient regions of the developing brain after retinal wave disruption. Significantly, we show that the spatiotemporal characteristics of retinal waves affect the development of specific visual circuits. These results conclusively establish retinal waves as necessary and instructive for circuit refinement in the developing nervous system and reveal how neural circuits adjust to altered patterns of activity prior to experience. PMID:25466916

Spatiotemporal distribution patterns of forest fires in northern Mexico

Treesearch

Gustavo Pérez-Verdin; M. A. Márquez-Linares; A. Cortes-Ortiz; M. Salmerón-Macias

2013-01-01

Using the 2000-2011 CONAFOR databases, a spatiotemporal analysis of the occurrence of forest fires in Durango, one of the most affected States in Mexico, was conducted. The Moran's index was used to determine a spatial distribution pattern; also, an analysis of seasonal and temporal autocorrelation of the data collected was completed. The geographically weighted...

Using Passive and Active Acoustics to Examine Relationships of Cetacean and Prey Densities

DTIC Science & Technology

2015-09-30

modulation or production to the marine soundscape with daily, lunar, and seasonal patterns. We aim to document how presence and intensity of certain...sounds relate to spatio-temporal variability of active acoustic backscatter strength. Additionally, several marine mammal species are predators of deep...scattering layer (DSL) species as well as krill. We intend to investigate if passive acoustic marine mammal detections are related to increased

NeuroCa: integrated framework for systematic analysis of spatiotemporal neuronal activity patterns from large-scale optical recording data

PubMed Central

Jang, Min Jee; Nam, Yoonkey

2015-01-01

Abstract. Optical recording facilitates monitoring the activity of a large neural network at the cellular scale, but the analysis and interpretation of the collected data remain challenging. Here, we present a MATLAB-based toolbox, named NeuroCa, for the automated processing and quantitative analysis of large-scale calcium imaging data. Our tool includes several computational algorithms to extract the calcium spike trains of individual neurons from the calcium imaging data in an automatic fashion. Two algorithms were developed to decompose the imaging data into the activity of individual cells and subsequently detect calcium spikes from each neuronal signal. Applying our method to dense networks in dissociated cultures, we were able to obtain the calcium spike trains of ∼1000 neurons in a few minutes. Further analyses using these data permitted the quantification of neuronal responses to chemical stimuli as well as functional mapping of spatiotemporal patterns in neuronal firing within the spontaneous, synchronous activity of a large network. These results demonstrate that our method not only automates time-consuming, labor-intensive tasks in the analysis of neural data obtained using optical recording techniques but also provides a systematic way to visualize and quantify the collective dynamics of a network in terms of its cellular elements. PMID:26229973

Climate-mediated spatiotemporal variability in the terrestrial productivity across Europe

NASA Astrophysics Data System (ADS)

Wu, X.; Mahecha, M. D.; Reichstein, M.; Ciais, P.; Wattenbach, M.; Babst, F.; Frank, D.; Zang, C.

2013-11-01

Quantifying the interannual variability (IAV) of the terrestrial productivity and its sensitivity to climate is crucial for improving carbon budget predictions. However, the influence of climate and other mechanisms underlying the spatiotemporal patterns of IAV of productivity are not well understood. In this study we investigated the spatiotemporal patterns of IAV of historical observations of crop yields, tree ring width, remote sensing retrievals of FAPAR and NDVI, and other variables relevant to the terrestrial productivity in Europe in tandem with a set of climate variables. Our results reveal distinct spatial patterns in the IAV of most variables linked to terrestrial productivity. In particular, we find higher IAV in water-limited regions of Europe (Mediterranean and temperate continental Europe) compared to other regions. Our results further indicate that variations in the water balance during active growing season exert a more pronounced and direct effect than variations of temperature on explaining the spatial patterns in IAV of productivity related variables in temperate Europe. We also observe a~temporally increasing trend in the IAV of terrestrial productivity and an increasing sensitivity of productivity to water availability in dry regions of Europe, which is likely attributable to the recently increased IAV of water availability in these regions. These findings suggest nonlinear responses of carbon fluxes to climate variability in Europe and that the IAV of terrestrial productivity has become more sensitive and more vulnerable to changes in water availability in the dry regions in Europe. The changing climate sensitivity of terrestrial productivity accompanied by the changing IAV of climate could impact carbon stocks and the net carbon balance of European ecosystems.

Combining satellite-based fire observations and ground-based lightning detections to identify lightning fires across the conterminous USA

USGS Publications Warehouse

Bar-Massada, A.; Hawbaker, T.J.; Stewart, S.I.; Radeloff, V.C.

2012-01-01

Lightning fires are a common natural disturbance in North America, and account for the largest proportion of the area burned by wildfires each year. Yet, the spatiotemporal patterns of lightning fires in the conterminous US are not well understood due to limitations of existing fire databases. Our goal here was to develop and test an algorithm that combined MODIS fire detections with lightning detections from the National Lightning Detection Network to identify lightning fires across the conterminous US from 2000 to 2008. The algorithm searches for spatiotemporal conjunctions of MODIS fire clusters and NLDN detected lightning strikes, given a spatiotemporal lag between lightning strike and fire ignition. The algorithm revealed distinctive spatial patterns of lightning fires in the conterminous US While a sensitivity analysis revealed that the algorithm is highly sensitive to the two thresholds that are used to determine conjunction, the density of fires it detected was moderately correlated with ground based fire records. When only fires larger than 0.4 km2 were considered, correlations were higher and the root-mean-square error between datasets was less than five fires per 625 km2 for the entire study period. Our algorithm is thus suitable for detecting broad scale spatial patterns of lightning fire occurrence, and especially lightning fire hotspots, but has limited detection capability of smaller fires because these cannot be consistently detected by MODIS. These results may enhance our understanding of large scale patterns of lightning fire activity, and can be used to identify the broad scale factors controlling fire occurrence.

Geographic and temporal trends in influenzalike illness, Japan, 1992-1999.

PubMed

Sakai, Takatsugu; Suzuki, Hiroshi; Sasaki, Asami; Saito, Reiko; Tanabe, Naohito; Taniguchi, Kiyosu

2004-10-01

From 1992 to 1999, we analyzed >2.5 million cases of influenzalike illness (ILI). Nationwide influenza epidemics generally lasted 3-4 months in winter. Kriging analysis, which illustrates geographic movement, showed that the starting areas of peak ILI activity were mostly found in western Japan. Two spreading patterns, monotonous and multitonous, were observed. Monotonous patterns in two seasons featured peak ILI activity that covered all of Japan within 3 to 5 weeks in larger epidemics with new antigenic variants of A/H3N2. Multitonous patterns, observed in the other five seasons, featured peak ILI activity within 12 to 15 weeks in small epidemics without new variants. Applying the kriging method allowed better visualization and understanding of spatiotemporal trends in seasonal ILI activity. This method will likely be an important tool for future influenza surveillance in Japan.

Discovery of spatio-temporal patterns from location-based social networks

NASA Astrophysics Data System (ADS)

Béjar, J.; Álvarez, S.; García, D.; Gómez, I.; Oliva, L.; Tejeda, A.; Vázquez-Salceda, J.

2016-03-01

Location-based social networks (LBSNs) such as Twitter or Instagram are a good source for user spatio-temporal behaviour. These networks collect data from users in such a way that they can be seen as a set of collective and distributed sensors of a geographical area. A low rate sampling of user's location information can be obtained during large intervals of time that can be used to discover complex patterns, including mobility profiles, points of interest or unusual events. These patterns can be used as the elements of a knowledge base for different applications in different domains such as mobility route planning, touristic recommendation systems or city planning. The aim of this paper is twofold, first to analyse the frequent spatio-temporal patterns that users share when living and visiting a city. This behaviour is studied by means of frequent itemsets algorithms in order to establish some associations among visits that can be interpreted as interesting routes or spatio-temporal connections. Second, to analyse how the spatio-temporal behaviour of a large number of users can be segmented in different profiles. These behavioural profiles are obtained by means of clustering algorithms that show the different patterns of behaviour of visitors and citizens. The data analysed were obtained from the public data feeds of Twitter and Instagram within an area surrounding the cities of Barcelona and Milan for a period of several months. The analysis of these data shows that these kinds of algorithms can be successfully applied to data from any city (or general area) to discover useful patterns that can be interpreted on terms of singular places and areas and their temporal relationships.

Modeling how shark and dolphin skin patterns control transitional wall-turbulence vorticity patterns using spatiotemporal phase reset mechanisms

PubMed Central

Bandyopadhyay, Promode R.; Hellum, Aren M.

2014-01-01

Many slow-moving biological systems like seashells and zebrafish that do not contend with wall turbulence have somewhat organized pigmentation patterns flush with their outer surfaces that are formed by underlying autonomous reaction-diffusion (RD) mechanisms. In contrast, sharks and dolphins contend with wall turbulence, are fast swimmers, and have more organized skin patterns that are proud and sometimes vibrate. A nonlinear spatiotemporal analytical model is not available that explains the mechanism underlying control of flow with such proud patterns, despite the fact that shark and dolphin skins are major targets of reverse engineering mechanisms of drag and noise reduction. Comparable to RD, a minimal self-regulation model is given for wall turbulence regeneration in the transitional regime—laterally coupled, diffusively—which, although restricted to pre-breakdown durations and to a plane close and parallel to the wall, correctly reproduces many experimentally observed spatiotemporal organizations of vorticity in both laminar-to-turbulence transitioning and very low Reynolds number but turbulent regions. We further show that the onset of vorticity disorganization is delayed if the skin organization is treated as a spatiotemporal template of olivo-cerebellar phase reset mechanism. The model shows that the adaptation mechanisms of sharks and dolphins to their fluid environment have much in common. PMID:25338940

Modeling how shark and dolphin skin patterns control transitional wall-turbulence vorticity patterns using spatiotemporal phase reset mechanisms.

PubMed

Bandyopadhyay, Promode R; Hellum, Aren M

2014-10-23

Many slow-moving biological systems like seashells and zebrafish that do not contend with wall turbulence have somewhat organized pigmentation patterns flush with their outer surfaces that are formed by underlying autonomous reaction-diffusion (RD) mechanisms. In contrast, sharks and dolphins contend with wall turbulence, are fast swimmers, and have more organized skin patterns that are proud and sometimes vibrate. A nonlinear spatiotemporal analytical model is not available that explains the mechanism underlying control of flow with such proud patterns, despite the fact that shark and dolphin skins are major targets of reverse engineering mechanisms of drag and noise reduction. Comparable to RD, a minimal self-regulation model is given for wall turbulence regeneration in the transitional regime--laterally coupled, diffusively--which, although restricted to pre-breakdown durations and to a plane close and parallel to the wall, correctly reproduces many experimentally observed spatiotemporal organizations of vorticity in both laminar-to-turbulence transitioning and very low Reynolds number but turbulent regions. We further show that the onset of vorticity disorganization is delayed if the skin organization is treated as a spatiotemporal template of olivo-cerebellar phase reset mechanism. The model shows that the adaptation mechanisms of sharks and dolphins to their fluid environment have much in common.

Detailed spatiotemporal brain mapping of chromatic vision combining high-resolution VEP with fMRI and retinotopy.

PubMed

Pitzalis, Sabrina; Strappini, Francesca; Bultrini, Alessandro; Di Russo, Francesco

2018-03-13

Neuroimaging studies have identified so far, several color-sensitive visual areas in the human brain, and the temporal dynamics of these activities have been separately investigated using the visual-evoked potentials (VEPs). In the present study, we combined electrophysiological and neuroimaging methods to determine a detailed spatiotemporal profile of chromatic VEP and to localize its neural generators. The accuracy of the present co-registration study was obtained by combining standard fMRI data with retinotopic and motion mapping data at the individual level. We found a sequence of occipito activities more complex than that typically reported for chromatic VEPs, including feed-forward and reentrant feedback. Results showed that chromatic human perception arises by the combined activity of at the least five parieto-occipital areas including V1, LOC, V8/VO, and the motion-sensitive dorsal region MT+. However, the contribution of V1 and V8/VO seems dominant because the re-entrant activity in these areas was present more than once (twice in V8/VO and thrice in V1). This feedforward and feedback chromatic processing appears delayed compared with the luminance processing. Associating VEPs and neuroimaging measures, we showed for the first time a complex spatiotemporal pattern of activity, confirming that chromatic stimuli produce intricate interactions of many different brain dorsal and ventral areas. © 2018 Wiley Periodicals, Inc.

Spatiotemporal pattern formation in a prey-predator model under environmental driving forces

NASA Astrophysics Data System (ADS)

Sirohi, Anuj Kumar; Banerjee, Malay; Chakraborti, Anirban

2015-09-01

Many existing studies on pattern formation in the reaction-diffusion systems rely on deterministic models. However, environmental noise is often a major factor which leads to significant changes in the spatiotemporal dynamics. In this paper, we focus on the spatiotemporal patterns produced by the predator-prey model with ratio-dependent functional response and density dependent death rate of predator. We get the reaction-diffusion equations incorporating the self-diffusion terms, corresponding to random movement of the individuals within two dimensional habitats, into the growth equations for the prey and predator population. In order to have the noise added model, small amplitude heterogeneous perturbations to the linear intrinsic growth rates are introduced using uncorrelated Gaussian white noise terms. For the noise added system, we then observe spatial patterns for the parameter values lying outside the Turing instability region. With thorough numerical simulations we characterize the patterns corresponding to Turing and Turing-Hopf domain and study their dependence on different system parameters like noise-intensity, etc.

Spontaneous formation of spiral-like patterns with distinct periodic physical properties by confined electrodeposition of Co-In disks

NASA Astrophysics Data System (ADS)

Golvano-Escobal, Irati; Gonzalez-Rosillo, Juan Carlos; Domingo, Neus; Illa, Xavi; López-Barberá, José Francisco; Fornell, Jordina; Solsona, Pau; Aballe, Lucia; Foerster, Michael; Suriñach, Santiago; Baró, Maria Dolors; Puig, Teresa; Pané, Salvador; Nogués, Josep; Pellicer, Eva; Sort, Jordi

2016-07-01

Spatio-temporal patterns are ubiquitous in different areas of materials science and biological systems. However, typically the motifs in these types of systems present a random distribution with many possible different structures. Herein, we demonstrate that controlled spatio-temporal patterns, with reproducible spiral-like shapes, can be obtained by electrodeposition of Co-In alloys inside a confined circular geometry (i.e., in disks that are commensurate with the typical size of the spatio-temporal features). These patterns are mainly of compositional nature, i.e., with virtually no topographic features. Interestingly, the local changes in composition lead to a periodic modulation of the physical (electric, magnetic and mechanical) properties. Namely, the Co-rich areas show higher saturation magnetization and electrical conductivity and are mechanically harder than the In-rich ones. Thus, this work reveals that confined electrodeposition of this binary system constitutes an effective procedure to attain template-free magnetic, electric and mechanical surface patterning with specific and reproducible shapes.

Spatiotemporal Patterns of Schistosomiasis-Related Deaths, Brazil, 2000–2011

PubMed Central

Martins-Melo, Francisco Rogerlândio; Pinheiro, Marta Cristhiany Cunha; Ramos, Alberto Novaes; Alencar, Carlos Henrique; Bezerra, Fernando Schemelzer de Moraes

2015-01-01

We analyzed spatiotemporal patterns of 8,756 schistosomiasis-related deaths in Brazil during 2000–2011 and identified high-risk clusters of deaths, mainly in highly schistosomiasis-endemic areas along the coast of Brazil’s Northeast Region. Schistosomiasis remains a neglected public health problem with a high number of deaths in disease-endemic and emerging focal areas. PMID:26401716

The transcription factor Grainy head primes epithelial enhancers for spatiotemporal activation by displacing nucleosomes.

PubMed

Jacobs, Jelle; Atkins, Mardelle; Davie, Kristofer; Imrichova, Hana; Romanelli, Lucia; Christiaens, Valerie; Hulselmans, Gert; Potier, Delphine; Wouters, Jasper; Taskiran, Ibrahim I; Paciello, Giulia; González-Blas, Carmen B; Koldere, Duygu; Aibar, Sara; Halder, Georg; Aerts, Stein

2018-06-04

Transcriptional enhancers function as docking platforms for combinations of transcription factors (TFs) to control gene expression. How enhancer sequences determine nucleosome occupancy, TF recruitment and transcriptional activation in vivo remains unclear. Using ATAC-seq across a panel of Drosophila inbred strains, we found that SNPs affecting binding sites of the TF Grainy head (Grh) causally determine the accessibility of epithelial enhancers. We show that deletion and ectopic expression of Grh cause loss and gain of DNA accessibility, respectively. However, although Grh binding is necessary for enhancer accessibility, it is insufficient to activate enhancers. Finally, we show that human Grh homologs-GRHL1, GRHL2 and GRHL3-function similarly. We conclude that Grh binding is necessary and sufficient for the opening of epithelial enhancers but not for their activation. Our data support a model positing that complex spatiotemporal expression patterns are controlled by regulatory hierarchies in which pioneer factors, such as Grh, establish tissue-specific accessible chromatin landscapes upon which other factors can act.

Hand gesture recognition in confined spaces with partial observability and occultation constraints

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir; Chan, Alex; Hu, Shuowen

2016-05-01

Human activity detection and recognition capabilities have broad applications for military and homeland security. These tasks are very complicated, however, especially when multiple persons are performing concurrent activities in confined spaces that impose significant obstruction, occultation, and observability uncertainty. In this paper, our primary contribution is to present a dedicated taxonomy and kinematic ontology that are developed for in-vehicle group human activities (IVGA). Secondly, we describe a set of hand-observable patterns that represents certain IVGA examples. Thirdly, we propose two classifiers for hand gesture recognition and compare their performance individually and jointly. Finally, we present a variant of Hidden Markov Model for Bayesian tracking, recognition, and annotation of hand motions, which enables spatiotemporal inference to human group activity perception and understanding. To validate our approach, synthetic (graphical data from virtual environment) and real physical environment video imagery are employed to verify the performance of these hand gesture classifiers, while measuring their efficiency and effectiveness based on the proposed Hidden Markov Model for tracking and interpreting dynamic spatiotemporal IVGA scenarios.

Spatiotemporal patterns of unburned areas within fire perimeters in the northwestern United States from 1984 to 2014

Treesearch

Arjan J. H. Meddens; Crystal A. Kolden; James A. Lutz; John T. Abatzoglou; Andrew T. Hudak

2018-01-01

A warming climate, fire exclusion, and land cover changes are altering the conditions that produced historical fire regimes and facilitating increased recent wildfire activity in the northwestern United States. Understanding the impacts of changing fire regimes on forest recruitment and succession, species distributions, carbon cycling, and ecosystem services is...

Transition from propagating localized states to spatiotemporal chaos in phase dynamics

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

Brand, H.R.; Deissler, R.J.; Brand, H.R.

1998-10-01

We study the nonlinear phase equation for propagating patterns. We investigate the transition from a propagating localized pattern to a space-filling spatiotemporally disordered pattern and discuss in detail to what extent there are propagating localized states that breathe in time periodically, quasiperiodically, and chaotically. Differences and similarities to the phenomena occurring for the quintic complex Ginzburg-Landau equation are elucidated. We also discuss for which experimentally accessible systems one could observe the phenomena described. {copyright} {ital 1998} {ital The American Physical Society}

Recruitment of local inhibitory networks by horizontal connections in layer 2/3 of ferret visual cortex.

PubMed

Tucker, Thomas R; Katz, Lawrence C

2003-01-01

To investigate how neurons in cortical layer 2/3 integrate horizontal inputs arising from widely distributed sites, we combined intracellular recording and voltage-sensitive dye imaging to visualize the spatiotemporal dynamics of neuronal activity evoked by electrical stimulation of multiple sites in visual cortex. Individual stimuli evoked characteristic patterns of optical activity, while delivering stimuli at multiple sites generated interacting patterns in the regions of overlap. We observed that neurons in overlapping regions received convergent horizontal activation that generated nonlinear responses due to the emergence of large inhibitory potentials. The results indicate that co-activation of multiple sets of horizontal connections recruit strong inhibition from local inhibitory networks, causing marked deviations from simple linear integration.

The characteristic patterns of neuronal avalanches in mice under anesthesia and at rest: An investigation using constrained artificial neural networks

PubMed Central

Knöpfel, Thomas; Leech, Robert

2018-01-01

Local perturbations within complex dynamical systems can trigger cascade-like events that spread across significant portions of the system. Cascades of this type have been observed across a broad range of scales in the brain. Studies of these cascades, known as neuronal avalanches, usually report the statistics of large numbers of avalanches, without probing the characteristic patterns produced by the avalanches themselves. This is partly due to limitations in the extent or spatiotemporal resolution of commonly used neuroimaging techniques. In this study, we overcome these limitations by using optical voltage (genetically encoded voltage indicators) imaging. This allows us to record cortical activity in vivo across an entire cortical hemisphere, at both high spatial (~30um) and temporal (~20ms) resolution in mice that are either in an anesthetized or awake state. We then use artificial neural networks to identify the characteristic patterns created by neuronal avalanches in our data. The avalanches in the anesthetized cortex are most accurately classified by an artificial neural network architecture that simultaneously connects spatial and temporal information. This is in contrast with the awake cortex, in which avalanches are most accurately classified by an architecture that treats spatial and temporal information separately, due to the increased levels of spatiotemporal complexity. This is in keeping with reports of higher levels of spatiotemporal complexity in the awake brain coinciding with features of a dynamical system operating close to criticality. PMID:29795654

Spatiotemporal Processing in Crossmodal Interactions for Perception of the External World: A Review

PubMed Central

Hidaka, Souta; Teramoto, Wataru; Sugita, Yoichi

2015-01-01

Research regarding crossmodal interactions has garnered much interest in the last few decades. A variety of studies have demonstrated that multisensory information (vision, audition, tactile sensation, and so on) can perceptually interact with each other in the spatial and temporal domains. Findings regarding crossmodal interactions in the spatiotemporal domain (i.e., motion processing) have also been reported, with updates in the last few years. In this review, we summarize past and recent findings on spatiotemporal processing in crossmodal interactions regarding perception of the external world. A traditional view regarding crossmodal interactions holds that vision is superior to audition in spatial processing, but audition is dominant over vision in temporal processing. Similarly, vision is considered to have dominant effects over the other sensory modalities (i.e., visual capture) in spatiotemporal processing. However, recent findings demonstrate that sound could have a driving effect on visual motion perception. Moreover, studies regarding perceptual associative learning reported that, after association is established between a sound sequence without spatial information and visual motion information, the sound sequence could trigger visual motion perception. Other sensory information, such as motor action or smell, has also exhibited similar driving effects on visual motion perception. Additionally, recent brain imaging studies demonstrate that similar activation patterns could be observed in several brain areas, including the motion processing areas, between spatiotemporal information from different sensory modalities. Based on these findings, we suggest that multimodal information could mutually interact in spatiotemporal processing in the percept of the external world and that common perceptual and neural underlying mechanisms would exist for spatiotemporal processing. PMID:26733827

Spatio-Temporal Patterns in Colonies of Rod-Shaped Bacteria

NASA Astrophysics Data System (ADS)

Kitsunezaki, S.

In incubation experiments of bacterial colonies of Proteus Mirabilis, macroscopic spatio-temporal patterns, such as turbulent and unidirectional spiral patterns, appear in colonies. Considering only kinetic propeties of rod-shaped bacteria, we propose a phenomenological model for the directional and positional distributions. As the average density increases, homogeneous states bifurcate sub-critically into nonuniform states exhibiting localized collective motion, and spiral patterns appear for sufficiently large density. These patterns result from interactions between the local bacteria densities and the order parameter representing collective motion. Our model can be described by reduced equations using a perturbative method for large density. The unidirectionality of sprial rotation is also discussed.

Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.

PubMed

Albers, Christian; Westkott, Maren; Pawelzik, Klaus

2016-01-01

Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns.

Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity

PubMed Central

Albers, Christian; Westkott, Maren; Pawelzik, Klaus

2016-01-01

Precise spatio-temporal patterns of neuronal action potentials underly e.g. sensory representations and control of muscle activities. However, it is not known how the synaptic efficacies in the neuronal networks of the brain adapt such that they can reliably generate spikes at specific points in time. Existing activity-dependent plasticity rules like Spike-Timing-Dependent Plasticity are agnostic to the goal of learning spike times. On the other hand, the existing formal and supervised learning algorithms perform a temporally precise comparison of projected activity with the target, but there is no known biologically plausible implementation of this comparison. Here, we propose a simple and local unsupervised synaptic plasticity mechanism that is derived from the requirement of a balanced membrane potential. Since the relevant signal for synaptic change is the postsynaptic voltage rather than spike times, we call the plasticity rule Membrane Potential Dependent Plasticity (MPDP). Combining our plasticity mechanism with spike after-hyperpolarization causes a sensitivity of synaptic change to pre- and postsynaptic spike times which can reproduce Hebbian spike timing dependent plasticity for inhibitory synapses as was found in experiments. In addition, the sensitivity of MPDP to the time course of the voltage when generating a spike allows MPDP to distinguish between weak (spurious) and strong (teacher) spikes, which therefore provides a neuronal basis for the comparison of actual and target activity. For spatio-temporal input spike patterns our conceptually simple plasticity rule achieves a surprisingly high storage capacity for spike associations. The sensitivity of the MPDP to the subthreshold membrane potential during training allows robust memory retrieval after learning even in the presence of activity corrupted by noise. We propose that MPDP represents a biophysically plausible mechanism to learn temporal target activity patterns. PMID:26900845

Active Brownian Particles. From Individual to Collective Stochastic Dynamics

NASA Astrophysics Data System (ADS)

Romanczuk, P.; Bär, M.; Ebeling, W.; Lindner, B.; Schimansky-Geier, L.

2012-03-01

We review theoretical models of individual motility as well as collective dynamics and pattern formation of active particles. We focus on simple models of active dynamics with a particular emphasis on nonlinear and stochastic dynamics of such self-propelled entities in the framework of statistical mechanics. Examples of such active units in complex physico-chemical and biological systems are chemically powered nano-rods, localized patterns in reaction-diffusion system, motile cells or macroscopic animals. Based on the description of individual motion of point-like active particles by stochastic differential equations, we discuss different velocity-dependent friction functions, the impact of various types of fluctuations and calculate characteristic observables such as stationary velocity distributions or diffusion coefficients. Finally, we consider not only the free and confined individual active dynamics but also different types of interaction between active particles. The resulting collective dynamical behavior of large assemblies and aggregates of active units is discussed and an overview over some recent results on spatiotemporal pattern formation in such systems is given.

Emergence and transitions of dynamic patterns of thickness oscillation of the plasmodium of the true slime mold Physarum polycephalum

NASA Astrophysics Data System (ADS)

Takagi, Seiji; Ueda, Tetsuo

2008-03-01

The emergence and transitions of various spatiotemporal patterns of thickness oscillation were studied in the freshly isolated protoplasm of the Physarum plasmodium. New patterns, such as standing waves, and chaotic and rotating spirals, developed successively before the well-documented synchronous pattern appeared. There was also a spontaneous opposite transition from synchrony to chaotic and rotating spirals. Rotating spiral waves were observed in the large migrating plasmodium, where the vein structures were being destroyed. Thus, the Physarum plasmodium exhibits versatile patterns, which are generally expected in coupled oscillator systems. This paper discusses the physiological roles of spatiotemporal patterns, comparing them with other biological systems.

Spatial distribution of tree species governs the spatio-temporal interaction of leaf area index and soil moisture across a forested landscape.

PubMed

Naithani, Kusum J; Baldwin, Doug C; Gaines, Katie P; Lin, Henry; Eissenstat, David M

2013-01-01

Quantifying coupled spatio-temporal dynamics of phenology and hydrology and understanding underlying processes is a fundamental challenge in ecohydrology. While variation in phenology and factors influencing it have attracted the attention of ecologists for a long time, the influence of biodiversity on coupled dynamics of phenology and hydrology across a landscape is largely untested. We measured leaf area index (L) and volumetric soil water content (θ) on a co-located spatial grid to characterize forest phenology and hydrology across a forested catchment in central Pennsylvania during 2010. We used hierarchical Bayesian modeling to quantify spatio-temporal patterns of L and θ. Our results suggest that the spatial distribution of tree species across the landscape created unique spatio-temporal patterns of L, which created patterns of water demand reflected in variable soil moisture across space and time. We found a lag of about 11 days between increase in L and decline in θ. Vegetation and soil moisture become increasingly homogenized and coupled from leaf-onset to maturity but heterogeneous and uncoupled from leaf maturity to senescence. Our results provide insight into spatio-temporal coupling between biodiversity and soil hydrology that is useful to enhance ecohydrological modeling in humid temperate forests.

Spatio-temporal scaling effects on longshore sediment transport pattern along the nearshore zone

NASA Astrophysics Data System (ADS)

Khorram, Saeed; Ergil, Mustafa

2018-03-01

A measure of uncertainties, entropy has been employed in such different applications as coastal engineering probability inferences. Entropy sediment transport integration theories present novel visions in coastal analyses/modeling the application and development of which are still far-reaching. Effort has been made in the present paper to propose a method that needs an entropy-power index for spatio-temporal patterns analyses. Results have shown that the index is suitable for marine/hydrological ecosystem components analyses based on a beach area case study. The method makes use of six Makran Coastal monthly data (1970-2015) and studies variables such as spatio-temporal patterns, LSTR (long-shore sediment transport rate), wind speed, and wave height all of which are time-dependent and play considerable roles in terrestrial coastal investigations; the mentioned variables show meaningful spatio-temporal variability most of the time, but explanation of their combined performance is not easy. Accordingly, the use of an entropy-power index can show considerable signals that facilitate the evaluation of water resources and will provide an insight regarding hydrological parameters' interactions at scales as large as beach areas. Results have revealed that an STDDPI (entropy based spatio-temporal disorder dynamics power index) can simulate wave, long-shore sediment transport rate, and wind when granulometry, concentration, and flow conditions vary.

Hierarchical Bayesian modeling of spatio-temporal patterns of lung cancer incidence risk in Georgia, USA: 2000-2007

NASA Astrophysics Data System (ADS)

Yin, Ping; Mu, Lan; Madden, Marguerite; Vena, John E.

2014-10-01

Lung cancer is the second most commonly diagnosed cancer in both men and women in Georgia, USA. However, the spatio-temporal patterns of lung cancer risk in Georgia have not been fully studied. Hierarchical Bayesian models are used here to explore the spatio-temporal patterns of lung cancer incidence risk by race and gender in Georgia for the period of 2000-2007. With the census tract level as the spatial scale and the 2-year period aggregation as the temporal scale, we compare a total of seven Bayesian spatio-temporal models including two under a separate modeling framework and five under a joint modeling framework. One joint model outperforms others based on the deviance information criterion. Results show that the northwest region of Georgia has consistently high lung cancer incidence risk for all population groups during the study period. In addition, there are inverse relationships between the socioeconomic status and the lung cancer incidence risk among all Georgian population groups, and the relationships in males are stronger than those in females. By mapping more reliable variations in lung cancer incidence risk at a relatively fine spatio-temporal scale for different Georgian population groups, our study aims to better support healthcare performance assessment, etiological hypothesis generation, and health policy making.

Mining User spatiotemporal Behavior in Geospatial Cyberinfrastructure --using GEOSS Clearinghouse as an example

NASA Astrophysics Data System (ADS)

XIA, J.; Yang, C.; Liu, K.; Huang, Q.; Li, Z.

2013-12-01

Big Data becomes increasingly important in almost all scientific domains, especially in geoscience where hundreds to millions of sensors are collecting data of the Earth continuously (Whitehouse News 2012). With the explosive growth of data, various Geospatial Cyberinfrastructure (GCI) (Yang et al. 2010) components are developed to manage geospatial resources and provide data access for the public. These GCIs are accessed by different users intensively on a daily basis. However, little research has been done to analyze the spatiotemporal patterns of user behavior, which could be critical to the management of Big Data and the operation of GCIs (Yang et al. 2011). For example, the spatiotemporal distribution of end users helps us better arrange and locate GCI computing facilities. A better indexing and caching mechanism could be developed based on the spatiotemporal pattern of user queries. In this paper, we use GEOSS Clearinghouse as an example to investigate spatiotemporal patterns of user behavior in GCIs. The investigation results show that user behaviors are heterogeneous but with patterns across space and time. Identified patterns include (1) the high access frequency regions; (2) local interests; (3) periodical accesses and rush hours; (4) spiking access. Based on identified patterns, this presentation reports several solutions to better support the operation of the GEOSS Clearinghouse and other GCIs. Keywords: Big Data, EarthCube, CyberGIS, Spatiotemporal Thinking and Computing, Data Mining, User Behavior Reference: Fayyad, U. M., Piatetsky-Shapiro, G., Smyth, P., & Uthurusamy, R. 1996. Advances in knowledge discovery and data mining. Whitehouse. 2012. Obama administration unveils 'BIG DATA' initiative: announces $200 million in new R&D investments. Whitehouse. Retrieved from http://www.whitehouse.gov/sites/default/files/microsites/ostp/big_data_press_release_final_2.pdf [Accessed 14 June 2013] Yang, C., Wu, H., Huang, Q., Li, Z., & Li, J. 2011. Using spatial principles to optimize distributed computing for enabling the physical science discoveries. Proceedings of the National Academy of Sciences, 108(14), 5498-5503. doi:10.1073/pnas.0909315108 Yang, C., Raskin, R., Goodchild, M., & Gahegan, M. 2010. Geospatial Cyberinfrastructure: Past, present and future. Computers, Environment and Urban Systems, 34(4), 264-277. doi:10.1016/j.compenvurbsys.2010.04.001

Mathematical Modeling the Geometric Regularity in Proteus Mirabilis Colonies

NASA Astrophysics Data System (ADS)

Zhang, Bin; Jiang, Yi; Minsu Kim Collaboration

Proteus Mirabilis colony exhibits striking spatiotemporal regularity, with concentric ring patterns with alternative high and low bacteria density in space, and periodicity for repetition process of growth and swarm in time. We present a simple mathematical model to explain the spatiotemporal regularity of P. Mirabilis colonies. We study a one-dimensional system. Using a reaction-diffusion model with thresholds in cell density and nutrient concentration, we recreated periodic growth and spread patterns, suggesting that the nutrient constraint and cell density regulation might be sufficient to explain the spatiotemporal periodicity in P. Mirabilis colonies. We further verify this result using a cell based model.

Characterization of New Otic Enhancers of the Pou3f4 Gene Reveal Distinct Signaling Pathway Regulation and Spatio-Temporal Patterns

PubMed Central

Robert-Moreno, Àlex; Naranjo, Silvia; de la Calle-Mustienes, Elisa; Gómez-Skarmeta, José Luis; Alsina, Berta

2010-01-01

POU3F4 is a member of the POU-homedomain transcription factor family with a prominent role in inner ear development. Mutations in the human POU3F4 coding unit leads to X-linked deafness type 3 (DFN3), characterized by conductive hearing loss and progressive sensorineural deafness. Microdeletions found 1 Mb 5′ upstream of the coding region also displayed the same phenotype, suggesting that cis-regulatory elements might be present in that region. Indeed, we and others have recently identified several enhancers at the 1 Mb 5′ upstream interval of the pou3f4 locus. Here we characterize the spatio-temporal patterns of these regulatory elements in zebrafish transgenic lines. We show that the most distal enhancer (HCNR 81675) is activated earlier and drives GFP reporter expression initially to a broad ear domain to progressively restrict to the sensory patches. The proximal enhancer (HCNR 82478) is switched later during development and promotes expression, among in other tissues, in sensory patches from its onset. The third enhancer (HCNR 81728) is also active at later stages in the otic mesenchyme and in the otic epithelium. We also characterize the signaling pathways regulating these enhancers. While HCNR 81675 is regulated by very early signals of retinoic acid, HCNR 82478 is regulated by Fgf activity at a later stage and the HCNR 81728 enhancer is under the control of Hh signaling. Finally, we show that Sox2 and Pax2 transcription factors are bound to HCNR 81675 genomic region during otic development and specific mutations to these transcription factor binding sites abrogates HCNR 81675 enhancer activity. Altogether, our results suggest that pou3f4 expression in inner ear might be under the control of distinct regulatory elements that fine-tune the spatio-temporal activity of this gene and provides novel data on the signaling mechanisms controlling pou3f4 function. PMID:21209840

Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior.

PubMed

Portugues, Ruben; Feierstein, Claudia E; Engert, Florian; Orger, Michael B

2014-03-19

Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate but ordered pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments systematically reveal the functional architecture of neural circuits underlying a sensorimotor behavior in a vertebrate brain. Copyright © 2014 Elsevier Inc. All rights reserved.

Whole-brain activity maps reveal stereotyped, distributed networks for visuomotor behavior

PubMed Central

Portugues, Ruben; Feierstein, Claudia E.; Engert, Florian; Orger, Michael B.

2014-01-01

Summary Most behaviors, even simple innate reflexes, are mediated by circuits of neurons spanning areas throughout the brain. However, in most cases, the distribution and dynamics of firing patterns of these neurons during behavior are not known. We imaged activity, with cellular resolution, throughout the whole brains of zebrafish performing the optokinetic response. We found a sparse, broadly distributed network that has an elaborate, but ordered, pattern, with a bilaterally symmetrical organization. Activity patterns fell into distinct clusters reflecting sensory and motor processing. By correlating neuronal responses with an array of sensory and motor variables, we find that the network can be clearly divided into distinct functional modules. Comparing aligned data from multiple fish, we find that the spatiotemporal activity dynamics and functional organization are highly stereotyped across individuals. These experiments reveal, for the first time in a vertebrate, the comprehensive functional architecture of the neural circuits underlying a sensorimotor behavior. PMID:24656252

Rotating waves during human sleep spindles organize global patterns of activity that repeat precisely through the night

PubMed Central

Muller, Lyle; Piantoni, Giovanni; Koller, Dominik; Cash, Sydney S; Halgren, Eric; Sejnowski, Terrence J

2016-01-01

During sleep, the thalamus generates a characteristic pattern of transient, 11-15 Hz sleep spindle oscillations, which synchronize the cortex through large-scale thalamocortical loops. Spindles have been increasingly demonstrated to be critical for sleep-dependent consolidation of memory, but the specific neural mechanism for this process remains unclear. We show here that cortical spindles are spatiotemporally organized into circular wave-like patterns, organizing neuronal activity over tens of milliseconds, within the timescale for storing memories in large-scale networks across the cortex via spike-time dependent plasticity. These circular patterns repeat over hours of sleep with millisecond temporal precision, allowing reinforcement of the activity patterns through hundreds of reverberations. These results provide a novel mechanistic account for how global sleep oscillations and synaptic plasticity could strengthen networks distributed across the cortex to store coherent and integrated memories. DOI: http://dx.doi.org/10.7554/eLife.17267.001 PMID:27855061

Cortical activity patterns predict robust speech discrimination ability in noise

PubMed Central

Shetake, Jai A.; Wolf, Jordan T.; Cheung, Ryan J.; Engineer, Crystal T.; Ram, Satyananda K.; Kilgard, Michael P.

2012-01-01

The neural mechanisms that support speech discrimination in noisy conditions are poorly understood. In quiet conditions, spike timing information appears to be used in the discrimination of speech sounds. In this study, we evaluated the hypothesis that spike timing is also used to distinguish between speech sounds in noisy conditions that significantly degrade neural responses to speech sounds. We tested speech sound discrimination in rats and recorded primary auditory cortex (A1) responses to speech sounds in background noise of different intensities and spectral compositions. Our behavioral results indicate that rats, like humans, are able to accurately discriminate consonant sounds even in the presence of background noise that is as loud as the speech signal. Our neural recordings confirm that speech sounds evoke degraded but detectable responses in noise. Finally, we developed a novel neural classifier that mimics behavioral discrimination. The classifier discriminates between speech sounds by comparing the A1 spatiotemporal activity patterns evoked on single trials with the average spatiotemporal patterns evoked by known sounds. Unlike classifiers in most previous studies, this classifier is not provided with the stimulus onset time. Neural activity analyzed with the use of relative spike timing was well correlated with behavioral speech discrimination in quiet and in noise. Spike timing information integrated over longer intervals was required to accurately predict rat behavioral speech discrimination in noisy conditions. The similarity of neural and behavioral discrimination of speech in noise suggests that humans and rats may employ similar brain mechanisms to solve this problem. PMID:22098331

Tracking and visualization of space-time activities for a micro-scale flu transmission study.

PubMed

Qi, Feng; Du, Fei

2013-02-07

Infectious diseases pose increasing threats to public health with increasing population density and more and more sophisticated social networks. While efforts continue in studying the large scale dissemination of contagious diseases, individual-based activity and behaviour study benefits not only disease transmission modelling but also the control, containment, and prevention decision making at the local scale. The potential for using tracking technologies to capture detailed space-time trajectories and model individual behaviour is increasing rapidly, as technological advances enable the manufacture of small, lightweight, highly sensitive, and affordable receivers and the routine use of location-aware devices has become widespread (e.g., smart cellular phones). The use of low-cost tracking devices in medical research has also been proved effective by more and more studies. This study describes the use of tracking devices to collect data of space-time trajectories and the spatiotemporal processing of such data to facilitate micro-scale flu transmission study. We also reports preliminary findings on activity patterns related to chances of influenza infection in a pilot study. Specifically, this study employed A-GPS tracking devices to collect data on a university campus. Spatiotemporal processing was conducted for data cleaning and segmentation. Processed data was validated with traditional activity diaries. The A-GPS data set was then used for visual explorations including density surface visualization and connection analysis to examine space-time activity patterns in relation to chances of influenza infection. When compared to diary data, the segmented tracking data demonstrated to be an effective alternative and showed greater accuracies in time as well as the details of routes taken by participants. A comparison of space-time activity patterns between participants who caught seasonal influenza and those who did not revealed interesting patterns. This study proved that tracking technology an effective technique for obtaining data for micro-scale influenza transmission research. The findings revealed micro-scale transmission hotspots on a university campus and provided insights for local control and prevention strategies.

Spatiotemporal Dynamics of a Network of Coupled Time-Delay Digital Tanlock Loops

NASA Astrophysics Data System (ADS)

Paul, Bishwajit; Banerjee, Tanmoy; Sarkar, B. C.

The time-delay digital tanlock loop (TDTLs) is an important class of phase-locked loop that is widely used in electronic communication systems. Although nonlinear dynamics of an isolated TDTL has been studied in the past but the collective behavior of TDTLs in a network is an important topic of research and deserves special attention as in practical communication systems separate entities are rarely isolated. In this paper, we carry out the detailed analysis and numerical simulations to explore the spatiotemporal dynamics of a network of a one-dimensional ring of coupled TDTLs with nearest neighbor coupling. The equation representing the network is derived and we carry out analytical calculations using the circulant matrix formalism to obtain the stability criteria. An extensive numerical simulation reveals that with the variation of gain parameter and coupling strength the network shows a variety of spatiotemporal dynamics such as frozen random pattern, pattern selection, spatiotemporal intermittency and fully developed spatiotemporal chaos. We map the distinct dynamical regions of the system in two-parameter space. Finally, we quantify the spatiotemporal dynamics by using quantitative measures like Lyapunov exponent and the average quadratic deviation of the full network.

Mining local climate data to assess spatiotemporal dengue fever epidemic patterns in French Guiana

PubMed Central

Flamand, Claude; Fabregue, Mickael; Bringay, Sandra; Ardillon, Vanessa; Quénel, Philippe; Desenclos, Jean-Claude; Teisseire, Maguelonne

2014-01-01

Objective To identify local meteorological drivers of dengue fever in French Guiana, we applied an original data mining method to the available epidemiological and climatic data. Through this work, we also assessed the contribution of the data mining method to the understanding of factors associated with the dissemination of infectious diseases and their spatiotemporal spread. Methods We applied contextual sequential pattern extraction techniques to epidemiological and meteorological data to identify the most significant climatic factors for dengue fever, and we investigated the relevance of the extracted patterns for the early warning of dengue outbreaks in French Guiana. Results The maximum temperature, minimum relative humidity, global brilliance, and cumulative rainfall were identified as determinants of dengue outbreaks, and the precise intervals of their values and variations were quantified according to the epidemiologic context. The strongest significant correlations were observed between dengue incidence and meteorological drivers after a 4–6-week lag. Discussion We demonstrated the use of contextual sequential patterns to better understand the determinants of the spatiotemporal spread of dengue fever in French Guiana. Future work should integrate additional variables and explore the notion of neighborhood for extracting sequential patterns. Conclusions Dengue fever remains a major public health issue in French Guiana. The development of new methods to identify such specific characteristics becomes crucial in order to better understand and control spatiotemporal transmission. PMID:24549761

Spatiotemporal analysis of tumor uptake patterns in dynamic (18)FDG-PET and dynamic contrast enhanced CT.

PubMed

Malinen, Eirik; Rødal, Jan; Knudtsen, Ingerid Skjei; Søvik, Åste; Skogmo, Hege Kippenes

2011-08-01

Molecular and functional imaging techniques such as dynamic positron emission tomography (DPET) and dynamic contrast enhanced computed tomography (DCECT) may provide improved characterization of tumors compared to conventional anatomic imaging. The purpose of the current work was to compare spatiotemporal uptake patterns in DPET and DCECT images. A PET/CT protocol comprising DCECT with an iodine based contrast agent and DPET with (18)F-fluorodeoxyglucose was set up. The imaging protocol was used for examination of three dogs with spontaneous tumors of the head and neck at sessions prior to and after fractionated radiotherapy. Software tools were developed for downsampling the DCECT image series to the PET image dimensions, for segmentation of tracer uptake pattern in the tumors and for spatiotemporal correlation analysis of DCECT and DPET images. DCECT images evaluated one minute post injection qualitatively resembled the DPET images at most imaging sessions. Segmentation by region growing gave similar tumor extensions in DCECT and DPET images, with a median Dice similarity coefficient of 0.81. A relatively high correlation (median 0.85) was found between temporal tumor uptake patterns from DPET and DCECT. The heterogeneity in tumor uptake was not significantly different in the DPET and DCECT images. The median of the spatial correlation was 0.72. DCECT and DPET gave similar temporal wash-in characteristics, and the images also showed a relatively high spatial correlation. Hence, if the limited spatial resolution of DPET is considered adequate, a single DPET scan only for assessing both tumor perfusion and metabolic activity may be considered. However, further work on a larger number of cases is needed to verify the correlations observed in the present study.

Unique patterns of organization and migration of FGF-expressing cells during Drosophila morphogenesis.

PubMed

Du, Lijuan; Zhou, Amy; Patel, Akshay; Rao, Mishal; Anderson, Kelsey; Roy, Sougata

2017-07-01

Fibroblast growth factors (FGF) are essential signaling proteins that regulate diverse cellular functions in developmental and metabolic processes. In Drosophila, the FGF homolog, branchless (bnl) is expressed in a dynamic and spatiotemporally restricted pattern to induce branching morphogenesis of the trachea, which expresses the Bnl-receptor, breathless (btl). Here we have developed a new strategy to determine bnl- expressing cells and study their interactions with the btl-expressing cells in the range of tissue patterning during Drosophila development. To enable targeted gene expression specifically in the bnl expressing cells, a new LexA based bnl enhancer trap line was generated using CRISPR/Cas9 based genome editing. Analyses of the spatiotemporal expression of the reporter in various embryonic stages, larval or adult tissues and in metabolic hypoxia, confirmed its target specificity and versatility. With this tool, new bnl expressing cells, their unique organization and functional interactions with the btl-expressing cells were uncovered in a larval tracheoblast niche in the leg imaginal discs, in larval photoreceptors of the developing retina, and in the embryonic central nervous system. The targeted expression system also facilitated live imaging of simultaneously labeled Bnl sources and tracheal cells, which revealed a unique morphogenetic movement of the embryonic bnl- source. Migration of bnl- expressing cells may create a dynamic spatiotemporal pattern of the signal source necessary for the directional growth of the tracheal branch. The genetic tool and the comprehensive profile of expression, organization, and activity of various types of bnl-expressing cells described in this study provided us with an important foundation for future research investigating the mechanisms underlying Bnl signaling in tissue morphogenesis. Copyright © 2017 Elsevier Inc. All rights reserved.

Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach

PubMed Central

Yu, Zhaoyuan; Yuan, Linwang; Luo, Wen; Feng, Linyao; Lv, Guonian

2015-01-01

Passive infrared (PIR) motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA)-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks. PMID:26729123

Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach.

PubMed

Yu, Zhaoyuan; Yuan, Linwang; Luo, Wen; Feng, Linyao; Lv, Guonian

2015-12-30

Passive infrared (PIR) motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA)-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks.

Consistency of vegetation index seasonality across the Amazon rainforest

NASA Astrophysics Data System (ADS)

Maeda, Eduardo Eiji; Moura, Yhasmin Mendes; Wagner, Fabien; Hilker, Thomas; Lyapustin, Alexei I.; Wang, Yujie; Chave, Jérôme; Mõttus, Matti; Aragão, Luiz E. O. C.; Shimabukuro, Yosio

2016-10-01

Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in VIs seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between VIs, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing.

Consistency of Vegetation Index Seasonality Across the Amazon Rainforest

NASA Technical Reports Server (NTRS)

Maeda, Eduardo Eiji; Moura, Yhasmin Mendes; Wagner, Fabien; Hilker, Thomas; Lyapustin, Alexei I.; Wang, Yujie; Chave, Jerome; Mottus, Matti; Aragao, Luiz E.O.C.; Shimabukuro, Yosio

2016-01-01

Vegetation indices (VIs) calculated from remotely sensed reflectance are widely used tools for characterizing the extent and status of vegetated areas. Recently, however, their capability to monitor the Amazon forest phenology has been intensely scrutinized. In this study, we analyze the consistency of VIs seasonal patterns obtained from two MODIS products: the Collection 5 BRDF product (MCD43) and the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC). The spatio-temporal patterns of the VIs were also compared with field measured leaf litterfall, gross ecosystem productivity and active microwave data. Our results show that significant seasonal patterns are observed in all VIs after the removal of view-illumination effects and cloud contamination. However, we demonstrate inconsistencies in the characteristics of seasonal patterns between different VIs and MODIS products. We demonstrate that differences in the original reflectance band values form a major source of discrepancy between MODIS VI products. The MAIAC atmospheric correction algorithm significantly reduces noise signals in the red and blue bands. Another important source of discrepancy is caused by differences in the availability of clear-sky data, as the MAIAC product allows increased availability of valid pixels in the equatorial Amazon. Finally, differences in VIs seasonal patterns were also caused by MODIS collection 5 calibration degradation. The correlation of remote sensing and field data also varied spatially, leading to different temporal offsets between VIs, active microwave and field measured data. We conclude that recent improvements in the MAIAC product have led to changes in the characteristics of spatio-temporal patterns of VIs seasonality across the Amazon forest, when compared to the MCD43 product. Nevertheless, despite improved quality and reduced uncertainties in the MAIAC product, a robust biophysical interpretation of VIs seasonality is still missing.

How can knowledge discovery methods uncover spatio-temporal patterns in environmental data?

NASA Astrophysics Data System (ADS)

Wachowicz, Monica

2000-04-01

This paper proposes the integration of KDD, GVis and STDB as a long-term strategy, which will allow users to apply knowledge discovery methods for uncovering spatio-temporal patterns in environmental data. The main goal is to combine innovative techniques and associated tools for exploring very large environmental data sets in order to arrive at valid, novel, potentially useful, and ultimately understandable spatio-temporal patterns. The GeoInsight approach is described using the principles and key developments in the research domains of KDD, GVis, and STDB. The GeoInsight approach aims at the integration of these research domains in order to provide tools for performing information retrieval, exploration, analysis, and visualization. The result is a knowledge-based design, which involves visual thinking (perceptual-cognitive process) and automated information processing (computer-analytical process).

Categorization for Faces and Tools—Two Classes of Objects Shaped by Different Experience—Differs in Processing Timing, Brain Areas Involved, and Repetition Effects

PubMed Central

Kozunov, Vladimir; Nikolaeva, Anastasia; Stroganova, Tatiana A.

2018-01-01

The brain mechanisms that integrate the separate features of sensory input into a meaningful percept depend upon the prior experience of interaction with the object and differ between categories of objects. Recent studies using representational similarity analysis (RSA) have characterized either the spatial patterns of brain activity for different categories of objects or described how category structure in neuronal representations emerges in time, but never simultaneously. Here we applied a novel, region-based, multivariate pattern classification approach in combination with RSA to magnetoencephalography data to extract activity associated with qualitatively distinct processing stages of visual perception. We asked participants to name what they see whilst viewing bitonal visual stimuli of two categories predominantly shaped by either value-dependent or sensorimotor experience, namely faces and tools, and meaningless images. We aimed to disambiguate the spatiotemporal patterns of brain activity between the meaningful categories and determine which differences in their processing were attributable to either perceptual categorization per se, or later-stage mentalizing-related processes. We have extracted three stages of cortical activity corresponding to low-level processing, category-specific feature binding, and supra-categorical processing. All face-specific spatiotemporal patterns were associated with bilateral activation of ventral occipito-temporal areas during the feature binding stage at 140–170 ms. The tool-specific activity was found both within the categorization stage and in a later period not thought to be associated with binding processes. The tool-specific binding-related activity was detected within a 210–220 ms window and was located to the intraparietal sulcus of the left hemisphere. Brain activity common for both meaningful categories started at 250 ms and included widely distributed assemblies within parietal, temporal, and prefrontal regions. Furthermore, we hypothesized and tested whether activity within face and tool-specific binding-related patterns would demonstrate oppositely acting effects following procedural perceptual learning. We found that activity in the ventral, face-specific network increased following the stimuli repetition. In contrast, tool processing in the dorsal network adapted by reducing its activity over the repetition period. Altogether, we have demonstrated that activity associated with visual processing of faces and tools during the categorization stage differ in processing timing, brain areas involved, and in their dynamics underlying stimuli learning. PMID:29379426

Categorization for Faces and Tools-Two Classes of Objects Shaped by Different Experience-Differs in Processing Timing, Brain Areas Involved, and Repetition Effects.

PubMed

Kozunov, Vladimir; Nikolaeva, Anastasia; Stroganova, Tatiana A

2017-01-01

The brain mechanisms that integrate the separate features of sensory input into a meaningful percept depend upon the prior experience of interaction with the object and differ between categories of objects. Recent studies using representational similarity analysis (RSA) have characterized either the spatial patterns of brain activity for different categories of objects or described how category structure in neuronal representations emerges in time, but never simultaneously. Here we applied a novel, region-based, multivariate pattern classification approach in combination with RSA to magnetoencephalography data to extract activity associated with qualitatively distinct processing stages of visual perception. We asked participants to name what they see whilst viewing bitonal visual stimuli of two categories predominantly shaped by either value-dependent or sensorimotor experience, namely faces and tools, and meaningless images. We aimed to disambiguate the spatiotemporal patterns of brain activity between the meaningful categories and determine which differences in their processing were attributable to either perceptual categorization per se , or later-stage mentalizing-related processes. We have extracted three stages of cortical activity corresponding to low-level processing, category-specific feature binding, and supra-categorical processing. All face-specific spatiotemporal patterns were associated with bilateral activation of ventral occipito-temporal areas during the feature binding stage at 140-170 ms. The tool-specific activity was found both within the categorization stage and in a later period not thought to be associated with binding processes. The tool-specific binding-related activity was detected within a 210-220 ms window and was located to the intraparietal sulcus of the left hemisphere. Brain activity common for both meaningful categories started at 250 ms and included widely distributed assemblies within parietal, temporal, and prefrontal regions. Furthermore, we hypothesized and tested whether activity within face and tool-specific binding-related patterns would demonstrate oppositely acting effects following procedural perceptual learning. We found that activity in the ventral, face-specific network increased following the stimuli repetition. In contrast, tool processing in the dorsal network adapted by reducing its activity over the repetition period. Altogether, we have demonstrated that activity associated with visual processing of faces and tools during the categorization stage differ in processing timing, brain areas involved, and in their dynamics underlying stimuli learning.

Iconic memory-based omnidirectional route panorama navigation.

PubMed

Yagi, Yasushi; Imai, Kousuke; Tsuji, Kentaro; Yachida, Masahiko

2005-01-01

A route navigation method for a mobile robot with an omnidirectional image sensor is described. The route is memorized from a series of consecutive omnidirectional images of the horizon when the robot moves to its goal. While the robot is navigating to the goal point, input is matched against the memorized spatio-temporal route pattern by using dual active contour models and the exact robot position and orientation is estimated from the converged shape of the active contour models.

Dynamic motif occupancy (DynaMO) analysis identifies transcription factors and their binding sites driving dynamic biological processes

PubMed Central

Kuang, Zheng; Ji, Zhicheng

2018-01-01

Abstract Biological processes are usually associated with genome-wide remodeling of transcription driven by transcription factors (TFs). Identifying key TFs and their spatiotemporal binding patterns are indispensable to understanding how dynamic processes are programmed. However, most methods are designed to predict TF binding sites only. We present a computational method, dynamic motif occupancy analysis (DynaMO), to infer important TFs and their spatiotemporal binding activities in dynamic biological processes using chromatin profiling data from multiple biological conditions such as time-course histone modification ChIP-seq data. In the first step, DynaMO predicts TF binding sites with a random forests approach. Next and uniquely, DynaMO infers dynamic TF binding activities at predicted binding sites using their local chromatin profiles from multiple biological conditions. Another landmark of DynaMO is to identify key TFs in a dynamic process using a clustering and enrichment analysis of dynamic TF binding patterns. Application of DynaMO to the yeast ultradian cycle, mouse circadian clock and human neural differentiation exhibits its accuracy and versatility. We anticipate DynaMO will be generally useful for elucidating transcriptional programs in dynamic processes. PMID:29325176

Visual representation of spatiotemporal structure

NASA Astrophysics Data System (ADS)

Schill, Kerstin; Zetzsche, Christoph; Brauer, Wilfried; Eisenkolb, A.; Musto, A.

1998-07-01

The processing and representation of motion information is addressed from an integrated perspective comprising low- level signal processing properties as well as higher-level cognitive aspects. For the low-level processing of motion information we argue that a fundamental requirement is the existence of a spatio-temporal memory. Its key feature, the provision of an orthogonal relation between external time and its internal representation, is achieved by a mapping of temporal structure into a locally distributed activity distribution accessible in parallel by higher-level processing stages. This leads to a reinterpretation of the classical concept of `iconic memory' and resolves inconsistencies on ultra-short-time processing and visual masking. The spatial-temporal memory is further investigated by experiments on the perception of spatio-temporal patterns. Results on the direction discrimination of motion paths provide evidence that information about direction and location are not processed and represented independent of each other. This suggests a unified representation on an early level, in the sense that motion information is internally available in form of a spatio-temporal compound. For the higher-level representation we have developed a formal framework for the qualitative description of courses of motion that may occur with moving objects.

Improved discriminability of spatiotemporal neural patterns in rat motor cortical areas as directional choice learning progresses

PubMed Central

Mao, Hongwei; Yuan, Yuan; Si, Jennie

2015-01-01

Animals learn to choose a proper action among alternatives to improve their odds of success in food foraging and other activities critical for survival. Through trial-and-error, they learn correct associations between their choices and external stimuli. While a neural network that underlies such learning process has been identified at a high level, it is still unclear how individual neurons and a neural ensemble adapt as learning progresses. In this study, we monitored the activity of single units in the rat medial and lateral agranular (AGm and AGl, respectively) areas as rats learned to make a left or right side lever press in response to a left or right side light cue. We noticed that rat movement parameters during the performance of the directional choice task quickly became stereotyped during the first 2–3 days or sessions. But learning the directional choice problem took weeks to occur. Accompanying rats' behavioral performance adaptation, we observed neural modulation by directional choice in recorded single units. Our analysis shows that ensemble mean firing rates in the cue-on period did not change significantly as learning progressed, and the ensemble mean rate difference between left and right side choices did not show a clear trend of change either. However, the spatiotemporal firing patterns of the neural ensemble exhibited improved discriminability between the two directional choices through learning. These results suggest a spatiotemporal neural coding scheme in a motor cortical neural ensemble that may be responsible for and contributing to learning the directional choice task. PMID:25798093

Analysis of the Spatiotemporal Characteristics of Hemorrhagic Fever with Renal Syndrome in Hubei Province, China

NASA Astrophysics Data System (ADS)

Fan, H.; Ge, L.; Song, L.; Zhao, Q.

2015-07-01

Hemorrhagic fever with renal syndrome(HFRS) is a worldwide fulminant infectious disease. Since the first HFRS cases in Hubei Province were reported in 1957, the disease has spread across the province and Hubei has become one of seriously affected areas in China. However, the epidemic characteristics of HFRS are still not entirely clear. Therefore, a systematic investigation of spatial and temporal distribution pattern of HFRS system is needed. In order to facilitate better prevention and control of HFRS in Hubei Province, in this paper, a GIS spatiotemporal analysis and modeling tool was developed to analyze the spatiotemporal dynamics of the HFRS epidemic, as well as providinga comprehensive examination the dynamic pattern of HFRS in Hubei over the past 30 years (1980-2009), to determine spatiotemporal change trends and the causes of HFRS. This paper describes the experiments and their results.

Spatiotemporal throughfall patterns beneath an urban tree row

NASA Astrophysics Data System (ADS)

Bogeholz, P.; Van Stan, J. T., II; Hildebrandt, A.; Friesen, J.; Dibble, M.; Norman, Z.

2016-12-01

Much recent research has focused on throughfall patterns in natural forests as they can influence the heterogeneity of surface ecohydrological and biogeochemical processes. However, to the knowledge of the authors, no work has assessed how urban forest structures affect the spatiotemporal variability of throughfall water flux. Urbanization greatly alters not only a significant portion of the land surface, but canopy structure, with the most typical urban forest configuration being landscaped tree rows along streets, swales, parking lot medians, etc. This study examines throughfall spatiotemporal patterns for a landscaped tree row of Pinus elliottii (Engelm., slash pine) on Georgia Southern University's campus (southeastern, USA) using 150 individual observations per storm. Throughfall correlation lengths beneath this tree row were similar to, but appeared to be more stable across storm size than, observations in past studies on natural forests. Individual tree overlap and the planting interval also may more strongly drive throughfall patterns in tree rows. Meteorological influences beyond storm magnitude (intensity, intermittency, wind conditions, and atmospheric moisture demand) are also examined.

A Modified Consumer Inkjet for Spatiotemporal Control of Gene Expression

PubMed Central

Cohen, Daniel J.; Morfino, Roberto C.; Maharbiz, Michel M.

2009-01-01

This paper presents a low-cost inkjet dosing system capable of continuous, two-dimensional spatiotemporal regulation of gene expression via delivery of diffusible regulators to a custom-mounted gel culture of E. coli. A consumer-grade, inkjet printer was adapted for chemical printing; E. coli cultures were grown on 750 µm thick agar embedded in micro-wells machined into commercial compact discs. Spatio-temporal regulation of the lac operon was demonstrated via the printing of patterns of lactose and glucose directly into the cultures; X-Gal blue patterns were used for visual feedback. We demonstrate how the bistable nature of the lac operon's feedback, when perturbed by patterning lactose (inducer) and glucose (inhibitor), can lead to coordination of cell expression patterns across a field in ways that mimic motifs seen in developmental biology. Examples of this include sharp boundaries and the generation of traveling waves of mRNA expression. To our knowledge, this is the first demonstration of reaction-diffusion effects in the well-studied lac operon. A finite element reaction-diffusion model of the lac operon is also presented which predicts pattern formation with good fidelity. PMID:19763256

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

NASA Astrophysics Data System (ADS)

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

1999-03-01

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

Baseline study of the spatio-temporal patterns of reef fish assemblages prior to a major mining project in New Caledonia (South Pacific).

PubMed

Chabanet, Pascale; Guillemot, Nicolas; Kulbicki, Michel; Vigliola, Laurent; Sarramegna, Sébastien

2010-01-01

From 2008 onwards, the coral reefs of Koné (New Caledonia) will be subjected to a major anthropogenic perturbation linked to development of a nickel mine. Dredging and sediment runoff may directly damage the reef environment whereas job creation should generate a large demographic increase and thus a rise in fishing activities. This study analyzed reef fish assemblages between 2002 and 2007 with a focus on spatio-temporal variability. Our results indicate strong spatial structure of fish assemblages through time. Total species richness, density and biomass were highly variable between years but temporal variations were consistent among biotopes. A remarkable spatio-temporal stability was observed for trophic (mean 4.6% piscivores, 53.1% carnivores, 30.8% herbivores and 11.4% planktivores) and home range structures of species abundance contributions. These results are discussed and compared with others sites of the South Pacific. For monitoring perspectives, some indicators related to expected disturbances are proposed. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Spatiotemporal earthquake clusters along the North Anatolian fault zone offshore Istanbul

USGS Publications Warehouse

Bulut, Fatih; Ellsworth, William L.; Bohnhoff, Marco; Aktar, Mustafa; Dresen, Georg

2011-01-01

We investigate earthquakes with similar waveforms in order to characterize spatiotemporal microseismicity clusters within the North Anatolian fault zone (NAFZ) in northwest Turkey along the transition between the 1999 ??zmit rupture zone and the Marmara Sea seismic gap. Earthquakes within distinct activity clusters are relocated with cross-correlation derived relative travel times using the double difference method. The spatiotemporal distribution of micro earthquakes within individual clusters is resolved with relative location accuracy comparable to or better than the source size. High-precision relative hypocenters define the geometry of individual fault patches, permitting a better understanding of fault kinematics and their role in local-scale seismotectonics along the region of interest. Temporal seismic sequences observed in the eastern Sea of Marmara region suggest progressive failure of mostly nonoverlapping areas on adjacent fault patches and systematic migration of microearthquakes within clusters during the progressive failure of neighboring fault patches. The temporal distributions of magnitudes as well as the number of events follow swarmlike behavior rather than a mainshock/aftershock pattern.

Decoding Spontaneous Emotional States in the Human Brain

PubMed Central

Kragel, Philip A.; Knodt, Annchen R.; Hariri, Ahmad R.; LaBar, Kevin S.

2016-01-01

Pattern classification of human brain activity provides unique insight into the neural underpinnings of diverse mental states. These multivariate tools have recently been used within the field of affective neuroscience to classify distributed patterns of brain activation evoked during emotion induction procedures. Here we assess whether neural models developed to discriminate among distinct emotion categories exhibit predictive validity in the absence of exteroceptive emotional stimulation. In two experiments, we show that spontaneous fluctuations in human resting-state brain activity can be decoded into categories of experience delineating unique emotional states that exhibit spatiotemporal coherence, covary with individual differences in mood and personality traits, and predict on-line, self-reported feelings. These findings validate objective, brain-based models of emotion and show how emotional states dynamically emerge from the activity of separable neural systems. PMID:27627738

Exploration of spatio-temporal patterns of students' movement in field trip by visualizing the log data

NASA Astrophysics Data System (ADS)

Cho, Nahye; Kang, Youngok

2018-05-01

A numerous log data in addition to user input data are being generated as mobile and web users continue to increase recently, and the studies in order to explore the patterns and meanings of various movement activities by making use of these log data are also rising rapidly. On the other hand, in the field of education, people have recognized the importance of field trip as the creative education is highlighted. Also, the examples which utilize the mobile devices in the field trip in accordance to the development of information technology are growing. In this study, we try to explore the patterns of student's activity by visualizing the log data generated from high school students' field trip with mobile device.

Understanding the spatiotemporal pattern of grazing cattle movement

NASA Astrophysics Data System (ADS)

Zhao, Kun; Jurdak, Raja

2016-08-01

Understanding the drivers of animal movement is significant for ecology and biology. Yet researchers have so far been unable to fully understand these drivers, largely due to low data resolution. In this study, we analyse a high-frequency movement dataset for a group of grazing cattle and investigate their spatiotemporal patterns using a simple two-state ‘stop-and-move’ mobility model. We find that the dispersal kernel in the moving state is best described by a mixture exponential distribution, indicating the hierarchical nature of the movement. On the other hand, the waiting time appears to be scale-invariant below a certain cut-off and is best described by a truncated power-law distribution, suggesting that the non-moving state is governed by time-varying dynamics. We explore possible explanations for the observed phenomena, covering factors that can play a role in the generation of mobility patterns, such as the context of grazing environment, the intrinsic decision-making mechanism or the energy status of different activities. In particular, we propose a new hypothesis that the underlying movement pattern can be attributed to the most probable observable energy status under the maximum entropy configuration. These results are not only valuable for modelling cattle movement but also provide new insights for understanding the underlying biological basis of grazing behaviour.

Cross-Diffusion Induced Turing Instability and Amplitude Equation for a Toxic-Phytoplankton-Zooplankton Model with Nonmonotonic Functional Response

NASA Astrophysics Data System (ADS)

Han, Renji; Dai, Binxiang

2017-06-01

The spatiotemporal pattern induced by cross-diffusion of a toxic-phytoplankton-zooplankton model with nonmonotonic functional response is investigated in this paper. The linear stability analysis shows that cross-diffusion is the key mechanism for the formation of spatial patterns. By taking cross-diffusion rate as bifurcation parameter, we derive amplitude equations near the Turing bifurcation point for the excited modes in the framework of a weakly nonlinear theory, and the stability analysis of the amplitude equations interprets the structural transitions and stability of various forms of Turing patterns. Furthermore, we illustrate the theoretical results via numerical simulations. It is shown that the spatiotemporal distribution of the plankton is homogeneous in the absence of cross-diffusion. However, when the cross-diffusivity is greater than the critical value, the spatiotemporal distribution of all the plankton species becomes inhomogeneous in spaces and results in different kinds of patterns: spot, stripe, and the mixture of spot and stripe patterns depending on the cross-diffusivity. Simultaneously, the impact of toxin-producing rate of toxic-phytoplankton (TPP) species and natural death rate of zooplankton species on pattern selection is also explored.

Spatiotemporal activity patterns detected from single cell measurements from behaving animals

NASA Astrophysics Data System (ADS)

Villa, Alessandro E. P.; Tetko, Igor V.

1999-03-01

Precise temporal patterning of activity within and between neurons has been predicted on theoretical grounds, and found in the spike trains of neurons recorded from anesthetized and conscious animals, in association with sensor stimuli and particular phases of task performance. However, the functional significance of such patterning in the generation of behavior has not been confirmed. We recorded from multiple single neurons in regions of rat auditory cortex during the waiting period of a Go/NoGo task. During this time the animal waited for an auditory signal with high cognitive load. Of note is the fact that neural activity during the period analyzed was essentially stationary, with no event related variability in firing. Detected patterns therefore provide a measure of brain state that could not be addressed by standard methods relying on analysis of changes in mean discharge rate. The possibility is discussed that some patterns might reflect a preset bias to a particular response, formed in the waiting period. Others patterns might reflect a state of prior preparation of appropriate neural assemblies for analyzing a signal that is expected but of unknown behavioral valence.

Boundary-induced pattern formation from uniform temporal oscillation

NASA Astrophysics Data System (ADS)

Kohsokabe, Takahiro; Kaneko, Kunihiko

2018-04-01

Pattern dynamics triggered by fixing a boundary is investigated. By considering a reaction-diffusion equation that has a unique spatially uniform and limit cycle attractor under a periodic or Neumann boundary condition, and then by choosing a fixed boundary condition, we found three novel phases depending on the ratio of diffusion constants of activator to inhibitor: transformation of temporally periodic oscillation into a spatially periodic fixed pattern, travelling wave emitted from the boundary, and aperiodic spatiotemporal dynamics. The transformation into a fixed, periodic pattern is analyzed by crossing of local nullclines at each spatial point, shifted by diffusion terms, as is analyzed by using recursive equations, to obtain the spatial pattern as an attractor. The generality of the boundary-induced pattern formation as well as its relevance to biological morphogenesis is discussed.

Similarities and differences among half-marathon runners according to their performance level

PubMed Central

Morante, Juan Carlos; Gómez-Molina, Josué; García-López, Juan

2018-01-01

This study aimed to identify the similarities and differences among half-marathon runners in relation to their performance level. Forty-eight male runners were classified into 4 groups according to their performance level in a half-marathon (min): Group 1 (n = 11, < 70 min), Group 2 (n = 13, < 80 min), Group 3 (n = 13, < 90 min), Group 4 (n = 11, < 105 min). In two separate sessions, training-related, anthropometric, physiological, foot strike pattern and spatio-temporal variables were recorded. Significant differences (p<0.05) between groups (ES = 0.55–3.16) and correlations with performance were obtained (r = 0.34–0.92) in training-related (experience and running distance per week), anthropometric (mass, body mass index and sum of 6 skinfolds), physiological (VO2max, RCT and running economy), foot strike pattern and spatio-temporal variables (contact time, step rate and length). At standardized submaximal speeds (11, 13 and 15 km·h-1), no significant differences between groups were observed in step rate and length, neither in contact time when foot strike pattern was taken into account. In conclusion, apart from training-related, anthropometric and physiological variables, foot strike pattern and step length were the only biomechanical variables sensitive to half-marathon performance, which are essential to achieve high running speeds. However, when foot strike pattern and running speeds were controlled (submaximal test), the spatio-temporal variables were similar. This indicates that foot strike pattern and running speed are responsible for spatio-temporal differences among runners of different performance level. PMID:29364940

Mining local climate data to assess spatiotemporal dengue fever epidemic patterns in French Guiana.

PubMed

Flamand, Claude; Fabregue, Mickael; Bringay, Sandra; Ardillon, Vanessa; Quénel, Philippe; Desenclos, Jean-Claude; Teisseire, Maguelonne

2014-10-01

To identify local meteorological drivers of dengue fever in French Guiana, we applied an original data mining method to the available epidemiological and climatic data. Through this work, we also assessed the contribution of the data mining method to the understanding of factors associated with the dissemination of infectious diseases and their spatiotemporal spread. We applied contextual sequential pattern extraction techniques to epidemiological and meteorological data to identify the most significant climatic factors for dengue fever, and we investigated the relevance of the extracted patterns for the early warning of dengue outbreaks in French Guiana. The maximum temperature, minimum relative humidity, global brilliance, and cumulative rainfall were identified as determinants of dengue outbreaks, and the precise intervals of their values and variations were quantified according to the epidemiologic context. The strongest significant correlations were observed between dengue incidence and meteorological drivers after a 4-6-week lag. We demonstrated the use of contextual sequential patterns to better understand the determinants of the spatiotemporal spread of dengue fever in French Guiana. Future work should integrate additional variables and explore the notion of neighborhood for extracting sequential patterns. Dengue fever remains a major public health issue in French Guiana. The development of new methods to identify such specific characteristics becomes crucial in order to better understand and control spatiotemporal transmission. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Spatiotemporal pattern of vegetation remote sensing phenology and its response to climatic factors on the Qinghai-Tibet Plateau

NASA Astrophysics Data System (ADS)

An, S.; Chen, X.

2015-12-01

Based on the MODIS MCD12Q2 remote sensing phenology product, we analyzed spatiotemporal variations of vegetation green-up, maturity, senescence and brown-off dates, and their relation to spatiotemporal patterns of air temperature and precipitation on the Qinghai-Tibet Plateau (QTP). From 2001 to 2012, phenological time series at about 11.7%~15.1% pixels indicate significant linear trends (P<0.1) with strong spatial consistency. Namely, pixels with significant phenological advancement and growing season lengthening are mainly distributed in the middle and eastern parts of the QTP, while pixels with significant phenological delay and growing season shortening are mainly distributed in the western and southern parts as well as the eastern edge of the QTP. Similar spatial patterns for positive and negative linear trends of the minimum and maximum EVI, and the time-integrated EVI during the growing season were detected in the above two regions, respectively. With regard to climatic factors, mean annual temperature shows an increased trend over the QTP except for the eastern edge, whereas annual precipitation displays an increased trend in the middle and eastern parts but a decreased trend in the western and southern parts as well as the eastern edge of the QTP. These findings suggest that phenological advancement, growing season lengthening, and vegetation activity enhancement in the middle and eastern parts might be attributed to coincident temperature and precipitation increase. By contrast, phenological delay, growing season shortening, and vegetation activity reduction in the western and southern parts as well as the eastern edge might be caused by opposite changes of temperature and precipitation, and strong evaporation induced water shortage. Furthermore, a partial correlation analysis indicates that green-up, maturity, and brown-off dates were influenced by preceding temperature and precipitation, while senescence date was affected by preceding precipitation.

Regular Wave Propagation Out of Noise in Chemical Active Media

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

Alonso, S.; Sendina-Nadal, I.; Perez-Munuzuri, V.

2001-08-13

A pacemaker, regularly emitting chemical waves, is created out of noise when an excitable photosensitive Belousov-Zhabotinsky medium, strictly unable to autonomously initiate autowaves, is forced with a spatiotemporal patterned random illumination. These experimental observations are also reproduced numerically by using a set of reaction-diffusion equations for an activator-inhibitor model, and further analytically interpreted in terms of genuine coupling effects arising from parametric fluctuations. Within the same framework we also address situations of noise-sustained propagation in subexcitable media.

Self-Organization of Embryonic Genetic Oscillators into Spatiotemporal Wave Patterns

PubMed Central

Tsiairis, Charisios D.; Aulehla, Alexander

2016-01-01

Summary In vertebrate embryos, somites, the precursor of vertebrae, form from the presomitic mesoderm (PSM), which is composed of cells displaying signaling oscillations. Cellular oscillatory activity leads to periodic wave patterns in the PSM. Here, we address the origin of such complex wave patterns. We employed an in vitro randomization and real-time imaging strategy to probe for the ability of cells to generate order from disorder. We found that, after randomization, PSM cells self-organized into several miniature emergent PSM structures (ePSM). Our results show an ordered macroscopic spatial arrangement of ePSM with evidence of an intrinsic length scale. Furthermore, cells actively synchronize oscillations in a Notch-signaling-dependent manner, re-establishing wave-like patterns of gene activity. We demonstrate that PSM cells self-organize by tuning oscillation dynamics in response to surrounding cells, leading to collective synchronization with an average frequency. These findings reveal emergent properties within an ensemble of coupled genetic oscillators. PMID:26871631

Modeling the spatio-temporal heterogeneity in the PM10-PM2.5 relationship

NASA Astrophysics Data System (ADS)

Chu, Hone-Jay; Huang, Bo; Lin, Chuan-Yao

2015-02-01

This paper explores the spatio-temporal patterns of particulate matter (PM) in Taiwan based on a series of methods. Using fuzzy c-means clustering first, the spatial heterogeneity (six clusters) in the PM data collected between 2005 and 2009 in Taiwan are identified and the industrial and urban areas of Taiwan (southwestern, west central, northwestern, and northern Taiwan) are found to have high PM concentrations. The PM10-PM2.5 relationship is then modeled with global ordinary least squares regression, geographically weighted regression (GWR), and geographically and temporally weighted regression (GTWR). The GTWR and GWR produce consistent results; however, GTWR provides more detailed information of spatio-temporal variations of the PM10-PM2.5 relationship. The results also show that GTWR provides a relatively high goodness of fit and sufficient space-time explanatory power. In particular, the PM2.5 or PM10 varies with time and space, depending on weather conditions and the spatial distribution of land use and emission patterns in local areas. Such information can be used to determine patterns of spatio-temporal heterogeneity in PM that will allow the control of pollutants and the reduction of public exposure.

A long-time, high spatiotemporal resolution optical recording system for membrane potential activity via real-time writing to the hard disk.

PubMed

Hirota, Akihiko; Ito, Shin-ichi

2006-06-01

Using real-time hard disk recording, we have developed an optical system for the long-duration detection of changes in membrane potential from 1,020 sites with a high temporal resolution. The signal-to-noise ratio was sufficient for analyzing the spreading pattern of excitatory waves in frog atria in a single sweep.

Spatio-temporal dynamics induced by competing instabilities in two asymmetrically coupled nonlinear evolution equations.

PubMed

Schüler, D; Alonso, S; Torcini, A; Bär, M

2014-12-01

Pattern formation often occurs in spatially extended physical, biological, and chemical systems due to an instability of the homogeneous steady state. The type of the instability usually prescribes the resulting spatio-temporal patterns and their characteristic length scales. However, patterns resulting from the simultaneous occurrence of instabilities cannot be expected to be simple superposition of the patterns associated with the considered instabilities. To address this issue, we design two simple models composed by two asymmetrically coupled equations of non-conserved (Swift-Hohenberg equations) or conserved (Cahn-Hilliard equations) order parameters with different characteristic wave lengths. The patterns arising in these systems range from coexisting static patterns of different wavelengths to traveling waves. A linear stability analysis allows to derive a two parameter phase diagram for the studied models, in particular, revealing for the Swift-Hohenberg equations, a co-dimension two bifurcation point of Turing and wave instability and a region of coexistence of stationary and traveling patterns. The nonlinear dynamics of the coupled evolution equations is investigated by performing accurate numerical simulations. These reveal more complex patterns, ranging from traveling waves with embedded Turing patterns domains to spatio-temporal chaos, and a wide hysteretic region, where waves or Turing patterns coexist. For the coupled Cahn-Hilliard equations the presence of a weak coupling is sufficient to arrest the coarsening process and to lead to the emergence of purely periodic patterns. The final states are characterized by domains with a characteristic length, which diverges logarithmically with the coupling amplitude.

Antipoaching standards in onshore hydrocarbon concessions drawn from a Central African case study.

PubMed

Vanthomme, Hadrien P A; Tobi, Elie; Todd, Angelique F; Korte, Lisa; Alonso, Alfonso

2017-06-01

Unsustainable hunting outside protected areas is threatening tropical biodiversity worldwide and requires conservationists to engage increasingly in antipoaching activities. Following the example of ecocertified logging companies, we argue that other extractive industries managing large concessions should engage in antipoaching activities as part of their environmental management plans. Onshore hydrocarbon concessions should also adopt antipoaching protocols as a standard because they represent a biodiversity threat comparable to logging. We examined the spatiotemporal patterns of small- and large-mammal poaching in an onshore oil concession in Gabon, Central Africa, with a Bayesian occupancy model based on signs of poaching collected from 2010 to 2015 on antipoaching patrols. Patrol locations were initially determined based on local intelligence and past patrol successes (adaptive management) and subsequently with a systematic sampling of the concession. We generated maps of poaching probability in the concession and determined the temporal trends of this threat over 5 years. The spatiotemporal patterns of large- and small-mammal poaching differed throughout the concession, and likely these groups will need different management strategies. By elucidating the relationship between site-specific sampling effort and detection probability, the Bayesian method allowed us to set goals for future antipoaching patrols. Our results indicate that a combination of systematic sampling and adaptive management data is necessary to infer spatiotemporal patterns with the statistical method we used. On the basis of our case study, we recommend hydrocarbon companies interested in implementing efficient antipoaching activities in their onshore concessions to lay the foundation of long-needed industry standards by: adequately measuring antipoaching effort; mixing adaptive management and balanced sampling; setting goals for antipoaching effort; pairing patrols with large-mammal monitoring; supporting antipoaching patrols across the landscape; restricting access to their concessions; performing random searches for bushmeat and mammal products at points of entry; controlling urban and agricultural expansion; supporting bushmeat alternatives; and supporting land-use planning. Published 2016. This article is a U.S. Government work and is in the public domain in the USA. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Exploring Spatiotemporal Trends in Commercial Fishing Effort of an Abalone Fishing Zone: A GIS-Based Hotspot Model

PubMed Central

Jalali, M. Ali; Ierodiaconou, Daniel; Gorfine, Harry; Monk, Jacquomo; Rattray, Alex

2015-01-01

Assessing patterns of fisheries activity at a scale related to resource exploitation has received particular attention in recent times. However, acquiring data about the distribution and spatiotemporal allocation of catch and fishing effort in small scale benthic fisheries remains challenging. Here, we used GIS-based spatio-statistical models to investigate the footprint of commercial diving events on blacklip abalone (Haliotis rubra) stocks along the south-west coast of Victoria, Australia from 2008 to 2011. Using abalone catch data matched with GPS location we found catch per unit of fishing effort (CPUE) was not uniformly spatially and temporally distributed across the study area. Spatial autocorrelation and hotspot analysis revealed significant spatiotemporal clusters of CPUE (with distance thresholds of 100’s of meters) among years, indicating the presence of CPUE hotspots focused on specific reefs. Cumulative hotspot maps indicated that certain reef complexes were consistently targeted across years but with varying intensity, however often a relatively small proportion of the full reef extent was targeted. Integrating CPUE with remotely-sensed light detection and ranging (LiDAR) derived bathymetry data using generalized additive mixed model corroborated that fishing pressure primarily coincided with shallow, rugose and complex components of reef structures. This study demonstrates that a geospatial approach is efficient in detecting patterns and trends in commercial fishing effort and its association with seafloor characteristics. PMID:25992800

Effects of hydrogen sulphide on motility patterns in the rat colon

PubMed Central

Gil, V; Parsons, SP; Gallego, D; Huizinga, JD; Jimenez, M

2013-01-01

Background and Purpose Hydrogen sulphide (H2S) is an endogenous gaseous signalling molecule with putative functions in gastrointestinal motility regulation. Characterization of H2S effects on colonic motility is crucial to establish its potential use as therapeutic agent in the treatment of colonic disorders. Experimental Approach H2S effects on colonic motility were characterized using video recordings and construction of spatio-temporal maps. Microelectrode and muscle bath studies were performed to investigate the mechanisms underlying H2S effects. NaHS was used as the source of H2S. Key Results Rhythmic propulsive motor complexes (RPMCs) and ripples were observed in colonic spatio-temporal maps. Serosal addition of NaHS concentration-dependently inhibited RPMCs. In contrast, NaHS increased amplitude of the ripples without changing their frequency. Therefore, ripples became the predominant motor pattern. Neuronal blockade with lidocaine inhibited RPMCs, which were restored after administration of carbachol. Subsequent addition of NaHS inhibited RPMCs. Luminal addition of NaHS did not modify motility patterns. NaHS inhibited cholinergic excitatory junction potentials, carbachol-induced contractions and hyperpolarized smooth muscle cells, but did not modify slow wave activity. Conclusions and Implications H2S modulated colonic motility inhibiting propulsive contractile activity and enhancing the amplitude of ripples, promoting mixing. Muscle hyperpolarization and inhibition of neurally mediated cholinergic responses contributed to the inhibitory effect on propulsive activity. H2S effects were not related to changes in the frequency of slow wave activity originating in the network of interstitial cells of Cajal located near the submuscular plexus. Luminal H2S did not modify colonic motility probably because of epithelial detoxification. PMID:23297830

Spatio-Temporal Neural Networks for Vision, Reasoning and Rapid Decision Making

DTIC Science & Technology

1994-08-31

something that is obviously not pattern for long-term knowledge base (LTKB) facts. As a matter possiblc in common neural networks (as units in a...Conferences on Neural Davis, P. (19W0) Application of op~tical chaos to temporal pattern search in a Networks . Piscataway, NJ. [SC] nonlinear optical...Science Institute PROJECT TITLE: Spatio-temporal Neural Networks for Vision, Reasoning and Rapid Decision Making (N00014-93-1-1149) Number of ONR

Precise-spike-driven synaptic plasticity: learning hetero-association of spatiotemporal spike patterns.

PubMed

Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2013-01-01

A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe.

Precise-Spike-Driven Synaptic Plasticity: Learning Hetero-Association of Spatiotemporal Spike Patterns

PubMed Central

Yu, Qiang; Tang, Huajin; Tan, Kay Chen; Li, Haizhou

2013-01-01

A new learning rule (Precise-Spike-Driven (PSD) Synaptic Plasticity) is proposed for processing and memorizing spatiotemporal patterns. PSD is a supervised learning rule that is analytically derived from the traditional Widrow-Hoff rule and can be used to train neurons to associate an input spatiotemporal spike pattern with a desired spike train. Synaptic adaptation is driven by the error between the desired and the actual output spikes, with positive errors causing long-term potentiation and negative errors causing long-term depression. The amount of modification is proportional to an eligibility trace that is triggered by afferent spikes. The PSD rule is both computationally efficient and biologically plausible. The properties of this learning rule are investigated extensively through experimental simulations, including its learning performance, its generality to different neuron models, its robustness against noisy conditions, its memory capacity, and the effects of its learning parameters. Experimental results show that the PSD rule is capable of spatiotemporal pattern classification, and can even outperform a well studied benchmark algorithm with the proposed relative confidence criterion. The PSD rule is further validated on a practical example of an optical character recognition problem. The results again show that it can achieve a good recognition performance with a proper encoding. Finally, a detailed discussion is provided about the PSD rule and several related algorithms including tempotron, SPAN, Chronotron and ReSuMe. PMID:24223789

Spatiotemporal patterns of severe fever with thrombocytopenia syndrome in China, 2011-2016.

PubMed

Sun, Jimin; Lu, Liang; Wu, Haixia; Yang, Jun; Liu, Keke; Liu, Qiyong

2018-05-01

Severe fever with thrombocytopenia syndrome (SFTS) is emerging and the number of SFTS cases have increased year by year in China. However, spatiotemporal patterns and trends of SFTS are less clear up to date. In order to explore spatiotemporal patterns and predict SFTS incidences, we analyzed temporal trends of SFTS using autoregressive integrated moving average (ARIMA) model, spatial patterns, and spatiotemporal clusters of SFTS cases at the county level based on SFTS data in China during 2011-2016. We determined the optimal time series model was ARIMA (2, 0, 1) × (0, 0, 1) 12 which fitted the SFTS cases reasonably well during the training process and forecast process. In the spatial clustering analysis, the global autocorrelation suggested that SFTS cases were not of random distribution. Local spatial autocorrelation analysis of SFTS identified foci mainly concentrated in Hubei Province, Henan Province, Anhui Province, Shandong Province, Liaoning Province, and Zhejiang Province. A most likely cluster including 21 counties in Henan Province and Hubei Province was observed in the central region of China from April 2015 to August 2016. Our results will provide a sound evidence base for future prevention and control programs of SFTS such as allocation of the health resources, surveillance in high-risk regions, health education, improvement of diagnosis and so on. Copyright © 2018 Elsevier GmbH. All rights reserved.

Meteor tracking via local pattern clustering in spatio-temporal domain

NASA Astrophysics Data System (ADS)

Kukal, Jaromír.; Klimt, Martin; Švihlík, Jan; Fliegel, Karel

2016-09-01

Reliable meteor detection is one of the crucial disciplines in astronomy. A variety of imaging systems is used for meteor path reconstruction. The traditional approach is based on analysis of 2D image sequences obtained from a double station video observation system. Precise localization of meteor path is difficult due to atmospheric turbulence and other factors causing spatio-temporal fluctuations of the image background. The proposed technique performs non-linear preprocessing of image intensity using Box-Cox transform as recommended in our previous work. Both symmetric and asymmetric spatio-temporal differences are designed to be robust in the statistical sense. Resulting local patterns are processed by data whitening technique and obtained vectors are classified via cluster analysis and Self-Organized Map (SOM).

The Perception of Dynamic and Static Facial Expressions of Happiness and Disgust Investigated by ERPs and fMRI Constrained Source Analysis

PubMed Central

Trautmann-Lengsfeld, Sina Alexa; Domínguez-Borràs, Judith; Escera, Carles; Herrmann, Manfred; Fehr, Thorsten

2013-01-01

A recent functional magnetic resonance imaging (fMRI) study by our group demonstrated that dynamic emotional faces are more accurately recognized and evoked more widespread patterns of hemodynamic brain responses than static emotional faces. Based on this experimental design, the present study aimed at investigating the spatio-temporal processing of static and dynamic emotional facial expressions in 19 healthy women by means of multi-channel electroencephalography (EEG), event-related potentials (ERP) and fMRI-constrained regional source analyses. ERP analysis showed an increased amplitude of the LPP (late posterior positivity) over centro-parietal regions for static facial expressions of disgust compared to neutral faces. In addition, the LPP was more widespread and temporally prolonged for dynamic compared to static faces of disgust and happiness. fMRI constrained source analysis on static emotional face stimuli indicated the spatio-temporal modulation of predominantly posterior regional brain activation related to the visual processing stream for both emotional valences when compared to the neutral condition in the fusiform gyrus. The spatio-temporal processing of dynamic stimuli yielded enhanced source activity for emotional compared to neutral conditions in temporal (e.g., fusiform gyrus), and frontal regions (e.g., ventromedial prefrontal cortex, medial and inferior frontal cortex) in early and again in later time windows. The present data support the view that dynamic facial displays trigger more information reflected in complex neural networks, in particular because of their changing features potentially triggering sustained activation related to a continuing evaluation of those faces. A combined fMRI and EEG approach thus provides an advanced insight to the spatio-temporal characteristics of emotional face processing, by also revealing additional neural generators, not identifiable by the only use of an fMRI approach. PMID:23818974

Changing and Differentiated Urban Landscape in China: Spatiotemporal Patterns and Driving Forces.

PubMed

Fang, Chuanglin; Li, Guangdong; Wang, Shaojian

2016-03-01

Urban landscape spatiotemporal change patterns and their driving mechanisms in China are poorly understood at the national level. Here we used remote sensing data, landscape metrics, and a spatial econometric model to characterize the spatiotemporal patterns of urban landscape change and investigate its driving forces in China between 1990 and 2005. The results showed that the urban landscape pattern has experienced drastic changes over the past 15 years. Total urban area has expanded approximately 1.61 times, with a 2.98% annual urban-growth rate. Compared to previous single-city studies, although urban areas are expanding rapidly, the overall fragmentation of the urban landscape is decreasing and is more irregular and complex at the national level. We also found a stair-stepping, urban-landscape changing pattern among eastern, central, and western counties. In addition, administrative level, urban size, and hierarchy have effects on the urban landscape pattern. We also found that a combination of landscape metrics can be used to supplement our understanding of the pattern of urbanization. The changes in these metrics are correlated with geographical indicators, socioeconomic factors, infrastructure variables, administrative level factors, policy factors, and historical factors. Our results indicate that the top priority should be strengthening the management of urban planning. A compact and congregate urban landscape may be a good choice of pattern for urban development in China.

Spatiotemporal modelling and mapping of the bubonic plague epidemic in India.

PubMed

Yu, Hwa-Lung; Christakos, George

2006-03-17

This work studies the spatiotemporal evolution of bubonic plague in India during 1896-1906 using stochastic concepts and geographical information science techniques. In the past, most investigations focused on selected cities to conduct different kinds of studies, such as the ecology of rats. No detailed maps existed incorporating the space-time dependence structure and uncertainty sources of the epidemic system and providing a composite space-time picture of the disease propagation characteristics. Informative spatiotemporal maps were generated that represented mortality rates and geographical spread of the disease, and epidemic indicator plots were derived that offered meaningful characterizations of the spatiotemporal disease distribution. The bubonic plague in India exhibited strong seasonal and geographical features. During its entire duration, the plague continued to invade new geographical areas, while it followed a re-emergence pattern at many localities; its rate changed significantly during each year and the mortality distribution exhibited space-time heterogeneous patterns; prevalence usually occurred in the autumn and spring, whereas the plague stopped moving towards new locations during the summers. Modern stochastic modelling and geographical information science provide powerful means to study the spatiotemporal distribution of the bubonic plague epidemic under conditions of uncertainty and multi-sourced databases; to account for various forms of interdisciplinary knowledge; and to generate informative space-time maps of mortality rates and propagation patterns. To the best of our knowledge, this kind of plague maps and plots become available for the first time, thus providing novel perspectives concerning the distribution and space-time propagation of the deadly epidemic. Furthermore, systematic maps and indicator plots make possible the comparison of the spatial-temporal propagation patterns of different diseases.

Spatiotemporal modelling and mapping of the bubonic plague epidemic in India

PubMed Central

Yu, Hwa-Lung; Christakos, George

2006-01-01

Background This work studies the spatiotemporal evolution of bubonic plague in India during 1896–1906 using stochastic concepts and geographical information science techniques. In the past, most investigations focused on selected cities to conduct different kinds of studies, such as the ecology of rats. No detailed maps existed incorporating the space-time dependence structure and uncertainty sources of the epidemic system and providing a composite space-time picture of the disease propagation characteristics. Results Informative spatiotemporal maps were generated that represented mortality rates and geographical spread of the disease, and epidemic indicator plots were derived that offered meaningful characterizations of the spatiotemporal disease distribution. The bubonic plague in India exhibited strong seasonal and geographical features. During its entire duration, the plague continued to invade new geographical areas, while it followed a re-emergence pattern at many localities; its rate changed significantly during each year and the mortality distribution exhibited space-time heterogeneous patterns; prevalence usually occurred in the autumn and spring, whereas the plague stopped moving towards new locations during the summers. Conclusion Modern stochastic modelling and geographical information science provide powerful means to study the spatiotemporal distribution of the bubonic plague epidemic under conditions of uncertainty and multi-sourced databases; to account for various forms of interdisciplinary knowledge; and to generate informative space-time maps of mortality rates and propagation patterns. To the best of our knowledge, this kind of plague maps and plots become available for the first time, thus providing novel perspectives concerning the distribution and space-time propagation of the deadly epidemic. Furthermore, systematic maps and indicator plots make possible the comparison of the spatial-temporal propagation patterns of different diseases. PMID:16545128

Network-constrained spatio-temporal clustering analysis of traffic collisions in Jianghan District of Wuhan, China

PubMed Central

Fan, Yaxin; Zhu, Xinyan; Guo, Wei; Guo, Tao

2018-01-01

The analysis of traffic collisions is essential for urban safety and the sustainable development of the urban environment. Reducing the road traffic injuries and the financial losses caused by collisions is the most important goal of traffic management. In addition, traffic collisions are a major cause of traffic congestion, which is a serious issue that affects everyone in the society. Therefore, traffic collision analysis is essential for all parties, including drivers, pedestrians, and traffic officers, to understand the road risks at a finer spatio-temporal scale. However, traffic collisions in the urban context are dynamic and complex. Thus, it is important to detect how the collision hotspots evolve over time through spatio-temporal clustering analysis. In addition, traffic collisions are not isolated events in space. The characteristics of the traffic collisions and their surrounding locations also present an influence of the clusters. This work tries to explore the spatio-temporal clustering patterns of traffic collisions by combining a set of network-constrained methods. These methods were tested using the traffic collision data in Jianghan District of Wuhan, China. The results demonstrated that these methods offer different perspectives of the spatio-temporal clustering patterns. The weighted network kernel density estimation provides an intuitive way to incorporate attribute information. The network cross K-function shows that there are varying clustering tendencies between traffic collisions and different types of POIs. The proposed network differential Local Moran’s I and network local indicators of mobility association provide straightforward and quantitative measures of the hotspot changes. This case study shows that these methods could help researchers, practitioners, and policy-makers to better understand the spatio-temporal clustering patterns of traffic collisions. PMID:29672551

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences

PubMed Central

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns. PMID:26147887

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

PubMed

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

Spatiotemporal Coding of Individual Chemicals by the Gustatory System

PubMed Central

Reiter, Sam; Campillo Rodriguez, Chelsey; Sun, Kui

2015-01-01

Four of the five major sensory systems (vision, olfaction, somatosensation, and audition) are thought to use different but partially overlapping sets of neurons to form unique representations of vast numbers of stimuli. The only exception is gustation, which is thought to represent only small numbers of basic taste categories. However, using new methods for delivering tastant chemicals and making electrophysiological recordings from the tractable gustatory system of the moth Manduca sexta, we found chemical-specific information is as follows: (1) initially encoded in the population of gustatory receptor neurons as broadly distributed spatiotemporal patterns of activity; (2) dramatically integrated and temporally transformed as it propagates to monosynaptically connected second-order neurons; and (3) observed in tastant-specific behavior. Our results are consistent with an emerging view of the gustatory system: rather than constructing basic taste categories, it uses a spatiotemporal population code to generate unique neural representations of individual tastant chemicals. SIGNIFICANCE STATEMENT Our results provide a new view of taste processing. Using a new, relatively simple model system and a new set of techniques to deliver taste stimuli and to examine gustatory receptor neurons and their immediate followers, we found no evidence for labeled line connectivity, or basic taste categories such as sweet, salty, bitter, and sour. Rather, individual tastant chemicals are represented as patterns of spiking activity distributed across populations of receptor neurons. These representations are transformed substantially as multiple types of receptor neurons converge upon follower neurons, leading to a combinatorial coding format that uniquely, rapidly, and efficiently represents individual taste chemicals. Finally, we found that the information content of these neurons can drive tastant-specific behavior. PMID:26338341

Heterogeneity induces spatiotemporal oscillations in reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Krause, Andrew L.; Klika, Václav; Woolley, Thomas E.; Gaffney, Eamonn A.

2018-05-01

We report on an instability arising in activator-inhibitor reaction-diffusion (RD) systems with a simple spatial heterogeneity. This instability gives rise to periodic creation, translation, and destruction of spike solutions that are commonly formed due to Turing instabilities. While this behavior is oscillatory in nature, it occurs purely within the Turing space such that no region of the domain would give rise to a Hopf bifurcation for the homogeneous equilibrium. We use the shadow limit of the Gierer-Meinhardt system to show that the speed of spike movement can be predicted from well-known asymptotic theory, but that this theory is unable to explain the emergence of these spatiotemporal oscillations. Instead, we numerically explore this system and show that the oscillatory behavior is caused by the destabilization of a steady spike pattern due to the creation of a new spike arising from endogeneous activator production. We demonstrate that on the edge of this instability, the period of the oscillations goes to infinity, although it does not fit the profile of any well-known bifurcation of a limit cycle. We show that nearby stationary states are either Turing unstable or undergo saddle-node bifurcations near the onset of the oscillatory instability, suggesting that the periodic motion does not emerge from a local equilibrium. We demonstrate the robustness of this spatiotemporal oscillation by exploring small localized heterogeneity and showing that this behavior also occurs in the Schnakenberg RD model. Our results suggest that this phenomenon is ubiquitous in spatially heterogeneous RD systems, but that current tools, such as stability of spike solutions and shadow-limit asymptotics, do not elucidate understanding. This opens several avenues for further mathematical analysis and highlights difficulties in explaining how robust patterning emerges from Turing's mechanism in the presence of even small spatial heterogeneity.

Spatiotemporal Coding of Individual Chemicals by the Gustatory System.

PubMed

Reiter, Sam; Campillo Rodriguez, Chelsey; Sun, Kui; Stopfer, Mark

2015-09-02

Four of the five major sensory systems (vision, olfaction, somatosensation, and audition) are thought to use different but partially overlapping sets of neurons to form unique representations of vast numbers of stimuli. The only exception is gustation, which is thought to represent only small numbers of basic taste categories. However, using new methods for delivering tastant chemicals and making electrophysiological recordings from the tractable gustatory system of the moth Manduca sexta, we found chemical-specific information is as follows: (1) initially encoded in the population of gustatory receptor neurons as broadly distributed spatiotemporal patterns of activity; (2) dramatically integrated and temporally transformed as it propagates to monosynaptically connected second-order neurons; and (3) observed in tastant-specific behavior. Our results are consistent with an emerging view of the gustatory system: rather than constructing basic taste categories, it uses a spatiotemporal population code to generate unique neural representations of individual tastant chemicals. Our results provide a new view of taste processing. Using a new, relatively simple model system and a new set of techniques to deliver taste stimuli and to examine gustatory receptor neurons and their immediate followers, we found no evidence for labeled line connectivity, or basic taste categories such as sweet, salty, bitter, and sour. Rather, individual tastant chemicals are represented as patterns of spiking activity distributed across populations of receptor neurons. These representations are transformed substantially as multiple types of receptor neurons converge upon follower neurons, leading to a combinatorial coding format that uniquely, rapidly, and efficiently represents individual taste chemicals. Finally, we found that the information content of these neurons can drive tastant-specific behavior. Copyright © 2015 the authors 0270-6474/15/3512309-13$15.00/0.

Different spatio-temporal electroencephalography features drive the successful decoding of binaural and monaural cues for sound localization.

PubMed

Bednar, Adam; Boland, Francis M; Lalor, Edmund C

2017-03-01

The human ability to localize sound is essential for monitoring our environment and helps us to analyse complex auditory scenes. Although the acoustic cues mediating sound localization have been established, it remains unknown how these cues are represented in human cortex. In particular, it is still a point of contention whether binaural and monaural cues are processed by the same or distinct cortical networks. In this study, participants listened to a sequence of auditory stimuli from different spatial locations while we recorded their neural activity using electroencephalography (EEG). The stimuli were presented over a loudspeaker array, which allowed us to deliver realistic, free-field stimuli in both the horizontal and vertical planes. Using a multivariate classification approach, we showed that it is possible to decode sound source location from scalp-recorded EEG. Robust and consistent decoding was shown for stimuli that provide binaural cues (i.e. Left vs. Right stimuli). Decoding location when only monaural cues were available (i.e. Front vs. Rear and elevational stimuli) was successful for a subset of subjects and showed less consistency. Notably, the spatio-temporal pattern of EEG features that facilitated decoding differed based on the availability of binaural and monaural cues. In particular, we identified neural processing of binaural cues at around 120 ms post-stimulus and found that monaural cues are processed later between 150 and 200 ms. Furthermore, different spatial activation patterns emerged for binaural and monaural cue processing. These spatio-temporal dissimilarities suggest the involvement of separate cortical mechanisms in monaural and binaural acoustic cue processing. © 2017 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Variability in spatio-temporal pattern of trapezius activity and coordination of hand-arm muscles during a sustained repetitive dynamic task.

PubMed

Samani, Afshin; Srinivasan, Divya; Mathiassen, Svend Erik; Madeleine, Pascal

2017-02-01

The spatio-temporal distribution of muscle activity has been suggested to be a determinant of fatigue development. Pursuing this hypothesis, we investigated the pattern of muscular activity in the shoulder and arm during a repetitive dynamic task performed until participants' rating of perceived exertion reached 8 on Borg's CR-10 scale. We collected high-density surface electromyogram (HD-EMG) over the upper trapezius, as well as bipolar EMG from biceps brachii, triceps brachii, deltoideus anterior, serratus anterior, upper and lower trapezius from 21 healthy women. Root-mean-square (RMS) and mean power frequency (MNF) were calculated for all EMG signals. The barycenter of RMS values over the HD-EMG grid was also determined, as well as normalized mutual information (NMI) for each pair of muscles. Cycle-to-cycle variability of these metrics was also assessed. With time, EMG RMS increased for most of the muscles, and MNF decreased. Trapezius activity became higher on the lateral side than on the medial side of the HD-EMG grid and the barycenter moved in a lateral direction. NMI between muscle pairs increased with time while its variability decreased. The variability of the metrics during the initial 10 % of task performance was not associated with the time to task termination. Our results suggest that the considerable variability in force and posture contained in the dynamic task per se masks any possible effects of differences between subjects in initial motor variability on the rate of fatigue development.

Electrical receptive fields of retinal ganglion cells: Influence of presynaptic neurons

PubMed Central

Apollo, Nicholas V.; Garrett, David J.

2018-01-01

Implantable retinal stimulators activate surviving neurons to restore a sense of vision in people who have lost their photoreceptors through degenerative diseases. Complex spatial and temporal interactions occur in the retina during multi-electrode stimulation. Due to these complexities, most existing implants activate only a few electrodes at a time, limiting the repertoire of available stimulation patterns. Measuring the spatiotemporal interactions between electrodes and retinal cells, and incorporating them into a model may lead to improved stimulation algorithms that exploit the interactions. Here, we present a computational model that accurately predicts both the spatial and temporal nonlinear interactions of multi-electrode stimulation of rat retinal ganglion cells (RGCs). The model was verified using in vitro recordings of ON, OFF, and ON-OFF RGCs in response to subretinal multi-electrode stimulation with biphasic pulses at three stimulation frequencies (10, 20, 30 Hz). The model gives an estimate of each cell’s spatiotemporal electrical receptive fields (ERFs); i.e., the pattern of stimulation leading to excitation or suppression in the neuron. All cells had excitatory ERFs and many also had suppressive sub-regions of their ERFs. We show that the nonlinearities in observed responses arise largely from activation of presynaptic interneurons. When synaptic transmission was blocked, the number of sub-regions of the ERF was reduced, usually to a single excitatory ERF. This suggests that direct cell activation can be modeled accurately by a one-dimensional model with linear interactions between electrodes, whereas indirect stimulation due to summated presynaptic responses is nonlinear. PMID:29432411

A hybrid spatiotemporal drought forecasting model for operational use

NASA Astrophysics Data System (ADS)

Vasiliades, L.; Loukas, A.

2010-09-01

Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.

Calcium, BOBs, QEDs, microdomains and a cellular decision: control of mitotic cell division in sand dollar blastomeres.

PubMed

Silver, R B

1996-08-01

The role of Ca2+ in controlling cell processes (e.g. mitosis) presents an enigma in its ubiquity and selectivity. Intracellular free Ca2+ (Ca2+i) is an essential regulator of specific biochemical and physiological aspects of mitosis (e.g. nuclear envelope breakdown (NEB)). Changes in Ca2+i concentrations during mitosis in second cell-cycle sand dollar (Echinaracnius parma) blastomeres were imaged as Ca(2+)-dependent luminescence of the photoprotein aequorin with multi-spectral analytical video microscopy. Photons of this luminescence were seen as bright observable blobs (BOBs). Spatiotemporal patterns of BOBs were followed through one or more cell cycles to detect directly changes in Ca2+i, and were seen to change in a characteristic fashion prior to NEB, the onset of anaphase chromosome movement, and during cytokinesis. These patterns were observed from one cell cycle to the next in a single cell, from cell to cell, and from egg batch to egg batch. In both mitosis and synaptic transmission increases in Ca2+i concentration occurs in discrete, short-lived, highly localized pulses we name quantum emission domains (QEDs) within regions we named microdomains. Signal and statistical optical analyses of spatiotemporal BOB patterns show that many BOBs are linked by constant displacements in space-time (velocity). Linked BOBs are thus nonrandom and are classified as QEDS. Analyses of QED patterns demonstrated that the calcium signals required for NEB are nonrandom, and are evoked by an agent(s) generated proximal to a Ca2+i-QED; models of waves, diffusible agonists and Ca(2+)-activated Ca2+ release do not fit pre-NEB cell data. Spatial and temporal resolution of this multispectral approach significantly exceeds that reported for other methods, and avoids the perturbations associated with many fluorescent Ca2+ reporters that interfere with cells being studied (Ca(2+)-buffering, UV toxicity, etc.). Spatiotemporal patterns of Ca2+i-QED can control so many different processes, i.e. specific frequencies used to control particular processes. Predictive and structured patterns of calcium signals (e.g. a language expressed in Ca2+) may selectively regulate specific Ca(2+)-dependent cellular processes.

Intersubject synchronization of cortical activity during natural vision.

PubMed

Hasson, Uri; Nir, Yuval; Levy, Ifat; Fuhrmann, Galit; Malach, Rafael

2004-03-12

To what extent do all brains work alike during natural conditions? We explored this question by letting five subjects freely view half an hour of a popular movie while undergoing functional brain imaging. Applying an unbiased analysis in which spatiotemporal activity patterns in one brain were used to "model" activity in another brain, we found a striking level of voxel-by-voxel synchronization between individuals, not only in primary and secondary visual and auditory areas but also in association cortices. The results reveal a surprising tendency of individual brains to "tick collectively" during natural vision. The intersubject synchronization consisted of a widespread cortical activation pattern correlated with emotionally arousing scenes and regionally selective components. The characteristics of these activations were revealed with the use of an open-ended "reverse-correlation" approach, which inverts the conventional analysis by letting the brain signals themselves "pick up" the optimal stimuli for each specialized cortical area.

Spatiotemporal characterization of mTOR kinase activity following kainic acid induced status epilepticus and analysis of rat brain response to chronic rapamycin treatment.

PubMed

Macias, Matylda; Blazejczyk, Magdalena; Kazmierska, Paulina; Caban, Bartosz; Skalecka, Agnieszka; Tarkowski, Bartosz; Rodo, Anna; Konopacki, Jan; Jaworski, Jacek

2013-01-01

Mammalian target of rapamycin (mTOR) is a protein kinase that senses nutrient availability, trophic factors support, cellular energy level, cellular stress, and neurotransmitters and adjusts cellular metabolism accordingly. Adequate mTOR activity is needed for development as well as proper physiology of mature neurons. Consequently, changes in mTOR activity are often observed in neuropathology. Recently, several groups reported that seizures increase mammalian target of rapamycin (mTOR) kinase activity, and such increased activity in genetic models can contribute to spontaneous seizures. However, the current knowledge about the spatiotemporal pattern of mTOR activation induced by proconvulsive agents is rather rudimentary. Also consequences of insufficient mTOR activity on a status epilepticus are poorly understood. Here, we systematically investigated these two issues. We showed that mTOR signaling was activated by kainic acid (KA)-induced status epilepticus through several brain areas, including the hippocampus and cortex as well as revealed two waves of mTOR activation: an early wave (2 h) that occurs in neurons and a late wave that predominantly occurs in astrocytes. Unexpectedly, we found that pretreatment with rapamycin, a potent mTOR inhibitor, gradually (i) sensitized animals to KA treatment and (ii) induced gross anatomical changes in the brain.

Spatiotemporal Characterization of mTOR Kinase Activity Following Kainic Acid Induced Status Epilepticus and Analysis of Rat Brain Response to Chronic Rapamycin Treatment

PubMed Central

Macias, Matylda; Blazejczyk, Magdalena; Kazmierska, Paulina; Caban, Bartosz; Skalecka, Agnieszka; Tarkowski, Bartosz; Rodo, Anna; Konopacki, Jan; Jaworski, Jacek

2013-01-01

Mammalian target of rapamycin (mTOR) is a protein kinase that senses nutrient availability, trophic factors support, cellular energy level, cellular stress, and neurotransmitters and adjusts cellular metabolism accordingly. Adequate mTOR activity is needed for development as well as proper physiology of mature neurons. Consequently, changes in mTOR activity are often observed in neuropathology. Recently, several groups reported that seizures increase mammalian target of rapamycin (mTOR) kinase activity, and such increased activity in genetic models can contribute to spontaneous seizures. However, the current knowledge about the spatiotemporal pattern of mTOR activation induced by proconvulsive agents is rather rudimentary. Also consequences of insufficient mTOR activity on a status epilepticus are poorly understood. Here, we systematically investigated these two issues. We showed that mTOR signaling was activated by kainic acid (KA)-induced status epilepticus through several brain areas, including the hippocampus and cortex as well as revealed two waves of mTOR activation: an early wave (2 h) that occurs in neurons and a late wave that predominantly occurs in astrocytes. Unexpectedly, we found that pretreatment with rapamycin, a potent mTOR inhibitor, gradually (i) sensitized animals to KA treatment and (ii) induced gross anatomical changes in the brain. PMID:23724051

Virtual active touch using randomly patterned intracortical microstimulation.

PubMed

O'Doherty, Joseph E; Lebedev, Mikhail A; Li, Zheng; Nicolelis, Miguel A L

2012-01-01

Intracortical microstimulation (ICMS) has promise as a means for delivering somatosensory feedback in neuroprosthetic systems. Various tactile sensations could be encoded by temporal, spatial, or spatiotemporal patterns of ICMS. However, the applicability of temporal patterns of ICMS to artificial tactile sensation during active exploration is unknown, as is the minimum discriminable difference between temporally modulated ICMS patterns. We trained rhesus monkeys in an active exploration task in which they discriminated periodic pulse-trains of ICMS (200 Hz bursts at a 10 Hz secondary frequency) from pulse trains with the same average pulse rate, but distorted periodicity (200 Hz bursts at a variable instantaneous secondary frequency). The statistics of the aperiodic pulse trains were drawn from a gamma distribution with mean inter-burst intervals equal to those of the periodic pulse trains. The monkeys distinguished periodic pulse trains from aperiodic pulse trains with coefficients of variation 0.25 or greater. Reconstruction of movement kinematics, extracted from the activity of neuronal populations recorded in the sensorimotor cortex concurrent with the delivery of ICMS feedback, improved when the recording intervals affected by ICMS artifacts were removed from analysis. These results add to the growing evidence that temporally patterned ICMS can be used to simulate a tactile sense for neuroprosthetic devices.

Dynamic motif occupancy (DynaMO) analysis identifies transcription factors and their binding sites driving dynamic biological processes.

PubMed

Kuang, Zheng; Ji, Zhicheng; Boeke, Jef D; Ji, Hongkai

2018-01-09

Biological processes are usually associated with genome-wide remodeling of transcription driven by transcription factors (TFs). Identifying key TFs and their spatiotemporal binding patterns are indispensable to understanding how dynamic processes are programmed. However, most methods are designed to predict TF binding sites only. We present a computational method, dynamic motif occupancy analysis (DynaMO), to infer important TFs and their spatiotemporal binding activities in dynamic biological processes using chromatin profiling data from multiple biological conditions such as time-course histone modification ChIP-seq data. In the first step, DynaMO predicts TF binding sites with a random forests approach. Next and uniquely, DynaMO infers dynamic TF binding activities at predicted binding sites using their local chromatin profiles from multiple biological conditions. Another landmark of DynaMO is to identify key TFs in a dynamic process using a clustering and enrichment analysis of dynamic TF binding patterns. Application of DynaMO to the yeast ultradian cycle, mouse circadian clock and human neural differentiation exhibits its accuracy and versatility. We anticipate DynaMO will be generally useful for elucidating transcriptional programs in dynamic processes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Spatio-temporal dynamics induced by competing instabilities in two asymmetrically coupled nonlinear evolution equations

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

Schüler, D.; Alonso, S.; Bär, M.

2014-12-15

Pattern formation often occurs in spatially extended physical, biological, and chemical systems due to an instability of the homogeneous steady state. The type of the instability usually prescribes the resulting spatio-temporal patterns and their characteristic length scales. However, patterns resulting from the simultaneous occurrence of instabilities cannot be expected to be simple superposition of the patterns associated with the considered instabilities. To address this issue, we design two simple models composed by two asymmetrically coupled equations of non-conserved (Swift-Hohenberg equations) or conserved (Cahn-Hilliard equations) order parameters with different characteristic wave lengths. The patterns arising in these systems range from coexistingmore » static patterns of different wavelengths to traveling waves. A linear stability analysis allows to derive a two parameter phase diagram for the studied models, in particular, revealing for the Swift-Hohenberg equations, a co-dimension two bifurcation point of Turing and wave instability and a region of coexistence of stationary and traveling patterns. The nonlinear dynamics of the coupled evolution equations is investigated by performing accurate numerical simulations. These reveal more complex patterns, ranging from traveling waves with embedded Turing patterns domains to spatio-temporal chaos, and a wide hysteretic region, where waves or Turing patterns coexist. For the coupled Cahn-Hilliard equations the presence of a weak coupling is sufficient to arrest the coarsening process and to lead to the emergence of purely periodic patterns. The final states are characterized by domains with a characteristic length, which diverges logarithmically with the coupling amplitude.« less

Robust stochastic Turing patterns in the development of a one-dimensional cyanobacterial organism.

PubMed

Di Patti, Francesca; Lavacchi, Laura; Arbel-Goren, Rinat; Schein-Lubomirsky, Leora; Fanelli, Duccio; Stavans, Joel

2018-05-01

Under nitrogen deprivation, the one-dimensional cyanobacterial organism Anabaena sp. PCC 7120 develops patterns of single, nitrogen-fixing cells separated by nearly regular intervals of photosynthetic vegetative cells. We study a minimal, stochastic model of developmental patterns in Anabaena that includes a nondiffusing activator, two diffusing inhibitor morphogens, demographic fluctuations in the number of morphogen molecules, and filament growth. By tracking developing filaments, we provide experimental evidence for different spatiotemporal roles of the two inhibitors during pattern maintenance and for small molecular copy numbers, justifying a stochastic approach. In the deterministic limit, the model yields Turing patterns within a region of parameter space that shrinks markedly as the inhibitor diffusivities become equal. Transient, noise-driven, stochastic Turing patterns are produced outside this region, which can then be fixed by downstream genetic commitment pathways, dramatically enhancing the robustness of pattern formation, also in the biologically relevant situation in which the inhibitors' diffusivities may be comparable.

Self-organization principles of intracellular pattern formation.

PubMed

Halatek, J; Brauns, F; Frey, E

2018-05-26

Dynamic patterning of specific proteins is essential for the spatio-temporal regulation of many important intracellular processes in prokaryotes, eukaryotes and multicellular organisms. The emergence of patterns generated by interactions of diffusing proteins is a paradigmatic example for self-organization. In this article, we review quantitative models for intracellular Min protein patterns in Escherichia coli , Cdc42 polarization in Saccharomyces cerevisiae and the bipolar PAR protein patterns found in Caenorhabditis elegans By analysing the molecular processes driving these systems we derive a theoretical perspective on general principles underlying self-organized pattern formation. We argue that intracellular pattern formation is not captured by concepts such as 'activators', 'inhibitors' or 'substrate depletion'. Instead, intracellular pattern formation is based on the redistribution of proteins by cytosolic diffusion, and the cycling of proteins between distinct conformational states. Therefore, mass-conserving reaction-diffusion equations provide the most appropriate framework to study intracellular pattern formation. We conclude that directed transport, e.g. cytosolic diffusion along an actively maintained cytosolic gradient, is the key process underlying pattern formation. Thus the basic principle of self-organization is the establishment and maintenance of directed transport by intracellular protein dynamics.This article is part of the theme issue 'Self-organization in cell biology'. © 2018 The Authors.

Characterizing and Discovering Spatiotemporal Social Contact Patterns for Healthcare.

PubMed

Yang, Bo; Pei, Hongbin; Chen, Hechang; Liu, Jiming; Xia, Shang

2017-08-01

During an epidemic, the spatial, temporal and demographic patterns of disease transmission are determined by multiple factors. In addition to the physiological properties of the pathogens and hosts, the social contact of the host population, which characterizes the reciprocal exposures of individuals to infection according to their demographic structure and various social activities, are also pivotal to understanding and predicting the prevalence of infectious diseases. How social contact is measured will affect the extent to which we can forecast the dynamics of infections in the real world. Most current work focuses on modeling the spatial patterns of static social contact. In this work, we use a novel perspective to address the problem of how to characterize and measure dynamic social contact during an epidemic. We propose an epidemic-model-based tensor deconvolution framework in which the spatiotemporal patterns of social contact are represented by the factors of the tensors. These factors can be discovered using a tensor deconvolution procedure with the integration of epidemic models based on rich types of data, mainly heterogeneous outbreak surveillance data, socio-demographic census data and physiological data from medical reports. Using reproduction models that include SIR/SIS/SEIR/SEIS models as case studies, the efficacy and applications of the proposed framework are theoretically analyzed, empirically validated and demonstrated through a set of rigorous experiments using both synthetic and real-world data.

Spatial, temporal and spatio-temporal clusters of measles incidence at the county level in Guangxi, China during 2004-2014: flexibly shaped scan statistics.

PubMed

Tang, Xianyan; Geater, Alan; McNeil, Edward; Deng, Qiuyun; Dong, Aihu; Zhong, Ge

2017-04-04

Outbreaks of measles re-emerged in Guangxi province during 2013-2014, where measles again became a major public health concern. A better understanding of the patterns of measles cases would help in identifying high-risk areas and periods for optimizing preventive strategies, yet these patterns remain largely unknown. Thus, this study aimed to determine the patterns of measles clusters in space, time and space-time at the county level over the period 2004-2014 in Guangxi. Annual data on measles cases and population sizes for each county were obtained from Guangxi CDC and Guangxi Bureau of Statistics, respectively. Epidemic curves and Kulldorff's temporal scan statistics were used to identify seasonal peaks and high-risk periods. Tango's flexible scan statistics were implemented to determine irregular spatial clusters. Spatio-temporal clusters in elliptical cylinder shapes were detected by Kulldorff's scan statistics. Population attributable risk percent (PAR%) of children aged ≤24 months was used to identify regions with a heavy burden of measles. Seasonal peaks occurred between April and June, and a temporal measles cluster was detected in 2014. Spatial clusters were identified in West, Southwest and North Central Guangxi. Three phases of spatio-temporal clusters with high relative risk were detected: Central Guangxi during 2004-2005, Midwest Guangxi in 2007, and West and Southwest Guangxi during 2013-2014. Regions with high PAR% were mainly clustered in West, Southwest, North and Central Guangxi. A temporal uptrend of measles incidence existed in Guangxi between 2010 and 2014, while downtrend during 2004-2009. The hotspots shifted from Central to West and Southwest Guangxi, regions overburdened with measles. Thus, intensifying surveillance of timeliness and completeness of routine vaccination and implementing supplementary immunization activities for measles should prioritized in these regions.

Patterning of functional human astrocytes onto parylene-C/SiO2 substrates for the study of Ca2+ dynamics in astrocytic networks

NASA Astrophysics Data System (ADS)

Raos, B. J.; Simpson, M. C.; Doyle, C. S.; Murray, A. F.; Graham, E. S.; Unsworth, C. P.

2018-06-01

Objective. Recent literature suggests that astrocytes form organized functional networks and communicate through transient changes in cytosolic Ca2+. Traditional techniques to investigate network activity, such as pharmacological blocking or genetic knockout, are difficult to restrict to individual cells. The objective of this work is to develop cell-patterning techniques to physically manipulate astrocytic interactions to enable the study of Ca2+ in astrocytic networks. Approach. We investigate how an in vitro cell-patterning platform that utilizes geometric patterns of parylene-C on SiO2 can be used to physically isolate single astrocytes and small astrocytic networks. Main results. We report that single astrocytes are effectively isolated on 75  ×  75 µm square parylene nodes, whereas multi-cellular astrocytic networks are isolated on larger nodes, with the mean number of astrocytes per cluster increasing as a function of node size. Additionally, we report that astrocytes in small multi-cellular clusters exhibit spatio-temporal clustering of Ca2+ transients. Finally, we report that the frequency and regularity of Ca2+ transients was positively correlated with astrocyte connectivity. Significance. The significance of this work is to demonstrate how patterning hNT astrocytes replicates spatio-temporal clustering of Ca2+ signalling that is observed in vivo but not in dissociated in vitro cultures. We therefore highlight the importance of the structure of astrocytic networks in determining ensemble Ca2+ behaviour.

Epigenomic Landscape of Human Fetal Brain, Heart, and Liver.

PubMed

Yan, Liying; Guo, Hongshan; Hu, Boqiang; Li, Rong; Yong, Jun; Zhao, Yangyu; Zhi, Xu; Fan, Xiaoying; Guo, Fan; Wang, Xiaoye; Wang, Wei; Wei, Yuan; Wang, Yan; Wen, Lu; Qiao, Jie; Tang, Fuchou

2016-02-26

The epigenetic regulation of spatiotemporal gene expression is crucial for human development. Here, we present whole-genome chromatin immunoprecipitation followed by high throughput DNA sequencing (ChIP-seq) analyses of a wide variety of histone markers in the brain, heart, and liver of early human embryos shortly after their formation. We identified 40,181 active enhancers, with a large portion showing tissue-specific and developmental stage-specific patterns, pointing to their roles in controlling the ordered spatiotemporal expression of the developmental genes in early human embryos. Moreover, using sequential ChIP-seq, we showed that all three organs have hundreds to thousands of bivalent domains that are marked by both H3K4me3 and H3K27me3, probably to keep the progenitor cells in these organs ready for immediate differentiation into diverse cell types during subsequent developmental processes. Our work illustrates the potentially critical roles of tissue-specific and developmental stage-specific epigenomes in regulating the spatiotemporal expression of developmental genes during early human embryonic development. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

A Comparative Study of Frequent and Maximal Periodic Pattern Mining Algorithms in Spatiotemporal Databases

NASA Astrophysics Data System (ADS)

Obulesu, O.; Rama Mohan Reddy, A., Dr; Mahendra, M.

2017-08-01

Detecting regular and efficient cyclic models is the demanding activity for data analysts due to unstructured, vigorous and enormous raw information produced from web. Many existing approaches generate large candidate patterns in the occurrence of huge and complex databases. In this work, two novel algorithms are proposed and a comparative examination is performed by considering scalability and performance parameters. The first algorithm is, EFPMA (Extended Regular Model Detection Algorithm) used to find frequent sequential patterns from the spatiotemporal dataset and the second one is, ETMA (Enhanced Tree-based Mining Algorithm) for detecting effective cyclic models with symbolic database representation. EFPMA is an algorithm grows models from both ends (prefixes and suffixes) of detected patterns, which results in faster pattern growth because of less levels of database projection compared to existing approaches such as Prefixspan and SPADE. ETMA uses distinct notions to store and manage transactions data horizontally such as segment, sequence and individual symbols. ETMA exploits a partition-and-conquer method to find maximal patterns by using symbolic notations. Using this algorithm, we can mine cyclic models in full-series sequential patterns including subsection series also. ETMA reduces the memory consumption and makes use of the efficient symbolic operation. Furthermore, ETMA only records time-series instances dynamically, in terms of character, series and section approaches respectively. The extent of the pattern and proving efficiency of the reducing and retrieval techniques from synthetic and actual datasets is a really open & challenging mining problem. These techniques are useful in data streams, traffic risk analysis, medical diagnosis, DNA sequence Mining, Earthquake prediction applications. Extensive investigational outcomes illustrates that the algorithms outperforms well towards efficiency and scalability than ECLAT, STNR and MAFIA approaches.

Spontaneous switching among multiple spatio-temporal patterns in three-oscillator systems constructed with oscillatory cells of true slime mold

NASA Astrophysics Data System (ADS)

Takamatsu, Atsuko

2006-11-01

Three-oscillator systems with plasmodia of true slime mold, Physarum polycephalum, which is an oscillatory amoeba-like unicellular organism, were experimentally constructed and their spatio-temporal patterns were investigated. Three typical spatio-temporal patterns were found: rotation ( R), partial in-phase ( PI), and partial anti-phase with double frequency ( PA). In pattern R, phase differences between adjacent oscillators were almost 120 ∘. In pattern PI, two oscillators were in-phase and the third oscillator showed anti-phase against the two oscillators. In pattern PA, two oscillators showed anti-phase and the third oscillator showed frequency doubling oscillation with small amplitude. Actually each pattern is not perfectly stable but quasi-stable. Interestingly, the system shows spontaneous switching among the multiple quasi-stable patterns. Statistical analyses revealed a characteristic in the residence time of each pattern: the histograms seem to have Gamma-like distribution form but with a sharp peak and a tail on the side of long period. That suggests the attractor of this system has complex structure composed of at least three types of sub-attractors: a “Gamma attractor”-involved with several Poisson processes, a “deterministic attractor”-the residence time is deterministic, and a “stable attractor”-each pattern is stable. When the coupling strength was small, only the Gamma attractor was observed and switching behavior among patterns R, PI, and PA almost always via an asynchronous pattern named O. A conjecture is as follows: Internal/external noise exposes each pattern of R, PI, and PA coexisting around bifurcation points: That is observed as the Gamma attractor. As coupling strength increases, the deterministic attractor appears then followed by the stable attractor, always accompanied with the Gamma attractor. Switching behavior could be caused by regular existence of the Gamma attractor.

Modeling spatio-temporal wildfire ignition point patterns

Treesearch

Amanda S. Hering; Cynthia L. Bell; Marc G. Genton

2009-01-01

We analyze and model the structure of spatio-temporal wildfire ignitions in the St. Johns River Water Management District in northeastern Florida. Previous studies, based on the K-function and an assumption of homogeneity, have shown that wildfire events occur in clusters. We revisit this analysis based on an inhomogeneous K-...

Spatiotemporal Coupling of the Tongue in Amyotrophic Lateral Sclerosis

ERIC Educational Resources Information Center

Kuruvilla, Mili S.; Green, Jordan R.; Yunusova, Yana; Hanford, Kathy

2012-01-01

Purpose: The primary aim of the investigation was to identify deficits in spatiotemporal coupling between tongue regions in amyotrophic lateral sclerosis (ALS). The relations between disease-related changes in tongue movement patterns and speech intelligibility were also determined. Methods: The authors recorded word productions from 11…

Spatiotemporal patterns in reaction-diffusion system and in a vibrated granular bed

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

Swinney, H.L.; Lee, K.J.; McCormick, W.D.

Experiments on a quasi-two-dimensional reaction-diffusion system reveal transitions from a uniform state to stationary hexagonal, striped, and rhombic spatial patterns. For other reactor conditions lamellae and self-replicating spot patterns are observed. These patterns form in continuously fed thin gel reactors that can be maintained indefinitely in well-defined nonequilibrium states. Reaction-diffusion models with two chemical species yield patterns similar to those observed in the experiments. Pattern formation is also being examined in vertically oscillated thin granular layers (typically 3-30 particle diameters deep). For small acceleration amplitudes, a granular layer is flat, but above a well-defined critical acceleration amplitude, spatial patterns spontaneouslymore » form. Disordered time-dependent granular patterns are observed as well as regular patterns of squares, stripes, and hexagons. A one-dimensional model consisting of a completely inelastic ball colliding with a sinusoidally oscillating platform provides a semi-quantitative description of most of the observed bifurcations between the different spatiotemporal regimes.« less

Global patterns of drought recovery

DOE PAGES

Schwalm, Christopher R.; Anderegg, William R. L.; Michalak, Anna M.; ...

2017-08-09

Drought has major impacts on natural and human systems, and is especially important for land carbon sink variability due to its influence on terrestrial biosphere climate regulation. While 20th Century trends in drought regimes have been varied, “more extreme extremes”, including more frequent and severe droughts, are expected in the 21st Century. Recovery time, the length of time an ecosystem requires to revert to its pre-drought functional state, is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns are largely unknown. Here we use three independent global data products of gross primary productivitymore » to show that, across diverse terrestrial ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO 2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: (1) Across the globe, recovery is longest in the tropics and high northern latitudes—critical tipping elements in Earth’s climate system. (2) Drought impacts, the area of ecosystems under active recovery and recovery times, have increased over the 20th century. If future droughts become more frequent, time between droughts may become shorter than drought recovery time, leading to chronically impacted ecosystems.« less

Global patterns of drought recovery

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

Schwalm, Christopher R.; Anderegg, William R. L.; Michalak, Anna M.

Drought has major impacts on natural and human systems, and is especially important for land carbon sink variability due to its influence on terrestrial biosphere climate regulation. While 20th Century trends in drought regimes have been varied, “more extreme extremes”, including more frequent and severe droughts, are expected in the 21st Century. Recovery time, the length of time an ecosystem requires to revert to its pre-drought functional state, is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns are largely unknown. Here we use three independent global data products of gross primary productivitymore » to show that, across diverse terrestrial ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO 2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: (1) Across the globe, recovery is longest in the tropics and high northern latitudes—critical tipping elements in Earth’s climate system. (2) Drought impacts, the area of ecosystems under active recovery and recovery times, have increased over the 20th century. If future droughts become more frequent, time between droughts may become shorter than drought recovery time, leading to chronically impacted ecosystems.« less

Global patterns of drought recovery.

PubMed

Schwalm, Christopher R; Anderegg, William R L; Michalak, Anna M; Fisher, Joshua B; Biondi, Franco; Koch, George; Litvak, Marcy; Ogle, Kiona; Shaw, John D; Wolf, Adam; Huntzinger, Deborah N; Schaefer, Kevin; Cook, Robert; Wei, Yaxing; Fang, Yuanyuan; Hayes, Daniel; Huang, Maoyi; Jain, Atul; Tian, Hanqin

2017-08-09

Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time-how long an ecosystem requires to revert to its pre-drought functional state-is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO 2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth's climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.

Global patterns of drought recovery

NASA Astrophysics Data System (ADS)

Schwalm, Christopher R.; Anderegg, William R. L.; Michalak, Anna M.; Fisher, Joshua B.; Biondi, Franco; Koch, George; Litvak, Marcy; Ogle, Kiona; Shaw, John D.; Wolf, Adam; Huntzinger, Deborah N.; Schaefer, Kevin; Cook, Robert; Wei, Yaxing; Fang, Yuanyuan; Hayes, Daniel; Huang, Maoyi; Jain, Atul; Tian, Hanqin

2017-08-01

Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time—how long an ecosystem requires to revert to its pre-drought functional state—is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth’s climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.

NeuroPG: open source software for optical pattern generation and data acquisition

PubMed Central

Avants, Benjamin W.; Murphy, Daniel B.; Dapello, Joel A.; Robinson, Jacob T.

2015-01-01

Patterned illumination using a digital micromirror device (DMD) is a powerful tool for optogenetics. Compared to a scanning laser, DMDs are inexpensive and can easily create complex illumination patterns. Combining these complex spatiotemporal illumination patterns with optogenetics allows DMD-equipped microscopes to probe neural circuits by selectively manipulating the activity of many individual cells or many subcellular regions at the same time. To use DMDs to study neural activity, scientists must develop specialized software to coordinate optical stimulation patterns with the acquisition of electrophysiological and fluorescence data. To meet this growing need we have developed an open source optical pattern generation software for neuroscience—NeuroPG—that combines, DMD control, sample visualization, and data acquisition in one application. Built on a MATLAB platform, NeuroPG can also process, analyze, and visualize data. The software is designed specifically for the Mightex Polygon400; however, as an open source package, NeuroPG can be modified to incorporate any data acquisition, imaging, or illumination equipment that is compatible with MATLAB’s Data Acquisition and Image Acquisition toolboxes. PMID:25784873

Increased biomagnetic activity in the ventral pathway in mild cognitive impairment.

PubMed

Maestú, F; Campo, P; Del Río, D; Moratti, S; Gil-Gregorio, P; Fernández, A; Capilla, A; Ortiz, T

2008-06-01

Mild cognitive impairment (MCI) patients represent an intermediary state between healthy aging and dementia. MCI activation profiles, recorded during a memory task, have been studied either through high spatial resolution or high temporal resolution techniques. However, little is known about the benefit of combining both dimensions. Here, we investigate, by means of magnetoencephalography (MEG), whether spatio-temporal profiles of neuromagnetic activity could differentiate between MCI and age-matched elderly participants. Taking the advantage of the high temporal resolution and good spatial resolution of MEG, neuromagnetic activity from 15 elderly MCI patients and 20 age-matched controls was recorded during the performance of a modified version of the Sternberg paradigm. Behavioral performance was similar in both groups. A between group analysis revealed that MCI patients showed bilateral higher activity in the ventral pathway, in both the target and the non-target stimuli. A within-group analysis of the target stimuli, indicates a lack of asymmetry through all late latency windows in both groups. MCI patients showed a compensatory mechanism represented by an increased bilateral activity of the ventral pathway in order to achieve a behavioral performance similar to the control group. This spatio-temporal pattern of activity could be another tool to differentiate between healthy aging and MCI patients.

Spatiotemporal Stochastic Resonance:Theory and Experiment

NASA Astrophysics Data System (ADS)

Peter, Jung

1996-03-01

The amplification of weak periodic signals in bistable or excitable systems via stochastic resonance has been studied intensively over the last years. We are going one step further and ask: Can noise enhance spatiotemporal patterns in excitable media and can this effect be observed in nature? To this end, we are looking at large, two dimensional arrays of coupled excitable elements. Due to the coupling, excitation can propagate through the array in form of nonlinear waves. We observe target waves, rotating spiral waves and other wave forms. If the coupling between the elements is below a critical threshold, any excitational pattern will die out in the absence of noise. Below this threshold, large scale rotating spiral waves - as they are observed above threshold - can be maintained by a proper level of the noise[1]. Furthermore, their geometric features, such as the curvature can be controlled by the homogeneous noise level[2]. If the noise level is too large, break up of spiral waves and collisions with spontaneously nucleated waves yields spiral turbulence. Driving our array with a spatiotemporal pattern, e.g. a rotating spiral wave, we show that for weak coupling the excitational response of the array shows stochastic resonance - an effect we have termed spatiotemporal stochastic resonance. In the last part of the talk I'll make contact with calcium waves, observed in astrocyte cultures and hippocampus slices[3]. A. Cornell-Bell and collaborators[3] have pointed out the role of calcium waves for long-range glial signaling. We demonstrate the similarity of calcium waves with nonlinear waves in noisy excitable media. The noise level in the tissue is characterized by spontaneous activity and can be controlled by applying neuro-transmitter substances[3]. Noise effects in our model are compared with the effect of neuro-transmitters on calcium waves. [1]P. Jung and G. Mayer-Kress, CHAOS 5, 458 (1995). [2]P. Jung and G. Mayer-Kress, Phys. Rev. Lett.62, 2682 (1995). [3] A. Cornell-Bell, Steven M. Finkbeiner, Mark.S. Cooper and Stephen J. Smith, SCIENCE, 247, 373 (1990).

A model for oscillations and pattern formation in protoplasmic droplets of Physarum polycephalum

NASA Astrophysics Data System (ADS)

Radszuweit, M.; Engel, H.; Bär, M.

2010-12-01

A mechano-chemical model for the spatiotemporal dynamics of free calcium and the thickness in protoplasmic droplets of the true slime mold Physarum polycephalum is derived starting from a physiologically detailed description of intracellular calcium oscillations proposed by Smith and Saldana (Biopys. J. 61, 368 (1992)). First, we have modified the Smith-Saldana model for the temporal calcium dynamics in order to reproduce the experimentally observed phase relation between calcium and mechanical tension oscillations. Then, we formulate a model for spatiotemporal dynamics by adding spatial coupling in the form of calcium diffusion and advection due to calcium-dependent mechanical contraction. In another step, the resulting reaction-diffusion model with mechanical coupling is simplified to a reaction-diffusion model with global coupling that approximates the mechanical part. We perform a bifurcation analysis of the local dynamics and observe a Hopf bifurcation upon increase of a biochemical activity parameter. The corresponding reaction-diffusion model with global coupling shows regular and chaotic spatiotemporal behaviour for parameters with oscillatory dynamics. In addition, we show that the global coupling leads to a long-wavelength instability even for parameters where the local dynamics possesses a stable spatially homogeneous steady state. This instability causes standing waves with a wavelength of twice the system size in one dimension. Simulations of the model in two dimensions are found to exhibit defect-mediated turbulence as well as various types of spiral wave patterns in qualitative agreement with earlier experimental observation by Takagi and Ueda (Physica D, 237, 420 (2008)).

Spatiotemporal Spike Coding of Behavioral Adaptation in the Dorsal Anterior Cingulate Cortex

PubMed Central

Logiaco, Laureline; Quilodran, René; Procyk, Emmanuel; Arleo, Angelo

2015-01-01

The frontal cortex controls behavioral adaptation in environments governed by complex rules. Many studies have established the relevance of firing rate modulation after informative events signaling whether and how to update the behavioral policy. However, whether the spatiotemporal features of these neuronal activities contribute to encoding imminent behavioral updates remains unclear. We investigated this issue in the dorsal anterior cingulate cortex (dACC) of monkeys while they adapted their behavior based on their memory of feedback from past choices. We analyzed spike trains of both single units and pairs of simultaneously recorded neurons using an algorithm that emulates different biologically plausible decoding circuits. This method permits the assessment of the performance of both spike-count and spike-timing sensitive decoders. In response to the feedback, single neurons emitted stereotypical spike trains whose temporal structure identified informative events with higher accuracy than mere spike count. The optimal decoding time scale was in the range of 70–200 ms, which is significantly shorter than the memory time scale required by the behavioral task. Importantly, the temporal spiking patterns of single units were predictive of the monkeys’ behavioral response time. Furthermore, some features of these spiking patterns often varied between jointly recorded neurons. All together, our results suggest that dACC drives behavioral adaptation through complex spatiotemporal spike coding. They also indicate that downstream networks, which decode dACC feedback signals, are unlikely to act as mere neural integrators. PMID:26266537

Spatiotemporal psychopathology I: No rest for the brain's resting state activity in depression? Spatiotemporal psychopathology of depressive symptoms.

PubMed

Northoff, Georg

2016-01-15

Despite intense neurobiological investigation in psychiatric disorders like major depressive disorder (MDD), the basic disturbance that underlies the psychopathological symptoms of MDD remains, nevertheless, unclear. Neuroimaging has focused mainly on the brain's extrinsic activity, specifically task-evoked or stimulus-induced activity, as related to the various sensorimotor, affective, cognitive, and social functions. Recently, the focus has shifted to the brain's intrinsic activity, otherwise known as its resting state activity. While various abnormalities have been observed during this activity, their meaning and significance for depression, along with its various psychopathological symptoms, are yet to be defined. Based on findings in healthy brain resting state activity and its particular spatial and temporal structure - defined in a functional and physiological sense rather than anatomical and structural - I claim that the various depressive symptoms are spatiotemporal disturbances of the resting state activity and its spatiotemporal structure. This is supported by recent findings that link ruminations and increased self-focus in depression to abnormal spatial organization of resting state activity. Analogously, affective and cognitive symptoms like anhedonia, suicidal ideation, and thought disorder can be traced to an increased focus on the past, increased past-focus as basic temporal disturbance o the resting state. Based on these findings, I conclude that the various depressive symptoms must be conceived as spatiotemporal disturbances of the brain's resting state's activity and its spatiotemporal structure. Importantly, this entails a new form of psychopathology, "Spatiotemporal Psychopathology" that directly links the brain and psyche, therefore having major diagnostic and therapeutic implications for clinical practice. Copyright © 2015 Elsevier B.V. All rights reserved.

Spatio-temporal foreshock activity during stick-slip experiments of large rock samples

NASA Astrophysics Data System (ADS)

Tsujimura, Y.; Kawakata, H.; Fukuyama, E.; Yamashita, F.; Xu, S.; Mizoguchi, K.; Takizawa, S.; Hirano, S.

2016-12-01

Foreshock activity has sometimes been reported for large earthquakes, and has been roughly classified into the following two classes. For shallow intraplate earthquakes, foreshocks occurred in the vicinity of the mainshock hypocenter (e.g., Doi and Kawakata, 2012; 2013). And for intraplate subduction earthquakes, foreshock hypocenters migrated toward the mainshock hypocenter (Kato, et al., 2012; Yagi et al., 2014). To understand how foreshocks occur, it is useful to investigate the spatio-temporal activities of foreshocks in the laboratory experiments under controlled conditions. We have conducted stick-slip experiments by using a large-scale biaxial friction apparatus at NIED in Japan (e.g., Fukuyama et al., 2014). Our previous results showed that stick-slip events repeatedly occurred in a run, but only those later events were preceded by foreshocks. Kawakata et al. (2014) inferred that the gouge generated during the run was an important key for foreshock occurrence. In this study, we proceeded to carry out stick-slip experiments of large rock samples whose interface (fault plane) is 1.5 meter long and 0.5 meter wide. After some runs to generate fault gouge between the interface. In the current experiments, we investigated spatio-temporal activities of foreshocks. We detected foreshocks from waveform records of 3D array of piezo-electric sensors. Our new results showed that more than three foreshocks (typically about twenty) had occurred during each stick-slip event, in contrast to the few foreshocks observed during previous experiments without pre-existing gouge. Next, we estimated the hypocenter locations of the stick-slip events, and found that they were located near the opposite end to the loading point. In addition, we observed a migration of foreshock hypocenters toward the hypocenter of each stick-slip event. This suggests that the foreshock activity observed in our current experiments was similar to that for the interplate earthquakes in terms of the spatio-temporal pattern. This work was supported by NIED research project "Development of monitoring and forecasting technology for crustal activity", JSPS KAKENHI Grant Number 23340131, and MEXT of Japan, under its Earthquake and Volcano Hazards Observation and Research Program.

Are species photosynthetic characteristics good predictors of seedling post-hurricane demographic patterns and species spatiotemporal distribution in a hurricane impacted wet montane forest?

NASA Astrophysics Data System (ADS)

Luke, Denneko; McLaren, Kurt

2018-05-01

In situ measurements of leaf level photosynthetic response to light were collected from seedlings of ten tree species from a tropical montane wet forest, the John Crow Mountains, Jamaica. A model-based recursive partitioning ('mob') algorithm was then used to identify species associations based on their fitted photosynthetic response curves. Leaf area dark respiration (RD) and light saturated maximum photosynthetic (Amax) rates were also used as 'mob' partitioning variables, to identify species associations based on seedling demographic patterns (from June 2007 to May 2010) following a hurricane (Aug. 2007) and the spatiotemporal distribution patterns of stems in 2006 and 2012. RD and Amax rates ranged from 1.14 to 2.02 μmol (CO2) m-2s-1 and 2.97-5.87 μmol (CO2) m-2s-1, respectively, placing the ten species in the range of intermediate shade tolerance. Several parsimonious species 'mob' groups were formed based on 1) interspecific differences among species response curves, 2) variations in post-hurricane seedling demographic trends and 3) RD rates and species spatiotemporal distribution patterns at aspects that are more or less exposed to hurricanes. The composition of parsimonious groupings based on photosynthetic curves was not concordant with the groups based on demographic trends but was partially concordant with the RD - species spatiotemporal distribution groups. Our results indicated that the influence of photosynthetic characteristics on demographic traits and species distributions was not straightforward. Rather, there was a complex pattern of interaction between ecophysiological and demographic traits, which determined species successional status, post-hurricane response and ultimately, species distribution at our study site.

Quantitative and qualitative characterization of zigzag spatiotemporal chaos in a system of amplitude equations for nematic electroconvection.

PubMed

Oprea, Iuliana; Triandaf, Ioana; Dangelmayr, Gerhard; Schwartz, Ira B

2007-06-01

It has been suggested by experimentalists that a weakly nonlinear analysis of the recently introduced equations of motion for the nematic electroconvection by M. Treiber and L. Kramer [Phys. Rev. E 58, 1973 (1998)] has the potential to reproduce the dynamics of the zigzag-type extended spatiotemporal chaos and localized solutions observed near onset in experiments [M. Dennin, D. S. Cannell, and G. Ahlers, Phys. Rev. E 57, 638 (1998); J. T. Gleeson (private communication)]. In this paper, we study a complex spatiotemporal pattern, identified as spatiotemporal chaos, that bifurcates at the onset from a spatially uniform solution of a system of globally coupled complex Ginzburg-Landau equations governing the weakly nonlinear evolution of four traveling wave envelopes. The Ginzburg-Landau system can be derived directly from the weak electrolyte model for electroconvection in nematic liquid crystals when the primary instability is a Hopf bifurcation to oblique traveling rolls. The chaotic nature of the pattern and the resemblance to the observed experimental spatiotemporal chaos in the electroconvection of nematic liquid crystals are confirmed through a combination of techniques including the Karhunen-Loeve decomposition, time-series analysis of the amplitudes of the dominant modes, statistical descriptions, and normal form theory, showing good agreement between theory and experiments.

Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago

PubMed Central

Zhou, Xiaolu

2015-01-01

The growing number of bike sharing systems (BSS) in many cities largely facilitates biking for transportation and recreation. Most recent bike sharing systems produce time and location specific data, which enables the study of travel behavior and mobility of each individual. However, despite a rapid growth of interest, studies on massive bike sharing data and the underneath travel pattern are still limited. Few studies have explored and visualized spatiotemporal patterns of bike sharing behavior using flow clustering, nor examined the station functional profiles based on over-demand patterns. This study investigated the spatiotemporal biking pattern in Chicago by analyzing massive BSS data from July to December in 2013 and 2014. The BSS in Chicago gained more popularity. About 15.9% more people subscribed to this service. Specifically, we constructed bike flow similarity graph and used fastgreedy algorithm to detect spatial communities of biking flows. By using the proposed methods, we discovered unique travel patterns on weekdays and weekends as well as different travel trends for customers and subscribers from the noisy massive amount data. In addition, we also examined the temporal demands for bikes and docks using hierarchical clustering method. Results demonstrated the modeled over-demand patterns in Chicago. This study contributes to offer better knowledge of biking flow patterns, which was difficult to obtain using traditional methods. Given the trend of increasing popularity of the BSS and data openness in different cities, methods used in this study can extend to examine the biking patterns and BSS functionality in different cities. PMID:26445357

Understanding Spatiotemporal Patterns of Biking Behavior by Analyzing Massive Bike Sharing Data in Chicago.

PubMed

Zhou, Xiaolu

2015-01-01

The growing number of bike sharing systems (BSS) in many cities largely facilitates biking for transportation and recreation. Most recent bike sharing systems produce time and location specific data, which enables the study of travel behavior and mobility of each individual. However, despite a rapid growth of interest, studies on massive bike sharing data and the underneath travel pattern are still limited. Few studies have explored and visualized spatiotemporal patterns of bike sharing behavior using flow clustering, nor examined the station functional profiles based on over-demand patterns. This study investigated the spatiotemporal biking pattern in Chicago by analyzing massive BSS data from July to December in 2013 and 2014. The BSS in Chicago gained more popularity. About 15.9% more people subscribed to this service. Specifically, we constructed bike flow similarity graph and used fastgreedy algorithm to detect spatial communities of biking flows. By using the proposed methods, we discovered unique travel patterns on weekdays and weekends as well as different travel trends for customers and subscribers from the noisy massive amount data. In addition, we also examined the temporal demands for bikes and docks using hierarchical clustering method. Results demonstrated the modeled over-demand patterns in Chicago. This study contributes to offer better knowledge of biking flow patterns, which was difficult to obtain using traditional methods. Given the trend of increasing popularity of the BSS and data openness in different cities, methods used in this study can extend to examine the biking patterns and BSS functionality in different cities.

An immunohistochemical study of APG-2 protein in the rat hippocampus after transient forebrain ischemia.

PubMed

Lee, Mun-Yong; Choi, Yun-Sik; Choi, Jeong-Sun; Min, Do Sik; Chun, Myung-Hoon; Kim, Ok Nyu; Lee, Sang Bok; Kim, Seong Yun

2002-01-11

The cellular localization and spatiotemporal expression pattern of APG-2 protein, a member of the heat shock protein 110 family, were investigated in the rat hippocampus after transient forebrain ischemia. The spatiotemporal patterns of immunoreactivity of both APG-2 and glial fibrillary acidic protein were very similar, indicating that reactive astrocytes express APG-2, which was confirmed by double immunofluorescence histochemistry. Colocalization of APG-2 and a neuronal marker NeuN in the neurons of the CA2 and CA3 subfields was also confirmed.

Control of transversal instabilities in reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Totz, Sonja; Löber, Jakob; Totz, Jan Frederik; Engel, Harald

2018-05-01

In two-dimensional reaction-diffusion systems, local curvature perturbations on traveling waves are typically damped out and vanish. However, if the inhibitor diffuses much faster than the activator, transversal instabilities can arise, leading from flat to folded, spatio-temporally modulated waves and to spreading spiral turbulence. Here, we propose a scheme to induce or inhibit these instabilities via a spatio-temporal feedback loop. In a piecewise-linear version of the FitzHugh–Nagumo model, transversal instabilities and spiral turbulence in the uncontrolled system are shown to be suppressed in the presence of control, thereby stabilizing plane wave propagation. Conversely, in numerical simulations with the modified Oregonator model for the photosensitive Belousov–Zhabotinsky reaction, which does not exhibit transversal instabilities on its own, we demonstrate the feasibility of inducing transversal instabilities and study the emerging wave patterns in a well-controlled manner.

"Core Knowledges": A Dissociation between Spatiotemporal Knowledge and Contact-Mechanics in a Non-Human Primate?

ERIC Educational Resources Information Center

Santos, Laurie R.

2004-01-01

Human toddlers demonstrate striking failures when searching for hidden objects that interact with other objects, yet successfully locate hidden objects that do not undergo mechanical interactions. This pattern hints at a developmental dissociation between contact-mechanical and spatiotemporal knowledge. Recent studies suggest that adult non-human…

Spatiotemporal evolution of the chlorophyll a trend in the North Atlantic Ocean.

PubMed

Zhang, Min; Zhang, Yuanling; Shu, Qi; Zhao, Chang; Wang, Gang; Wu, Zhaohua; Qiao, Fangli

2018-01-15

Analyses of the chlorophyll a concentration (chla) from satellite ocean color products have suggested the decadal-scale variability of chla linked to the climate change. The decadal-scale variability in chla is both spatially and temporally non-uniform. We need to understand the spatiotemporal evolution of chla in decadal or multi-decadal timescales to better evaluate its linkage to climate variability. Here, the spatiotemporal evolution of the chla trend in the North Atlantic Ocean for the period 1997-2016 is analyzed using the multidimensional ensemble empirical mode decomposition method. We find that this variable trend signal of chla shows a dipole pattern between the subpolar gyre and along the Gulf Stream path, and propagation along the opposite direction of the North Atlantic Current. This propagation signal has an overlapping variability of approximately twenty years. Our findings suggest that the spatiotemporal evolution of chla during the two most recent decades is part of the multidecadal variations and possibly regulated by the changes of Atlantic Meridional Overturning Circulation, whereas the mechanisms of such evolution patterns still need to be explored. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatio-Temporal Pattern Mining on Trajectory Data Using Arm

NASA Astrophysics Data System (ADS)

Khoshahval, S.; Farnaghi, M.; Taleai, M.

2017-09-01

Preliminary mobile was considered to be a device to make human connections easier. But today the consumption of this device has been evolved to a platform for gaming, web surfing and GPS-enabled application capabilities. Embedding GPS in handheld devices, altered them to significant trajectory data gathering facilities. Raw GPS trajectory data is a series of points which contains hidden information. For revealing hidden information in traces, trajectory data analysis is needed. One of the most beneficial concealed information in trajectory data is user activity patterns. In each pattern, there are multiple stops and moves which identifies users visited places and tasks. This paper proposes an approach to discover user daily activity patterns from GPS trajectories using association rules. Finding user patterns needs extraction of user's visited places from stops and moves of GPS trajectories. In order to locate stops and moves, we have implemented a place recognition algorithm. After extraction of visited points an advanced association rule mining algorithm, called Apriori was used to extract user activity patterns. This study outlined that there are useful patterns in each trajectory that can be emerged from raw GPS data using association rule mining techniques in order to find out about multiple users' behaviour in a system and can be utilized in various location-based applications.

Parallel and patterned optogenetic manipulation of neurons in the brain slice using a DMD-based projector.

PubMed

Sakai, Seiichiro; Ueno, Kenichi; Ishizuka, Toru; Yawo, Hiromu

2013-01-01

Optical manipulation technologies greatly advanced the understanding of the neuronal network and its dysfunctions. To achieve patterned and parallel optical switching, we developed a microscopic illumination system using a commercial DMD-based projector and a software program. The spatiotemporal patterning of the system was evaluated using acute slices of the hippocampus. The neural activity was optically manipulated, positively by the combination of channelrhodopsin-2 (ChR2) and blue light, and negatively by the combination of archaerhodopsin-T (ArchT) and green light. It is suggested that our projector-managing optical system (PMOS) would effectively facilitate the optogenetic analyses of neurons and their circuits. Copyright © 2012 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Tracking brain states under general anesthesia by using global coherence analysis.

PubMed

Cimenser, Aylin; Purdon, Patrick L; Pierce, Eric T; Walsh, John L; Salazar-Gomez, Andres F; Harrell, Priscilla G; Tavares-Stoeckel, Casie; Habeeb, Kathleen; Brown, Emery N

2011-05-24

Time and frequency domain analyses of scalp EEG recordings are widely used to track changes in brain states under general anesthesia. Although these analyses have suggested that different spatial patterns are associated with changes in the state of general anesthesia, the extent to which these patterns are spatially coordinated has not been systematically characterized. Global coherence, the ratio of the largest eigenvalue to the sum of the eigenvalues of the cross-spectral matrix at a given frequency and time, has been used to analyze the spatiotemporal dynamics of multivariate time-series. Using 64-lead EEG recorded from human subjects receiving computer-controlled infusions of the anesthetic propofol, we used surface Laplacian referencing combined with spectral and global coherence analyses to track the spatiotemporal dynamics of the brain's anesthetic state. During unconsciousness the spectrograms in the frontal leads showed increasing α (8-12 Hz) and δ power (0-4 Hz) and in the occipital leads δ power greater than α power. The global coherence detected strong coordinated α activity in the occipital leads in the awake state that shifted to the frontal leads during unconsciousness. It revealed a lack of coordinated δ activity during both the awake and unconscious states. Although strong frontal power during general anesthesia-induced unconsciousness--termed anteriorization--is well known, its possible association with strong α range global coherence suggests highly coordinated spatial activity. Our findings suggest that combined spectral and global coherence analyses may offer a new approach to tracking brain states under general anesthesia.

Active modulation of laser coded systems using near infrared video projection system based on digital micromirror device (DMD)

NASA Astrophysics Data System (ADS)

Khalifa, Aly A.; Aly, Hussein A.; El-Sherif, Ashraf F.

2016-02-01

Near infrared (NIR) dynamic scene projection systems are used to perform hardware in-the-loop (HWIL) testing of a unit under test operating in the NIR band. The common and complex requirement of a class of these units is a dynamic scene that is spatio-temporal variant. In this paper we apply and investigate active external modulation of NIR laser in different ranges of temporal frequencies. We use digital micromirror devices (DMDs) integrated as the core of a NIR projection system to generate these dynamic scenes. We deploy the spatial pattern to the DMD controller to simultaneously yield the required amplitude by pulse width modulation (PWM) of the mirror elements as well as the spatio-temporal pattern. Desired modulation and coding of high stable, high power visible (Red laser at 640 nm) and NIR (Diode laser at 976 nm) using the combination of different optical masks based on DMD were achieved. These spatial versatile active coding strategies for both low and high frequencies in the range of kHz for irradiance of different targets were generated by our system and recorded using VIS-NIR fast cameras. The temporally-modulated laser pulse traces were measured using array of fast response photodetectors. Finally using a high resolution spectrometer, we evaluated the NIR dynamic scene projection system response in terms of preserving the wavelength and band spread of the NIR source after projection.

Quantitative assessment of the effects of 6 months of adapted physical activity on gait in people with multiple sclerosis: a randomized controlled trial.

PubMed

Pau, Massimiliano; Corona, Federica; Coghe, Giancarlo; Marongiu, Elisabetta; Loi, Andrea; Crisafulli, Antonio; Concu, Alberto; Galli, Manuela; Marrosu, Maria Giovanna; Cocco, Eleonora

2018-01-01

The purpose of this study is to quantitatively assess the effect of 6 months of supervised adapted physical activity (APA i.e. physical activity designed for people with special needs) on spatio-temporal and kinematic parameters of gait in persons with Multiple Sclerosis (pwMS). Twenty-two pwMS with Expanded Disability Status Scale scores ranging from 1.5 to 5.5 were randomly assigned either to the intervention group (APA, n = 11) or the control group (CG, n = 11). The former underwent 6 months of APA consisting of 3 weekly 60-min sessions of aerobic and strength training, while CG participants were engaged in no structured PA program. Gait patterns were analyzed before and after the training using three-dimensional gait analysis by calculating spatio-temporal parameters and concise indexes of gait kinematics (Gait Profile Score - GPS and Gait Variable Score - GVS) as well as dynamic Range of Motion (ROM) of hip, knee, and ankle joints. The training originated significant improvements in stride length, gait speed and cadence in the APA group, while GPS and GVS scores remained practically unchanged. A trend of improvement was also observed as regard the dynamic ROM of hip, knee, and ankle joints. No significant changes were observed in the CG for any of the parameters considered. The quantitative analysis of gait supplied mixed evidence about the actual impact of 6 months of APA on pwMS. Although some improvements have been observed, the substantial constancy of kinematic patterns of gait suggests that the full transferability of the administered training on the ambulation function may require more specific exercises. Implications for rehabilitation Adapted Physical Activity (APA) is effective in improving spatio-temporal parameters of gait, but not kinematics, in people with multiple sclerosis. Dynamic range of motion during gait is increased after APA. The full transferability of APA on the ambulation function may require specific exercises rather than generic lower limbs strength/flexibility training.

Spatio-temporal pattern analysis for evaluation of the spread of human infections with avian influenza A(H7N9) virus in China, 2013-2014.

PubMed

Dong, Wen; Yang, Kun; Xu, Quanli; Liu, Lin; Chen, Juan

2017-10-24

A large number (n = 460) of A(H7N9) human infections have been reported in China from March 2013 through December 2014, and H7N9 outbreaks in humans became an emerging issue for China health, which have caused numerous disease outbreaks in domestic poultry and wild bird populations, and threatened human health severely. The aims of this study were to investigate the directional trend of the epidemic and to identify the significant presence of spatial-temporal clustering of influenza A(H7N9) human cases between March 2013 and December 2014. Three distinct epidemic phases of A(H7N9) human infections were identified in this study. In each phase, standard deviational ellipse analysis was conducted to examine the directional trend of disease spreading, and retrospective space-time permutation scan statistic was then used to identify the spatio-temporal cluster patterns of H7N9 outbreaks in humans. The ever-changing location and the increasing size of the three identified standard deviational ellipses showed that the epidemic moved from east to southeast coast, and hence to some central regions, with a future epidemiological trend of continue dispersing to more central regions of China, and a few new human cases might also appear in parts of the western China. Furthermore, A(H7N9) human infections were clustering in space and time in the first two phases with five significant spatio-temporal clusters (p < 0.05), but there was no significant cluster identified in phase III. There was a new epidemiologic pattern that the decrease in significant spatio-temporal cluster of A(H7N9) human infections was accompanied with an obvious spatial expansion of the outbreaks during the study period, and identification of the spatio-temporal patterns of the epidemic can provide valuable insights for better understanding the spreading dynamics of the disease in China.

Annotating spatio-temporal datasets for meaningful analysis in the Web

NASA Astrophysics Data System (ADS)

Stasch, Christoph; Pebesma, Edzer; Scheider, Simon

2014-05-01

More and more environmental datasets that vary in space and time are available in the Web. This comes along with an advantage of using the data for other purposes than originally foreseen, but also with the danger that users may apply inappropriate analysis procedures due to lack of important assumptions made during the data collection process. In order to guide towards a meaningful (statistical) analysis of spatio-temporal datasets available in the Web, we have developed a Higher-Order-Logic formalism that captures some relevant assumptions in our previous work [1]. It allows to proof on meaningful spatial prediction and aggregation in a semi-automated fashion. In this poster presentation, we will present a concept for annotating spatio-temporal datasets available in the Web with concepts defined in our formalism. Therefore, we have defined a subset of the formalism as a Web Ontology Language (OWL) pattern. It allows capturing the distinction between the different spatio-temporal variable types, i.e. point patterns, fields, lattices and trajectories, that in turn determine whether a particular dataset can be interpolated or aggregated in a meaningful way using a certain procedure. The actual annotations that link spatio-temporal datasets with the concepts in the ontology pattern are provided as Linked Data. In order to allow data producers to add the annotations to their datasets, we have implemented a Web portal that uses a triple store at the backend to store the annotations and to make them available in the Linked Data cloud. Furthermore, we have implemented functions in the statistical environment R to retrieve the RDF annotations and, based on these annotations, to support a stronger typing of spatio-temporal datatypes guiding towards a meaningful analysis in R. [1] Stasch, C., Scheider, S., Pebesma, E., Kuhn, W. (2014): "Meaningful spatial prediction and aggregation", Environmental Modelling & Software, 51, 149-165.

Identifying food deserts and swamps based on relative healthy food access: a spatio-temporal Bayesian approach.

PubMed

Luan, Hui; Law, Jane; Quick, Matthew

2015-12-30

Obesity and other adverse health outcomes are influenced by individual- and neighbourhood-scale risk factors, including the food environment. At the small-area scale, past research has analysed spatial patterns of food environments for one time period, overlooking how food environments change over time. Further, past research has infrequently analysed relative healthy food access (RHFA), a measure that is more representative of food purchasing and consumption behaviours than absolute outlet density. This research applies a Bayesian hierarchical model to analyse the spatio-temporal patterns of RHFA in the Region of Waterloo, Canada, from 2011 to 2014 at the small-area level. RHFA is calculated as the proportion of healthy food outlets (healthy outlets/healthy + unhealthy outlets) within 4-km from each small-area. This model measures spatial autocorrelation of RHFA, temporal trend of RHFA for the study region, and spatio-temporal trends of RHFA for small-areas. For the study region, a significant decreasing trend in RHFA is observed (-0.024), suggesting that food swamps have become more prevalent during the study period. For small-areas, significant decreasing temporal trends in RHFA were observed for all small-areas. Specific small-areas located in south Waterloo, north Kitchener, and southeast Cambridge exhibited the steepest decreasing spatio-temporal trends and are classified as spatio-temporal food swamps. This research demonstrates a Bayesian spatio-temporal modelling approach to analyse RHFA at the small-area scale. Results suggest that food swamps are more prevalent than food deserts in the Region of Waterloo. Analysing spatio-temporal trends of RHFA improves understanding of local food environment, highlighting specific small-areas where policies should be targeted to increase RHFA and reduce risk factors of adverse health outcomes such as obesity.

Spatiotemporal patterns of ERP based on combined ICA-LORETA analysis

NASA Astrophysics Data System (ADS)

Zhang, Jiacai; Guo, Taomei; Xu, Yaqin; Zhao, Xiaojie; Yao, Li

2007-03-01

In contrast to the FMRI methods widely used up to now, this method try to understand more profoundly how the brain systems work under sentence processing task map accurately the spatiotemporal patterns of activity of the large neuronal populations in the human brain from the analysis of ERP data recorded on the brain scalp. In this study, an event-related brain potential (ERP) paradigm to record the on-line responses to the processing of sentences is chosen as an example. In order to give attention to both utilizing the ERPs' temporal resolution of milliseconds and overcoming the insensibility of cerebral location ERP sources, we separate these sources in space and time based on a combined method of independent component analysis (ICA) and low-resolution tomography (LORETA) algorithms. ICA blindly separate the input ERP data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. And then the spatial maps associated with each ICA component are analyzed, with use of LORETA to uniquely locate its cerebral sources throughout the full brain according to the assumption that neighboring neurons are simultaneously and synchronously activated. Our results show that the cerebral computation mechanism underlies content words reading is mediated by the orchestrated activity of several spatially distributed brain sources located in the temporal, frontal, and parietal areas, and activate at distinct time intervals and are grouped into different statistically independent components. Thus ICA-LORETA analysis provides an encouraging and effective method to study brain dynamics from ERP.

Subcellular, Cellular and Circuit Mechanisms underlying Classical Conditioning in Hermissenda crassicornis

PubMed Central

2009-01-01

A breakthrough for studying the neuronal basis of learning emerged when invertebrates with simple nervous systems, such as the sea slug Hermissenda crassicornis, were shown to exhibit classical conditioning. Hermissenda learns to associate light with turbulence: prior to learning, naive animals move toward light (phototaxis) and contract their foot in response to turbulence; after learning, conditioned animals delay phototaxis in response to light. The photoreceptors of the eye, which receive monosynaptic inputs from statocyst hair cells, are both sensory neurons and the first site of sensory convergence. The memory of light associated with turbulence is stored as changes in intrinsic and synaptic currents in these photoreceptors. The subcellular mechanisms producing these changes include activation of protein kinase C and MAP kinase, which act as coincidence detectors because they are activated by convergent signaling pathways. Pathways of interneurons and motorneurons, where additional changes in excitability and synaptic connections are found, contribute to delayed phototaxis. Bursting activity recorded at several points suggest the existence of small networks that produce complex spatio-temporal firing patterns. Thus, the change in behavior may be produced by a non-linear transformation of spatio-temporal firing patterns caused by plasticity of synaptic and intrinsic channels. The change in currents and the activation of PKC and MAPK produced by associative learning are similar to that observed in hippocampal and cerebellar neurons after rabbit classical conditioning, suggesting that these represent general mechanisms of memory storage. Thus, the knowledge gained from further study of Hermissenda will continue to illuminate mechanisms of mammalian learning. PMID:16437555

Slow Spatial Recruitment of Neocortex during Secondarily Generalized Seizures and Its Relation to Surgical Outcome

PubMed Central

Martinet, Louis-Emmanuel; Ahmed, Omar J.; Lepage, Kyle Q.; Cash, Sydney S.

2015-01-01

Understanding the spatiotemporal dynamics of brain activity is crucial for inferring the underlying synaptic and nonsynaptic mechanisms of brain dysfunction. Focal seizures with secondary generalization are traditionally considered to begin in a limited spatial region and spread to connected areas, which can include both pathological and normal brain tissue. The mechanisms underlying this spread are important to our understanding of seizures and to improve therapies for surgical intervention. Here we study the properties of seizure recruitment—how electrical brain activity transitions to large voltage fluctuations characteristic of spike-and-wave seizures. We do so using invasive subdural electrode arrays from a population of 16 patients with pharmacoresistant epilepsy. We find an average delay of ∼30 s for a broad area of cortex (8 × 8 cm) to be recruited into the seizure, at an estimated speed of ∼4 mm/s. The spatiotemporal characteristics of recruitment reveal two categories of patients: one in which seizure recruitment of neighboring cortical regions follows a spatially organized pattern consistent from seizure to seizure, and a second group without consistent spatial organization of activity during recruitment. The consistent, organized recruitment correlates with a more regular, compared with small-world, connectivity pattern in simulation and successful surgical treatment of epilepsy. We propose that an improved understanding of how the seizure recruits brain regions into large amplitude voltage fluctuations provides novel information to improve surgical treatment of epilepsy and highlights the slow spread of massive local activity across a vast extent of cortex during seizure. PMID:26109670

Activity induces traveling waves, vortices and spatiotemporal chaos in a model actomyosin layer

NASA Astrophysics Data System (ADS)

Ramaswamy, Rajesh; Jülicher, Frank

2016-02-01

Inspired by the actomyosin cortex in biological cells, we investigate the spatiotemporal dynamics of a model describing a contractile active polar fluid sandwiched between two external media. The external media impose frictional forces at the interface with the active fluid. The fluid is driven by a spatially-homogeneous activity measuring the strength of the active stress that is generated by processes consuming a chemical fuel. We observe that as the activity is increased over two orders of magnitude the active polar fluid first shows spontaneous flow transition followed by transition to oscillatory dynamics with traveling waves and traveling vortices in the flow field. In the flow-tumbling regime, the active polar fluid also shows transition to spatiotemporal chaos at sufficiently large activities. These results demonstrate that level of activity alone can be used to tune the operating point of actomyosin layers with qualitatively different spatiotemporal dynamics.

Monitoring the Spatiotemporal Activities of miRNAs in Small Animal Models Using Molecular Imaging Modalities

PubMed Central

Baril, Patrick; Ezzine, Safia; Pichon, Chantal

2015-01-01

MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression by binding mRNA targets via sequence complementary inducing translational repression and/or mRNA degradation. A current challenge in the field of miRNA biology is to understand the functionality of miRNAs under physiopathological conditions. Recent evidence indicates that miRNA expression is more complex than simple regulation at the transcriptional level. MiRNAs undergo complex post-transcriptional regulations such miRNA processing, editing, accumulation and re-cycling within P-bodies. They are dynamically regulated and have a well-orchestrated spatiotemporal localization pattern. Real-time and spatio-temporal analyses of miRNA expression are difficult to evaluate and often underestimated. Therefore, important information connecting miRNA expression and function can be lost. Conventional miRNA profiling methods such as Northern blot, real-time PCR, microarray, in situ hybridization and deep sequencing continue to contribute to our knowledge of miRNA biology. However, these methods can seldom shed light on the spatiotemporal organization and function of miRNAs in real-time. Non-invasive molecular imaging methods have the potential to address these issues and are thus attracting increasing attention. This paper reviews the state-of-the-art of methods used to detect miRNAs and discusses their contribution in the emerging field of miRNA biology and therapy. PMID:25749473

Monitoring the spatiotemporal activities of miRNAs in small animal models using molecular imaging modalities.

PubMed

Baril, Patrick; Ezzine, Safia; Pichon, Chantal

2015-03-04

MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression by binding mRNA targets via sequence complementary inducing translational repression and/or mRNA degradation. A current challenge in the field of miRNA biology is to understand the functionality of miRNAs under physiopathological conditions. Recent evidence indicates that miRNA expression is more complex than simple regulation at the transcriptional level. MiRNAs undergo complex post-transcriptional regulations such miRNA processing, editing, accumulation and re-cycling within P-bodies. They are dynamically regulated and have a well-orchestrated spatiotemporal localization pattern. Real-time and spatio-temporal analyses of miRNA expression are difficult to evaluate and often underestimated. Therefore, important information connecting miRNA expression and function can be lost. Conventional miRNA profiling methods such as Northern blot, real-time PCR, microarray, in situ hybridization and deep sequencing continue to contribute to our knowledge of miRNA biology. However, these methods can seldom shed light on the spatiotemporal organization and function of miRNAs in real-time. Non-invasive molecular imaging methods have the potential to address these issues and are thus attracting increasing attention. This paper reviews the state-of-the-art of methods used to detect miRNAs and discusses their contribution in the emerging field of miRNA biology and therapy.

The pyrogeography of eastern boreal Canada from 1901 to 2012 simulated with the LPJ-LMfire model

NASA Astrophysics Data System (ADS)

Chaste, Emeline; Girardin, Martin P.; Kaplan, Jed O.; Portier, Jeanne; Bergeron, Yves; Hély, Christelle

2018-03-01

Wildland fires are the main natural disturbance shaping forest structure and composition in eastern boreal Canada. On average, more than 700 000 ha of forest burns annually and causes as much as CAD 2.9 million worth of damage. Although we know that occurrence of fires depends upon the coincidence of favourable conditions for fire ignition, propagation, and fuel availability, the interplay between these three drivers in shaping spatiotemporal patterns of fires in eastern Canada remains to be evaluated. The goal of this study was to reconstruct the spatiotemporal patterns of fire activity during the last century in eastern Canada's boreal forest as a function of changes in lightning ignition, climate, and vegetation. We addressed this objective using the dynamic global vegetation model LPJ-LMfire, which we parametrized for four plant functional types (PFTs) that correspond to the prevalent tree genera in eastern boreal Canada (Picea, Abies, Pinus, Populus). LPJ-LMfire was run with a monthly time step from 1901 to 2012 on a 10 km2 resolution grid covering the boreal forest from Manitoba to Newfoundland. Outputs of LPJ-LMfire were analyzed in terms of fire frequency, net primary productivity (NPP), and aboveground biomass. The predictive skills of LPJ-LMfire were examined by comparing our simulations of annual burn rates and biomass with independent data sets. The simulation adequately reproduced the latitudinal gradient in fire frequency in Manitoba and the longitudinal gradient from Manitoba towards southern Ontario, as well as the temporal patterns present in independent fire histories. However, the simulation led to the underestimation and overestimation of fire frequency at both the northern and southern limits of the boreal forest in Québec. The general pattern of simulated total tree biomass also agreed well with observations, with the notable exception of overestimated biomass at the northern treeline, mainly for PFT Picea. In these northern areas, the predictive ability of LPJ-LMfire is likely being affected by the low density of weather stations, which leads to underestimation of the strength of fire-weather interactions and, therefore, vegetation consumption during extreme fire years. Agreement between the spatiotemporal patterns of fire frequency and the observed data across a vast portion of the study area confirmed that fire therein is strongly ignition limited. A drier climate coupled with an increase in lightning frequency during the second half of the 20th century notably led to an increase in fire activity. Finally, our simulations highlighted the importance of both climate and fire in vegetation: despite an overarching CO2-induced enhancement of NPP in LPJ-LMfire, forest biomass was relatively stable because of the compensatory effects of increasing fire activity.

Spatio-temporal patterns of Barmah Forest virus disease in Queensland, Australia.

PubMed

Naish, Suchithra; Hu, Wenbiao; Mengersen, Kerrie; Tong, Shilu

2011-01-01

Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ(2) = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland.

Defining multiple, distinct, and shared spatiotemporal patterns of DNA replication and endoreduplication from 3D image analysis of developing maize (Zea mays L.) root tip nuclei.

PubMed

Bass, Hank W; Hoffman, Gregg G; Lee, Tae-Jin; Wear, Emily E; Joseph, Stacey R; Allen, George C; Hanley-Bowdoin, Linda; Thompson, William F

2015-11-01

Spatiotemporal patterns of DNA replication have been described for yeast and many types of cultured animal cells, frequently after cell cycle arrest to aid in synchronization. However, patterns of DNA replication in nuclei from plants or naturally developing organs remain largely uncharacterized. Here we report findings from 3D quantitative analysis of DNA replication and endoreduplication in nuclei from pulse-labeled developing maize root tips. In both early and middle S phase nuclei, flow-sorted on the basis of DNA content, replicative labeling was widely distributed across euchromatic regions of the nucleoplasm. We did not observe the perinuclear or perinucleolar replicative labeling patterns characteristic of middle S phase in mammals. Instead, the early versus middle S phase patterns in maize could be distinguished cytologically by correlating two quantitative, continuous variables, replicative labeling and DAPI staining. Early S nuclei exhibited widely distributed euchromatic labeling preferentially localized to regions with weak DAPI signals. Middle S nuclei also exhibited widely distributed euchromatic labeling, but the label was preferentially localized to regions with strong DAPI signals. Highly condensed heterochromatin, including knobs, replicated during late S phase as previously reported. Similar spatiotemporal replication patterns were observed for both mitotic and endocycling maize nuclei. These results revealed that maize euchromatin exists as an intermingled mixture of two components distinguished by their condensation state and replication timing. These different patterns might reflect a previously described genome organization pattern, with "gene islands" mostly replicating during early S phase followed by most of the intergenic repetitive regions replicating during middle S phase.

Harbour porpoise distribution can vary at small spatiotemporal scales in energetic habitats

NASA Astrophysics Data System (ADS)

Benjamins, Steven; van Geel, Nienke; Hastie, Gordon; Elliott, Jim; Wilson, Ben

2017-07-01

Marine habitat heterogeneity underpins species distribution and can be generated through interactions between physical and biological drivers at multiple spatiotemporal scales. Passive acoustic monitoring (PAM) is used worldwide to study potential impacts of marine industrial activities on cetaceans, but understanding of animals' site use at small spatiotemporal scales (<1 km, <1 day) remains limited. Small-scale variability in vocalising harbour porpoise (Phocoena phocoena) distribution within two Scottish marine renewable energy development (MRED) sites was investigated by deploying dense arrays of C-POD passive acoustic detectors at a wave energy test site (the European Marine Energy Centre [Billia Croo, Orkney]) and by a minor tidal-stream site (Scarba [Inner Hebrides]). Respective arrays consisted of 7 and 11 moorings containing two C-PODs each and were deployed for up to 55 days. Minimum inter-mooring distances varied between 300-600 m. All C-POD data were analysed at a temporal resolution of whole minutes, with each minute classified as 1 or 0 on the basis of presence/absence of porpoise click trains (Porpoise-Positive Minutes/PPMs). Porpoise detection rates were analysed using Generalised Additive Models (GAMs) with Generalised Estimation Equations (GEEs). Although there were many porpoise detections (wave test site: N=3,432; tidal-stream site: N=17,366), daily detection rates varied significantly within both arrays. Within the wave site array (<1 km diameter), average daily detection rates varied from 4.3 to 14.8 PPMs/day. Within the tidal-stream array (<2 km diameter), average daily detection rates varied from 10.3 to 49.7 PPMs/day. GAM-GEE model results for individual moorings within both arrays indicated linkages between porpoise presence and small-scale heterogeneity among different environmental covariates (e.g., tidal phase, time of day). Porpoise detection rates varied considerably but with coherent patterns between moorings only several hundred metres apart and within hours. These patterns presumably have ecological relevance. These results indicate that, in energetically active and heterogeneous areas, porpoises can display significant spatiotemporal variability in site use at scales of hundreds of metres and hours. Such variability will not be identified when using solitary moored PAM detectors (a common practice for site-based cetacean monitoring), but may be highly relevant for site-based impact assessments of MRED and other coastal developments. PAM arrays encompassing several detectors spread across a site therefore appear to be a more appropriate tool to study site-specific cetacean use of spatiotemporally heterogeneous habitat and assess the potential impacts of coastal and nearshore developments at small scales.

Routes to spatiotemporal chaos in Kerr optical frequency combs.

PubMed

Coillet, Aurélien; Chembo, Yanne K

2014-03-01

We investigate the various routes to spatiotemporal chaos in Kerr optical frequency combs, obtained through pumping an ultra-high Q-factor whispering-gallery mode resonator with a continuous-wave laser. The Lugiato-Lefever model is used to build bifurcation diagrams with regards to the parameters that are externally controllable, namely, the frequency and the power of the pumping laser. We show that the spatiotemporal chaos emerging from Turing patterns and solitons display distinctive dynamical features. Experimental spectra of chaotic Kerr combs are also presented for both cases, in excellent agreement with theoretical spectra.

Spatio-temporal Analysis for New York State SPARCS Data

PubMed Central

Chen, Xin; Wang, Yu; Schoenfeld, Elinor; Saltz, Mary; Saltz, Joel; Wang, Fusheng

2017-01-01

Increased accessibility of health data provides unique opportunities to discover spatio-temporal patterns of diseases. For example, New York State SPARCS (Statewide Planning and Research Cooperative System) data collects patient level detail on patient demographics, diagnoses, services, and charges for each hospital inpatient stay and outpatient visit. Such data also provides home addresses for each patient. This paper presents our preliminary work on spatial, temporal, and spatial-temporal analysis of disease patterns for New York State using SPARCS data. We analyzed spatial distribution patterns of typical diseases at ZIP code level. We performed temporal analysis of common diseases based on 12 years’ historical data. We then compared the spatial variations for diseases with different levels of clustering tendency, and studied the evolution history of such spatial patterns. Case studies based on asthma demonstrated that the discovered spatial clusters are consistent with prior studies. We visualized our spatial-temporal patterns as animations through videos. PMID:28815148

Two-dimensional wave patterns of spreading depolarization: Retracting, re-entrant, and stationary waves

NASA Astrophysics Data System (ADS)

Dahlem, Markus A.; Graf, Rudolf; Strong, Anthony J.; Dreier, Jens P.; Dahlem, Yuliya A.; Sieber, Michaela; Hanke, Wolfgang; Podoll, Klaus; Schöll, Eckehard

2010-06-01

We present spatio-temporal characteristics of spreading depolarizations (SD) in two experimental systems: retracting SD wave segments observed with intrinsic optical signals in chicken retina, and spontaneously occurring re-entrant SD waves that repeatedly spread across gyrencephalic feline cortex observed by laser speckle flowmetry. A mathematical framework of reaction-diffusion systems with augmented transmission capabilities is developed to explain the emergence and transitions between these patterns. Our prediction is that the observed patterns are reaction-diffusion patterns controlled and modulated by weak nonlocal coupling such as long-range, time-delayed, and global coupling. The described spatio-temporal characteristics of SD are of important clinical relevance under conditions of migraine and stroke. In stroke, the emergence of re-entrant SD waves is believed to worsen outcome. In migraine, retracting SD wave segments cause neurological symptoms and transitions to stationary SD wave patterns may cause persistent symptoms without evidence from noninvasive imaging of infarction.

Spatiotemporal patterns of paddy rice croplands in China and India from 2000 to 2015.

PubMed

Zhang, Geli; Xiao, Xiangming; Biradar, Chandrashekhar M; Dong, Jinwei; Qin, Yuanwei; Menarguez, Michael A; Zhou, Yuting; Zhang, Yao; Jin, Cui; Wang, Jie; Doughty, Russell B; Ding, Mingjun; Moore, Berrien

2017-02-01

Due to rapid population growth and urbanization, paddy rice agriculture is experiencing substantial changes in the spatiotemporal pattern of planting areas in the two most populous countries-China and India-where food security is always the primary concern. However, there is no spatially explicit and continuous rice-planting information in either country. This knowledge gap clearly hinders our ability to understand the effects of spatial paddy rice area dynamics on the environment, such as food and water security, climate change, and zoonotic infectious disease transmission. To resolve this problem, we first generated annual maps of paddy rice planting areas for both countries from 2000 to 2015, which are derived from time series Moderate Resolution Imaging Spectroradiometer (MODIS) data and the phenology- and pixel-based rice mapping platform (RICE-MODIS), and analyzed the spatiotemporal pattern of paddy rice dynamics in the two countries. We found that China experienced a general decrease in paddy rice planting area with a rate of 0.72 million (m) ha/yr from 2000 to 2015, while a significant increase at a rate of 0.27mha/yr for the same time period happened in India. The spatial pattern of paddy rice agriculture in China shifted northeastward significantly, due to simultaneous expansions in paddy rice planting areas in northeastern China and contractions in southern China. India showed an expansion of paddy rice areas across the entire country, particularly in the northwestern region of the Indo-Gangetic Plain located in north India and the central and south plateau of India. In general, there has been a northwesterly shift in the spatial pattern of paddy rice agriculture in India. These changes in the spatiotemporal patterns of paddy rice planting area have raised new concerns on how the shift may affect national food security and environmental issues relevant to water, climate, and biodiversity. Copyright © 2016 Elsevier B.V. All rights reserved.

Spatio-temporal patterns in land use and management affecting surface runoff response of agricultural catchments - a review

NASA Astrophysics Data System (ADS)

Fiener, P.; Auerswald, K.; van Oost, K.

2009-04-01

In many landscapes, land use creates a complex pattern in addition to the patterns resulting from soil, topography and rain. Despite the static layout of fields, a spatio-temporally highly variable situation regarding the surface runoff and erosion processes results from the asynchronous seasonal variation associated with different land uses. While the behaviour of individual land-uses and their seasonal variation is analyzed in many studies, the spatio-temporal interaction related to this pattern is rarely studied despite its crucial influence on hydrological and geomorphic response of catchments. The difficulty in studying such interactions mainly results from the fact that it is impossible to set up a replicated experiment on the landscape scale. The purpose of this review is to present the advances made thus far in quantifying the effects of patchiness of land use and management on surface runoff response in agricultural catchments. We will focus on the effects of spatio-temporal patterns in land use patches on hydraulic connectivity between patches and within catchments. This will include the temporal patterns in land management affecting infiltration, surface roughness and hence runoff concentration within single fields or land use patches insofar as these effects must be known to evaluate the combined effect of patch behaviour in space and time on catchment connectivity and surface runoff. Surface runoff effects of patchiness and connectivity between patches or within a catchment, can either be addressed by modelling studies or by comprehensive catchment field measurements, e.g. paired-watershed experiments or landscape scale studies on different scales. This limits our review to studies at the scale of small catchments < 10 km², where the time constant of the network (i.e. travel time through it) is smaller than the infiltration phase. Despite this limitation, these small catchments are important as they constitute 2/3 of the total surface of large water drainage networks.

Virtual Active Touch Using Randomly Patterned Intracortical Microstimulation

PubMed Central

O’Doherty, Joseph E.; Lebedev, Mikhail A.; Li, Zheng; Nicolelis, Miguel A.L.

2012-01-01

Intracortical microstimulation (ICMS) has promise as a means for delivering somatosensory feedback in neuroprosthetic systems. Various tactile sensations could be encoded by temporal, spatial, or spatiotemporal patterns of ICMS. However, the applicability of temporal patterns of ICMS to artificial tactile sensation during active exploration is unknown, as is the minimum discriminable difference between temporally modulated ICMS patterns. We trained rhesus monkeys in an active exploration task in which they discriminated periodic pulse-trains of ICMS (200 Hz bursts at a 10 Hz secondary frequency) from pulse trains with the same average pulse rate, but distorted periodicity (200 Hz bursts at a variable instantaneous secondary frequency). The statistics of the aperiodic pulse trains were drawn from a gamma distribution with mean inter-burst intervals equal to those of the periodic pulse trains. The monkeys distinguished periodic pulse trains from aperiodic pulse trains with coefficients of variation 0.25 or greater. Reconstruction of movement kinematics, extracted from the activity of neuronal populations recorded in the sensorimotor cortex concurrent with the delivery of ICMS feedback, improved when the recording intervals affected by ICMS artifacts were removed from analysis. These results add to the growing evidence that temporally patterned ICMS can be used to simulate a tactile sense for neuroprosthetic devices. PMID:22207642

Spatiotemporal changes of CVOC concentrations in karst aquifers: analysis of three decades of data from Puerto Rico

PubMed Central

Yu, Xue; Ghasemizadeh, Reza; Padilla, Ingrid; Irizarry, Celys; Kaeli, David; Alshawabkeh, Akram

2014-01-01

We studied the spatial and temporal distribution patterns of Chlorinated Volatile Organic Compounds (CVOCs) in the karst aquifers in northern Puerto Rico (1982-2013). Seventeen CVOCs were widely detected across the study area, with the most detected and persistent contaminated CVOCs including trichloroethylene (TCE), tetrachloroethylene (PCE), carbon tetrachloride (CT), chloroform (TCM), and methylene chloride (DCM). Historically, 471 (76%) and 319 (52%) of the 615 sampling sites have CVOC concentrations above the detection limit and maximum contamination level (MCL), respectively. The spatiotemporal patterns of the CVOC concentrations showed two clusters of contaminated areas, one near the Superfund site “Upjohn” and another near “Vega Alta Public Supply Wells.” Despite a decreasing trend in concentrations, there is a general northward movement and spreading of contaminants even beyond the extent of known sources of the Superfund and landfill sites. Our analyses suggest that, besides the source conditions, karst characteristics (high heterogeneity, complex hydraulic and biochemical environment) are linked to the long-term spatiotemporal patterns of CVOCs in groundwater. PMID:25522355

Geovisualization of Local and Regional Migration Using Web-mined Demographics

NASA Astrophysics Data System (ADS)

Schuermann, R. T.; Chow, T. E.

2014-11-01

The intent of this research was to augment and facilitate analyses, which gauges the feasibility of web-mined demographics to study spatio-temporal dynamics of migration. As a case study, we explored the spatio-temporal dynamics of Vietnamese Americans (VA) in Texas through geovisualization of mined demographic microdata from the World Wide Web. Based on string matching across all demographic attributes, including full name, address, date of birth, age and phone number, multiple records of the same entity (i.e. person) over time were resolved and reconciled into a database. Migration trajectories were geovisualized through animated sprites by connecting the different addresses associated with the same person and segmenting the trajectory into small fragments. Intra-metropolitan migration patterns appeared at the local scale within many metropolitan areas. At the scale of metropolitan area, varying degrees of immigration and emigration manifest different types of migration clusters. This paper presents a methodology incorporating GIS methods and cartographic design to produce geovisualization animation, enabling the cognitive identification of migration patterns at multiple scales. Identification of spatio-temporal patterns often stimulates further research to better understand the phenomenon and enhance subsequent modeling.

Spatio-Temporal Pattern Analysis for Regional Climate Change Using Mathematical Morphology

NASA Astrophysics Data System (ADS)

Das, M.; Ghosh, S. K.

2015-07-01

Of late, significant changes in climate with their grave consequences have posed great challenges on humankind. Thus, the detection and assessment of climatic changes on a regional scale is gaining importance, since it helps to adopt adequate mitigation and adaptation measures. In this paper, we have presented a novel approach for detecting spatio-temporal pattern of regional climate change by exploiting the theory of mathematical morphology. At first, the various climatic zones in the region have been identified by using multifractal cross-correlation analysis (MF-DXA) of different climate variables of interest. Then, the directional granulometry with four different structuring elements has been studied to detect the temporal changes in spatial distribution of the identified climatic zones in the region and further insights have been drawn with respect to morphological uncertainty index and Hurst exponent. The approach has been evaluated with the daily time series data of land surface temperature (LST) and precipitation rate, collected from Microsoft Research - Fetch Climate Explorer, to analyze the spatio-temporal climatic pattern-change in the Eastern and North-Eastern regions of India throughout four quarters of the 20th century.

Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2016-10-02

Here, we present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) tomore » compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. Lastly, we present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.« less

Upper-hybrid wave-driven Alfvenic turbulence in magnetized dusty plasmas

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

Misra, A. P.; Banerjee, S.

The nonlinear dynamics of coupled electrostatic upper-hybrid (UH) and Alfven waves (AWs) is revisited in a magnetized electron-ion plasma with charged dust impurities. A pair of nonlinear equations that describe the interaction of UH wave envelopes (including the relativistic electron mass increase) and the density as well as the compressional magnetic field perturbations associated with the AWs are solved numerically to show that many coherent solitary patterns can be excited and saturated due to modulational instability of unstable UH waves. The evolution of these solitary patterns is also shown to appear in the states of spatiotemporal coherence, temporal as wellmore » as spatiotemporal chaos, due to collision and fusion among the patterns in stochastic motion. Furthermore, these spatiotemporal features are demonstrated by the analysis of wavelet power spectra. It is found that a redistribution of wave energy takes place to higher harmonic modes with small wavelengths, which, in turn, results in the onset of Alfvenic turbulence in dusty magnetoplasmas. Such a scenario can occur in the vicinity of Saturn's magnetosphere as many electrostatic solitary structures have been observed there by the Cassini spacecraft.« less

Spatio-temporal cluster detection of chickenpox in Valencia, Spain in the period 2008-2012.

PubMed

Iftimi, Adina; Martínez-Ruiz, Francisco; Míguez Santiyán, Ana; Montes, Francisco

2015-05-18

Chickenpox is a highly contagious airborne disease caused by Varicella zoster, which affects nearly all non-immune children worldwide with an annual incidence estimated at 80-90 million cases. To analyze the spatiotemporal pattern of the chickenpox incidence in the city of Valencia, Spain two complementary statistical approaches were used. First, we evaluated the existence of clusters and spatio-temporal interaction; secondly, we used this information to find the locations of the spatio-temporal clusters via the space-time permutation model. The first method used detects any aggregation in our data but does not provide the spatial and temporal information. The second method gives the locations, areas and time-frame for the spatio-temporal clusters. An overall decreasing time trend, a pronounced 12-monthly periodicity and two complementary periods were observed. Several areas with high incidence, surrounding the center of the city were identified. The existence of aggregation in time and space was observed, and a number of spatio-temporal clusters were located.

Comparison of Spatiotemporal Mapping Techniques for Enormous Etl and Exploitation Patterns

NASA Astrophysics Data System (ADS)

Deiotte, R.; La Valley, R.

2017-10-01

The need to extract, transform, and exploit enormous volumes of spatiotemporal data has exploded with the rise of social media, advanced military sensors, wearables, automotive tracking, etc. However, current methods of spatiotemporal encoding and exploitation simultaneously limit the use of that information and increase computing complexity. Current spatiotemporal encoding methods from Niemeyer and Usher rely on a Z-order space filling curve, a relative of Peano's 1890 space filling curve, for spatial hashing and interleaving temporal hashes to generate a spatiotemporal encoding. However, there exist other space-filling curves, and that provide different manifold coverings that could promote better hashing techniques for spatial data and have the potential to map spatiotemporal data without interleaving. The concatenation of Niemeyer's and Usher's techniques provide a highly efficient space-time index. However, other methods have advantages and disadvantages regarding computational cost, efficiency, and utility. This paper explores the several methods using a range of sizes of data sets from 1K to 10M observations and provides a comparison of the methods.

Spatiotemporal Heterogeneity Analysis of Hemorrhagic Fever with Renal Syndrome in China Using Geographically Weighted Regression Models

PubMed Central

Li, Shujuan; Ren, Hongyan; Hu, Wensheng; Lu, Liang; Xu, Xinliang; Zhuang, Dafang; Liu, Qiyong

2014-01-01

Hemorrhagic fever with renal syndrome (HFRS) is an important public health problem in China. The identification of the spatiotemporal pattern of HFRS will provide a foundation for the effective control of the disease. Based on the incidence of HFRS, as well as environmental factors, and social-economic factors of China from 2005–2012, this paper identified the spatiotemporal characteristics of HFRS distribution and the factors that impact this distribution. The results indicate that the spatial distribution of HFRS had a significant, positive spatial correlation. The spatiotemporal heterogeneity was affected by the temperature, precipitation, humidity, NDVI of January, NDVI of August for the previous year, land use, and elevation in 2005–2009. However, these factors did not explain the spatiotemporal heterogeneity of HFRS incidences in 2010–2012. Spatiotemporal heterogeneity of provincial HFRS incidences and its relation to environmental factors would provide valuable information for hygiene authorities to design and implement effective measures for the prevention and control of HFRS in China. PMID:25429681

Spatiotemporal Aeration and Lung Injury Patterns Are Influenced by the First Inflation Strategy at Birth.

PubMed

Tingay, David G; Rajapaksa, Anushi; Zonneveld, C Elroy; Black, Don; Perkins, Elizabeth J; Adler, Andy; Grychtol, Bartłomiej; Lavizzari, Anna; Frerichs, Inéz; Zahra, Valerie A; Davis, Peter G

2016-02-01

Ineffective aeration during the first inflations at birth creates regional aeration and ventilation defects, initiating injurious pathways. This study aimed to compare a sustained first inflation at birth or dynamic end-expiratory supported recruitment during tidal inflations against ventilation without intentional recruitment on gas exchange, lung mechanics, spatiotemporal regional aeration and tidal ventilation, and regional lung injury in preterm lambs. Lambs (127 ± 2 d gestation), instrumented at birth, were ventilated for 60 minutes from birth with either lung-protective positive pressure ventilation (control) or as per control after either an initial 30 seconds of 40 cm H2O sustained inflation (SI) or an initial stepwise end-expiratory pressure recruitment maneuver during tidal inflations (duration 180 s; open lung ventilation [OLV]). At study completion, molecular markers of lung injury were analyzed. The initial use of an OLV maneuver, but not SI, at birth resulted in improved lung compliance, oxygenation, end-expiratory lung volume, and reduced ventilatory needs compared with control, persisting throughout the study. These changes were due to more uniform inter- and intrasubject gravity-dependent spatiotemporal patterns of aeration (measured using electrical impedance tomography). Spatial distribution of tidal ventilation was more stable after either recruitment maneuver. All strategies caused regional lung injury patterns that mirrored associated regional volume states. Irrespective of strategy, spatiotemporal volume loss was consistently associated with up-regulation of early growth response-1 expression. Our results show that mechanical and molecular consequences of lung aeration at birth are not simply related to rapidity of fluid clearance; they are also related to spatiotemporal pressure-volume interactions within the lung during inflation and deflation.

Use of Numerical Groundwater Model and Analytical Empirical Orthogonal Function for Calibrating Spatiotemporal pattern of Pumpage, Recharge and Parameter

NASA Astrophysics Data System (ADS)

Huang, C. L.; Hsu, N. S.; Hsu, F. C.; Liu, H. J.

2016-12-01

This study develops a novel methodology for the spatiotemporal groundwater calibration of mega-quantitative recharge and parameters by coupling a specialized numerical model and analytical empirical orthogonal function (EOF). The actual spatiotemporal patterns of groundwater pumpage are estimated by an originally developed back propagation neural network-based response matrix with the electrical consumption analysis. The spatiotemporal patterns of the recharge from surface water and hydrogeological parameters (i.e. horizontal hydraulic conductivity and vertical leakance) are calibrated by EOF with the simulated error hydrograph of groundwater storage, in order to qualify the multiple error sources and quantify the revised volume. The objective function of the optimization model is minimizing the root mean square error of the simulated storage error percentage across multiple aquifers, meanwhile subject to mass balance of groundwater budget and the governing equation in transient state. The established method was applied on the groundwater system of Chou-Shui River Alluvial Fan. The simulated period is from January 2012 to December 2014. The total numbers of hydraulic conductivity, vertical leakance and recharge from surface water among four aquifers are 126, 96 and 1080, respectively. Results showed that the RMSE during the calibration process was decreased dramatically and can quickly converse within 6th iteration, because of efficient filtration of the transmission induced by the estimated error and recharge across the boundary. Moreover, the average simulated error percentage according to groundwater level corresponding to the calibrated budget variables and parameters of aquifer one is as small as 0.11%. It represent that the developed methodology not only can effectively detect the flow tendency and error source in all aquifers to achieve accurately spatiotemporal calibration, but also can capture the peak and fluctuation of groundwater level in shallow aquifer.

Optical dissection of odor information processing in vivo using GCaMPs expressed in specified cell types of the olfactory bulb

PubMed Central

Wachowiak, Matt; Economo, Michael N.; Díaz-Quesada, Marta; Brunert, Daniela; Wesson, Daniel W.; White, John. A.; Rothermel, Markus

2013-01-01

Understanding central processing requires precise monitoring of neural activity across populations of identified neurons in the intact brain. Here we used recently-optimized variants of the genetically-encoded calcium sensor GCaMP (GCaMP3 and GCaMPG5G) to image activity among genetically- and anatomically-defined neuronal populations in the olfactory bulb (OB), including two types of GABA-ergic interneurons (periglomerular (PG) and short axon (SA) cells) and OB output neurons (mitral/tufted (MT) cells) projecting to piriform cortex. We first established that changes in neuronal spiking can be accurately related to GCaMP fluorescence changes via a simple quantitative relationship over a large dynamic range. We next used in vivo two-photon imaging from individual neurons and epifluorescence signals reflecting population-level activity to investigate the spatiotemporal representation of odorants across these neuron types in anesthetized and awake mice. Under anesthesia, individual PG and SA cells showed temporally simple responses and little spontaneous activity, while MT cells were spontaneously active and showed diverse temporal responses. At the population level, response patterns of PG, SA and MT cells were surprisingly similar to those imaged from sensory inputs, with shared odorant-specific topography across the dorsal OB and inhalation-coupled temporal dynamics. During wakefulness, PG and SA cell responses increased in magnitude but remained temporally simple while those of MT cells changed to complex spatiotemporal patterns reflecting restricted excitation and widespread inhibition. These results point to multiple circuit elements with distinct roles in transforming odor representations in the OB and provide a framework for further dissecting early olfactory processing using optical and genetic tools. PMID:23516293

Development of five digits is controlled by a bipartite long-range cis-regulator.

PubMed

Lettice, Laura A; Williamson, Iain; Devenney, Paul S; Kilanowski, Fiona; Dorin, Julia; Hill, Robert E

2014-04-01

Conservation within intergenic DNA often highlights regulatory elements that control gene expression from a long range. How conservation within a single element relates to regulatory information and how internal composition relates to function is unknown. Here, we examine the structural features of the highly conserved ZRS (also called MFCS1) cis-regulator responsible for the spatiotemporal control of Shh in the limb bud. By systematically dissecting the ZRS, both in transgenic assays and within in the endogenous locus, we show that the ZRS is, in effect, composed of two distinct domains of activity: one domain directs spatiotemporal activity but functions predominantly from a short range, whereas a second domain is required to promote long-range activity. We show further that these two domains encode activities that are highly integrated and that the second domain is crucial in promoting the chromosomal conformational changes correlated with gene activity. During limb bud development, these activities encoded by the ZRS are interpreted differently by the fore limbs and the hind limbs; in the absence of the second domain there is no Shh activity in the fore limb, and in the hind limb low levels of Shh lead to a variant digit pattern ranging from two to four digits. Hence, in the embryo, the second domain stabilises the developmental programme providing a buffer for SHH morphogen activity and this ensures that five digits form in both sets of limbs.

Spatio-temporal conditional inference and hypothesis tests for neural ensemble spiking precision

PubMed Central

Harrison, Matthew T.; Amarasingham, Asohan; Truccolo, Wilson

2014-01-01

The collective dynamics of neural ensembles create complex spike patterns with many spatial and temporal scales. Understanding the statistical structure of these patterns can help resolve fundamental questions about neural computation and neural dynamics. Spatio-temporal conditional inference (STCI) is introduced here as a semiparametric statistical framework for investigating the nature of precise spiking patterns from collections of neurons that is robust to arbitrarily complex and nonstationary coarse spiking dynamics. The main idea is to focus statistical modeling and inference, not on the full distribution of the data, but rather on families of conditional distributions of precise spiking given different types of coarse spiking. The framework is then used to develop families of hypothesis tests for probing the spatio-temporal precision of spiking patterns. Relationships among different conditional distributions are used to improve multiple hypothesis testing adjustments and to design novel Monte Carlo spike resampling algorithms. Of special note are algorithms that can locally jitter spike times while still preserving the instantaneous peri-stimulus time histogram (PSTH) or the instantaneous total spike count from a group of recorded neurons. The framework can also be used to test whether first-order maximum entropy models with possibly random and time-varying parameters can account for observed patterns of spiking. STCI provides a detailed example of the generic principle of conditional inference, which may be applicable in other areas of neurostatistical analysis. PMID:25380339

Defined types of cortical interneurone structure space and spike timing in the hippocampus

PubMed Central

Somogyi, Peter; Klausberger, Thomas

2005-01-01

The cerebral cortex encodes, stores and combines information about the internal and external environment in rhythmic activity of multiple frequency ranges. Neurones of the cortex can be defined, recognized and compared on the comprehensive application of the following measures: (i) brain area- and cell domain-specific distribution of input and output synapses, (ii) expression of molecules involved in cell signalling, (iii) membrane and synaptic properties reflecting the expression of membrane proteins, (iv) temporal structure of firing in vivo, resulting from (i)–(iii). Spatial and temporal measures of neurones in the network reflect an indivisible unity of evolutionary design, i.e. neurones do not have separate structure or function. The blueprint of this design is most easily accessible in the CA1 area of the hippocampus, where a relatively uniform population of pyramidal cells and their inputs follow an instantly recognizable laminated pattern and act within stereotyped network activity patterns. Reviewing the cell types and their spatio-temporal interactions, we suggest that CA1 pyramidal cells are supported by at least 16 distinct types of GABAergic neurone. During a given behaviour-contingent network oscillation, interneurones of a given type exhibit similar firing patterns. During different network oscillations representing two distinct brain states, interneurones of the same class show different firing patterns modulating their postsynaptic target-domain in a brain-state-dependent manner. These results suggest roles for specific interneurone types in structuring the activity of pyramidal cells via their respective target domains, and accurately timing and synchronizing pyramidal cell discharge, rather than providing generalized inhibition. Finally, interneurones belonging to different classes may fire preferentially at distinct time points during a given oscillation. As different interneurones innervate distinct domains of the pyramidal cells, the different compartments will receive GABAergic input differentiated in time. Such a dynamic, spatio-temporal, GABAergic control, which evolves distinct patterns during different brain states, is ideally suited to regulating the input integration of individual pyramidal cells contributing to the formation of cell assemblies and representations in the hippocampus and, probably, throughout the cerebral cortex. PMID:15539390

Pattern Formation in Active Nematics

NASA Astrophysics Data System (ADS)

Mishra, Prashant

This thesis presents analytical and numerical studies of the nonequilibrium dynamics of active nematic liquid crystals. Active nematics are a new class of liquid crystals consisting of elongated rod-like units that convert energy into motion and spontaneously organize in large-scale structures with orientational order and self-sustained flows. Examples include suspensions of cytoskeletal filaments and associated motor proteins, monolayers of epithelial cells plated on a substrate, and bacteria swimming in a nematic liquid crystal. In these systems activity drives the continuous generation and annihilation of topological defects and streaming flows, resulting in spatio-temporal chaotic dynamics akin to fluid turbulence, but that occurs in a regime of flow of vanishing Reynolds number, where inertia is negligible. Quantifying the origin of this nonequilibrium dynamics has implications for understanding phenomena ranging from bacterial swarming to cytoplasmic flows in living cells. After a brief review (Chapter 2) of the properties of equilibrium or passive nematic liquid crystals, in Chapter 3 we discuss how the hydrodynamic equations of nematic liquid crystals can be modified to account for the effect of activity. We then use these equations of active nemato-hydrodynamics to characterize analytically the nonequilibrium steady states of the system and their stability. We supplement the analytical work with numerical solution of the full nonlinear equations for the active suspension and construct a phase diagram that identifies the various emergent patterns as a function of activity and nematic stiffness. In Chapter 4 we compare results obtained with two distinct hydrodynamic models that have been employed in previous studies. In both models we find that the chaotic spatio-temporal dynamics in the regime of fully developed active turbulence is controlled by a single active scale determined by the balance of active and elastic stresses. This work provides a unified understanding of apparent discrepancies in the previous literature and demonstrate that the essential physics is robust to the choice of model. Finally, in Chapter 5 we examine the dynamics of a compressible active nematic on a substrate. When frictional damping dominates over viscous dissipation, we eliminate flow in favor of active stresses to obtain a minimal model with renormalized elastic constants driven negative by activity. We show that spatially inhomogeneous patterns are selected via a mechanism analogous to that responsible for modulated phases at an equilibrium Lifshitz point.

Spatio-temporal dynamics of multimodal EEG-fNIRS signals in the loss and recovery of consciousness under sedation using midazolam and propofol

PubMed Central

Won, Dong-Ok; Chi, Seong In; Seo, Kwang-Suk; Kim, Hyun Jeong; Müller, Klaus-Robert; Lee, Seong-Whan

2017-01-01

On sedation motivated by the clinical needs for safety and reliability, recent studies have attempted to identify brain-specific signatures for tracking patient transition into and out of consciousness, but the differences in neurophysiological effects between 1) the sedative types and 2) the presence/absence of surgical stimulations still remain unclear. Here we used multimodal electroencephalography–functional near-infrared spectroscopy (EEG–fNIRS) measurements to observe electrical and hemodynamic responses during sedation simultaneously. Forty healthy volunteers were instructed to push the button to administer sedatives in response to auditory stimuli every 9–11 s. To generally illustrate brain activity at repetitive transition points at the loss of consciousness (LOC) and the recovery of consciousness (ROC), patient-controlled sedation was performed using two different sedatives (midazolam (MDZ) and propofol (PPF)) under two surgical conditions. Once consciousness was lost via sedatives, we observed gradually increasing EEG power at lower frequencies (<15 Hz) and decreasing power at higher frequencies (>15 Hz), as well as spatially increased EEG powers in the delta and lower alpha bands, and particularly also in the upper alpha rhythm, at the frontal and parieto-occipital areas over time. During ROC from unconsciousness, these spatio-temporal changes were reversed. Interestingly, the level of consciousness was switched on/off at significantly higher effect-site concentrations of sedatives in the brain according to the use of surgical stimuli, but the spatio-temporal EEG patterns were similar, regardless of the sedative used. We also observed sudden phase shifts in fronto-parietal connectivity at the LOC and the ROC as critical points. fNIRS measurement also revealed mild hemodynamic fluctuations. Compared with general anesthesia, our results provide insights into critical hallmarks of sedative-induced (un)consciousness, which have similar spatio-temporal EEG-fNIRS patterns regardless of the stage and the sedative used. PMID:29121108

Spatio-temporal dynamics of multimodal EEG-fNIRS signals in the loss and recovery of consciousness under sedation using midazolam and propofol.

PubMed

Yeom, Seul-Ki; Won, Dong-Ok; Chi, Seong In; Seo, Kwang-Suk; Kim, Hyun Jeong; Müller, Klaus-Robert; Lee, Seong-Whan

2017-01-01

On sedation motivated by the clinical needs for safety and reliability, recent studies have attempted to identify brain-specific signatures for tracking patient transition into and out of consciousness, but the differences in neurophysiological effects between 1) the sedative types and 2) the presence/absence of surgical stimulations still remain unclear. Here we used multimodal electroencephalography-functional near-infrared spectroscopy (EEG-fNIRS) measurements to observe electrical and hemodynamic responses during sedation simultaneously. Forty healthy volunteers were instructed to push the button to administer sedatives in response to auditory stimuli every 9-11 s. To generally illustrate brain activity at repetitive transition points at the loss of consciousness (LOC) and the recovery of consciousness (ROC), patient-controlled sedation was performed using two different sedatives (midazolam (MDZ) and propofol (PPF)) under two surgical conditions. Once consciousness was lost via sedatives, we observed gradually increasing EEG power at lower frequencies (<15 Hz) and decreasing power at higher frequencies (>15 Hz), as well as spatially increased EEG powers in the delta and lower alpha bands, and particularly also in the upper alpha rhythm, at the frontal and parieto-occipital areas over time. During ROC from unconsciousness, these spatio-temporal changes were reversed. Interestingly, the level of consciousness was switched on/off at significantly higher effect-site concentrations of sedatives in the brain according to the use of surgical stimuli, but the spatio-temporal EEG patterns were similar, regardless of the sedative used. We also observed sudden phase shifts in fronto-parietal connectivity at the LOC and the ROC as critical points. fNIRS measurement also revealed mild hemodynamic fluctuations. Compared with general anesthesia, our results provide insights into critical hallmarks of sedative-induced (un)consciousness, which have similar spatio-temporal EEG-fNIRS patterns regardless of the stage and the sedative used.

Circumpolar spatio-temporal patterns and contributing climatic factors of wildfire activity in the Arctic tundra from 2001-2015

NASA Astrophysics Data System (ADS)

Masrur, Arif; Petrov, Andrey N.; DeGroote, John

2018-01-01

Recent years have seen an increased frequency of wildfire events in different parts of Arctic tundra ecosystems. Contemporary studies have largely attributed these wildfire events to the Arctic’s rapidly changing climate and increased atmospheric disturbances (i.e. thunderstorms). However, existing research has primarily examined the wildfire-climate dynamics of individual large wildfire events. No studies have investigated wildfire activity, including climatic drivers, for the entire tundra biome across multiple years, i.e. at the planetary scale. To address this limitation, this paper provides a planetary/circumpolar scale analyses of space-time patterns of tundra wildfire occurrence and climatic association in the Arctic over a 15 year period (2001-2015). In doing so, we have leveraged and analyzed NASA Terra’s MODIS active fire and MERRA climate reanalysis products at multiple temporal scales (decadal, seasonal and monthly). Our exploratory spatial data analysis found that tundra wildfire occurrence was spatially clustered and fire intensity was spatially autocorrelated across the Arctic regions. Most of the wildfire events occurred in the peak summer months (June-August). Our multi-temporal (decadal, seasonal and monthly) scale analyses provide further support to the link between climate variability and wildfire activity. Specifically, we found that warm and dry conditions in the late spring to mid-summer influenced tundra wildfire occurrence, spatio-temporal distribution, and fire intensity. Additionally, reduced average surface precipitation and soil moisture levels in the winter-spring period were associated with increased fire intensity in the following summer. These findings enrich contemporary knowledge on tundra wildfire’s spatial and seasonal patterns, and shed new light on tundra wildfire-climate relationships in the circumpolar context. Furthermore, this first pan-Arctic analysis provides a strong incentive and direction for future studies which integrate multiple datasets (i.e. climate, fuels, topography, and ignition sources) to accurately estimate carbon emission from tundra burning and its global climate feedbacks in coming decades.

Spatiotemporal canards in neural field equations

NASA Astrophysics Data System (ADS)

Avitabile, D.; Desroches, M.; Knobloch, E.

2017-04-01

Canards are special solutions to ordinary differential equations that follow invariant repelling slow manifolds for long time intervals. In realistic biophysical single-cell models, canards are responsible for several complex neural rhythms observed experimentally, but their existence and role in spatially extended systems is largely unexplored. We identify and describe a type of coherent structure in which a spatial pattern displays temporal canard behavior. Using interfacial dynamics and geometric singular perturbation theory, we classify spatiotemporal canards and give conditions for the existence of folded-saddle and folded-node canards. We find that spatiotemporal canards are robust to changes in the synaptic connectivity and firing rate. The theory correctly predicts the existence of spatiotemporal canards with octahedral symmetry in a neural field model posed on the unit sphere.

Incremental Principal Component Analysis Based Outlier Detection Methods for Spatiotemporal Data Streams

NASA Astrophysics Data System (ADS)

Bhushan, A.; Sharker, M. H.; Karimi, H. A.

2015-07-01

In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Real-time detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA) is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud detection, pattern recognition, and image analysis. However, the suitability of applying IPCA for outlier detection in spatiotemporal data streams is unknown and needs to be investigated. To fill this research gap, this paper contributes by presenting two new IPCA-based outlier detection methods and performing a comparative analysis with the existing IPCA-based outlier detection methods to assess their suitability for spatiotemporal sensor data streams.

Spatio-temporal models of mental processes from fMRI.

PubMed

Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos

2011-07-15

Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.

Eliciting naturalistic cortical responses with a sensory prosthesis via optimized microstimulation

NASA Astrophysics Data System (ADS)

Choi, John S.; Brockmeier, Austin J.; McNiel, David B.; von Kraus, Lee M.; Príncipe, José C.; Francis, Joseph T.

2016-10-01

Objective. Lost sensations, such as touch, could one day be restored by electrical stimulation along the sensory neural pathways. Such stimulation, when informed by electronic sensors, could provide naturalistic cutaneous and proprioceptive feedback to the user. Perceptually, microstimulation of somatosensory brain regions produces localized, modality-specific sensations, and several spatiotemporal parameters have been studied for their discernibility. However, systematic methods for encoding a wide array of naturally occurring stimuli into biomimetic percepts via multi-channel microstimulation are lacking. More specifically, generating spatiotemporal patterns for explicitly evoking naturalistic neural activation has not yet been explored. Approach. We address this problem by first modeling the dynamical input-output relationship between multichannel microstimulation and downstream neural responses, and then optimizing the input pattern to reproduce naturally occurring touch responses as closely as possible. Main results. Here we show that such optimization produces responses in the S1 cortex of the anesthetized rat that are highly similar to natural, tactile-stimulus-evoked counterparts. Furthermore, information on both pressure and location of the touch stimulus was found to be highly preserved. Significance. Our results suggest that the currently presented stimulus optimization approach holds great promise for restoring naturalistic levels of sensation.

Priming with real motion biases visual cortical response to bistable apparent motion

PubMed Central

Zhang, Qing-fang; Wen, Yunqing; Zhang, Deng; She, Liang; Wu, Jian-young; Dan, Yang; Poo, Mu-ming

2012-01-01

Apparent motion quartet is an ambiguous stimulus that elicits bistable perception, with the perceived motion alternating between two orthogonal paths. In human psychophysical experiments, the probability of perceiving motion in each path is greatly enhanced by a brief exposure to real motion along that path. To examine the neural mechanism underlying this priming effect, we used voltage-sensitive dye (VSD) imaging to measure the spatiotemporal activity in the primary visual cortex (V1) of awake mice. We found that a brief real motion stimulus transiently biased the cortical response to subsequent apparent motion toward the spatiotemporal pattern representing the real motion. Furthermore, intracellular recording from V1 neurons in anesthetized mice showed a similar increase in subthreshold depolarization in the neurons representing the path of real motion. Such short-term plasticity in early visual circuits may contribute to the priming effect in bistable visual perception. PMID:23188797

High-Frequency Network Oscillations in Cerebellar Cortex

PubMed Central

Middleton, Steven J.; Racca, Claudia; Cunningham, Mark O.; Traub, Roger D.; Monyer, Hannah; Knöpfel, Thomas; Schofield, Ian S.; Jenkins, Alistair; Whittington, Miles A.

2016-01-01

SUMMARY Both cerebellum and neocortex receive input from the somatosensory system. Interaction between these regions has been proposed to underpin the correct selection and execution of motor commands, but it is not clear how such interactions occur. In neocortex, inputs give rise to population rhythms, providing a spatiotemporal coding strategy for inputs and consequent outputs. Here, we show that similar patterns of rhythm generation occur in cerebellum during nicotinic receptor subtype activation. Both gamma oscillations (30–80 Hz) and very fast oscillations (VFOs, 80–160 Hz) were generated by intrinsic cerebellar cortical circuitry in the absence of functional glutamatergic connections. As in neocortex, gamma rhythms were dependent on GABAA receptor-mediated inhibition, whereas VFOs required only nonsynaptically connected intercellular networks. The ability of cerebellar cortex to generate population rhythms within the same frequency bands as neocortex suggests that they act as a common spatiotemporal code within which corticocerebellar dialog may occur. PMID:18549787

Square cell packing in the Drosophila embryo through spatiotemporally regulated EGF receptor signaling

PubMed Central

Tamada, Masako; Zallen, Jennifer A.

2015-01-01

Summary Cells display dynamic and diverse morphologies during development, but the strategies by which differentiated tissues achieve precise shapes and patterns are not well understood. Here we identify a developmental program that generates a highly ordered square cell grid in the Drosophila embryo through sequential and spatially regulated cell alignment, oriented cell division, and apicobasal cell elongation. The basic leucine zipper transcriptional regulator Cnc is necessary and sufficient to produce a square cell grid in the presence of a midline signal provided by the EGF receptor ligand, Spitz. Spitz orients cell divisions through a Pins/LGN-dependent spindle positioning mechanism and controls cell shape and alignment through a transcriptional pathway that requires the Pointed ETS domain protein. These results identify a strategy for producing ordered square cell packing configurations in epithelia and reveal a molecular mechanism by which organized tissue structure is generated through spatiotemporally regulated responses to EGF receptor activation. PMID:26506305

Effects of Pacing Site and Stimulation History on Alternans Dynamics and the Development of Complex Spatiotemporal Patterns in Cardiac Tissue

PubMed Central

Gizzi, Alessio; Cherry, Elizabeth M.; Gilmour, Robert F.; Luther, Stefan; Filippi, Simonetta; Fenton, Flavio H.

2013-01-01

Alternans of action potential duration has been associated with T wave alternans and the development of arrhythmias because it produces large gradients of repolarization. However, little is known about alternans dynamics in large mammalian hearts. Using optical mapping to record electrical activations simultaneously from the epicardium and endocardium of 9 canine right ventricles, we demonstrate novel arrhythmogenic complex spatiotemporal dynamics. (i) Alternans predominantly develops first on the endocardium. (ii) The postulated simple progression from normal rhythm to concordant to discordant alternans is not always observed; concordant alternans can develop from discordant alternans as the pacing period is decreased. (iii) In contrast to smaller tissue preparations, multiple stationary nodal lines may exist and need not be perpendicular to the pacing site or to each other. (iv) Alternans has fully three-dimensional dynamics and the epicardium and endocardium can show significantly different dynamics: multiple nodal surfaces can be transmural or intramural and can form concave/convex surfaces resulting in islands of discordant alternans. (v) The complex spatiotemporal patterns observed during alternans are very sensitive to both the site of stimulation and the stimulation history. Alternans in canine ventricles not only exhibit larger amplitudes and persist for longer cycle length regimes compared to those found in smaller mammalian hearts, but also show novel dynamics not previously described that enhance dispersion and show high sensitivity to initial conditions. This indicates some underlying predisposition to chaos and can help to guide the design of new drugs and devices controlling and preventing arrhythmic events. PMID:23637684

Be together, not the same: Spatiotemporal organization of different cilia types generates distinct transport functions

NASA Astrophysics Data System (ADS)

Nawroth, Janna; Guo, Hanliang; Ruby, Edward; Dabiri, John; McFall-Ngai, Margaret; Kanso, Eva

2016-11-01

Motile cilia are microscopic, hair-like structures on the cell surface that can sense and propel the extracellular fluid environment. Cilia are often thought to be limited to stereotypic morphologies, beat kinematics and non-discriminatory clearance functions, but we find that the spatiotemporal organization of different cilia types and beat behaviors can generate complex flow patterns and transport functions. Here, we present a case study in the Hawaiian bobtail squid where collective ciliary activity and resulting flow fields help recruit symbiont bacteria to the animal host. In particular, we demonstrate empirically and computationally how the squid's internal cilia act like a microfluidic device that actively filters the water for potential bacterial candidates and also provides a sheltered zone allowing for accumulation of mucus and bacteria into a biofilm. Moreover, in this sheltered zone, different cilia-driven flows enhance diffusion of biochemical signals, which could accelerate specific bacteria-host recognition. These results suggest that studying cilia activity on the population level might reveal a diverse range of biological transport and sensing functions. Moreover, understanding cilia as functional building blocks could inspire the design of ciliated robots and devices.

Spatio-temporal analysis of wildfire ignitions in the St. Johns River Water Management District, Florida

Treesearch

Marc G. Genton; David T. Butry; Marcia L. Gumpertz; Jeffrey P. Prestemon

2006-01-01

We analyse the spatio-temporal structure of wildfire ignitions in the St. Johns River Water Management District in north-eastern Florida. We show, using tools to analyse point patterns (e.g. the L-function), that wildfire events occur in clusters. Clustering of these events correlates with irregular distribution of fire ignitions, including lightning...

Spatiotemporal patterns of ring-width variability in the northern interior west

Treesearch

R. Justin DeRose; John D. Shaw; James N. Long

2015-01-01

A fundamental goal of forest biogeography is to understand the factors that drive spatiotemporal variability in forest growth across large areas (e.g., states or regions). The ancillary collection of increment cores as part of the IW FIA Program represents an important non-traditional role for the development of unprecedented data sets. Individual-tree growth data from...

Spatio-Temporal Patterns of Barmah Forest Virus Disease in Queensland, Australia

PubMed Central

Naish, Suchithra; Hu, Wenbiao; Mengersen, Kerrie; Tong, Shilu

2011-01-01

Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland. PMID:22022430

Spatiotemporal patterns, annual baseline and movement-related incidence of Streptococcus agalactiae infection in Danish dairy herds: 2000-2009.

PubMed

Mweu, Marshal M; Nielsen, Søren S; Halasa, Tariq; Toft, Nils

2014-02-01

Several decades after the inception of the five-point plan for the control of contagious mastitis pathogens, Streptococcus agalactiae (S. agalactiae) persists as a fundamental threat to the dairy industry in many countries. A better understanding of the relative importance of within- and between-herd sources of new herd infections coupled with the spatiotemporal distribution of the infection, may aid in effective targeting of control efforts. Thus, the objectives of this study were: (1) to describe the spatiotemporal patterns of infection with S. agalactiae in the population of Danish dairy herds from 2000 to 2009 and (2) to estimate the annual herd-level baseline and movement-related incidence risks of S. agalactiae infection over the 10-year period. The analysis involved registry data on bacteriological culture of all bulk tank milk samples collected as part of the mandatory Danish S. agalactiae surveillance scheme as well as live cattle movements into dairy herds during the specified 10-year period. The results indicated that the predicted risk of a herd becoming infected with S. agalactiae varied spatiotemporally; the risk being more homogeneous and higher in the period after 2005. Additionally, the annual baseline risks yielded significant yet distinctive patterns before and after 2005 - the risk of infection being higher in the latter phase. On the contrary, the annual movement-related risks revealed a non-significant pattern over the 10-year period. There was neither evidence for spatial clustering of cases relative to the population of herds at risk nor spatial dependency between herds. Nevertheless, the results signal a need to beef up within-herd biosecurity in order to reduce the risk of new herd infections. Copyright © 2013 Elsevier B.V. All rights reserved.

Electrophysiological spatiotemporal dynamics during implicit visual threat processing.

PubMed

DeLaRosa, Bambi L; Spence, Jeffrey S; Shakal, Scott K M; Motes, Michael A; Calley, Clifford S; Calley, Virginia I; Hart, John; Kraut, Michael A

2014-11-01

Numerous studies have found evidence for corticolimbic theta band electroencephalographic (EEG) oscillations in the neural processing of visual stimuli perceived as threatening. However, varying temporal and topographical patterns have emerged, possibly due to varying arousal levels of the stimuli. In addition, recent studies suggest neural oscillations in delta, theta, alpha, and beta-band frequencies play a functional role in information processing in the brain. This study implemented a data-driven PCA based analysis investigating the spatiotemporal dynamics of electroencephalographic delta, theta, alpha, and beta-band frequencies during an implicit visual threat processing task. While controlling for the arousal dimension (the intensity of emotional activation), we found several spatial and temporal differences for threatening compared to nonthreatening visual images. We detected an early posterior increase in theta power followed by a later frontal increase in theta power, greatest for the threatening condition. There was also a consistent left lateralized beta desynchronization for the threatening condition. Our results provide support for a dynamic corticolimbic network, with theta and beta band activity indexing processes pivotal in visual threat processing. Published by Elsevier Inc.

Spatiotemporal Patterns and Socioeconomic Dimensions of Shared Accommodations: the Case of Airbnb in LOS Angeles, California

NASA Astrophysics Data System (ADS)

Sarkar, A.; Koohikamali, M.; Pick, J. B.

2017-10-01

In recent years, disruptive innovation by peer-to-peer platforms in a variety of industries, notably transportation and hospitality have altered the way individuals consume everyday essential services. With growth in sharing economy platforms such as Uber for ridesharing and Airbnb for short-term accommodations, interest in examining spatiotemporal patterns of participation in the sharing economy by suppliers and consumers is increasing. This research is motivated by key questions: who are the sharing economy workers, where are they located, and does their location influence their participation in the sharing economy? This paper is the first systematic effort to analyze spatiotemporal patterns of participation by hosts in the shared accommodation-based economy. Using three different kinds of shared accommodations listed in a 3-year period in the popular short-term accommodation platform, Airbnb, we examine spatiotemporal dimensions of host participation in a major U.S. market, Los Angeles CA. The paper also develops a conceptual model by positing associations of demographic, socioeconomic, occupational, and social capital attributes of hosts, along with their attitudes toward trust and greener consumption with hosts' participation in a shared accommodation market. Results confirm host participation to be influenced by young dependency ratio, the potential of supplemental income, as well as the sustainability potential of collaborative consumption, along with finance, insurance, and real estate occupation, but not so much by trust for our overall study area. These results add new insights to limited prior knowledge about the sharing economy worker and have policy implications.

Self-organized mechano-chemical dynamics in amoeboid locomotion of Physarum fragments

NASA Astrophysics Data System (ADS)

Zhang, Shun; Guy, Robert D.; Lasheras, Juan C.; del Álamo, Juan C.

2017-05-01

The aim of this work is to quantify the spatio-temporal dynamics of flow-driven amoeboid locomotion in small (∼100 μm) fragments of the true slime mold Physarum polycephalum. In this model organism, cellular contraction drives intracellular flows, and these flows transport the chemical signals that regulate contraction in the first place. As a consequence of these non-linear interactions, a diversity of migratory behaviors can be observed in migrating Physarum fragments. To study these dynamics, we measure the spatio-temporal distributions of the velocities of the endoplasm and ectoplasm of each migrating fragment, the traction stresses it generates on the substratum, and the concentration of free intracellular calcium. Using these unprecedented experimental data, we classify migrating Physarum fragments according to their dynamics, finding that they often exhibit spontaneously coordinated waves of flow, contractility and chemical signaling. We show that Physarum fragments exhibiting symmetric spatio-temporal patterns of endoplasmic flow migrate significantly slower than fragments with asymmetric patterns. In addition, our joint measurements of ectoplasm velocity and traction stress at the substratum suggest that forward motion of the ectoplasm is enabled by a succession of stick-slip transitions, which we conjecture are also organized in the form of waves. Combining our experiments with a simplified convection-diffusion model, we show that the convective transport of calcium ions may be key for establishing and maintaining the spatio-temporal patterns of calcium concentration that regulate the generation of contractile forces.

Modeling distributional changes in winter precipitation of Canada using Bayesian spatiotemporal quantile regression subjected to different teleconnections

NASA Astrophysics Data System (ADS)

Tan, Xuezhi; Gan, Thian Yew; Chen, Shu; Liu, Bingjun

2018-05-01

Climate change and large-scale climate patterns may result in changes in probability distributions of climate variables that are associated with changes in the mean and variability, and severity of extreme climate events. In this paper, we applied a flexible framework based on the Bayesian spatiotemporal quantile (BSTQR) model to identify climate changes at different quantile levels and their teleconnections to large-scale climate patterns such as El Niño-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO) and Pacific-North American (PNA). Using the BSTQR model with time (year) as a covariate, we estimated changes in Canadian winter precipitation and their uncertainties at different quantile levels. There were some stations in eastern Canada showing distributional changes in winter precipitation such as an increase in low quantiles but a decrease in high quantiles. Because quantile functions in the BSTQR model vary with space and time and assimilate spatiotemporal precipitation data, the BSTQR model produced much spatially smoother and less uncertain quantile changes than the classic regression without considering spatiotemporal correlations. Using the BSTQR model with five teleconnection indices (i.e., SOI, PDO, PNA, NP and NAO) as covariates, we investigated effects of large-scale climate patterns on Canadian winter precipitation at different quantile levels. Winter precipitation responses to these five teleconnections were found to occur differently at different quantile levels. Effects of five teleconnections on Canadian winter precipitation were stronger at low and high than at medium quantile levels.

Tracking brain states under general anesthesia by using global coherence analysis

PubMed Central

Cimenser, Aylin; Purdon, Patrick L.; Pierce, Eric T.; Walsh, John L.; Salazar-Gomez, Andres F.; Harrell, Priscilla G.; Tavares-Stoeckel, Casie; Habeeb, Kathleen; Brown, Emery N.

2011-01-01

Time and frequency domain analyses of scalp EEG recordings are widely used to track changes in brain states under general anesthesia. Although these analyses have suggested that different spatial patterns are associated with changes in the state of general anesthesia, the extent to which these patterns are spatially coordinated has not been systematically characterized. Global coherence, the ratio of the largest eigenvalue to the sum of the eigenvalues of the cross-spectral matrix at a given frequency and time, has been used to analyze the spatiotemporal dynamics of multivariate time-series. Using 64-lead EEG recorded from human subjects receiving computer-controlled infusions of the anesthetic propofol, we used surface Laplacian referencing combined with spectral and global coherence analyses to track the spatiotemporal dynamics of the brain's anesthetic state. During unconsciousness the spectrograms in the frontal leads showed increasing α (8–12 Hz) and δ power (0–4 Hz) and in the occipital leads δ power greater than α power. The global coherence detected strong coordinated α activity in the occipital leads in the awake state that shifted to the frontal leads during unconsciousness. It revealed a lack of coordinated δ activity during both the awake and unconscious states. Although strong frontal power during general anesthesia-induced unconsciousness—termed anteriorization—is well known, its possible association with strong α range global coherence suggests highly coordinated spatial activity. Our findings suggest that combined spectral and global coherence analyses may offer a new approach to tracking brain states under general anesthesia. PMID:21555565

Mechanisms for the target patterns formation in a stochastic bistable excitable medium

NASA Astrophysics Data System (ADS)

Verisokin, Andrey Yu.; Verveyko, Darya V.; Postnov, Dmitry E.

2018-04-01

We study the features of formation and evolution of spatiotemporal chaotic regime generated by autonomous pacemakers in excitable deterministic and stochastic bistable active media using the example of the FitzHugh - Nagumo biological neuron model under discrete medium conditions. The following possible mechanisms for the formation of autonomous pacemakers have been studied: 1) a temporal external force applied to a small region of the medium, 2) geometry of the solution region (the medium contains regions with Dirichlet or Neumann boundaries). In our work we explore the conditions for the emergence of pacemakers inducing target patterns in a stochastic bistable excitable system and propose the algorithm for their analysis.

Three-dimensional spatiotemporal focusing of holographic patterns

PubMed Central

Hernandez, Oscar; Papagiakoumou, Eirini; Tanese, Dimitrii; Fidelin, Kevin; Wyart, Claire; Emiliani, Valentina

2016-01-01

Two-photon excitation with temporally focused pulses can be combined with phase-modulation approaches, such as computer-generated holography and generalized phase contrast, to efficiently distribute light into two-dimensional, axially confined, user-defined shapes. Adding lens-phase modulations to 2D-phase holograms enables remote axial pattern displacement as well as simultaneous pattern generation in multiple distinct planes. However, the axial confinement linearly degrades with lateral shape area in previous reports where axially shifted holographic shapes were not temporally focused. Here we report an optical system using two spatial light modulators to independently control transverse- and axial-target light distribution. This approach enables simultaneous axial translation of single or multiple spatiotemporally focused patterns across the sample volume while achieving the axial confinement of temporal focusing. We use the system's capability to photoconvert tens of Kaede-expressing neurons with single-cell resolution in live zebrafish larvae. PMID:27306044

Seasonal Changes in Socio-Spatial Structure in a Group of Free-Living Spider Monkeys (Ateles geoffroyi)

PubMed Central

Ramos-Fernández, Gabriel; Getz, Wayne M.

2016-01-01

Ecological and social factors influence individual movement and group membership decisions, which ultimately determine how animal groups adjust their behavior in spatially and temporally heterogeneous environments. The mechanisms behind these behavioral adjustments can be better understood by studying the relationship between association and space use patterns of groups and how these change over time. We examined the socio-spatial patterns of adult individuals in a free-ranging group of spider monkeys (Ateles geoffroyi), a species with high fission-fusion dynamics. Data comprised 4916 subgroup scans collected during 325 days throughout a 20-month period and was used to evaluate changes from fruit-scarce to fruit-abundant periods in individual core-area size, subgroup size and two types of association measures: spatial (core-area overlap) and spatio-temporal (occurrence in the same subgroup) associations. We developed a 3-level analysis framework to distinguish passive associations, where individuals are mostly brought together by resources of common interest, from active association, where individuals actively seek or avoid certain others. Results indicated a more concentrated use of space, increased individual gregariousness and higher spatio-temporal association rates in the fruit-abundant seasons, as is compatible with an increase in passive associations. Nevertheless, results also suggested active associations in all the periods analyzed, although associations differed across seasons. In particular, females seem to actively avoid males, perhaps prompted by an increased probability of random encounters among individuals, resulting from the contraction of individual core areas. Our framework proved useful in investigating the interplay between ecological and social constraints and how these constraints can influence individual ranging and grouping decisions in spider monkeys, and possibly other species with high fission-fusion dynamics. PMID:27280800

Emergent Archetype Hydrological-Biogeochemical Response Patterns in Heterogeneous Catchments

NASA Astrophysics Data System (ADS)

Jawitz, J. W.; Gall, H. E.; Rao, P.

2013-12-01

What can spatiotemporally integrated patterns observed in stream hydrologic and biogeochemical signals generated in response to transient hydro-climatic and anthropogenic forcing tell us about the interactions between spatially heterogeneous soil-mediated hydrological and biogeochemical processes? We seek to understand how the spatial structure of solute sources coupled with hydrologic responses affect observed concentration-discharge (C-Q) patterns. These patterns are expressions of the spatiotemporal structure of solute loads exported from managed catchments, and their likely ecological consequences manifested in receiving water bodies (e.g., wetlands, rivers, lakes, and coastal waters). We investigated the following broad questions: (1) How does the correlation between flow-generating areas and biogeochemical source areas across a catchment evolve under stochastic hydro-climatic forcing? (2) What are the feasible hydrologic and biogeochemical responses that lead to the emergence of the observed archetype C-Q patterns? and; (3) What implications do these coupled dynamics have for catchment monitoring and implementation of management practices? We categorize the observed temporal signals into three archetypical C-Q patterns: dilution; accretion, and constant concentration. We introduce a parsimonious stochastic model of heterogeneous catchments, which act as hydrologic and biogeochemical filters, to examine the relationship between spatial heterogeneity and temporal history of solute export signals. The core concept of the modeling framework is considering the types and degree of spatial correlation between solute source zones and flow generating zones, and activation of different portions of the catchments during rainfall events. Our overarching hypothesis is that each of the archetype C-Q patterns can be generated by explicitly linking landscape-scale hydrologic responses and spatial distributions of solute source properties within a catchment. The model simulations reproduce the three major C-Q patterns observed in published data, offering valuable insight into coupled catchment processes. The findings have important implications for effective catchment management for water quality improvement, and stream monitoring strategies.

Resting state networks in empirical and simulated dynamic functional connectivity.

PubMed

Glomb, Katharina; Ponce-Alvarez, Adrián; Gilson, Matthieu; Ritter, Petra; Deco, Gustavo

2017-10-01

It is well-established that patterns of functional connectivity (FC) - measures of correlated activity between pairs of voxels or regions observed in the human brain using neuroimaging - are robustly expressed in spontaneous activity during rest. These patterns are not static, but exhibit complex spatio-temporal dynamics. Over the last years, a multitude of methods have been proposed to reveal these dynamics on the level of the whole brain. One finding is that the brain transitions through different FC configurations over time, and substantial effort has been put into characterizing these configurations. However, the dynamics governing these transitions are more elusive, specifically, the contribution of stationary vs. non-stationary dynamics is an active field of inquiry. In this study, we use a whole-brain approach, considering FC dynamics between 66 ROIs covering the entire cortex. We combine an innovative dimensionality reduction technique, tensor decomposition, with a mean field model which possesses stationary dynamics. It has been shown to explain resting state FC averaged over time and multiple subjects, however, this average FC summarizes the spatial distribution of correlations while hiding their temporal dynamics. First, we apply tensor decomposition to resting state scans from 24 healthy controls in order to characterize spatio-temporal dynamics present in the data. We simultaneously utilize temporal and spatial information by creating tensors that are subsequently decomposed into sets of brain regions ("communities") that share similar temporal dynamics, and their associated time courses. The tensors contain pairwise FC computed inside of overlapping sliding windows. Communities are discovered by clustering features pooled from all subjects, thereby ensuring that they generalize. We find that, on the group level, the data give rise to four distinct communities that resemble known resting state networks (RSNs): default mode network, visual network, control networks, and somatomotor network. Second, we simulate data with our stationary mean field model whose nodes are connected according to results from DTI and fiber tracking. In this model, all spatio-temporal structure is due to noisy fluctuations around the average FC. We analyze the simulated data in the same way as the empirical data in order to determine whether stationary dynamics can explain the emergence of distinct FC patterns (RSNs) which have their own time courses. We find that this is the case for all four networks using the spatio-temporal information revealed by tensor decomposition if nodes in the simulation are connected according to model-based effective connectivity. Furthermore, we find that these results require only a small part of the FC values, namely the highest values that occur across time and ROI pair. Our findings show that stationary dynamics can account for the emergence of RSNs. We provide an innovative method that does not make strong assumptions about the underlying data and is generally applicable to resting state or task data from different subject populations. Copyright © 2017 Elsevier Inc. All rights reserved.

New type of chimera and mutual synchronization of spatiotemporal structures in two coupled ensembles of nonlocally interacting chaotic maps

NASA Astrophysics Data System (ADS)

Bukh, Andrei; Rybalova, Elena; Semenova, Nadezhda; Strelkova, Galina; Anishchenko, Vadim

2017-11-01

We study numerically the dynamics of a network made of two coupled one-dimensional ensembles of discrete-time systems. The first ensemble is represented by a ring of nonlocally coupled Henon maps and the second one by a ring of nonlocally coupled Lozi maps. We find that the network of coupled ensembles can realize all the spatio-temporal structures which are observed both in the Henon map ensemble and in the Lozi map ensemble while uncoupled. Moreover, we reveal a new type of spatiotemporal structure, a solitary state chimera, in the considered network. We also establish and describe the effect of mutual synchronization of various complex spatiotemporal patterns in the system of two coupled ensembles of Henon and Lozi maps.

Early perception and structural identity: neural implementation

NASA Astrophysics Data System (ADS)

Ligomenides, Panos A.

1992-03-01

It is suggested that there exists a minimal set of rules for the perceptual composition of the unending variety of spatio-temporal patterns in our perceptual world. Driven by perceptual discernment of "sudden change" and "unexpectedness", these rules specify conditions (such as co-linearity and virtual continuation) for perceptual grouping and for recursive compositions of perceptual "modalities" and "signatures". Beginning with a smallset of primitive perceptual elements, selected contextually at some relevant level of abstraction, perceptual compositions can graduate to an unlimited variety of spatiotemporal signatures, scenes and activities. Local discernible elements, often perceptually ambiguous by themselves, may be integrated into spatiotemporal compositions, which generate unambiguous perceptual separations between "figure" and "ground". The definition of computational algorithms for the effective instantiation of the rules of perceptual grouping remains a principal problem. In this paper we present our approach for solving the problem of perceptual recognition within the confines of one-D variational profiles. More specifically, concerning "early" (pre-attentive) recognition, we define the "structural identity of a k-norm, k ∈ K,"--SkID--as a tool for discerning and locating the instantiation of spatiotemporal objects or events. The SkID profile also serves a s a reference coordinate framework for the "perceptual focusing of attention" and the eventual assessment of resemblance. Neural network implementations of pre-attentive and attentive recognition are also discussed briefly. Our principles are exemplified by application to one-D perceptual profiles, which allows simplicity of definitions and of the rules of perceptual composition.

Concentric superlattice pattern in dielectric barrier discharge

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

Feng, Jianyu; Dong, Lifang, E-mail: donglfhbu@163.com; Wei, Lingyan

2016-09-15

The concentric superlattice pattern with three sub-lattices is observed in the dielectric barrier discharge in air/argon for the first time. Its spatiotemporal structure investigated by an intensified charge-coupled device shows that it is an interleaving of three different sub-lattices, which are concentric-ring, concentric-framework, and concentric-dot, respectively. The images of single-frame indicate that the concentric-ring and concentric-framework are composed of individual filaments. By using the optical emission spectrum method, it is found that plasma parameters of the concentric-dot are different from those of the concentric-ring and concentric-framework. The spatiotemporal dynamics of the concentric superlattice pattern is dependent upon the effective fieldmore » of the distribution of the wall charges field and the applied field.« less

A functionally conserved Polycomb response element from mouse HoxD complex responds to heterochromatin factors

NASA Astrophysics Data System (ADS)

Vasanthi, Dasari; Nagabhushan, A.; Matharu, Navneet Kaur; Mishra, Rakesh K.

2013-10-01

Anterior-posterior body axis in all bilaterians is determined by the Hox gene clusters that are activated in a spatio-temporal order. This expression pattern of Hox genes is established and maintained by regulatory mechanisms that involve higher order chromatin structure and Polycomb group (PcG) and trithorax group (trxG) proteins. We identified earlier a Polycomb response element (PRE) in the mouse HoxD complex that is functionally conserved in flies. We analyzed the molecular and genetic interactions of mouse PRE using Drosophila melanogaster and vertebrate cell culture as the model systems. We demonstrate that the repressive activity of this PRE depends on PcG/trxG genes as well as the heterochromatin components. Our findings indicate that a wide range of factors interact with the HoxD PRE that can contribute to establishing the expression pattern of homeotic genes in the complex early during development and maintain that pattern at subsequent stages.

Irregular behavior in an excitatory-inhibitory neuronal network

NASA Astrophysics Data System (ADS)

Park, Choongseok; Terman, David

2010-06-01

Excitatory-inhibitory networks arise in many regions throughout the central nervous system and display complex spatiotemporal firing patterns. These neuronal activity patterns (of individual neurons and/or the whole network) are closely related to the functional status of the system and differ between normal and pathological states. For example, neurons within the basal ganglia, a group of subcortical nuclei that are responsible for the generation of movement, display a variety of dynamic behaviors such as correlated oscillatory activity and irregular, uncorrelated spiking. Neither the origins of these firing patterns nor the mechanisms that underlie the patterns are well understood. We consider a biophysical model of an excitatory-inhibitory network in the basal ganglia and explore how specific biophysical properties of the network contribute to the generation of irregular spiking. We use geometric dynamical systems and singular perturbation methods to systematically reduce the model to a simpler set of equations, which is suitable for analysis. The results specify the dependence on the strengths of synaptic connections and the intrinsic firing properties of the cells in the irregular regime when applied to the subthalamopallidal network of the basal ganglia.

Cellular automata rule characterization and classification using texture descriptors

NASA Astrophysics Data System (ADS)

Machicao, Jeaneth; Ribas, Lucas C.; Scabini, Leonardo F. S.; Bruno, Odermir M.

2018-05-01

The cellular automata (CA) spatio-temporal patterns have attracted the attention from many researchers since it can provide emergent behavior resulting from the dynamics of each individual cell. In this manuscript, we propose an approach of texture image analysis to characterize and classify CA rules. The proposed method converts the CA spatio-temporal patterns into a gray-scale image. The gray-scale is obtained by creating a binary number based on the 8-connected neighborhood of each dot of the CA spatio-temporal pattern. We demonstrate that this technique enhances the CA rule characterization and allow to use different texture image analysis algorithms. Thus, various texture descriptors were evaluated in a supervised training approach aiming to characterize the CA's global evolution. Our results show the efficiency of the proposed method for the classification of the elementary CA (ECAs), reaching a maximum of 99.57% of accuracy rate according to the Li-Packard scheme (6 classes) and 94.36% for the classification of the 88 rules scheme. Moreover, within the image analysis context, we found a better performance of the method by means of a transformation of the binary states to a gray-scale.

Spatio-temporal patterns of tree establishment are indicative of biotic interactions during early invasion of a montane meadow

Treesearch

J.M. Rice; C.B. Halpern; J.A. Antos; J.A. Jones

2012-01-01

Tree invasions of grasslands are occurring globally, with profound consequences for ecosystem structure and function. We explore the spatio-temporal dynamics of tree invasion of a montane meadow in the Cascade Mountains of Oregon, where meadow loss is a conservation concern. We examine the early stages of invasion, where extrinsic and intrinsic processes can be clearly...

Using geovisual analytics in Google Earth to understand disease distribution: a case study of campylobacteriosis in the Czech Republic (2008-2012).

PubMed

Marek, Lukáš; Tuček, Pavel; Pászto, Vít

2015-01-28

Visual analytics aims to connect the processing power of information technologies and the user's ability of logical thinking and reasoning through the complex visual interaction. Moreover, the most of the data contain the spatial component. Therefore, the need for geovisual tools and methods arises. Either one can develop own system but the dissemination of findings and its usability might be problematic or the widespread and well-known platform can be utilized. The aim of this paper is to prove the applicability of Google Earth™ software as a tool for geovisual analytics that helps to understand the spatio-temporal patterns of the disease distribution. We combined the complex joint spatio-temporal analysis with comprehensive visualisation. We analysed the spatio-temporal distribution of the campylobacteriosis in the Czech Republic between 2008 and 2012. We applied three main approaches in the study: (1) the geovisual analytics of the surveillance data that were visualised in the form of bubble chart; (2) the geovisual analytics of the disease's weekly incidence surfaces computed by spatio-temporal kriging and (3) the spatio-temporal scan statistics that was employed in order to identify high or low rates clusters of affected municipalities. The final data are stored in Keyhole Markup Language files and visualised in Google Earth™ in order to apply geovisual analytics. Using geovisual analytics we were able to display and retrieve information from complex dataset efficiently. Instead of searching for patterns in a series of static maps or using numerical statistics, we created the set of interactive visualisations in order to explore and communicate results of analyses to the wider audience. The results of the geovisual analytics identified periodical patterns in the behaviour of the disease as well as fourteen spatio-temporal clusters of increased relative risk. We prove that Google Earth™ software is a usable tool for the geovisual analysis of the disease distribution. Google Earth™ has many indisputable advantages (widespread, freely available, intuitive interface, space-time visualisation capabilities and animations, communication of results), nevertheless it is still needed to combine it with pre-processing tools that prepare the data into a form suitable for the geovisual analytics itself.

Introduction to the Focus Issue: Chemo-Hydrodynamic Patterns and Instabilities

NASA Astrophysics Data System (ADS)

De Wit, A.; Eckert, K.; Kalliadasis, S.

2012-09-01

Pattern forming instabilities are often encountered in a wide variety of natural phenomena and technological applications, from self-organization in biological and chemical systems to oceanic or atmospheric circulation and heat and mass transport processes in engineering systems. Spatio-temporal structures are ubiquitous in hydrodynamics where numerous different convective instabilities generate pattern formation and complex spatiotemporal dynamics, which have been much studied both theoretically and experimentally. In parallel, reaction-diffusion processes provide another large family of pattern forming instabilities and spatio-temporal structures which have been analyzed for several decades. At the intersection of these two fields, "chemo-hydrodynamic patterns and instabilities" resulting from the coupling of hydrodynamic and reaction-diffusion processes have been less studied. The exploration of the new instability and symmetry-breaking scenarios emerging from the interplay between chemical reactions, diffusion and convective motions is a burgeoning field in which numerous exciting problems have emerged during the last few years. These problems range from fingering instabilities of chemical fronts and reactive fluid-fluid interfaces to the dynamics of reaction-diffusion systems in the presence of chaotic mixing. The questions to be addressed are at the interface of hydrodynamics, chemistry, engineering or environmental sciences to name a few and, as a consequence, they have started to draw the attention of several communities including both the nonlinear chemical dynamics and hydrodynamics communities. The collection of papers gathered in this Focus Issue sheds new light on a wide range of phenomena in the general area of chemo-hydrodynamic patterns and instabilities. It also serves as an overview of the current research and state-of-the-art in the field.

Attempting to physically explain space-time correlation of extremes

NASA Astrophysics Data System (ADS)

Bernardara, Pietro; Gailhard, Joel

2010-05-01

Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.

A Hippocampal Cognitive Prosthesis: Multi-Input, Multi-Output Nonlinear Modeling and VLSI Implementation

PubMed Central

Berger, Theodore W.; Song, Dong; Chan, Rosa H. M.; Marmarelis, Vasilis Z.; LaCoss, Jeff; Wills, Jack; Hampson, Robert E.; Deadwyler, Sam A.; Granacki, John J.

2012-01-01

This paper describes the development of a cognitive prosthesis designed to restore the ability to form new long-term memories typically lost after damage to the hippocampus. The animal model used is delayed nonmatch-to-sample (DNMS) behavior in the rat, and the “core” of the prosthesis is a biomimetic multi-input/multi-output (MIMO) nonlinear model that provides the capability for predicting spatio-temporal spike train output of hippocampus (CA1) based on spatio-temporal spike train inputs recorded presynaptically to CA1 (e.g., CA3). We demonstrate the capability of the MIMO model for highly accurate predictions of CA1 coded memories that can be made on a single-trial basis and in real-time. When hippocampal CA1 function is blocked and long-term memory formation is lost, successful DNMS behavior also is abolished. However, when MIMO model predictions are used to reinstate CA1 memory-related activity by driving spatio-temporal electrical stimulation of hippocampal output to mimic the patterns of activity observed in control conditions, successful DNMS behavior is restored. We also outline the design in very-large-scale integration for a hardware implementation of a 16-input, 16-output MIMO model, along with spike sorting, amplification, and other functions necessary for a total system, when coupled together with electrode arrays to record extracellularly from populations of hippocampal neurons, that can serve as a cognitive prosthesis in behaving animals. PMID:22438335

Following the ontogeny of retinal waves: pan-retinal recordings of population dynamics in the neonatal mouse

PubMed Central

Maccione, Alessandro; Hennig, Matthias H; Gandolfo, Mauro; Muthmann, Oliver; van Coppenhagen, James; Eglen, Stephen J; Berdondini, Luca; Sernagor, Evelyne

2014-01-01

The immature retina generates spontaneous waves of spiking activity that sweep across the ganglion cell layer during a limited period of development before the onset of visual experience. The spatiotemporal patterns encoded in the waves are believed to be instructive for the wiring of functional connections throughout the visual system. However, the ontogeny of retinal waves is still poorly documented as a result of the relatively low resolution of conventional recording techniques. Here, we characterize the spatiotemporal features of mouse retinal waves from birth until eye opening in unprecedented detail using a large-scale, dense, 4096-channel multielectrode array that allowed us to record from the entire neonatal retina at near cellular resolution. We found that early cholinergic waves propagate with random trajectories over large areas with low ganglion cell recruitment. They become slower, smaller and denser when GABAA signalling matures, as occurs beyond postnatal day (P) 7. Glutamatergic influences dominate from P10, coinciding with profound changes in activity dynamics. At this time, waves cease to be random and begin to show repetitive trajectories confined to a few localized hotspots. These hotspots gradually tile the retina with time, and disappear after eye opening. Our observations demonstrate that retinal waves undergo major spatiotemporal changes during ontogeny. Our results support the hypotheses that cholinergic waves guide the refinement of retinal targets and that glutamatergic waves may also support the wiring of retinal receptive fields. PMID:24366261

Acute differences in foot strike and spatiotemporal variables for shod, barefoot or minimalist male runners.

PubMed

McCallion, Ciara; Donne, Bernard; Fleming, Neil; Blanksby, Brian

2014-05-01

This study compared stride length, stride frequency, contact time, flight time and foot-strike patterns (FSP) when running barefoot, and in minimalist and conventional running shoes. Habitually shod male athletes (n = 14; age 25 ± 6 yr; competitive running experience 8 ± 3 yr) completed a randomised order of 6 by 4-min treadmill runs at velocities (V1 and V2) equivalent to 70 and 85% of best 5-km race time, in the three conditions. Synchronous recording of 3-D joint kinematics and ground reaction force data examined spatiotemporal variables and FSP. Most participants adopted a mid-foot strike pattern, regardless of condition. Heel-toe latency was less at V2 than V1 (-6 ± 20 vs. -1 ± 13 ms, p < 0.05), which indicated a velocity related shift towards a more FFS pattern. Stride duration and flight time, when shod and in minimalist footwear, were greater than barefoot (713 ± 48 and 701 ± 49 vs. 679 ± 56 ms, p < 0.001; and 502 ± 45 and 503 ± 41 vs. 488 ±4 9 ms, p < 0.05, respectively). Contact time was significantly longer when running shod than barefoot or in minimalist footwear (211±30 vs. 191 ± 29 ms and 198 ± 33 ms, p < 0.001). When running barefoot, stride frequency was significantly higher (p < 0.001) than in conventional and minimalist footwear (89 ± 7 vs. 85 ± 6 and 86 ± 6 strides·min(-1)). In conclusion, differences in spatiotemporal variables occurred within a single running session, irrespective of barefoot running experience, and, without a detectable change in FSP. Key pointsDifferences in spatiotemporal variables occurred within a single running session, without a change in foot strike pattern.Stride duration and flight time were greater when shod and in minimalist footwear than when barefoot.Stride frequency when barefoot was higher than when shod or in minimalist footwear.Contact time when shod was longer than when barefoot or in minimalist footwear.Spatiotemporal variables when running in minimalist footwear more closely resemble shod than barefoot running.

Acute Differences in Foot Strike and Spatiotemporal Variables for Shod, Barefoot or Minimalist Male Runners

PubMed Central

McCallion, Ciara; Donne, Bernard; Fleming, Neil; Blanksby, Brian

2014-01-01

This study compared stride length, stride frequency, contact time, flight time and foot-strike patterns (FSP) when running barefoot, and in minimalist and conventional running shoes. Habitually shod male athletes (n = 14; age 25 ± 6 yr; competitive running experience 8 ± 3 yr) completed a randomised order of 6 by 4-min treadmill runs at velocities (V1 and V2) equivalent to 70 and 85% of best 5-km race time, in the three conditions. Synchronous recording of 3-D joint kinematics and ground reaction force data examined spatiotemporal variables and FSP. Most participants adopted a mid-foot strike pattern, regardless of condition. Heel-toe latency was less at V2 than V1 (-6 ± 20 vs. -1 ± 13 ms, p < 0.05), which indicated a velocity related shift towards a more FFS pattern. Stride duration and flight time, when shod and in minimalist footwear, were greater than barefoot (713 ± 48 and 701 ± 49 vs. 679 ± 56 ms, p < 0.001; and 502 ± 45 and 503 ± 41 vs. 488 ±4 9 ms, p < 0.05, respectively). Contact time was significantly longer when running shod than barefoot or in minimalist footwear (211±30 vs. 191 ± 29 ms and 198 ± 33 ms, p < 0.001). When running barefoot, stride frequency was significantly higher (p < 0.001) than in conventional and minimalist footwear (89 ± 7 vs. 85 ± 6 and 86 ± 6 strides·min-1). In conclusion, differences in spatiotemporal variables occurred within a single running session, irrespective of barefoot running experience, and, without a detectable change in FSP. Key points Differences in spatiotemporal variables occurred within a single running session, without a change in foot strike pattern. Stride duration and flight time were greater when shod and in minimalist footwear than when barefoot. Stride frequency when barefoot was higher than when shod or in minimalist footwear. Contact time when shod was longer than when barefoot or in minimalist footwear. Spatiotemporal variables when running in minimalist footwear more closely resemble shod than barefoot running. PMID:24790480

Exploring Instructive Physiological Signaling with the Bioelectric Tissue Simulation Engine

PubMed Central

Pietak, Alexis; Levin, Michael

2016-01-01

Bioelectric cell properties have been revealed as powerful targets for modulating stem cell function, regenerative response, developmental patterning, and tumor reprograming. Spatio-temporal distributions of endogenous resting potential, ion flows, and electric fields are influenced not only by the genome and external signals but also by their own intrinsic dynamics. Ion channels and electrical synapses (gap junctions) both determine, and are themselves gated by, cellular resting potential. Thus, the origin and progression of bioelectric patterns in multicellular tissues is complex, which hampers the rational control of voltage distributions for biomedical interventions. To improve understanding of these dynamics and facilitate the development of bioelectric pattern control strategies, we developed the BioElectric Tissue Simulation Engine (BETSE), a finite volume method multiphysics simulator, which predicts bioelectric patterns and their spatio-temporal dynamics by modeling ion channel and gap junction activity and tracking changes to the fundamental property of ion concentration. We validate performance of the simulator by matching experimentally obtained data on membrane permeability, ion concentration and resting potential to simulated values, and by demonstrating the expected outcomes for a range of well-known cases, such as predicting the correct transmembrane voltage changes for perturbation of single cell membrane states and environmental ion concentrations, in addition to the development of realistic transepithelial potentials and bioelectric wounding signals. In silico experiments reveal factors influencing transmembrane potential are significantly different in gap junction-networked cell clusters with tight junctions, and identify non-linear feedback mechanisms capable of generating strong, emergent, cluster-wide resting potential gradients. The BETSE platform will enable a deep understanding of local and long-range bioelectrical dynamics in tissues, and assist the development of specific interventions to achieve greater control of pattern during morphogenesis and remodeling. PMID:27458581

Assessing global vegetation activity using spatio-temporal Bayesian modelling

NASA Astrophysics Data System (ADS)

Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

2016-04-01

This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support our hypothesis. That is, the change of vegetation in space and time may be better understood when modelling vegetation change as both a dynamic and multivariate process. Therefore, future research will focus on a multivariate dynamical spatio-temporal modelling approach. This ongoing research is performed within the context of the project "Global impacts of hydrological and climatic extremes on vegetation" (project acronym: SAT-EX) which is part of the Belgian research programme for Earth Observation Stereo III.

The statistics of local motion signals in naturalistic movies

PubMed Central

Nitzany, Eyal I.; Victor, Jonathan D.

2014-01-01

Extraction of motion from visual input plays an important role in many visual tasks, such as separation of figure from ground and navigation through space. Several kinds of local motion signals have been distinguished based on mathematical and computational considerations (e.g., motion based on spatiotemporal correlation of luminance, and motion based on spatiotemporal correlation of flicker), but little is known about the prevalence of these different kinds of signals in the real world. To address this question, we first note that different kinds of local motion signals (e.g., Fourier, non-Fourier, and glider) are characterized by second- and higher-order correlations in slanted spatiotemporal regions. The prevalence of local motion signals in natural scenes can thus be estimated by measuring the extent to which each of these correlations are present in space-time patches and whether they are coherent across spatiotemporal scales. We apply this technique to several popular movies. The results show that all three kinds of local motion signals are present in natural movies. While the balance of the different kinds of motion signals varies from segment to segment during the course of each movie, the overall pattern of prevalence of the different kinds of motion and their subtypes, and the correlations between them, is strikingly similar across movies (but is absent from white noise movies). In sum, naturalistic movies contain a diversity of local motion signals that occur with a consistent prevalence and pattern of covariation, indicating a substantial regularity of their high-order spatiotemporal image statistics. PMID:24732243

[Mortality from Suicide in the Municipalities of Mainland Portugal: Spatio-Temporal Evolution between 1980 and 2015].

PubMed

Loureiro, Adriana; Almendra, Ricardo; Costa, Cláudia; Santana, Paula

2018-01-31

Suicide is considered a public health priority. It is a complex phenomenon resulting from the interaction of several factors, which do not depend solely on individual conditions. This study analyzes the spatio-temporal evolution of suicide mortality between 1980 and 2015, identifying areas of high risk, and their variation, in the 278 municipalities of Continental Portugal. Based on the number of self-inflicted injuries and deaths from suicide and the resident population, the spatio-temporal evolution of the suicide mortality rate was assessed via: i) a Poisson joinpoint regression model, and ii) spatio-temporal clustering methods. The suicide mortality rate evolution showed statistically significant increases over three periods (1980 - 1984; 1999 - 2002 and 2006 - 2015) and two statistically significant periods of decrease (1984 - 1995 and 1995 - 1999). The spatio-temporal analysis identified five clusters of high suicide risk (relative risk >1) and four clusters of low suicide risk (relative risk < 1). The periods when suicide mortality increases seem to overlap with times of economic and financial instability. The geographical pattern of suicide risk has changed: presently, the suicide rates from the municipalities in the Center and North are showing more similarity with those seen in the South, thus increasing the ruralization of the phenomenon of suicide. Between 1980 and 2015 the spacio-temporal pattern of mortality from suicide has been changing and is a phenomenon that is currently experiencing a growing trend (since 2006) and is of higher risk in rural areas.

The statistics of local motion signals in naturalistic movies.

PubMed

Nitzany, Eyal I; Victor, Jonathan D

2014-04-14

Extraction of motion from visual input plays an important role in many visual tasks, such as separation of figure from ground and navigation through space. Several kinds of local motion signals have been distinguished based on mathematical and computational considerations (e.g., motion based on spatiotemporal correlation of luminance, and motion based on spatiotemporal correlation of flicker), but little is known about the prevalence of these different kinds of signals in the real world. To address this question, we first note that different kinds of local motion signals (e.g., Fourier, non-Fourier, and glider) are characterized by second- and higher-order correlations in slanted spatiotemporal regions. The prevalence of local motion signals in natural scenes can thus be estimated by measuring the extent to which each of these correlations are present in space-time patches and whether they are coherent across spatiotemporal scales. We apply this technique to several popular movies. The results show that all three kinds of local motion signals are present in natural movies. While the balance of the different kinds of motion signals varies from segment to segment during the course of each movie, the overall pattern of prevalence of the different kinds of motion and their subtypes, and the correlations between them, is strikingly similar across movies (but is absent from white noise movies). In sum, naturalistic movies contain a diversity of local motion signals that occur with a consistent prevalence and pattern of covariation, indicating a substantial regularity of their high-order spatiotemporal image statistics.

Simulations of Western North American Hydroclimate during the Little Ice Age and Medieval Climate Anomaly

NASA Astrophysics Data System (ADS)

Simon, S. M.; Mann, M. E.; Steinman, B. A.; Feng, S.; Zhang, Y.; Miller, S. K.

2013-12-01

Despite the immense impact that large, modern North American droughts, such as those of the 1930s and 1950s, have had on economic, social, aquacultural, and agricultural systems, they are smaller in duration and magnitude than the multidecadal megadroughts that affected North America, in particular the western United States, during the Medieval Climate Anomaly (MCA, ~ 900-1300 AD) and the Little Age (LIA, ~1450-1850 AD). Although various proxy records have been used to reconstruct the timing of these MCA and LIA megadroughts in the western United States, there still exists great uncertainty in the magnitude and spatial coherence of such droughts in the Pacific Northwest region, especially on decadal to centennial timescales. This uncertainty motivates the following study to establish a causal link between the climate forcing that induced these megadroughts and the spatiotemporal response of regional North American hydroclimates to this forcing. This study seeks to establish a better understanding of the influence of tropical Pacific and North Atlantic SSTs on North American drought during the MCA and LIA. We force NCAR's Community Atmospheric Model version 5.1.1 (CAM 5) with prescribed proxy-reconstructed tropical Pacific and North Atlantic SST anomalies from the MCA and LIA, in order to investigate the influence that these SST anomalies had on the spatiotemporal patterns of drought in North America. To isolate the effects of individual ocean basin SSTs on the North American climate system, the model experiments use a variety of SST permutations in the tropical Pacific and North Atlantic basin as external forcing. In order to quantify the spatiotemporal response of the North American climate system to these SST forcing permutations, temperature and precipitation data derived from the MCA and LIA model experiments are compared to lake sediment isotope and tree ring-based hydroclimate reconstructions from the Pacific Northwest. The spatiotemporal temperature and precipitation patterns from the model experiments indicate that in the Pacific Northwest, the MCA and LIA were anomalously wet and dry periods, respectively, a finding that is largely supported by the lake sediment records. This pattern contrasts with the dry MCA/wet LIA pattern diagnosed in model experiments for the U.S Southwest and indicated by tree ring-based proxy data. Thus, the CAM 5 model experiments confirm the wet/dry dipole pattern suggested by proxy data for the western U.S. during the MCA and LIA and highlights the role that the natural variability of tropical Pacific and North Atlantic SSTs played in driving this spatiotemporal climate pattern and its related teleconnections.

Wide-threat detection: recognition of adversarial missions and activity patterns in Empire Challenge 2009

NASA Astrophysics Data System (ADS)

Levchuk, Georgiy; Shabarekh, Charlotte; Furjanic, Caitlin

2011-06-01

In this paper, we present results of adversarial activity recognition using data collected in the Empire Challenge (EC 09) exercise. The EC09 experiment provided an opportunity to evaluate our probabilistic spatiotemporal mission recognition algorithms using the data from live air-born and ground sensors. Using ambiguous and noisy data about locations of entities and motion events on the ground, the algorithms inferred the types and locations of OPFOR activities, including reconnaissance, cache runs, IED emplacements, logistics, and planning meetings. In this paper, we present detailed summary of the validation study and recognition accuracy results. Our algorithms were able to detect locations and types of over 75% of hostile activities in EC09 while producing 25% false alarms.

Spatiotemporal Patterns and its Instability of Land Use Change in Five Chinese Node Cities of the Belt and Road

NASA Astrophysics Data System (ADS)

Quan, B.; Guo, T.; Liu, P. L.; Ren, H. G.

2017-09-01

It has long recognized that there exists three different terrain belt in China, i.e. east, central, and west can have very different impacts on the land use changes. It is therefore better understand how spatiotemporal patterns linked with processes and instability of land use change are evolving in China across different regions. This paper compares trends of the similarities and differences to understand the spatiotemporal characteristics and the linked processes i.e. states, incidents and instability of land use change of 5 Chinese cities which are located in the nodes of The Silk Road in China. The results show that on the whole, the more land transfer times and the more land categories involved changes happens in Quanzhou City, one of eastern China than those in central and western China. Basically, cities in central and western China such as Changsha, Kunming and Urumuqi City become instable while eastern city like Quanzhou City turns to be stable over time.

Electric organ discharges and near-field spatiotemporal patterns of the electromotive force in a sympatric assemblage of Neotropical electric knifefish.

PubMed

Waddell, Joseph C; Rodríguez-Cattáneo, Alejo; Caputi, Angel A; Crampton, William G R

2016-10-01

Descriptions of the head-to-tail electric organ discharge (ht-EOD) waveform - typically recorded with electrodes at a distance of approximately 1-2 body lengths from the center of the subject - have traditionally been used to characterize species diversity in gymnotiform electric fish. However, even taxa with relatively simple ht-EODs show spatiotemporally complex fields near the body surface that are determined by site-specific electrogenic properties of the electric organ and electric filtering properties of adjacent tissues and skin. In Brachyhypopomus, a pulse-discharging genus in the family Hypopomidae, the regional characteristics of the electric organ and the role that the complex 'near field' plays in communication and/or electrolocation are not well known. Here we describe, compare, and discuss the functional significance of diversity in the ht-EOD waveforms and near-field spatiotemporal patterns of the electromotive force (emf-EODs) among a species-rich sympatric community of Brachyhypopomus from the upper Amazon. Copyright © 2016 Elsevier Ltd. All rights reserved.

Chimera states in spatiotemporal systems: Theory and Applications

NASA Astrophysics Data System (ADS)

Yao, Nan; Zheng, Zhigang

2016-03-01

In this paper, we propose a retrospective and summary on recent studies of chimera states. Chimera states demonstrate striking inhomogeneous spatiotemporal patterns emerging in homogeneous systems through unexpected spontaneous symmetry breaking, where the consequent spatiotemporal patterns are composed of both coherence and incoherence domains, respectively characterized by the synchronized and desynchronized motions of oscillators. Since the discovery of chimera states by Kuramoto and others, this striking collective behavior has attracted a great deal of research interest in the community of physics and related interdisciplinary fields from both theoretical and experimental viewpoints. In recent works exploring chimera states, rich phenomena such as the spiral wave chimera, multiple cluster chimera, amplitude chimera were observed from various types of model systems. Theoretical framework by means of self-consistency approach and Ott-Antonsen approach were proposed for further understanding to this symmetry-breaking-induced behavior. The stability and robustness of chimera states were also discussed. More importantly, experiments ranging from optical, chemical to mechanical designs successfully approve the existence of chimera states.

Discovering Coherent Structures Using Local Causal States

NASA Astrophysics Data System (ADS)

Rupe, Adam; Crutchfield, James P.; Kashinath, Karthik; Prabhat, Mr.

2017-11-01

Coherent structures were introduced in the study of fluid dynamics and were initially defined as regions characterized by high levels of coherent vorticity, i.e. regions where instantaneously space and phase correlated vorticity are high. In a more general spatiotemporal setting, coherent structures can be seen as localized broken symmetries which persist in time. Building off the computational mechanics framework, which integrates tools from computation and information theory to capture pattern and structure in nonlinear dynamical systems, we introduce a theory of coherent structures, in the more general sense. Central to computational mechanics is the causal equivalence relation, and a local spatiotemporal generalization of it is used to construct the local causal states, which are utilized to uncover a system's spatiotemporal symmetries. Coherent structures are then identified as persistent, localized deviations from these symmetries. We illustrate how novel patterns and structures can be discovered in cellular automata and outline the path from them to laminar, transitional and turbulent flows. Funded by Intel through the Big Data Center at LBNL and the IPCC at UC Davis.

Energy prediction using spatiotemporal pattern networks

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

Jiang, Zhanhong; Liu, Chao; Akintayo, Adedotun

This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamical filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependencies among different sub-systems. To quantify causal dependencies, a mutual information based metric is presented and an energy prediction approach is subsequently proposed based on the STPN framework. To validate the proposed scheme, two case studies are presented, one involving wind turbine power prediction (supply side energy) using the Western Wind Integration data set generated bymore » the National Renewable Energy Laboratory (NREL) for identifying spatiotemporal characteristics, and the other, residential electric energy disaggregation (demand side energy) using the Building America 2010 data set from NREL for exploring temporal features. In the energy disaggregation context, convex programming techniques beyond the STPN framework are developed and applied to achieve improved disaggregation performance.« less

Violence in the prehistoric period of Japan: the spatio-temporal pattern of skeletal evidence for violence in the Jomon period.

PubMed

Nakao, Hisashi; Tamura, Kohei; Arimatsu, Yui; Nakagawa, Tomomi; Matsumoto, Naoko; Matsugi, Takehiko

2016-03-01

Whether man is predisposed to lethal violence, ranging from homicide to warfare, and how that may have impacted human evolution, are among the most controversial topics of debate on human evolution. Although recent studies on the evolution of warfare have been based on various archaeological and ethnographic data, they have reported mixed results: it is unclear whether or not warfare among prehistoric hunter-gatherers was common enough to be a component of human nature and a selective pressure for the evolution of human behaviour. This paper reports the mortality attributable to violence, and the spatio-temporal pattern of violence thus shown among ancient hunter-gatherers using skeletal evidence in prehistoric Japan (the Jomon period: 13 000 cal BC-800 cal BC). Our results suggest that the mortality due to violence was low and spatio-temporally highly restricted in the Jomon period, which implies that violence including warfare in prehistoric Japan was not common. © 2016 The Author(s).

Violence in the prehistoric period of Japan: the spatio-temporal pattern of skeletal evidence for violence in the Jomon period

PubMed Central

Nakao, Hisashi; Tamura, Kohei; Arimatsu, Yui; Nakagawa, Tomomi; Matsumoto, Naoko; Matsugi, Takehiko

2016-01-01

Whether man is predisposed to lethal violence, ranging from homicide to warfare, and how that may have impacted human evolution, are among the most controversial topics of debate on human evolution. Although recent studies on the evolution of warfare have been based on various archaeological and ethnographic data, they have reported mixed results: it is unclear whether or not warfare among prehistoric hunter–gatherers was common enough to be a component of human nature and a selective pressure for the evolution of human behaviour. This paper reports the mortality attributable to violence, and the spatio-temporal pattern of violence thus shown among ancient hunter–gatherers using skeletal evidence in prehistoric Japan (the Jomon period: 13 000 cal BC–800 cal BC). Our results suggest that the mortality due to violence was low and spatio-temporally highly restricted in the Jomon period, which implies that violence including warfare in prehistoric Japan was not common. PMID:27029838

Early-warning signals for catastrophic soil degradation

NASA Astrophysics Data System (ADS)

Karssenberg, Derek

2010-05-01

Many earth systems have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been described, among others, for climate, vegetation, animal populations, and geomorphology. Predicting the timing of critical transitions before they are reached is of importance because of the large impact on nature and society associated with the transition. However, it is notably difficult to predict the timing of a transition. This is because the state variables of the system show little change before the threshold is reached. As a result, the precision of field observations is often too low to provide predictions of the timing of a transition. A possible solution is the use of spatio-temporal patterns in state variables as leading indicators of a transition. It is becoming clear that the critically slowing down of a system causes spatio-temporal autocorrelation and variance to increase before the transition. Thus, spatio-temporal patterns are important candidates for early-warning signals. In this research we will show that these early-warning signals also exist in geomorphological systems. We consider a modelled vegetation-soil system under a gradually increasing grazing pressure causing an abrupt shift towards extensive soil degradation. It is shown that changes in spatio-temporal patterns occur well ahead of this catastrophic transition. A distributed model describing the coupled processes of vegetation growth and geomorphological denudation is adapted. The model uses well-studied simple process representations for vegetation and geomorphology. A logistic growth model calculates vegetation cover as a function of grazing pressure and vegetation growth rate. Evolution of the soil thickness is modelled by soil creep and wash processes, as a function of net rain reaching the surface. The vegetation and soil system are coupled by 1) decreasing vegetation growth with decreasing soil thickness and 2) increasing soil wash with decreasing vegetation cover. The model describes a critical, catastrophic transition of an underexploited system with low grazing pressure towards an overexploited system. The underexploited state has high vegetation cover and well developed soils, while the overexploited state has low vegetation cover and largely degraded soils. We first show why spatio-temporal patterns in vegetation cover, morphology, erosion rate, and sediment load should be expected to change well before the critical transition towards the overexploited state. Subsequently, spatio-temporal patterns are quantified by calculating statistics, in particular first order statistics and autocorrelation in space and time. It is shown that these statistics gradually change before the transition is reached. This indicates that the statistics may serve as early-warning signals in real-world applications. We also discuss the potential use of remote sensing to predict the critical transition in real-world landscapes.

Indo-Pacific Variability on Seasonal to Multidecadal Time Scales. Part I: Intrinsic SST Modes in Models and Observations

NASA Astrophysics Data System (ADS)

Slawinska, Joanna; Giannakis, Dimitrios

2017-07-01

The variability of Indo-Pacific SST on seasonal to multidecadal timescales is investigated using a recently introduced technique called nonlinear Laplacian spectral analysis (NLSA). Through this technique, drawbacks associated with ad hoc pre-filtering of the input data are avoided, enabling recovery of low-frequency and intermittent modes not previously accessible via classical approaches. Here, a multiscale hierarchy of spatiotemporal modes is identified for Indo-Pacific SST in millennial control runs of CCSM4 and CM3 and in HadISST data. On interannual timescales, a mode with spatiotemporal patterns corresponding to the fundamental component of ENSO emerges, along with ENSO-modulated annual modes consistent with combination mode theory. The ENSO combination modes also feature prominent activity in the Indian Ocean, explaining significant fraction of the SST variance in regions associated with the Indian Ocean dipole. A pattern resembling the tropospheric biennial oscillation emerges in addition to ENSO and the associated combination modes. On multidecadal timescales, the dominant NLSA mode in the model data is predominantly active in the western tropical Pacific. The interdecadal Pacific oscillation also emerges as a distinct NLSA mode, though with smaller explained variance than the western Pacific multidecadal mode. Analogous modes on interannual and decadal timescales are also identified in HadISST data for the industrial era, as well as in model data of comparable timespan, though decadal modes are either absent or of degraded quality in these datasets.

Development of five digits is controlled by a bipartite long-range cis-regulator

PubMed Central

Lettice, Laura A.; Williamson, Iain; Devenney, Paul S.; Kilanowski, Fiona; Dorin, Julia; Hill, Robert E.

2014-01-01

Conservation within intergenic DNA often highlights regulatory elements that control gene expression from a long range. How conservation within a single element relates to regulatory information and how internal composition relates to function is unknown. Here, we examine the structural features of the highly conserved ZRS (also called MFCS1) cis-regulator responsible for the spatiotemporal control of Shh in the limb bud. By systematically dissecting the ZRS, both in transgenic assays and within in the endogenous locus, we show that the ZRS is, in effect, composed of two distinct domains of activity: one domain directs spatiotemporal activity but functions predominantly from a short range, whereas a second domain is required to promote long-range activity. We show further that these two domains encode activities that are highly integrated and that the second domain is crucial in promoting the chromosomal conformational changes correlated with gene activity. During limb bud development, these activities encoded by the ZRS are interpreted differently by the fore limbs and the hind limbs; in the absence of the second domain there is no Shh activity in the fore limb, and in the hind limb low levels of Shh lead to a variant digit pattern ranging from two to four digits. Hence, in the embryo, the second domain stabilises the developmental programme providing a buffer for SHH morphogen activity and this ensures that five digits form in both sets of limbs. PMID:24715461

Multiscale energy reallocation during low-frequency steady-state brain response.

PubMed

Wang, Yifeng; Chen, Wang; Ye, Liangkai; Biswal, Bharat B; Yang, Xuezhi; Zou, Qijun; Yang, Pu; Yang, Qi; Wang, Xinqi; Cui, Qian; Duan, Xujun; Liao, Wei; Chen, Huafu

2018-05-01

Traditional task-evoked brain activations are based on detection and estimation of signal change from the mean signal. By contrast, the low-frequency steady-state brain response (lfSSBR) reflects frequency-tagging activity at the fundamental frequency of the task presentation and its harmonics. Compared to the activity at these resonant frequencies, brain responses at nonresonant frequencies are largely unknown. Additionally, because the lfSSBR is defined by power change, we hypothesize using Parseval's theorem that the power change reflects brain signal variability rather than the change of mean signal. Using a face recognition task, we observed power increase at the fundamental frequency (0.05 Hz) and two harmonics (0.1 and 0.15 Hz) and power decrease within the infra-slow frequency band (<0.1 Hz), suggesting a multifrequency energy reallocation. The consistency of power and variability was demonstrated by the high correlation (r > .955) of their spatial distribution and brain-behavior relationship at all frequency bands. Additionally, the reallocation of finite energy was observed across various brain regions and frequency bands, forming a particular spatiotemporal pattern. Overall, results from this study strongly suggest that frequency-specific power and variability may measure the same underlying brain activity and that these results may shed light on different mechanisms between lfSSBR and brain activation, and spatiotemporal characteristics of energy reallocation induced by cognitive tasks. © 2018 Wiley Periodicals, Inc.

Spatiotemporal commonalities of fronto-parietal activation in attentional orienting triggered by supraliminal and subliminal gaze cues: An event-related potential study.

PubMed

Uono, Shota; Sato, Wataru; Sawada, Reiko; Kochiyama, Takanori; Toichi, Motomi

2018-05-04

Eye gaze triggers attentional shifts with and without conscious awareness. It remains unclear whether the spatiotemporal patterns of electric neural activity are the same for conscious and unconscious attentional shifts. Thus, the present study recorded event-related potentials (ERPs) and evaluated the neural activation involved in attentional orienting induced by subliminal and supraliminal gaze cues. Nonpredictive gaze cues were presented in the central field of vision, and participants were asked to detect a subsequent peripheral target. The mean reaction time was shorter for congruent gaze cues than for incongruent gaze cues under both presentation conditions, indicating that both types of cues reliably trigger attentional orienting. The ERP analysis revealed that averted versus straight gaze induced greater negative deflection in the bilateral fronto-central and temporal regions between 278 and 344 ms under both supraliminal and subliminal presentation conditions. Supraliminal cues, irrespective of gaze direction, induced a greater negative amplitude than did subliminal cues at the right posterior cortices at a peak of approximately 170 ms and in the 200-300 ms. These results suggest that similar spatial and temporal fronto-parietal activity is involved in attentional orienting triggered by both supraliminal and subliminal gaze cues, although inputs from different visual processing routes (cortical and subcortical regions) may trigger activity in the attentional network. Copyright © 2018 Elsevier B.V. All rights reserved.

Leaders and followers: quantifying consistency in spatio-temporal propagation patterns

NASA Astrophysics Data System (ADS)

Kreuz, Thomas; Satuvuori, Eero; Pofahl, Martin; Mulansky, Mario

2017-04-01

Repetitive spatio-temporal propagation patterns are encountered in fields as wide-ranging as climatology, social communication and network science. In neuroscience, perfectly consistent repetitions of the same global propagation pattern are called a synfire pattern. For any recording of sequences of discrete events (in neuroscience terminology: sets of spike trains) the questions arise how closely it resembles such a synfire pattern and which are the spike trains that lead/follow. Here we address these questions and introduce an algorithm built on two new indicators, termed SPIKE-order and spike train order, that define the synfire indicator value, which allows to sort multiple spike trains from leader to follower and to quantify the consistency of the temporal leader-follower relationships for both the original and the optimized sorting. We demonstrate our new approach using artificially generated datasets before we apply it to analyze the consistency of propagation patterns in two real datasets from neuroscience (giant depolarized potentials in mice slices) and climatology (El Niño sea surface temperature recordings). The new algorithm is distinguished by conceptual and practical simplicity, low computational cost, as well as flexibility and universality.

Which EEG patterns in coma are nonconvulsive status epilepticus?

PubMed

Trinka, Eugen; Leitinger, Markus

2015-08-01

Nonconvulsive status epilepticus (NCSE) is common in patients with coma with a prevalence between 5% and 48%. Patients in deep coma may exhibit epileptiform EEG patterns, such as generalized periodic spikes, and there is an ongoing debate about the relationship of these patterns and NCSE. The purposes of this review are (i) to discuss the various EEG patterns found in coma, its fluctuations, and transitions and (ii) to propose modified criteria for NCSE in coma. Classical coma patterns such as diffuse polymorphic delta activity, spindle coma, alpha/theta coma, low output voltage, or burst suppression do not reflect NCSE. Any ictal patterns with a typical spatiotemporal evolution or epileptiform discharges faster than 2.5 Hz in a comatose patient reflect nonconvulsive seizures or NCSE and should be treated. Generalized periodic diacharges or lateralized periodic discharges (GPDs/LPDs) with a frequency of less than 2.5 Hz or rhythmic discharges (RDs) faster than 0.5 Hz are the borderland of NCSE in coma. In these cases, at least one of the additional criteria is needed to diagnose NCSE (a) subtle clinical ictal phenomena, (b) typical spatiotemporal evolution, or (c) response to antiepileptic drug treatment. There is currently no consensus about how long these patterns must be present to qualify for NCSE, and the distinction from nonconvulsive seizures in patients with critical illness or in comatose patients seems arbitrary. The Salzburg Consensus Criteria for NCSE [1] have been modified according to the Standardized Terminology of the American Clinical Neurophysiology Society [2] and validated in three different cohorts, with a sensitivity of 97.2%, a specificity of 95.9%, and a diagnostic accuracy of 96.3% in patients with clinical signs of NCSE. Their diagnostic utility in different cohorts with patients in deep coma has to be studied in the future. This article is part of a Special Issue entitled "Status Epilepticus". Copyright © 2015. Published by Elsevier Inc.

Spatiotemporal Dynamics and Reliable Computations in Recurrent Spiking Neural Networks

NASA Astrophysics Data System (ADS)

Pyle, Ryan; Rosenbaum, Robert

2017-01-01

Randomly connected networks of excitatory and inhibitory spiking neurons provide a parsimonious model of neural variability, but are notoriously unreliable for performing computations. We show that this difficulty is overcome by incorporating the well-documented dependence of connection probability on distance. Spatially extended spiking networks exhibit symmetry-breaking bifurcations and generate spatiotemporal patterns that can be trained to perform dynamical computations under a reservoir computing framework.

Spatio-Temporal Change Modeling of Lulc: a Semantic Kriging Approach

NASA Astrophysics Data System (ADS)

Bhattacharjee, S.; Ghosh, S. K.

2015-07-01

Spatio-temporal land-use/ land-cover (LULC) change modeling is important to forecast the future LULC distribution, which may facilitate natural resource management, urban planning, etc. The spatio-temporal change in LULC trend often exhibits non-linear behavior, due to various dynamic factors, such as, human intervention (e.g., urbanization), environmental factors, etc. Hence, proper forecasting of LULC distribution should involve the study and trend modeling of historical data. Existing literatures have reported that the meteorological attributes (e.g., NDVI, LST, MSI), are semantically related to the terrain. Being influenced by the terrestrial dynamics, the temporal changes of these attributes depend on the LULC properties. Hence, incorporating meteorological knowledge into the temporal prediction process may help in developing an accurate forecasting model. This work attempts to study the change in inter-annual LULC pattern and the distribution of different meteorological attributes of a region in Kolkata (a metropolitan city in India) during the years 2000-2010 and forecast the future spread of LULC using semantic kriging (SemK) approach. A new variant of time-series SemK is proposed, namely Rev-SemKts to capture the multivariate semantic associations between different attributes. From empirical analysis, it may be observed that the augmentation of semantic knowledge in spatio-temporal modeling of meteorological attributes facilitate more precise forecasting of LULC pattern.

Synchronization stability and pattern selection in a memristive neuronal network.

PubMed

Wang, Chunni; Lv, Mi; Alsaedi, Ahmed; Ma, Jun

2017-11-01

Spatial pattern formation and selection depend on the intrinsic self-organization and cooperation between nodes in spatiotemporal systems. Based on a memory neuron model, a regular network with electromagnetic induction is proposed to investigate the synchronization and pattern selection. In our model, the memristor is used to bridge the coupling between the magnetic flux and the membrane potential, and the induction current results from the time-varying electromagnetic field contributed by the exchange of ion currents and the distribution of charged ions. The statistical factor of synchronization predicts the transition of synchronization and pattern stability. The bifurcation analysis of the sampled time series for the membrane potential reveals the mode transition in electrical activity and pattern selection. A formation mechanism is outlined to account for the emergence of target waves. Although an external stimulus is imposed on each neuron uniformly, the diversity in the magnetic flux and the induction current leads to emergence of target waves in the studied network.

Generation of shape complexity through tissue conflict resolution

PubMed Central

Rebocho, Alexandra B; Southam, Paul; Kennaway, J Richard; Coen, Enrico

2017-01-01

Out-of-plane tissue deformations are key morphogenetic events during plant and animal development that generate 3D shapes, such as flowers or limbs. However, the mechanisms by which spatiotemporal patterns of gene expression modify cellular behaviours to generate such deformations remain to be established. We use the Snapdragon flower as a model system to address this problem. Combining cellular analysis with tissue-level modelling, we show that an orthogonal pattern of growth orientations plays a key role in generating out-of-plane deformations. This growth pattern is most likely oriented by a polarity field, highlighted by PIN1 protein localisation, and is modulated by dorsoventral gene activity. The orthogonal growth pattern interacts with other patterns of differential growth to create tissue conflicts that shape the flower. Similar shape changes can be generated by contraction as well as growth, suggesting tissue conflict resolution provides a flexible morphogenetic mechanism for generating shape diversity in plants and animals. DOI: http://dx.doi.org/10.7554/eLife.20156.001 PMID:28166865

Synchronization stability and pattern selection in a memristive neuronal network

NASA Astrophysics Data System (ADS)

Wang, Chunni; Lv, Mi; Alsaedi, Ahmed; Ma, Jun

2017-11-01

Spatial pattern formation and selection depend on the intrinsic self-organization and cooperation between nodes in spatiotemporal systems. Based on a memory neuron model, a regular network with electromagnetic induction is proposed to investigate the synchronization and pattern selection. In our model, the memristor is used to bridge the coupling between the magnetic flux and the membrane potential, and the induction current results from the time-varying electromagnetic field contributed by the exchange of ion currents and the distribution of charged ions. The statistical factor of synchronization predicts the transition of synchronization and pattern stability. The bifurcation analysis of the sampled time series for the membrane potential reveals the mode transition in electrical activity and pattern selection. A formation mechanism is outlined to account for the emergence of target waves. Although an external stimulus is imposed on each neuron uniformly, the diversity in the magnetic flux and the induction current leads to emergence of target waves in the studied network.

An Online Atlas for Exploring Spatio-Temporal Patterns of Cancer Mortality (1972–2011) and Incidence (1995–2008) in Taiwan

PubMed Central

Ku, Wen-Yuan; Liaw, Yung-Po; Huang, Jing-Yang; Nfor, Oswald Ndi; Hsu, Shu-Yi; Ko, Pei-Chieh; Lee, Wen-Chung; Chen, Chien-Jen

2016-01-01

Abstract Public health mapping and Geographical Information Systems (GIS) are already being used to locate the geographical spread of diseases. This study describes the construction of an easy-to-use online atlas of cancer mortality (1972–2011) and incidence (1995–2008) in Taiwan. Two sets of color maps were made based on “age-adjusted mortality by rate” and “age-adjusted mortality by rank.” AJAX (Asynchronous JavaScript and XML), JSON (JavaScript Object Notation), and SVG (Scaling Vector Graphic) were used to create the online atlas. Spatio-temporal patterns of cancer mortality and incidence in Taiwan over the period from 1972 to 2011 and from 1995 to 2008. The constructed online atlas contains information on cancer mortality and incidence (http://taiwancancermap.csmu-liawyp.tw/). The common GIS functions include zoom and pan and identity tools. Users can easily customize the maps to explore the spatio-temporal trends of cancer mortality and incidence using different devices (such as personal computers, mobile phone, or pad). This study suggests an easy- to-use, low-cost, and independent platform for exploring cancer incidence and mortality. It is expected to serve as a reference tool for cancer prevention and risk assessment. This online atlas is a cheap and fast tool that integrates various cancer maps. Therefore, it can serve as a powerful tool that allows users to examine and compare spatio-temporal patterns of various maps. Furthermore, it is an-easy-to use tool for updating data and assessing risk factors of cancer in Taiwan. PMID:27227915

An Online Atlas for Exploring Spatio-Temporal Patterns of Cancer Mortality (1972-2011) and Incidence (1995-2008) in Taiwan.

PubMed

Ku, Wen-Yuan; Liaw, Yung-Po; Huang, Jing-Yang; Nfor, Oswald Ndi; Hsu, Shu-Yi; Ko, Pei-Chieh; Lee, Wen-Chung; Chen, Chien-Jen

2016-05-01

Public health mapping and Geographical Information Systems (GIS) are already being used to locate the geographical spread of diseases. This study describes the construction of an easy-to-use online atlas of cancer mortality (1972-2011) and incidence (1995-2008) in Taiwan.Two sets of color maps were made based on "age-adjusted mortality by rate" and "age-adjusted mortality by rank." AJAX (Asynchronous JavaScript and XML), JSON (JavaScript Object Notation), and SVG (Scaling Vector Graphic) were used to create the online atlas. Spatio-temporal patterns of cancer mortality and incidence in Taiwan over the period from 1972 to 2011 and from 1995 to 2008.The constructed online atlas contains information on cancer mortality and incidence (http://taiwancancermap.csmu-liawyp.tw/). The common GIS functions include zoom and pan and identity tools. Users can easily customize the maps to explore the spatio-temporal trends of cancer mortality and incidence using different devices (such as personal computers, mobile phone, or pad). This study suggests an easy- to-use, low-cost, and independent platform for exploring cancer incidence and mortality. It is expected to serve as a reference tool for cancer prevention and risk assessment.This online atlas is a cheap and fast tool that integrates various cancer maps. Therefore, it can serve as a powerful tool that allows users to examine and compare spatio-temporal patterns of various maps. Furthermore, it is an-easy-to use tool for updating data and assessing risk factors of cancer in Taiwan.

Comparative Epidemiology of Highly Pathogenic Avian Influenza Virus H5N1 and H5N6 in Vietnamese Live Bird Markets: Spatiotemporal Patterns of Distribution and Risk Factors.

PubMed

Mellor, Kate C; Meyer, Anne; Elkholly, Doaa A; Fournié, Guillaume; Long, Pham T; Inui, Ken; Padungtod, Pawin; Gilbert, Marius; Newman, Scott H; Vergne, Timothée; Pfeiffer, Dirk U; Stevens, Kim B

2018-01-01

Highly pathogenic avian influenza (HPAI) H5N1 virus has been circulating in Vietnam since 2003, whilst outbreaks of HPAI H5N6 virus are more recent, having only been reported since 2014. Although the spatial distribution of H5N1 outbreaks and risk factors for virus occurrence has been extensively studied, there have been no comparative studies for H5N6. Data collected through active surveillance of Vietnamese live bird markets (LBMs) between 2011 and 2015 were used to explore and compare the spatiotemporal distributions of H5N1- and H5N6-positive LBMs. Conditional autoregressive models were developed to quantify spatiotemporal associations between agroecological factors and the two HPAI strains using the same set of predictor variables. Unlike H5N1, which exhibited a strong north-south divide, with repeated occurrence in the extreme south of a cluster of high-risk provinces, H5N6 was homogeneously distributed throughout Vietnam. Similarly, different agroecological factors were associated with each strain. Sample collection in the months of January and February and higher average maximum temperature were associated with higher likelihood of H5N1-positive market-day status. The likelihood of market days being positive for H5N6 increased with decreased river density, and with successive Rounds of data collection. This study highlights marked differences in spatial patterns and risk factors for H5N1 and H5N6 in Vietnam, suggesting the need for tailored surveillance and control approaches.

Comparative Epidemiology of Highly Pathogenic Avian Influenza Virus H5N1 and H5N6 in Vietnamese Live Bird Markets: Spatiotemporal Patterns of Distribution and Risk Factors

PubMed Central

Mellor, Kate C.; Meyer, Anne; Elkholly, Doaa A.; Fournié, Guillaume; Long, Pham T.; Inui, Ken; Padungtod, Pawin; Gilbert, Marius; Newman, Scott H.; Vergne, Timothée; Pfeiffer, Dirk U.; Stevens, Kim B.

2018-01-01

Highly pathogenic avian influenza (HPAI) H5N1 virus has been circulating in Vietnam since 2003, whilst outbreaks of HPAI H5N6 virus are more recent, having only been reported since 2014. Although the spatial distribution of H5N1 outbreaks and risk factors for virus occurrence has been extensively studied, there have been no comparative studies for H5N6. Data collected through active surveillance of Vietnamese live bird markets (LBMs) between 2011 and 2015 were used to explore and compare the spatiotemporal distributions of H5N1- and H5N6-positive LBMs. Conditional autoregressive models were developed to quantify spatiotemporal associations between agroecological factors and the two HPAI strains using the same set of predictor variables. Unlike H5N1, which exhibited a strong north–south divide, with repeated occurrence in the extreme south of a cluster of high-risk provinces, H5N6 was homogeneously distributed throughout Vietnam. Similarly, different agroecological factors were associated with each strain. Sample collection in the months of January and February and higher average maximum temperature were associated with higher likelihood of H5N1-positive market-day status. The likelihood of market days being positive for H5N6 increased with decreased river density, and with successive Rounds of data collection. This study highlights marked differences in spatial patterns and risk factors for H5N1 and H5N6 in Vietnam, suggesting the need for tailored surveillance and control approaches. PMID:29675418

Novel Reporter for Faithful Monitoring of ERK2 Dynamics in Living Cells and Model Organisms

PubMed Central

Sipieter, François; Cappe, Benjamin; Gonzalez Pisfil, Mariano; Spriet, Corentin; Bodart, Jean-François; Cailliau-Maggio, Katia; Vandenabeele, Peter; Héliot, Laurent; Riquet, Franck B.

2015-01-01

Uncoupling of ERK1/2 phosphorylation from subcellular localization is essential towards the understanding of molecular mechanisms that control ERK1/2-mediated cell-fate decision. ERK1/2 non-catalytic functions and discoveries of new specific anchors responsible of the subcellular compartmentalization of ERK1/2 signaling pathway have been proposed as regulation mechanisms for which dynamic monitoring of ERK1/2 localization is necessary. However, studying the spatiotemporal features of ERK2, for instance, in different cellular processes in living cells and tissues requires a tool that can faithfully report on its subcellular distribution. We developed a novel molecular tool, ERK2-LOC, based on the T2A-mediated coexpression of strictly equimolar levels of eGFP-ERK2 and MEK1, to faithfully visualize ERK2 localization patterns. MEK1 and eGFP-ERK2 were expressed reliably and functionally both in vitro and in single living cells. We then assessed the subcellular distribution and mobility of ERK2-LOC using fluorescence microscopy in non-stimulated conditions and after activation/inhibition of the MAPK/ERK1/2 signaling pathway. Finally, we used our coexpression system in Xenopus laevis embryos during the early stages of development. This is the first report on MEK1/ERK2 T2A-mediated coexpression in living embryos, and we show that there is a strong correlation between the spatiotemporal subcellular distribution of ERK2-LOC and the phosphorylation patterns of ERK1/2. Our approach can be used to study the spatiotemporal localization of ERK2 and its dynamics in a variety of processes in living cells and embryonic tissues. PMID:26517832

The influence of the interactions between anthropogenic activities and multiple ecological factors on land surface temperatures of urban forests

NASA Astrophysics Data System (ADS)

Ren, Y.

2017-12-01

Context Land surface temperatures (LSTs) spatio-temporal distribution pattern of urban forests are influenced by many ecological factors; the identification of interaction between these factors can improve simulations and predictions of spatial patterns of urban cold islands. This quantitative research requires an integrated method that combines multiple sources data with spatial statistical analysis. Objectives The purpose of this study was to clarify urban forest LST influence interaction between anthropogenic activities and multiple ecological factors using cluster analysis of hot and cold spots and Geogdetector model. We introduced the hypothesis that anthropogenic activity interacts with certain ecological factors, and their combination influences urban forests LST. We also assumed that spatio-temporal distributions of urban forest LST should be similar to those of ecological factors and can be represented quantitatively. Methods We used Jinjiang as a representative city in China as a case study. Population density was employed to represent anthropogenic activity. We built up a multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) on a unified urban scale to support urban forest LST influence interaction research. Through a combination of spatial statistical analysis results, multi-source spatial data, and Geogdetector model, the interaction mechanisms of urban forest LST were revealed. Results Although different ecological factors have different influences on forest LST, in two periods with different hot spots and cold spots, the patch area and dominant tree species were the main factors contributing to LST clustering in urban forests. The interaction between anthropogenic activity and multiple ecological factors increased LST in urban forest stands, linearly and nonlinearly. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. Conclusions In conclusion, a combination of spatial statistics and GeogDetector models should be effective for quantitatively evaluating interactive relationships among ecological factors, anthropogenic activity and LST.

Small-Scale Spatio-Temporal Distribution of Bactrocera minax (Enderlein) (Diptera: Tephritidae) Using Probability Kriging.

PubMed

Wang, S Q; Zhang, H Y; Li, Z L

2016-10-01

Understanding spatio-temporal distribution of pest in orchards can provide important information that could be used to design monitoring schemes and establish better means for pest control. In this study, the spatial and temporal distribution of Bactrocera minax (Enderlein) (Diptera: Tephritidae) was assessed, and activity trends were evaluated by using probability kriging. Adults of B. minax were captured in two successive occurrences in a small-scale citrus orchard by using food bait traps, which were placed both inside and outside the orchard. The weekly spatial distribution of B. minax within the orchard and adjacent woods was examined using semivariogram parameters. The edge concentration was discovered during the most weeks in adult occurrence, and the population of the adults aggregated with high probability within a less-than-100-m-wide band on both of the sides of the orchard and the woods. The sequential probability kriged maps showed that the adults were estimated in the marginal zone with higher probability, especially in the early and peak stages. The feeding, ovipositing, and mating behaviors of B. minax are possible explanations for these spatio-temporal patterns. Therefore, spatial arrangement and distance to the forest edge of traps or spraying spot should be considered to enhance pest control on B. minax in small-scale orchards.

A cdk1 gradient guides surface contraction waves in oocytes.

PubMed

Bischof, Johanna; Brand, Christoph A; Somogyi, Kálmán; Májer, Imre; Thome, Sarah; Mori, Masashi; Schwarz, Ulrich S; Lénárt, Péter

2017-10-11

Surface contraction waves (SCWs) in oocytes and embryos lead to large-scale shape changes coupled to cell cycle transitions and are spatially coordinated with the cell axis. Here, we show that SCWs in the starfish oocyte are generated by a traveling band of myosin II-driven cortical contractility. At the front of the band, contractility is activated by removal of cdk1 inhibition of the RhoA/RhoA kinase/myosin II signaling module, while at the rear, contractility is switched off by negative feedback originating downstream of RhoA kinase. The SCW's directionality and speed are controlled by a spatiotemporal gradient of cdk1-cyclinB. This gradient is formed by the release of cdk1-cyclinB from the asymmetrically located nucleus, and progressive degradation of cyclinB. By combining quantitative imaging, biochemical and mechanical perturbations with mathematical modeling, we demonstrate that the SCWs result from the spatiotemporal integration of two conserved regulatory modules, cdk1-cyclinB for cell cycle regulation and RhoA/Rok/NMYII for actomyosin contractility.Surface contraction waves (SCWs) are prominent shape changes coupled to cell cycle transitions in oocytes. Here the authors show that SCWs are patterned by the spatiotemporal integration of two conserved modules, cdk1-cyclinB for cell cycle regulation and RhoA/Rok/NMYII for actomyosin contractility.

Excitatory Local Interneurons Enhance Tuning of Sensory Information

PubMed Central

Assisi, Collins; Stopfer, Mark; Bazhenov, Maxim

2012-01-01

Neurons in the insect antennal lobe represent odors as spatiotemporal patterns of activity that unfold over multiple time scales. As these patterns unspool they decrease the overlap between odor representations and thereby increase the ability of the olfactory system to discriminate odors. Using a realistic model of the insect antennal lobe we examined two competing components of this process –lateral excitation from local excitatory interneurons, and slow inhibition from local inhibitory interneurons. We found that lateral excitation amplified differences between representations of similar odors by recruiting projection neurons that did not receive direct input from olfactory receptors. However, this increased sensitivity also amplified noisy variations in input and compromised the ability of the system to respond reliably to multiple presentations of the same odor. Slow inhibition curtailed the spread of projection neuron activity and increased response reliability. These competing influences must be finely balanced in order to decorrelate odor representations. PMID:22807661

Muscle Coordination and Locomotion in Humans.

PubMed

Sylos-Labini, Francesca; Zago, Myrka; Guertin, Pierre A; Lacquaniti, Francesco; Ivanenko, Yury P

2017-01-01

Locomotion is a semi-automatic daily task. Several studies show that muscle activity is fairly stereotyped during normal walking. Nevertheless, each human leg contains over 50 muscles and locomotion requires flexibility in order to adapt to different conditions as, for instance, different speeds, gaits, turning, obstacle avoidance, altered gravity levels, etc. Therefore, locomotor control has to deal with a certain level of flexibility and non-linearity. In this review, we describe and discuss different findings dealing with both simplicity and variability of the muscular control, as well as with its maturation during development. Despite complexity and redundancy, muscle activity patterns and spatiotemporal maps of spinal motoneuron output during human locomotion show both stereotypical features as well as functional re-organization. Flexibility and different solutions to adjust motor patterns should be considered when considering new rehabilitation strategies to treat disorders involving deficits in gait. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Decoding memory features from hippocampal spiking activities using sparse classification models.

PubMed

Dong Song; Hampson, Robert E; Robinson, Brian S; Marmarelis, Vasilis Z; Deadwyler, Sam A; Berger, Theodore W

2016-08-01

To understand how memory information is encoded in the hippocampus, we build classification models to decode memory features from hippocampal CA3 and CA1 spatio-temporal patterns of spikes recorded from epilepsy patients performing a memory-dependent delayed match-to-sample task. The classification model consists of a set of B-spline basis functions for extracting memory features from the spike patterns, and a sparse logistic regression classifier for generating binary categorical output of memory features. Results show that classification models can extract significant amount of memory information with respects to types of memory tasks and categories of sample images used in the task, despite the high level of variability in prediction accuracy due to the small sample size. These results support the hypothesis that memories are encoded in the hippocampal activities and have important implication to the development of hippocampal memory prostheses.

A microfluidic device to study neuronal and motor responses to acute chemical stimuli in zebrafish.

PubMed

Candelier, Raphaël; Murmu, Meena Sriti; Romano, Sebastián Alejo; Jouary, Adrien; Debrégeas, Georges; Sumbre, Germán

2015-07-21

Zebrafish larva is a unique model for whole-brain functional imaging and to study sensory-motor integration in the vertebrate brain. To take full advantage of this system, one needs to design sensory environments that can mimic the complex spatiotemporal stimulus patterns experienced by the animal in natural conditions. We report on a novel open-ended microfluidic device that delivers pulses of chemical stimuli to agarose-restrained larvae with near-millisecond switching rate and unprecedented spatial and concentration accuracy and reproducibility. In combination with two-photon calcium imaging and recordings of tail movements, we found that stimuli of opposite hedonic values induced different circuit activity patterns. Moreover, by precisely controlling the duration of the stimulus (50-500 ms), we found that the probability of generating a gustatory-induced behavior is encoded by the number of neurons activated. This device may open new ways to dissect the neural-circuit principles underlying chemosensory perception.

Spatiotemporal analysis of land use and land cover change in the Brazilian Amazon

PubMed Central

Li, Guiying; Moran, Emilio; Hetrick, Scott

2013-01-01

This paper provides a comparative analysis of land use and land cover (LULC) changes among three study areas with different biophysical environments in the Brazilian Amazon at multiple scales, from per-pixel, polygon, census sector, to study area. Landsat images acquired in the years of 1990/1991, 1999/2000, and 2008/2010 were used to examine LULC change trajectories with the post-classification comparison approach. A classification system composed of six classes – forest, savanna, other-vegetation (secondary succession and plantations), agro-pasture, impervious surface, and water, was designed for this study. A hierarchical-based classification method was used to classify Landsat images into thematic maps. This research shows different spatiotemporal change patterns, composition and rates among the three study areas and indicates the importance of analyzing LULC change at multiple scales. The LULC change analysis over time for entire study areas provides an overall picture of change trends, but detailed change trajectories and their spatial distributions can be better examined at a per-pixel scale. The LULC change at the polygon scale provides the information of the changes in patch sizes over time, while the LULC change at census sector scale gives new insights on how human-induced activities (e.g., urban expansion, roads, and land use history) affect LULC change patterns and rates. This research indicates the necessity to implement change detection at multiple scales for better understanding the mechanisms of LULC change patterns and rates. PMID:24127130

Optimal design of a bank of spatio-temporal filters for EEG signal classification.

PubMed

Higashi, Hiroshi; Tanaka, Toshihisa

2011-01-01

The spatial weights for electrodes called common spatial pattern (CSP) are known to be effective in EEG signal classification for motor imagery based brain computer interfaces (MI-BCI). To achieve accurate classification in CSP, the frequency filter should be properly designed. To this end, several methods for designing the filter have been proposed. However, the existing methods cannot consider plural brain activities described with different frequency bands and different spatial patterns such as activities of mu and beta rhythms. In order to efficiently extract these brain activities, we propose a method to design plural filters and spatial weights which extract desired brain activity. The proposed method designs finite impulse response (FIR) filters and the associated spatial weights by optimization of an objective function which is a natural extension of CSP. Moreover, we show by a classification experiment that the bank of FIR filters which are designed by introducing an orthogonality into the objective function can extract good discriminative features. Moreover, the experiment result suggests that the proposed method can automatically detect and extract brain activities related to motor imagery.

Spatio-temporal cerebral blood flow perfusion patterns in cortical spreading depression

NASA Astrophysics Data System (ADS)

Verisokin, Andrey Yu.; Verveyko, Darya V.; Postnov, Dmitry E.

2017-04-01

Cortical spreading depression (CSD) is an example of one of the most common abnormalities in biophysical brain functioning. Despite the fact that there are many mathematical models describing the cortical spreading depression (CSD), most of them do not take into consideration the role of redistribution of cerebral blood flow (CBF), that results in the formation of spatio-temporal patterns. The paper presents a mathematical model, which successfully explains the CBD role in the CSD process. Numerical study of this model has revealed the formation of stationary dissipative structures, visually analogous to Turing structures. However, the mechanism of their formation is not diffusion. We show these structures occur due to another type of spatial coupling, that is related to tissue perfusion rate. The proposed model predicts that at similar state of neurons the distribution of blood flow and oxygenation may by different. Currently, this effect is not taken into account when the Blood oxygen-level dependent (BOLD) contrast imaging used in functional magnetic resonance imaging (fMRI). Thus, the diagnosis on the BOLD signal can be ambiguous. We believe that our results can be used in the future for a more correct interpretation of the data obtained with fMRI, NIRS and other similar methods for research of the brain activity.

Spatiotemporal Patterns of the Use of Urban Green Spaces and External Factors Contributing to Their Use in Central Beijing

PubMed Central

Li, Fangzheng; Zhang, Fen; Li, Xiong; Wang, Peng; Liang, Junhui; Mei, Yuting; Cheng, Wenwen; Qian, Yun

2017-01-01

Urban green spaces encourage outdoor activity and social communication that contribute to the health of local residents. Examining the relationship between the use of urban green spaces and factors influencing their utilization can provide essential references for green space site selection in urban planning. In contrast to previous studies that focused on internal factors, this study highlights the external factors (traffic convenience, population density and commercial facilities) contributing to the use of urban green spaces. We conducted a spatiotemporal analysis of the distribution of visitors in 208 selected green spaces in central Beijing. We examined the relationship between the spatial pattern of visitor distribution within urban green spaces and external factors, using the Gini coefficient, kernel density estimation, and geographical detectors. The results of the study were as follows. The spatial distribution of visitors within central Beijing’s green spaces was concentrated, forming different agglomerations. The three examined external factors are all associated with the use of green spaces. Among them, commercial facilities are the important external factor associated with the use of green spaces. For the selection of sites for urban green spaces, we recommend consideration of external factors in order to balance urban green space utilization. PMID:28264451

Spatiotemporal Patterns of the Use of Urban Green Spaces and External Factors Contributing to Their Use in Central Beijing.

PubMed

Li, Fangzheng; Zhang, Fen; Li, Xiong; Wang, Peng; Liang, Junhui; Mei, Yuting; Cheng, Wenwen; Qian, Yun

2017-02-27

Urban green spaces encourage outdoor activity and social communication that contribute to the health of local residents. Examining the relationship between the use of urban green spaces and factors influencing their utilization can provide essential references for green space site selection in urban planning. In contrast to previous studies that focused on internal factors, this study highlights the external factors (traffic convenience, population density and commercial facilities) contributing to the use of urban green spaces. We conducted a spatiotemporal analysis of the distribution of visitors in 208 selected green spaces in central Beijing. We examined the relationship between the spatial pattern of visitor distribution within urban green spaces and external factors, using the Gini coefficient, kernel density estimation, and geographical detectors. The results of the study were as follows. The spatial distribution of visitors within central Beijing's green spaces was concentrated, forming different agglomerations. The three examined external factors are all associated with the use of green spaces. Among them, commercial facilities are the important external factor associated with the use of green spaces. For the selection of sites for urban green spaces, we recommend consideration of external factors in order to balance urban green space utilization.

Evaluation of spatial and spatiotemporal estimation methods in simulation of precipitation variability patterns

NASA Astrophysics Data System (ADS)

Bayat, Bardia; Zahraie, Banafsheh; Taghavi, Farahnaz; Nasseri, Mohsen

2013-08-01

Identification of spatial and spatiotemporal precipitation variations plays an important role in different hydrological applications such as missing data estimation. In this paper, the results of Bayesian maximum entropy (BME) and ordinary kriging (OK) are compared for modeling spatial and spatiotemporal variations of annual precipitation with and without incorporating elevation variations. The study area of this research is Namak Lake watershed located in the central part of Iran with an area of approximately 90,000 km2. The BME and OK methods have been used to model the spatial and spatiotemporal variations of precipitation in this watershed, and their performances have been evaluated using cross-validation statistics. The results of the case study have shown the superiority of BME over OK in both spatial and spatiotemporal modes. The results have shown that BME estimates are less biased and more accurate than OK. The improvements in the BME estimates are mostly related to incorporating hard and soft data in the estimation process, which resulted in more detailed and reliable results. Estimation error variance for BME results is less than OK estimations in the study area in both spatial and spatiotemporal modes.

A multi-scale model for hair follicles reveals heterogeneous domains driving rapid spatiotemporal hair growth patterning.

PubMed

Wang, Qixuan; Oh, Ji Won; Lee, Hye-Lim; Dhar, Anukriti; Peng, Tao; Ramos, Raul; Guerrero-Juarez, Christian Fernando; Wang, Xiaojie; Zhao, Ran; Cao, Xiaoling; Le, Jonathan; Fuentes, Melisa A; Jocoy, Shelby C; Rossi, Antoni R; Vu, Brian; Pham, Kim; Wang, Xiaoyang; Mali, Nanda Maya; Park, Jung Min; Choi, June-Hyug; Lee, Hyunsu; Legrand, Julien M D; Kandyba, Eve; Kim, Jung Chul; Kim, Moonkyu; Foley, John; Yu, Zhengquan; Kobielak, Krzysztof; Andersen, Bogi; Khosrotehrani, Kiarash; Nie, Qing; Plikus, Maksim V

2017-07-11

The control principles behind robust cyclic regeneration of hair follicles (HFs) remain unclear. Using multi-scale modeling, we show that coupling inhibitors and activators with physical growth of HFs is sufficient to drive periodicity and excitability of hair regeneration. Model simulations and experimental data reveal that mouse skin behaves as a heterogeneous regenerative field, composed of anatomical domains where HFs have distinct cycling dynamics. Interactions between fast-cycling chin and ventral HFs and slow-cycling dorsal HFs produce bilaterally symmetric patterns. Ear skin behaves as a hyper-refractory domain with HFs in extended rest phase. Such hyper-refractivity relates to high levels of BMP ligands and WNT antagonists, in part expressed by ear-specific cartilage and muscle. Hair growth stops at the boundaries with hyper-refractory ears and anatomically discontinuous eyelids, generating wave-breaking effects. We posit that similar mechanisms for coupled regeneration with dominant activator, hyper-refractory, and wave-breaker regions can operate in other actively renewing organs.

Neural congruence between intertemporal and interpersonal self-control: Evidence from delay and social discounting.

PubMed

Hill, Paul F; Yi, Richard; Spreng, R Nathan; Diana, Rachel A

2017-11-15

Behavioral studies using delay and social discounting as indices of self-control and altruism, respectively, have revealed functional similarities between farsighted and social decisions. However, neural evidence for this functional link is lacking. Twenty-five young adults completed a delay and social discounting task during fMRI scanning. A spatiotemporal partial least squares analysis revealed that both forms of discounting were well characterized by a pattern of brain activity in areas comprising frontoparietal control, default, and mesolimbic reward networks. Both forms of discounting appear to draw on common neurocognitive mechanisms, regardless of whether choices involve intertemporal or interpersonal outcomes. We also observed neural profiles differentiating between high and low discounters. High discounters were well characterized by increased medial temporal lobe and limbic activity. In contrast, low discount rates were associated with activity in the medial prefrontal cortex and right temporoparietal junction. This pattern may reflect biological mechanisms underlying behavioral heterogeneity in discount rates. Copyright © 2017 Elsevier Inc. All rights reserved.

Spatio-temporal patterns of the effects of precipitation variability and land use/cover changes on long-term changes in sediment yield in the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Gao, Guangyao; Zhang, Jianjun; Liu, Yu; Ning, Zheng; Fu, Bojie; Sivapalan, Murugesu

2017-09-01

Within China's Loess Plateau there have been concerted revegetation efforts and engineering measures since the 1950s aimed at reducing soil erosion and land degradation. As a result, annual streamflow, sediment yield, and sediment concentration have all decreased considerably. Human-induced land use/cover change (LUCC) was the dominant factor, contributing over 70 % of the sediment load reduction, whereas the contribution of precipitation was less than 30 %. In this study, we use 50-year time series data (1961-2011), showing decreasing trends in the annual sediment loads of 15 catchments, to generate spatio-temporal patterns in the effects of LUCC and precipitation variability on sediment yield. The space-time variability of sediment yield was expressed notionally as a product of two factors representing (i) the effect of precipitation and (ii) the fraction of treated land surface area. Under minimal LUCC, the square root of annual sediment yield varied linearly with precipitation, with the precipitation-sediment load relationship showing coherent spatial patterns amongst the catchments. As the LUCC increased and took effect, the changes in sediment yield pattern depended more on engineering measures and vegetation restoration campaign, and the within-year rainfall patterns (especially storm events) also played an important role. The effect of LUCC is expressed in terms of a sediment coefficient, i.e., the ratio of annual sediment yield to annual precipitation. Sediment coefficients showed a steady decrease over the study period, following a linear decreasing function of the fraction of treated land surface area. In this way, the study has brought out the separate roles of precipitation variability and LUCC in controlling spatio-temporal patterns of sediment yield at catchment scale.

Do we really use rainfall observations consistent with reality in hydrological modelling?

NASA Astrophysics Data System (ADS)

Ciampalini, Rossano; Follain, Stéphane; Raclot, Damien; Crabit, Armand; Pastor, Amandine; Moussa, Roger; Le Bissonnais, Yves

2017-04-01

Spatial and temporal patterns in rainfall control how water reaches soil surface and interacts with soil properties (i.e., soil wetting, infiltration, saturation). Once a hydrological event is defined by a rainfall with its spatiotemporal variability and by some environmental parameters such as soil properties (including land use, topographic and anthropic features), the evidence shows that each parameter variation produces different, specific outputs (e.g., runoff, flooding etc.). In this study, we focus on the effect of rainfall patterns because, due to the difficulty to dispose of detailed data, their influence in modelling is frequently underestimated or neglected. A rainfall event affects a catchment non uniformly, it is spatially localized and its pattern moves in space and time. The way and the time how the water reaches the soil and saturates it respect to the geometry of the catchment deeply influences soil saturation, runoff, and then sediment delivery. This research, approaching a hypothetical, simple case, aims to stimulate the debate on the reliability of the rainfall quality used in hydrological / soil erosion modelling. We test on a small catchment of the south of France (Roujan, Languedoc Roussillon) the influence of rainfall variability with the use of a HD hybrid hydrological - soil erosion model, combining a cinematic wave with the St. Venant equation and a simplified "bucket" conceptual model for ground water, able to quantify the effect of different spatiotemporal patterns of a very-high-definition synthetic rainfall. Results indicate that rainfall spatiotemporal patterns are crucial simulating an erosive event: differences between spatially uniform rainfalls, as frequently adopted in simulations, and some hypothetical rainfall patterns here applied, reveal that the outcome of a simulated event can be highly underestimated.

Spatiotemporal causal modeling for the management of Dengue Fever

NASA Astrophysics Data System (ADS)

Yu, Hwa-Lung; Huang, Tailin; Lee, Chieh-Han

2015-04-01

Increasing climatic extremes have caused growing concerns about the health effects and disease outbreaks. The association between climate variation and the occurrence of epidemic diseases play an important role on a country's public health systems. Part of the impacts are direct casualties associated with the increasing frequency and intensity of typhoons, the proliferation of disease vectors and the short-term increase of clinic visits on gastro-intestinal discomforts, diarrhea, dermatosis, or psychological trauma. Other impacts come indirectly from the influence of disasters on the ecological and socio-economic systems, including the changes of air/water quality, living environment and employment condition. Previous risk assessment studies on dengue fever focus mostly on climatic and non-climatic factors and their association with vectors' reproducing pattern. The public-health implication may appear simple. Considering the seasonal changes and regional differences, however, the causality of the impacts is full of uncertainties. Without further investigation, the underlying dengue fever risk dynamics may not be assessed accurately. The objective of this study is to develop an epistemic framework for assessing dynamic dengue fever risk across space and time. The proposed framework integrates cross-departmental data, including public-health databases, precipitation data over time and various socio-economic data. We explore public-health issues induced by typhoon through literature review and spatiotemporal analytic techniques on public health databases. From those data, we identify relevant variables and possible causal relationships, and their spatiotemporal patterns derived from our proposed spatiotemporal techniques. Eventually, we create a spatiotemporal causal network and a framework for modeling dynamic dengue fever risk.

Mushroom biomass and diversity are driven by different spatio-temporal scales along Mediterranean elevation gradients

NASA Astrophysics Data System (ADS)

Alday, Josu G.; Martínez de Aragón, Juan; de-Miguel, Sergio; Bonet, José Antonio

2017-04-01

Mushrooms are important non-wood-forest-products in many Mediterranean ecosystems, being highly vulnerable to climate change. However, the ecological scales of variation of mushroom productivity and diversity, and climate dependence has been usually overlooked due to a lack of available data. We determined the spatio-temporal variability of epigeous sporocarps and the climatic factors driving their fruiting to plan future sustainable management of wild mushrooms production. We collected fruiting bodies in Pinus sylvestris stands along an elevation gradient for 8 consecutive years. Overall, sporocarp biomass was mainly dependent on inter-annual variations, whereas richness was more spatial-scale dependent. Elevation was not significant, but there were clear elevational differences in biomass and richness patterns between ectomycorrhizal and saprotrophic guilds. The main driver of variation was late-summer-early-autumn precipitation. Thus, different scale processes (inter-annual vs. spatial-scale) drive sporocarp biomass and diversity patterns; temporal effects for biomass and ectomycorrhizal fungi vs. spatial scale for diversity and saprotrophic fungi. The significant role of precipitation across fungal guilds and spatio-temporal scales indicates that it is a limiting resource controlling sporocarp production and diversity in Mediterranean regions. The high spatial and temporal variability of mushrooms emphasize the need for long-term datasets of multiple spatial points to effectively characterize fungal fruiting patterns.

Analyzing seasonal patterns of wildfire exposure factors in Sardinia, Italy.

PubMed

Salis, Michele; Ager, Alan A; Alcasena, Fermin J; Arca, Bachisio; Finney, Mark A; Pellizzaro, Grazia; Spano, Donatella

2015-01-01

In this paper, we applied landscape scale wildfire simulation modeling to explore the spatiotemporal patterns of wildfire likelihood and intensity in the island of Sardinia (Italy). We also performed wildfire exposure analysis for selected highly valued resources on the island to identify areas characterized by high risk. We observed substantial variation in burn probability, fire size, and flame length among time periods within the fire season, which starts in early June and ends in late September. Peak burn probability and flame length were observed in late July. We found that patterns of wildfire likelihood and intensity were mainly related to spatiotemporal variation in ignition locations, fuel moisture, and wind vectors. Our modeling approach allowed consideration of historical patterns of winds, ignition locations, and live and dead fuel moisture on fire exposure factors. The methodology proposed can be useful for analyzing potential wildfire risk and effects at landscape scale, evaluating historical changes and future trends in wildfire exposure, as well as for addressing and informing fuel management and risk mitigation issues.

Development of coherent neuronal activity patterns in mammalian cortical networks: common principles and local hetereogeneity.

PubMed

Egorov, Alexei V; Draguhn, Andreas

2013-01-01

Many mammals are born in a very immature state and develop their rich repertoire of behavioral and cognitive functions postnatally. This development goes in parallel with changes in the anatomical and functional organization of cortical structures which are involved in most complex activities. The emerging spatiotemporal activity patterns in multi-neuronal cortical networks may indeed form a direct neuronal correlate of systemic functions like perception, sensorimotor integration, decision making or memory formation. During recent years, several studies--mostly in rodents--have shed light on the ontogenesis of such highly organized patterns of network activity. While each local network has its own peculiar properties, some general rules can be derived. We therefore review and compare data from the developing hippocampus, neocortex and--as an intermediate region--entorhinal cortex. All cortices seem to follow a characteristic sequence starting with uncorrelated activity in uncoupled single neurons where transient activity seems to have mostly trophic effects. In rodents, before and shortly after birth, cortical networks develop weakly coordinated multineuronal discharges which have been termed synchronous plateau assemblies (SPAs). While these patterns rely mostly on electrical coupling by gap junctions, the subsequent increase in number and maturation of chemical synapses leads to the generation of large-scale coherent discharges. These patterns have been termed giant depolarizing potentials (GDPs) for predominantly GABA-induced events or early network oscillations (ENOs) for mostly glutamatergic bursts, respectively. During the third to fourth postnatal week, cortical areas reach their final activity patterns with distinct network oscillations and highly specific neuronal discharge sequences which support adult behavior. While some of the mechanisms underlying maturation of network activity have been elucidated much work remains to be done in order to fully understand the rules governing transition from immature to mature patterns of network activity. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Optical control of antibacterial activity

NASA Astrophysics Data System (ADS)

Velema, Willem A.; van der Berg, Jan Pieter; Hansen, Mickel J.; Szymanski, Wiktor; Driessen, Arnold J. M.; Feringa, Ben L.

2013-11-01

Bacterial resistance is a major problem in the modern world, stemming in part from the build-up of antibiotics in the environment. Novel molecular approaches that enable an externally triggered increase in antibiotic activity with high spatiotemporal resolution and auto-inactivation are highly desirable. Here we report a responsive, broad-spectrum, antibacterial agent that can be temporally activated with light, whereupon it auto-inactivates on the scale of hours. The use of such a ‘smart’ antibiotic might prevent the build-up of active antimicrobial material in the environment. Reversible optical control over active drug concentration enables us to obtain pharmacodynamic information. Precisely localized control of activity is achieved, allowing the growth of bacteria to be confined to defined patterns, which has potential for the development of treatments that avoid interference with the endogenous microbial population in other parts of the organism.

Travelling waves and spatial hierarchies in measles epidemics

NASA Astrophysics Data System (ADS)

Grenfell, B. T.; Bjørnstad, O. N.; Kappey, J.

2001-12-01

Spatio-temporal travelling waves are striking manifestations of predator-prey and host-parasite dynamics. However, few systems are well enough documented both to detect repeated waves and to explain their interaction with spatio-temporal variations in population structure and demography. Here, we demonstrate recurrent epidemic travelling waves in an exhaustive spatio-temporal data set for measles in England and Wales. We use wavelet phase analysis, which allows for dynamical non-stationarity-a complication in interpreting spatio-temporal patterns in these and many other ecological time series. In the pre-vaccination era, conspicuous hierarchical waves of infection moved regionally from large cities to small towns; the introduction of measles vaccination restricted but did not eliminate this hierarchical contagion. A mechanistic stochastic model suggests a dynamical explanation for the waves-spread via infective `sparks' from large `core' cities to smaller `satellite' towns. Thus, the spatial hierarchy of host population structure is a prerequisite for these infection waves.

Voltage Imaging of Waking Mouse Cortex Reveals Emergence of Critical Neuronal Dynamics

PubMed Central

Scott, Gregory; Fagerholm, Erik D.; Mutoh, Hiroki; Leech, Robert; Sharp, David J.; Shew, Woodrow L.

2014-01-01

Complex cognitive processes require neuronal activity to be coordinated across multiple scales, ranging from local microcircuits to cortex-wide networks. However, multiscale cortical dynamics are not well understood because few experimental approaches have provided sufficient support for hypotheses involving multiscale interactions. To address these limitations, we used, in experiments involving mice, genetically encoded voltage indicator imaging, which measures cortex-wide electrical activity at high spatiotemporal resolution. Here we show that, as mice recovered from anesthesia, scale-invariant spatiotemporal patterns of neuronal activity gradually emerge. We show for the first time that this scale-invariant activity spans four orders of magnitude in awake mice. In contrast, we found that the cortical dynamics of anesthetized mice were not scale invariant. Our results bridge empirical evidence from disparate scales and support theoretical predictions that the awake cortex operates in a dynamical regime known as criticality. The criticality hypothesis predicts that small-scale cortical dynamics are governed by the same principles as those governing larger-scale dynamics. Importantly, these scale-invariant principles also optimize certain aspects of information processing. Our results suggest that during the emergence from anesthesia, criticality arises as information processing demands increase. We expect that, as measurement tools advance toward larger scales and greater resolution, the multiscale framework offered by criticality will continue to provide quantitative predictions and insight on how neurons, microcircuits, and large-scale networks are dynamically coordinated in the brain. PMID:25505314

Nonequilibrium phase transitions, fluctuations and correlations in an active contractile polar fluid.

PubMed

Gowrishankar, Kripa; Rao, Madan

2016-02-21

We study the patterning, fluctuations and correlations of an active polar fluid consisting of contractile polar filaments on a two-dimensional substrate, using a hydrodynamic description. The steady states generically consist of arrays of inward pointing asters and show a continuous transition from a moving lamellar phase, a moving aster street, to a stationary aster lattice with no net polar order. We next study the effect of spatio-temporal athermal noise, parametrized by an active temperature TA, on the stability of the ordered phases. In contrast to its equilibrium counterpart, we find that the active crystal shows true long range order at low TA. On increasing TA, the asters dynamically remodel, concomitantly we find novel phase transitions characterized by bond-orientational and polar order upon "heating".

The three α1-adrenoceptor subtypes show different spatio-temporal mechanisms of internalization and ERK1/2 phosphorylation.

PubMed

Perez-Aso, M; Segura, V; Montó, F; Barettino, D; Noguera, M A; Milligan, G; D'Ocon, P

2013-10-01

We analyzed the kinetic and spatial patterns characterizing activation of the MAP kinases ERK 1 and 2 (ERK1/2) by the three α1-adrenoceptor (α1-AR) subtypes in HEK293 cells and the contribution of two different pathways to ERK1/2 phosphorylation: protein kinase C (PKC)-dependent ERK1/2 activation and internalization-dependent ERK1/2 activation. The different pathways of phenylephrine induced ERK phosphorylation were determined by western blot, using the PKC inhibitor Ro 31-8425, the receptor internalization inhibitor concanavalin A and the siRNA targeting β-arrestin 2. Receptor internalization properties were studied using CypHer5 technology and VSV-G epitope-tagged receptors. Activation of α1A- and α1B-ARs by phenylephrine elicited rapid ERK1/2 phosphorylation that was directed to the nucleus and inhibited by Ro 31-8425. Concomitant with phenylephrine induced receptor internalization α1A-AR, but not α1B-AR, produced a maintained and PKC-independent ERK phosphorylation, which was restricted to the cytosol and inhibited by β-arrestin 2 knockdown or concanavalin A treatment. α1D-AR displayed constitutive ERK phosphorylation, which was reduced by incubation with prazosin or the selective α1D antagonist BMY7378. Following activation by phenylephrine, α1D-AR elicited rapid, transient ERK1/2 phosphorylation that was restricted to the cytosol and not inhibited by Ro 31-8425. Internalization of the α1D-AR subtype was not observed via CypHer5 technology. The three α1-AR subtypes present different spatio-temporal patterns of receptor internalization, and only α1A-AR stimulation translates to a late, sustained ERK1/2 phosphorylation that is restricted to the cytosol and dependent on β-arrestin 2 mediated internalization. Copyright © 2013 Elsevier B.V. All rights reserved.

Growth dynamics explain the development of spatiotemporal burst activity of young cultured neuronal networks in detail.

PubMed

Gritsun, Taras A; le Feber, Joost; Rutten, Wim L C

2012-01-01

A typical property of isolated cultured neuronal networks of dissociated rat cortical cells is synchronized spiking, called bursting, starting about one week after plating, when the dissociated cells have sufficiently sent out their neurites and formed enough synaptic connections. This paper is the third in a series of three on simulation models of cultured networks. Our two previous studies [26], [27] have shown that random recurrent network activity models generate intra- and inter-bursting patterns similar to experimental data. The networks were noise or pacemaker-driven and had Izhikevich-neuronal elements with only short-term plastic (STP) synapses (so, no long-term potentiation, LTP, or depression, LTD, was included). However, elevated pre-phases (burst leaders) and after-phases of burst main shapes, that usually arise during the development of the network, were not yet simulated in sufficient detail. This lack of detail may be due to the fact that the random models completely missed network topology .and a growth model. Therefore, the present paper adds, for the first time, a growth model to the activity model, to give the network a time dependent topology and to explain burst shapes in more detail. Again, without LTP or LTD mechanisms. The integrated growth-activity model yielded realistic bursting patterns. The automatic adjustment of various mutually interdependent network parameters is one of the major advantages of our current approach. Spatio-temporal bursting activity was validated against experiment. Depending on network size, wave reverberation mechanisms were seen along the network boundaries, which may explain the generation of phases of elevated firing before and after the main phase of the burst shape.In summary, the results show that adding topology and growth explain burst shapes in great detail and suggest that young networks still lack/do not need LTP or LTD mechanisms.

Event Networks and the Identification of Crime Pattern Motifs

PubMed Central

2015-01-01

In this paper we demonstrate the use of network analysis to characterise patterns of clustering in spatio-temporal events. Such clustering is of both theoretical and practical importance in the study of crime, and forms the basis for a number of preventative strategies. However, existing analytical methods show only that clustering is present in data, while offering little insight into the nature of the patterns present. Here, we show how the classification of pairs of events as close in space and time can be used to define a network, thereby generalising previous approaches. The application of graph-theoretic techniques to these networks can then offer significantly deeper insight into the structure of the data than previously possible. In particular, we focus on the identification of network motifs, which have clear interpretation in terms of spatio-temporal behaviour. Statistical analysis is complicated by the nature of the underlying data, and we provide a method by which appropriate randomised graphs can be generated. Two datasets are used as case studies: maritime piracy at the global scale, and residential burglary in an urban area. In both cases, the same significant 3-vertex motif is found; this result suggests that incidents tend to occur not just in pairs, but in fact in larger groups within a restricted spatio-temporal domain. In the 4-vertex case, different motifs are found to be significant in each case, suggesting that this technique is capable of discriminating between clustering patterns at a finer granularity than previously possible. PMID:26605544

Gait Analysis Methods for Rodent Models of Arthritic Disorders: Reviews and Recommendations

PubMed Central

Lakes, Emily H.; Allen, Kyle D.

2016-01-01

Gait analysis is a useful tool to understand behavioral changes in preclinical arthritis models. While observational scoring and spatiotemporal gait parameters are the most widely performed gait analyses in rodents, commercially available systems can now provide quantitative assessments of spatiotemporal patterns. However, inconsistencies remain between testing platforms, and laboratories often select different gait pattern descriptors to report in the literature. Rodent gait can also be described through kinetic and kinematic analyses, but systems to analyze rodent kinetics and kinematics are typically custom made and often require sensitive, custom equipment. While the use of rodent gait analysis rapidly expands, it is important to remember that, while rodent gait analysis is a relatively modern behavioral assay, the study of quadrupedal gait is not new. Nearly all gait parameters are correlated, and a collection of gait parameters is needed to understand a compensatory gait pattern used by the animal. As such, a change in a single gait parameter is unlikely to tell the full biomechanical story; and to effectively use gait analysis, one must consider how multiple different parameters contribute to an altered gait pattern. The goal of this article is to review rodent gait analysis techniques and provide recommendations on how to use these technologies in rodent arthritis models, including discussions on the strengths and limitations of observational scoring, spatiotemporal, kinetic, and kinematic measures. Recognizing rodent gait analysis is an evolving tool, we also provide technical recommendations we hope will improve the utility of these analyses in the future. PMID:26995111

Adaptive changes in spatiotemporal gait characteristics in women during pregnancy.

PubMed

Błaszczyk, Janusz W; Opala-Berdzik, Agnieszka; Plewa, Michał

2016-01-01

Spatiotemporal gait cycle characteristics were assessed at early (P1), and late (P2) pregnancy, as well as at 2 months (PP1) and 6 months (PP2) postpartum. A substantial decrease in walking speed was observed throughout the pregnancy, with the slowest speed (1±0.2m/s) being during the third trimester. Walking at slower velocity resulted in complex adaptive adjustments to their spatiotemporal gait pattern, including a shorter step length and an increased duration of both their stance and double-support phases. Duration of the swing phase remained the least susceptible to changes. Habitual walking velocity (1.13±0.2m/s) and the optimal gait pattern were fully recovered 6 months after childbirth. Documented here adaptive changes in the preferred gait pattern seem to result mainly from the altered body anthropometry leading to temporary balance impairments. All the observed changes within stride cycle aimed to improve gait safety by focusing on its dynamic stability. The pregnant women preferred to walk at a slower velocity which allowed them to spend more time in double-support compared with their habitual pattern. Such changes provided pregnant women with a safer and more tentative ambulation that reduced the single-support period and, hence, the possibility of instability. As pregnancy progressed a significant increase in stance width and a decrease in step length was observed. Both factors allow also for gait stability improvement. Copyright © 2015 Elsevier B.V. All rights reserved.

Neurogenic and myogenic motor patterns of rabbit proximal, mid, and distal colon.

PubMed

Dinning, P G; Costa, M; Brookes, S J; Spencer, N J

2012-07-01

The rabbit colon consists of four distinct regions. The motility of each region is controlled by myogenic and neurogenic mechanisms. Associating these mechanisms with specific motor patterns throughout all regions of the colon has not previously been achieved. Three sections of the colon (the proximal, mid, and distal colon) were removed from euthanized rabbits. The proximal colon consists of a triply teniated region and a single tenia region. Spatio-temporal maps were constructed from video recordings of colonic wall diameter, with associated intraluminal pressure recorded from the aboral end. Hexamethonium (100 μM) and tetrodotoxin (TTX; 0.6 μM) were used to inhibit neural activity. Four distinct patterns of motility were detected: 1 myogenic and 3 neurogenic. The myogenic activity consisted of circular muscle (CM) contractions (ripples) that occurred throughout the colon and propagated in both antegrade (anal) and retrograde (oral) directions. The neural activity of the proximal colon consisted of slowly (0.1 mm/s) propagating colonic migrating motor complexes, which were abolished by hexamethonium. These complexes were observed in the region of the proximal colon with a single band of tenia. In the distal colon, tetrodotoxin-sensitive, thus neurally mediated, but hexamethonium-resistant, peristaltic (anal) and antiperistaltic (oral) contractions were identified. The distinct patterns of neurogenic and myogenic motor activity recorded from isolated rabbit colon are specific to each anatomically distinct region. The regional specificity motor pattern is likely to facilitate orderly transit of colonic content from semi-liquid to solid composition of feces.

Pattern formation in diffusive excitable systems under magnetic flow effects

NASA Astrophysics Data System (ADS)

Mvogo, Alain; Takembo, Clovis N.; Ekobena Fouda, H. P.; Kofané, Timoléon C.

2017-07-01

We study the spatiotemporal formation of patterns in a diffusive FitzHugh-Nagumo network where the effect of electromagnetic induction has been introduced in the standard mathematical model by using magnetic flux, and the modulation of magnetic flux on membrane potential is realized by using memristor coupling. We use the multi-scale expansion to show that the system equations can be reduced to a single differential-difference nonlinear equation. The linear stability analysis is performed and discussed with emphasis on the impact of magnetic flux. It is observed that the effect of memristor coupling importantly modifies the features of modulational instability. Our analytical results are supported by the numerical experiments, which reveal that the improved model can lead to nonlinear quasi-periodic spatiotemporal patterns with some features of synchronization. It is observed also the generation of pulses and rhythmics behaviors like breathing or swimming which are important in brain researches.

3D Printed, Microgroove Pattern-Driven Generation of Oriented Ligamentous Architectures.

PubMed

Park, Chan Ho; Kim, Kyoung-Hwa; Lee, Yong-Moo; Giannobile, William V; Seol, Yang-Jo

2017-09-08

Specific orientations of regenerated ligaments are crucially required for mechanoresponsive properties and various biomechanical adaptations, which are the key interplay to support mineralized tissues. Although various 2D platforms or 3D printing systems can guide cellular activities or aligned organizations, it remains a challenge to develop ligament-guided, 3D architectures with the angular controllability for parallel, oblique or perpendicular orientations of cells required for biomechanical support of organs. Here, we show the use of scaffold design by additive manufacturing for specific topographies or angulated microgroove patterns to control cell orientations such as parallel (0°), oblique (45°) and perpendicular (90°) angulations. These results demonstrate that ligament cells displayed highly predictable and controllable orientations along microgroove patterns on 3D biopolymeric scaffolds. Our findings demonstrate that 3D printed topographical approaches can regulate spatiotemporal cell organizations that offer strong potential for adaptation to complex tissue defects to regenerate ligament-bone complexes.

Segmentation and classification of cell cycle phases in fluorescence imaging.

PubMed

Ersoy, Ilker; Bunyak, Filiz; Chagin, Vadim; Cardoso, M Christina; Palaniappan, Kannappan

2009-01-01

Current chemical biology methods for studying spatiotemporal correlation between biochemical networks and cell cycle phase progression in live-cells typically use fluorescence-based imaging of fusion proteins. Stable cell lines expressing fluorescently tagged protein GFP-PCNA produce rich, dynamically varying sub-cellular foci patterns characterizing the cell cycle phases, including the progress during the S-phase. Variable fluorescence patterns, drastic changes in SNR, shape and position changes and abundance of touching cells require sophisticated algorithms for reliable automatic segmentation and cell cycle classification. We extend the recently proposed graph partitioning active contours (GPAC) for fluorescence-based nucleus segmentation using regional density functions and dramatically improve its efficiency, making it scalable for high content microscopy imaging. We utilize surface shape properties of GFP-PCNA intensity field to obtain descriptors of foci patterns and perform automated cell cycle phase classification, and give quantitative performance by comparing our results to manually labeled data.

Prediction limits of mobile phone activity modelling

NASA Astrophysics Data System (ADS)

Kondor, Dániel; Grauwin, Sebastian; Kallus, Zsófia; Gódor, István; Sobolevsky, Stanislav; Ratti, Carlo

2017-02-01

Thanks to their widespread usage, mobile devices have become one of the main sensors of human behaviour and digital traces left behind can be used as a proxy to study urban environments. Exploring the nature of the spatio-temporal patterns of mobile phone activity could thus be a crucial step towards understanding the full spectrum of human activities. Using 10 months of mobile phone records from Greater London resolved in both space and time, we investigate the regularity of human telecommunication activity on urban scales. We evaluate several options for decomposing activity timelines into typical and residual patterns, accounting for the strong periodic and seasonal components. We carry out our analysis on various spatial scales, showing that regularity increases as we look at aggregated activity in larger spatial units with more activity in them. We examine the statistical properties of the residuals and show that it can be explained by noise and specific outliers. Also, we look at sources of deviations from the general trends, which we find to be explainable based on knowledge of the city structure and places of attractions. We show examples how some of the outliers can be related to external factors such as specific social events.

Prediction limits of mobile phone activity modelling.

PubMed

Kondor, Dániel; Grauwin, Sebastian; Kallus, Zsófia; Gódor, István; Sobolevsky, Stanislav; Ratti, Carlo

2017-02-01

Thanks to their widespread usage, mobile devices have become one of the main sensors of human behaviour and digital traces left behind can be used as a proxy to study urban environments. Exploring the nature of the spatio-temporal patterns of mobile phone activity could thus be a crucial step towards understanding the full spectrum of human activities. Using 10 months of mobile phone records from Greater London resolved in both space and time, we investigate the regularity of human telecommunication activity on urban scales. We evaluate several options for decomposing activity timelines into typical and residual patterns, accounting for the strong periodic and seasonal components. We carry out our analysis on various spatial scales, showing that regularity increases as we look at aggregated activity in larger spatial units with more activity in them. We examine the statistical properties of the residuals and show that it can be explained by noise and specific outliers. Also, we look at sources of deviations from the general trends, which we find to be explainable based on knowledge of the city structure and places of attractions. We show examples how some of the outliers can be related to external factors such as specific social events.

Recurrent patterns of atrial depolarization during atrial fibrillation assessed by recurrence plot quantification.

PubMed

Censi, F; Barbaro, V; Bartolini, P; Calcagnini, G; Michelucci, A; Gensini, G F; Cerutti, S

2000-01-01

The aim of this study was to determine the presence of organization of atrial activation processes during atrial fibrillation (AF) by assessing whether the activation sequences are wholly random or are governed by deterministic mechanisms. We performed both linear and nonlinear analyses based on the cross correlation function (CCF) and recurrence plot quantification (RPQ), respectively. Recurrence plots were quantified by three variables: percent recurrence (PR), percent determinism (PD), and entropy of recurrences (ER). We recorded bipolar intra-atrial electrograms in two atrial sites during chronic AF in 19 informed subjects, following two protocols. In one, both recording sites were in the right atrium; in the other protocol, one site was in the right atrium, the other one in the left atrium. We extracted 19 episodes of type I AF (Wells' classification). RPQ detected transient recurrent patterns in all the episodes, while CCF was significant only in ten episodes. Surrogate data analysis, based on a cross-phase randomization procedure, decreased PR, PD, and ER values. The detection of spatiotemporal recurrent patterns together with the surrogate data results indicate that during AF a certain degree of local organization exists, likely caused by deterministic mechanisms of activation.

Spatiotemporal chaos and two-dimensional dissipative rogue waves in Lugiato-Lefever model

NASA Astrophysics Data System (ADS)

Panajotov, Krassimir; Clerc, Marcel G.; Tlidi, Mustapha

2017-06-01

Driven nonlinear optical cavities can exhibit complex spatiotemporal dynamics. We consider the paradigmatic Lugiato-Lefever model describing driven nonlinear optical resonator. This model is one of the most-studied nonlinear equations in optics. It describes a large spectrum of nonlinear phenomena from bistability, to periodic patterns, localized structures, self-pulsating localized structures and to a complex spatiotemporal behavior. The model is considered also as prototype model to describe several optical nonlinear devices such as Kerr media, liquid crystals, left handed materials, nonlinear fiber cavity, and frequency comb generation. We focus our analysis on a spatiotemporal chaotic dynamics in one-dimension. We identify a route to spatiotemporal chaos through an extended quasiperiodicity. We have estimated the Kaplan-Yorke dimension that provides a measure of the strange attractor complexity. Likewise, we show that the Lugiato-Leferver equation supports rogues waves in two-dimensional settings. We characterize rogue-wave formation by computing the probability distribution of the pulse height. Contribution to the Topical Issue "Theory and Applications of the Lugiato-Lefever Equation", edited by Yanne K. Chembo, Damia Gomila, Mustapha Tlidi, Curtis R. Menyuk.

Lag threads organize the brain’s intrinsic activity

PubMed Central

Mitra, Anish; Snyder, Abraham Z.; Blazey, Tyler; Raichle, Marcus E.

2015-01-01

It has been widely reported that intrinsic brain activity, in a variety of animals including humans, is spatiotemporally structured. Specifically, propagated slow activity has been repeatedly demonstrated in animals. In human resting-state fMRI, spontaneous activity has been understood predominantly in terms of zero-lag temporal synchrony within widely distributed functional systems (resting-state networks). Here, we use resting-state fMRI from 1,376 normal, young adults to demonstrate that multiple, highly reproducible, temporal sequences of propagated activity, which we term “lag threads,” are present in the brain. Moreover, this propagated activity is largely unidirectional within conventionally understood resting-state networks. Modeling experiments show that resting-state networks naturally emerge as a consequence of shared patterns of propagation. An implication of these results is that common physiologic mechanisms may underlie spontaneous activity as imaged with fMRI in humans and slowly propagated activity as studied in animals. PMID:25825720

Spatiotemporal Pattern Analysis of Scarlet Fever Incidence in Beijing, China, 2005–2014

PubMed Central

Mahara, Gehendra; Wang, Chao; Huo, Da; Xu, Qin; Huang, Fangfang; Tao, Lixin; Guo, Jin; Cao, Kai; Long, Liu; Chhetri, Jagadish K.; Gao, Qi; Wang, Wei; Wang, Quanyi; Guo, Xiuhua

2016-01-01

Objective: To probe the spatiotemporal patterns of the incidence of scarlet fever in Beijing, China, from 2005 to 2014. Methods: A spatiotemporal analysis was conducted at the district/county level in the Beijing region based on the reported cases of scarlet fever during the study period. Moran’s autocorrelation coefficient was used to examine the spatial autocorrelation of scarlet fever, whereas the Getis-Ord Gi* statistic was used to determine the hotspot incidence of scarlet fever. Likewise, the space-time scan statistic was used to detect the space-time clusters, including the relative risk of scarlet fever incidence across all settings. Results: A total of 26,860 scarlet fever cases were reported in Beijing during the study period (2005–2014). The average annual incidence of scarlet fever was 14.25 per 100,000 population (range, 6.76 to 32.03 per 100,000). The incidence among males was higher than that among females, and more than two-thirds of scarlet fever cases (83.8%) were among children 3–8 years old. The seasonal incidence peaks occurred from March to July. A higher relative risk area was mainly in the city and urban districts of Beijing. The most likely space-time clusters and secondary clusters were detected to be diversely distributed in every study year. Conclusions: The spatiotemporal patterns of scarlet fever were relatively unsteady in Beijing from 2005 to 2014. The at-risk population was mainly scattered in urban settings and dense districts with high population, indicating a positive relationship between population density and increased risk of scarlet fever exposure. Children under 15 years of age were the most susceptible to scarlet fever. PMID:26784213

Spatiotemporal Pattern Analysis of Scarlet Fever Incidence in Beijing, China, 2005-2014.

PubMed

Mahara, Gehendra; Wang, Chao; Huo, Da; Xu, Qin; Huang, Fangfang; Tao, Lixin; Guo, Jin; Cao, Kai; Long, Liu; Chhetri, Jagadish K; Gao, Qi; Wang, Wei; Wang, Quanyi; Guo, Xiuhua

2016-01-15

To probe the spatiotemporal patterns of the incidence of scarlet fever in Beijing, China, from 2005 to 2014. A spatiotemporal analysis was conducted at the district/county level in the Beijing region based on the reported cases of scarlet fever during the study period. Moran's autocorrelation coefficient was used to examine the spatial autocorrelation of scarlet fever, whereas the Getis-Ord Gi* statistic was used to determine the hotspot incidence of scarlet fever. Likewise, the space-time scan statistic was used to detect the space-time clusters, including the relative risk of scarlet fever incidence across all settings. A total of 26,860 scarlet fever cases were reported in Beijing during the study period (2005-2014). The average annual incidence of scarlet fever was 14.25 per 100,000 population (range, 6.76 to 32.03 per 100,000). The incidence among males was higher than that among females, and more than two-thirds of scarlet fever cases (83.8%) were among children 3-8 years old. The seasonal incidence peaks occurred from March to July. A higher relative risk area was mainly in the city and urban districts of Beijing. The most likely space-time clusters and secondary clusters were detected to be diversely distributed in every study year. The spatiotemporal patterns of scarlet fever were relatively unsteady in Beijing from 2005 to 2014. The at-risk population was mainly scattered in urban settings and dense districts with high population, indicating a positive relationship between population density and increased risk of scarlet fever exposure. Children under 15 years of age were the most susceptible to scarlet fever.

How innate is locomotion in precocial animals? A study on the early development of spatio-temporal gait variables and gait symmetry in piglets.

PubMed

Vanden Hole, Charlotte; Goyens, Jana; Prims, Sara; Fransen, Erik; Ayuso Hernando, Miriam; Van Cruchten, Steven; Aerts, Peter; Van Ginneken, Chris

2017-08-01

Locomotion is one of the most important ecological functions in animals. Precocial animals, such as pigs, are capable of independent locomotion shortly after birth. This raises the question whether coordinated movement patterns and the underlying muscular control in these animals is fully innate or whether there still exists a rapid maturation. We addressed this question by studying gait development in neonatal pigs through the analysis of spatio-temporal gait characteristics during locomotion at self-selected speed. To this end, we made video recordings of piglets walking along a corridor at several time points (from 0 h to 96 h). After digitization of the footfalls, we analysed self-selected speed and spatio-temporal characteristics (e.g. stride and step lengths, stride frequency and duty factor) to study dynamic similarity, intralimb coordination and interlimb coordination. To assess the variability of the gait pattern, left-right asymmetry was studied. To distinguish neuromotor maturation from effects caused by growth, both absolute and normalized data (according to the dynamic similarity concept) were included in the analysis. All normalized spatio-temporal variables reached stable values within 4 h of birth, with most of them showing little change after the age of 2 h. Most asymmetry indices showed stable values, hovering around 10%, within 8 h of birth. These results indicate that coordinated movement patterns are not entirely innate, but that a rapid neuromotor maturation, potentially also the result of the rearrangement or recombination of existing motor modules, takes place in these precocial animals. © 2017. Published by The Company of Biologists Ltd.

Complex, Dynamic Combination of Physical, Chemical and Nutritional Variables Controls Spatio-Temporal Variation of Sandy Beach Community Structure

PubMed Central

Ortega Cisneros, Kelly; Smit, Albertus J.; Laudien, Jürgen; Schoeman, David S.

2011-01-01

Sandy beach ecological theory states that physical features of the beach control macrobenthic community structure on all but the most dissipative beaches. However, few studies have simultaneously evaluated the relative importance of physical, chemical and biological factors as potential explanatory variables for meso-scale spatio-temporal patterns of intertidal community structure in these systems. Here, we investigate macroinfaunal community structure of a micro-tidal sandy beach that is located on an oligotrophic subtropical coast and is influenced by seasonal estuarine input. We repeatedly sampled biological and environmental variables at a series of beach transects arranged at increasing distances from the estuary mouth. Sampling took place over a period of five months, corresponding with the transition between the dry and wet season. This allowed assessment of biological-physical relationships across chemical and nutritional gradients associated with a range of estuarine inputs. Physical, chemical, and biological response variables, as well as measures of community structure, showed significant spatio-temporal patterns. In general, bivariate relationships between biological and environmental variables were rare and weak. However, multivariate correlation approaches identified a variety of environmental variables (i.e., sampling session, the C∶N ratio of particulate organic matter, dissolved inorganic nutrient concentrations, various size fractions of photopigment concentrations, salinity and, to a lesser extent, beach width and sediment kurtosis) that either alone or combined provided significant explanatory power for spatio-temporal patterns of macroinfaunal community structure. Overall, these results showed that the macrobenthic community on Mtunzini Beach was not structured primarily by physical factors, but instead by a complex and dynamic blend of nutritional, chemical and physical drivers. This emphasises the need to recognise ocean-exposed sandy beaches as functional ecosystems in their own right. PMID:21858213

Complex, dynamic combination of physical, chemical and nutritional variables controls spatio-temporal variation of sandy beach community structure.

PubMed

Ortega Cisneros, Kelly; Smit, Albertus J; Laudien, Jürgen; Schoeman, David S

2011-01-01

Sandy beach ecological theory states that physical features of the beach control macrobenthic community structure on all but the most dissipative beaches. However, few studies have simultaneously evaluated the relative importance of physical, chemical and biological factors as potential explanatory variables for meso-scale spatio-temporal patterns of intertidal community structure in these systems. Here, we investigate macroinfaunal community structure of a micro-tidal sandy beach that is located on an oligotrophic subtropical coast and is influenced by seasonal estuarine input. We repeatedly sampled biological and environmental variables at a series of beach transects arranged at increasing distances from the estuary mouth. Sampling took place over a period of five months, corresponding with the transition between the dry and wet season. This allowed assessment of biological-physical relationships across chemical and nutritional gradients associated with a range of estuarine inputs. Physical, chemical, and biological response variables, as well as measures of community structure, showed significant spatio-temporal patterns. In general, bivariate relationships between biological and environmental variables were rare and weak. However, multivariate correlation approaches identified a variety of environmental variables (i.e., sampling session, the C∶N ratio of particulate organic matter, dissolved inorganic nutrient concentrations, various size fractions of photopigment concentrations, salinity and, to a lesser extent, beach width and sediment kurtosis) that either alone or combined provided significant explanatory power for spatio-temporal patterns of macroinfaunal community structure. Overall, these results showed that the macrobenthic community on Mtunzini Beach was not structured primarily by physical factors, but instead by a complex and dynamic blend of nutritional, chemical and physical drivers. This emphasises the need to recognise ocean-exposed sandy beaches as functional ecosystems in their own right.

Effective and efficient analysis of spatio-temporal data

NASA Astrophysics Data System (ADS)

Zhang, Zhongnan

Spatio-temporal data mining, i.e., mining knowledge from large amount of spatio-temporal data, is a highly demanding field because huge amounts of spatio-temporal data have been collected in various applications, ranging from remote sensing, to geographical information systems (GIS), computer cartography, environmental assessment and planning, etc. The collection data far exceeded human's ability to analyze which make it crucial to develop analysis tools. Recent studies on data mining have extended to the scope of data mining from relational and transactional datasets to spatial and temporal datasets. Among the various forms of spatio-temporal data, remote sensing images play an important role, due to the growing wide-spreading of outer space satellites. In this dissertation, we proposed two approaches to analyze the remote sensing data. The first one is about applying association rules mining onto images processing. Each image was divided into a number of image blocks. We built a spatial relationship for these blocks during the dividing process. This made a large number of images into a spatio-temporal dataset since each image was shot in time-series. The second one implemented co-occurrence patterns discovery from these images. The generated patterns represent subsets of spatial features that are located together in space and time. A weather analysis is composed of individual analysis of several meteorological variables. These variables include temperature, pressure, dew point, wind, clouds, visibility and so on. Local-scale models provide detailed analysis and forecasts of meteorological phenomena ranging from a few kilometers to about 100 kilometers in size. When some of above meteorological variables have some special change tendency, some kind of severe weather will happen in most cases. Using the discovery of association rules, we found that some special meteorological variables' changing has tight relation with some severe weather situation that will happen very soon. This dissertation is composed of three parts: an introduction, some basic knowledges and relative works, and my own three contributions to the development of approaches for spatio-temporal data mining: DYSTAL algorithm, STARSI algorithm, and COSTCOP+ algorithm.

Multi-perspective analysis and spatiotemporal mapping of air pollution monitoring data.

PubMed

Kolovos, Alexander; Skupin, André; Jerrett, Michael; Christakos, George

2010-09-01

Space-time data analysis and assimilation techniques in atmospheric sciences typically consider input from monitoring measurements. The input is often processed in a manner that acknowledges characteristics of the measurements (e.g., underlying patterns, fluctuation features) under conditions of uncertainty; it also leads to the derivation of secondary information that serves study-oriented goals, and provides input to space-time prediction techniques. We present a novel approach that blends a rigorous space-time prediction model (Bayesian maximum entropy, BME) with a cognitively informed visualization of high-dimensional data (spatialization). The combined BME and spatialization approach (BME-S) is used to study monthly averaged NO2 and mean annual SO4 measurements in California over the 15-year period 1988-2002. Using the original scattered measurements of these two pollutants BME generates spatiotemporal predictions on a regular grid across the state. Subsequently, the prediction network undergoes the spatialization transformation into a lower-dimensional geometric representation, aimed at revealing patterns and relationships that exist within the input data. The proposed BME-S provides a powerful spatiotemporal framework to study a variety of air pollution data sources.

Spatiotemporal topology and temporal sequence identification with an adaptive time-delay neural network

NASA Astrophysics Data System (ADS)

Lin, Daw-Tung; Ligomenides, Panos A.; Dayhoff, Judith E.

1993-08-01

Inspired from the time delays that occur in neurobiological signal transmission, we describe an adaptive time delay neural network (ATNN) which is a powerful dynamic learning technique for spatiotemporal pattern transformation and temporal sequence identification. The dynamic properties of this network are formulated through the adaptation of time-delays and synapse weights, which are adjusted on-line based on gradient descent rules according to the evolution of observed inputs and outputs. We have applied the ATNN to examples that possess spatiotemporal complexity, with temporal sequences that are completed by the network. The ATNN is able to be applied to pattern completion. Simulation results show that the ATNN learns the topology of a circular and figure eight trajectories within 500 on-line training iterations, and reproduces the trajectory dynamically with very high accuracy. The ATNN was also trained to model the Fourier series expansion of the sum of different odd harmonics. The resulting network provides more flexibility and efficiency than the TDNN and allows the network to seek optimal values for time-delays as well as optimal synapse weights.

Spatio-Temporal Dynamics of Fructan Metabolism in Developing Barley Grains[W

PubMed Central

Peukert, Manuela; Thiel, Johannes; Peshev, Darin; Weschke, Winfriede; Van den Ende, Wim; Mock, Hans-Peter; Matros, Andrea

2014-01-01

Barley (Hordeum vulgare) grain development follows a series of defined morphological and physiological stages and depends on the supply of assimilates (mainly sucrose) from the mother plant. Here, spatio-temporal patterns of sugar distributions were investigated by mass spectrometric imaging, targeted metabolite analyses, and transcript profiling of microdissected grain tissues. Distinct spatio-temporal sugar balances were observed, which may relate to differentiation and grain filling processes. Notably, various types of oligofructans showed specific distribution patterns. Levan- and graminan-type oligofructans were synthesized in the cellularized endosperm prior to the commencement of starch biosynthesis, while during the storage phase, inulin-type oligofructans accumulated to a high concentration in and around the nascent endosperm cavity. In the shrunken endosperm mutant seg8, with a decreased sucrose flux toward the endosperm, fructan accumulation was impaired. The tight partitioning of oligofructan biosynthesis hints at distinct functions of the various fructan types in the young endosperm prior to starch accumulation and in the endosperm transfer cells that accomplish the assimilate supply toward the endosperm at the storage phase. PMID:25271242

Postnatal developmental changes in activation profiles of the respiratory neuronal network in the rat ventral medulla

PubMed Central

Oku, Yoshitaka; Masumiya, Haruko; Okada, Yasumasa

2007-01-01

Two putative respiratory rhythm generators (RRGs), the para-facial respiratory group (pFRG) and the pre-Bötzinger complex (preBötC), have been identified in the neonatal rodent brainstem. To elucidate their functional roles during the neonatal period, we evaluated developmental changes of these RRGs by optical imaging using a voltage-sensitive dye. Optical signals, recorded from the ventral medulla of brainstem–spinal cord preparations of neonatal (P0–P4) rats (n = 44), were analysed by a cross correlation method. With development during the first few postnatal days, the respiratory-related activity in the pFRG reduced and shifted from a preinspiratory (P0–P1) to an inspiratory (P2–P4) pattern, whereas preBötC activity remained unchanged. The μ-opioid agonist [d-Ala(2),N-Me-Phe(4),Gly(5)-ol]-enkephalin (DAMGO) augmented preinspiratory activity in the pFRG, while the μ-opioid antagonist naloxone induced changes in spatiotemporal activation profiles that closely mimicked the developmental changes. These results are consistent with the recently proposed hypothesis by Janczewski and Feldman that the pFRG is activated to compensate for the depression of the preBötC by perinatal opiate surge. We conclude that significant reorganization of the respiratory neuronal network, characterized by a reduction of preinspiratory activity in the pFRG, occurs at P1–P2 in rats. The changes in spatiotemporal activation profiles of the pFRG neurones may reflect changes in the mode of coupling of the two respiratory rhythm generators. PMID:17884928

Spatiotemporal drought forecasting using nonlinear models

NASA Astrophysics Data System (ADS)

Vasiliades, Lampros; Loukas, Athanasios

2010-05-01

Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. In order to achieve spatiotemporal forecasting, some mature analysis tools, e.g., time series and spatial statistics are extended to the spatial dimension and the temporal dimension, respectively. Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Despite the widespread application of nonlinear mathematical models, comparative studies on spatiotemporal drought forecasting using different models are still a huge task for modellers. This study uses a promising approach, the Gamma Test (GT), to select the input variables and the training data length, so that the trial and error workload could be greatly reduced. The GT enables to quickly evaluate and estimate the best mean squared error that can be achieved by a smooth model on any unseen data for a given selection of inputs, prior to model construction. The GT is applied to forecast droughts using monthly Standardized Precipitation Index (SPI) timeseries at multiple timescales in several precipitation stations at Pinios river basin in Thessaly region, Greece. Several nonlinear models have been developed efficiently, with the aid of the GT, for 1-month up to 12-month ahead forecasting. Several temporal and spatial statistical indices were considered for the performance evaluation of the models. The predicted results show reasonably good agreement with the actual data for short lead times, whereas the forecasting accuracy decreases with increase in lead time. Finally, the developed nonlinear models could be used in an early warning system for risk and decision analyses at the study area.

Holographic imaging and photostimulation of neural activity.

PubMed

Yang, Weijian; Yuste, Rafael

2018-06-01

Optical imaging methods are powerful tools in neuroscience as they can systematically monitor the activity of neuronal populations with high spatiotemporal resolution using calcium or voltage indicators. Moreover, caged compounds and optogenetic actuators enable to optically manipulate neural activity. Among optical methods, computer-generated holography offers an enormous flexibility to sculpt the excitation light in three-dimensions (3D), particularly when combined with two-photon light sources. By projecting holographic light patterns on the sample, the activity of multiple neurons across a 3D brain volume can be simultaneously imaged or optically manipulated with single-cell precision. This flexibility makes two-photon holographic microscopy an ideal all-optical platform to simultaneously read and write activity in neuronal populations in vivo in 3D, a critical ability to dissect the function of neural circuits. Copyright © 2018 Elsevier Ltd. All rights reserved.

Multistability, local pattern formation, and global collective firing in a small-world network of nonleaky integrate-and-fire neurons.

PubMed

Rothkegel, Alexander; Lehnertz, Klaus

2009-03-01

We investigate numerically the collective dynamical behavior of pulse-coupled nonleaky integrate-and-fire neurons that are arranged on a two-dimensional small-world network. To ensure ongoing activity, we impose a probability for spontaneous firing for each neuron. We study network dynamics evolving from different sets of initial conditions in dependence on coupling strength and rewiring probability. Besides a homogeneous equilibrium state for low coupling strength, we observe different local patterns including cyclic waves, spiral waves, and turbulentlike patterns, which-depending on network parameters-interfere with the global collective firing of the neurons. We attribute the various network dynamics to distinct regimes in the parameter space. For the same network parameters different network dynamics can be observed depending on the set of initial conditions only. Such a multistable behavior and the interplay between local pattern formation and global collective firing may be attributable to the spatiotemporal dynamics of biological networks.

3D Printed Programmable Release Capsules.

PubMed

Gupta, Maneesh K; Meng, Fanben; Johnson, Blake N; Kong, Yong Lin; Tian, Limei; Yeh, Yao-Wen; Masters, Nina; Singamaneni, Srikanth; McAlpine, Michael C

2015-08-12

The development of methods for achieving precise spatiotemporal control over chemical and biomolecular gradients could enable significant advances in areas such as synthetic tissue engineering, biotic-abiotic interfaces, and bionanotechnology. Living organisms guide tissue development through highly orchestrated gradients of biomolecules that direct cell growth, migration, and differentiation. While numerous methods have been developed to manipulate and implement biomolecular gradients, integrating gradients into multiplexed, three-dimensional (3D) matrices remains a critical challenge. Here we present a method to 3D print stimuli-responsive core/shell capsules for programmable release of multiplexed gradients within hydrogel matrices. These capsules are composed of an aqueous core, which can be formulated to maintain the activity of payload biomolecules, and a poly(lactic-co-glycolic) acid (PLGA, an FDA approved polymer) shell. Importantly, the shell can be loaded with plasmonic gold nanorods (AuNRs), which permits selective rupturing of the capsule when irradiated with a laser wavelength specifically determined by the lengths of the nanorods. This precise control over space, time, and selectivity allows for the ability to pattern 2D and 3D multiplexed arrays of enzyme-loaded capsules along with tunable laser-triggered rupture and release of active enzymes into a hydrogel ambient. The advantages of this 3D printing-based method include (1) highly monodisperse capsules, (2) efficient encapsulation of biomolecular payloads, (3) precise spatial patterning of capsule arrays, (4) "on the fly" programmable reconfiguration of gradients, and (5) versatility for incorporation in hierarchical architectures. Indeed, 3D printing of programmable release capsules may represent a powerful new tool to enable spatiotemporal control over biomolecular gradients.

Spatio-temporal patterns of soil water storage under dryland agriculture at the watershed scale

USDA-ARS?s Scientific Manuscript database

Soil water patterns vary significantly due to precipitation, soil properties, topographic features, and land use. We used empirical orthogonal function (EOF) analysis to characterize the spatial variability of soil water across a 37-ha field of the Washington State University Cook Agronomy Farm near...

Pattern Informatics Approach to Earthquake Forecasting in 3D

NASA Astrophysics Data System (ADS)

Toya, Y.; Tiampo, K. F.; Rundle, J. B.; Chen, C.; Li, H.; Klein, W.

2009-05-01

Natural seismicity is correlated across multiple spatial and temporal scales, but correlations in seismicity prior to a large earthquake are locally subtle (e.g. seismic quiescence) and often prominent in broad scale (e.g., seismic activation), resulting in local and regional seismicity patterns, e.g. a Mogi's donut. Recognizing that patterns in seismicity rate are reflecting the regional dynamics of the directly unobservable crustal stresses, the Pattern Informatics (PI) approach was introduced by Tiampo et al. in 2002 [Europhys. Lett., 60 (3), 481-487,] Rundle et al., 2002 [PNAS 99, suppl. 1, 2514-2521.] In this study, we expand the PI approach to forecasting earthquakes into the third, or vertical dimension, and illustrate its further improvement in the forecasting performance through case studies of both natural and synthetic data. The PI characterizes rapidly evolving spatio-temporal seismicity patterns as angular drifts of a unit state vector in a high dimensional correlation space, and systematically identifies anomalous shifts in seismic activity with respect to the regional background. 3D PI analysis is particularly advantageous over 2D analysis in resolving vertically overlapped seismicity anomalies in a highly complex tectonic environment. Case studies will help to illustrate some important properties of the PI forecasting tool. [Submitted to: Concurrency and Computation: Practice and Experience, Wiley, Special Issue: ACES2008.

Spatiotemporal dynamics of brain activity during the transition from visually guided to memory-guided force control

PubMed Central

Poon, Cynthia; Chin-Cottongim, Lisa G.; Coombes, Stephen A.; Corcos, Daniel M.

2012-01-01

It is well established that the prefrontal cortex is involved during memory-guided tasks whereas visually guided tasks are controlled in part by a frontal-parietal network. However, the nature of the transition from visually guided to memory-guided force control is not as well established. As such, this study examines the spatiotemporal pattern of brain activity that occurs during the transition from visually guided to memory-guided force control. We measured 128-channel scalp electroencephalography (EEG) in healthy individuals while they performed a grip force task. After visual feedback was removed, the first significant change in event-related activity occurred in the left central region by 300 ms, followed by changes in prefrontal cortex by 400 ms. Low-resolution electromagnetic tomography (LORETA) was used to localize the strongest activity to the left ventral premotor cortex and ventral prefrontal cortex. A second experiment altered visual feedback gain but did not require memory. In contrast to memory-guided force control, altering visual feedback gain did not lead to early changes in the left central and midline prefrontal regions. Decreasing the spatial amplitude of visual feedback did lead to changes in the midline central region by 300 ms, followed by changes in occipital activity by 400 ms. The findings show that subjects rely on sensorimotor memory processes involving left ventral premotor cortex and ventral prefrontal cortex after the immediate transition from visually guided to memory-guided force control. PMID:22696535

Infraslow Electroencephalographic and Dynamic Resting State Network Activity.

PubMed

Grooms, Joshua K; Thompson, Garth J; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H; Epstein, Charles M; Keilholz, Shella D

2017-06-01

A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies.

Infraslow Electroencephalographic and Dynamic Resting State Network Activity

PubMed Central

Grooms, Joshua K.; Thompson, Garth J.; Pan, Wen-Ju; Billings, Jacob; Schumacher, Eric H.; Epstein, Charles M.

2017-01-01

Abstract A number of studies have linked the blood oxygenation level dependent (BOLD) signal to electroencephalographic (EEG) signals in traditional frequency bands (δ, θ, α, β, and γ), but the relationship between BOLD and its direct frequency correlates in the infraslow band (<1 Hz) has been little studied. Previously, work in rodents showed that infraslow local field potentials play a role in functional connectivity, particularly in the dynamic organization of large-scale networks. To examine the relationship between infraslow activity and network dynamics in humans, direct current (DC) EEG and resting state magnetic resonance imaging data were acquired simultaneously. The DC EEG signals were correlated with the BOLD signal in patterns that resembled resting state networks. Subsequent dynamic analysis showed that the correlation between DC EEG and the BOLD signal varied substantially over time, even within individual subjects. The variation in DC EEG appears to reflect the time-varying contribution of different resting state networks. Furthermore, some of the patterns of DC EEG and BOLD correlation are consistent with previous work demonstrating quasiperiodic spatiotemporal patterns of large-scale network activity in resting state. These findings demonstrate that infraslow electrical activity is linked to BOLD fluctuations in humans and that it may provide a basis for large-scale organization comparable to that observed in animal studies. PMID:28462586

Harmonic Brain Modes: A Unifying Framework for Linking Space and Time in Brain Dynamics.

PubMed

Atasoy, Selen; Deco, Gustavo; Kringelbach, Morten L; Pearson, Joel

2018-06-01

A fundamental characteristic of spontaneous brain activity is coherent oscillations covering a wide range of frequencies. Interestingly, these temporal oscillations are highly correlated among spatially distributed cortical areas forming structured correlation patterns known as the resting state networks, although the brain is never truly at "rest." Here, we introduce the concept of harmonic brain modes-fundamental building blocks of complex spatiotemporal patterns of neural activity. We define these elementary harmonic brain modes as harmonic modes of structural connectivity; that is, connectome harmonics, yielding fully synchronous neural activity patterns with different frequency oscillations emerging on and constrained by the particular structure of the brain. Hence, this particular definition implicitly links the hitherto poorly understood dimensions of space and time in brain dynamics and its underlying anatomy. Further we show how harmonic brain modes can explain the relationship between neurophysiological, temporal, and network-level changes in the brain across different mental states ( wakefulness, sleep, anesthesia, psychedelic). Notably, when decoded as activation of connectome harmonics, spatial and temporal characteristics of neural activity naturally emerge from the interplay between excitation and inhibition and this critical relation fits the spatial, temporal, and neurophysiological changes associated with different mental states. Thus, the introduced framework of harmonic brain modes not only establishes a relation between the spatial structure of correlation patterns and temporal oscillations (linking space and time in brain dynamics), but also enables a new dimension of tools for understanding fundamental principles underlying brain dynamics in different states of consciousness.

Solar Radiation Patterns and Glaciers in the Western Himalaya

NASA Astrophysics Data System (ADS)

Dobreva, I. D.; Bishop, M. P.

2013-12-01

Glacier dynamics in the Himalaya are poorly understood, in part due to variations in topography and climate. It is well known that solar radiation is the dominant surface-energy component governing ablation, although the spatio-temporal patterns of surface irradiance have not been thoroughly investigated given modeling limitations and topographic variations including altitude, relief, and topographic shielding. Glaciation and topographic conditions may greatly influence supraglacial characteristics and glacial dynamics. Consequently, our research objectives were to develop a GIS-based solar radiation model that accounts for Earth's orbital, spectral, atmospheric and topographic dependencies, in order to examine the spatio-temporal surface irradiance patterns on glaciers in the western Himalaya. We specifically compared irradiance patterns to supraglacial characteristics and ice-flow velocity fields. Shuttle Radar Mapping Mission (SRTM) 90 m data were used to compute geomorphometric parameters that were input into the solar radiation model. Simulations results for 2013 were produced for the summer ablation season. Direct irradiance, diffuse-skylight, and total irradiance variations were compared and related to glacier altitude profiles of ice velocity and land-surface topographic parameters. Velocity and surface information were derived from analyses of ASTER satellite data. Results indicate that the direct irradiance significantly varies across the surface of glaciers given local topography and meso-scale relief conditions. Furthermore, the magnitude of the diffuse-skylight irradiance varies with altitude and as a result, glaciers in different topographic settings receive different amounts of surface irradiance. Spatio-temporal irradiance patterns appear to be related to glacier surface conditions including supraglacial lakes, and are spatially coincident with ice-flow velocity conditions on some glaciers. Collectively, our results demonstrate that glacier sensitivity to climate change is also locally controlled by numerous multi-scale topographic parameters.

Predicting variations of perceptual performance across individuals from neural activity using pattern classifiers.

PubMed

Das, Koel; Giesbrecht, Barry; Eckstein, Miguel P

2010-07-15

Within the past decade computational approaches adopted from the field of machine learning have provided neuroscientists with powerful new tools for analyzing neural data. For instance, previous studies have applied pattern classification algorithms to electroencephalography data to predict the category of presented visual stimuli, human observer decision choices and task difficulty. Here, we quantitatively compare the ability of pattern classifiers and three ERP metrics (peak amplitude, mean amplitude, and onset latency of the face-selective N170) to predict variations across individuals' behavioral performance in a difficult perceptual task identifying images of faces and cars embedded in noise. We investigate three different pattern classifiers (Classwise Principal Component Analysis, CPCA; Linear Discriminant Analysis, LDA; and Support Vector Machine, SVM), five training methods differing in the selection of training data sets and three analyses procedures for the ERP measures. We show that all three pattern classifier algorithms surpass traditional ERP measurements in their ability to predict individual differences in performance. Although the differences across pattern classifiers were not large, the CPCA method with training data sets restricted to EEG activity for trials in which observers expressed high confidence about their decisions performed the highest at predicting perceptual performance of observers. We also show that the neural activity predicting the performance across individuals was distributed through time starting at 120ms, and unlike the face-selective ERP response, sustained for more than 400ms after stimulus presentation, indicating that both early and late components contain information correlated with observers' behavioral performance. Together, our results further demonstrate the potential of pattern classifiers compared to more traditional ERP techniques as an analysis tool for modeling spatiotemporal dynamics of the human brain and relating neural activity to behavior. Copyright 2010 Elsevier Inc. All rights reserved.

Spatiotemporal trends of illegal activities from ranger-collected data in a Ugandan national park.

PubMed

Critchlow, R; Plumptre, A J; Driciru, M; Rwetsiba, A; Stokes, E J; Tumwesigye, C; Wanyama, F; Beale, C M

2015-10-01

Within protected areas, biodiversity loss is often a consequence of illegal resource use. Understanding the patterns and extent of illegal activities is therefore essential for effective law enforcement and prevention of biodiversity declines. We used extensive data, commonly collected by ranger patrols in many protected areas, and Bayesian hierarchical models to identify drivers, trends, and distribution of multiple illegal activities within the Queen Elizabeth Conservation Area (QECA), Uganda. Encroachment (e.g., by pastoralists with cattle) and poaching of noncommercial animals (e.g., snaring bushmeat) were the most prevalent illegal activities within the QECA. Illegal activities occurred in different areas of the QECA. Poaching of noncommercial animals was most widely distributed within the national park. Overall, ecological covariates, although significant, were not useful predictors for occurrence of illegal activities. Instead, the location of illegal activities in previous years was more important. There were significant increases in encroachment and noncommercial plant harvesting (nontimber products) during the study period (1999-2012). We also found significant spatiotemporal variation in the occurrence of all activities. Our results show the need to explicitly model ranger patrol effort to reduce biases from existing uncorrected or capture per unit effort analyses. Prioritization of ranger patrol strategies is needed to target illegal activities; these strategies are determined by protected area managers, and therefore changes at a site-level can be implemented quickly. These strategies should also be informed by the location of past occurrences of illegal activity: the most useful predictor of future events. However, because spatial and temporal changes in illegal activities occurred, regular patrols throughout the protected area, even in areas of low occurrence, are also required. © 2015 Society for Conservation Biology.

Spatio-temporal pattern of viral meningitis in Michigan, 1993-2001

NASA Astrophysics Data System (ADS)

Greene, Sharon K.; Schmidt, Mark A.; Stobierski, Mary Grace; Wilson, Mark L.

2005-05-01

To characterize Michigan's high viral meningitis incidence rates, 8,803 cases from 1993-2001 were analyzed for standard epidemiological indices, geographic distribution, and spatio-temporal clusters. Blacks and infants were found to be high-risk groups. Annual seasonality and interannual variability in epidemic magnitude were apparent. Cases were concentrated in southern Michigan, and cumulative incidence was correlated with population density at the county level (r=0.45, p<0.001). Kulldorff's Scan test identified the occurrence of spatio-temporal clusters in Lower Michigan during July-October 1998 and 2001 (p=0.01). More extensive data on cases, laboratory isolates, sociodemographics, and environmental exposures should improve detection and enhance the effectiveness of a Space-Time Information System aimed at prevention.

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks.

PubMed

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-22

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

PubMed Central

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-01-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability. PMID:27874024

Exploring Spatio-temporal Dynamics of Cellular Automata for Pattern Recognition in Networks

NASA Astrophysics Data System (ADS)

Miranda, Gisele Helena Barboni; Machicao, Jeaneth; Bruno, Odemir Martinez

2016-11-01

Network science is an interdisciplinary field which provides an integrative approach for the study of complex systems. In recent years, network modeling has been used for the study of emergent phenomena in many real-world applications. Pattern recognition in networks has been drawing attention to the importance of network characterization, which may lead to understanding the topological properties that are related to the network model. In this paper, the Life-Like Network Automata (LLNA) method is introduced, which was designed for pattern recognition in networks. LLNA uses the network topology as a tessellation of Cellular Automata (CA), whose dynamics produces a spatio-temporal pattern used to extract the feature vector for network characterization. The method was evaluated using synthetic and real-world networks. In the latter, three pattern recognition applications were used: (i) identifying organisms from distinct domains of life through their metabolic networks, (ii) identifying online social networks and (iii) classifying stomata distribution patterns varying according to different lighting conditions. LLNA was compared to structural measurements and surpasses them in real-world applications, achieving improvement in the classification rate as high as 23%, 4% and 7% respectively. Therefore, the proposed method is a good choice for pattern recognition applications using networks and demonstrates potential for general applicability.

Similar Running Economy With Different Running Patterns Along the Aerial-Terrestrial Continuum.

PubMed

Lussiana, Thibault; Gindre, Cyrille; Hébert-Losier, Kim; Sagawa, Yoshimasa; Gimenez, Philippe; Mourot, Laurent

2017-04-01

No unique or ideal running pattern is the most economical for all runners. Classifying the global running patterns of individuals into 2 categories (aerial and terrestrial) using the Volodalen method could permit a better understanding of the relationship between running economy (RE) and biomechanics. The main purpose was to compare the RE of aerial and terrestrial runners. Two coaches classified 58 runners into aerial (n = 29) or terrestrial (n = 29) running patterns on the basis of visual observations. RE, muscle activity, kinematics, and spatiotemporal parameters of both groups were measured during a 5-min run at 12 km/h on a treadmill. Maximal oxygen uptake (V̇O 2 max) and peak treadmill speed (PTS) were assessed during an incremental running test. No differences were observed between aerial and terrestrial patterns for RE, V̇O 2 max, and PTS. However, at 12 km/h, aerial runners exhibited earlier gastrocnemius lateralis activation in preparation for contact, less dorsiflexion at ground contact, higher coactivation indexes, and greater leg stiffness during stance phase than terrestrial runners. Terrestrial runners had more pronounced semitendinosus activation at the start and end of the running cycle, shorter flight time, greater leg compression, and a more rear-foot strike. Different running patterns were associated with similar RE. Aerial runners appear to rely more on elastic energy utilization with a rapid eccentric-concentric coupling time, whereas terrestrial runners appear to propel the body more forward rather than upward to limit work against gravity. Excluding runners with a mixed running pattern from analyses did not affect study interpretation.

Spatiotemporal Symmetry in Rings of Coupled Biological Oscillators of Physarum Plasmodial Slime Mold

NASA Astrophysics Data System (ADS)

Takamatsu, Atsuko; Tanaka, Reiko; Yamada, Hiroyasu; Nakagaki, Toshiyuki; Fujii, Teruo; Endo, Isao

2001-08-01

Spatiotemporal patterns in rings of coupled biological oscillators of the plasmodial slime mold, Physarum polycephalum, were investigated by comparing with results analyzed by the symmetric Hopf bifurcation theory based on group theory. In three-, four-, and five-oscillator systems, all types of oscillation modes predicted by the theory were observed including a novel oscillation mode, a half period oscillation, which has not been reported anywhere in practical systems. Our results support the effectiveness of the symmetric Hopf bifurcation theory in practical systems.

Spatiotemporal symmetry in rings of coupled biological oscillators of Physarum plasmodial slime mold.

PubMed

Takamatsu, A; Tanaka, R; Yamada, H; Nakagaki, T; Fujii, T; Endo, I

2001-08-13

Spatiotemporal patterns in rings of coupled biological oscillators of the plasmodial slime mold, Physarum polycephalum, were investigated by comparing with results analyzed by the symmetric Hopf bifurcation theory based on group theory. In three-, four-, and five-oscillator systems, all types of oscillation modes predicted by the theory were observed including a novel oscillation mode, a half period oscillation, which has not been reported anywhere in practical systems. Our results support the effectiveness of the symmetric Hopf bifurcation theory in practical systems.

Spatiotemporal Mapping of Interictal Spike Propagation: A Novel Methodology Applied to Pediatric Intracranial EEG Recordings

PubMed Central

Tomlinson, Samuel B.; Bermudez, Camilo; Conley, Chiara; Brown, Merritt W.; Porter, Brenda E.; Marsh, Eric D.

2016-01-01

Synchronized cortical activity is implicated in both normative cognitive functioning and many neurologic disorders. For epilepsy patients with intractable seizures, irregular synchronization within the epileptogenic zone (EZ) is believed to provide the network substrate through which seizures initiate and propagate. Mapping the EZ prior to epilepsy surgery is critical for detecting seizure networks in order to achieve postsurgical seizure control. However, automated techniques for characterizing epileptic networks have yet to gain traction in the clinical setting. Recent advances in signal processing and spike detection have made it possible to examine the spatiotemporal propagation of interictal spike discharges across the epileptic cortex. In this study, we present a novel methodology for detecting, extracting, and visualizing spike propagation and demonstrate its potential utility as a biomarker for the EZ. Eighteen presurgical intracranial EEG recordings were obtained from pediatric patients ultimately experiencing favorable (i.e., seizure-free, n = 9) or unfavorable (i.e., seizure-persistent, n = 9) surgical outcomes. Novel algorithms were applied to extract multichannel spike discharges and visualize their spatiotemporal propagation. Quantitative analysis of spike propagation was performed using trajectory clustering and spatial autocorrelation techniques. Comparison of interictal propagation patterns revealed an increase in trajectory organization (i.e., spatial autocorrelation) among Sz-Free patients compared with Sz-Persist patients. The pathophysiological basis and clinical implications of these findings are considered. PMID:28066315

Spatio-temporal variations in the diversity and abundance of commercially important Decapoda and Stomatopoda in subtropical Hong Kong waters

NASA Astrophysics Data System (ADS)

Lui, Karen K. Y.; Ng, Jasmine S. S.; Leung, Kenneth M. Y.

2007-05-01

In subtropical Hong Kong, western waters (WW) are strongly influenced by the freshwater input from the Pearl River estuary, especially during summer monsoon, whereas eastern waters (EW) are predominantly influenced by oceanic currents throughout the year. Such hydrographical differences may lead to spatio-temporal differences in biodiversity of benthic communities. This study investigated the diversity and abundance of commercially important decapods and stomatopods in EW (i.e. Tolo Harbour and Channel) and WW (i.e. Tuen Mun and Lantau Island) of Hong Kong using monthly trawl surveys (August 2003-May 2005). In total, 22 decapod and nine stomatopod species were recorded. The penaeid Metapenaeopsis sp. and stomatopod Oratosquillina interrupta were the most abundant and dominant crustaceans in EW and WW, respectively. Both univariate and multivariate analyses showed that WW supported significantly higher abundance, biomass and diversity of crustaceans than EW, although there were significant between-site and within-site variations in community structure. Higher abundance and biomass of crustaceans were recorded in summer than winter. Such spatio-temporal variations could be explained by differences in the hydrography, environmental conditions and anthropogenic impacts between the two areas. Temporal patterns in the abundance-biomass comparison curves and negative W-statistics suggest that the communities have been highly disturbed in both areas, probably due to anthropogenic activities such as bottom trawling and marine pollution.

Aging and rejuvenation of active matter under topological constraints.

PubMed

Janssen, Liesbeth M C; Kaiser, Andreas; Löwen, Hartmut

2017-07-18

The coupling of active, self-motile particles to topological constraints can give rise to novel non-equilibrium dynamical patterns that lack any passive counterpart. Here we study the behavior of self-propelled rods confined to a compact spherical manifold by means of Brownian dynamics simulations. We establish the state diagram and find that short active rods at sufficiently high density exhibit a glass transition toward a disordered state characterized by persistent self-spinning motion. By periodically melting and revitrifying the spherical spinning glass, we observe clear signatures of time-dependent aging and rejuvenation physics. We quantify the crucial role of activity in these non-equilibrium processes, and rationalize the aging dynamics in terms of an absorbing-state transition toward a more stable active glassy state. Our results demonstrate both how concepts of passive glass phenomenology can carry over into the realm of active matter, and how topology can enrich the collective spatiotemporal dynamics in inherently non-equilibrium systems.

Measuring Memory and Attention to Preview in Motion.

PubMed

Jagacinski, Richard J; Hammond, Gordon M; Rizzi, Emanuele

2017-08-01

Objective Use perceptual-motor responses to perturbations to reveal the spatio-temporal detail of memory for the recent past and attention to preview when participants track a winding roadway. Background Memory of the recently passed roadway can be inferred from feedback control models of the participants' manual movement patterns. Similarly, attention to preview of the upcoming roadway can be inferred from feedforward control models of manual movement patterns. Method Perturbation techniques were used to measure these memory and attention functions. Results In a laboratory tracking task, the bandwidth of lateral roadway deviations was found to primarily influence memory for the past roadway rather than attention to preview. A secondary auditory/verbal/vocal memory task resulted in higher velocity error and acceleration error in the tracking task but did not affect attention to preview. Attention to preview was affected by the frequency pattern of sinusoidal perturbations of the roadway. Conclusion Perturbation techniques permit measurement of the spatio-temporal span of memory and attention to preview that affect tracking a winding roadway. They also provide new ways to explore goal-directed forgetting and spatially distributed attention in the context of movement. More generally, these techniques provide sensitive measures of individual differences in cognitive aspects of action. Application Models of driving behavior and assessment of driving skill may benefit from more detailed spatio-temporal measurement of attention to preview.

Alternans and Spiral Breakup in an Excitable Reaction-Diffusion System: A Simulation Study

PubMed Central

Gani, M. Osman; Ogawa, Toshiyuki

2014-01-01

The determination of the mechanisms of spiral breakup in excitable media is still an open problem for researchers. In the context of cardiac electrophysiological activities, spiral breakup exhibits complex spatiotemporal pattern known as ventricular fibrillation. The latter is the major cause of sudden cardiac deaths all over the world. In this paper, we numerically study the instability of periodic planar traveling wave solution in two dimensions. The emergence of stable spiral pattern is observed in the considered model. This pattern occurs when the heart is malfunctioning (i.e., ventricular tachycardia). We show that the spiral wave breakup is a consequence of the transverse instability of the planar traveling wave solutions. The alternans, that is, the oscillation of pulse widths, is observed in our simulation results. Moreover, we calculate the widths of spiral pulses numerically and observe that the stable spiral pattern bifurcates to an oscillatory wave pattern in a one-parameter family of solutions. The spiral breakup occurs far below the bifurcation when the maximum and the minimum excited states become more distinct, and hence the alternans becomes more pronounced. PMID:27379274

Alternans and Spiral Breakup in an Excitable Reaction-Diffusion System: A Simulation Study.

PubMed

Gani, M Osman; Ogawa, Toshiyuki

2014-01-01

The determination of the mechanisms of spiral breakup in excitable media is still an open problem for researchers. In the context of cardiac electrophysiological activities, spiral breakup exhibits complex spatiotemporal pattern known as ventricular fibrillation. The latter is the major cause of sudden cardiac deaths all over the world. In this paper, we numerically study the instability of periodic planar traveling wave solution in two dimensions. The emergence of stable spiral pattern is observed in the considered model. This pattern occurs when the heart is malfunctioning (i.e., ventricular tachycardia). We show that the spiral wave breakup is a consequence of the transverse instability of the planar traveling wave solutions. The alternans, that is, the oscillation of pulse widths, is observed in our simulation results. Moreover, we calculate the widths of spiral pulses numerically and observe that the stable spiral pattern bifurcates to an oscillatory wave pattern in a one-parameter family of solutions. The spiral breakup occurs far below the bifurcation when the maximum and the minimum excited states become more distinct, and hence the alternans becomes more pronounced.

Characterization of the Fire Regime and Drivers of Fires in the West African Tropical Forest

NASA Astrophysics Data System (ADS)

Dwomoh, F. K.; Wimberly, M. C.

2016-12-01

The Upper Guinean forest (UGF), encompassing the tropical regions of West Africa, is a globally significant biodiversity hotspot and a critically important socio-economic and ecological resource for the region. However, the UGF is one of the most human-disturbed tropical forest ecosystems with the only remaining large patches of original forests distributed in protected areas, which are embedded in a hotspot of climate stress & land use pressures, increasing their vulnerability to fire. We hypothesized that human impacts and climate interact to drive spatial and temporal variability in fire, with fire exhibiting distinctive seasonality and sensitivity to drought in areas characterized by different population densities, agricultural practices, vegetation types, and levels of forest degradation. We used the MODIS active fire product to identify and characterize fire activity in the major ecoregions of the UGF. We used TRMM rainfall data to measure climatic variability and derived indicators of human land use from a variety of geospatial datasets. We employed time series modeling to identify the influences of drought indices and other antecedent climatic indicators on temporal patterns of active fire occurrence. We used a variety of modeling approaches to assess the influences of human activities and land cover variables on the spatial pattern of fire activity. Our results showed that temporal patterns of fire activity in the UGF were related to precipitation, but these relationships were spatially heterogeneous. The pattern of fire seasonality varied geographically, reflecting both climatological patterns and agricultural practices. The spatial pattern of fire activity was strongly associated with vegetation gradients and anthropogenic activities occurring at fine spatial scales. The Guinean forest-savanna mosaic ecoregion had the most fires. This study contributes to our understanding of UGF fire regime and the spatio-temporal dynamics of tropical forest fires in response to intense human and climatic drivers.

Spatiotemporal and plantar pressure patterns of 1000 healthy individuals aged 3-101 years.

PubMed

McKay, Marnee J; Baldwin, Jennifer N; Ferreira, Paulo; Simic, Milena; Vanicek, Natalie; Wojciechowski, Elizabeth; Mudge, Anita; Burns, Joshua

2017-10-01

The purpose of this study was to establish normative reference values for spatiotemporal and plantar pressure parameters, and to investigate the influence of demographic, anthropometric and physical characteristics. In 1000 healthy males and females aged 3-101 years, spatiotemporal and plantar pressure data were collected barefoot with the Zeno™ walkway and Emed ® platform. Correlograms were developed to visualise the relationships between widely reported spatiotemporal and pressure variables with demographic (age, gender), anthropometric (height, mass, waist circumference) and physical characteristics (ankle strength, ankle range of motion, vibration perception) in children aged 3-9 years, adolescents aged 10-19 years, adults aged 20-59 years and older adults aged over 60 years. A comprehensive catalogue of 31 spatiotemporal and pressure variables were generated from 1000 healthy individuals. The key findings were that gait velocity was stable during adolescence and adulthood, while children and older adults walked at a comparable slower speed. Peak pressures increased during childhood to older adulthood. Children demonstrated highest peak pressures beneath the rearfoot whilst adolescents, adults and older adults demonstrated highest pressures at the forefoot. Main factors influencing spatiotemporal and pressure parameters were: increased age, height, body mass and waist circumference, as well as ankle dorsiflexion and plantarflexion strength. This study has established whole of life normative reference values of widely used spatiotemporal and plantar pressure parameters, and revealed changes to be expected across the lifespan. Copyright © 2017 Elsevier B.V. All rights reserved.

Defects formation and spiral waves in a network of neurons in presence of electromagnetic induction.

PubMed

Rostami, Zahra; Jafari, Sajad

2018-04-01

Complex anatomical and physiological structure of an excitable tissue (e.g., cardiac tissue) in the body can represent different electrical activities through normal or abnormal behavior. Abnormalities of the excitable tissue coming from different biological reasons can lead to formation of some defects. Such defects can cause some successive waves that may end up to some additional reorganizing beating behaviors like spiral waves or target waves. In this study, formation of defects and the resulting emitted waves in an excitable tissue are investigated. We have considered a square array network of neurons with nearest-neighbor connections to describe the excitable tissue. Fundamentally, electrophysiological properties of ion currents in the body are responsible for exhibition of electrical spatiotemporal patterns. More precisely, fluctuation of accumulated ions inside and outside of cell causes variable electrical and magnetic field. Considering undeniable mutual effects of electrical field and magnetic field, we have proposed the new Hindmarsh-Rose (HR) neuronal model for the local dynamics of each individual neuron in the network. In this new neuronal model, the influence of magnetic flow on membrane potential is defined. This improved model holds more bifurcation parameters. Moreover, the dynamical behavior of the tissue is investigated in different states of quiescent, spiking, bursting and even chaotic state. The resulting spatiotemporal patterns are represented and the time series of some sampled neurons are displayed, as well.

Spatiotemporal Organization of Energy Release Events in the Quiet Solar Corona

NASA Technical Reports Server (NTRS)

Uritsky, Vadim M.; Davila, Joseph M.

2014-01-01

Using data from the STEREO and SOHO spacecraft, we show that temporal organization of energy release events in the quiet solar corona is close to random, in contrast to the clustered behavior of flaring times in solar active regions. The locations of the quiet-Sun events follow the meso- and supergranulation pattern of the underling photosphere. Together with earlier reports of the scale-free event size statistics, our findings suggest that quiet solar regions responsible for bulk coronal heating operate in a driven self-organized critical state, possibly involving long-range Alfvenic interactions.

A New Individually Addressable Micro-LED Array for Photogenetic Neural Stimulation.

PubMed

McGovern, B; Berlinguer Palmini, R; Grossman, N; Drakakis, E; Poher, V; Neil, M A A; Degenaar, P

2010-12-01

Here, we demonstrate the use of a micro light emitting diode (LED) array as a powerful tool for complex spatiotemporal control of photosensitized neurons. The array can generate arbitrary, 2-D, excitation patterns with millisecond and micrometer resolution. In particular, we describe an active matrix control address system to allow simultaneous control of 256 individual micro LEDs. We present the system optically integrated into a microscope environment and patch clamp electrophysiology. The results show that the emitters have sufficient radiance at the required wavelength to stimulate neurons expressing channelrhodopsin-2 (ChR2).

Recent human history governs global ant invasion dynamics

Treesearch

Cleo Bertelsmeier; Sébastien Ollier; Andrew Liebhold; Laurent Keller

2017-01-01

Human trade and travel are breaking down biogeographic barriers, resulting in shifts in the geographical distribution of organisms, yet it remains largely unknown whether different alien species generally follow similar spatiotemporal colonization patterns and how such patterns are driven by trends in global trade. Here, we analyse the global distribution of 241 alien...

Changes in spatiotemporal land use patterns in selected hydrogeomorphic areas of China and the USA

USDA-ARS?s Scientific Manuscript database

Differences exist in land use/cover pattern and its change between the P. R. China and the USA. In order to describe those differences, land use changes in representative regions were quantitatively analyzed and compared. Xiamen City, Changzhutan region and Liupan Mountains regions were selected to ...

Analyzing seasonal patterns of wildfire exposure factors in Sardinia, Italy

Treesearch

Michele Salis; Alan A. Ager; Fermin J. Alcasena; Bachisio Arca; Mark A. Finney; Grazia Pellizzaro; Donatella Spano

2015-01-01

In this paper, we applied landscape scale wildfire simulation modeling to explore the spatiotemporal patterns of wildfire likelihood and intensity in the island of Sardinia (Italy). We also performed wildfire exposure analysis for selected highly valued resources on the island to identify areas characterized by high risk. We observed substantial variation in burn...

Spatio-temporal dynamics of a tree-killing beetle and its predator

Treesearch

Aaron S. Weed; Matthew P. Ayres; Andrew M. Liebhold; Ronald F. Billings

2016-01-01

Resolving linkages between local-scale processes and regional-scale patterns in abundance of interacting species is important for understanding long-term population stability across spatial scales. Landscape patterning in consumer population dynamics may be largely the result of interactions between consumers and their predators, or driven by spatial variation in basal...

Influence of aging on the neural correlates of autobiographical, episodic, and semantic memory retrieval.

PubMed

St-Laurent, Marie; Abdi, Hervé; Burianová, Hana; Grady, Cheryl L

2011-12-01

We used fMRI to assess the neural correlates of autobiographical, semantic, and episodic memory retrieval in healthy young and older adults. Participants were tested with an event-related paradigm in which retrieval demand was the only factor varying between trials. A spatio-temporal partial least square analysis was conducted to identify the main patterns of activity characterizing the groups across conditions. We identified brain regions activated by all three memory conditions relative to a control condition. This pattern was expressed equally in both age groups and replicated previous findings obtained in a separate group of younger adults. We also identified regions whose activity differentiated among the different memory conditions. These patterns of differentiation were expressed less strongly in the older adults than in the young adults, a finding that was further confirmed by a barycentric discriminant analysis. This analysis showed an age-related dedifferentiation in autobiographical and episodic memory tasks but not in the semantic memory task or the control condition. These findings suggest that the activation of a common memory retrieval network is maintained with age, whereas the specific aspects of brain activity that differ with memory content are more vulnerable and less selectively engaged in older adults. Our results provide a potential neural mechanism for the well-known age differences in episodic/autobiographical memory, and preserved semantic memory, observed when older adults are compared with younger adults.

Genetically Encoded Voltage Indicators: Opportunities and Challenges

PubMed Central

Yang, Helen H.

2016-01-01

A longstanding goal in neuroscience is to understand how spatiotemporal patterns of neuronal electrical activity underlie brain function, from sensory representations to decision making. An emerging technology for monitoring electrical dynamics, voltage imaging using genetically encoded voltage indicators (GEVIs), couples the power of genetics with the advantages of light. Here, we review the properties that determine indicator performance and applicability, discussing both recent progress and technical limitations. We then consider GEVI applications, highlighting studies that have already deployed GEVIs for biological discovery. We also examine which classes of biological questions GEVIs are primed to address and which ones are beyond their current capabilities. As GEVIs are further developed, we anticipate that they will become more broadly used by the neuroscience community to eavesdrop on brain activity with unprecedented spatiotemporal resolution. SIGNIFICANCE STATEMENT Genetically encoded voltage indicators are engineered light-emitting protein sensors that typically report neuronal voltage dynamics as changes in brightness. In this review, we systematically discuss the current state of this emerging method, considering both its advantages and limitations for imaging neural activity. We also present recent applications of this technology and discuss what is feasible now and what we anticipate will become possible with future indicator development. This review will inform neuroscientists of recent progress in the field and help potential users critically evaluate the suitability of genetically encoded voltage indicator imaging to answer their specific biological questions. PMID:27683896

A review and guidance for pattern selection in spatiotemporal system

NASA Astrophysics Data System (ADS)

Wang, Chunni; Ma, Jun

2018-03-01

Pattern estimation and selection in media can give important clues to understand the collective response to external stimulus by detecting the observable variables. Both reaction-diffusion systems (RDs) and neuronal networks can be treated as multi-agent systems from molecular level, intrinsic cooperation, competition. An external stimulus or attack can cause collapse of spatial order and distribution, while appropriate noise can enhance the consensus in the spatiotemporal systems. Pattern formation and synchronization stability can bridge isolated oscillators and the network by coupling these nodes with appropriate connection types. As a result, the dynamical behaviors can be detected and discussed by developing different spatial patterns and realizing network synchronization. Indeed, the collective response of network and multi-agent system depends on the local kinetics of nodes and cells. It is better to know the standard bifurcation analysis and stability control schemes before dealing with network problems. In this review, dynamics discussion and synchronization control on low-dimensional systems, pattern formation and synchronization stability on network, wave stability in RDs and neuronal network are summarized. Finally, possible guidance is presented when some physical effects such as polarization field and electromagnetic induction are considered.

Algorithm for real-time detection of signal patterns using phase synchrony: an application to an electrode array

NASA Astrophysics Data System (ADS)

Sadeghi, Saman; MacKay, William A.; van Dam, R. Michael; Thompson, Michael

2011-02-01

Real-time analysis of multi-channel spatio-temporal sensor data presents a considerable technical challenge for a number of applications. For example, in brain-computer interfaces, signal patterns originating on a time-dependent basis from an array of electrodes on the scalp (i.e. electroencephalography) must be analyzed in real time to recognize mental states and translate these to commands which control operations in a machine. In this paper we describe a new technique for recognition of spatio-temporal patterns based on performing online discrimination of time-resolved events through the use of correlation of phase dynamics between various channels in a multi-channel system. The algorithm extracts unique sensor signature patterns associated with each event during a training period and ranks importance of sensor pairs in order to distinguish between time-resolved stimuli to which the system may be exposed during real-time operation. We apply the algorithm to electroencephalographic signals obtained from subjects tested in the neurophysiology laboratories at the University of Toronto. The extension of this algorithm for rapid detection of patterns in other sensing applications, including chemical identification via chemical or bio-chemical sensor arrays, is also discussed.

Spatiotemporal Interpolation of Elevation Changes Derived from Satellite Altimetry for Jakobshavn Isbrae, Greenland

NASA Technical Reports Server (NTRS)

Hurkmans, R.T.W.L.; Bamber, J.L.; Sorensen, L. S.; Joughin, I. R.; Davis, C. H.; Krabill, W. B.

2012-01-01

Estimation of ice sheet mass balance from satellite altimetry requires interpolation of point-scale elevation change (dHdt) data over the area of interest. The largest dHdt values occur over narrow, fast-flowing outlet glaciers, where data coverage of current satellite altimetry is poorest. In those areas, straightforward interpolation of data is unlikely to reflect the true patterns of dHdt. Here, four interpolation methods are compared and evaluated over Jakobshavn Isbr, an outlet glacier for which widespread airborne validation data are available from NASAs Airborne Topographic Mapper (ATM). The four methods are ordinary kriging (OK), kriging with external drift (KED), where the spatial pattern of surface velocity is used as a proxy for that of dHdt, and their spatiotemporal equivalents (ST-OK and ST-KED).

Parametric spatiotemporal oscillation in reaction-diffusion systems.

PubMed

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Parametric spatiotemporal oscillation in reaction-diffusion systems

NASA Astrophysics Data System (ADS)

Ghosh, Shyamolina; Ray, Deb Shankar

2016-03-01

We consider a reaction-diffusion system in a homogeneous stable steady state. On perturbation by a time-dependent sinusoidal forcing of a suitable scaling parameter the system exhibits parametric spatiotemporal instability beyond a critical threshold frequency. We have formulated a general scheme to calculate the threshold condition for oscillation and the range of unstable spatial modes lying within a V-shaped region reminiscent of Arnold's tongue. Full numerical simulations show that depending on the specificity of nonlinearity of the models, the instability may result in time-periodic stationary patterns in the form of standing clusters or spatially localized breathing patterns with characteristic wavelengths. Our theoretical analysis of the parametric oscillation in reaction-diffusion system is corroborated by full numerical simulation of two well-known chemical dynamical models: chlorite-iodine-malonic acid and Briggs-Rauscher reactions.

Spatio-temporal Outlier Detection in Precipitation Data

NASA Astrophysics Data System (ADS)

Wu, Elizabeth; Liu, Wei; Chawla, Sanjay

The detection of outliers from spatio-temporal data is an important task due to the increasing amount of spatio-temporal data available and the need to understand and interpret it. Due to the limitations of current data mining techniques, new techniques to handle this data need to be developed. We propose a spatio-temporal outlier detection algorithm called Outstretch, which discovers the outlier movement patterns of the top-k spatial outliers over several time periods. The top-k spatial outliers are found using the Exact-Grid Top- k and Approx-Grid Top- k algorithms, which are an extension of algorithms developed by Agarwal et al. [1]. Since they use the Kulldorff spatial scan statistic, they are capable of discovering all outliers, unaffected by neighbouring regions that may contain missing values. After generating the outlier sequences, we show one way they can be interpreted, by comparing them to the phases of the El Niño Southern Oscilliation (ENSO) weather phenomenon to provide a meaningful analysis of the results.

Spatiotemporal coupling of the tongue in amyotrophic lateral sclerosis

PubMed Central

Kuruvilla, Mili S.; Green, Jordan R.; Yunusova, Yana; Hanford, Kathy

2013-01-01

Purpose The primary aim of the investigation was to identify deficits in spatiotemporal coupling between tongue regions in amyotrophic lateral sclerosis (ALS). The relations between disease-related changes in tongue movement patterns and speech intelligibility was also determined. Methods Eleven individuals with ALS with mild, moderate, and severe dysarthria were recorded using the x-ray microbeam during word productions. A coupling index based on sliding window covariance was used to determine disease-related changes in the coupling between the tongue regions across each word. Results The results indicate decreased spatiotemporal coupling and reduced tongue speed in the moderate-ALS subgroup. Spatiotemporal coupling of the mid-posterior tongue was significantly affected in the moderate-ALS group. Changes in the range of tongue coupling relations and speed of movement were highly correlated with speech intelligibility. Conclusions These results provide new insights into the loss of lingual motor control due to ALS and suggest that measures of tongue performance may provide useful indicators of bulbar disease severity and progression. PMID:22615476

Bayesian Spatiotemporal Analysis of Socio-Ecologic Drivers of Ross River Virus Transmission in Queensland, Australia

PubMed Central

Hu, Wenbiao; Clements, Archie; Williams, Gail; Tong, Shilu; Mengersen, Kerrie

2010-01-01

This study aims to examine the impact of socio-ecologic factors on the transmission of Ross River virus (RRV) infection and to identify areas prone to social and ecologic-driven epidemics in Queensland, Australia. We used a Bayesian spatiotemporal conditional autoregressive model to quantify the relationship between monthly variation of RRV incidence and socio-ecologic factors and to determine spatiotemporal patterns. Our results show that the average increase in monthly RRV incidence was 2.4% (95% credible interval (CrI): 0.1–4.5%) and 2.0% (95% CrI: 1.6–2.3%) for a 1°C increase in monthly average maximum temperature and a 10 mm increase in monthly average rainfall, respectively. A significant spatiotemporal variation and interactive effect between temperature and rainfall on RRV incidence were found. No association between Socio-economic Index for Areas (SEIFA) and RRV was observed. The transmission of RRV in Queensland, Australia appeared to be primarily driven by ecologic variables rather than social factors. PMID:20810846

Spatio-temporal interactions facilitate large carnivore sympatry across a resource gradient

PubMed Central

Karanth, K. Ullas; Srivathsa, Arjun; Puri, Mahi; Parameshwaran, Ravishankar; Kumar, N. Samba

2017-01-01

Species within a guild vary their use of time, space and resources, thereby enabling sympatry. As intra-guild competition intensifies, such behavioural adaptations may become prominent. We assessed mechanisms of facilitating sympatry among dhole (Cuon alpinus), leopard (Panthera pardus) and tiger (Panthera tigris) in tropical forests of India using camera-trap surveys. We examined population-level temporal, spatial and spatio-temporal segregation among them across four reserves representing a gradient of carnivore and prey densities. Temporal and spatial overlaps were higher at lower prey densities. Combined spatio-temporal overlap was minimal, possibly due to chance. We found fine-scale avoidance behaviours at one high-density reserve. Our results suggest that: (i) patterns of spatial, temporal and spatio-temporal segregation in sympatric carnivores do not necessarily mirror each other; (ii) carnivores are likely to adopt temporal, spatial, and spatio-temporal segregation as alternative mechanisms to facilitate sympatry; and (iii) carnivores show adaptability across a gradient of resource availability, a driver of inter-species competition. We discuss behavioural mechanisms that permit carnivores to co-occupy rather than dominate functional niches, and adaptations to varying intensities of competition that are likely to shape structure and dynamics of carnivore guilds. PMID:28179511

Spatio-temporal interactions facilitate large carnivore sympatry across a resource gradient.

PubMed

Karanth, K Ullas; Srivathsa, Arjun; Vasudev, Divya; Puri, Mahi; Parameshwaran, Ravishankar; Kumar, N Samba

2017-02-08

Species within a guild vary their use of time, space and resources, thereby enabling sympatry. As intra-guild competition intensifies, such behavioural adaptations may become prominent. We assessed mechanisms of facilitating sympatry among dhole ( Cuon alpinus ), leopard ( Panthera pardus ) and tiger ( Panthera tigris ) in tropical forests of India using camera-trap surveys. We examined population-level temporal, spatial and spatio-temporal segregation among them across four reserves representing a gradient of carnivore and prey densities. Temporal and spatial overlaps were higher at lower prey densities. Combined spatio-temporal overlap was minimal, possibly due to chance. We found fine-scale avoidance behaviours at one high-density reserve. Our results suggest that: (i) patterns of spatial, temporal and spatio-temporal segregation in sympatric carnivores do not necessarily mirror each other; (ii) carnivores are likely to adopt temporal, spatial, and spatio-temporal segregation as alternative mechanisms to facilitate sympatry; and (iii) carnivores show adaptability across a gradient of resource availability, a driver of inter-species competition. We discuss behavioural mechanisms that permit carnivores to co-occupy rather than dominate functional niches, and adaptations to varying intensities of competition that are likely to shape structure and dynamics of carnivore guilds. © 2017 The Author(s).

Macro-Scale Patterns in Upwelling/Downwelling Activity at North American West Coast

PubMed Central

Saldívar-Lucio, Romeo; Di Lorenzo, Emanuele; Nakamura, Miguel; Villalobos, Héctor; Lluch-Cota, Daniel; Del Monte-Luna, Pablo

2016-01-01

The seasonal and interannual variability of vertical transport (upwelling/downwelling) has been relatively well studied, mainly for the California Current System, including low-frequency changes and latitudinal heterogeneity. The aim of this work was to identify potentially predictable patterns in upwelling/downwelling activity along the North American west coast and discuss their plausible mechanisms. To this purpose we applied the min/max Autocorrelation Factor technique and time series analysis. We found that spatial co-variation of seawater vertical movements present three dominant low-frequency signals in the range of 33, 19 and 11 years, resembling periodicities of: atmospheric circulation, nodal moon tides and solar activity. Those periodicities might be related to the variability of vertical transport through their influence on dominant wind patterns, the position/intensity of pressure centers and the strength of atmospheric circulation cells (wind stress). The low-frequency signals identified in upwelling/downwelling are coherent with temporal patterns previously reported at the study region: sea surface temperature along the Pacific coast of North America, catch fluctuations of anchovy Engraulis mordax and sardine Sardinops sagax, the Pacific Decadal Oscillation, changes in abundance and distribution of salmon populations, and variations in the position and intensity of the Aleutian low. Since the vertical transport is an oceanographic process with strong biological relevance, the recognition of their spatio-temporal patterns might allow for some reasonable forecasting capacity, potentially useful for marine resources management of the region. PMID:27893826

Raindrops of synaptic noise on dual excitability landscape: an approach to astrocyte network modelling

NASA Astrophysics Data System (ADS)

Verisokin, Andrey Yu.; Postnov, Dmitry E.; Verveyko, Darya V.; Brazhe, Alexey R.

2018-04-01

The most abundant non-neuronal cells in the brain, astrocytes, populate all parts of the central nervous system (CNS). Astrocytic calcium activity ranging from subcellular sparkles to intercellular waves is believed to be the key to a plethora of regulatory pathways in the central nervous system from synaptic plasticity to blood flow regulation. Modeling of the calcium wave initiation and transmission and their spatiotemporal dynamics is therefore an important step stone in understanding the crucial cogs of cognition. Astrocytes are active sensors of ongoing neuronal and synaptic activity, and neurotransmitters diffusing from the synaptic cleft make a strong impact on the astrocytic activity. Here we propose a model describing the patterns of calcium wave formation at a single cell level and discuss the interplay between astrocyte shape the calcium waves dynamics driven by local stochastic surges of glutamate simulating synaptic activity.

The effect of the neural activity on topological properties of growing neural networks.

PubMed

Gafarov, F M; Gafarova, V R

2016-09-01

The connectivity structure in cortical networks defines how information is transmitted and processed, and it is a source of the complex spatiotemporal patterns of network's development, and the process of creation and deletion of connections is continuous in the whole life of the organism. In this paper, we study how neural activity influences the growth process in neural networks. By using a two-dimensional activity-dependent growth model we demonstrated the neural network growth process from disconnected neurons to fully connected networks. For making quantitative investigation of the network's activity influence on its topological properties we compared it with the random growth network not depending on network's activity. By using the random graphs theory methods for the analysis of the network's connections structure it is shown that the growth in neural networks results in the formation of a well-known "small-world" network.

Neural Language Processing in Adolescent First-Language Learners

PubMed Central

Ferjan Ramirez, Naja; Leonard, Matthew K.; Torres, Christina; Hatrak, Marla; Halgren, Eric; Mayberry, Rachel I.

2014-01-01

The relation between the timing of language input and development of neural organization for language processing in adulthood has been difficult to tease apart because language is ubiquitous in the environment of nearly all infants. However, within the congenitally deaf population are individuals who do not experience language until after early childhood. Here, we investigated the neural underpinnings of American Sign Language (ASL) in 2 adolescents who had no sustained language input until they were approximately 14 years old. Using anatomically constrained magnetoencephalography, we found that recently learned signed words mainly activated right superior parietal, anterior occipital, and dorsolateral prefrontal areas in these 2 individuals. This spatiotemporal activity pattern was significantly different from the left fronto-temporal pattern observed in young deaf adults who acquired ASL from birth, and from that of hearing young adults learning ASL as a second language for a similar length of time as the cases. These results provide direct evidence that the timing of language experience over human development affects the organization of neural language processing. PMID:23696277

A multi-scale model for hair follicles reveals heterogeneous domains driving rapid spatiotemporal hair growth patterning

PubMed Central

Wang, Qixuan; Oh, Ji Won; Lee, Hye-Lim; Dhar, Anukriti; Peng, Tao; Ramos, Raul; Guerrero-Juarez, Christian Fernando; Wang, Xiaojie; Zhao, Ran; Cao, Xiaoling; Le, Jonathan; Fuentes, Melisa A; Jocoy, Shelby C; Rossi, Antoni R; Vu, Brian; Pham, Kim; Wang, Xiaoyang; Mali, Nanda Maya; Park, Jung Min; Choi, June-Hyug; Lee, Hyunsu; Legrand, Julien M D; Kandyba, Eve; Kim, Jung Chul; Kim, Moonkyu; Foley, John; Yu, Zhengquan; Kobielak, Krzysztof; Andersen, Bogi; Khosrotehrani, Kiarash; Nie, Qing; Plikus, Maksim V

2017-01-01

The control principles behind robust cyclic regeneration of hair follicles (HFs) remain unclear. Using multi-scale modeling, we show that coupling inhibitors and activators with physical growth of HFs is sufficient to drive periodicity and excitability of hair regeneration. Model simulations and experimental data reveal that mouse skin behaves as a heterogeneous regenerative field, composed of anatomical domains where HFs have distinct cycling dynamics. Interactions between fast-cycling chin and ventral HFs and slow-cycling dorsal HFs produce bilaterally symmetric patterns. Ear skin behaves as a hyper-refractory domain with HFs in extended rest phase. Such hyper-refractivity relates to high levels of BMP ligands and WNT antagonists, in part expressed by ear-specific cartilage and muscle. Hair growth stops at the boundaries with hyper-refractory ears and anatomically discontinuous eyelids, generating wave-breaking effects. We posit that similar mechanisms for coupled regeneration with dominant activator, hyper-refractory, and wave-breaker regions can operate in other actively renewing organs. DOI: http://dx.doi.org/10.7554/eLife.22772.001 PMID:28695824

Stochastic many-body problems in ecology, evolution, neuroscience, and systems biology

NASA Astrophysics Data System (ADS)

Butler, Thomas C.

Using the tools of many-body theory, I analyze problems in four different areas of biology dominated by strong fluctuations: The evolutionary history of the genetic code, spatiotemporal pattern formation in ecology, spatiotemporal pattern formation in neuroscience and the robustness of a model circadian rhythm circuit in systems biology. In the first two research chapters, I demonstrate that the genetic code is extremely optimal (in the sense that it manages the effects of point mutations or mistranslations efficiently), more than an order of magnitude beyond what was previously thought. I further show that the structure of the genetic code implies that early proteins were probably only loosely defined. Both the nature of early proteins and the extreme optimality of the genetic code are interpreted in light of recent theory [1] as evidence that the evolution of the genetic code was driven by evolutionary dynamics that were dominated by horizontal gene transfer. I then explore the optimality of a proposed precursor to the genetic code. The results show that the precursor code has only limited optimality, which is interpreted as evidence that the precursor emerged prior to translation, or else never existed. In the next part of the dissertation, I introduce a many-body formalism for reaction-diffusion systems described at the mesoscopic scale with master equations. I first apply this formalism to spatially-extended predator-prey ecosystems, resulting in the prediction that many-body correlations and fluctuations drive population cycles in time, called quasicycles. Most of these results were previously known, but were derived using the system size expansion [2, 3]. I next apply the analytical techniques developed in the study of quasi-cycles to a simple model of Turing patterns in a predator-prey ecosystem. This analysis shows that fluctuations drive the formation of a new kind of spatiotemporal pattern formation that I name "quasi-patterns." These quasi-patterns exist over a much larger range of physically accessible parameters than the patterns predicted in mean field theory and therefore account for the apparent observations in ecology of patterns in regimes where Turing patterns do not occur. I further show that quasi-patterns have statistical properties that allow them to be distinguished empirically from mean field Turing patterns. I next analyze a model of visual cortex in the brain that has striking similarities to the activator-inhibitor model of ecosystem quasi-pattern formation. Through analysis of the resulting phase diagram, I show that the architecture of the neural network in the visual cortex is configured to make the visual cortex robust to unwanted internally generated spatial structure that interferes with normal visual function. I also predict that some geometric visual hallucinations are quasi-patterns and that the visual cortex supports a new phase of spatially scale invariant behavior present far from criticality. In the final chapter, I explore the effects of fluctuations on cycles in systems biology, specifically the pervasive phenomenon of circadian rhythms. By exploring the behavior of a generic stochastic model of circadian rhythms, I show that the circadian rhythm circuit exploits leaky mRNA production to safeguard the cycle from failure. I also show that this safeguard mechanism is highly robust to changes in the rate of leaky mRNA production. Finally, I explore the failure of the deterministic model in two different contexts, one where the deterministic model predicts cycles where they do not exist, and another context in which cycles are not predicted by the deterministic model.

Intra-Urban Human Mobility and Activity Transition: Evidence from Social Media Check-In Data

PubMed Central

Wu, Lun; Zhi, Ye; Sui, Zhengwei; Liu, Yu

2014-01-01

Most existing human mobility literature focuses on exterior characteristics of movements but neglects activities, the driving force that underlies human movements. In this research, we combine activity-based analysis with a movement-based approach to model the intra-urban human mobility observed from about 15 million check-in records during a yearlong period in Shanghai, China. The proposed model is activity-based and includes two parts: the transition of travel demands during a specific time period and the movement between locations. For the first part, we find the transition probability between activities varies over time, and then we construct a temporal transition probability matrix to represent the transition probability of travel demands during a time interval. For the second part, we suggest that the travel demands can be divided into two classes, locationally mandatory activity (LMA) and locationally stochastic activity (LSA), according to whether the demand is associated with fixed location or not. By judging the combination of predecessor activity type and successor activity type we determine three trip patterns, each associated with a different decay parameter. To validate the model, we adopt the mechanism of an agent-based model and compare the simulated results with the observed pattern from the displacement distance distribution, the spatio-temporal distribution of activities, and the temporal distribution of travel demand transitions. The results show that the simulated patterns fit the observed data well, indicating that these findings open new directions for combining activity-based analysis with a movement-based approach using social media check-in data. PMID:24824892

Kalman filter control of a model of spatiotemporal cortical dynamics

PubMed Central

Schiff, Steven J; Sauer, Tim

2007-01-01

Recent advances in Kalman filtering to estimate system state and parameters in nonlinear systems have offered the potential to apply such approaches to spatiotemporal nonlinear systems. We here adapt the nonlinear method of unscented Kalman filtering to observe the state and estimate parameters in a computational spatiotemporal excitable system that serves as a model for cerebral cortex. We demonstrate the ability to track spiral wave dynamics, and to use an observer system to calculate control signals delivered through applied electrical fields. We demonstrate how this strategy can control the frequency of such a system, or quench the wave patterns, while minimizing the energy required for such results. These findings are readily testable in experimental applications, and have the potential to be applied to the treatment of human disease. PMID:18310806

Defects and spatiotemporal disorder in a pattern of falling liquid columns

NASA Astrophysics Data System (ADS)

Brunet, Philippe; Limat, Laurent

2004-10-01

Disordered regimes of a one-dimensional pattern of liquid columns hanging below an overflowing circular dish are investigated experimentally. The interaction of two basic dynamical modes (oscillations and drift) combined with the occurrence of defects (birth of new columns, disappearances by coalescences of two columns) leads to spatiotemporal chaos. When the flow rate is progressively increased, a continuous transition between transient and permanent chaos is pointed into evidence. We introduce the rate of defects as the sole relevant quantity to quantify this “turbulence” without ambiguity. Statistics on both transient and endlessly chaotic regimes enable to define a critical flow rate around which exponents are extracted. Comparisons are drawn with other interfacial pattern-forming systems, where transition towards chaos follows similar steps. Qualitatively, careful examinations of the global dynamics show that the contamination processes are nonlocal and involve the propagation of blocks of elementary laminar states (such as propagative domains or local oscillations), emitted near the defects, which turn out to be essential ingredients of this self-sustained disorder.

Characterization of spiraling patterns in spatial rock-paper-scissors games.

PubMed

Szczesny, Bartosz; Mobilia, Mauro; Rucklidge, Alastair M

2014-09-01

The spatiotemporal arrangement of interacting populations often influences the maintenance of species diversity and is a subject of intense research. Here, we study the spatiotemporal patterns arising from the cyclic competition between three species in two dimensions. Inspired by recent experiments, we consider a generic metapopulation model comprising "rock-paper-scissors" interactions via dominance removal and replacement, reproduction, mutations, pair exchange, and hopping of individuals. By combining analytical and numerical methods, we obtain the model's phase diagram near its Hopf bifurcation and quantitatively characterize the properties of the spiraling patterns arising in each phase. The phases characterizing the cyclic competition away from the Hopf bifurcation (at low mutation rate) are also investigated. Our analytical approach relies on the careful analysis of the properties of the complex Ginzburg-Landau equation derived through a controlled (perturbative) multiscale expansion around the model's Hopf bifurcation. Our results allow us to clarify when spatial "rock-paper-scissors" competition leads to stable spiral waves and under which circumstances they are influenced by nonlinear mobility.

Molecular signaling in live cells studied by FRET

NASA Astrophysics Data System (ADS)

Chien, Shu; Wang, Yingxiao

2011-11-01

Genetically encoded biosensors based on fluorescence resonance energy transfer (FRET) enables visualization of signaling events in live cells with high spatiotemporal resolution. We have used FRET to assess temporal and spatial characteristics for signaling molecules, including tyrosine kinases Src and FAK, small GTPase Rac, calcium, and a membrane-bound matrix metalloproteinase MT1-MMP. Activations of Src and Rac by platelet derived growth factor (PDGF) led to distinct subcellular patterns during cell migration on micropatterned surface, and these two enzymes interact with each other to form a feedback loop with differential regulations at different subcellular locations. We have developed FRET biosensors to monitor FAK activities at rafts vs. non-raft regions of plasma membrane in live cells. In response to cell adhesion on matrix proteins or stimulation by PDGF, the raft-targeting FAK biosensor showed a stronger FRET response than that at non-rafts. The FAK activation at rafts induced by PDGF is mediated by Src. In contrast, the FAK activation at rafts induced by adhesion is independent of Src activity, but rather is essential for Src activation. Thus, Src is upstream to FAK in response to chemical stimulation (PDGF), but FAK is upstream to Src in response to mechanical stimulation (adhesion). A novel biosensor has been developed to dynamically visualize the activity of membrane type-1-matrix metalloproteinase (MT1-MMP), which proteolytically remodels the extracellular matrix. Epidermal growth factor (EGF) directed active MT1-MMP to the leading edge of migrating live cancer cells with local accumulation of EGF receptor via a process dependent on an intact cytoskeletal network. In summary, FRET-based biosensors enable the elucidation of molecular processes and hierarchies underlying spatiotemporal regulation of biological and pathological processes, thus advancing our knowledge on how cells perceive mechanical/chemical cues in space and time to coordinate molecular/cellular functions.

Molecular signaling in live cells studied by FRET

NASA Astrophysics Data System (ADS)

Chien, Shu; Wang, Yingxiao

2012-03-01

Genetically encoded biosensors based on fluorescence resonance energy transfer (FRET) enables visualization of signaling events in live cells with high spatiotemporal resolution. We have used FRET to assess temporal and spatial characteristics for signaling molecules, including tyrosine kinases Src and FAK, small GTPase Rac, calcium, and a membrane-bound matrix metalloproteinase MT1-MMP. Activations of Src and Rac by platelet derived growth factor (PDGF) led to distinct subcellular patterns during cell migration on micropatterned surface, and these two enzymes interact with each other to form a feedback loop with differential regulations at different subcellular locations. We have developed FRET biosensors to monitor FAK activities at rafts vs. non-raft regions of plasma membrane in live cells. In response to cell adhesion on matrix proteins or stimulation by PDGF, the raft-targeting FAK biosensor showed a stronger FRET response than that at non-rafts. The FAK activation at rafts induced by PDGF is mediated by Src. In contrast, the FAK activation at rafts induced by adhesion is independent of Src activity, but rather is essential for Src activation. Thus, Src is upstream to FAK in response to chemical stimulation (PDGF), but FAK is upstream to Src in response to mechanical stimulation (adhesion). A novel biosensor has been developed to dynamically visualize the activity of membrane type-1-matrix metalloproteinase (MT1-MMP), which proteolytically remodels the extracellular matrix. Epidermal growth factor (EGF) directed active MT1-MMP to the leading edge of migrating live cancer cells with local accumulation of EGF receptor via a process dependent on an intact cytoskeletal network. In summary, FRET-based biosensors enable the elucidation of molecular processes and hierarchies underlying spatiotemporal regulation of biological and pathological processes, thus advancing our knowledge on how cells perceive mechanical/chemical cues in space and time to coordinate molecular/cellular functions.

Spatio-temporal mapping of variation potentials in leaves of Helianthus annuus L. seedlings in situ using multi-electrode array

PubMed Central

Zhao, Dong-Jie; Wang, Zhong-Yi; Huang, Lan; Jia, Yong-Peng; Leng, John Q.

2014-01-01

Damaging thermal stimuli trigger long-lasting variation potentials (VPs) in higher plants. Owing to limitations in conventional plant electrophysiological recording techniques, recorded signals are composed of signals originating from all of the cells that are connected to an electrode. This limitation does not enable detailed spatio-temporal distributions of transmission and electrical activities in plants to be visualised. Multi-electrode array (MEA) enables the recording and imaging of dynamic spatio-temporal electrical activities in higher plants. Here, we used an 8 × 8 MEA with a polar distance of 450 μm to measure electrical activities from numerous cells simultaneously. The mapping of the data that were recorded from the MEA revealed the transfer mode of the thermally induced VPs in the leaves of Helianthus annuus L. seedlings in situ. These results suggest that MEA can enable recordings with high spatio-temporal resolution that facilitate the determination of the bioelectrical response mode of higher plants under stress. PMID:24961469

Spatio-temporal mapping of variation potentials in leaves of Helianthus annuus L. seedlings in situ using multi-electrode array.

PubMed

Zhao, Dong-Jie; Wang, Zhong-Yi; Huang, Lan; Jia, Yong-Peng; Leng, John Q

2014-06-25

Damaging thermal stimuli trigger long-lasting variation potentials (VPs) in higher plants. Owing to limitations in conventional plant electrophysiological recording techniques, recorded signals are composed of signals originating from all of the cells that are connected to an electrode. This limitation does not enable detailed spatio-temporal distributions of transmission and electrical activities in plants to be visualised. Multi-electrode array (MEA) enables the recording and imaging of dynamic spatio-temporal electrical activities in higher plants. Here, we used an 8 × 8 MEA with a polar distance of 450 μm to measure electrical activities from numerous cells simultaneously. The mapping of the data that were recorded from the MEA revealed the transfer mode of the thermally induced VPs in the leaves of Helianthus annuus L. seedlings in situ. These results suggest that MEA can enable recordings with high spatio-temporal resolution that facilitate the determination of the bioelectrical response mode of higher plants under stress.

Human spinal locomotor control is based on flexibly organized burst generators.

PubMed

Danner, Simon M; Hofstoetter, Ursula S; Freundl, Brigitta; Binder, Heinrich; Mayr, Winfried; Rattay, Frank; Minassian, Karen

2015-03-01

Constant drive provided to the human lumbar spinal cord by epidural electrical stimulation can cause local neural circuits to generate rhythmic motor outputs to lower limb muscles in people paralysed by spinal cord injury. Epidural spinal cord stimulation thus allows the study of spinal rhythm and pattern generating circuits without their configuration by volitional motor tasks or task-specific peripheral feedback. To reveal spinal locomotor control principles, we studied the repertoire of rhythmic patterns that can be generated by the functionally isolated human lumbar spinal cord, detected as electromyographic activity from the legs, and investigated basic temporal components shared across these patterns. Ten subjects with chronic, motor-complete spinal cord injury were studied. Surface electromyographic responses to lumbar spinal cord stimulation were collected from quadriceps, hamstrings, tibialis anterior, and triceps surae in the supine position. From these data, 10-s segments of rhythmic activity present in the four muscle groups of one limb were extracted. Such samples were found in seven subjects. Physiologically adequate cycle durations and relative extension- and flexion-phase durations similar to those needed for locomotion were generated. The multi-muscle activation patterns exhibited a variety of coactivation, mixed-synergy and locomotor-like configurations. Statistical decomposition of the electromyographic data across subjects, muscles and samples of rhythmic patterns identified three common temporal components, i.e. basic or shared activation patterns. Two of these basic patterns controlled muscles to contract either synchronously or alternatingly during extension- and flexion-like phases. The third basic pattern contributed to the observed muscle activities independently from these extensor- and flexor-related basic patterns. Each bifunctional muscle group was able to express both extensor- and flexor-patterns, with variable ratios across the samples of rhythmic patterns. The basic activation patterns can be interpreted as central drives implemented by spinal burst generators that impose specific spatiotemporally organized activation on the lumbosacral motor neuron pools. Our data thus imply that the human lumbar spinal cord circuits can form burst-generating elements that flexibly combine to obtain a wide range of locomotor outputs from a constant, repetitive input. It may be possible to use this flexibility to incorporate specific adaptations to gait and stance to improve locomotor control, even after severe central nervous system damage. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Human spinal locomotor control is based on flexibly organized burst generators

PubMed Central

Danner, Simon M.; Hofstoetter, Ursula S.; Freundl, Brigitta; Binder, Heinrich; Mayr, Winfried; Rattay, Frank

2015-01-01

Constant drive provided to the human lumbar spinal cord by epidural electrical stimulation can cause local neural circuits to generate rhythmic motor outputs to lower limb muscles in people paralysed by spinal cord injury. Epidural spinal cord stimulation thus allows the study of spinal rhythm and pattern generating circuits without their configuration by volitional motor tasks or task-specific peripheral feedback. To reveal spinal locomotor control principles, we studied the repertoire of rhythmic patterns that can be generated by the functionally isolated human lumbar spinal cord, detected as electromyographic activity from the legs, and investigated basic temporal components shared across these patterns. Ten subjects with chronic, motor-complete spinal cord injury were studied. Surface electromyographic responses to lumbar spinal cord stimulation were collected from quadriceps, hamstrings, tibialis anterior, and triceps surae in the supine position. From these data, 10-s segments of rhythmic activity present in the four muscle groups of one limb were extracted. Such samples were found in seven subjects. Physiologically adequate cycle durations and relative extension- and flexion-phase durations similar to those needed for locomotion were generated. The multi-muscle activation patterns exhibited a variety of coactivation, mixed-synergy and locomotor-like configurations. Statistical decomposition of the electromyographic data across subjects, muscles and samples of rhythmic patterns identified three common temporal components, i.e. basic or shared activation patterns. Two of these basic patterns controlled muscles to contract either synchronously or alternatingly during extension- and flexion-like phases. The third basic pattern contributed to the observed muscle activities independently from these extensor- and flexor-related basic patterns. Each bifunctional muscle group was able to express both extensor- and flexor-patterns, with variable ratios across the samples of rhythmic patterns. The basic activation patterns can be interpreted as central drives implemented by spinal burst generators that impose specific spatiotemporally organized activation on the lumbosacral motor neuron pools. Our data thus imply that the human lumbar spinal cord circuits can form burst-generating elements that flexibly combine to obtain a wide range of locomotor outputs from a constant, repetitive input. It may be possible to use this flexibility to incorporate specific adaptations to gait and stance to improve locomotor control, even after severe central nervous system damage. PMID:25582580

Comparison of glomerular activity patterns by fMRI and wide-field calcium imaging: implications for principles underlying odor mapping

PubMed Central

Sanganahalli, Basavaraju G.; Rebello, Michelle R.; Herman, Peter; Papademetris, Xenophon; Shepherd, Gordon M.; Verhagen, Justus V.; Hyder, Fahmeed

2015-01-01

Functional imaging signals arise from distinct metabolic and hemodynamic events at the neuropil, but how these processes are influenced by pre- and post-synaptic activities need to be understood for quantitative interpretation of stimulus-evoked mapping data. The olfactory bulb (OB) glomeruli, spherical neuropil regions with well-defined neuronal circuitry, can provide insights into this issue. Optical calcium-sensitive fluorescent dye imaging (OICa2+) reflects dynamics of pre-synaptic input to glomeruli, whereas high-resolution functional magnetic resonance imaging (fMRI) using deoxyhemoglobin contrast reveals neuropil function within the glomerular layer where both pre- and post-synaptic activities contribute. We imaged odor-specific activity patterns of the dorsal OB in the same anesthetized rats with fMRI and OICa2+ and then co-registered the respective maps to compare patterns in the same space. Maps by each modality were very reproducible as trial-to-trial patterns for a given odor, overlapping by ~80%. Maps evoked by ethyl butyrate and methyl valerate for a given modality overlapped by ~80%, suggesting activation of similar dorsal glomerular networks by these odors. Comparison of maps generated by both methods for a given odor showed ~70% overlap, indicating similar odor-specific maps by each method. These results suggest that odor-specific glomerular patterns by high-resolution fMRI primarily tracks pre-synaptic input to the OB. Thus combining OICa2+ and fMRI lays the framework for studies of OB processing over a range of spatiotemporal scales, where OICa2+ can feature the fast dynamics of dorsal glomerular clusters and fMRI can map the entire glomerular sheet in the OB. PMID:26631819

Spatial and temporal dimensions of fire activity in the fire-prone eastern Canadian taiga.

PubMed

Erni, Sandy; Arseneault, Dominique; Parisien, Marc-André; Bégin, Yves

2017-03-01

The forest age mosaic is a fundamental attribute of the North American boreal forest. Given that fires are generally lethal to trees, the time since last fire largely determines the composition and structure of forest stands and landscapes. Although the spatiotemporal dynamics of such mosaics has long been assumed to be random under the overwhelming influence of severe fire weather, no long-term reconstruction of mosaic dynamics has been performed from direct field evidence. In this study, we use fire length as a proxy for fire extent across the fire-prone eastern Canadian taiga and systematically reconstruct the spatiotemporal variability of fire extent and fire intervals, as well as the resulting forest age along a 340-km transect for the 1840-2013 time period. Our results indicate an extremely active fire regime over the last two centuries, with an overall burn rate of 2.1% of the land area yr -1 , mainly triggered by seasonal anomalies of high temperature and severe drought. However, the rejuvenation of the age mosaic was strongly patterned in space and time due to the intrinsically lower burn rates in wetland-dominated areas and, more importantly, to the much-reduced likelihood of burning of stands up to 50 years postfire. An extremely high burn rate of ~5% yr -1 would have characterized our study region during the last century in the absence of such fuel age effect. Although recent burn rates and fire sizes are within their range of variability of the last 175 years, a particularly severe weather event allowed a 2013 fire to spread across a large fire refuge, thus shifting the abundance of mature and old forest to a historic low. These results provide reference conditions to evaluate the significance and predict the spatiotemporal dynamics and impacts of the currently strengthening fire activity in the North American boreal forest. © 2016 John Wiley & Sons Ltd.

Optogenetic Modulation and Multi-Electrode Analysis of Cerebellar Networks In Vivo

PubMed Central

Kruse, Wolfgang; Krause, Martin; Aarse, Janna; Mark, Melanie D.; Manahan-Vaughan, Denise; Herlitze, Stefan

2014-01-01

The firing patterns of cerebellar Purkinje cells (PCs), as the sole output of the cerebellar cortex, determine and tune motor behavior. PC firing is modulated by various inputs from different brain regions and by cell-types including granule cells (GCs), climbing fibers and inhibitory interneurons. To understand how signal integration in PCs occurs and how subtle changes in the modulation of PC firing lead to adjustment of motor behaviors, it is important to precisely record PC firing in vivo and to control modulatory pathways in a spatio-temporal manner. Combining optogenetic and multi-electrode approaches, we established a new method to integrate light-guides into a multi-electrode system. With this method we are able to variably position the light-guide in defined regions relative to the recording electrode with micrometer precision. We show that PC firing can be precisely monitored and modulated by light-activation of channelrhodopsin-2 (ChR2) expressed in PCs, GCs and interneurons. Thus, this method is ideally suited to investigate the spatio/temporal modulation of PCs in anesthetized and in behaving mice. PMID:25144735

The Redox Code.

PubMed

Jones, Dean P; Sies, Helmut

2015-09-20

The redox code is a set of principles that defines the positioning of the nicotinamide adenine dinucleotide (NAD, NADP) and thiol/disulfide and other redox systems as well as the thiol redox proteome in space and time in biological systems. The code is richly elaborated in an oxygen-dependent life, where activation/deactivation cycles involving O₂ and H₂O₂ contribute to spatiotemporal organization for differentiation, development, and adaptation to the environment. Disruption of this organizational structure during oxidative stress represents a fundamental mechanism in system failure and disease. Methodology in assessing components of the redox code under physiological conditions has progressed, permitting insight into spatiotemporal organization and allowing for identification of redox partners in redox proteomics and redox metabolomics. Complexity of redox networks and redox regulation is being revealed step by step, yet much still needs to be learned. Detailed knowledge of the molecular patterns generated from the principles of the redox code under defined physiological or pathological conditions in cells and organs will contribute to understanding the redox component in health and disease. Ultimately, there will be a scientific basis to a modern redox medicine.

Possible Quantum Absorber Effects in Cortical Synchronization

NASA Astrophysics Data System (ADS)

Kämpf, Uwe

The Wheeler-Feynman transactional "absorber" approach was proposed originally to account for anomalous resonance coupling between spatio-temporally distant measurement partners in entangled quantum states of so-called Einstein-Podolsky-Rosen paradoxes, e.g. of spatio-temporal non-locality, quantum teleportation, etc. Applied to quantum brain dynamics, however, this view provides an anticipative resonance coupling model for aspects of cortical synchronization and recurrent visual action control. It is proposed to consider the registered activation patterns of neuronal loops in so-called synfire chains not as a result of retarded brain communication processes, but rather as surface effects of a system of standing waves generated in the depth of visual processing. According to this view, they arise from a counterbalance between the actual input's delayed bottom-up data streams and top-down recurrent information-processing of advanced anticipative signals in a Wheeler-Feynman-type absorber mode. In the framework of a "time-loop" model, findings about mirror neurons in the brain cortex are suggested to be at least partially associated with temporal rather than spatial mirror functions of visual processing, similar to phase conjugate adaptive resonance-coupling in nonlinear optics.

A CMOS IC-based multisite measuring system for stimulation and recording in neural preparations in vitro

PubMed Central

Tateno, Takashi; Nishikawa, Jun

2014-01-01

In this report, we describe the system integration of a complementary metal oxide semiconductor (CMOS) integrated circuit (IC) chip, capable of both stimulation and recording of neurons or neural tissues, to investigate electrical signal propagation within cellular networks in vitro. The overall system consisted of three major subunits: a 5.0 × 5.0 mm CMOS IC chip, a reconfigurable logic device (field-programmable gate array, FPGA), and a PC. To test the system, microelectrode arrays (MEAs) were used to extracellularly measure the activity of cultured rat cortical neurons and mouse cortical slices. The MEA had 64 bidirectional (stimulation and recording) electrodes. In addition, the CMOS IC chip was equipped with dedicated analog filters, amplification stages, and a stimulation buffer. Signals from the electrodes were sampled at 15.6 kHz with 16-bit resolution. The measured input-referred circuitry noise was 10.1 μ V root mean square (10 Hz to 100 kHz), which allowed reliable detection of neural signals ranging from several millivolts down to approximately 33 μ Vpp. Experiments were performed involving the stimulation of neurons with several spatiotemporal patterns and the recording of the triggered activity. An advantage over current MEAs, as demonstrated by our experiments, includes the ability to stimulate (voltage stimulation, 5-bit resolution) spatiotemporal patterns in arbitrary subsets of electrodes. Furthermore, the fast stimulation reset mechanism allowed us to record neuronal signals from a stimulating electrode around 3 ms after stimulation. We demonstrate that the system can be directly applied to, for example, auditory neural prostheses in conjunction with an acoustic sensor and a sound processing system. PMID:25346683

Ongoing Walking Recovery 2 Years After Locomotor Training in a Child With Severe Incomplete Spinal Cord Injury

PubMed Central

Fox, Emily J.; Tester, Nicole J.; Phadke, Chetan P.; Nair, Preeti M.; Senesac, Claudia R.; Howland, Dena R.

2010-01-01

Background and Purpose The authors previously reported on walking recovery in a nonambulatory child with chronic, severe, incomplete cervical spinal cord injury (SCI) after 76 sessions of locomotor training (LT). Although clinical measures did not predict his recovery, reciprocal patterned leg movements developed, affording recovery of independent walking with a reverse rolling walker. The long-term functional limitations and secondary complications often associated with pediatric-onset SCI necessitate continued follow-up of children with SCI. Therefore, the purpose of this case report is to describe this child's walking function and musculoskeletal growth and development during the 2 years since his participation in an LT program and subsequent walking recovery. Case Description Following LT, the child attended elementary school as a full-time ambulator. He was evaluated 1 month (baseline), 1 year, and 2 years after LT. Examination of walking function included measures of walking independence, gait speed and spatiotemporal parameters, gait kinematics, and daily step activity. Growth and development were assessed by tracking his height, weight, incidence of musculoskeletal complications, and gross motor task performance. Outcomes Over the 2 years, the child continued to ambulate independently with a reverse rolling walker, increasing his fastest gait speed. Spatiotemporal and kinematic features of his walking improved, and daily step activity increased. Height and weight remained on their preinjury trajectory and within age-appropriate norms. The child experienced only minor musculoskeletal complications. Additionally, he gained the ability to use reciprocal patterned leg movements during locomotor tasks such as assisted stair climbing and independent tricycle pedaling. Conclusions Two years after recovery of walking, this child with incomplete SCI had maintained and improved his walking function and experienced age-appropriate growth and development. PMID:20299409

Ongoing walking recovery 2 years after locomotor training in a child with severe incomplete spinal cord injury.

PubMed

Fox, Emily J; Tester, Nicole J; Phadke, Chetan P; Nair, Preeti M; Senesac, Claudia R; Howland, Dena R; Behrman, Andrea L

2010-05-01

The authors previously reported on walking recovery in a nonambulatory child with chronic, severe, incomplete cervical spinal cord injury (SCI) after 76 sessions of locomotor training (LT). Although clinical measures did not predict his recovery, reciprocal patterned leg movements developed, affording recovery of independent walking with a reverse rolling walker. The long-term functional limitations and secondary complications often associated with pediatric-onset SCI necessitate continued follow-up of children with SCI. Therefore, the purpose of this case report is to describe this child's walking function and musculoskeletal growth and development during the 2 years since his participation in an LT program and subsequent walking recovery. Following LT, the child attended elementary school as a full-time ambulator. He was evaluated 1 month (baseline), 1 year, and 2 years after LT. Examination of walking function included measures of walking independence, gait speed and spatiotemporal parameters, gait kinematics, and daily step activity. Growth and development were assessed by tracking his height, weight, incidence of musculoskeletal complications, and gross motor task performance. Over the 2 years, the child continued to ambulate independently with a reverse rolling walker, increasing his fastest gait speed. Spatiotemporal and kinematic features of his walking improved, and daily step activity increased. Height and weight remained on their preinjury trajectory and within age-appropriate norms. The child experienced only minor musculoskeletal complications. Additionally, he gained the ability to use reciprocal patterned leg movements during locomotor tasks such as assisted stair climbing and independent tricycle pedaling. Two years after recovery of walking, this child with incomplete SCI had maintained and improved his walking function and experienced age-appropriate growth and development.

A quantitative validated model reveals two phases of transcriptional regulation for the gap gene giant in Drosophila.

PubMed

Hoermann, Astrid; Cicin-Sain, Damjan; Jaeger, Johannes

2016-03-15

Understanding eukaryotic transcriptional regulation and its role in development and pattern formation is one of the big challenges in biology today. Most attempts at tackling this problem either focus on the molecular details of transcription factor binding, or aim at genome-wide prediction of expression patterns from sequence through bioinformatics and mathematical modelling. Here we bridge the gap between these two complementary approaches by providing an integrative model of cis-regulatory elements governing the expression of the gap gene giant (gt) in the blastoderm embryo of Drosophila melanogaster. We use a reverse-engineering method, where mathematical models are fit to quantitative spatio-temporal reporter gene expression data to infer the regulatory mechanisms underlying gt expression in its anterior and posterior domains. These models are validated through prediction of gene expression in mutant backgrounds. A detailed analysis of our data and models reveals that gt is regulated by domain-specific CREs at early stages, while a late element drives expression in both the anterior and the posterior domains. Initial gt expression depends exclusively on inputs from maternal factors. Later, gap gene cross-repression and gt auto-activation become increasingly important. We show that auto-regulation creates a positive feedback, which mediates the transition from early to late stages of regulation. We confirm the existence and role of gt auto-activation through targeted mutagenesis of Gt transcription factor binding sites. In summary, our analysis provides a comprehensive picture of spatio-temporal gene regulation by different interacting enhancer elements for an important developmental regulator. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

A CMOS IC-based multisite measuring system for stimulation and recording in neural preparations in vitro.

PubMed

Tateno, Takashi; Nishikawa, Jun

2014-01-01

In this report, we describe the system integration of a complementary metal oxide semiconductor (CMOS) integrated circuit (IC) chip, capable of both stimulation and recording of neurons or neural tissues, to investigate electrical signal propagation within cellular networks in vitro. The overall system consisted of three major subunits: a 5.0 × 5.0 mm CMOS IC chip, a reconfigurable logic device (field-programmable gate array, FPGA), and a PC. To test the system, microelectrode arrays (MEAs) were used to extracellularly measure the activity of cultured rat cortical neurons and mouse cortical slices. The MEA had 64 bidirectional (stimulation and recording) electrodes. In addition, the CMOS IC chip was equipped with dedicated analog filters, amplification stages, and a stimulation buffer. Signals from the electrodes were sampled at 15.6 kHz with 16-bit resolution. The measured input-referred circuitry noise was 10.1 μ V root mean square (10 Hz to 100 kHz), which allowed reliable detection of neural signals ranging from several millivolts down to approximately 33 μ Vpp. Experiments were performed involving the stimulation of neurons with several spatiotemporal patterns and the recording of the triggered activity. An advantage over current MEAs, as demonstrated by our experiments, includes the ability to stimulate (voltage stimulation, 5-bit resolution) spatiotemporal patterns in arbitrary subsets of electrodes. Furthermore, the fast stimulation reset mechanism allowed us to record neuronal signals from a stimulating electrode around 3 ms after stimulation. We demonstrate that the system can be directly applied to, for example, auditory neural prostheses in conjunction with an acoustic sensor and a sound processing system.

A new method for discovering behavior patterns among animal movements

USGS Publications Warehouse

Wang, Y.; Luo, Ze; Takekawa, John Y.; Prosser, Diann J.; Xiong, Y.; Newman, S.; Xiao, X.; Batbayar, N.; Spragens, Kyle A.; Balachandran, S.; Yan, B.

2016-01-01

Advanced satellite tracking technologies enable biologists to track animal movements at fine spatial and temporal scales. The resultant data present opportunities and challenges for understanding animal behavioral mechanisms. In this paper, we develop a new method to elucidate animal movement patterns from tracking data. Here, we propose the notion of continuous behavior patterns as a concise representation of popular migration routes and underlying sequential behaviors during migration. Each stage in the pattern is characterized in terms of space (i.e., the places traversed during movements) and time (i.e. the time spent in those places); that is, the behavioral state corresponding to a stage is inferred according to the spatiotemporal and sequential context. Hence, the pattern may be interpreted predictably. We develop a candidate generation and refinement framework to derive all continuous behavior patterns from raw trajectories. In the framework, we first define the representative spots to denote the underlying potential behavioral states that are extracted from individual trajectories according to the similarity of relaxed continuous locations in certain distinct time intervals. We determine the common behaviors of multiple individuals according to the spatiotemporal proximity of representative spots and apply a projection-based extension approach to generate candidate sequential behavior sequences as candidate patterns. Finally, the candidate generation procedure is combined with a refinement procedure to derive continuous behavior patterns. We apply an ordered processing strategy to accelerate candidate refinement. The proposed patterns and discovery framework are evaluated through conceptual experiments on both real GPS-tracking and large synthetic datasets.

A new method for discovering behavior patterns among animal movements.

PubMed

Wang, Yuwei; Luo, Ze; Takekawa, John; Prosser, Diann; Xiong, Yan; Newman, Scott; Xiao, Xiangming; Batbayar, Nyambayar; Spragens, Kyle; Balachandran, Sivananinthaperumal; Yan, Baoping

Advanced satellite tracking technologies enable biologists to track animal movements at fine spatial and temporal scales. The resultant data present opportunities and challenges for understanding animal behavioral mechanisms. In this paper, we develop a new method to elucidate animal movement patterns from tracking data. Here, we propose the notion of continuous behavior patterns as a concise representation of popular migration routes and underlying sequential behaviors during migration. Each stage in the pattern is characterized in terms of space (i.e., the places traversed during movements) and time (i.e. the time spent in those places); that is, the behavioral state corresponding to a stage is inferred according to the spatiotemporal and sequential context. Hence, the pattern may be interpreted predictably. We develop a candidate generation and refinement framework to derive all continuous behavior patterns from raw trajectories. In the framework, we first define the representative spots to denote the underlying potential behavioral states that are extracted from individual trajectories according to the similarity of relaxed continuous locations in certain distinct time intervals. We determine the common behaviors of multiple individuals according to the spatiotemporal proximity of representative spots and apply a projection-based extension approach to generate candidate sequential behavior sequences as candidate patterns. Finally, the candidate generation procedure is combined with a refinement procedure to derive continuous behavior patterns. We apply an ordered processing strategy to accelerate candidate refinement. The proposed patterns and discovery framework are evaluated through conceptual experiments on both real GPS-tracking and large synthetic datasets.