scholarly journals Analysis and Model of Cortical Slow Waves Acquired with Optical Techniques

2020 ◽  
Vol 3 (1) ◽  
pp. 14 ◽  
Author(s):  
Marco Celotto ◽  
Chiara De Luca ◽  
Paolo Muratore ◽  
Francesco Resta ◽  
Anna Letizia Allegra Mascaro ◽  
...  
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
Imaging Techniques ◽  
Simulated Data ◽  
Neuronal Population ◽  
Slow Waves ◽  
Wide Field ◽  
Analysis Pipeline ◽  
Spatio Temporal

Slow waves (SWs) are spatio-temporal patterns of cortical activity that occur both during natural sleep and anesthesia and are preserved across species. Even though electrophysiological recordings have been largely used to characterize brain states, they are limited in the spatial resolution and cannot target specific neuronal population. Recently, large-scale optical imaging techniques coupled with functional indicators overcame these restrictions, and new pipelines of analysis and novel approaches of SWs modelling are needed to extract relevant features of the spatio-temporal dynamics of SWs from these highly spatially resolved data-sets. Here we combined wide-field fluorescence microscopy and a transgenic mouse model expressing a calcium indicator (GCaMP6f) in excitatory neurons to study SW propagation over the meso-scale under ketamine anesthesia. We developed a versatile analysis pipeline to identify and quantify the spatio-temporal propagation of the SWs. Moreover, we designed a computational simulator based on a simple theoretical model, which takes into account the statistics of neuronal activity, the response of fluorescence proteins and the slow waves dynamics. The simulator was capable of synthesizing artificial signals that could reliably reproduce several features of the SWs observed in vivo, thus enabling a calibration tool for the analysis pipeline. Comparison of experimental and simulated data shows the robustness of the analysis tools and its potential to uncover mechanistic insights of the Slow Wave Activity (SWA).

scholarly journals Development of a Rap1 Flare.Dc Biosensor for Quantitative Measurement of Spatio-Temporal Dynamics In Vivo

2013 ◽  
Vol 104 (2) ◽  
pp. 160a-161a
Author(s):  
Ellen O-Shaughnessy ◽  
Timothy C. Elston ◽  
Klaus M. Hahn
Keyword(s):  
Quantitative Measurement ◽  
Temporal Dynamics ◽  
Spatio Temporal

scholarly journals Arctic avian predators synchronise their spring migration with the northern progression of snowmelt

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Teja Curk ◽  
Ivan Pokrovsky ◽  
Nicolas Lecomte ◽  
Tomas Aarvak ◽  
David F. Brinker ◽  
...  
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
The Arctic ◽  
Migratory Species ◽  
Migration Patterns ◽  
Predator Species ◽  
Movement Data ◽  
Breeding Grounds ◽  
Spatio Temporal ◽  
Spring Snowmelt

Abstract Migratory species display a range of migration patterns between irruptive (facultative) to regular (obligate), as a response to different predictability of resources. In the Arctic, snow directly influences resource availability. The causes and consequences of different migration patterns of migratory species as a response to the snow conditions remains however unexplored. Birds migrating to the Arctic are expected to follow the spring snowmelt to optimise their arrival time and select for snow-free areas to maximise prey encounter en-route. Based on large-scale movement data, we compared the migration patterns of three top predator species of the tundra in relation to the spatio-temporal dynamics of snow cover. The snowy owl, an irruptive migrant, the rough-legged buzzard, with an intermediary migration pattern, and the peregrine falcon as a regular migrant, all followed, as expected, the spring snowmelt during their migrations. However, the owl stayed ahead, the buzzard stayed on, and the falcon stayed behind the spatio-temporal peak in snowmelt. Although none of the species avoided snow-covered areas, they presumably used snow presence as a cue to time their arrival at their breeding grounds. We show the importance of environmental cues for species with different migration patterns.

scholarly journals Early alterations of large-scale brain networks temporal dynamics in young children with autism

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Aurélie Bochet ◽  
Holger Franz Sperdin ◽  
Tonia Anahi Rihs ◽  
Nada Kojovic ◽  
Martina Franchini ◽  
...  
Keyword(s):  
Large Scale ◽  
Developmental Stages ◽  
Temporal Dynamics ◽  
Brain Networks ◽  
Autism Spectrum ◽  
Brain Network ◽  
Clustering Methods ◽  
Early Developmental Stages ◽  
Spatio Temporal ◽  
Early Developmental

AbstractAutism spectrum disorders (ASD) are associated with disruption of large-scale brain network. Recently, we found that directed functional connectivity alterations of social brain networks are a core component of atypical brain development at early developmental stages in ASD. Here, we investigated the spatio-temporal dynamics of whole-brain neuronal networks at a subsecond scale in 113 toddlers and preschoolers (66 with ASD) using an EEG microstate approach. We first determined the predominant microstates using established clustering methods. We identified five predominant microstate (labeled as microstate classes A–E) with significant differences in the temporal dynamics of microstate class B between the groups in terms of increased appearance and prolonged duration. Using Markov chains, we found differences in the dynamic syntax between several maps in toddlers and preschoolers with ASD compared to their TD peers. Finally, exploratory analysis of brain–behavioral relationships within the ASD group suggested that the temporal dynamics of some maps were related to conditions comorbid to ASD during early developmental stages.

scholarly journals Spatio-Temporal Dynamics of Feed Grain Demand of Dairy Cows in China

2020 ◽  
Vol 12 (2) ◽  
pp. 663 ◽  
Author(s):  
Chao Yang Dong ◽  
Bei Bei Ma ◽  
Chun Xia LU
Keyword(s):  
Dairy Cows ◽  
Dairy Cow ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Hot Spot ◽  
Market Environment ◽  
Relative Level ◽  
Resource Endowment ◽  
Spatio Temporal ◽  
Feeding Technology

As the income of urban and rural residents has increased in recent decades in China, dairy products have become an important part of the Chinese diet. Therefore, keeping up with the growing demand for feed grain for dairy cows is a critical issue of feed grain security. Utilizing traditional statistical and spatial statistical methods, this study analyzes the spatio-temporal dynamics of dairy cow feed grain (DCFG) demand on the provincial, regional, and national levels across China from 1990 to 2016. Additionally, this paper explores the impacts of various factors on the spatio-temporal dynamics of DCFG demand using the Geo-Detector method. The results demonstrate that: (1) the temporal dynamics of DCFG demand can be divided into three stages of slow growth, rapid growth, and high-level stability, and the relative level of DCFG demand in the whole animal husbandry tends to decline; (2) at the regional and national levels, the spatial concentration of high DCFG demand has intensified; in particular, North China was the region where the largest demand for DCFG was localized and was increasing at the highest rate; (3) based on the hot spot analysis of provincial DCFG demand, the high and low demand provinces of DCFG have sharp characteristic contrast from north to south China; (4) the spatio-temporal dynamics of DCFG demand in China were essentially co-affected by the four groups of factors (e.g., resource endowment, feeding scale, feeding technology, and market environment), of which resource endowment and feeding scale were the dominant factors. Therefore, in the future, dairy cow feeding in China should promote grain-saving feeding technology, improve the utilization of forage, expand large-scale feeding, and create a good market environment to ensure the reasonable development and sustainability of DCFG demand.

scholarly journals Millennial-scale faunal record reveals differential resilience of European large mammals to human impacts across the Holocene

2016 ◽  
Vol 283 (1827) ◽  
pp. 20152152 ◽  
Author(s):  
Jennifer J. Crees ◽  
Chris Carbone ◽  
Robert S. Sommer ◽  
Norbert Benecke ◽  
Samuel T. Turvey
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
Human Impacts ◽  
Biodiversity Loss ◽  
Mammal Species ◽  
The Holocene ◽  
Range Change ◽  
Spatio Temporal ◽  
Patterns And Processes ◽  
Species Specific

The use of short-term indicators for understanding patterns and processes of biodiversity loss can mask longer-term faunal responses to human pressures. We use an extensive database of approximately 18 700 mammalian zooarchaeological records for the last 11 700 years across Europe to reconstruct spatio-temporal dynamics of Holocene range change for 15 large-bodied mammal species. European mammals experienced protracted, non-congruent range losses, with significant declines starting in some species approximately 3000 years ago and continuing to the present, and with the timing, duration and magnitude of declines varying individually between species. Some European mammals became globally extinct during the Holocene, whereas others experienced limited or no significant range change. These findings demonstrate the relatively early onset of prehistoric human impacts on postglacial biodiversity, and mirror species-specific patterns of mammalian extinction during the Late Pleistocene. Herbivores experienced significantly greater declines than carnivores, revealing an important historical extinction filter that informs our understanding of relative resilience and vulnerability to human pressures for different taxa. We highlight the importance of large-scale, long-term datasets for understanding complex protracted extinction processes, although the dynamic pattern of progressive faunal depletion of European mammal assemblages across the Holocene challenges easy identification of ‘static’ past baselines to inform current-day environmental management and restoration.

scholarly journals Simultaneous in vivo time-lapse stiffness mapping and fluorescence imaging of developing tissue

2018 ◽  
Author(s):  
Amelia J. Thompson ◽  
Iva K. Pillai ◽  
Ivan B. Dimov ◽  
Christine E. Holt ◽  
Kristian Franze
Keyword(s):  
Fluorescence Imaging ◽  
Temporal Dynamics ◽  
Time Lapse ◽  
Tissue Mechanics ◽  
Tissue Stiffness ◽  
Time Resolved ◽  
Force Microscopy ◽  
Atomic Force ◽  
Spatio Temporal

AbstractTissue mechanics is important for development; however, the spatio-temporal dynamics of in vivo tissue stiffness is still poorly understood. We here developed tiv-AFM, combining time-lapse in vivo atomic force microscopy with upright fluorescence imaging of embryonic tissue, to show that in the developing Xenopus brain, a stiffness gradient evolves over time because of differential cell proliferation. Subsequently, axons turn to follow this gradient, underpinning the importance of time-resolved mechanics measurements.

scholarly journals Spatio-temporal dynamics of dengue in Brazil: seasonal travelling waves and determinants of regional synchrony

2018 ◽  
Author(s):  
Mikhail Churakov ◽  
Christian J. Villabona-Arenas ◽  
Moritz U.G. Kraemer ◽  
Henrik Salje ◽  
Simon Cauchemez
Keyword(s):  
Large Scale ◽  
Temporal Dynamics ◽  
Mosquito Control ◽  
Human Mobility ◽  
Travelling Waves ◽  
Seasonal Pattern ◽  
Temporal Analysis ◽  
Vector Ecology ◽  
Spatio Temporal ◽  
Dengue Epidemics

AbstractDengue continues to be the most important vector-borne viral disease globally and in Brazil, where more than 1.4 million cases and over 500 deaths were reported in 2016. Mosquito control programmes and other interventions have not stopped the alarming trend of increasingly large epidemics in the past few years.Here, we analyzed monthly dengue cases reported in Brazil between 2001 and 2016 to better characterize the key drivers of dengue epidemics. Spatio-temporal analysis revealed recurring travelling waves of disease occurrence. Using wavelet methods, we characterised the average seasonal pattern of dengue in Brazil, which starts in the western states of Acre and Rondônia, then travels eastward to the coast before reaching the northeast of the country. Only two states in the north of Brazil (Roraima and Amapá) did not follow the countrywide pattern and had inconsistent timing of dengue epidemics throughout the study period.We also explored epidemic synchrony and timing of annual dengue cycles in Brazilian regions. Using gravity style models combined with climate factors, we showed that both human mobility and vector ecology contribute to spatial patterns of dengue occurrence.This study offers a characterization of the spatial dynamics of dengue in Brazil and its drivers, which could inform intervention strategies against dengue and other arboviruses.Author summaryIn this paper we studied the synchronization of dengue epidemics in Brazilian regions. We found that a typical dengue season in Brazil can be described as a wave travelling from the western part of the country towards the east, with the exception of the two most northern equatorial states that experienced inconsistent seasonality of dengue epidemics.We found that the spatial structure of dengue cases is driven by both climate and human mobility patterns. In particular, precipitation was the most important factor for the seasonality of dengue at finer spatial resolutions.Our findings increase our understanding of large scale dengue patterns and could be used to enhance national control programs against dengue and other arboviruses.

scholarly journals Video Question Answering via Hierarchical Spatio-Temporal Attention Networks

2017 ◽  
Author(s):  
Zhou Zhao ◽  
Qifan Yang ◽  
Deng Cai ◽  
Xiaofei He ◽  
Yueting Zhuang
Keyword(s):  
Visual Information ◽  
Large Scale ◽  
Question Answering ◽  
Temporal Dynamics ◽  
Temporal Attention ◽  
Attention Networks ◽  
Learning Framework ◽  
Spatio Temporal ◽  
The Given ◽  
Video Question Answering

Open-ended video question answering is a challenging problem in visual information retrieval, which automatically generates the natural language answer from the referenced video content according to the question. However, the existing visual question answering works only focus on the static image, which may be ineffectively applied to video question answering due to the temporal dynamics of video contents. In this paper, we consider the problem of open-ended video question answering from the viewpoint of spatio-temporal attentional encoder-decoder learning framework. We propose the hierarchical spatio-temporal attention network for learning the joint representation of the dynamic video contents according to the given question. We then develop the encoder-decoder learning method with reasoning recurrent neural networks for open-ended video question answering. We construct a large-scale video question answering dataset. The extensive experiments show the effectiveness of our method.

scholarly journals Emergence of stable coexistence in a complex microbial community through metabolic cooperation and spatio-temporal niche partitioning

2019 ◽  
Author(s):  
Sonja Blasche ◽  
Yongkyu Kim ◽  
Ruben Mars ◽  
Eleni Kafkia ◽  
Maria Maansson ◽  
...  
Keyword(s):  
Species Interactions ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Niche Partitioning ◽  
Metabolic Cooperation ◽  
Stable Coexistence ◽  
Milk Fermentation ◽  
Complex Microbial Community ◽  
Spatio Temporal ◽  
Natural Milk

SummaryMicrobial communities in nature often feature complex compositional dynamics yet also stable coexistence of diverse species. The mechanistic underpinnings of such dynamic stability remain unclear as system-wide studies have been limited to small engineered communities or synthetic assemblies. Here we show how kefir, a natural milk-fermenting community, realizes stable coexistence through spatio-temporal orchestration of species and metabolite dynamics. During milk fermentation, kefir grains (a polysaccharide matrix synthesized by kefir microbes) grow in mass but remain unchanged in composition. In contrast, the milk is colonized in a dynamic fashion with early members opening metabolic niches for the followers. Through large-scale mapping of metabolic preferences and inter-species interactions, we show how microbes poorly suited for milk survive in, and even dominate, the community through metabolic cooperation and uneven partitioning between the grain and the liquid phase. Overall, our findings reveal how spatio-temporal dynamics promote stable coexistence and have implications for deciphering and modulating complex microbial ecosystems.

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