Extracting neuronal functional network dynamics via adaptive Granger causality analysis

Sheikhattar Alireza; Miran Sina; Liu JiFritz Jonathan B.Shamma Shihab A.Kanold Patrick O.Babadi Behtash

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Extracting neuronal functional network dynamics via adaptive Granger causality analysis

机译：Extracting neuronal functional network dynamics via adaptive Granger causality analysis

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摘要

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

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《Proceedings of the National Academy of Sciences of the United States of America.》 |2018年第17期|E3869-E3878|共10页
作者
Sheikhattar Alireza; Miran Sina; Liu JiFritz Jonathan B.Shamma Shihab A.Kanold Patrick O.Babadi Behtash;
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作者单位

Univ Maryland, Dept Elect & Comp Engn, College Pk, MD 20742 USA;

Univ Maryland, Dept Biol, College Pk, MD 20742 USA;

Univ Maryland, Inst Syst Res, College Pk, MD 20742 USA;

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收录信息美国《科学引文索引》(SCI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
原文格式 PDF
正文语种英语
中图分类自然科学总论;
关键词
Granger causality; adaptive filtering; functional network dynamics; point processes; sparsity;

Extracting neuronal functional network dynamics via adaptive Granger causality analysis

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