Name
Title | ||
|---|---|---|
Probing The Functional Circuitry Underlying Auditory Attention Via Dynamic Granger Causality Analysis |
Abstract | ||
|---|---|---|
We consider the problem of inferring time-varying Granger causal interactions among multiple simultaneously recorded spike trains from a neuronal ensemble. We present a dynamic Granger causality measure with sparsity and adaptivity features for point process observations, and estimate it recursively. We develop a statistical inference framework based on asymptotic analysis of deviance, and perform a multiple-hypothesis testing procedure to control the false discovery rate. We apply our method to electrophysiology data recorded from the ferrets auditory and prefrontal cortices during a series of auditory tasks in order to probe the functional circuitry underlying auditory attention at the neuronal scale. |
Year | Venue | Field |
|---|---|---|
2016 | 2016 50TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS | Time series,Computer science,Point process,Granger causality,Statistical inference,Artificial intelligence,Asymptotic analysis,Recursion,False discovery rate,Mathematical optimization,Pattern recognition,Granger causality analysis,Machine learning |
DocType | ISSN | Citations |
Conference | 1058-6393 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| alireza sheikhattar | 1 | 7 | 2.16 |
| Sina Miran | 2 | 2 | 2.44 |
| Jonathan B. Fritz | 3 | 12 | 2.46 |
| Shihab Shamma | 4 | 554 | 67.25 |
| Babadi, Behtash | 5 | 325 | 36.16 |