Journal article
Copula regression analysis of simultaneously recorded frontal eye field and inferotemporal spiking activity during object-based working memory
The Journal of neuroscience, v 35(23), pp 8745-8757
10 Jun 2015
PMID: 26063909
Abstract
Inferotemporal (IT) neurons are known to exhibit persistent, stimulus-selective activity during the delay period of object-based working memory tasks. Frontal eye field (FEF) neurons show robust, spatially selective delay period activity during memory-guided saccade tasks. We present a copula regression paradigm to examine neural interaction of these two types of signals between areas IT and FEF of the monkey during a working memory task. This paradigm is based on copula models that can account for both marginal distribution over spiking activity of individual neurons within each area and joint distribution over ensemble activity of neurons between areas. Considering the popular GLMs as marginal models, we developed a general and flexible likelihood framework that uses the copula to integrate separate GLMs into a joint regression analysis. Such joint analysis essentially leads to a multivariate analog of the marginal GLM theory and hence efficient model estimation. In addition, we show that Granger causality between spike trains can be readily assessed via the likelihood ratio statistic. The performance of this method is validated by extensive simulations, and compared favorably to the widely used GLMs. When applied to spiking activity of simultaneously recorded FEF and IT neurons during working memory task, we observed significant Granger causality influence from FEF to IT, but not in the opposite direction, suggesting the role of the FEF in the selection and retention of visual information during working memory. The copula model has the potential to provide unique neurophysiological insights about network properties of the brain.
Metrics
Details
- Title
- Copula regression analysis of simultaneously recorded frontal eye field and inferotemporal spiking activity during object-based working memory
- Creators
- Meng Hu - School of Biomedical Engineering, Drexel University, Philadelphia, Pennsylvania 19104Kelsey L Clark - Department of Neurobiology andXiajing Gong - School of Biomedical Engineering, Drexel University, Philadelphia, Pennsylvania 19104Behrad Noudoost - Department of Neurobiology andMingyao Li - Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania 19104Tirin Moore - Department of Neurobiology and Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, California 94305, andHualou Liang - School of Biomedical Engineering, Drexel University, Philadelphia, Pennsylvania 19104, hualou.liang@drexel.edu
- Publication Details
- The Journal of neuroscience, v 35(23), pp 8745-8757
- Publisher
- Society for Neuroscience; United States
- Grant note
- EY014924 / NEI NIH HHS R01 EY014924 / NEI NIH HHS T32 MH020016 / NIMH NIH HHS R56 EY014924 / NEI NIH HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000358249000008
- Scopus ID
- 2-s2.0-84930905247
- Other Identifier
- 991014878011704721
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Neurosciences