Multivariate time series analysis of neuroscience data: Some challenges and opportunities

Mohsen Pourahmadi; Siamak Noorbaloochi

doi:10.1016/j.conb.2015.12.006

Multivariate time series analysis of neuroscience data: Some challenges and opportunities

Mohsen Pourahmadi, Siamak Noorbaloochi

Medicine - Veteran's Administration Medical Center

Research output: Contribution to journal › Review article › peer-review

6 Scopus citations

Abstract

Neuroimaging data may be viewed as high-dimensional multivariate time series, and analyzed using techniques from regression analysis, time series analysis and spatiotemporal analysis. We discuss issues related to data quality, model specification, estimation, interpretation, dimensionality and causality. Some recent research areas addressing aspects of some recurring challenges are introduced.

Original language	English (US)
Pages (from-to)	12-15
Number of pages	4
Journal	Current opinion in neurobiology
Volume	37
DOIs	https://doi.org/10.1016/j.conb.2015.12.006
State	Published - Apr 1 2016

Bibliographical note

Funding Information:
The work of the first author was supported by the NSF grant DMS-1309586 and the second author was supported by IIR 12-340 HSR&D grant, Department of Veterans Affairs , Veterans Health Administration , Office of Research and Development , Health Services Research and Development . The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States government.

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abstract = "Neuroimaging data may be viewed as high-dimensional multivariate time series, and analyzed using techniques from regression analysis, time series analysis and spatiotemporal analysis. We discuss issues related to data quality, model specification, estimation, interpretation, dimensionality and causality. Some recent research areas addressing aspects of some recurring challenges are introduced.",

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