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

12 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

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© 2015 Elsevier Ltd.

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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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AB - 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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JO - Current opinion in neurobiology

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

Abstract

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