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

Curr Opin Neurobiol. 2016 Apr:37:12-15. doi: 10.1016/j.conb.2015.12.006. Epub 2016 Jan 2.

Authors

Mohsen Pourahmadi¹, Siamak Noorbaloochi²

Affiliations

¹ Department of Statistics, Texas A&M University, College Station, TX 77843-3143, United States. Electronic address: [email protected].
² VA HSR&D Center for Chronic Diseases Outcome Research and Department of Medicine, University of Minnesota, Minneapolis, MN 55455-0460, United States.

PMID: 26752736
DOI: 10.1016/j.conb.2015.12.006

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.

Publication types

Review

MeSH terms

Humans
Multivariate Analysis*
Neuroimaging
Neurosciences / standards
Neurosciences / trends*
Time