title: Multivariate time series analysis of neuroscience data: some challenges and opportunities.
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.
authors.affiliation: Department of Statistics, Texas A&M University, College Station, TX 77843-3143, United States. Electronic address: siamak.noorbaloochi@va.gov.
authors.forename: Mohsen
authors.initials: M
authors.lastname: Pourahmadi
authors.affiliation: VA HSR&D Center for Chronic Diseases Outcome Research and Department of Medicine, University of Minnesota, Minneapolis, MN 55455-0460, United States.
authors.forename: Siamak
authors.initials: S
authors.lastname: Noorbaloochi
mesh_terms: D006801:Humans; D015999:Multivariate Analysis; D059906:Neuroimaging; D009488:Neurosciences / Q000592:standards / Q000639:trends*; D013995:Time