Literature DB >> 26752736

Multivariate time series analysis of neuroscience data: some challenges and opportunities.

Mohsen Pourahmadi1, Siamak Noorbaloochi2.   

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.
Copyright © 2015 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2016        PMID: 26752736     DOI: 10.1016/j.conb.2015.12.006

Source DB:  PubMed          Journal:  Curr Opin Neurobiol        ISSN: 0959-4388            Impact factor:   6.627


  5 in total

1.  Characterizing Cortex-Wide Dynamics with Wide-Field Calcium Imaging.

Authors:  Chi Ren; Takaki Komiyama
Journal:  J Neurosci       Date:  2021-04-23       Impact factor: 6.167

Review 2.  Brain Synchronization and Multivariate Autoregressive (MVAR) Modeling in Cognitive Neurodynamics.

Authors:  Steven L Bressler; Ashvin Kumar; Isaac Singer
Journal:  Front Syst Neurosci       Date:  2022-06-24

3.  Biclustering fMRI time series: a comparative study.

Authors:  Eduardo N Castanho; Helena Aidos; Sara C Madeira
Journal:  BMC Bioinformatics       Date:  2022-05-23       Impact factor: 3.307

4.  Cross multivariate correlation coefficients as screening tool for analysis of concurrent EEG-fMRI recordings.

Authors:  Hong Ji; Nathan M Petro; Badong Chen; Zejian Yuan; Jianji Wang; Nanning Zheng; Andreas Keil
Journal:  J Neurosci Res       Date:  2018-02-06       Impact factor: 4.164

5.  Exact Partial Information Decompositions for Gaussian Systems Based on Dependency Constraints.

Authors:  Jim W Kay; Robin A A Ince
Journal:  Entropy (Basel)       Date:  2018-03-30       Impact factor: 2.524

  5 in total

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