Literature DB >> 27845889

Resting state functional magnetic resonance imaging processing techniques in stroke studies.

Golrokh Mirzaei, Hojjat Adeli.   

Abstract

In recent years, there has been considerable research interest in the study of brain connectivity using the resting state functional magnetic resonance imaging (rsfMRI). Studies have explored the brain networks and connection between different brain regions. These studies have revealed interesting new findings about the brain mapping as well as important new insights in the overall organization of functional communication in the brain network. In this paper, after a general discussion of brain networks and connectivity imaging, the brain connectivity and resting state networks are described with a focus on rsfMRI imaging in stroke studies. Then, techniques for preprocessing of the rsfMRI for stroke patients are reviewed, followed by brain connectivity processing techniques. Recent research on brain connectivity using rsfMRI is reviewed with an emphasis on stroke studies. The authors hope this paper generates further interest in this emerging area of computational neuroscience with potential applications in rehabilitation of stroke patients.

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Year:  2016        PMID: 27845889     DOI: 10.1515/revneuro-2016-0052

Source DB:  PubMed          Journal:  Rev Neurosci        ISSN: 0334-1763            Impact factor:   4.353


  3 in total

1.  Ability of an altered functional coupling between resting-state networks to predict behavioral outcomes in subcortical ischemic stroke: A longitudinal study.

Authors:  Yongxin Li; Zeyun Yu; Ping Wu; Jiaxu Chen
Journal:  Front Aging Neurosci       Date:  2022-09-15       Impact factor: 5.702

2.  Co-sparse Non-negative Matrix Factorization.

Authors:  Fan Wu; Jiahui Cai; Canhong Wen; Haizhu Tan
Journal:  Front Neurosci       Date:  2022-01-12       Impact factor: 4.677

3.  Functional Connectivity Changes in Multiple-Frequency Bands in Acute Basal Ganglia Ischemic Stroke Patients: A Machine Learning Approach.

Authors:  Jie Li; Lulu Cheng; Shijian Chen; Jian Zhang; Dongqiang Liu; Zhijian Liang; Huayun Li
Journal:  Neural Plast       Date:  2022-03-20       Impact factor: 3.599

  3 in total

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