Literature DB >> 26208871

Significant feed-forward connectivity revealed by high frequency components of BOLD fMRI signals.

Fa-Hsuan Lin1, Ying-Hua Chu2, Yi-Cheng Hsu2, Jo-Fu Lotus Lin2, Kevin W-K Tsai3, Shang-Yueh Tsai4, Wen-Jui Kuo5.   

Abstract

Granger causality analysis has been suggested as a method of estimating causal modulation without specifying the direction of information flow a priori. Using BOLD-contrast functional MRI (fMRI) data, such analysis has been typically implemented in the time domain. In this study, we used magnetic resonance inverse imaging, a method of fast fMRI enabled by massively parallel detection allowing up to 10 Hz sampling rate, to investigate the causal modulation at different frequencies up to 5 Hz. Using a visuomotor two-choice reaction-time task, both the spectral decomposition of Granger causality and isolated effective coherence revealed that the BOLD signal at frequency up to 3 Hz can still be used to estimate significant dominant directions of information flow consistent with results from the time-domain Granger causality analysis. We showed the specificity of estimated dominant directions of information flow at high frequencies by contrasting causality estimates using data collected during the visuomotor task and resting state. Our data suggest that hemodynamic responses carry physiological information related to inter-regional modulation at frequency higher than what has been commonly considered.
Copyright © 2015 Elsevier Inc. All rights reserved.

Keywords:  Causality; Granger; Spectral decomposition; Visuomotor

Mesh:

Year:  2015        PMID: 26208871     DOI: 10.1016/j.neuroimage.2015.07.036

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  14 in total

1.  Nuisance Regression of High-Frequency Functional Magnetic Resonance Imaging Data: Denoising Can Be Noisy.

Authors:  Jingyuan E Chen; Hesamoddin Jahanian; Gary H Glover
Journal:  Brain Connect       Date:  2017-01-05

2.  Enhanced subject-specific resting-state network detection and extraction with fast fMRI.

Authors:  Burak Akin; Hsu-Lei Lee; Jürgen Hennig; Pierre LeVan
Journal:  Hum Brain Mapp       Date:  2016-10-03       Impact factor: 5.038

3.  Integrated and segregated frequency architecture of the human brain network.

Authors:  Junji Ma; Ying Lin; Chuanlin Hu; Jinbo Zhang; Yangyang Yi; Zhengjia Dai
Journal:  Brain Struct Funct       Date:  2021-01-03       Impact factor: 3.270

4.  Fast fMRI can detect oscillatory neural activity in humans.

Authors:  Laura D Lewis; Kawin Setsompop; Bruce R Rosen; Jonathan R Polimeni
Journal:  Proc Natl Acad Sci U S A       Date:  2016-10-11       Impact factor: 11.205

5.  Investigating mechanisms of fast BOLD responses: The effects of stimulus intensity and of spatial heterogeneity of hemodynamics.

Authors:  Jingyuan E Chen; Gary H Glover; Nina E Fultz; Bruce R Rosen; Jonathan R Polimeni; Laura D Lewis
Journal:  Neuroimage       Date:  2021-10-14       Impact factor: 7.400

6.  Sparse Estimation of Resting-State Effective Connectivity From fMRI Cross-Spectra.

Authors:  Carolin Lennartz; Jonathan Schiefer; Stefan Rotter; Jürgen Hennig; Pierre LeVan
Journal:  Front Neurosci       Date:  2018-05-08       Impact factor: 4.677

7.  On the detection of high frequency correlations in resting state fMRI.

Authors:  Cameron Trapp; Kishore Vakamudi; Stefan Posse
Journal:  Neuroimage       Date:  2017-02-03       Impact factor: 6.556

Review 8.  Imaging faster neural dynamics with fast fMRI: A need for updated models of the hemodynamic response.

Authors:  Jonathan R Polimeni; Laura D Lewis
Journal:  Prog Neurobiol       Date:  2021-09-12       Impact factor: 11.685

9.  Immediate and Longitudinal Alterations of Functional Networks after Thalamotomy in Essential Tremor.

Authors:  Changwon Jang; Hae-Jeong Park; Won Seok Chang; Chongwon Pae; Jin Woo Chang
Journal:  Front Neurol       Date:  2016-10-24       Impact factor: 4.003

10.  Large-scale cortico-subcortical functional networks in focal epilepsies: The role of the basal ganglia.

Authors:  Eva Výtvarová; Radek Mareček; Jan Fousek; Ondřej Strýček; Ivan Rektor
Journal:  Neuroimage Clin       Date:  2016-12-18       Impact factor: 4.881

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.