Literature DB >> 24702246

Functional integration between brain regions at rest occurs in multiple-frequency bands.

Suril R Gohel1, Bharat B Biswal.   

Abstract

Studies of resting-state fMRI have shown that blood oxygen level dependent (BOLD) signals giving rise to temporal correlation across voxels (or regions) are dominated by low-frequency fluctuations in the range of ∼ 0.01-0.1 Hz. These low-frequency fluctuations have been further divided into multiple distinct frequency bands (slow-5 and -4) based on earlier neurophysiological studies, though low sampling frequency of fMRI (∼ 0.5 Hz) has substantially limited the exploration of other known frequency bands of neurophysiological origins (slow-3, -2, and -1). In this study, we used resting-state fMRI data acquired from 21 healthy subjects at a higher sampling frequency of 1.5 Hz to assess the presence of resting-state functional connectivity (RSFC) across multiple frequency bands: slow-5 to slow-1. The effect of different frequency bands on spatial extent and connectivity strength for known resting-state networks (RSNs) was also evaluated. RSNs were derived using independent component analysis and seed-based correlation. Commonly known RSNs, such as the default mode, the fronto-parietal, the dorsal attention, and the visual networks, were consistently observed at multiple frequency bands. Significant inter-hemispheric connectivity was observed between each seed and its contra lateral brain region across all frequency bands, though overall spatial extent of seed-based correlation maps decreased in slow-2 and slow-1 frequency bands. These results suggest that functional integration between brain regions at rest occurs over multiple frequency bands and RSFC is a multiband phenomenon. These results also suggest that further investigation of BOLD signal in multiple frequency bands for related cognitive processes should be undertaken.

Entities:  

Keywords:  BOLD; ICA; RSFC; high frequency; multiband

Mesh:

Year:  2014        PMID: 24702246      PMCID: PMC4313418          DOI: 10.1089/brain.2013.0210

Source DB:  PubMed          Journal:  Brain Connect        ISSN: 2158-0014


  45 in total

1.  High-resolution fMRI using multislice partial k-space GR-EPI with cubic voxels.

Authors:  J S Hyde; B B Biswal; A Jesmanowicz
Journal:  Magn Reson Med       Date:  2001-07       Impact factor: 4.668

2.  Functional covariance networks: obtaining resting-state networks from intersubject variability.

Authors:  Paul A Taylor; Suril Gohel; Xin Di; Martin Walter; Bharat B Biswal
Journal:  Brain Connect       Date:  2012-08-28

3.  Electrophysiological signatures of resting state networks in the human brain.

Authors:  D Mantini; M G Perrucci; C Del Gratta; G L Romani; M Corbetta
Journal:  Proc Natl Acad Sci U S A       Date:  2007-08-01       Impact factor: 11.205

4.  Resting-state functional connectivity reflects structural connectivity in the default mode network.

Authors:  Michael D Greicius; Kaustubh Supekar; Vinod Menon; Robert F Dougherty
Journal:  Cereb Cortex       Date:  2008-04-09       Impact factor: 5.357

Review 5.  The intrinsic electrophysiological properties of mammalian neurons: insights into central nervous system function.

Authors:  R R Llinás
Journal:  Science       Date:  1988-12-23       Impact factor: 47.728

6.  Rat brains also have a default mode network.

Authors:  Hanbing Lu; Qihong Zou; Hong Gu; Marcus E Raichle; Elliot A Stein; Yihong Yang
Journal:  Proc Natl Acad Sci U S A       Date:  2012-02-21       Impact factor: 11.205

7.  Very low frequency EEG oscillations and the resting brain in young adults: a preliminary study of localisation, stability and association with symptoms of inattention.

Authors:  S Helps; C James; S Debener; A Karl; E J S Sonuga-Barke
Journal:  J Neural Transm (Vienna)       Date:  2007-11-12       Impact factor: 3.575

8.  Resting-state functional connectivity of the rat brain.

Authors:  Christopher P Pawela; Bharat B Biswal; Younghoon R Cho; Dennis S Kao; Rupeng Li; Seth R Jones; Marie L Schulte; Hani S Matloub; Anthony G Hudetz; James S Hyde
Journal:  Magn Reson Med       Date:  2008-05       Impact factor: 4.668

9.  Tracking dynamic resting-state networks at higher frequencies using MR-encephalography.

Authors:  Hsu-Lei Lee; Benjamin Zahneisen; Thimo Hugger; Pierre LeVan; Jürgen Hennig
Journal:  Neuroimage       Date:  2012-10-13       Impact factor: 6.556

10.  Multiplexed echo planar imaging for sub-second whole brain FMRI and fast diffusion imaging.

Authors:  David A Feinberg; Steen Moeller; Stephen M Smith; Edward Auerbach; Sudhir Ramanna; Matthias Gunther; Matt F Glasser; Karla L Miller; Kamil Ugurbil; Essa Yacoub
Journal:  PLoS One       Date:  2010-12-20       Impact factor: 3.240

View more
  79 in total

1.  Low frequency steady-state brain responses modulate large scale functional networks in a frequency-specific means.

Authors:  Yi-Feng Wang; Zhiliang Long; Qian Cui; Feng Liu; Xiu-Juan Jing; Heng Chen; Xiao-Nan Guo; Jin H Yan; Hua-Fu Chen
Journal:  Hum Brain Mapp       Date:  2015-10-29       Impact factor: 5.038

2.  Dysfunctional white-matter networks in medicated and unmedicated benign epilepsy with centrotemporal spikes.

Authors:  Yuchao Jiang; Li Song; Xuan Li; Yaodan Zhang; Yan Chen; Sisi Jiang; Changyue Hou; Dezhong Yao; Xiaoming Wang; Cheng Luo
Journal:  Hum Brain Mapp       Date:  2019-04-01       Impact factor: 5.038

3.  Using Low-Frequency Oscillations to Detect Temporal Lobe Epilepsy with Machine Learning.

Authors:  Gyujoon Hwang; Veena A Nair; Jed Mathis; Cole J Cook; Rosaleena Mohanty; Gengyan Zhao; Neelima Tellapragada; Candida Ustine; Onyekachi O Nwoke; Charlene Rivera-Bonet; Megan Rozman; Linda Allen; Courtney Forseth; Dace N Almane; Peter Kraegel; Andrew Nencka; Elizabeth Felton; Aaron F Struck; Rasmus Birn; Rama Maganti; Lisa L Conant; Colin J Humphries; Bruce Hermann; Manoj Raghavan; Edgar A DeYoe; Jeffrey R Binder; Elizabeth Meyerand; Vivek Prabhakaran
Journal:  Brain Connect       Date:  2019-03

4.  Altered power spectra in antisocial males during rest as a function of cocaine dependence: A network analysis.

Authors:  Isabelle Simard; William J Denomme; Matthew S Shane
Journal:  Psychiatry Res Neuroimaging       Date:  2020-12-11       Impact factor: 2.376

5.  High frequency functional brain networks in neonates revealed by rapid acquisition resting state fMRI.

Authors:  Adam P R Smith-Collins; Karen Luyt; Axel Heep; Risto A Kauppinen
Journal:  Hum Brain Mapp       Date:  2015-03-18       Impact factor: 5.038

6.  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

7.  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

8.  Identification of Subclinical Language Deficit Using Machine Learning Classification Based on Poststroke Functional Connectivity Derived from Low Frequency Oscillations.

Authors:  Rosaleena Mohanty; Veena A Nair; Neelima Tellapragada; Leroy M Williams; Theresa J Kang; Vivek Prabhakaran
Journal:  Brain Connect       Date:  2019-02-07

9.  Stronger right hemisphere functional connectivity supports executive aspects of language in older adults.

Authors:  Victoria H Gertel; Haoyun Zhang; Michele T Diaz
Journal:  Brain Lang       Date:  2020-04-11       Impact factor: 2.381

10.  BOLD fractional contribution to resting-state functional connectivity above 0.1 Hz.

Authors:  Jingyuan E Chen; Gary H Glover
Journal:  Neuroimage       Date:  2014-12-12       Impact factor: 6.556

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.