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Modeling the Functional Network for Spatial Navigation in the Human Brain
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Frequency-specific network topologies in the resting human brain.

Shuntaro Sasai1, Fumitaka Homae2, Hama Watanabe3

  • 1Graduate School of Education, University of Tokyo Tokyo, Japan ; Department of Psychiatry, University of Wisconsin - Madison Madison, WI, USA.

Frontiers in Human Neuroscience
|January 8, 2015
PubMed
Summary
This summary is machine-generated.

The brain exhibits distinct network organizations at different timescales. Very low frequency (VLF) brain activity supports information segregation, while low frequency (LF) activity facilitates integration, revealing timescale-dependent functional organization.

Keywords:
communityfrequency-dependencyfunctional connectivityintegrationnetwork analysisresting-state fMRIrich-club connectivitysegregation

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Area of Science:

  • Neuroscience
  • Network Science
  • Functional Magnetic Resonance Imaging (fMRI)

Background:

  • The brain's functional connectivity network (FCN) exhibits community structures and hubs, balancing information segregation and integration.
  • Previous studies estimated FCN using spontaneous fluctuations in fMRI signals within the 0.01-0.10 Hz range.

Purpose of the Study:

  • To investigate frequency-specific network topologies within the 0.01-0.10 Hz range.
  • To determine how different frequency bands contribute to information segregation and integration in the brain.

Main Methods:

  • Analyzed the coherence spectrum across 87 brain regions.
  • Compared graph theoretical indices for two distinct frequency bands: very low frequency (VLF, 0.01-0.03 Hz) and low frequency (LF, 0.07-0.09 Hz).
  • Identified hub locations within each frequency band.

Main Results:

  • The VLF band (0.01-0.03 Hz) showed a higher capacity for information segregation compared to the LF band (0.07-0.09 Hz).
  • VLF band hubs were predominantly in anterior cingulate cortices.
  • LF band hubs were located in posterior cingulate cortices and the thalamus.

Conclusions:

  • Distinct network topologies, characterized by frequency-specific contributions to segregation and integration, exist within the low-frequency range.
  • The brain possesses intrinsically timescale-dependent functional organizations, with different frequency bands supporting different network properties.
  • These findings highlight the importance of considering frequency-specific dynamics in understanding brain network organization.