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Related Experiment Video

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BOLD cofluctuation 'events' are predicted from static functional connectivity.

Zach Ladwig1, Benjamin A Seitzman2, Ally Dworetsky3

  • 1Interdepartmental Neuroscience Program, Northwestern University.

Neuroimage
|July 16, 2022
PubMed
Summary
This summary is machine-generated.

Brain activity "events" in functional Magnetic Resonance Imaging (fMRI) are not unique drivers of brain network information. Instead, these high cofluctuation periods likely arise from a single, static, but noisy, functional connectivity structure.

Keywords:
CofluctuationsEventsNetworksRSFCResting-state fMRISimulations

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Area of Science:

  • Neuroimaging
  • Cognitive Neuroscience
  • Network Science

Background:

  • Recent functional Magnetic Resonance Imaging (fMRI) studies identified specific time points, termed "events," characterized by high regional cofluctuation.
  • These events were proposed to contain substantial large-scale brain network information, suggesting they are discrete signals driving functional connectivity (FC).

Purpose of the Study:

  • To investigate the relationship between cofluctuation and brain network structure.
  • To determine if the observed network information in fMRI events is unique or attributable to sampling variability from a static signal.

Main Methods:

  • Analysis of both real and simulated functional Magnetic Resonance Imaging (fMRI) data.
  • Examination of the relationship between regional cofluctuation and large-scale brain network structure.
  • Simulations to test the hypothesis that sampling variability on a static FC signal can explain observed patterns.

Main Results:

  • The study found a gradual relationship between network structure and cofluctuation, indicating events are not discrete; approximately 50% of samples exhibit strong network structure.
  • Simulations demonstrated that this relationship can be accurately predicted by sampling variability from a static functional connectivity (FC) structure.
  • Randomly selected time points, due to their temporal spacing, captured network structure comparably to identified "events."

Conclusions:

  • The findings challenge the notion that fMRI "events" are unique, temporally sparse drivers of brain network structure.
  • A more parsimonious explanation is that "events" represent periods of particularly strong representation of an underlying static, albeit noisy, functional connectivity structure.