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Related Concept Videos

Brain Imaging01:14

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic Stimulation (TMS).

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Related Experiment Video

Updated: May 14, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
17:06

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

Published on: November 8, 2012

Linking human brain local activity fluctuations to structural and functional network architectures.

A T Baria1, A Mansour, L Huang

  • 1Department of Physiology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.

Neuroimage
|February 12, 2013
PubMed
Summary
This summary is machine-generated.

Brain activity fluctuations share organizational rules, linking local neuronal dynamics to network architecture. Functional and structural connectivity correlate with brain-oxygenation-level-dependent signal characteristics.

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Last Updated: May 14, 2026

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Dynamic Inter-subject Functional Connectivity Reveals Moment-to-Moment Brain Network Configurations Driven by Continuous or Communication Paradigms

Published on: March 21, 2019

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Systems Neuroscience

Background:

  • Cortical local neuronal populations exhibit continuous activity fluctuations.
  • A significant portion of these neuronal fluctuations are shared across different neuronal populations.

Purpose of the Study:

  • To identify organizational rules governing the relationship between local neuronal activity fluctuations and large-scale brain network architecture.
  • To investigate how frequency characteristics of local brain activity relate to the underlying brain network structure.

Main Methods:

  • Utilized resting-state functional magnetic resonance imaging (fMRI) to measure brain-oxygenation-level-dependent (BOLD) signal fluctuations.
  • Derived a measure of fluctuation dynamics (α, spectral slope) and functional connectivity (temporal coherence) for brain regions.
  • Employed diffusion tensor imaging (DTI) for structural connectivity analysis and developed a computational model.

Main Results:

  • Found similar spatial organization between fluctuation dynamics (α) and functional connectivity maps (correlation coefficient of 0.75).
  • Demonstrated that synaptic low-pass filtering can explain the observed interrelationships.
  • Observed that the correlation between α and structural connectivity is state-dependent, being higher during rest than during task attention.

Conclusions:

  • Established global rules linking the frequency characteristics of local brain activity to the architecture of underlying brain networks.
  • Suggests that the interplay between local dynamics and network structure is fundamental to brain function.
  • Highlights the dynamic nature of brain network organization influenced by attentional states.