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Related Experiment Video

Updated: May 15, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Hierarchical structural mapping for globally optimized estimation of functional networks.

Alex D Leow1, Liang Zhan, Donatello Arienzo

  • 1Department of Psychiatry, University of Illinois, Chicago, IL, USA. alexfeuillet@gmail.com

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|January 5, 2013
PubMed
Summary

This study introduces functional by structural hierarchical (FSH) mapping to link brain activity and structure. Body dysmorphic disorder patients showed under-utilization of visual system connections, offering insights into their brain function.

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Functional Mapping with Simultaneous MEG and EEG
06:04

Functional Mapping with Simultaneous MEG and EEG

Published on: June 14, 2010

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Last Updated: May 15, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Functional Mapping with Simultaneous MEG and EEG
06:04

Functional Mapping with Simultaneous MEG and EEG

Published on: June 14, 2010

Area of Science:

  • Neuroimaging
  • Computational Neuroscience
  • Psychiatry

Background:

  • Functional magnetic resonance imaging (fMRI) measures brain activity, while diffusion tensor imaging (DTI) tractography maps structural brain connections.
  • Integrating functional and structural brain data is crucial for understanding neural pathways and disorders.
  • Body dysmorphic disorder (BDD) is associated with altered brain activity, but the underlying structural connectivity differences remain unclear.

Purpose of the Study:

  • To develop and validate a novel framework, functional by structural hierarchical (FSH) mapping, for integrating fMRI and DTI data.
  • To investigate group differences in structural connection utilization between individuals with BDD and healthy controls during a visual task.
  • To elucidate the neural underpinnings of BDD by examining brain connectivity patterns.

Main Methods:

  • Developed the FSH mapping framework to model regional fMRI activation origins using DTI-derived "N-step reachable structural maps".
  • Employed simulated annealing to create a utilization matrix, quantifying the predictive value of specific structural connections for fMRI signals.
  • Applied the FSH mapping framework to fMRI data from BDD subjects and healthy controls performing a visual task, with statistical inference via permutation testing.

Main Results:

  • BDD subjects demonstrated significant under-utilization of specific local connections within the visual system compared to controls.
  • The FSH mapping framework successfully predicted fMRI signals based on structural connectivity patterns.
  • Permutation testing revealed statistically significant group differences in the utilization of visual network connections.

Conclusions:

  • FSH mapping provides a powerful method for linking brain structure and function, offering new insights into neurological and psychiatric conditions.
  • Under-utilization of local visual connections in BDD may explain aberrant visual processing and contribute to the disorder's pathophysiology.
  • This framework has the potential to advance our understanding of brain connectivity in various neuropsychiatric disorders.