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Traumatic Brain Injury l: Introduction

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Biomarkers in an Animal Model for Revealing Neural, Hematologic, and Behavioral Correlates of PTSD

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Published on: October 10, 2012

Data-Driven Approach to Dynamic Resting State Functional Connectivity in Post-Traumatic Stress Disorder: An

Carissa W Tomas^1,2, Jacklynn M Fitzgerald³, C Lexi Baird^4,5

¹Division of Epidemiology and Social Sciences, Institute of Health and Equity, Medical College of Wisconsin, Milwaukee, Wisconsin, USA.

Human Brain Mapping

|July 30, 2025

Summary

This summary is machine-generated.

This study found no significant differences in brain network connectivity between individuals with and without posttraumatic stress disorder (PTSD). Advanced dynamic functional connectivity analysis did not reveal group-specific network disruptions in this large trauma-exposed cohort.

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

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:

Neuroimaging
Psychiatry
Computational Neuroscience

Background:

Posttraumatic stress disorder (PTSD) symptoms are linked to altered resting-state brain networks.
Previous research often used static functional connectivity (FC) and hypothesis-driven approaches.
Dynamic FC and data-driven methods may offer more sensitive insights into PTSD-related network dysfunction.

Purpose of the Study:

To compare brain network dynamics and connectivity states in individuals with and without PTSD using a large, multi-cohort sample.
To investigate differences in both static and dynamic functional connectivity.
To explore recurrent connectivity states and their temporal characteristics.

Main Methods:

Utilized functional magnetic resonance imaging (fMRI) data from 1035 trauma-exposed individuals.
Employed group independent component analysis (ICA) for a data-driven network analysis.
Applied graph theory principles to characterize network dynamics and connectivity states.

Main Results:

No robust differences were observed in static FC between PTSD and control groups.
Dynamic FC analysis also revealed no significant group differences.
No significant differences were found in the dwell time or number of transitions between connectivity states.

Conclusions:

Large-scale analysis using advanced methods did not identify distinct brain network differences between PTSD and control groups.
The heterogeneity of PTSD symptoms and trauma types may obscure group-level network findings.
Future research should explore brain network dynamics in relation to specific symptom profiles and trauma characteristics.