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Related Experiment Video

Updated: Jan 31, 2026

Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment

Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment

Published on: August 7, 2017

Comparing directed functional connectivity between groups with confirmatory subgrouping GIMME.

Teague Rhine Henry¹, Eric Feczko², Michaela Cordova³

¹Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.

|December 25, 2018

Summary

This summary is machine-generated.

Confirmatory subgrouping GIMME identifies distinct brain connectivity patterns in typically developing children and those with autism spectrum disorder or ADHD. This method reveals both shared and unique functional connections across these groups.

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Application of Granger Causality Analysis of the Directed Functional Connection in Alzheimer's Disease and Mild Cognitive Impairment

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Published on: August 7, 2017

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Whole-Brain 3D Activation and Functional Connectivity Mapping in Mice using Transcranial Functional Ultrasound Imaging

Whole-Brain 3D Activation and Functional Connectivity Mapping in Mice using Transcranial Functional Ultrasound Imaging

Published on: February 24, 2021

Area of Science:

Neuroimaging
Functional Connectivity Analysis
Computational Neuroscience

Background:

Functional neuroimaging connectivity modeling is crucial for understanding brain architecture.
Group Iterative Multiple Model Estimation (GIMME) identifies group-level and individual-level brain connectivity edges.
Existing methods allow for generalizable results and personalized connectivity maps, but capturing subgroup heterogeneity requires advancement.

Purpose of the Study:

Introduce confirmatory subgrouping GIMME, an extension of GIMME for estimating subgroup-level brain connectivity.
Enable subgroup-specific inferences and aid in interpreting connectivity map heterogeneity for predefined groups.
Demonstrate the algorithm's utility in identifying distinct functional connectivity patterns in neurodevelopmental disorders.

Main Methods:

Developed confirmatory subgrouping GIMME, an extension of the Group Iterative Multiple Model Estimation (GIMME) algorithm.
Applied the novel method to resting-state functional connectivity data from four groups of children: typically developing controls (TDC), autism spectrum disorder (ASD), and two subtypes of ADHD (Inattentive and Combined).
Described methods for examining results, focusing on identifying subgroup-level edges.

Main Results:

Identified common involvement of the left Broca's area in all clinical groups (ASD, ADHD-I, ADHD-C).
Revealed unique patterns of functional connectivity specific to each disorder.
Demonstrated similarities and differences in resting-state functional connectivity across the four pediatric groups.

Conclusions:

Confirmatory subgrouping GIMME provides a reliable tool for capturing heterogeneity in brain connectivity within complex mental health disorders.
The findings highlight the potential for subgroup-specific inferences in neuroimaging research.
This novel approach advances the understanding of functional architecture in typically developing and clinical pediatric populations.