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Brain Imaging

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...

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Related Experiment Video

Updated: Dec 9, 2025

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Published on: September 12, 2011

A Whole-Brain and Cross-Diagnostic Perspective on Functional Brain Network Dysfunction.

Marjolein Spronk¹, Brian P Keane^1,2, Takuya Ito¹

¹Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ 07102, USA.

Cerebral Cortex (New York, N.Y. : 1991)

|September 10, 2020

Summary

Mental illnesses show subtle, not large, brain network differences. These small changes in functional connectomes are informative and may guide targeted treatments for various mental disorders.

Keywords:

attention-deficit hyperactivity disorder autism spectrum disorder functional connectivity resting state schizophrenia

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Published on: October 13, 2023

Related Experiment Videos

Last Updated: Dec 9, 2025

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Published on: September 12, 2011

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

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

Published on: November 8, 2012

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Area of Science:

Neuroscience
Psychiatry
Network Science

Background:

Mental disorders are linked to altered resting-state functional networks, suggesting large-scale brain system disruptions.
Current research often isolates network differences, lacking a whole-brain perspective.

Purpose of the Study:

To investigate whole-brain functional network organization similarity across individuals with and without mental illness.
To determine if subtle network differences can predict diagnosis.

Main Methods:

Utilized a graph distance approach, specifically connectome-wide similarity.
Analyzed resting-state functional network organization.

Main Results:

Found high similarity in whole-brain resting-state functional network organization across healthy individuals and those with autism spectrum disorder, attention-deficit hyperactivity disorder, and schizophrenia.
Subtle differences in network graph distance were predictive of diagnosis.

Conclusions:

Functional connectomes exhibit high similarity between health and mental illness, challenging theories of large-scale disruption.
Subtle functional brain network alterations play a role in mental diseases and may offer targets for effective interventions.