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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 24, 2025

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Published on: September 25, 2019

Functional anomaly mapping reveals local and distant dysfunction caused by brain lesions.

Andrew T DeMarco¹, Peter E Turkeltaub²

¹Department of Neurology, Georgetown University, Washington, DC, 20057, United States.

|April 13, 2020

Summary

This study introduces functional anomaly maps derived from resting-state fMRI to precisely measure brain lesions and their effects. This new method accurately maps both direct and distant brain dysfunction, improving our understanding of brain-behavior relationships.

Keywords:

Aphasia Functional anomaly mapping Lesion Lesion-behavior mapping Machine learning Stroke Support vector machine

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Last Updated: Dec 24, 2025

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Area of Science:

Neuroscience
Cognitive Science
Medical Imaging

Background:

Traditional lesion mapping relies on structural damage, potentially misidentifying functional tissue as abnormal and ignoring remote effects.
Understanding brain-behavior relationships requires methods that capture functional integrity beyond structural damage.

Purpose of the Study:

To develop and validate a novel method for mapping functional integrity of brain tissue to improve lesion measurement.
To investigate the remote functional effects of focal brain lesions using advanced machine learning techniques.

Main Methods:

Utilized machine learning on 4D resting-state fMRI data from stroke survivors and control subjects.
Generated graded functional anomaly maps to identify both structural lesions and functionally impaired, yet structurally intact, brain regions.
Employed multivariate lesion-behavior mapping using these functional anomaly maps.

Main Results:

Functional anomaly maps accurately identified structural lesions and were stable over time.
The maps revealed functionally anomalous regions in structurally intact tissue, indicating remote effects of lesions.
Lesion-behavior mapping replicated known functional localizations and identified novel distant relationships between tissue function and behavior.

Conclusions:

Functional anomaly maps offer a valuable new approach to lesion measurement, capturing both direct and remote functional deficits.
This method enhances the study of brain-behavior associations and recovery after brain injury.
Brain-wide functional mapping of focal lesions has broad implications for neuroscience research.