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Brain Mapping Using a Graphene Electrode Array

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Brainprints: Computer-Generated Two-Dimensional Maps of the Human Cerebral Cortex in vivo.

M L Jouandet¹, M J Tramo, D M Herron

¹Program in Cognitive Neuroscience, Dartmouth Medical School.

Journal of Cognitive Neuroscience

|August 24, 2013

Summary

This study introduces a new in vivo method for quantitatively measuring human brain anatomy. This technique enables detailed analysis of brain structure and function, with applications in understanding cognitive and neurological performance.

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Published on: May 12, 2019

Area of Science:

Neuroscience
Anatomical Imaging
Quantitative Biology

Background:

Accurate quantitative analysis of human brain anatomy is crucial for understanding neurological disorders.
Existing methods may lack the precision or in vivo capabilities for detailed morphological and functional assessments.

Purpose of the Study:

To present a novel in vivo method for the quantitative analysis of human brain anatomy.
To demonstrate the technique's utility in measuring cortical regions and surface areas.
To explore potential applications in cognitive and neurological research.

Main Methods:

Development of an in vivo quantitative analysis technique for human brain anatomy.
Planimetric measurement of unfolded brain regions of interest.
Generation of 2D cortical maps and surface area calculations using magnetic resonance imaging (MRI).
Reconstruction and measurement of published post-mortem hemisphere data.

Main Results:

Successful application of the in vivo method for quantitative anatomical analysis.
Presentation of 2D cortical maps and surface area data from monozygotic twins.
Validation of the technique through measurements of published human and rhesus monkey brain data.

Conclusions:

The described in vivo method offers a powerful tool for quantitative analysis of human brain anatomy.
This technique has significant potential for studying brain organization in relation to performance in both healthy and neurologically impaired individuals.
Further research can leverage this method to advance our understanding of brain-behavior relationships.