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Measuring and Manipulating Functionally Specific Neural Pathways in the Human Motor System with Transcranial Magnetic Stimulation

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Published on: February 23, 2020

Quantifying person-level brain network functioning to facilitate clinical translation.

T M Ball¹, A N Goldstein-Piekarski¹, J M Gatt^2,3

¹Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA.

Translational Psychiatry

|October 18, 2017

Summary

This summary is machine-generated.

Researchers identified average connectivity as a reliable metric for default mode network (DMN) function. This neuroimaging metric shows promise for clinical translation in diagnosing brain disorders.

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Area of Science:

Neuroimaging
Network Neuroscience
Clinical Neuroscience

Background:

Neuroimaging advances offer insights into brain networks and disorders but lack clinical translation.
Clinical translation requires reproducible, reliable summary metrics with normative data, similar to neuropsychological tests.

Purpose of the Study:

Establish proof of principle for a summary metric of default mode network (DMN) function.
Identify a reproducible and reliable DMN metric for potential clinical use.

Main Methods:

Compared three candidate summary metrics (global clustering coefficient, characteristic path length, average connectivity) for the DMN.
Evaluated metrics across three independent samples totaling 322 healthy adults.
Assessed internal consistency and eight-week test-retest reliability.

Main Results:

Average connectivity demonstrated the best performance among the candidate metrics.
Achieved good internal consistency (Cronbach's α=0.69-0.70).
Showed adequate eight-week test-retest reliability (intra-class coefficient=0.62).

Conclusions:

Average connectivity is a promising summary metric for DMN function.
Normative data for DMN average connectivity are presented.
This work represents a crucial step toward translating neuroimaging findings into clinical practice for quantifying DMN function.