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Related Experiment Video

Updated: Feb 25, 2026

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping
13:12

Translational Brain Mapping at the University of Rochester Medical Center: Preserving the Mind Through Personalized Brain Mapping

Published on: August 12, 2019

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Precision Functional Mapping of Individual Human Brains.

Evan M Gordon1, Timothy O Laumann2, Adrian W Gilmore3

  • 1VISN 17 Center of Excellence for Research on Returning War Veterans, Waco, TX, 76711, USA; Center for Vital Longevity, School of Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, 75235, USA.

Neuron
|August 1, 2017
PubMed

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Summary

This study introduces precision individual connectomics, creating detailed brain maps for ten adults. This approach reveals unique brain network variations specific to each person, advancing our understanding of individual brain organization.

Area of Science:

  • Neuroscience
  • Neuroimaging
  • Human Brain Imaging

Background:

  • Current human functional MRI (fMRI) research relies on group-averaged data, limiting individual specificity and clinical applications.
  • Resting-state functional connectivity (RSFC) and task-activation maps lack detailed individual insights.

Purpose of the Study:

  • To develop high-fidelity, individual-specific functional connectomes for ten adults.
  • To explore spatial and organizational variability in individual brain networks.
  • To propose precision individual connectomics as a future research model.

Main Methods:

  • Assembled a novel MRI dataset with extensive RSFC (5 hr), task fMRI (6 hr), structural MRIs, and neuropsychological tests from ten adults.
  • Generated ten high-fidelity, individual-specific functional connectomes.
Keywords:
brain networksfMRIfunctional connectivityindividual variabilitymyelin mapping

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Last Updated: Feb 25, 2026

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Published on: August 12, 2019

46.6K
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  • Analyzed network features, topologies, and their correspondence with structural and task data.

    • Main Results:

    • Revealed novel types of spatial and organizational variability in individual brain networks.
    • Identified unique network features and topologies specific to each individual.
    • Demonstrated correspondence between individual connectome features and structural/task-derived brain characteristics.

    Conclusions:

    • The individual-connectome approach offers a more detailed and specific understanding of functional brain organization.
    • Precision individual connectomics provides a valuable model for studying healthy and diseased individual brains.
    • The released dataset serves as a resource for advancing neuroscientific research on individual brain variability.