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Human Connectomics across the Life Span.

Xi-Nian Zuo¹, Ye He², Richard F Betzel³

¹CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China; Magnetic Resonance Imaging Research Center, Institute of Psychology, Beijing, China; Lifespan Connectomics and Behavior Team, Institute of Psychology, Beijing, China; Key Laboratory for Brain and Education Sciences, Guangxi Teachers Education University, Nanning, Guangxi, China; Center for Longevity Research, Guangxi Teachers Education University, Nanning, Guangxi, China.

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|November 21, 2016

Summary

This summary is machine-generated.

Life-span connectomics reveals how brain organization shifts from anatomical to topological. This review proposes a framework for modeling these dynamic changes throughout human development and aging.

Keywords:

brain network connectomics data sharing generative model life-span development normative trajectory

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Area of Science:

Neuroscience
Network Science
Developmental Neuroscience

Background:

Connectomics integrates network science to study neurocognitive development and decline across the human lifespan.
Previous studies often analyzed life stages independently, limiting integrated models of brain dynamics.
A comprehensive understanding of life-span brain organization requires integrated approaches.

Purpose of the Study:

To review empirical findings in life-span connectomics.
To propose a computational framework for modeling the human connectome across the lifespan.
To highlight the shift in brain organization from anatomical to topological throughout life.

Main Methods:

Survey of empirical findings in life-span connectomics research.
Development of a generative computational framework for connectome modeling.
Analysis of the transition in brain organization across developmental and aging stages.

Main Results:

The human connectome organization gradually shifts from 'anatomically driven' to 'topological' across the lifespan.
Initial findings support a dynamic model of brain organization over time.
Recent advances offer integrative perspectives on brain plasticity.

Conclusions:

An integrated, systems-level perspective is crucial for understanding human brain plasticity.
The proposed framework facilitates computational modeling of life-span connectome changes.
Addressing challenges in life-span connectomics is essential for future research.