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Neurosci Biobehav Rev. 2017 Apr;75:53-64. doi: 10.1016/j.neubiorev.2017.01.016. Epub 2017 Jan 16.

Brain and cognitive reserve: Translation via network control theory.

Author information

1
Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, United States.
2
Department of Mechanical Engineering, University of California-Riverside, Riverside, CA 92521, United States.
3
Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, United States.
4
Department of Bioengineering, University of Pennsylvania, PA 19104, United States; Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104, United States. Electronic address: dsb@seas.upenn.edu.

Abstract

Traditional approaches to understanding the brain's resilience to neuropathology have identified neurophysiological variables, often described as brain or cognitive "reserve," associated with better outcomes. However, mechanisms of function and resilience in large-scale brain networks remain poorly understood. Dynamic network theory may provide a basis for substantive advances in understanding functional resilience in the human brain. In this perspective, we describe recent theoretical approaches from network control theory as a framework for investigating network level mechanisms underlying cognitive function and the dynamics of neuroplasticity in the human brain. We describe the theoretical opportunities offered by the application of network control theory at the level of the human connectome to understand cognitive resilience and inform translational intervention.

KEYWORDS:

Control theory; Graph theory; Network science; Neurology; Neuropsychology

PMID:
28104411
PMCID:
PMC5359115
DOI:
10.1016/j.neubiorev.2017.01.016
[Indexed for MEDLINE]
Free PMC Article

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