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Annu Rev Biomed Eng. 2017 Jun 21;19:327-352. doi: 10.1146/annurev-bioeng-071516-044511. Epub 2017 Mar 27.

Emerging Frontiers of Neuroengineering: A Network Science of Brain Connectivity.

Author information

1
Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104.
2
Department of Electrical and Systems Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104.
3
UCSB Brain Imaging Center and Department of Psychological and Brain Sciences, University of California, Santa Barbara, California 93106.
4
Institute for Collaborative Biotechnologies, University of California, Santa Barbara, California 93106.

Abstract

Neuroengineering is faced with unique challenges in repairing or replacing complex neural systems that are composed of many interacting parts. These interactions form intricate patterns over large spatiotemporal scales and produce emergent behaviors that are difficult to predict from individual elements. Network science provides a particularly appropriate framework in which to study and intervene in such systems by treating neural elements (cells, volumes) as nodes in a graph and neural interactions (synapses, white matter tracts) as edges in that graph. Here, we review the emerging discipline of network neuroscience, which uses and develops tools from graph theory to better understand and manipulate neural systems from micro- to macroscales. We present examples of how human brain imaging data are being modeled with network analysis and underscore potential pitfalls. We then highlight current computational and theoretical frontiers and emphasize their utility in informing diagnosis and monitoring, brain-machine interfaces, and brain stimulation. A flexible and rapidly evolving enterprise, network neuroscience provides a set of powerful approaches and fundamental insights that are critical for the neuroengineer's tool kit.

KEYWORDS:

control theory; graph theory; network neuroscience; neuroengineering; neuroimaging

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