Format

Send to

Choose Destination
Neuroimage. 2017 Mar 1;148:305-317. doi: 10.1016/j.neuroimage.2017.01.003. Epub 2017 Jan 11.

Optimal trajectories of brain state transitions.

Author information

1
Applied Mathematics and Computational Science, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA.
2
Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA.
3
Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA.
4
Department of Psychological and Brain Sciences, University of California, Santa Barbara, CA 93106, USA.
5
Department of Psychological and Brain Sciences, University of California, Santa Barbara, CA 93106, USA; Neurology Associates of Santa Barbara, Santa Barbara, CA 93105, USA.
6
Department of Mechanical Engineering, University of California, Riverside, CA 92521, USA.
7
Department of Bioengineering, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Electrical & Systems Engineering, University of Pennsylvania, Philadelphia, PA 19104, USA. Electronic address: dsb@seas.upenn.com.

Abstract

The complexity of neural dynamics stems in part from the complexity of the underlying anatomy. Yet how white matter structure constrains how the brain transitions from one cognitive state to another remains unknown. Here we address this question by drawing on recent advances in network control theory to model the underlying mechanisms of brain state transitions as elicited by the collective control of region sets. We find that previously identified attention and executive control systems are poised to affect a broad array of state transitions that cannot easily be classified by traditional engineering-based notions of control. This theoretical versatility comes with a vulnerability to injury. In patients with mild traumatic brain injury, we observe a loss of specificity in putative control processes, suggesting greater susceptibility to neurophysiological noise. These results offer fundamental insights into the mechanisms driving brain state transitions in healthy cognition and their alteration following injury.

KEYWORDS:

Cognitive control; Control theory; Diffusion imaging; Network neuroscience; Traumatic brain injury

PMID:
28088484
PMCID:
PMC5489344
DOI:
10.1016/j.neuroimage.2017.01.003
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Elsevier Science Icon for PubMed Central
Loading ...
Support Center