Disruptions of network connectivity predict impairment in multiple behavioral domains after stroke
Edited by Danielle S. Bassett, University of Pennsylvania, Philadelphia, PA, and accepted by Editorial Board Member Michael S. Gazzaniga May 31, 2016 (received for review October 29, 2015)
Significance
Since the early days of neuroscience, the relative merit of structural vs. functional network accounts in explaining neurological deficits has been intensely debated. Using a large stroke cohort and a machine-learning approach, we show that visual memory and verbal memory deficits are better predicted by functional connectivity than by lesion location, and visual and motor deficits are better predicted by lesion location than functional connectivity. In addition, we show that disruption to a subset of cortical areas predicts general cognitive deficit (spanning multiple behavior domains). These results shed light on the complementary value of structural vs. functional accounts of stroke, and provide a physiological mechanism for general multidomain deficits seen after stroke.
Abstract
Deficits following stroke are classically attributed to focal damage, but recent evidence suggests a key role of distributed brain network disruption. We measured resting functional connectivity (FC), lesion topography, and behavior in multiple domains (attention, visual memory, verbal memory, language, motor, and visual) in a cohort of 132 stroke patients, and used machine-learning models to predict neurological impairment in individual subjects. We found that visual memory and verbal memory were better predicted by FC, whereas visual and motor impairments were better predicted by lesion topography. Attention and language deficits were well predicted by both. Next, we identified a general pattern of physiological network dysfunction consisting of decrease of interhemispheric integration and intrahemispheric segregation, which strongly related to behavioral impairment in multiple domains. Network-specific patterns of dysfunction predicted specific behavioral deficits, and loss of interhemispheric communication across a set of regions was associated with impairment across multiple behavioral domains. These results link key organizational features of brain networks to brain–behavior relationships in stroke.
Data Availability
Data deposition: Neuroimaging and neuropsychological data are publicly available at https://cnda.wustl.edu/app/template/Login.vm. Matlab scripts were written to perform all analyses described. Scripts used for the main analyses (Figs. 1–3 and 6) can be found at www.nil.wustl.edu/labs/corbetta/resources/.
Acknowledgments
We thank Nico Dosenbach and Brad Schlaggar for assistance with visualization software; Carl Hacker, Timothy Laumann, and Evan Gordon for data processing assistance; and Alexandre Carter for conceptual development. This study was supported by National Institute of Child Health and Human Development Health Award 5R01HD061117 (to M.C.), National Institute of Neurologic Disorders and Stroke (P30 NS048056 to A.Z.S.), National Institute of Health Medical Scientist Training Award 5T32GM007200-39 and American Heart Association Predoctoral Fellowship Award 14PRE19610010 (to J.S.S.).
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Data Availability
Data deposition: Neuroimaging and neuropsychological data are publicly available at https://cnda.wustl.edu/app/template/Login.vm. Matlab scripts were written to perform all analyses described. Scripts used for the main analyses (Figs. 1–3 and 6) can be found at www.nil.wustl.edu/labs/corbetta/resources/.
Submission history
Published online: July 11, 2016
Published in issue: July 26, 2016
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Acknowledgments
We thank Nico Dosenbach and Brad Schlaggar for assistance with visualization software; Carl Hacker, Timothy Laumann, and Evan Gordon for data processing assistance; and Alexandre Carter for conceptual development. This study was supported by National Institute of Child Health and Human Development Health Award 5R01HD061117 (to M.C.), National Institute of Neurologic Disorders and Stroke (P30 NS048056 to A.Z.S.), National Institute of Health Medical Scientist Training Award 5T32GM007200-39 and American Heart Association Predoctoral Fellowship Award 14PRE19610010 (to J.S.S.).
Notes
This article is a PNAS Direct Submission. D.S.B. is a guest editor invited by the Editorial Board.
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The authors declare no conflict of interest.
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