Resting Network Plasticity Following Brain Injury

PLOS ONE, Dec 2009

The purpose of this study was to examine neural network properties at separate time-points during recovery from traumatic brain injury (TBI) using graph theory. Whole-brain analyses of the topological properties of the fMRI signal were conducted in 6 participants at 3 months and 6 months following severe TBI. Results revealed alterations of network properties including a change in the degree distribution, reduced overall strength in connectivity, and increased “small-worldness” from 3 months to 6 months post injury. The findings here indicate that, during recovery from injury, the strength but not the number of network connections diminishes, so that over the course of recovery, the network begins to approximate what is observed in healthy adults. These are the first data examining functional connectivity in a disrupted neural system during recovery.

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Resting Network Plasticity Following Brain Injury

Citation: Nakamura T, Hillary FG, Biswal BB ( Resting Network Plasticity Following Brain Injury Toru Nakamura 0 Frank G. Hillary 0 Bharat B. Biswal 0 Olaf Sporns, Indiana University, United States of America 0 1 Department of Radiology, University of Medicine and Dentistry of New Jersey - New Jersey Medical School , Newark , New Jersey, United States of America, 2 Department of Psychology, Penn State University , University Park, Pennsylvania , United States of America The purpose of this study was to examine neural network properties at separate time-points during recovery from traumatic brain injury (TBI) using graph theory. Whole-brain analyses of the topological properties of the fMRI signal were conducted in 6 participants at 3 months and 6 months following severe TBI. Results revealed alterations of network properties including a change in the degree distribution, reduced overall strength in connectivity, and increased ''small-worldness'' from 3 months to 6 months post injury. The findings here indicate that, during recovery from injury, the strength but not the number of network connections diminishes, so that over the course of recovery, the network begins to approximate what is observed in healthy adults. These are the first data examining functional connectivity in a disrupted neural system during recovery. - Funding: The current work is supported by US National Institutes of Health grant 5R01NS049176 to B.B. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. Advancing the understanding of traumatic brain injury via functional imaging Traumatic brain injury (TBI) is a debilitating neurological disorder defined as an injury from an external source resulting in a period of altered consciousness and deficits in physical, cognitive, and/or psychosocial functioning. While examination of behavioral deficits associated with head trauma has a very long history, spanning over 60 years, only recently have the consequences of TBI received attention via functional imaging methods. Activation studies using functional MRI and positron emission tomography have been used to examine TBI-related deficits in episodic memory [1,2], working memory [37], and executive control [8]. While the results of these studies have generated working hypotheses regarding how plasticity is expressed in disrupted neural systems, discrete regions of interest and localized activation results have not been interpreted in the context of an integrated neural network. There has been recent emphasis in studies using BOLD fMRI to approximate brain activity, to incorporate baseline or resting measurements of the BOLD signal. Systematic examination of baseline BOLD signal was first introduced by examining motor cortex [9] and has recently received significant attention resulting in demonstration of a discrete system of networks that are non-task or default mode [10,11]. Emanating from these early findings has been a wellspring of studies examining resting brain states in the context of cognitive, sensory, and motor functioning. Most recently, these methods have been applied in cross-sectional work examining resting BOLD states in the clinical neurosciences. Resting state fMRI has thus provided unique information about the behavior of voxels (or networks) in the absence of direct stimulation. What has not been examined in this relatively new literature is if resting states are plastic, and, in particular, if they are changing after neural disruption. The current study aims to document change in resting neural networks during recovery from brain injury by examining macro-level functional connectivity in the BOLD fMRI signal via graph theory (described below). To date, there has been no work using serial MRI to examine changes in neural connectivity during recovery from neurological insult and such methods may provide additional insight into how neural plasticity is expressed in the injured brain. Such analyses may offer insight into how networks adapt to neurological disruption. For example, it remains unclear if the neural recruitment observed almost universally in cross-sectional activation studies of working memory deficit is due to formal brain reorganization or is indicative of neural inefficiency during periods of cognitive challenge [12,13]. What appears to be a critical element in making this determination is the nature of this neural recruitment over time and if the number of neural connections is altered during recovery. Activation studies in clinical samples can be methodologically challenging [1417] and one potential method for examining how plasticity is expressed in the injured brain during recovery is to first document how resting networks are altered. Thus, it is an important aim to determine if, during recovery, networks become more elaborate, including the creat (...truncated)


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Toru Nakamura, Frank G. Hillary, Bharat B. Biswal. Resting Network Plasticity Following Brain Injury, PLOS ONE, 2009, Volume 4, Issue 12, DOI: 10.1371/journal.pone.0008220