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.
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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)