https://jneuroengrehab.biomedcentral.com/articles/10.1186/s12984-017-0277-3
- Gavin R. PhilipsEmail authorView ORCID ID profile,
- Janis J. Daly and
- José C. Príncipe
Journal of NeuroEngineering and Rehabilitation201714:67
DOI: 10.1186/s12984-017-0277-3
© The Author(s) 2017
Received: 24 February 2017
Accepted: 20 June 2017
Published: 6 July 2017
Abstract
Background
Biomarkers derived from neural activity
of the brain present a vital tool for the prediction and evaluation of
post-stroke motor recovery, as well as for real-time biofeedback
opportunities.
Methods
In order to encapsulate recovery-related
reorganization of brain networks into such biomarkers, we have utilized
the generalized measure of association (GMA) and graph analyses, which
include global and local efficiency, as well as hemispheric interdensity
and intradensity. These methods were applied to electroencephalogram
(EEG) data recorded during a study of 30 stroke survivors (21 male, mean
age 57.9 years, mean stroke duration 22.4 months) undergoing 12 weeks
of intensive therapeutic intervention.
Results
We observed that decreases of the intradensity of the unaffected hemisphere are correlated (r
s
=−0.46;p<0.05)
with functional recovery, as measured by the upper-extremity portion of
the Fugl-Meyer Assessment (FMUE). In addition, high initial values of
local efficiency predict greater improvement in FMUE (R
2=0.16;p<0.05).
In a subset of 17 subjects possessing lesions of the cerebral cortex,
reductions of global and local efficiency, as well as the intradensity
of the unaffected hemisphere are found to be associated with functional
improvement (r
s
=−0.60,−0.66,−0.75;p<0.05). Within the same subgroup, high initial values of global and local efficiency, are predictive of improved recovery (R
2=0.24,0.25;p<0.05). All significant findings were specific to the 12.5–25 Hz band.
Conclusions
These topological measures show promise
for prognosis and evaluation of therapeutic outcomes, as well as
potential application to BCI-enabled biofeedback.
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