Brenton Hordacre
Nigel C. Rogasch
Mitchell R. Goldsworthy
A commentary on
Utility of EEG measures of brain function in patients with acute stroke
Utility of EEG measures of brain function in patients with acute stroke
by Wu, J., Srinivasan, R., Quinlan, E.
B., Solodkin, A., Small, S. L., and Cramer, S. C. (2016). J.
Neurophysiol. 115, 2399–2405. doi: 10.1152/jn.00978.2015
Several imaging and neurophysiological assessments are
used to characterize both neural injury and neural function after
stroke. These measures can inform clinical practice, map longitudinal
changes, and guide therapeutic interventions. Electroencephalography
(EEG) is one technique that measures neural function and can provide
detailed assessment of spontaneous and task-related cortical oscillatory
function. Neural oscillations reflect synchronized activity of large
populations of cortical neurons which are fundamental for network
communication and information processing. Although not currently a
routine clinical assessment following stroke, EEG is a sensitive measure
of cortical function and subsequent neural changes resulting from brain
insults such as cerebral ischemia, and therefore has potential for
wider clinical use.
Recently, Wu et al. (2016)
investigated the capacity of EEG to capture behavioral impairment
shortly following stroke. Resting state EEG recordings were performed in
25 patients between 3 and 12 days post-stroke in complex acute clinical
settings. Using partial least squares (PLS) regression analysis, it was
reported that delta power from a subset of electrodes predicted 72% of
variance in acute stroke impairment measured with the National Institute
of Health Stroke Scale, while beta power predicted 73% of variance
(leave-one-out cross-validated). EEG coherence, a marker of functional
connectivity, did not predict acute stroke impairment. Further,
investigation of the PLS models revealed higher delta power in two
regions, one overlying the ipsilesional sensorimotor cortex and one over
the contralesional frontoparietal cortex, were associated with greater
impairment. Similarly, reduced beta power in two regions, one overlying
the ipsilesional primary motor cortex (M1) and the other over the
contralesional parietal cortex, correlated with greater impairment.
Wu et al. (2016)
reported several interesting findings which provide unique insight to
acute stroke neurophysiology. Here, we highlight those key findings and
discuss their significance in advancing the field. First, the finding
that abnormalities in spectral power, but not coherence, were related to
acute post-stroke impairment is an interesting observation in light of
recent findings in chronic stroke. Using a similar PLS approach, EEG
recorded in chronic stroke survivors identified that beta frequency
coherence between M1 and ipsilesional motor networks was a strong
predictor of motor impairment and recovery of function (Wu et al., 2015).
Why similar relationships were not observed in the acute post-stroke
period is not clear. It may be that acute neural damage following an
ischemic lesion causes rapid changes in synchronization of the local
neural network, affecting functional output. As the motor network
reorganizes across the sub-acute post-stroke period, different neural
populations may be recruited in order to restore function, meaning the
strength and flexibility of motor network connectivity would become an
important marker of function and capacity for further recovery (Park et al., 2011).
Nevertheless, these results suggest power is an early marker of stroke
impairment, while the importance of connectivity may increase during
sub-acute or chronic post-stroke periods.
An important application of EEG is the ability to
investigate neural oscillations in specific frequency bands. Insight
into the functional significance of different frequency oscillations may
provide an additional source of neurophysiological information. For
example, previous stroke studies suggest delta oscillations originate
from the region of the obstructed cerebral artery, reflecting reduced
regional cerebral blood flow (Finnigan et al., 2006; Finnigan and van Putten, 2013).
Furthermore, restoration of cerebral blood flow following
administration of a tissue plasminogen activator was associated with
normalization of delta power within minutes (Finnigan et al., 2006). Wu et al. (2016)
report a positive correlation between ipsilesional delta power and
infarct volume which appears to support previous findings indicating a
relationship between delta power and cerebral blood flow following
ischemic stroke. However, the relationship between beta power and
impairment may reflect the importance of beta oscillations to motor
function. Beta oscillations are associated with motor preparation and
output and have been recorded over motor network regions during movement
(Wheaton et al., 2005). Furthermore, beta coherence in sensorimotor regions recorded at rest was found to be a strong predictor of motor learning (Wu et al., 2014).
However, the relationships between abnormalities in beta power and
impairment following stroke are unclear. It may be that reduced beta
power and impairment are both driven by neuronal loss following ischemic
stroke. Investigating causal relationships between power and impairment
represents an important progression in determining the clinical utility
of EEG and may direct further interventional studies to facilitate
greater functional recovery following stroke. Transcranial alternating
current stimulation (tACS) has been shown to entrain neural oscillations
in a frequency specific manner (Zaehle et al., 2010), resulting in subsequent behavioral change (Pollok et al., 2015).
Similarly, biofeedback allows participants to control frequency
specific neural rhythms and has been used to modulate spectral power (Mulholland, 1995). Following on from the findings of Wu et al. (2016),
an important progression would be to employ these neuromodulatory
techniques to determine if changing EEG power has an effect on motor
recovery following stroke. Such studies may advance acute stroke care by
informing novel interventional approaches capable of improving
post-stroke brain function and reducing impairment. While speculative
and requiring further investigation, if abnormalities in beta power are
related to post-stroke impairment, beta frequency tACS or biofeedback
could be used as interventional techniques to normalize beta power
recorded over the ipsilesional M1 and contralesional parietal cortex.
Such interventions may assist restitution of motor function and
represent an important progression in stroke recovery.
Future studies investigating causal relationships
between EEG measures and impairment should also consider approaches to
improve the spatial specificity of scalp EEG. Volume conduction is a
significant limitation for interpreting the anatomical location of
neural oscillatory activity. Several analytical techniques can increase
the spatial specificity of oscillatory power and connectivity analyses,
such as using spatial filtering methods (e.g., Laplacian re-referencing
or source localization; Nunez et al., 1997; Schoffelen and Gross, 2009)
or measures of connectivity which are less sensitive to volume
conduction than coherence (e.g., imaginary coherence or weighted phase
lag index; Nolte et al., 2004; Vinck et al., 2011). However, the field is still advancing these methods, and thus, results need to be treated carefully.
In summary, Wu et al. (2016)
report several interesting neurophysiological observations following
acute stroke. To further advance this field of research, future studies
should investigate causal relationships between neural function and
impairment using techniques such as tACS and biofeedback. These
approaches may help decipher the clinical utility of EEG and inform
future interventional studies which may lead to improved clinical
outcomes.