NHMRC Early Career Research Fellow, The University of South Australia
Characteristics of the brain can help tailor therapies in stroke
Stroke is a global leading cause of disability requiring extensive and lengthy periods of rehabilitation aimed at restoring function. Therapies which help people recovery following stroke utilise the brains unique ability to learn and change - known as neuroplasticity. Function of the damaged brain area is taken over by nearby brain regions and can help compensate for the injury. However, despite this intriguing ability of the brain, recovery following stroke is often incomplete, with survivors forced to life with lifelong impairments such as arm or leg weakness, difficulty with speech or cognitive issues. Treatments which improve the level of recovery by enhancing the neuroplasticity process would be highly valued by patients, family members and health service providers as it may provide a more complete and efficient recovery.
One approach is to stimulate the brain tissue with an electric current. Several studies have shown that brain stimulation is able to increase brain activity and improve recovery following stroke. However, this approach does not appear to be one-size-fits-all with recent studies reporting a high level of variability in response to brain stimulation. As a result, brain stimulation does not provide a reliable and consistent response across all stroke survivors and this has limited any possibility of this treatment being used clinically. It is perhaps unreasonable to assume that one therapy approach could be used as a ‘magic bullet’ and be suitable for every individual since each brain is unique as a result of different life experiences, genetics or characteristics of the injury.
My research investigates neural characteristics following stroke that predict response to brain stimulation therapy. A series of studies will be presented at the World Congress for Neurorehabilitation which will show that brain connectivity following stroke can predict, with a high level of accuracy, who will respond to brain stimulation and who won’t. The significance of this work lies in the opportunity to harness the full potential of brain stimulation by specifically targeting the patients who will benefit most from this therapy. The ability to do so could assist clinical uptake of brain stimulation as a treatment and assist those patients who are desperate for a greater level of recovery. This body of work is an exciting and novel advance in brain stimulation therapy for stroke and has potential to accelerate clinical translation of this treatment.
Abstract: Introduction: Transcranial alternating current stimulation (tACS) is emerging as an interventional tool to modulate different functions of the brain, potentially by interacting with intrinsic ongoing neuronal oscillations. Functionally different intrinsic alpha oscillations are found throughout the cortex. Yet it remains unclear whether tACS is capable of specifically modulating the somatosensory mu-rhythm in amplitude. Objectives: We used tACS to modulate mu-alpha oscillations in amplitude. When compared to sham stimulation we expected a modulation of mu-alpha oscillations but not visual alpha oscillations by tACS. Methods: Individual mu-alpha frequencies were determined in 25 participants. Subsequently, blocks of tACS with individual mu-alpha frequency and sham stimulation were applied over primary somatosensory cortex (SI). Electroencephalogram (EEG) was recorded before and after either stimulation or sham. Modulations of mu-alpha and, for control, visual alpha amplitudes were then compared between tACS and sham. Results: Somatosensory mu-alpha oscillations decreased in amplitude after tACS was applied at participants' individual mu-alpha frequency. No changes in amplitude were observed for sham stimulation. Furthermore, visual alpha oscillations were not affected by tACS or sham, respectively. Conclusion: Our results demonstrate the capability of tACS to specifically modulate the targeted somatosensory mu-rhythm when the tACS frequency is tuned to the individual endogenous rhythm and applied over somatosensory areas. Our results are in contrast to previously reported amplitude increases of visual alpha oscillations induced by tACS applied over visual cortex. Our results may point to a specific interaction between our stimulation protocol and the functional architecture of the somatosensory system.
Pub.: 12 Sep '17, Pinned: 27 Sep '17
Abstract: We recently reported that spatial and nonspatial attention deficits in stroke patients with hemispatial neglect are correlated at 2 weeks postonset with widespread alterations of interhemispheric and intrahemispheric functional connectivity (FC) measured with resting-state functional magnetic resonance imaging across multiple brain networks. The mechanisms underlying neglect recovery are largely unknown. In this study, we test the hypothesis that recovery of hemispatial neglect correlates with a return of network connectivity toward a normal pattern, herein defined as "network normalization."We measured attention deficits with a neuropsychological battery and FC in a large cohort of stroke patients at, on average, 2 weeks (n = 99), 3 months (n = 77), and 12 months (n = 64) postonset. The relationship between behavioral improvement and changes in FC was analyzed both in terms of a priori regions and networks known to be abnormal subacutely and in a data-driven manner.Attention deficit recovery was mostly complete by 3 months and was significantly correlated with a normalization of abnormal FC across many networks. Improvement of attention deficits, independent of initial severity, was correlated with improvements of previously depressed interhemispheric FC across attention, sensory, and motor networks, and a restoration of the normal anticorrelation between dorsal attention/motor regions and default-mode/frontoparietal regions, particularly in the damaged hemisphere.These results demonstrate that abnormal network connectivity in hemispatial neglect is behaviorally relevant. A return toward normal network interactions, and presumably optimal information processing, is therefore a systems-level mechanism that is associated with improvements of attention over time after focal injury. Ann Neurol 2016.
Pub.: 10 Jun '16, Pinned: 27 Sep '17
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.
Pub.: 13 Jul '16, Pinned: 27 Sep '17
Abstract: Background After cerebral ischemia, disruption and subsequent reorganization of functional connections occur both locally and remote to the lesion. Recently, complexity of brain connectivity has been described using graph theory, a mathematical approach that depicts important properties of complex systems by quantifying topologies of network representations. Functional and dynamic changes of brain connectivity can be reliably analyzed via electroencephalography (EEG) recordings even when they are not yet reflected in structural changes of connections. Objective We tested whether and how ischemic stroke in the acute stage may determine changes in small-worldness of cortical networks as measured by cortical sources of EEG. Methods Graph characteristics of EEG of 30 consecutive stroke patients in acute stage (no more than 5 days after the event) were examined. Connectivity analysis was performed using eLORETA in both hemispheres. Results Network rearrangements were mainly detected in delta, theta, and alpha bands when patients were compared with healthy subjects. In delta and alpha bands similar findings were observed in both hemispheres regardless of the side of ischemic lesion: bilaterally decreased small-worldness in the delta band and bilaterally increased small-worldness in the alpha2 band. In the theta band, bilaterally decreased small-worldness was observed only in patients with stroke in the left hemisphere. Conclusions After an acute stroke, brain cortex rearranges its network connections diffusely, in a frequency-dependent modality probably in order to face the new anatomical and functional frame.
Pub.: 12 Aug '16, Pinned: 27 Sep '17
Abstract: Li Wang, Jingna Zhang, Ye Zhang, Linqiong Sang, Rubing Yan, Chen Liu, Mingguo Qiu Digital Medicine 2016 2(2):72-79 Objective: The objective of this study was to analyze the functional brain activation in acute stroke patients during motor execution (ME) and motor imagery (MI) and to discuss the association between damaged brain structure and impaired brain function in stroke patients. Methods: The functional magnetic resonance imaging technique was used to observe activation of the brain during ME/MI of the upper limbs in 12 acute stroke patients (with the left brain damage) and 12 healthy controls. Results: During ME, the stroke patients appeared to be activated more strongly than the healthy controls in the ipsilateral primary motor areas. The MI of the affected hand in the stroke patients was not significantly different from that of the healthy hand. The nonmotor areas, the angular gyrus, and the fusiform gyrus were also activated during ME/MI. Conclusion: Structural damage in the brain is associated with the activation of brain function in acute stroke patients. Ipsilateral inhibition is reduced in stroke patients during ME and the damaged brain needs to recruit more brain areas to complete the desired action due to motion difficulties resulting from brain damage. The participation of nonmotor brain areas in ME/MI indicates that cortical reorganization may contribute to the restoration of motor function following stroke. MI can be used to improve injured brain areas, helping with the rehabilitation of stroke patients.
Pub.: 30 Aug '16, Pinned: 27 Sep '17
Abstract: After stroke, the less affected upper-limb shows slight but substantial and longterm motor deficits . Kinematically, this is reflected by an increased segmentation of movements. Here, we aim to define how these changes in behavior are accompanied by changes in brain activation.Twenty-one sub-acute post-stroke patients with a first-ever unilateral ischemic stroke of the middle cerebral artery participated in this study twice: within the first 6 weeks post-stroke and after 6 weeks of rehabilitation. Participants performed a self-paced flexion/extion of the elbow with the less-affected upper-limb. Its kinematic features were analysed and related to the observed fMRI activations during task execution. Results were compared with those of 12 healthy controls with no history of neurological or orthopeadic disease.Initially, post-stroke patients showed an extended activation of the primary sensorimotor cortex, with an additional recruitment of both the middle temporal and rolandic opercularis areas. After intervention, the rolandic opercularis which is involved in movement visualization  remained activated.Movements of the less affected upper-limb were not only atypical in motor outcome, but were also abnormally controlled. This indicates a disturbance of the bihemispheric motor network that is marked by: - an overload of the non-damaged hemisphere; - the employment of alternative control strategies to ensure optimal task execution.
Pub.: 28 Sep '16, Pinned: 27 Sep '17
Abstract: Recent studies using resting-state functional magnetic resonance imaging (rs-fMRI) demonstrated that changes in functional connectivity (FC) after stroke correlate with recovery. The aim of this study was to explore whether combining motor learning to dual transcranial direct current stimulation (dual-tDCS, applied over both primary motor cortices (M1)) modulated FC in stroke patients. Twenty-two chronic hemiparetic stroke patients participated in a baseline rs-fMRI session. One week later, dual-tDCS/sham was applied during motor skill learning (intervention session); one week later, the retention session started with the acquisition of a run of rs-fMRI imaging. The intervention + retention sessions were performed once with dual-tDCS and once with sham in a randomised, cross-over, placebo-controlled, double-blind design. A whole-brain independent component analysis based ANOVA demonstrated no changes between baseline and sham sessions in the somatomotor network, whereas a FC increase was observed one week after dual-tDCS compared to baseline (qFDR < 0.05, t(63) = 4.15). A seed-based analysis confirmed specific stimulation-driven changes within a network of motor and premotor regions in both hemispheres. At baseline and one week after sham, the strongest FC was observed between the M1 and dorsal premotor cortex (PMd) of the undamaged hemisphere. In contrast, one week after dual-tDCS, the strongest FC was found between the M1 and PMd of the damaged hemisphere. Thus, a single session of dual-tDCS combined with motor skill learning increases FC in the somatomotor network of chronic stroke patients for one week.
Pub.: 09 Nov '16, Pinned: 27 Sep '17
Abstract: The primary motor cortex (M1) is often abnormally recruited in stroke patients with motor disabilities. However, little is known about the alterations in the causal connectivity of M1 following stroke. The purpose of the present study was to investigate whether the effective connectivity of the ipsilesional M1 is disturbed in stroke patients who show different outcomes in hand motor function. 23 patients with left-hemisphere subcortical stroke were selected and divided into two subgroups: partially paralyzed hands (PPH) and completely paralyzed hands (CPH). Further, 24 matched healthy controls (HCs) were recruited. A voxel-wise Granger causality analysis (GCA) on the resting-state fMRI data between the ipsilesional M1 and the whole brain was performed to explore differences between the three groups. Our results showed that the influence from the frontoparietal cortices to ipsilesional M1 was diminished in both stroke subgroups and the influence from ipsilesional M1 to the sensorimotor cortices decreased greater in the CPH group than in the PPH group. Moreover, compared with the PPH group, the decreased influence from ipsilesional M1 to the contralesional cerebellum and from the contralesional superior parietal lobe to ipsilesional M1 were observed in the CPH group, and their GCA values were positively correlated with the FMA scores; Conversely, the increased influence from ipsilesional M1 to the ipsilesional middle frontal gyrus and middle temporal gyrus were observed, whose GCA values were negatively correlated with the FMA scores. This study suggests that the abnormalities of casual flow in the ipsilesional M1 are related to the severity of stroke-hand dysfunction, providing valuable information to understand the deficits in resting-state effective connectivity of motor execution and the frontoparietal motor control network during brain plasticity following stroke.
Pub.: 16 Nov '16, Pinned: 27 Sep '17
Abstract: In recent years, there has been considerable research interest in the study of brain connectivity using the resting state functional magnetic resonance imaging (rsfMRI). Studies have explored the brain networks and connection between different brain regions. These studies have revealed interesting new findings about the brain mapping as well as important new insights in the overall organization of functional communication in the brain network. In this paper, after a general discussion of brain networks and connectivity imaging, the brain connectivity and resting state networks are described with a focus on rsfMRI imaging in stroke studies. Then, techniques for preprocessing of the rsfMRI for stroke patients are reviewed, followed by brain connectivity processing techniques. Recent research on brain connectivity using rsfMRI is reviewed with an emphasis on stroke studies. The authors hope this paper generates further interest in this emerging area of computational neuroscience with potential applications in rehabilitation of stroke patients.
Pub.: 16 Nov '16, Pinned: 27 Sep '17
Abstract: Publication date: Available online 9 November 2016 Source:Brain Stimulation Author(s): Georgios Naros, Alireza Gharabaghi Background Unlike in healthy controls, sensorimotor β-desynchronization (β-ERD) is compromised in stroke patients, i.e., the more severe the patient's motor impairment, the less β-ERD. This, in turn, provides a target substrate for therapeutic brain self-regulation and neurofeedback. Objective Transcranial alternating current stimulation (tACS) has been shown to modulate brain oscillations during and after stimulation, and may thus facilitate brain self-regulation during neurofeedback interventions. Methods Twenty severely impaired, chronic stroke patients performed kinesthetic motor-imagery while a brain-robot interface transformed β-ERD (17–23 Hz) of the ipsilesional sensorimotor cortex into opening of the paralyzed hand by a robotic orthosis. In a parallel group design, β-tACS (20 Hz, 1.1 mA peak-to-peak amplitude) was applied to the lesioned motor cortex either continuously (c-tACS) before or intermittently (i-tACS) during the intervention. Physiological effects of β-tACS were studied using electroencephalography. The patients' ability for brain self-regulation was captured by neurofeedback performance metrics. Results i-tACS - but not c-tACS - improved the classification accuracy of the neurofeedback intervention in comparison to baseline. This effect was mediated via the increased specificity of the classification, i.e., reduced variance of resting oscillations. Neither i-tACS nor c-tACS had aftereffects following the stimulation period. Conclusion β-tACS may constitute an adjunct neuromodulation technique during neurofeedback-based interventions for stroke rehabilitation.
Pub.: 14 Nov '16, Pinned: 27 Sep '17
Abstract: Several approaches to rehabilitation of the hand following a stroke have emerged over the last two decades. These treatments, including repetitive task practice (RTP), robotically assisted rehabilitation and virtual rehabilitation activities, produce improvements in hand function but have yet to reinstate function to pre-stroke levels-which likely depends on developing the therapies to impact cortical reorganization in a manner that favors or supports recovery. Understanding cortical reorganization that underlies the above interventions is therefore critical to inform how such therapies can be utilized and improved and is the focus of the current investigation. Specifically, we compare neural reorganization elicited in stroke patients participating in two interventions: a hybrid of robot-assisted virtual reality (RAVR) rehabilitation training and a program of RTP training. Ten chronic stroke subjects participated in eight 3-h sessions of RAVR therapy. Another group of nine stroke subjects participated in eight sessions of matched RTP therapy. Functional magnetic resonance imaging (fMRI) data were acquired during paretic hand movement, before and after training. We compared the difference between groups and sessions (before and after training) in terms of BOLD intensity, laterality index of activation in sensorimotor areas, and the effective connectivity between ipsilesional motor cortex (iMC), contralesional motor cortex, ipsilesional primary somatosensory cortex (iS1), ipsilesional ventral premotor area (iPMv), and ipsilesional supplementary motor area. Last, we analyzed the relationship between changes in fMRI data and functional improvement measured by the Jebsen Taylor Hand Function Test (JTHFT), in an attempt to identify how neurophysiological changes are related to motor improvement. Subjects in both groups demonstrated motor recovery after training, but fMRI data revealed RAVR-specific changes in neural reorganization patterns. First, BOLD signal in multiple regions of interest was reduced and re-lateralized to the ipsilesional side. Second, these changes correlated with improvement in JTHFT scores. Our findings suggest that RAVR training may lead to different neurophysiological changes when compared with traditional therapy. This effect may be attributed to the influence that augmented visual and haptic feedback during RAVR training exerts over higher-order somatosensory and visuomotor areas.
Pub.: 21 Sep '17, Pinned: 27 Sep '17
Abstract: Advanced lesion mapping and connectivity analyses are currently the main tools used to understand the mechanisms underlying post-stroke cognitive deficits. However, the factors contributing to pre-stroke architecture of cognitive networks are often ignored, even though they reportedly play a decisive role in the manifestation of cognitive impairment in neurodegeneration. The present review on post-stroke cognitive deficits therefore adopts the concept of brain and cognitive reserve, which was originally developed to account for the individual differences in the course of aging and neurodegenerative diseases. By focusing on spatial neglect, a typical network disorder, it is discussed how individual susceptibility to stroke lesion might explain the reported discrepancies in lesion anatomy, non-spatial deficits and recovery courses. A detailed analysis of the literature reveals that premorbid brain (age, brain atrophy, previous strokes, leukoaraiosis, genetic factors, etc.) and cognitive reserve (IQ, life experience, education, occupation, premorbid cognitive impairment, etc.) greatly impact the brain's capacity for compensation. Furthermore, the interaction between pre-stroke brain/cognitive reserve and the degree of stroke-induced system impairment (e.g., hypoperfusion, lesion load) determines both the extent of neglect symptoms variability and the course of recovery. Premorbid brain/cognitive reserves should thus be considered to: (i) understand the mechanisms of post-stroke cognitive disorders and sufficiently explain their inter-individual variability; (ii) provide a prognosis for cognitive recovery and hence post-stroke dependency; (iii) identify individual targets for cognitive rehabilitation: in the case of reduced brain/cognitive reserve, neglect might occur even with a confined lesion, and non-spatial training of general attentional capacity should represent the main therapeutic target also for treatment of neglect; this might be true also for non-cognitive domains, e.g., motor deficit. This alternative view of how neglect and other cognitive deficits occur and recover promotes discussion about plasticity and recovery to a general rather than a single stroke-based domain, providing more efficiency in recovery research.
Pub.: 05 Jan '17, Pinned: 27 Sep '17
Abstract: Responses to non-invasive brain stimulation are highly variable between subjects. Resting state functional connectivity was investigated as a marker of plasticity induced by anodal transcranial direct current stimulation (tDCS). Twenty-six healthy adults (15 male, 26.4±6.5 years) were tested. Experiment 1 investigated whether functional connectivity could predict modulation of corticospinal excitability following anodal tDCS. Experiment 2 determined test-retest reliability of connectivity measures. Three minutes of electroencephalography was recorded and connectivity was quantified with the debiased weighted phase lag index. Anodal (1mA, 20 minutes) or sham tDCS was applied to the left primary motor cortex (M1), with a change in motor evoked potential amplitude recorded from the right first dorsal interosseous used as a marker of tDCS response. Connectivity in the high beta frequency (20-30 Hz) between an electrode approximating the left M1 (C3) and electrodes overlying the left parietal cortex was a strong predictor of tDCS response (cross validated R(2) =0.69). Similar relationships were observed for alpha (8-13 Hz; R(2) =0.64), theta (4-7 Hz; R(2) = 0.53) and low beta (14-19 Hz; R(2) =0.58) frequencies, however test-retest reliability of connectivity measures was strongest for the high beta frequency model (ICC=0.65; good reliability). Further investigation of the high beta model found that greater connectivity between C3 and a cluster of electrodes approximately overlying the left parietal cortex was associated with stronger responses to anodal (rho=0.61, p=0.03), but not sham tDCS (rho=0.43, p=0.14). Functional connectivity is a strong predictor of the neuroplastic response to tDCS and may be one important characteristic to assist targeted tDCS application. This article is protected by copyright. All rights reserved.
Pub.: 20 Dec '16, Pinned: 27 Sep '17
Abstract: At the present time, there is enormous interest in methods of non-invasive brain stimulation. These interact with ongoing neural activity, mainly in cerebral cortex, and have measureable effects on behaviours in healthy people. More intriguingly, they appear to have effects on synaptic plasticity that persist even after stimulation has ceased. This has led, as might be expected, to the proposal that brain stimulation methods might be therapeutically useful in rehabilitation. The rationale is that physical therapy involves learning new patterns of activity to compensate for those lost to the stroke. Enhanced "plasticity" produced by brain stimulation might increase the ability to learn and enhance therapy. However, if things really were as simple as this, brain stimulation would be on its way to becoming a standard addition to treatment in all departments of rehabilitation. The fact that this has not happened means that something is not quite correct. Is the theory untenable, or are the methods of stimulation suboptimal?
Pub.: 31 Dec '16, Pinned: 27 Sep '17
Abstract: While several studies have shown that focal lesions affect the communication between structurally normal regions of the brain, and that these changes may correlate with behavioural deficits, their impact on brain's information processing capacity is currently unknown. Here we test the hypothesis that focal lesions decrease the brain's information processing capacity, of which changes in functional connectivity may be a measurable correlate. To measure processing capacity, we turned to whole brain computational modelling to estimate the integration and segregation of information in brain networks. First, we measured functional connectivity between different brain areas with resting state functional magnetic resonance imaging in healthy subjects (n = 26), and subjects who had suffered a cortical stroke (n = 36). We then used a whole-brain network model that coupled average excitatory activities of local regions via anatomical connectivity. Model parameters were optimized in each healthy or stroke participant to maximize correlation between model and empirical functional connectivity, so that the model's effective connectivity was a veridical representation of healthy or lesioned brain networks. Subsequently, we calculated two model-based measures: 'integration', a graph theoretical measure obtained from functional connectivity, which measures the connectedness of brain networks, and 'information capacity', an information theoretical measure that cannot be obtained empirically, representative of the segregative ability of brain networks to encode distinct stimuli. We found that both measures were decreased in stroke patients, as compared to healthy controls, particularly at the level of resting-state networks. Furthermore, we found that these measures, especially information capacity, correlate with measures of behavioural impairment and the segregation of resting-state networks empirically measured. This study shows that focal lesions affect the brain's ability to represent stimuli and task states, and that information capacity measured through whole brain models is a theory-driven measure of processing capacity that could be used as a biomarker of injury for outcome prediction or target for rehabilitation intervention.
Pub.: 24 Mar '17, Pinned: 27 Sep '17
Abstract: To support the recovery of disability and the reduced functional capacity influencing the independence of daily life after focal brain lesions like stroke, the application of noninvasive brain stimulation (NIBS) by repetitive transcranial magnetic stimulation or transcranial electric stimulation has been found useful in the last decades. Still, a positive influence on the recovery seems to be restricted to specific subgroups of patients. Therefore, a closer look on individual parameters influencing the recovery course and the effect of NIBS is needed.Neuroimaging studies investigated alterations in neuronal network settings during the recovery process from stroke and can explain a relevant amount of variance in residual motor function. In this regard for instance, the microstructural integrity of the corticospinal tract and its influence on cortical and subcortical functional and structural connectivity alterations shows a relevant impact on individual recovery from the acute to the chronic state.Based on this understanding, a 'one-suits-all' NIBS strategy for clinical application appears insufficient and understanding of therapeutic susceptibility to NIBS gained from structural and functional imaging studies will help to develop patient-tailored NIBS-based interventional strategies towards precision medicine, as a promising future prospective within this field.
Pub.: 27 May '17, Pinned: 27 Sep '17
Abstract: Rehabilitation is the main therapeutic approach for reducing poststroke functional deficits in the affected upper limb; however, significant between-patient variability in rehabilitation efficacy indicates the need to target patients who are likely to have clinically significant improvement after treatment. Many studies have determined robust predictors of recovery and treatment gains and yielded many great results using linear approachs. Evidence has emerged that the nonlinearity is a crucial aspect to study the inter-areal communication in human brains and abnormality of oscillatory activities in the motor system is linked to the pathological states. In this study, we hypothesized that combinations of linear and nonlinear (cross-frequency) network connectivity parameters are favourable biomarkers for stratifying patients for upper limb rehabilitation with increased accuracy. We identified the biomarkers by using 37 prerehabilitation electroencephalogram (EEG) datasets during a movement task through effective connectivity and logistic regression analyses. The predictive power of these biomarkers was then tested by using 16 independent datasets (i.e. construct validation). In addition, 14 right handed healthy subjects were also enrolled for comparisons. The result shows that the beta plus gamma or theta network features provided the best classification accuracy of 92%. The predictive value and the sensitivity of these biomarkers were 81.3% and 90.9%, respectively. Subcortical lesion, the time poststroke and initial Wolf Motor Function Test (WMFT) score were identified as the most significant clinical variables affecting the classification accuracy of this predictive model. Moreover, 12 of 14 normal controls were classified as having favourable recovery. In conclusion, EEG-based linear and nonlinear motor network biomarkers are robust and can help clinical decision making.
Pub.: 15 Jun '17, Pinned: 27 Sep '17
Abstract: 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.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.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.These topological measures show promise for prognosis and evaluation of therapeutic outcomes, as well as potential application to BCI-enabled biofeedback.
Pub.: 08 Jul '17, Pinned: 27 Sep '17
Abstract: There is currently a dearth of treatment options for stroke or traumatic brain injury that can restore cognitive and motor function. Regenerative and translational medicine have ushered forth promising new methods for mediating recovery in the central nervous system, the most salient of which are rehabilitation and stem cell therapies that, when combined, result in more pronounced recovery than one approach alone.
Pub.: 18 Jul '17, Pinned: 27 Sep '17
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