A pinboard by
Brenton Hordacre

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.


Increased functional connectivity one week after motor learning and tDCS in stroke patients.

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

Altered Effective Connectivity of the Primary Motor Cortex in Stroke: A Resting-State fMRI Study with Granger Causality Analysis.

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

Physiological and behavioral effects of β-tACS on brain self-regulation in chronic stroke

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

Neural Patterns of Reorganization after Intensive Robot-Assisted Virtual Reality Therapy and Repetitive Task Practice in Patients with Chronic Stroke.

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

Adapting the concepts of brain and cognitive reserve to post-stroke cognitive deficits: Implications for understanding neglect.

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

Resting state functional connectivity measures correlate with the response to anodal transcranial direct current stimulation.

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

Decreased integration and information capacity in stroke measured by whole brain models of resting state activity.

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

Toward precision medicine: tailoring interventional strategies based on noninvasive brain stimulation for motor recovery after stroke.

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

EEG-based motor network biomarkers for identifying target patients with stroke for upper limb rehabilitation and its construct validity.

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

Topographical measures of functional connectivity as biomarkers for post-stroke motor recovery.

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