Author name cluster

Nick S. Ward

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

12 papers

1 author row

YNICL Journal 2025 Journal Article

Post-stroke changes in brain structure and function can both influence acute upper limb function and subsequent recovery

Catharina Zich
Nick S. Ward
Nina Forss
Sven Bestmann
Andrew J. Quinn
Eeva Karhunen
Kristina Laaksonen

Improving outcomes after stroke depends on understanding both the causes of initial function/impairment and the mechanisms of recovery. Recovery in patients with initially low function/high impairment is variable, suggesting the factors relating to initial function/impairment are different to the factors important for subsequent recovery. Here we aimed to determine the contribution of altered brain structure and function to initial severity and subsequent recovery of the upper limb post-stroke. The Nine-Hole Peg Test was recorded in week 1 and one-month post-stroke and used to divide 36 stroke patients (18 females, age: M = 66.56 years) into those with high/low initial function and high/low subsequent recovery. We determined differences in week 1 brain structure (Magnetic Resonance Imaging) and function (Magnetoencephalography, tactile stimulation) between high/low patients for both initial function and subsequent recovery. Lastly, we examined the relative contribution of changes in brain structure and function to recovery in patients with low levels of initial function. Low initial function and low subsequent recovery are related to lower sensorimotor β power and greater lesion-induced disconnection of contralateral [ipsilesional] white-matter motor projection connections. Moreover, differences in intra-hemispheric connectivity (structural and functional) are unique to initial motor function, while differences in inter-hemispheric connectivity (structural and functional) are unique to subsequent motor recovery. Function-related and recovery-related differences in brain function and structure after stroke are related, yet not identical. Separating out the factors that contribute to each process is key to identifying potential therapeutic targets for improving outcomes.

Details DOI

YNIMG Journal 2019 Journal Article

Cortical beta oscillations are associated with motor performance following visuomotor learning

Svenja Espenhahn
Bernadette C.M. van Wijk
Holly E. Rossiter
Archy O. de Berker
Nell D. Redman
Jane Rondina
Joern Diedrichsen
Nick S. Ward

People vary in their capacity to learn and retain new motor skills. Although the relationship between neuronal oscillations in the beta frequency range (15–30 Hz) and motor behaviour is well established, the electrophysiological mechanisms underlying individual differences in motor learning are incompletely understood. Here, we investigated the degree to which measures of resting and movement-related beta power from sensorimotor cortex account for inter-individual differences in motor learning behaviour in the young and elderly. Twenty young (18–30 years) and twenty elderly (62–77 years) healthy adults were trained on a novel wrist flexion/extension tracking task and subsequently retested at two different time points (45–60 min and 24 h after initial training). Scalp EEG was recorded during a separate simple motor task before each training and retest session. Although short-term motor learning was comparable between young and elderly individuals, there was considerable variability within groups with subsequent analysis aiming to find the predictors of this variability. As expected, performance during the training phase was the best predictor of performance at later time points. However, regression analysis revealed that movement-related beta activity significantly explained additional variance in individual performance levels 45–60 min, but not 24 h after initial training. In the context of disease, these findings suggest that measurements of beta-band activity may offer novel targets for therapeutic interventions designed to promote rehabilitative outcomes.

Details DOI

YNICL Journal 2018 Journal Article

Disrupted functional network integrity and flexibility after stroke: Relation to motor impairments

Sara Larivière
Nick S. Ward
Marie-Hélène Boudrias

Previous studies investigating brain activation present during upper limb movement after stroke have greatly detailed activity alterations in the ipsi- and contralesional primary motor cortices (M1). Despite considerable interest in M1, investigations into the integration and coordination of large-scale functional networks subserving motor, sensory, and cognitive control after stroke remain scarce. The purpose of this study was to assess non-static functional connectivity within whole-brain networks involved in the production of isometric, visually-paced hand grips. Seventeen stroke patients and 24 healthy controls underwent functional MRI while performing a series of 50 isometric hand grips with their affected hand (stroke patients) or dominant hand (control subjects). We used task-based multivariate functional connectivity to derive spatial and temporal information of whole-brain networks specifically underlying hand movement. This technique has the advantage of extracting within-network commonalities across groups and identifying connectivity differences between these groups. We further used a nonparametric statistical approach to identify group differences in regional activity within these task-specific networks and assess whether such alterations were related to the degree of motor impairment in stroke patients. Our whole-brain multivariate analysis revealed group differences in two networks: (1) a motor network, including pre- and postcentral gyri, dorsal and ventral premotor cortices, as well as supplementary motor area, in which stroke patients showed reduced task-related activation compared to controls, and (2) a default-mode network (DMN), including the posterior cingulate cortex, precuneus, and medial prefrontal cortex, in which patients showed less deactivation than controls. Within-network group differences revealed decreased activity in ipsilesional primary sensorimotor cortex in stroke patients, which also positively correlated with lower levels of motor impairment. Moreover, the temporal information extracted from the functional networks revealed that stroke patients did not show a reciprocal DMN deactivation peak following activation of their motor network. This finding suggests that allocation of functional resources to motor areas during hand movement may impair their ability to efficiently switch from one network to another. Taken together, our study expands our understanding of functional reorganization during motor recovery after a stroke, and suggests that modulation of ipsilesional sensorimotor activity may increase the integrity of a whole-brain motor network, contribute to better motor performance, and optimize network flexibility.

Details DOI

YNIMG Journal 2017 Journal Article

Movement-related beta oscillations show high intra-individual reliability

Svenja Espenhahn
Archy O. de Berker
Bernadette C.M. van Wijk
Holly E. Rossiter
Nick S. Ward

Oscillatory activity in the beta frequency range (15–30Hz) recorded from human sensorimotor cortex is of increasing interest as a putative biomarker of motor system function and dysfunction. Despite its increasing use in basic and clinical research, surprisingly little is known about the test-retest reliability of spectral power and peak frequency measures of beta oscillatory signals from sensorimotor cortex. Establishing that these beta measures are stable over time in healthy populations is a necessary precursor to their use in the clinic. Here, we used scalp electroencephalography (EEG) to evaluate intra-individual reliability of beta-band oscillations over six sessions, focusing on changes in beta activity during movement (Movement-Related Beta Desynchronization, MRBD) and after movement termination (Post-Movement Beta Rebound, PMBR). Subjects performed visually-cued unimanual wrist flexion and extension. We assessed Intraclass Correlation Coefficients (ICC) and between-session correlations for spectral power and peak frequency measures of movement-related and resting beta activity. Movement-related and resting beta power from both sensorimotor cortices was highly reliable across sessions. Resting beta power yielded highest reliability (average ICC=0. 903), followed by MRBD (average ICC=0. 886) and PMBR (average ICC=0. 663). Notably, peak frequency measures yielded lower ICC values compared to the assessment of spectral power, particularly for movement-related beta activity (ICC=0. 386–0. 402). Our data highlight that power measures of movement-related beta oscillations are highly reliable, while corresponding peak frequency measures show greater intra-individual variability across sessions. Importantly, our finding that beta power estimates show high intra-individual reliability over time serves to validate the notion that these measures reflect meaningful individual differences that can be utilised in basic research and clinical studies.

Details DOI

YNIMG Journal 2016 Journal Article

Computational modelling of movement-related beta-oscillatory dynamics in human motor cortex

Mrudul B. Bhatt
Stephanie Bowen
Holly E. Rossiter
Joshua Dupont-Hadwen
Rosalyn J. Moran
Karl J. Friston
Nick S. Ward

Oscillatory activity in the beta range, in human primary motor cortex (M1), shows interesting dynamics that are tied to behaviour and change systematically in disease. To investigate the pathophysiology underlying these changes, we must first understand how changes in beta activity are caused in healthy subjects. We therefore adapted a canonical (repeatable) microcircuit model used in dynamic causal modelling (DCM) previously used to model induced responses in visual cortex. We adapted this model to accommodate cytoarchitectural differences between visual and motor cortex. Using biologically plausible connections, we used Bayesian model selection to identify the best model of measured MEG data from 11 young healthy participants, performing a simple handgrip task. We found that the canonical M1 model had substantially more model evidence than the generic canonical microcircuit model when explaining measured MEG data. The canonical M1 model reproduced measured dynamics in humans at rest, in a manner consistent with equivalent studies performed in mice. Furthermore, the changes in excitability (self-inhibition) necessary to explain beta suppression during handgrip were consistent with the attenuation of sensory precision implied by predictive coding. These results establish the face validity of a model that can be used to explore the laminar interactions that underlie beta-oscillatory dynamics in humans in vivo. Our canonical M1 model may be useful for characterising the synaptic mechanisms that mediate pathophysiological beta dynamics associated with movement disorders, such as stroke or Parkinson's disease.

Details DOI

YNICL Journal 2016 Journal Article

Decoding post-stroke motor function from structural brain imaging

Jane M. Rondina
Maurizio Filippone
Mark Girolami
Nick S. Ward

Clinical research based on neuroimaging data has benefited from machine learning methods, which have the ability to provide individualized predictions and to account for the interaction among units of information in the brain. Application of machine learning in structural imaging to investigate diseases that involve brain injury presents an additional challenge, especially in conditions like stroke, due to the high variability across patients regarding characteristics of the lesions. Extracting data from anatomical images in a way that translates brain damage information into features to be used as input to learning algorithms is still an open question. One of the most common approaches to capture regional information from brain injury is to obtain the lesion load per region (i.e. the proportion of voxels in anatomical structures that are considered to be damaged). However, no systematic evaluation has yet been performed to compare this approach with using patterns of voxels (i.e. considering each voxel as a single feature). In this paper we compared both approaches applying Gaussian Process Regression to decode motor scores in 50 chronic stroke patients based solely on data derived from structural MRI. For both approaches we compared different ways to delimit anatomical areas: regions of interest from an anatomical atlas, the corticospinal tract, a mask obtained from fMRI analysis with a motor task in healthy controls and regions selected using lesion-symptom mapping. Our analysis showed that extracting features through patterns of voxels that represent lesion probability produced better results than quantifying the lesion load per region. In particular, from the different ways to delimit anatomical areas compared, the best performance was obtained with a combination of a range of cortical and subcortical motor areas as well as the corticospinal tract. These results will inform the appropriate methodology for predicting long term motor outcomes from early post-stroke structural brain imaging.

Details DOI

YNIMG Journal 2014 Journal Article

Beta oscillations reflect changes in motor cortex inhibition in healthy ageing

Holly E. Rossiter
Emma M. Davis
Ella V. Clark
Marie-Hélène Boudrias
Nick S. Ward

Beta oscillations are involved in movement and have previously been linked to levels of the inhibitory neurotransmitter GABA. We examined changes in beta oscillations during rest and movement in primary motor cortex (M1). Amplitude and frequency of beta power at rest and movement-related beta desynchronization (MRBD) were measured during a simple unimanual grip task and their relationship with age was explored in a group of healthy participants. We were able to show that at rest, increasing age was associated with greater baseline beta power in M1 contralateral to the active hand, with a similar (non-significant) trend in ipsilateral M1. During movement, increasing age was associated with increased MRBD amplitude in ipsilateral M1 and reduced frequency (in contralateral and ipsilateral M1). These findings would be consistent with greater GABAergic inhibitory activity within motor cortices of older subjects. These oscillatory parameters have the potential to reveal changes in the excitatory–inhibitory balance in M1 which in turn may be a useful marker of plasticity in the brain, both in healthy ageing and disease.

Details DOI

YNIMG Journal 2014 Journal Article

Re-thinking the role of motor cortex: Context-sensitive motor outputs?

Marta Gandolla
Simona Ferrante
Franco Molteni
Eleonora Guanziroli
Tiziano Frattini
Alberto Martegani
Giancarlo Ferrigno
Karl Friston

The standard account of motor control considers descending outputs from primary motor cortex (M1) as motor commands and efference copy. This account has been challenged recently by an alternative formulation in terms of active inference: M1 is considered as part of a sensorimotor hierarchy providing top–down proprioceptive predictions. The key difference between these accounts is that predictions are sensitive to the current proprioceptive context, whereas efference copy is not. Using functional electric stimulation to experimentally manipulate proprioception during voluntary movement in healthy human subjects, we assessed the evidence for context sensitive output from M1. Dynamic causal modeling of functional magnetic resonance imaging responses showed that FES altered proprioception increased the influence of M1 on primary somatosensory cortex (S1). These results disambiguate competing accounts of motor control, provide some insight into the synaptic mechanisms of sensory attenuation and may speak to potential mechanisms of action of FES in promoting motor learning in neurorehabilitation.

Details DOI

YNICL Journal 2013 Journal Article

Assessing a standardised approach to measuring corticospinal integrity after stroke with DTI

Chang-hyun Park
Nancy Kou
Marie-Hélène Boudrias
E. Diane Playford
Nick S. Ward

The structural integrity of the corticospinal tract (CST) after stroke is closely linked to the degree of motor impairment. Simple and reliable methods of assessing white matter integrity within the CST would facilitate the use of this measure in routine clinical practice. Commonly, diffusion tensor imaging is used to measure voxel-wise fractional anisotropy (FA) in a variety of regions of interest (ROIs) representing the CST. Several methods are currently in use with no consensus about which approach is best. ROIs are usually either the whole CST or the posterior limb of the internal capsule (PLIC). These are created manually on brain images or with reference to an individual's CST determined by tractography. Once the ROI has been defined, the FA can be reported as an absolute measure from the ipsilesional side or as a ratio in comparison to the contralesional side. Both corticospinal tracking and manual ROI definition in individual stroke patients are time consuming and subject to bias. Here, we investigated whether using a CST template derived from healthy volunteers was a feasible method for defining the appropriate ROI within which to measure changes in FA. We reconstructed the CST connecting the primary motor cortex to the ipsilateral pons in 23 age-matched control subjects and 21 stroke patients. An average healthy CST template was created from the 23 control subjects. For each patient, FA values were then calculated for both the template CST and for their own CST. We compared patients' FA metrics between the two tracts by considering four measures (FA in the ipsilesional side, FA in the contralesional side, FA ratio of the ipsilesional side to the contralesional side and FA asymmetry between the two sides) and in two tract-based ROIs (whole tract and tract section traversing the PLIC). There were no significant differences in FA metrics for either method, except for contralesional FA. Furthermore, we found that FA metrics relating to CST damage all correlated with motor ability post-stroke equally well. These results suggest that the healthy CST template could be a surrogate structure for defining tract-based ROIs with which to measure stroke patients' FA metrics, avoiding the necessity for CST tracking in individual patients. CST template-based automated quantification of structural integrity would greatly facilitate implementation of practical clinical applications of diffusion tensor imaging.

Details DOI

YNICL Journal 2013 Journal Article

Changes in the location of cortico-muscular coherence following stroke

Holly E. Rossiter
Christiane Eaves
Emma Davis
Marie-Hélène Boudrias
Chang-hyun Park
Simon Farmer
Gareth Barnes
Vladimir Litvak

Stroke results in reorganization of residual brain networks. The functional role of brain regions within these networks remains unclear, particularly those in the contralesional hemisphere. We studied 25 stroke patients with a range of motor impairment and 23 healthy age-matched controls using magnetoencephalography (MEG) and electromyography (EMG) to measure oscillatory signals from the brain and affected muscles simultaneously during a simple isometric hand grip, from which cortico-muscular coherence (CMC) was calculated. Peaks of cortico-muscular coherence in both the beta and gamma bands were found in the contralateral sensorimotor cortex in all healthy controls, but were more widespread in stroke patients, including some peaks found in the contralesional hemisphere (7 patients for beta coherence and 5 for gamma coherence). Neither the coherence value nor the distance of the coherence peak from the mean of controls correlated with impairment. Peak CMC in the contralesional hemisphere was found not only in some highly impaired patients, but also in some patients with good functional recovery. Our results provide evidence that a wide range of cortical brain regions, including some in the contralesional hemisphere, may have influence over EMG activity in the affected muscles after stroke thereby supporting functional recovery.

Details DOI

YNIMG Journal 2012 Journal Article

A dynamic causal model for evoked and induced responses

Chun-Chuan Chen
Stefan J. Kiebel
James M. Kilner
Nick S. Ward
Klaas E. Stephan
Wei- Jen Wang
Karl J. Friston

Neuronal responses exhibit two stimulus or task-related components: evoked and induced. The functional role of induced responses has been ascribed to ‘top-down’ modulation through backward connections and lateral interactions; as opposed to the bottom-up driving processes that may predominate in evoked components. The implication is that evoked and induced components may reflect different neuronal processes. The conventional way of separating evoked and induced responses assumes that they can be decomposed linearly; in that induced responses are the average of the power minus the power of the average (the evoked component). However, this decomposition may not hold if both components are generated by nonlinear processes. In this work, we propose a Dynamic Causal Model that models evoked and induced responses at the same time. This allows us to explain both components in terms of shared mechanisms (coupling) and changes in coupling that are necessary to explain any induced components. To establish the face validity of our approach, we used Bayesian Model Selection to show that the scheme can disambiguate between models of synthetic data that did and did not contain induced components. We then repeated the analysis using MEG data during a hand grip task to ask whether induced responses in motor control circuits are mediated by ‘top-down’ or backward connections. Our result provides empirical evidence that induced responses are more likely to reflect backward message passing in the brain, while evoked and induced components share certain characteristics and mechanisms.

Details DOI

YNIMG Journal 2012 Journal Article

Age-related changes in causal interactions between cortical motor regions during hand grip

Marie-Hélène Boudrias
Carla Sá Gonçalves
Will D. Penny
Chang-hyun Park
Holly E. Rossiter
Penelope Talelli
Nick S. Ward

Brain activity during motor performance becomes more widespread and less lateralized with advancing age in response to ongoing degenerative processes. In this study, we were interested in the mechanism by which this change in the pattern of activity supports motor performance with advancing age. We used both transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) to assess age related changes in motor system connectivity during isometric hand grip. Paired pulse TMS was used to measure the change in interhemispheric inhibition (IHI) from contralateral M1 (cM1) to ipsilateral M1 (iM1) during right hand grip. Dynamic Causal Modelling (DCM) of fMRI data was used to investigate the effect of age on causal interactions throughout the cortical motor network during right hand grip. Bayesian model selection was used to identify the causal model that best explained the data for all subjects. Firstly, we confirmed that the TMS and DCM measures both demonstrated a less inhibitory/more facilitatory influence of cM1 on iM1 during hand grip with advancing age. These values correlated with one another providing face validity for our DCM measures of connectivity. We found increasing reciprocal facilitatory influences with advancing age (i) between all ipsilateral cortical motor areas and (ii) between cortical motor areas of both hemispheres and iM1. There were no differences in the performance of our task with ageing suggesting that the ipsilateral cortical motor areas, in particular iM1, play a central role in maintaining performance levels with ageing through increasingly facilitatory cortico-cortical influences.

Details DOI