Post-stroke reorganization of transient brain activity characterizes deficits and recovery of cognitive functions

Functional magnetic resonance imaging (fMRI) has been widely employed to study stroke pathophysiology. In particular, analyses of fMRI signals at rest were directed at quantifying the impact of stroke on spatial features of brain networks. However, brain networks have intrinsic time features that were, so far, disregarded in these analyses. In consequence, standard fMRI analysis failed to capture temporal imbalance resulting from stroke lesions, hence restricting their ability to reveal the interdependent pathological changes in structural and temporal network features following stroke. Here, we longitudinally analyzed hemodynamic-informed transient activity in a large cohort of stroke patients (n = 103) to assess spatial and temporal changes of brain networks after stroke. Metrics extracted from the hemodynamic-informed transient activity were replicable within- and between-individuals in healthy participants, hence supporting their robustness and their clinical applicability. While large-scale spatial patterns of brain networks were preserved after stroke, their durations were altered, with stroke subjects exhibiting a varied pattern of longer and shorter network activations compared to healthy individuals. Specifically, patients showed a longer duration in the lateral precentral gyrus and anterior cingulum, and a shorter duration in the occipital lobe and in the cerebellum. These temporal alterations were associated with white matter damage in projection and association pathways. Furthermore, they were tied to deficits in specific behavioral domains as restoration of healthy brain dynamics paralleled recovery of cognitive functions (attention, language and spatial memory), but was not significantly correlated to motor recovery. These findings underscore the critical importance of network temporal properties in dissecting the pathophysiology of brain changes after stroke, thus shedding new light on the clinical potential of time-resolved methods for fMRI analysis

Balancing the playing field: collaborative gaming for physical training.

BACKGROUND: Multiplayer video games promoting exercise-based rehabilitation may facilitate motor learning, by increasing motivation through social interaction. However, a major design challenge is to enable meaningful inter-subject interaction, whilst allowing for significant skill differences between players. We present a novel motor-training paradigm that allows real-time collaboration and performance enhancement, across a wide range of inter-subject skill mismatches, including disabled vs. able-bodied partnerships. METHODS: A virtual task consisting of a dynamic ball on a beam, is controlled at each end using independent digital force-sensing handgrips. Interaction is mediated through simulated physical coupling and locally-redundant control. Game performance was measured in 16 healthy-healthy and 16 patient-expert dyads, where patients were hemiparetic stroke survivors using their impaired arm. Dual-player was compared to single-player performance, in terms of score, target tracking, stability, effort and smoothness; and questionnaires probing user-experience and engagement. RESULTS: Performance of less-able subjects (as ranked from single-player ability) was enhanced by dual-player mode, by an amount proportionate to the partnership's mismatch. The more abled partners' performances decreased by a similar amount. Such zero-sum interactions were observed for both healthy-healthy and patient-expert interactions. Dual-player was preferred by the majority of players independent of baseline ability and subject group; healthy subjects also felt more challenged, and patients more skilled. CONCLUSION: This is the first demonstration of implicit skill balancing in a truly collaborative virtual training task leading to heightened engagement, across both healthy subjects and stroke patients

Central and peripheral mechanisms: a multimodal approach to understanding and restoring human motor control

All human actions involve motor control. Even the simplest movement requires the coordinated recruitment of many muscles, orchestrated by neuronal circuits in the brain and the spinal cord. As a consequence, lesions affecting the central nervous system, such as stroke, can lead to a wide range of motor impairments. While a certain degree of recovery can often be achieved by harnessing the plasticity of the motor hierarchy, patients typically struggle to regain full motor control. In this context, technology-assisted interventions offer the prospect of intense, controllable and quantifiable motor training. Yet, clinical outcomes remain comparable to conventional approaches, suggesting the need for a paradigm shift towards customized knowledge-driven treatments to fully exploit their potential. In this thesis, we argue that a detailed understanding of healthy and impaired motor pathways can foster the development of therapies optimally engaging plasticity. To this end, we develop and apply multimodal methodologies to investigate the central and peripheral mechanisms underlying motor control and recovery. In the first part of this work, we concentrate on the transition from one-suits-all approaches to patient-tailored protocols, in the context of robot-assisted rehabilitation. We start addressing this question from a technical viewpoint and propose methods to assess individual dynamics of recovery in stroke patients. First, we demonstrate the applicability of a model-based approach to continuously personalize training based on kinematic motor improvement. Then, we show how complementary knowledge can be gleaned from kinematics, muscular and neural signals, and we introduce a versatile framework to distill this multimodal information into a set of clinically relevant variables. These results highlight the pivotal importance of multimodality, stressing the need for a comprehensive view of the human motor hierarchy. To this end, the second part of this work focuses on the spinal cord, whose functional properties remain largely unexplored in humans. As this gap of knowledge primarily pertains to the dearth of non-invasive methods to assess its function in vivo, we first propose a pipeline for spinal cord functional magnetic resonance imaging (fMRI) and demonstrate its ability to capture cervical activation patterns during upper limb movements. We then present a dynamic functional connectivity framework to dissect spinal spontaneous fluctuations into fine-grained components mirroring neuroanatomical and physiological principles. Next, we extend the use of this approach to fMRI data acquired in the entire neural axis during motor sequence learning, hence shedding light on specific cortical, subcortical and spinal correlates of skill acquisition and consolidation. Finally, we glimpse into the implementation of these methodologies in the scope of translational applications, providing evidence of their potential to explore spinal plasticity following stroke. These findings are a valuable contribution towards an extensive characterization of human motor control. This system-level view deepens our understanding of motor pathways, fully acknowledging the active and plastic nature of the spinal cord and emphasizing its key role in sensorimotor functions. We envision that the synergy between technology and knowledge will open promising avenues for strategies leveraging each patientâs residual function to optimize clinical outcome

Spinal Cord fMRI: A New Window into the Central Nervous System

With the brain, the spinal cord forms the central nervous system. Initially considered a passive relay between the brain and the periphery, the spinal cord is now recognized as being active and plastic. Yet, it remains largely overlooked by the human neuroscience community, in stark contrast with the wealth of research investigating the brain. In this review, we argue that fMRI, traditionally used to image cerebral function, can be extended beyond the brain to help unravel spinal mechanisms involved in human behaviors. To this end, we first outline strategies that have been proposed to tackle the challenges inherent to spinal cord fMRI. Then, we discuss how they have been utilized to provide insights into the functional organization of spinal sensorimotor circuits, highlighting their potential to address fundamental and clinical questions. By summarizing guidelines and applications of spinal cord fMRI, we hope to stimulate and support further research into this promising yet underexplored field.</p

Dynamic functional connectivity of resting-state spinal cord fMRI reveals fine-grained intrinsic architecture

The neuroimaging community has shown tremendous interest in exploring the brain's spontaneous activity using functional magnetic resonance imaging (fMRI). On the contrary, the spinal cord has been largely overlooked despite its pivotal role in processing sensorimotor signals. Only a handful of studies have probed the organization of spinal resting-state fluctuations, always using static measures of connectivity. Many innovative approaches have emerged for analyzing dynamics of brain fMRI, but they have not yet been applied to the spinal cord, although they could help disentangle its functional architecture. Here, we leverage a dynamic connectivity method based on the clustering of hemodynamic-informed transients to unravel the rich dynamic organization of spinal resting-state signals. We test this approach in 19 healthy subjects, uncovering fine-grained spinal components and highlighting their neuroanatomical and physiological nature. We provide a versatile tool, the spinal innovation-driven co-activation patterns (SpiCiCAP) framework, to characterize spinal circuits during rest and task, as well as their disruption in neurological disorders

System for personalized robotic therapy and related methods

The present invention provides an apparatus and a method able to estimate motor improvement in real-time during three-dimensional rehabilitation tasks and to consequently dynamically personalize the therapy.The method can be carried out by a computer program. The use of said apparatus for restoring motor functions in a subject suffering from neuromotor impairment is also within the scope of the invention

Towards reliable spinal cord fMRI: Assessment of common imaging protocols

Functional magnetic resonance imaging (fMRI) has revolutionized the investigation of brain function. Similar approaches can be translated to probe spinal mechanisms. However, imaging the spinal cord remains challenging, notably due to its size and location. Technological advances are gradually tackling these issues, though there is yet no consensus on optimal acquisition protocols. In this study, we assessed the performance of three sequences during a simple motor task and at rest, in 15 healthy humans. Building upon recent literature, we selected three imaging protocols: a sequence integrating outer volume suppression (OVS) and two sequences implementing inner field-of-view imaging (ZOOMit) with different spatial and temporal resolutions. Images acquired using the OVS sequence appeared more prone to breathing-induced signal fluctuations, though they exhibited a higher temporal signal-to-noise ratio than ZOOMit sequences. Conversely, the spatial signal-to-noise ratio was higher for the two ZOOMit schemes. In spite of these differences in signal properties, all sequences yielded comparable performance in detecting group-level task-related activity, observed in the expected spinal levels. Nevertheless, our results suggest a superior sensitivity and robustness of patterns imaged using the OVS acquisition scheme. To analyze the data acquired at rest, we deployed a dynamic functional connectivity framework, SpiCiCAP, and we evaluated the ability of the three acquisition schemes to disentangle intrinsic spinal signals. We demonstrated that meaningful subdivisions of the spinal cord's functional architecture could be uncovered for all three sequences, with similar spatio-temporal properties across acquisition parameters. Cleaner and more stable components were, however, obtained using ZOOMit sequences. This study emphasizes the potential of fMRI as a robust tool to image spinal activity in vivo and it highlights specificities and similarities of three acquisition methods. This represents a key step towards the establishment of standardized spinal cord fMRI protocols

Evolution of Cortical Asymmetry with Post-stroke Rehabilitation: A Pilot Study

The lesions induced by unilateral strokes perturb the complex and critical interhemispheric balance. While a high asymmetry measured in the acute phase is known to be a predictor for poor motor recovery, the evolution of this imbalance along motor recovery has not been studied. Here, we evaluated the evolution of the cortical power asymmetry during a robot-assisted motor task along a rehabilitation intervention. Preliminary results suggest that a reduction of the brain asymmetry towards values exhibited by healthy controls is associated with higher motor recovery

Motor improvement estimation and task adaptation for personalized robot-aided therapy: a feasibility study

In the past years, robotic systems have become increasingly popular in upper limb rehabilitation. Nevertheless, clinical studies have so far not been able to confirm superior efficacy of robotic therapy over conventional methods. The personalization of robot-aided therapy according to the patients' individual motor deficits has been suggested as a pivotal step to improve the clinical outcome of such approaches

Resting-State Functional Connectivity in Stroke Patients After Upper Limb Robot-Assisted Therapy: A Pilot Study

Motor deficit is a prominent feature among stroke survivors. Robot-assisted therapies have been proposed as a strategy to boost rehabilitation, byallowing therapy to be provided in a more reproducible and intense manner,while quantitatively monitoring patient’s improvement. However, thoseapproaches have so far not shown superiority over conventional treatments. Onepotential solution to reach better outcomes would be to personalize the treatment.In this regard, a better understanding of the mechanisms underlying motorrecovery is pivotal to tailor therapy to each patient. Here, we explored the corticalchanges occurring during robotic training. We recorded resting-state fMRI beforeand after the treatment in three sub-acute post-stroke survivors, and we investi-gated the functional connectivity between motor regions. We observed a corticalreorganization following training, consistent with motor improvement