Computational neurorehabilitation: modeling plasticity and learning to predict recovery

Despite progress in using computational approaches to inform medicine and neuroscience in the last 30 years, there have been few attempts to model the mechanisms underlying sensorimotor rehabilitation. We argue that a fundamental understanding of neurologic recovery, and as a result accurate predictions at the individual level, will be facilitated by developing computational models of the salient neural processes, including plasticity and learning systems of the brain, and integrating them into a context specific to rehabilitation. Here, we therefore discuss Computational Neurorehabilitation, a newly emerging field aimed at modeling plasticity and motor learning to understand and improve movement recovery of individuals with neurologic impairment. We first explain how the emergence of robotics and wearable sensors for rehabilitation is providing data that make development and testing of such models increasingly feasible. We then review key aspects of plasticity and motor learning that such models will incorporate. We proceed by discussing how computational neurorehabilitation models relate to the current benchmark in rehabilitation modeling – regression-based, prognostic modeling. We then critically discuss the first computational neurorehabilitation models, which have primarily focused on modeling rehabilitation of the upper extremity after stroke, and show how even simple models have produced novel ideas for future investigation. Finally, we conclude with key directions for future research, anticipating that soon we will see the emergence of mechanistic models of motor recovery that are informed by clinical imaging results and driven by the actual movement content of rehabilitation therapy as well as wearable sensor-based records of daily activity

Action Observation for Neurorehabilitation in Apraxia

Neurorehabilitation and brain stimulation studies of post-stroke patients suggest that action-observation effects can lead to rapid improvements in the recovery of motor functions and long-term motor cortical reorganization. Apraxia is a clinically important disorder characterized by marked impairment in representing and performing skillful movements [gestures], which limits many daily activities and impedes independent functioning. Recent clinical research has revealed errors of visuo-motor integration in patients with apraxia. This paper presents a rehabilitative perspective focusing on the possibility of action observation as a therapeutic treatment for patients with apraxia. This perspective also outlines impacts on neurorehabilitation and brain repair following the reinforcement of the perceptual-motor coupling. To date, interventions based primarily on action observation in apraxia have not been undertaken

Effects on mobility training and de-adaptations in subjects with Spinal Cord Injury due to a Wearable Robot: A preliminary report

open7noopenSale, Patrizio; Russo, Emanuele Francesco; Russo, Michele; Masiero, Stefano; Piccione, Francesco; Calabrò, Rocco Salvatore; Filoni, SerenaSale, Patrizio; Russo, Emanuele Francesco; Russo, Michele; Masiero, Stefano; Piccione, Francesco; Calabrò, Rocco Salvatore; Filoni, Seren

Occasional essay: upper motor neuron syndrome in amyotrophic lateral sclerosis

The diagnosis of amyotrophic lateral sclerosis (ALS) requires recognition of both lower (LMN) and upper motor neuron (UMN) dysfunction.1 However, classical UMN signs are frequently difficult to identify in ALS.2 LMN involvement is sensitively detected by electromyography (EMG)3 but, as yet, there are no generally accepted markers for monitoring UMN abnormalities,4 the neurobiology of ALS itself, and disease spread through the brain and spinal cord,.5 Full clinical assessment is therefore necessary to exclude other diagnoses and to monitor disease progression. In part, this difficulty regarding detection of UMN involvement in ALS derives from the definition of ‘the UMN syndrome’. Abnormalities of motor control in ALS require reformulation within an expanded concept of the UMN, together with the neuropathological, neuro-imaging and neurophysiological abnormalities in ALS. We review these issues here

Rehabilitative devices for a top-down approach

In recent years, neurorehabilitation has moved from a "bottom-up" to a "top down" approach. This change has also involved the technological devices developed for motor and cognitive rehabilitation. It implies that during a task or during therapeutic exercises, new "top-down" approaches are being used to stimulate the brain in a more direct way to elicit plasticity-mediated motor re-learning. This is opposed to "Bottom up" approaches, which act at the physical level and attempt to bring about changes at the level of the central neural system. Areas covered: In the present unsystematic review, we present the most promising innovative technological devices that can effectively support rehabilitation based on a top-down approach, according to the most recent neuroscientific and neurocognitive findings. In particular, we explore if and how the use of new technological devices comprising serious exergames, virtual reality, robots, brain computer interfaces, rhythmic music and biofeedback devices might provide a top-down based approach. Expert commentary: Motor and cognitive systems are strongly harnessed in humans and thus cannot be separated in neurorehabilitation. Recently developed technologies in motor-cognitive rehabilitation might have a greater positive effect than conventional therapies

Effect of Sensory Attenuation on Cortical Movement-Related Oscillations

This study examined the impact of induced sensory deficits on cortical, movement-related oscillations measured using electroencephalography (EEG). We hypothesized that EEG patterns in healthy subjects with induced sensory reduction would be comparable to EEG found after chronic loss of sensory feedback. EEG signals from 64 scalp locations were measured from 10 healthy subjects. Participants dorsiflexed their ankle after prolonged vibration of the tibialis anterior (TA). Beta band time frequency decompositions were calculated using wavelets and compared across conditions. Changes in patterns of movement-related brain activity were observed following attenuation of sensory feedback. A significant decrease in beta power of event-related synchronization was associated with simple ankle dorsiflexion after prolonged vibration of the TA. Attenuation of sensory feedback in young, healthy subjects led to a corresponding decrease in beta band synchronization. This temporary change in beta oscillations suggests that these modulations are a mechanism for sensorimotor integration. The loss of sensory feedback found in spinal cord injury patients contributes to changes in EEG signals underlying motor commands. Similar alterations in cortical signals in healthy subjects with reduced sensory feedback implies these changes reflect normal sensorimotor integration after reduced sensory input rather than brain plasticity

Inside the brain of an elite athlete: The neural processes that support high achievement in sports

Events like the World Championships in athletics and the Olympic Games raise the public profile of competitive sports. They may also leave us wondering what sets the competitors in these events apart from those of us who simply watch. Here we attempt to link neural and cognitive processes that have been found to be important for elite performance with computational and physiological theories inspired by much simpler laboratory tasks. In this way we hope to inspire neuroscientists to consider how their basic research might help to explain sporting skill at the highest levels of performance

Changes in Intramuscular Coherence in Tibialis Anterior Muscle following a Visuomotor Gait Task

openThe aim of the study is to measure changes in intramuscular coherence between two sections of the Tibialis anterior muscle (proximal and distal) before and after performing a visuomotor gait task. The study is conducted on typically developed adults and children as well as individuals with cerebral palsy

Combining brain-computer interfaces and assistive technologies: state-of-the-art and challenges

In recent years, new research has brought the field of EEG-based Brain-Computer Interfacing (BCI) out of its infancy and into a phase of relative maturity through many demonstrated prototypes such as brain-controlled wheelchairs, keyboards, and computer games. With this proof-of-concept phase in the past, the time is now ripe to focus on the development of practical BCI technologies that can be brought out of the lab and into real-world applications. In particular, we focus on the prospect of improving the lives of countless disabled individuals through a combination of BCI technology with existing assistive technologies (AT). In pursuit of more practical BCIs for use outside of the lab, in this paper, we identify four application areas where disabled individuals could greatly benefit from advancements in BCI technology, namely,“Communication and Control”, “Motor Substitution”, “Entertainment”, and “Motor Recovery”. We review the current state of the art and possible future developments, while discussing the main research issues in these four areas. In particular, we expect the most progress in the development of technologies such as hybrid BCI architectures, user-machine adaptation algorithms, the exploitation of users’ mental states for BCI reliability and confidence measures, the incorporation of principles in human-computer interaction (HCI) to improve BCI usability, and the development of novel BCI technology including better EEG devices