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Reinkensmeyer, D. J.

Publications and source records attributed to Reinkensmeyer, D. J..

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Bilateral Mechanoreception Discrimination based on Bihemispheric Somatosensory Response Patterns is Associated with Proprioception and Motor Function After Stroke

ObjectivesStroke commonly impairs proprioception and motor function, yet the cortical sensory processes underlying these impairments remain poorly understood. Prior electrophysiological studies have primarily focused on the average magnitude of unilateral cortical sensory responses to vibration, potentially overlooking distributed and trial-to-trial features of sensory processing that may be functionally relevant to proprioceptive processing and motor performance. We therefore aimed to characterize bilateral cortical sensory responses to determine their relationships with proprioceptive and motor function. MethodsEEG was recorded from forty-six individuals with chronic stroke during a rapid, passive, vibrotactile stimulation paradigm applied to the left and right fingertips. Somatosensory evoked potentials (SEPs) and event-related desynchronization (ERD) were quantified. Finger proprioceptive performance was assessed using a passive, robotic, finger crossing identification task, while motor function was evaluated using the Box and Block Test, Fugl-Meyer Assessment, and Nine Hole Peg Test. Associations with function were assessed using (i) unilateral sensory response magnitude at the contralateral parietal cortex and (ii) somatosensory decoder performance, defined as the accuracy with which a decoder identified the location of the stimulated hand (i.e. paretic vs. non-paretic) from combined bihemispheric response patterns. The association between these responses and proprioceptive ability and motor function was assessed. These associations were further evaluated jointly across multiple motor function measures using an exploratory analysis leveraging nonlinear dimensionality reduction and clustering. ResultsVibrotactile stimulation of the paretic hand elicited ipsilesional SEP and ERD that were reduced in magnitude compared to stimulation of the non-paretic hand. Both decreased SEP magnitude and reduced sensory decoder performance were associated with greater finger proprioceptive error. Unlike unilateral responses, the somatosensory decoders performance was also strongly associated with motor function, explaining approximately 22.5% of the variance in motor performance. Dimensionality reduction and clustering across multiple motor assessment scores showed distinct subgroups, that showed significant differences in sensory decoding. ConclusionsThe hemispheric distribution and discriminability of cortical sensory responses are functionally relevant markers of sensorimotor integrity after stroke. Assessing relative lateralization of somatosensory responses for each hand, rather than the magnitude of dominant contralateral responses alone, may better capture the reliability of sensory processing after stroke, as well as the distributed cortical reorganization supporting sensorimotor function. These findings support the potential value of a novel decoding-based neurophysiological measure for sensory-driven rehabilitation, biomarker development, and patient stratification.

neuroscience↗

Targeting Neuroplasticity to Improve Motor Recovery after Stroke

After neurological injury, people develop abnormal patterns of neural activity that limit motor recovery. Traditional rehabilitation, which concentrates on practicing impaired skills, is seldom fully effective. New targeted neuroplasticity (TNP) protocols interact with the CNS to induce beneficial plasticity in key sites and thereby enable wider beneficial plasticity. They can complement traditional therapy and enhance recovery. However, their development and validation is difficult because many different TNP protocols are conceivable, and evaluating even one of them is lengthy, laborious, and expensive. Computational models can address this problem by triaging numerous candidate protocols rapidly and effectively. Animal and human empirical testing can then concentrate on the most promising ones. Here we simulate a neural network of corticospinal neurons that control motoneurons eliciting unilateral finger extension. We use this network to (1) study the mechanisms and patterns of cortical reorganization after a stroke, and (2) identify and parameterize a TNP protocol that improves recovery of extension force. After a simulated stroke, standard training produced abnormal bilateral cortical activation and suboptimal force recovery. To enhance recovery, we interdigitated standard trials with trials in which the teaching signal came from a targeted population of sub-optimized neurons. Targeting neurons in secondary motor areas on 5-20% of the total trials restored lateralized cortical activation and improved recovery of extension force. The results illuminate mechanisms underlying suboptimal cortical activity post-stroke; they enable identification and parameterization of the most promising TNP protocols. By providing initial guidance, computational models could facilitate and accelerate realization of new therapies that improve motor recovery.

neuroscience↗