Distinct locomotor control and awareness in awake sleepwalkers

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Publications associées (29)

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Mapping behavioural actions to neural activity is a fundamental goal of neuroscience. As our ability to record large neural and behavioural data increases, there is growing interest in modelling neural dynamics during adaptive behaviours to probe neural re ...

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Nonlinear model predictive control (NMPC) has been widely adopted to manipulate bilinear systems with dynamics that include products of the inputs and the states. These systems are ubiquitous in chemical processes, mechanical systems, and quantum physics, ...

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Neurophysiological underpinnings of an intensive protocol for upper limb motor recovery in subacute and chronic stroke patients

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ABS T R A C T BACKGROUND: Upper limb (UL) motor impairment following stroke is a leading cause of functional limitations in activities of daily living. Robot-assisted therapy supports rehabilitation, but how its efficacy and the underlying neural mechanism ...

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Prediction of post-stroke motor recovery benefits from measures of sub-acute widespread network damages

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Rivier et al. report that global measures of brain connectivity estimated by introducing virtual lesions in healthy structural connectomes significantly increase the accuracy of motor recovery prediction in stroke patients when added to focal and clinical ...

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Inter-Task Transfer of Prism Adaptation through Motor Imagery

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Prism adaptation (PA) is a useful method to investigate short-term sensorimotor plasticity. Following active exposure to prisms, individuals show consistent after-effects, probing that they have adapted to the perturbation. Whether after-effects are transf ...

MDPI2023

Early decoding of walking tasks with minimal set of EMG channels

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Objective. Powered lower-limb prostheses relying on decoding motor intentions from non-invasive sensors, like electromyographic (EMG) signals, can significantly improve the quality of life of amputee subjects. However, the optimal combination of high decod ...

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The motor learning process entails plastic changes in the brain, especially in brain network reconfigurations. In the current study, we sought to characterize motor learning by determining changes in the coupling behaviour between the brain functional and ...

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Computational design and additive manufacturing of electromagnetic coils

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The modern world is heavily reliant on electromagnetic devices to convert mechanical energy into electrical energy and vice versa. These devices are fundamental to powering our society, and the growing need for automated production lines and electrified tr ...

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Identifying important sensory feedback for learning locomotion skills

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Robot motor skills can be acquired by deep reinforcement learning as neural networks to reflect state-action mapping. The selection of states has been demonstrated to be crucial for successful robot motor learning. However, because of the complexity of neu ...

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