ArticleJournal of neural engineering2020
A comprehensive model-based framework for optimal design of biomimetic patterns of electrical stimulation for prosthetic sensation.
Article in Journal of neural engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 32 citations in OpenAlex.
- The optimization of neuroprosthetic interfaces relying on biophysical and surrogate digital twins.npj biomedical innovations · 2026Review
- Integration of learned artificial sensation with vision during freely moving navigation.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- NRV: An open framework for in silico evaluation of peripheral nerve electrical stimulation strategies.PLoS computational biology · 2024Article
- NRV: An open framework forbioRxiv : the preprint server for biology · 2024Article
- Neural Plasticity in Sensorimotor Brain-Machine Interfaces.Annual review of biomedical engineering · 2023Review
- Autonomous optimization of neuroprosthetic stimulation parameters that drive the motor cortex and spinal cord outputs in rats and monkeys.Cell reports. Medicine · 2023Article
- Peripheral neurostimulation for encoding artificial somatosensations.The European journal of neuroscience · 2022Review
- A prosthesis utilizing natural vestibular encoding strategies improves sensorimotor performance in monkeys.PLoS biology · 2022Article
- The science and engineering behind sensitized brain-controlled bionic hands.Physiological reviews · 2022Review
- Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier.Brain computer interfaces (Abingdon, England) · 2022Article
- Normalization by valence and motivational intensity in the sensorimotor cortices (PMd, M1, and S1).Scientific reports · 2021Article
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- Stoney vs. Histed: Quantifying the spatial effects of intracortical microstimulation.Brain stimulationArticle
- Neural mechanisms of the temporal response of cortical neurons to intracortical microstimulation.Brain stimulationArticle
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Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
objectiveTouch and proprioception are essential to motor function as shown by the movement deficits that result from the loss of these senses, e.g. due to neuropathy of sensory nerves. To achieve a high-performance brain-controlled prosthetic arm/hand thus requires the restoration of somatosensation, perhaps through intracortical microstimulation (ICMS) of somatosensory cortex (S1). The challenge is to generate patterns of neuronal activation that evoke interpretable percepts. We present a framework to design optimal spatiotemporal patterns of ICMS (STIM) that evoke naturalistic patterns of neuronal activity and demonstrate performance superior to four previous approaches. APPROACH: We recorded multiunit activity from S1 during a center-out reach task (from proprioceptive neurons in Brodmann's area 2) and during application of skin indentations (from cutaneous neurons in Brodmann's area 1). We implemented a computational model of a cortical hypercolumn and used a genetic algorithm to design STIM that evoked patterns of model neuron activity that mimicked their experimentally-measured counterparts. Finally, from the ICMS patterns, the evoked neuronal activity, and the stimulus parameters that gave rise to it, we trained a recurrent neural network (RNN) to learn the mapping function between the physical stimulus and the biomimetic stimulation pattern, i.e. the sensory encoder to be integrated into a neuroprosthetic device. MAIN
resultsWe identified ICMS patterns that evoked simulated responses that closely approximated the measured responses for neurons within 50 µm of the electrode tip. The RNN-based sensory encoder generalized well to untrained limb movements or skin indentations. STIM designed using the model-based optimization approach outperformed STIM designed using existing linear and nonlinear mappings. SIGNIFICANCE: The proposed framework produces an encoder that converts limb state or patterns of pressure exerted onto the prosthetic hand into STIM that evoke naturalistic patterns of neuronal activation.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.