ArticleeNeuro
The Representation of Finger Movement and Force in Human Motor and Premotor Cortices.
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Who cites it
18 citing papers in PubMed, 41 citations in OpenAlex.
- Flexible reorientation of conserved neural dynamics underlies grasp control.bioRxiv : the preprint server for biology · 2026Article
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- A general model based on Riemannian manifold for stable decoding movement trajectory from ECoG signals.iScience · 2026Article
- Stabilizing brain-computer interfaces through alignment of latent dynamics.Nature communications · 2025Article
- 5-year follow-up of a fully implanted brain-computer interface in a spinal cord injury patient.Journal of neural engineering · 2025Article
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- Reducing power requirements for high-accuracy decoding in iBCIs.Journal of neural engineering · 2024Article
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- Flexible regulation of representations on a drifting manifold enables long-term stable complex neuroprosthetic control.bioRxiv : the preprint server for biology · 2023Article
- Sensory weighting of position and force feedback during pinching.Experimental brain research · 2023Article
- Quantifying Hand Strength and Isometric Pinch Individuation Using a Flexible Pressure Sensor Grid.Sensors (Basel, Switzerland) · 2023Article
- Investigating the concept of representation in the neural and psychological sciences.Frontiers in psychology · 2023Article
- Noninvasively recorded high-gamma signals improve synchrony of force feedback in a novel neurorehabilitation brain-machine interface for brain injury.Journal of neural engineering · 2022Article
- On-scalp magnetocorticography with optically pumped magnetometers: Simulated performance in resolving simultaneous sources.Neuroimage. Reports · 2022Article
- A generic neural network model to estimate populational neural activity for robust neural decoding.Computers in biology and medicine · 2022Article
- Article
- Decoding Digital Visual Stimulation From Neural Manifold With Fuzzy Leaning on Cortical Oscillatory Dynamics.Frontiers in computational neuroscience · 2022Article
- Multi-scale neural decoding and analysis.Journal of neural engineering · 2021Review
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
The ability to grasp and manipulate objects requires controlling both finger movement kinematics and isometric force in rapid succession. Previous work suggests that these behavioral modes are controlled separately, but it is unknown whether the cerebral cortex represents them differently. Here, we asked the question of how movement and force were represented cortically, when executed sequentially with the same finger. We recorded high-density electrocorticography (ECoG) from the motor and premotor cortices of seven human subjects performing a movement-force motor task. We decoded finger movement [0.7 ± 0.3 fractional variance accounted for (FVAF)] and force (0.7 ± 0.2 FVAF) with high accuracy, yet found different spatial representations. In addition, we used a state-of-the-art deep learning method to uncover smooth, repeatable trajectories through ECoG state space during the movement-force task. We also summarized ECoG across trials and participants by developing a new metric, the neural vector angle (NVA). Thus, state-space techniques can help to investigate broad cortical networks. Finally, we were able to classify the behavioral mode from neural signals with high accuracy (90 ± 6%). Thus, finger movement and force appear to have distinct representations in motor/premotor cortices. These results inform our understanding of the neural control of movement, as well as the design of grasp brain-machine interfaces (BMIs).
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Registered trials
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.