Evidence map›Paper›PMID 40819020›Full record

ArticleScientific reports2025

Directional hand movement can be classified from insular cortex SEEG signals using recurrent neural networks and high-gamma band features.

Xiecheng Shao, Ryan S Chung, Jonathon M Cavaleri, Roberto Martin Del Campo-Vera, Miguel Parra, Shivani Sundaram, Selena Zhang, Ashwitha Surabhi, Ryan J McGinn, Charles Y Liu and 2 more

Abstract read
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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Xiecheng Shao *Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, 1200 N State Street, Suite 3300, Los Angeles, 90033, CA, USA.
Ryan S Chung *Department of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, 1200 N State Street, Suite 3300, Los Angeles, 90033, CA, USA. rschung@usc.edu.
Jonathon M CavaleriDepartment of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, 1200 N State Street, Suite 3300, Los Angeles, 90033, CA, USA.
Roberto Martin Del Campo-VeraDepartment of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, 1200 N State Street, Suite 3300, Los Angeles, 90033, CA, USA.
Miguel ParraDepartment of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, 1200 N State Street, Suite 3300, Los Angeles, 90033, CA, USA.
Shivani SundaramDepartment of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, 1200 N State Street, Suite 3300, Los Angeles, 90033, CA, USA.
Selena ZhangDepartment of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, 1200 N State Street, Suite 3300, Los Angeles, 90033, CA, USA.
Ashwitha SurabhiDepartment of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, 1200 N State Street, Suite 3300, Los Angeles, 90033, CA, USA.
Ryan J McGinnKeck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA.
Charles Y LiuDepartment of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, 1200 N State Street, Suite 3300, Los Angeles, 90033, CA, USA.
Spencer S KellisDepartment of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, 1200 N State Street, Suite 3300, Los Angeles, 90033, CA, USA.
Brian LeeDepartment of Neurological Surgery, Keck School of Medicine of USC, University of Southern California, 1200 N State Street, Suite 3300, Los Angeles, 90033, CA, USA.

Funding

Decoding / encoding somatosensation from the hand area of the human primary somatosensory (S1) cortex for a closed-loop motor / sensory brain-machine interface (BMI)K23NS114190 · NINDS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI LEE, BRIAN · 2020 to 2024
$950k
NINDS NIH HHS K23 NS114190
6 · The paper itself

Abstract

Motor BCIs, with the help of Artificial Intelligence (AI) and machine learning, have shown promise in decoding neural signals for restoring motor function. Structures beyond motor cortex have provided additional sources for movement signals. New evidence points to the role of the insula in motor control, specifically directional hand-movements. In this study, we applied AI and machine learning techniques to decode directional hand-movements from high-gamma band (70-200 Hz) activity in the insular cortex. Seven participants with medication-resistant epilepsy underwent stereo electroencephalographic (SEEG) implantation of depth electrodes for seizure monitoring in the insula. SEEG data were sampled throughout a cued motor task involving three conditions: left-hand movement, right-hand movement, or no movement. Neural signal processing focused on high-gamma band activity. Demixed Principal Component Analysis (dPCA) was used for dimension reduction (d = 10) and feature extraction from the time-frequency analysis. For movement classification, we implemented a bidirectional Long Short-Term Memory (LSTM) architecture with a single layer, utilizing the capacity to process temporal sequences in forward and back directions for optimal decoding of movement direction. Our findings revealed robust directional-specific high-gamma modulation within the insular cortex during motor execution. Temporal decomposition through dPCA demonstrated distinct spatiotemporal patterns of high-gamma activity across movement conditions. Subsequently, LSTM networks successfully decoded these condition-specific neural signatures, achieving a classification accuracy of 72.6% ± 13.0% (mean ± SD), which significantly exceeded chance-level performance of 33.3% (p < 0.0001, n = 16 sessions). Furthermore, we identified a strong negative correlation between temporal distance of training-testing sessions and decoding performance (r = -0.868, p < 0.0001), indicating temporal difference of the neural representations. Our study highlights the potential role of deep brain structures, such as the insula, in conditional movement discrimination. We demonstrate that LSTM networks and high-gamma band analysis can advance the understanding of neural mechanisms underlying movement. These insights may pave the way for improvements in SEEG-based BCI.

Indexed as

ElectroencephalographyGamma RhythmHandInsular CortexNeural Networks, ComputerAdultBrain-Computer InterfacesFemaleHumansMachine LearningMaleMiddle AgedMotor CortexMovementRecurrent Neural NetworksYoung AdultAIBCIInsulaInsular cortexNeural networksSEEG

Identifiers

PMID40819020
PMCPMC12357955

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

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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.