Neural geometry from mixed sensorimotor selectivity for predictive sensorimotor control
Although recent studies suggest that activity in the motor cortex, in addition to generating motor outputs, receives substantial information regarding sensory inputs, it is still unclear how sensory context adjusts the motor commands. Here, we recorded population neural activity in the motor cortex...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
eLife Sciences Publications Ltd
2025-05-01
|
| Series: | eLife |
| Subjects: | |
| Online Access: | https://elifesciences.org/articles/100064 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849314564718460928 |
|---|---|
| author | Yiheng Zhang Yun Chen Tianwei Wang He Cui |
| author_facet | Yiheng Zhang Yun Chen Tianwei Wang He Cui |
| author_sort | Yiheng Zhang |
| collection | DOAJ |
| description | Although recent studies suggest that activity in the motor cortex, in addition to generating motor outputs, receives substantial information regarding sensory inputs, it is still unclear how sensory context adjusts the motor commands. Here, we recorded population neural activity in the motor cortex via microelectrode arrays while monkeys performed flexible manual interceptions of moving targets. During this task, which requires predictive sensorimotor control, the activity of most neurons in the motor cortex encoding upcoming movements was influenced by ongoing target motion. Single-trial neural states at the movement onset formed staggered orbital geometries, suggesting that target motion modulates peri-movement activity in an orthogonal manner. This neural geometry was further evaluated with a representational model and recurrent neural networks (RNNs) with task-specific input-output mapping. We propose that the sensorimotor dynamics can be derived from neuronal mixed sensorimotor selectivity and dynamic interaction between modulations. |
| format | Article |
| id | doaj-art-5eaeaaef924b4b61bbc6a908773b2a87 |
| institution | Kabale University |
| issn | 2050-084X |
| language | English |
| publishDate | 2025-05-01 |
| publisher | eLife Sciences Publications Ltd |
| record_format | Article |
| series | eLife |
| spelling | doaj-art-5eaeaaef924b4b61bbc6a908773b2a872025-08-20T03:52:25ZengeLife Sciences Publications LtdeLife2050-084X2025-05-011310.7554/eLife.100064Neural geometry from mixed sensorimotor selectivity for predictive sensorimotor controlYiheng Zhang0https://orcid.org/0000-0002-5370-1316Yun Chen1https://orcid.org/0000-0002-0817-2160Tianwei Wang2https://orcid.org/0000-0002-5192-5594He Cui3https://orcid.org/0000-0001-6277-9804Center for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China; Chinese Institute for Brain Research, Beijing, China; University of Chinese Academy of Sciences, Beijing, ChinaCenter for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China; Chinese Institute for Brain Research, Beijing, China; University of Chinese Academy of Sciences, Beijing, ChinaCenter for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China; Chinese Institute for Brain Research, Beijing, ChinaCenter for Excellence in Brain Science and Intelligence Technology, Institute of Neuroscience, Chinese Academy of Sciences, Shanghai, China; Chinese Institute for Brain Research, Beijing, ChinaAlthough recent studies suggest that activity in the motor cortex, in addition to generating motor outputs, receives substantial information regarding sensory inputs, it is still unclear how sensory context adjusts the motor commands. Here, we recorded population neural activity in the motor cortex via microelectrode arrays while monkeys performed flexible manual interceptions of moving targets. During this task, which requires predictive sensorimotor control, the activity of most neurons in the motor cortex encoding upcoming movements was influenced by ongoing target motion. Single-trial neural states at the movement onset formed staggered orbital geometries, suggesting that target motion modulates peri-movement activity in an orthogonal manner. This neural geometry was further evaluated with a representational model and recurrent neural networks (RNNs) with task-specific input-output mapping. We propose that the sensorimotor dynamics can be derived from neuronal mixed sensorimotor selectivity and dynamic interaction between modulations.https://elifesciences.org/articles/100064neural codingmanual interceptionmulti-channel recordingmonkeyreachneural dynamics |
| spellingShingle | Yiheng Zhang Yun Chen Tianwei Wang He Cui Neural geometry from mixed sensorimotor selectivity for predictive sensorimotor control eLife neural coding manual interception multi-channel recording monkey reach neural dynamics |
| title | Neural geometry from mixed sensorimotor selectivity for predictive sensorimotor control |
| title_full | Neural geometry from mixed sensorimotor selectivity for predictive sensorimotor control |
| title_fullStr | Neural geometry from mixed sensorimotor selectivity for predictive sensorimotor control |
| title_full_unstemmed | Neural geometry from mixed sensorimotor selectivity for predictive sensorimotor control |
| title_short | Neural geometry from mixed sensorimotor selectivity for predictive sensorimotor control |
| title_sort | neural geometry from mixed sensorimotor selectivity for predictive sensorimotor control |
| topic | neural coding manual interception multi-channel recording monkey reach neural dynamics |
| url | https://elifesciences.org/articles/100064 |
| work_keys_str_mv | AT yihengzhang neuralgeometryfrommixedsensorimotorselectivityforpredictivesensorimotorcontrol AT yunchen neuralgeometryfrommixedsensorimotorselectivityforpredictivesensorimotorcontrol AT tianweiwang neuralgeometryfrommixedsensorimotorselectivityforpredictivesensorimotorcontrol AT hecui neuralgeometryfrommixedsensorimotorselectivityforpredictivesensorimotorcontrol |