Interactively Integrating Reach and Grasp Information in Macaque Premotor Cortex.
10.1007/s12264-025-01430-3
- Author:
Junjun CHEN
1
;
Guanghao SUN
1
;
Yiwei ZHANG
1
;
Weidong CHEN
1
;
Xiaoxiang ZHENG
1
;
Shaomin ZHANG
2
;
Yaoyao HAO
3
Author Information
1. Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, 310027, China.
2. Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, 310027, China. shaomin@zju.edu.cn.
3. Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, 310027, China. yaoyaoh@zju.edu.cn.
- Publication Type:Journal Article
- Keywords:
Canonical correlation analysis;
Dorsal premotor cortex;
Interactive encoding;
Macaque monkey;
Motor planning;
Reach-to-grasp
- MeSH:
Animals;
Motor Cortex/physiology*;
Hand Strength/physiology*;
Macaca mulatta;
Psychomotor Performance/physiology*;
Neurons/physiology*;
Male;
Cues;
Movement/physiology*;
Gestures
- From:
Neuroscience Bulletin
2025;41(11):1991-2009
- CountryChina
- Language:English
-
Abstract:
Reach-to-grasp movements require integrating information on both object location and grip type, but how these elements are planned and to what extent they interact remains unclear. We designed a new experimental paradigm in which monkeys sequentially received reach and grasp cues with delays, requiring them to retain and integrate both cues to grasp the goal object with appropriate hand gestures. Neural activity in the dorsal premotor cortex (PMd) revealed that reach and grasp were similarly represented yet not independent. Upon receiving the second cue, the PMd continued encoding the first, but over half of the neurons displayed incongruent modulations: enhanced, attenuated, or even reversed. Population-level analysis showed significant changes in encoding structure, forming distinct neural patterns. Leveraging canonical correlation analysis, we identified a shared subspace preserving the initial cue's encoding, contributed by both congruent and incongruent neurons. Together, these findings reveal a novel perspective on the interactive planning of reach and grasp within the PMd, providing insights into potential applications for brain-machine interfaces.
