Visual target and task-critical feedback uncertainty impair different stages of reach planning in motor cortex

Sensory uncertainty jeopardizes accurate movement. During reaching, visual uncertainty can affect the estimation of hand position (feedback) and the desired movement endpoint (target). While impairing motor learning, it is unclear how either form of uncertainty affects cortical reach goal encoding. We show that reach trajectories vary more with higher visual uncertainty of the target, but not the feedback. Accordingly, cortical motor goal activities in male rhesus monkeys are less accurate during planning and movement initiation under target but not feedback uncertainty. Yet, when monkeys critically depend on visual feedback to conduct reaches via a brain-computer interface, then visual feedback uncertainty impairs reach accuracy and neural motor goal encoding around movement initiation. Neural state space analyses reveal a dimension that separates population activity by uncertainty level in all tested conditions. Our findings demonstrate that while both target and feedback uncertainty always reflect in neural activity, uncertain feedback only deteriorates neural reach goal information and behavior when it is task-critical, i.e., when having to rely on the sensory feedback and no other more reliable sensory modalities are available. Further, uncertain target and feedback impair reach goal encoding in a time-dependent manner, suggesting that they are integrated during different stages of reach planning.

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Publication Details

Journal
Nature Communications
Published
2025-04-09
DOI
https://doi.org/10.1038/s41467-025-58738-x
Citations
4
Primary Topic
EEG and Brain-Computer Interfaces
Type
article
Field-Weighted Citation Impact
5.72

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article

Visual target and task-critical feedback uncertainty impair different stages of reach planning in motor cortex

Alexander Gail, Virginia Casasnovas, Lukas K Amann
4 citations
Nature Communications
EEG and Brain-Computer Interfaces
5.72
article

Visual target and task-critical feedback uncertainty impair different stages of reach planning in motor cortex

Alexander Gail, Virginia Casasnovas, Lukas K Amann
article en
4 citations

Abstract

Sensory uncertainty jeopardizes accurate movement. During reaching, visual uncertainty can affect the estimation of hand position (feedback) and the desired movement endpoint (target). While impairing motor learning, it is unclear how either form of uncertainty affects cortical reach goal encoding. We show that reach trajectories vary more with higher visual uncertainty of the target, but not the feedback. Accordingly, cortical motor goal activities in male rhesus monkeys are less accurate during planning and movement initiation under target but not feedback uncertainty. Yet, when monkeys critically depend on visual feedback to conduct reaches via a brain-computer interface, then visual feedback uncertainty impairs reach accuracy and neural motor goal encoding around movement initiation. Neural state space analyses reveal a dimension that separates population activity by uncertainty level in all tested conditions. Our findings demonstrate that while both target and feedback uncertainty always reflect in neural activity, uncertain feedback only deteriorates neural reach goal information and behavior when it is task-critical, i.e., when having to rely on the sensory feedback and no other more reliable sensory modalities are available. Further, uncertain target and feedback impair reach goal encoding in a time-dependent manner, suggesting that they are integrated during different stages of reach planning.

Nature CommunicationsVol. 16(1)
German Primate Center (DE), Bernstein Center for Computational Neuroscience Göttingen (DE), Gesellschaft für wissenschaftliche Datenverarbeitung mbH Göttingen (DE), Leibniz ScienceCampus Primate Cognition (DE), University of Göttingen (DE)
Niedersächsische Ministerium für Wissenschaft und Kultur, European Commission, Deutsche Forschungsgemeinschaft, Horizon 2020 Framework Programme
Climate action
Openalex Percentile: Top 4%
EEG and Brain-Computer Interfaces
5.72
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