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Anticipatory grasping control modulates somatosensory perception.
Dimitris Voudouris1, Maximilian Davide Broda1, Katja Fiehler1
1Experimental Psychology, Justus-Liebig University Giessen, Germany.
Journal of Vision
|May 7, 2019
Summary
Predicting object features during movement enhances sensory suppression. This means your brain tunes out touch sensations more when it anticipates what will happen during a goal-directed action.
Area of Science:
- Neuroscience
- Motor Control
- Sensory Perception
Background:
- Somatosensory perception is reduced during limb movement, often explained by internal forward models predicting sensory consequences of motor commands.
- The influence of object predictability on this sensory suppression during grasping is not well understood.
Purpose of the Study:
- To investigate how the predictability of object features modulates somatosensory suppression during a goal-directed grasping movement.
- To determine if anticipating object properties affects the brain's ability to process tactile information during manipulation.
Main Methods:
- Participants performed a reach-and-grasp task with objects having predictable (blocked) or unpredictable (random) mass distributions.
- Vibrotactile stimuli were applied to the index finger during object contact, and detection rates were recorded.
- Grasping configurations and subsequent object roll were analyzed to assess movement control.
Main Results:
- Predictable object mass distributions led to modulated grasping, minimizing object roll.
- Unpredictable distributions resulted in default grasping and increased object roll for asymmetric masses.
- Somatosensory suppression was significantly stronger when object features were predictable compared to unpredictable.
Conclusions:
- The predictability of movement-relevant object features modulates somatosensory suppression during goal-directed actions.
- Anticipating object properties enhances the brain's filtering of sensory information, suggesting a predictive coding mechanism.
- This finding has implications for understanding sensorimotor integration and adaptive motor control.
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