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Does the sensorimotor system minimize prediction error or select the most likely prediction during object lifting?

Joshua G A Cashaback¹, Heather R McGregor^2,3, Henry C H Pun⁴

¹Brain and Mind Institute, Department of Psychology, Western University, London, Ontario, Canada; cashabackjga@gmail.com.

Journal of Neurophysiology

|October 21, 2016

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The human sensorimotor system predicts object weight by minimizing squared errors, not by choosing the most likely weight. This strategy ensures efficient lifting and prevents dropping, even with uncertain object weights.

Area of Science:

Neuroscience
Biomechanics
Human motor control

Background:

Accurate weight prediction is crucial for efficient and safe object manipulation.
Weight uncertainty and sparse sensory cues challenge the sensorimotor system's predictive capabilities.

Purpose of the Study:

To investigate the strategies the sensorimotor system employs for weight prediction under uncertainty.
To differentiate between minimizing prediction error and selecting the most probable weight.

Main Methods:

Developed a novel experimental model for object lifting with variable weights.
Utilized a skewed probability distribution to dissociate prediction strategies.
Analyzed sensorimotor prediction indexes including grip force and load force.

Keywords:

Bayesian feedforward control fingertip force object lifting prediction

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Main Results:

Sensorimotor predictions were consistent with a feedforward strategy minimizing the square of prediction errors.
This finding held across multiple sensorimotor indexes (grip force rate, grip force, load force rate, load force).

Conclusions:

The sensorimotor system employs a minimal squared error strategy for object weight prediction.
This finding suggests overlapping neural mechanisms between sensorimotor and visuomotor control systems.