A common stochastic accumulator with effector-dependent noise can explain eye-hand coordination

Area of Science:

• Neuroscience
• Cognitive Science
• Computational Neuroscience

Background:

• The neural mechanisms for flexible eye-hand coordination remain unclear.
• Understanding how independent motor systems are coupled is crucial for explaining complex behaviors.

Purpose of the Study:

• To investigate the computational architecture underlying eye-hand coordination.
• To test if a common stochastic accumulator model can explain reaction time distributions in coupled eye-hand movements.

Main Methods:

• Utilized a drift diffusion framework to analyze reaction time (RT) distributions.
• Combined behavioral experiments, computational modeling, and electromyography (EMG).
• Compared a common accumulator model against independent accumulator models.

Main Results:

• A single stochastic accumulator with noisy, effector-dependent delays successfully explained eye-hand coordination.
• This model did not account for RT distributions during isolated eye or hand movements.
• Independent, interactive accumulator models failed to explain the observed eye-hand coordination.

Conclusions:

• Data suggest a dedicated neural circuit for coordinated eye-hand planning.
• The findings challenge models assuming independent processing for coupled movements.
• This provides a novel computational framework for understanding sensorimotor integration.