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Related Experiment Videos

Gain mechanisms for contextually guided visuomotor transformations.

Marina Brozović1, Alexander Gail, Richard A Andersen

  • 1Division of Biology, California Institute of Technology, Pasadena, California 91125, USA. brozovic@vis.caltech.edu

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
|September 28, 2007
PubMed
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Neural network models reveal how context influences sensorimotor decisions. Top-down feedback mechanisms in neural networks are crucial for context-specific motor planning, potentially explaining parietal cortex activity.

Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Cognitive Science

Background:

  • Sensorimotor research investigates integrating sensory input with behavioral rules (contexts) for motor actions.
  • Understanding how context influences visuomotor transformations is key to explaining decision-making processes.

Purpose of the Study:

  • To investigate context-specific visuomotor remapping using neural network models.
  • To explore the role of functional connectivity and context signal propagation (bottom-up vs. top-down) in sensorimotor integration.

Main Methods:

  • Developed two neural network models trained on context-dependent visuomotor associations (rotational transformations based on stimulus color).
  • Network I utilized bottom-up context signal propagation; Network II used top-down feedback.

Related Experiment Videos

  • Simulated multimodal integration over time using recurrent hidden layers.

    • Main Results:

    • Both networks integrated context and sensory information via a gain-field-like mechanism.
    • Network I showed context-modulated memory for visuomotor transformations.
    • Network II exhibited a rapid shift from sensory response to context-modulated motor-goal representation due to top-down feedback.

    Conclusions:

    • Top-down feedback plays a significant role in establishing context-modulated motor-goal representations.
    • The origin of context information is not strictly tied to top-down feedback.
    • Strong top-down feedback may explain motor-goal representations in the parietal cortex during context-specific planning.