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Two models for transforming auditory signals from head-centered to eye-centered coordinates.
1Institute of Neurological Sciences, University of Pennsylvania, Philadelphia 19104.
Biological Cybernetics
|January 1, 1992
Summary
Two computational models transform auditory signals from head-centered to eye-centered coordinates. These models simulate neural processing in the primate superior colliculus for spatial awareness.
Area of Science:
- Neuroscience
- Computational Neuroscience
- Auditory Processing
Background:
- The brain must transform sensory information into a usable coordinate system for action.
- Understanding how auditory spatial information is remapped to eye-centered coordinates is crucial for explaining sensorimotor control.
- The primate superior colliculus contains a topographic map of auditory space in eye-centered coordinates.
Purpose of the Study:
- To present two novel computational models for transforming auditory signals from head-centered to eye-centered reference frames.
- To elucidate the neural mechanisms underlying auditory spatial remapping.
- To provide a framework for understanding visual-to-head-centered coordinate transformations.
Main Methods:
- Vector subtraction model: Subtracts eye position signal from auditory target signal.
- Dendrite model: Maps head-centered auditory space onto eye-centered dendritic units.
- Both models utilize rate-coding and place-coding principles with synaptic weighting and inhibition.
Main Results:
- Both models successfully generate a topographic map of auditory space in eye-centered coordinates.
- The models replicate key features of neural representations found in the primate superior colliculus.
- The proposed models offer plausible mechanisms for auditory spatial remapping.
Conclusions:
- The vector subtraction and dendrite models provide viable computational explanations for auditory-to-eye-centered coordinate transformations.
- These models contribute to our understanding of neural representations in sensorimotor systems.
- The models can be adapted to explain visual spatial transformations.