Simulating the cortical 3D visuomotor transformation of reach depth

We effortlessly perform reach movements to objects in different directions and depths. However, how networks of cortical neurons compute reach depth from binocular visual inputs remains largely unknown. To bridge the gap between behavior and neurophysiology, we trained a feed-forward artificial neur...

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Bibliographic Details
Published in:PloS one 2012-07, Vol.7 (7), p.e41241-e41241
Main Author: Blohm, Gunnar
Format: Article
Language:English
Subjects:
Artificial neural networks
Binocular vision
Biology
Coding
Computer Science
Computer Simulation
Cortex (parietal)
Engineering
Eye
Frontal Lobe
Humans
Imaging, Three-Dimensional
Medicine
Models, Neurological
Models, Theoretical
Monkeys & apes
Movement - physiology
Neural coding
Neural networks
Neural Networks (Computer)
Neurons
Neurons - physiology
Neurophysiology
Neurophysiology - methods
Object motion
Parietal Lobe - physiology
Psychomotor Performance - physiology
Retina - physiology
Sensorimotor integration
Transformation
Vergence eye movements
Vision, Ocular - physiology
Visual cortex
Visual signals
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Summary:We effortlessly perform reach movements to objects in different directions and depths. However, how networks of cortical neurons compute reach depth from binocular visual inputs remains largely unknown. To bridge the gap between behavior and neurophysiology, we trained a feed-forward artificial neural network to uncover potential mechanisms that might underlie the 3D transformation of reach depth. Our physiologically-inspired 4-layer network receives distributed 3D visual inputs (1(st) layer) along with eye, head and vergence signals. The desired motor plan was coded in a population (3(rd) layer) that we read out (4(th) layer) using an optimal linear estimator. After training, our network was able to reproduce all known single-unit recording evidence on depth coding in the parietal cortex. Network analyses predict the presence of eye/head and vergence changes of depth tuning, pointing towards a gain-modulation mechanism of depth transformation. In addition, reach depth was computed directly from eye-centered (relative) visual distances, without explicit absolute depth coding. We suggest that these effects should be observable in parietal and pre-motor areas.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0041241