1. Sensorimotor Learning and the Development of Position Invariance
Muhua Li and James J. Clark
Biological: the position invariance property of many higher-level visual cortex neurons.
Theoretical: the sensorimotor contingency theory of O’Regan and Noe [1] which holds that perception is based on the laws relating motor activity and the resulting sensory input.
Motivation
Learning Procedure
Simulation Results
Our techniques are applied to the invariant representation of images of straight lines. The projection of straight lines in space onto the spherical retinal surface will form 2D curvatures that vary with eccentricity.
Main Idea
The position invariance recognition can be achieved by learning the sensorimotor contingencies associated with neural responses from the lower-level feature detectors.
In cases with a 10% undershooting probability in the training data:
Without feedback, the estimated canonical images associate the undershot stimuli as well as the foveal stimuli with the input peripheral feature stimuli.
With feedback, the network is able to discard the disturbance from the undershot stimuli and make the correct association.
A TD reinforcement learning algorithm [2] can learn the sensorimotor contingencies associated with saccadic eye movements.
Once the association matrix V has been learned, the response of the network given a peripherally located stimulus P is a prediction M (the estimated canonical image) of what the corresponding foveal stimulus would look like:
Temporal Difference (TD) Learning Algorithm
Enhanced Algorithm
A feedback from the higher-level layer is used to handle cases where the saccade does not succeed in foveating the target, but instead undershoots the target, at which point a small corrective saccade is made.
Position invariance of higher-level cortical neurons may arise from a learning of sensorimotor contingencies.
A TD network as we propose here is able to perform such learning, and generate the estimated canonical response as would occur after foveation of a physical stimuli from the activities of the lower-level visual feature detectors.
Conclusion
Basic Learning Rules
V is the association matrix relating pre- and post-saccadic stimuli. is the foveal stimuli (post-motor) as the reinforcement reward. The pre-motor stimulus X is held in a short-term memory generating an eligibility trace , which will be used to enhance, in a Hebbian fashion, the association to the post-motor stimulus.
References
[1] O’Regan, J.K. and Noe, A. “A sensorimotor account of vision and visual consciousness”, submitted to Behavioral and Brain Sciences.
[2] Clark, J.J. “Sensorimotor development of position invarianct feature detectors”, ICPR2002
The reinforcement reward is composed of both the post-saccade stimulus and its estimated canonical image, which are weighted by a confidence: