Joint development of disparity tuning and vergence control

Behavior and sensory perception are mutually dependent. Sensory perception drives behavior, but behavior can also influence the development of sensory perception, by altering the statistics of the sensory input. Thus, there is a “chicken-and-egg” problem as to which arises first. We propose here a solution to this problem in the context of the neural processing of binocular disparity and the behavioral control of binocular vergence to maintain fixation. We show that it is possible for both the neural processing and the control policy to develop simultaneously. In particular, we assume that the neural processing develops through learning a sparse complex-cell representation of the input, and that the control policy simultaneously develops through reinforcement learning to maximize the activity in this complex cell representation. These processes are coupled. The control policy determines the statistics of the input, which determines the sparse coding that develops, which in turn determines the reward maximized by the control policy. Our experiments show that both disparity selective binocular receptive fields and a successful binocular fixation policy develop. Our results underline the importance of behavior, as we show that on the same input but in the absence of learned behavior, much fewer disparity selective binocular receptive fields develop.

[1]  David J. Fleet,et al.  Neural encoding of binocular disparity: Energy models, position shifts and phase shifts , 1996, Vision Research.

[2]  F. A. Miles,et al.  Vergence eye movements in response to binocular disparity without depth perception , 1997, Nature.

[3]  Aapo Hyvärinen,et al.  A two-layer sparse coding model learns simple and complex cell receptive fields and topography from natural images , 2001, Vision Research.

[4]  Bertram E. Shi,et al.  Autonomous Development of Vergence Control Driven by Disparity Energy Neuron Populations , 2010, Neural Computation.

[5]  H. Sakata,et al.  Integration of perspective and disparity cues in surface-orientation-selective neurons of area CIP. , 2001, Journal of neurophysiology.

[6]  Ning Qian,et al.  Computing Stereo Disparity and Motion with Known Binocular Cell Properties , 1994, Neural Computation.

[7]  J. Triesch,et al.  Emergence of Disparity Tuning during the Development of Vergence Eye Movements , 2007, 2007 IEEE 6th International Conference on Development and Learning.

[8]  David J. Field,et al.  Sparse coding with an overcomplete basis set: A strategy employed by V1? , 1997, Vision Research.

[9]  Erkki Oja,et al.  Independent component analysis: algorithms and applications , 2000, Neural Networks.

[10]  Pieter R. Roelfsema,et al.  Attention-Gated Reinforcement Learning of Internal Representations for Classification , 2005, Neural Computation.

[11]  K. N. Ogle Researches in binocular vision. , 1950 .

[12]  Bertram E. Shi,et al.  Disparity Estimation by Pooling Evidence From Energy Neurons , 2009, IEEE Transactions on Neural Networks.

[13]  D. G. Albrecht,et al.  Motion selectivity and the contrast-response function of simple cells in the visual cortex , 1991, Visual Neuroscience.

[14]  D. Hubel,et al.  Binocular interaction in striate cortex of kittens reared with artificial squint. , 1965, Journal of neurophysiology.

[15]  Robert A. Jacobs,et al.  Developmental Constraints Aid the Acquisition of Binocular Disparity Sensitivities , 2003, Neural Computation.

[16]  Bertram E. Shi,et al.  Improved Binocular Vergence Control via a Neural Network That Maximizes an Internally Defined Reward , 2011, IEEE Transactions on Autonomous Mental Development.

[17]  David J. Field,et al.  Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.

[18]  J. Movshon,et al.  Linearity and Normalization in Simple Cells of the Macaque Primary Visual Cortex , 1997, The Journal of Neuroscience.

[19]  Jean-Baptiste Durand,et al.  Neural bases of stereopsis across visual field of the alert macaque monkey. , 2007, Cerebral cortex.

[20]  D. Heeger Normalization of cell responses in cat striate cortex , 1992, Visual Neuroscience.

[21]  R. Held,et al.  MOVEMENT-PRODUCED STIMULATION IN THE DEVELOPMENT OF VISUALLY GUIDED BEHAVIOR. , 1963, Journal of comparative and physiological psychology.

[22]  I. Ohzawa,et al.  Stereoscopic depth discrimination in the visual cortex: neurons ideally suited as disparity detectors. , 1990, Science.