A general mechanism for tuning: Gain control circuits and synapses underlie tuning of cortical neurons

Abstract Tuning toanoptimal stimulus is a widespreadpropertyof neurons incortex. We propose that suchtuningis a consequence of normalization or gain control circuits. We also present a biologically plausible neuralcircuitry of tuning. Copyright c Massachusetts Institute of Technology, 2004This report describes research done at the Center for Biological & Computational Learning, which is in the McGovern Institutefor Brain Research at MIT, as well as in the Dept. of Brain & Cognitive Sciences, and which is affiliated with the ComputerSciences & Artificial Intelligence Laboratory (CSAIL).This research was sponsored by grants from: Office of Naval Research (DARPA) Contract No. MDA972-04-1-0037, Office ofNaval Research (DARPA) Contract No. N00014-02-1-0915, National Science Foundation (ITR/IM) Contract No. IIS-0085836,National Science Foundation (ITR/SYS) Contract No. IIS-0112991, National Science Foundation (ITR) Contract No. IIS-0209289,National Science Foundation-NIH (CRCNS) Contract No. EIA-0218693, National Science Foundation-NIH (CRCNS) ContractNo. EIA-0218506, and National Institutes of Health (Conte) Contract No. 1 P20 MH66239-01A1.Additional support was provided by: Central Research Institute of Electric Power Industry, Center for e-Business (MIT),Daimler-Chrysler AG, Compaq/Digital Equipment Corporation, Eastman Kodak Company, Honda R&D Co., Ltd., ITRI, Ko-matsuLtd.,EugeneMcDermottFoundation,Merrill-Lynch,MitsubishiCorporation,NECFund,NipponTelegraph&Telephone,Oxygen, Siemens Corporate Research, Inc., Sony MOU, Sumitomo Metal Industries, Toyota Motor Corporation, and WatchVi-sion Co., Ltd.

[1]  Gabriel Kreiman,et al.  Neural coding: computational and biophysical perspectives , 2004, Physics of Life Reviews.

[2]  Peter Dayan,et al.  Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems , 2001 .

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

[4]  T. Poggio,et al.  A synaptic mechanism possibly underlying directional selectivity to motion , 1978, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[5]  Tomaso Poggio,et al.  Generalization in vision and motor control , 2004, Nature.

[6]  H. Sompolinsky,et al.  Theory of orientation tuning in visual cortex. , 1995, Proceedings of the National Academy of Sciences of the United States of America.

[7]  N. Logothetis,et al.  Shape representation in the inferior temporal cortex of monkeys , 1995, Current Biology.

[8]  D. Heeger Modeling simple-cell direction selectivity with normalized, half-squared, linear operators. , 1993, Journal of neurophysiology.

[9]  C. Connor,et al.  Shape representation in area V4: position-specific tuning for boundary conformation. , 2001, Journal of neurophysiology.

[10]  Martin A. Giese,et al.  Biophysiologically Plausible Implementations of the Maximum Operation , 2002, Neural Computation.

[11]  Gilles Laurent,et al.  Transformation of Olfactory Representations in the Drosophila Antennal Lobe , 2004, Science.

[12]  J. Movshon,et al.  Nature and interaction of signals from the receptive field center and surround in macaque V1 neurons. , 2002, Journal of neurophysiology.

[13]  K. D. Punta,et al.  An ultra-sparse code underlies the generation of neural sequences in a songbird , 2002 .

[14]  M. Carandini,et al.  Summation and division by neurons in primate visual cortex. , 1994, Science.

[15]  S. Nelson,et al.  An emergent model of orientation selectivity in cat visual cortical simple cells , 1995, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[16]  Charles E Connor,et al.  Underlying principles of visual shape selectivity in posterior inferotemporal cortex , 2004, Nature Neuroscience.

[17]  Werner Reichardt,et al.  Figure-ground discrimination by relative movement in the visual system of the fly , 2004, Biological Cybernetics.

[18]  Dario L Ringach,et al.  Haphazard wiring of simple receptive fields and orientation columns in visual cortex. , 2004, Journal of neurophysiology.

[19]  T. Poggio,et al.  Hierarchical models of object recognition in cortex , 1999, Nature Neuroscience.

[20]  F. Girosi,et al.  A Connection Between GRBF and MLP , 1992 .

[21]  T. Poggio,et al.  How Visual Cortex Recognizes Objects: The Tale of the Standard Model , 2002 .

[22]  T Poggio,et al.  Regularization Algorithms for Learning That Are Equivalent to Multilayer Networks , 1990, Science.

[23]  Keiji Tanaka,et al.  Neuronal selectivities to complex object features in the ventral visual pathway of the macaque cerebral cortex. , 1994, Journal of neurophysiology.

[24]  Eero P. Simoncelli,et al.  Natural signal statistics and sensory gain control , 2001, Nature Neuroscience.

[25]  D. C. Essen,et al.  Neural responses to polar, hyperbolic, and Cartesian gratings in area V4 of the macaque monkey. , 1996, Journal of neurophysiology.

[26]  D. Ferster,et al.  Neural mechanisms of orientation selectivity in the visual cortex. , 2000, Annual review of neuroscience.