Stability analysis of a neural field self-organizing map

We provide theoretical conditions guaranteeing that a self-organizing map efficiently develops representations of the input space. The study relies on a neural field model of spatiotemporal activity in area 3b of the primary somatosensory cortex. We rely on Lyapunov’s theory for neural fields to derive theoretical conditions for stability. We verify the theoretical conditions by numerical experiments. The analysis highlights the key role played by the balance between excitation and inhibition of lateral synaptic coupling and the strength of synaptic gains in the formation and maintenance of self-organizing maps.

[1]  Olivier D. Faugeras,et al.  Local/Global Analysis of the Stationary Solutions of Some Neural Field Equations , 2009, SIAM J. Appl. Dyn. Syst..

[2]  Olivier D. Faugeras,et al.  Hebbian Learning of Recurrent Connections: A Geometrical Perspective , 2012, Neural Computation.

[3]  Nicolas P. Rougier,et al.  A Neural Field Model of the Somatosensory Cortex: Formation, Maintenance and Reorganization of Ordered Topographic Maps , 2012, PloS one.

[4]  W. Tabbara,et al.  Laboratoire des Signaux et Systsmes , 1984 .

[5]  S. Amari Dynamics of pattern formation in lateral-inhibition type neural fields , 1977, Biological Cybernetics.

[6]  M. V. Velzen,et al.  Self-organizing maps , 2007 .

[7]  E. Oja Simplified neuron model as a principal component analyzer , 1982, Journal of mathematical biology.

[8]  P. Demartines Organization Measures and Representations of the Kohonen Maps , 1992 .

[9]  Marco Raugi,et al.  Stability analysis of self-organizing maps and vector quantization algorithms , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

[10]  Tony J. Prescott,et al.  Modeling the Emergence of Whisker Direction Maps in Rat Barrel Cortex , 2010, PloS one.

[11]  T. Kohonen Self-organized formation of topographically correct feature maps , 1982 .

[12]  P. Bressloff Spatiotemporal dynamics of continuum neural fields , 2012 .

[13]  Nasser M. Nasrabadi,et al.  Vector quantization of images based upon the Kohonen self-organizing feature maps , 1988, IEEE 1988 International Conference on Neural Networks.

[14]  Pierre-Antoine Absil,et al.  Principal Manifolds for Data Visualization and Dimension Reduction , 2007 .

[15]  Yann Boniface,et al.  Dynamic self-organising map , 2011, Neurocomputing.

[16]  L. Abbott,et al.  Synaptic plasticity: taming the beast , 2000, Nature Neuroscience.

[17]  J. Knott The organization of behavior: A neuropsychological theory , 1951 .

[18]  P. Olver Nonlinear Systems , 2013 .

[19]  Hans-Jochen Heinze,et al.  Task-relevant modulation of primary somatosensory cortex suggests a prefrontal–cortical sensory gating system , 2005, NeuroImage.

[20]  Nicolas P. Rougier,et al.  Structure of receptive fields in a computational model of area 3b of primary sensory cortex , 2014, Front. Comput. Neurosci..

[21]  Olivier D. Faugeras,et al.  Persistent Neural States: Stationary Localized Activity Patterns in Nonlinear Continuous n-Population, q-Dimensional Neural Networks , 2009, Neural Computation.

[22]  M. Abramowitz,et al.  Handbook of Mathematical Functions With Formulas, Graphs and Mathematical Tables (National Bureau of Standards Applied Mathematics Series No. 55) , 1965 .

[23]  Todd M. Preuss,et al.  Somatosensory Areas of the Cerebral Cortex: Architectonic Characteristics and Modular Organization , 2008 .

[24]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[25]  Adrienne L Fairhall,et al.  Emergence of Adaptive Computation by Single Neurons in the Developing Cortex , 2013, The Journal of Neuroscience.

[26]  Michael Merzenich,et al.  Neural Network Simulation of Somatosensory Representational Plasticity , 1989, NIPS.

[27]  Olivier D. Faugeras,et al.  Absolute Stability and Complete Synchronization in a Class of Neural Fields Models , 2008, SIAM J. Appl. Math..

[28]  Stephen Coombes,et al.  Waves, bumps, and patterns in neural field theories , 2005, Biological Cybernetics.

[29]  G. Gerstein,et al.  Networks with lateral connectivity. III. Plasticity and reorganization of somatosensory cortex. , 1996, Journal of neurophysiology.

[30]  Risto Miikkulainen,et al.  Ocular Dominance and Patterned Lateral Connections in a Self-Organizing Model of the Primary Visual Cortex , 1994, NIPS.

[31]  T. Kohonen,et al.  Bibliography of Self-Organizing Map SOM) Papers: 1998-2001 Addendum , 2003 .

[32]  Teuvo Kohonen,et al.  Self-organized formation of topologically correct feature maps , 2004, Biological Cybernetics.

[33]  G. Gerstein,et al.  Networks with lateral connectivity. II. Development of neuronal grouping and corresponding receptive field changes. , 1996, Journal of neurophysiology.

[34]  Risto Miikkulainen,et al.  Computational Maps in the Visual Cortex , 2005 .

[35]  R. Knight,et al.  Prefrontal cortex regulates inhibition and excitation in distributed neural networks. , 1999, Acta psychologica.

[36]  L A Krubitzer,et al.  The organization and connections of somatosensory cortex in marmosets , 1990, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[37]  G. Gerstein,et al.  Networks with lateral connectivity. I. dynamic properties mediated by the balance of intrinsic excitation and inhibition. , 1996, Journal of neurophysiology.

[38]  Teuvo Kohonen,et al.  Physiological interpretation of the Self-Organizing Map algorithm , 1993, Neural Networks.

[39]  Hujun Yin,et al.  Learning Nonlinear Principal Manifolds by Self-Organising Maps , 2008 .

[40]  Samuel Kaski,et al.  Bibliography of Self-Organizing Map (SOM) Papers: 1981-1997 , 1998 .

[41]  Klaus Schulten,et al.  Self-organizing maps: ordering, convergence properties and energy functions , 1992, Biological Cybernetics.