Gerhard Werner
David DeMaris

Course Information
WebCT  (Forums, Calendar, etc.)

Essay:  Computation in Nervous Systems   G. Werner

General resources for indpendent study or selected assignments:
M.A. Arbib et al: The Handbook of Brain Theory and Neural Networks (Reserve in Life Sci)
M. Arbib, P Erdi &J. Szentagothai: Structure, Function and Dynamics: an integrated approach to Neural Organization,  (1997)   (Reserve in Life Sci)

Theoretical Neuroscience : Abbot & Dayan
Neuro science Glossary

An Online course in dynamics:  Sprott
Nonlinear Dynamics FAQ

What is Connectionism: Berkeley
 A Brief History of Connectionism: Medler  (Good info; broken diagrams & equations)

A primer on Information Theory
 An Online Course in Information Theory
Algorithmic Information Theory: Szabo

Section I:   Fundamental Concepts  in Neuroscience, Computation, and Dynamics.  Timelines in Neuroscience, Neural Computation, Psychology

Aug 31   Course Overview;  History;  Space and Time Scales in the Brain
    Slides (.pdf)    Scale Issues in Brain Science       Roots of the Digital Brain

Readings Group 1
    P.A. Getting: Emerging principles governing the operations of neural networks, Ann. Rev. Neurosci. 12:185-204, 1989
    Knudsen et al.  Computational Maps in the Brain, Ann. Rev. of Neurosci., 10:41-65, 1987
    Serra, R. and Zanarini, G.  Complex Systems and Cognitive Processes Ch. 2

Sept 5   Fundamentals of Neuroscience Review with Pictures
   Slides (.pdf)  Intro Neuroscience   This is a list of the contents of Dr. Werner's slides, not the actual slides.  We may scan selected slides.
Sept 7   Computational Maps;   Neural Networks Intro
    Discussion of Knudsen et. al.
Sept 9 Neural Networks and Rate Coding; Attractors; Entropy
    Slides   Neural Networks Overview      Entropy: Classical Information Theory
Sept 12  Mapping in the Brain
    Discussion of Knudsen
Sept 14 Biological Complexity:  Principles governing biological neural networks
    Discussion of Getting;  some ideas of emergent function
Sept 19  Contrasting dynamical and symbolic approaches to cognition;  Neural Code
Serra  and Zanarini continued;  begin Abott Sejnowski

Readings Group 2
Abbott, L. and Sejnowski, T.J.   Introduction: Neural Codes and Distributed Representations, MIT Press 1999
Miller, K.D. Models of activity dependent neural development, in van Pelt, J., Corner, M.A. Uylings, H.B.M, lopes da Silva F.H. (eds.)
     Progress in Brain Research v. 102, Elsevier Science, 1994
Nicolis G.  Physics of far-from-equilibrium systems and self organization. in  Davies, P.  The New Physics, 1988
van Gelder, T. and Port, R.  It's About Time: An overview of the dynamical approach to cognition  Introduction to Mind as Motion,
    Cambridge: MIT Press 1995
Clark A.  The Dynamical Challenge  Cognitive Science 21: 461-481, 1997
Rueger, A.  and Sharp, W. D.  Simple Theories of a Messy World:  Truth and Explanatory Power in Nonlinear Dynamics,  Brit. J. Phil. Sci. 47, 93-112, 1996

Sept 21 Neural Code;  Relevance of Shannon Information Theory concepts
    Abbot & Sejnowski;
Sept 26  Development of neural maps;  Nonequilibrium Systems
    Miller; begin Nicolis
Sept 28  Nonlinear Dynamics and Pattern Formation
    Finish Nicolis:  Pattern Formation Demos
Oct 3  Dynamical Psychology
  Clark , Van Gelder and Port
Oct 5
  Slides (.pdf)  Psychology Timeline      Related Links
Oct 10   Dynamical Psychology and some philosophical issues
   Van Gelder and Port,  Rueger,  and Sharp

Readings Group 3
Aertsen, A. Erb, M. Palm, G. Dynamics of functional coupling in the cerebral cortex: an attempt at model based interpretation
    Phsica D 75: 103-128
Freeman, W. J. .Qualitative overview of population neurodynamics.  in  Neural Networks and Neural Modeling.
     F. Ventriglia. New York, Pergamon: 185-216, 1994
Skarda C., Freeman, W. J.  How brains make chaos in order to make sense of the world, Behavioral
   and Brain Sciences 10,  pp. 161-195, 1987
Miyashita, Y. and  Chang, H. S.  Neuronal correlate of pictorial short-term memory in the primate temporal cortex,
   Nature 331, 68-70, 1988
Miyashita, Y.  Neuronal correlate of visual associative long-term memory in the primate cortex,  Nature 335, 817-920,  1988
Sakai, K. and Miyashita, Y.  Neural Organization for the long-term memory of paired associates,. Nature 354, 152-155,  1991
Griniasty, M.,  Tsodyks, M.V., and Amit, D. J. Conversion fo Temporal Correlations Between Stimuli to Spatial Correlations  Between Attractors, Neural Computation 5, 1-17, 1993
Fuji, H., J. Ito, et al.   Dynamical Cell Assembly Hypothesis: Theoretical Possibility of Spatio-temporal Coding in the Cortex.
  Neural Networks 9: 1303-1350,  1996
Gochin, P. M., M. Colombo, et al.  Neural ensemble coding in inferior temporal cortex.  Journal of Neurophysiology 71:  2325-2337.    1994
Eckhorn, R.  Cortical Processing by Fast Synchronization: High Frequency Rhythmic and Non-rhythmic signals in  the
   visual cortex point  in general principles of spatiotemporal coding,  in Time and Brain,  Miller R.  Lausanne, Gordon and Breach,
   169-201,  2000
Lopes da Silva, F.   Neural mechanisms underlying brain waves: from neural membranes to networks,  Electroencephelography
   and clinical Neurophysiology, 79, 81-93 1991
Bressler, S. L.  Large-scale cortical networks and cognition.  Brain Research Reviews 20, 288-304, 1995
Amit,  D.  The Hebbian paradigm reintegrated: Local reverberations as internal representation.  Behavioral and Brain Sciences 18,
  617-657, 1995

Oct 12   Single Cell Recordings in IT cortex during priming period and some interpretation
   Miyashita 1-3 ,  Griniasty et. al
Oct 17    Attractor Dynamics and Hebbian Assembly;  Need for Specific Theory Competition
   Amit BBS article and Commentary
Oct 19  Population Neurodynamics and Local Field Potential (EEG) Observables in Olfactory System
   Freeman Neurodynamics Article;  Skarda and Freeman BBS
Oct 24  Chaos in Local Field Potentials:  spatio-temporal amplitude patterns as carrier; role of chaos in novel input detection
    Skarda and Freeman commentary,  Lopes da Silva
Oct 26  Stimulus Dependent Synchronization and Coupling:  Experimental Observations
    Eckhorn,  Aertsen et al. papers
Oct 31  No class:   Analysis of Fuji et. al on IT cortical dynamics  Due Nov. 8
Nov 2   Signal Processing in Spike Trains, EEG
Nov 7   Large Scale Cortical Networks

Readings Group 4

Wright,  J.J.  and Liley, D.T.J.  Dynamics of the brain at global and microscopic scales: Neural networks and the EEG
Wright, J.J.,  Boureke, P.D.,  Chapman C.L.  Synchronous oscillation in the cerebral corex and object coherence: simulation of
  basic electrophysiological findings.
Kay, L.  Shimoide K.  Freeman, W.   Comparison of EEG time series from rat olfactory system with model composed of
   nonlinear coupled oscillators
S. Campbell and D. Wang, Synchronization and Desynchronization in a Network of Locally Coupled
  (Wilson-Cowan)   Oscillators,   IEEE Transactions on Neural Networks 7 541-554.  (1996)
Ito, J.   Kaneko, K.  Self -organized hierarchical structure in a plastic network of chaotic units
   Neural Networks 13 , 275-281,  2000
Tsuda, I.  Towards an interpretation of dynamic neural activity in terms of chaotic dynamical systems, Behavioral and
  Brain Sciences,  24:4  (target article online for commentary)
Wolpert, D. and Ghahramani, Z.  Computational Principles of Movement Neuroscience
   Nature Neuroscience Supplement 3, 2000
Pollack, J.B.  The Induction of Dynamical Recognizers, Machine Learning 7, 227-252 (1991)
Blair, A.D. and Pollack, J.B.  Analysis of Dynamical Recognizers
Lloyd, D.   Terra Cognita: From functional neuroimaging to the map of the mind
    Brain and Mind 1 93-116, 2000
Uttal, W.   On the limits of localization of cognitive processes in the brain.,  2000
Farah, M.  Neuropsychological inference with an interactive brain:  a critique of the locality assumption
Bauer, R. and Dicke, P.  Fast Cortical Selection: a principle of neuronal self-organization for perception
Goertzel, B.  Delay Vectors as Perceptual Chunks: Understanding Nonlinear Time Series Analysis as Self-Organizing Cognition   Dynamical Psychology, 1999 
Hegger, R.  Kantz, H.  Olbrich, E.  Problems in the Reconstruction of High-dimensional Deterministic Dynamics
   from Time Series, in Kantz, H.  (Ed.),  Nonlinear analysis of  physiological data.  Berlin, 1998
Palus, M.  Chaotic Measures and Real-World Systems: Deos the Lyapunov Exponent Always Measure Chaos?
  in Kantz, H.  (Ed.),  Nonlinear analysis of  physiological data.  Berlin, 1998

Nov 9   Wave Models of Neural Activity
       Wright and Liley, Wright et al.
Nov 14    Chaotic Itinerancy and Neural Activity
Nov 16 Synchronization in Coupled Oscillators for Cognitive Systems
   synchronization   presentation   D. DeMaris
Nov 21  Motor Control
   Wolpert & Ghahramani, (J. Dunphy leads discussion )
Nov 28  Dynamical Recognizers
   Pollack ,  Blair and Pollack  (T. Tversky leads discussion)
Nov  30  Imaging and Locality
      Lloyd, Uttal, Farah    (J. Schumake leads discussion)
Dec 5  Delay Embedding in Cognitive Processes ?  Measurement processes for High Dimensional Systems
           &nb sp;  Goertzel,  Hegger et al,  Palus          (S. Moon leads discussion)
Dec 7   Fast Cortical Selection Dynamics;   Pipelined Hardware Implementation of CML kernel
       Bauer and Dicke  (W.  Yu leads discussion)  ;  Young Cho presents coupled map hardware

Additional Material

Panzeri and Schultz : a unified approach
to the study of temporal, correlational and rate coding

Philosopher Tim Van Gelder'  1994 talk on the Dynamical Approach to Cognition

New Scientist 1997 article on Dynamical Neuroscience   J. McCrone

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