Foreword Neural Pulse Coding

Neurons use action potentials to signal over long distances, as summarized in Chapter 1 by Gerstner. The all-or-none nature of the action potential means that it codes information by its presence or absence, but not by its size or shape. In this respect, an action potential can be considered a pulse. This is an important fact about how brains are built, but it is equally important as a theoretical challenge to understanding the function of the brain. How do action potentials represent sensory states? How is information contained in the firing patterns of action potentials stored and retrieved? These are old questions that have been the focus of much research, but recent advances in experimental techniques are opening new ways to test theories for how information is encoded and decoded by spiking neurons in neural systems [Rieke et al., 19971. The papers in the collection provide a window into the current state of theoretical and computational thinking based on spikes.

[1]  William Bialek,et al.  Spikes: Exploring the Neural Code , 1996 .

[2]  H. Sompolinsky,et al.  Chaos in Neuronal Networks with Balanced Excitatory and Inhibitory Activity , 1996, Science.

[3]  R. Traub,et al.  Neuronal networks for induced ‘40 Hz’ rhythms , 1996, Trends in Neurosciences.

[4]  G D Lewen,et al.  Reproducibility and Variability in Neural Spike Trains , 1997, Science.

[5]  H Sompolinsky,et al.  Simple models for reading neuronal population codes. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[6]  H. Markram,et al.  Redistribution of synaptic efficacy between neocortical pyramidal neurons , 1996, Nature.

[7]  W. Newsome,et al.  The Variable Discharge of Cortical Neurons: Implications for Connectivity, Computation, and Information Coding , 1998, The Journal of Neuroscience.

[8]  T. Sejnowski,et al.  Spatial Transformations in the Parietal Cortex Using Basis Functions , 1997, Journal of Cognitive Neuroscience.

[9]  H. Markram,et al.  Physiology and anatomy of synaptic connections between thick tufted pyramidal neurones in the developing rat neocortex. , 1997, The Journal of physiology.

[10]  Michael N. Shadlen,et al.  Noise, neural codes and cortical organization , 1994, Current Opinion in Neurobiology.

[11]  G. Laurent,et al.  Impaired odour discrimination on desynchronization of odour-encoding neural assemblies , 1997, Nature.

[12]  Peter E. Latham,et al.  Statistically Efficient Estimation Using Population Coding , 1998, Neural Computation.

[13]  T. Sejnowski,et al.  Effects of cholinergic modulation on responses of neocortical neurons to fluctuating input. , 1997, Cerebral cortex.

[14]  B L McNaughton,et al.  Interpreting neuronal population activity by reconstruction: unified framework with application to hippocampal place cells. , 1998, Journal of neurophysiology.

[15]  Masakazu Konishi,et al.  Deciphering the Brain's Codes , 1999, Neural Computation.

[16]  B. McNaughton,et al.  Tetrodes markedly improve the reliability and yield of multiple single-unit isolation from multi-unit recordings in cat striate cortex , 1995, Journal of Neuroscience Methods.

[17]  W. Kristan,et al.  A neuronal network for computing population vectors in the leech , 1998, Nature.

[18]  A. P. Georgopoulos,et al.  Primate motor cortex and free arm movements to visual targets in three- dimensional space. I. Relations between single cell discharge and direction of movement , 1988, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[19]  Walter Heiligenberg,et al.  Neural Nets in Electric Fish , 1991 .

[20]  Bartlett W. Mel NMDA-Based Pattern Discrimination in a Modeled Cortical Neuron , 1992, Neural Computation.

[21]  Eberhard E. Fetz,et al.  Effects of Input Synchrony on the Firing Rate of a Three-Conductance Cortical Neuron Model , 1994, Neural Computation.

[22]  M. Meister Multineuronal codes in retinal signaling. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[23]  S. Lehky,et al.  Neural model of stereoacuity and depth interpolation based on a distributed representation of stereo disparity [published erratum appears in J Neurosci 1991 Mar;11(3):following Table of Contents] , 1990, The Journal of neuroscience : the official journal of the Society for Neuroscience.

[24]  J. O’Keefe,et al.  Phase relationship between hippocampal place units and the EEG theta rhythm , 1993, Hippocampus.

[25]  B L McNaughton,et al.  Dynamics of the hippocampal ensemble code for space. , 1993, Science.

[26]  D. Snodderly,et al.  Response Variability of Neurons in Primary Visual Cortex (V1) of Alert Monkeys , 1997, The Journal of Neuroscience.

[27]  O. Prospero-Garcia,et al.  Reliability of Spike Timing in Neocortical Neurons , 1995 .

[28]  Terrence J. Sejnowski,et al.  Neuronal Tuning: To Sharpen or Broaden? , 1999, Neural Computation.

[29]  W. Singer,et al.  Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties , 1989, Nature.

[30]  T. Sanger,et al.  Probability density estimation for the interpretation of neural population codes. , 1996, Journal of neurophysiology.

[31]  Terrence J. Sejnowski,et al.  RAPID STATE SWITCHING IN BALANCED CORTICAL NETWORK MODELS , 1995 .

[32]  J J Hopfield,et al.  Transforming neural computations and representing time. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[33]  T J Sejnowski Pattern recognition. Time for a new neural code? , 1995, Nature.

[34]  N. Suga,et al.  Delay lines and amplitude selectivity are created in subthalamic auditory nuclei: the brachium of the inferior colliculus of the mustached bat. , 1993, Journal of neurophysiology.

[35]  B. Finlay,et al.  Short-term response variability of monkey striate neurons , 1976, Brain Research.

[36]  T. Sejnowski,et al.  Synchronous oscillatory activity in sensory systems: new vistas on mechanisms , 1997, Current Opinion in Neurobiology.