INSTITUTE OF PHYSICS PUBLISHING NETWORK: COMPUTATION IN NEURAL SYSTEMS
Network: Comput. Neural Syst. 14 (2003) 303–319 PII: S0954-898X(03)60761-X
Optimal neural rate coding leads to bimodal firing
rate distributions
M Bethge, D Rotermund and K Pawelzik
Institute of Theoretical Physics, University Bremen, Otto-Hahn-Alle, D-28334, Germany
E-mail: mbethge@physik.uni-bremen.de
Received 23 July 2002, in final form 4 February 2003
Published 8 April 2003
Online at stacks.iop.org/Network/14/303
Abstract
Many experimental studies concerning the neuronal code are based on graded
responses of neurons, given by the emitted number of spikes measured in
a certain time window. Correspondingly, a large body of neural network
theory deals with analogue neuron models and discusses their potential use
for computation or function approximation. All physical signals, however,
are of limited precision, and neuronal firing rates in cortex are relatively low.
Here, we investigate the relevance of analogue signal processing with spikes in
terms of optimal stimulus reconstruction and information theory. In particular,
we derive optimal tuning functions taking the biological constraint of limited
firing rates into account. It turns out that depending on the available decoding
time T , optimal encoding undergoes a phase transition from discrete binary
coding for small T towards analogue or quasi-analogue encoding for large T .
The corresponding firing rate distributions are bimodal for all relevant T , in
particular in the case of population coding.
(Some figures in this article are in colour only in the electronic version)
1. Introduction
Since the discovery by Adrian (1926) that action potentials are generated by sensory neurons
with a frequency that is substantially determined by the stimulus, the idea of rate coding has
become the prevalent paradigm in neuroscience (Perkel and Bullock 1968). In particular, today
the coding properties of many neurons from various areas in the cortex have been characterized
by tuning curves, which describe the average firing rate response as a function of certain
stimulus parameters. Remarkably, almost all tuning functions measured in the mammalian
cortex have a smooth bell-shaped form, which suggests an analogue neural code.
On the other hand it is obvious that the maximum number of spikes k
max
that can be taken
into account by subsequent neurons is limited by their integration time, so that a rate code
actually constitutes a discrete code with k
max
+ 1 different symbols. Therefore, the precision
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