While it is generally agreed that the spike train output by a neuron encodes information about the inputs to that neuron, the code by which the information is transmitted remains unclear (see [Stevens and Zador, 1995, Ferster and Spruston, 1995] for recent discussions). One idea--the traditional view in systems physiology--is that it is the mean firing rate alone that encodes the signal, and that variability about this mean is noise [Shadlen and Newsome, 1994, Shadlen and Newsome, 1995]. An alternative view that has recently gained increasing support is that it is the variability itself that encodes the signal, i.e. that the information is encoded in the precise times at which spikes occur [Bialek et al., 1991, Abeles et al., 1994, Softky, 1995, Rieke et al., 1997].
Our results make no assumptions about the neuronal code. Rather, they provide an exact expression for the maximum information that could possibly be transmitted, given the stimuli and the neuronal parameters. The precise timing of spikes is used to achieve this maximum; how much of this available information is actually used by ``downstream'' neurons is a separate question.
The importance of spike timing in encoding time-varying signals is now well-established in some systems, such as the motion-sensitive H1 neuron of the fly [Bialek et al., 1991]. A comparable role for spike timing in mammalian cortex has been more controversial. It has been suggested that motion sensitive neurons in area MT of awake monkeys encode only fractions of a bit per second, and that all of the encoded information is available in the spike count over a relatively long time window [Britten et al., 1992]. However, more recent experiments [Buracas et al., 1996, Bair et al., 1997] suggest that these neurons encode information at rates (1-2 bits/spike) comparable to those of the H1 neuron of the fly, when presented with visual stimuli that have appropriately rich temporal structure. Thus it may be wrong to speak of the neural code: it may well turn out that some components of the input stimulus (e.g. those that are changing rapidly) are encoded by precise firing times, while others are not.
We have shown that an increase in the number of functional contacts per axon can lead to an increase in transmitted information if the timing of spikes encodes the signal, but not if a mean rate code is used. Such an increase can be seen as a special case of neuronal synchrony in which all synapses from a single axon are stimulated at precisely the same instant. This seemingly paradoxical observation is a consequence of the manner in which synchrony affects firing patterns: it increases timing precision, but also increases the trial-to-trial variability in the spike count. It is not clear how synaptic unreliability could be compensated for in a mean rate scenario.