Temporal information processing plays a significant role in the brain, especially in the auditory pathway. Temporal information is carried by the timing of individual action potentials (spikes) produced by neurons, which communicate with one another in intricate networks. The traditional view has been that the mean rate at which neurons fire provides an adequate description of the information that they convey. However, there are a number of instances within the nervous system where the temporal information contained in the timing of individual spikes plays an important role, most notably in the auditory system where spikes are correlated to the phase of low frequency sounds.

One aim is to understand the mechanisms by which such temporal information is encoded and decoded through the interaction of systems of neurons. By analyzing the relationship between the synaptic input to a neuron and the spikes that it generates as output, it is possible to address important questions about the extent to which temporal information can be processed by neurons. The physiological characteristics of neurons, which have particular time scales associated with their functioning (such as the membrane time constant and rise time), play an important role in determining what type of temporal information processing is possible. The models that the Computational Neuroscience Group have been developing enable us to examine the roles of coincidence detection, inhibition, synchronization and spatiotemporal summation. This research has a direct application to cochlear implants, with the goal of effectively incorporating temporal information into the design of more optimal electrical stimulation strategies.