  Does synchronization between action potentials from different neurons in the
visual system play a substantial role in solving the binding problem? The
binding problem can be studied quantitatively in the broader framework of the
information contained in neural spike trains about some external correlate,
which in this case is object configurations in the visual field. We approach
this problem by using a mathematical formalism that quantifies the impact of
correlated firing in short time scales. Using a power series expansion, the
mutual information an ensemble of neurons conveys about external stimuli is
broken down into firing rate and correlation components. This leads to a new
quantification procedure directly applicable to simultaneous multiple neuron
recordings. It theoretically constrains the neural code, showing that
correlations contribute less significantly than firing rates to rapid
information processing. By using this approach to study the limits upon the
amount of information that an ideal observer is able to extract from a
synchrony code, it may be possible to determine whether the available amount of
information is sufficient to support computational processes such as feature
binding.
