Spikes: exploring the neural code
Spikes: exploring the neural code
A Unified Approach to the Study of Temporal, Correlational, and Rate Coding
Neural Computation
The Neurophysiology of Backward Visual Masking: Information Analysis
Journal of Cognitive Neuroscience
How precise is neuronal synchronization?
Neural Computation
Towards Novel Neuroscience-Inspired Computing
Emergent Neural Computational Architectures Based on Neuroscience - Towards Neuroscience-Inspired Computing
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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.