TY - JOUR T1 - Computing with Neural Synchrony A1 - Brette, Romain Y1 - 2012/06/14 N2 - Author Summary How does the brain compute? Traditional theories of neural computation describe the operating function of neurons in terms of average firing rates, with the timing of spikes bearing little information. However, numerous studies have shown that spike timing can convey information and that neurons are highly sensitive to synchrony in their inputs. Here I propose a simple spike-based computational framework, based on the idea that stimulus-induced synchrony can be used to extract sensory invariants (for example, the location of a sound source), which is a difficult task for classical neural networks. It relies on the simple remark that a series of repeated coincidences is in itself an invariant. Many aspects of perception rely on extracting invariant features, such as the spatial location of a time-varying sound, the identity of an odor with fluctuating intensity, the pitch of a musical note. I demonstrate that simple synchrony-based neuron models can extract these useful features, by using spiking models in several sensory modalities. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 8 IS - 6 UR - https://doi.org/10.1371/journal.pcbi.1002561 SP - e1002561 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1002561 ER -