The Maseeh Mathematics and Statistics Colloquium Series*
Mainak Patel, Ph.D.
Department of Mathematics
The Essential Role of Phase Delayed Inhibition in Decoding Synchronized Oscillations within the Brain
The widespread presence of synchronized neuronal oscillations within the brain suggests that a mechanism must exist that is capable of decoding such activity. Two realistic designs for such a decoder include: 1) a read-out neuron with a high spike threshold, or 2) a phase-delayed inhibition network motif. Despite requiring a more elaborate network architecture, phase-delayed inhibition has been observed in multiple systems, suggesting that it may provide inherent advantages over simply imposing a high spike threshold. We use a computational and mathematical approach to investigate the efficacy of the phase-delayed inhibition motif in detecting synchronized oscillations. We show that phase-delayed inhibition is capable of creating a synchrony detector with sharp synchrony filtering properties that depend critically on the time course of inputs. Additionally, we show that phase-delayed inhibition creates a synchrony filter that detects synchrony far more robustly than that created by a high spike threshold. A high spike threshold detects a minimum number of synchronous input spikes (absolute synchrony), while phase-delayed inhibition requires a fixed fraction of incoming spikes to be synchronous (relative synchrony). Furthermore, we show that, in a system with noisy encoders where stimuli are encoded through synchrony, phase-delayed inhibition enables the creation of a decoder that can respond both reliably and specifically to a stimulus, while a high spike threshold does not.
Friday, January 10th, 2014 at 3:15 p.m.
Neuberger Hall room 454
(Refreshments served at 3:00 in presentation room)
* Sponsored by the Maseeh Mathematics and Statistics Colloquium Series Fund and the Fariborz Maseeh Department of Mathematics & Statistics, PSU. This event is free and open to the public.