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A Neuronal Network Model for Context-Dependent Perceptual Decision on Ambiguous Sound Comparison

Speaker: Dr. Cheng-Cheng Huang, Courant Institute of Mathematical Sciences, New York University

Abstract: Many natural stimuli contain perceptual ambiguities that can be cognitively resolved by the surrounding context, e.g. preceding stimuli. In audition, preceding context can bias the perception of speech and non-speech stimuli. Here, we developed neuronal network model to account for how preceding auditory stimuli affects our perception of pitch change direction. Our model draws inspiration from a recent psychophysical experiment where listeners experienced opposite percepts (either ascending or descending) of an ambiguous tone pair depending on the spectral positions of the preceding tones. Our recurrent firing-rate network model can detect frequency change of successively played stimuli due to asymmetric inhibition. We propose a novel adaptation mechanism, facilitation of inhibitory synapses, which successfully accounts for the context-dependent perception demonstrated in behavioral experiments.

Date&Time: January 14, 2015 (Wednesday), 10:30–11:30 a.m.
Location: 606 Conference Room



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