C5 Population dynamics in multi-stable perception.
Multi-stable stimuli can provide unique insights into visual processing, as changes in perception are decoupled from changes in the stimulus. Single-neuron studies have shown that higher in the visual hierarchy firing rates increasingly correlate with perception. However, very little is known about the underlying populationlevel mechanisms mediating the selection process and whether this process can be interpreted as the result of probabilistic inference when the posterior has more than one mode. We will address these questions on three fronts: a) using multi-electrode recordings in behaving macaques while presenting ambiguous motion stimuli, b) performing human psychophysics with the same stimuli, c) developing a dynamic states spiking neural network (DSNN) for probabilistic population coding to model the results obtained from electrophysiology and psychophysics. This integrative approach will provide novel
insights into multi-stable perception by combining population dynamics and probabilistic inference to uncover the mechanisms of multi-stability in the cortex.
Project leaders: Georgios A. Keliris, Wolfgang Rosenstiel, Roland Fleming, Nikos K. Logothetis
Coworkers: Martin Bogdan, Armin Walter, Qing Lin Li*, Hamed Bahmani
* funded by BMBF
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