Bernstein Center for Computational Neuroscience Berlin
will speak on
Institute for Theoretical Biology, Humboldt-University Berlin
Is slowness a learning principle for complex cells
in V1 and visual invariances in IT?
Different representations of our visual environment vary on different time scales. Retinal responses vary quickly because they are very sensitive to saccades or object motion while representations in the inferior temporal cortex (IT) display a large degree of invariance and therefore vary more slowly. Turning this argument around leads to slowness as a learning principle. By learning input-output functions that generate slowly varying output signals, units become invariant to frequently occurring transformations, such as translation, rotation, or illumination changes. We argue that this is an effective mechanism by which IT could learn its invariant representations. Interestingly the same principle also leads to a number of complex-cell receptive-field properties even though invariance does not seem to be such an issue so early in the visual system. Some of the simulation results presented here are complemented by analytical results obtained with variational calculus.
The seminar will take place
in 44 Cummington St. Room 203
on Monday – October 22, 2007
Hosted by the Brain and Vision Research Laboratory