Part of Advances in Neural Information Processing Systems 19 (NIPS 2006)
Danko Nikolić, Stefan Haeusler, Wolf Singer, Wolfgang Maass
We use multi-electrode recordings from cat primary visual cortex and investigate whether a simple linear classifier can extract information about the presented stim(cid:173) uli. We find that information is extractable and that it even lasts for several hun(cid:173) dred milliseconds after the stimulus has been removed. In a fast sequence of stim(cid:173) ulus presentation, information about both new and old stimuli is present simul(cid:173) taneously and nonlinear relations between these stimuli can be extracted. These results suggest nonlinear properties of cortical representations. The important im(cid:173) plications of these properties for the nonlinear brain theory are discussed.