Max Planck Institute for Dynamics and Self-Organization -- Department for Nonlinear Dynamics and Network Dynamics Group
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BCCN/BFNT AG-Seminar

Tuesday, 28.05.2013 17 c.t.

Things look black for the receptive field hypothesis in the primary visual cortex (V1)

by Prof. Robert Shapley
from Center for Neural Science, New York University, New York, USA

Contact person: Demian Battaglia

Location

Ludwig Prandtl lecture hall

Abstract

The receptive field hypothesis (RFH) is the idea that the response of a neuron to any spatial pattern can be predicted from the sensitivity map across its receptive field. For instance, the RFH predicts that a visual neuron’s response to an edge in a visual image’s lightness pattern can be predicted from the location of the edge in the neuron’s receptive field. The RFH works very well when applied to retinal ganglion cells in the cat or monkey retinas, and to some neurons in the visual cortex. But we (Yeh, Xing, Williams and Shapley) found that the RFH fails for most neurons in the output layers of V1 cortex, neurons in layer 2/3. There isn’t really one receptive field for a layer 2/3 neuron but rather different receptive fields for different stimulus ensembles, different contexts. The remarkable thing is that when their receptive fields are mapped with what I have called “sparse noise”, layer 2/3 neurons respond selectively to black spots rather than white.

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