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Behavioral/Systems/Cognitive Multiple Object Response Normalization in Monkey

Summary: Behavioral/Systems/Cognitive
Multiple Object Response Normalization in Monkey
Inferotemporal Cortex
Davide Zoccolan,1,2,3* David D. Cox,1,2* and James J. DiCarlo1,2
1McGovern Institute for Brain Research, 2Department of Brain and Cognitive Sciences, and 3Center for Biological and Computational Learning,
Massachusetts Institute of Technology, Cambridge, Massachusetts 02139
The highest stages of the visual ventral pathway are commonly assumed to provide robust representation of object identity by disregard-
responses in monkey inferotemporal cortex (IT) can show robust tolerance to position and size changes, previous work shows that
responses to preferred objects are usually reduced by the presence of nonpreferred objects. More broadly, we do not yet understand
multiple object representation in IT. In this study, we systematically examined IT responses to pairs and triplets of objects in three
passively viewing monkeys across a broad range of object effectiveness. We found that, at least under these limited clutter conditions, a
large fraction of the response of each IT neuron to multiple objects is reliably predicted as the average of its responses to the constituent
of object identity. This average effect becomes virtually perfect when populations of IT neurons are pooled. Furthermore, the average
effect cannot simply be explained by attentional shifts but behaves as a primarily feedforward response property. Together, our obser-
vations are most consistent with mechanistic models in which IT neuronal outputs are normalized by summed synaptic drive into IT or
spiking activity within IT and suggest that normalization mechanisms previously revealed at earlier visual areas are operating through-
out the ventral visual stream.
Key words: inferotemporal cortex; monkey; object recognition; multiple objects; normalization; clutter tolerance


Source: Andrzejak, Ralph Gregor - Departament de Tecnologia, Universitat Pompeu Fabra
Oliva, Aude - Department of Brain and Cognitive Science, Massachusetts Institute of Technology (MIT)
Poggio, Tomaso - Center for Biological and Computational Learning, Massachusetts Institute of Technology (MIT)
Zoccolan, Davide - Neurobiology Sector, Scuola Internazionale Superiore di Studi Avanzati (SISSA)


Collections: Biology and Medicine; Computer Technologies and Information Sciences