Abstract
Object recognition in the natural world usually occurs in the presence of multiple surrounding objects, but responses of neurons in inferotemporal (IT) cortex, the large brain area responsible for object recognition, have mostly been studied only to isolated objects. We study rules governing responses to multiple objects by cells in two category-selective regions of macaque IT cortex, the middle lateral face patch (ML) and the middle body patch (MB). We find that responses of single ML and MB cells to pairs of objects can be explained by the widely accepted framework of normalization, with one added ingredient: homogeneous category selectivity of neighboring neurons forming the normalization pool. This rule leads to winner-take-all, contralateral-take-all, or weighted averaging behavior in single cells, depending on the category, spatial configuration, and relative contrast of the two objects. The winner-take-all behavior suggests a potential mechanism for clutter-invariant representation of face and bodies under certain conditions.
Highlights
Object recognition in the natural world usually occurs in the presence of multiple surrounding objects, but responses of neurons in inferotemporal (IT) cortex, the large brain area responsible for object recognition, have mostly been studied only to isolated objects
Consistent with previous studies, we found 90% of cells had a face selectivity index greater than 0.33 (Supplementary Fig. 1, see Methods for details); these units were selected for further study
We tackled the question of how IT cortex integrates responses to multiple objects during passive fixation through targeted recordings in face patch middle lateral face patch (ML) and body patch middle body patch (MB)
Summary
Object recognition in the natural world usually occurs in the presence of multiple surrounding objects, but responses of neurons in inferotemporal (IT) cortex, the large brain area responsible for object recognition, have mostly been studied only to isolated objects. Previous electrophysiological studies exploring the rules governing responses to multiple objects (“multiple object integration”) in IT during passive fixation suffered one important limitation: they all recorded from randomly selected IT neurons whose role in coding the object set tested was unknown[4,6,7,13]. Up to now, this limitation has been difficult to overcome: for most cells in IT, the only clue we have to whether the cell is involved in encoding a particular object is whether the cell under study responds to the object. The rules used by cells in face/body patches for multiple object integration involving faces/ bodies have higher likelihood to be behaviorally relevant than those used by randomly sampled IT cells for multiple object integration involving random objects
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