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Reverse Engineering Primate Visual Object Perception

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Air date: Monday, October 2, 2017, 12:00:00 PM
Time displayed is Eastern Time, Washington DC Local
Views: Total views: 68, (21 Live, 47 On-demand)
Category: Neuroscience
Runtime: 01:13:34
Description: NIH Neuroscience Series Seminar

The research goal of Dr. DiCarlo's laboratory is to understand the mechanisms underlying visual object recognition. Specifically they seek to understand how sensory input is transformed by the brain from an initial representation (essentially a photograph on the retina), to a new, remarkably powerful form of representation -- one that can support our seemingly effortless ability to solve the computationally difficult problem of object recognition. They are particularly focused on patterns of neuronal activity in the highest levels of the ventral visual stream (primate inferior temporal cortex, IT) that likely directly underlie recognition. At these high levels, individual neurons can have the remarkable response property of being highly selective for object identity, even though each object’s image on the retinal surface is highly variable -- for example, due to changes in object position, distance, pose, lighting and background clutter. Understanding the creation of such neuronal responses by transformations carried out along the ventral visual processing stream is the key to understanding visual recognition.

To approach these very difficult problems, the work of their laboratory is directed along three main lines: 1) characterize the computational usefulness of patterns of IT neuronal activity for supporting immediate visual object recognition, 2) test and develop computational theories of how visual input is transformed along the ventral processing stream from a pixel-wise representation, to a powerful representation in IT, 3) understand the spatial organization of this representation. Their primary research approaches are: neurophysiology in awake, behaving non-human primates, functional brain imaging (fMRI), human psychophysics, and computational modeling. Across all of these endeavors they aim to develop innovative methods and tools to facilitate this work in their laboratory and others. Their approaches are often synergistic with those of other MIT laboratories, and this has greatly enhanced their progress.

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Author: James DiCarlo, M.D., Ph.D., MIT
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CIT Live ID: 24835
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