Mounting evidence suggests that 'core object recognition,' the ability to rapidly recognize objects despite substantial appearance variation, is solved in the brain via a cascade of reflexive, largely feedforward computations that culminate in a powerful neuronal representation in the inferior temporal cortex. However, the algorithm that produces this solution remains poorly understood. Here we review evidence ranging from individual neurons and neuronal populations to behavior and computational models. We propose that understanding this algorithm will require using neuronal and psychophysical data to sift through many computational models, each based on building blocks of small, canonical subnetworks with a common functional goal.

How Does the Brain Solve Visual Object Recognition? / Dicarlo, Jj; Zoccolan, Davide Franco; Rust, Nc. - In: NEURON. - ISSN 0896-6273. - 73:3(2012), pp. 415-434. [10.1016/j.neuron.2012.01.010]

How Does the Brain Solve Visual Object Recognition?

Zoccolan, Davide Franco;
2012-01-01

Abstract

Mounting evidence suggests that 'core object recognition,' the ability to rapidly recognize objects despite substantial appearance variation, is solved in the brain via a cascade of reflexive, largely feedforward computations that culminate in a powerful neuronal representation in the inferior temporal cortex. However, the algorithm that produces this solution remains poorly understood. Here we review evidence ranging from individual neurons and neuronal populations to behavior and computational models. We propose that understanding this algorithm will require using neuronal and psychophysical data to sift through many computational models, each based on building blocks of small, canonical subnetworks with a common functional goal.
2012
73
3
415
434
10.1016/j.neuron.2012.01.010
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3306444/
Dicarlo, Jj; Zoccolan, Davide Franco; Rust, Nc
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11767/13025
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