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A theory of how the brain might work

Author: Tomaso Poggio; Massachusetts Institute of Technology. Artificial Intelligence Laboratory.
Publisher: Cambridge, Mass. : Massachusetts Institute of Technology, Artificial Intelligence Laboratory and Center for Biological Information Processing, Whitaker College, ©1990.
Series: A.I. memo, 1253.
Edition/Format:   Print book : English
Database:WorldCat
Summary:
Abstract: "I wish to propose a quite speculative new version of the grandmother cell theory to explain how the brain, or parts of it, may work. In particular, I discuss how the visual system may learn to recognize 3D objects. The model would apply directly to the cortical cells involved in visual face recognition. I will also outline the relation of our theory to existing models of the cerebellum and of motor
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Details

Document Type: Book
All Authors / Contributors: Tomaso Poggio; Massachusetts Institute of Technology. Artificial Intelligence Laboratory.
OCLC Number: 24915092
Notes: Cover title.
"December 1990."
"C.B.I.P. Memo No. 50."
Description: 26, [8] pages : illustrations ; 28 cm.
Series Title: A.I. memo, 1253.
Responsibility: Tomaso Poggio.

Abstract:

Abstract: "I wish to propose a quite speculative new version of the grandmother cell theory to explain how the brain, or parts of it, may work. In particular, I discuss how the visual system may learn to recognize 3D objects. The model would apply directly to the cortical cells involved in visual face recognition. I will also outline the relation of our theory to existing models of the cerebellum and of motor control. Specific biophysical mechanisms can be readily suggested as part of a basic type of neural circuitry that can learn to approximate multidimensional input-output mappings from sets of examples and that is expected to be replicated in different regions of the brain and across modalities.

The main points of the theory are: the brain uses modules for multivariate function approximation as basic components of several of its information processing subsystems. these [sic] modules are realized as HyperBF networks (Poggio and Girosi, 1990a, b). Hyper BF networks can be implemented in terms of biologically plausible mechanisms and circuitry. The theory predicts a specific type of population coding that represents an extension of schemes such as look-up tables. I will conclude with some speculations about the trade-off between memory and computation and the evolution of intelligence."

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