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Approximate Hubel-Wiesel Modules and the Data Structures of Neural Computation

2015/12/28 by Joel Z. Leibo, Julien Cornebise, Leibo, Joel Z. +5 · 1 citation
Biochemistry, Genetics and Molecular Biology · Computer Science · Neuroscience · #Cognitive Science and Education Research #Neural dynamics and brain function #Visual perception and processing mechanisms #cs.NE #q-bio.NC

paper · pdf · doi:10.48550/arxiv.1512.08457

13 pages, 4 figures

arxiv created 2015/12/28 · arxiv updated 2015/12/29

Abstract

This paper describes a framework for modeling the interface between perception and memory on the algorithmic level of analysis. It is consistent with phenomena associated with many different brain regions. These include view-dependence (and invariance) effects in visual psychophysics and inferotemporal cortex physiology, as well as episodic memory recall interference effects associated with the medial temporal lobe. The perspective developed here relies on a novel interpretation of Hubel and Wiesel's conjecture for how receptive fields tuned to complex objects, and invariant to details, could be achieved. It complements existing accounts of two-speed learning systems in neocortex and hippocampus (e.g., McClelland et al. 1995) while significantly expanding their scope to encompass a unified view of the entire pathway from V1 to hippocampus.

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