RuCCS Colloquia

A scale-invariant neural architecture for cognitive computation (talk recording available)

Dr. Marc Howard

Tuesday, October 06, 2015, 01:00pm - 02:00pm

Boston University, Department of Psychological and Brain Sciences and Center for Memory and Brain

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The Weber-Fechner law is among the oldest quantitative relationships in experimental psychology.  Neural codes with Weber-Fechner spacing are widely-observed in the nervous system, most famously extrafoveal retinal position.  We show new evidence suggesting that a neural representation for time in the rodent hippocampus obeys Weber-Fechner spacing; preliminary evidence suggests a similar relationship may also hold in the mPFC and striatum.  We describe a neural mechanism for constructing Weber-Fechner scales.  The mechanism relies on taking the Laplace transform of incoming experience and can be applied to generate scale-invariant representations of time, space and number.  The apparent ubiquity of Weber-Fechner scales in the brain and the Laplace method for constructing representations of time, space, and number suggest a general framework for cognitive computation.  Operations such as translation, convolution, and cross-correlation can be efficiently computed in the Laplace domain, enabling flexible computation on scale-invariant representations.   Circuits constructed in this way obey properties such as compositionality that are challenging for traditional connectionist models.  A simple circuit for performing subtraction is demonstrated.

To view a recording of this talk click here (You will need a Rutgers NetID and password)

Dr. Marc Howard

The RuCCS Colloquia Series is organized by Dr. Julien Musolino and Dr. Sara Pixley. The talks are held on Tuesdays in the Psychology Building, Room 101 on the Busch Campus from 1:00-2:30pm.

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