DocumentCode :
3032643
Title :
Analyzing composability in a sparse encoding model of memorization and association
Author :
Beal, Jacob ; Knight, Thomas F., Jr.
Author_Institution :
MIT CSAIL, Cambridge, MA
fYear :
2008
fDate :
9-12 Aug. 2008
Firstpage :
180
Lastpage :
185
Abstract :
A key question in neuroscience is how memorization and association are supported by the mammalian cortex. One possible model, proposed by Valiant, uses sparse encodings in a sparse random graph, but the composability of operations in this model (e.g. an association triggering another association) has not previously been evaluated. We evaluate composability by measuring the size of ldquoitemsrdquo produced by memorization and the propagation of signals through the ldquocircuitsrdquo created by memorization and association. While the association operation is sound, the memorization operation produces ldquoitemsrdquo with unstable size and produces circuits that are extremely sensitive to noise. We therefore amend the model, introducing an association stage into memorization. The amended model preserves and strengthens the sparse encoding hypothesis and invites further characterization of properties such as capacity and interference.
Keywords :
cognition; neurophysiology; sparse matrices; association; composability; mammalian cortex; memorization; neuroscience; sparse encoding model; sparse random graph; Acoustic noise; Acoustic propagation; Brain modeling; Circuit noise; Encoding; Humans; Interference; Mice; Neurons; Neuroscience;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Development and Learning, 2008. ICDL 2008. 7th IEEE International Conference on
Conference_Location :
Monterey, CA
Print_ISBN :
978-1-4244-2661-4
Electronic_ISBN :
978-1-4244-2662-1
Type :
conf
DOI :
10.1109/DEVLRN.2008.4640826
Filename :
4640826
Link To Document :
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