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  Correlations strike back (again): the case of associative memory retrieval

Savin, C., Dayan, P., & Lengyel, M. (2014). Correlations strike back (again): the case of associative memory retrieval. In C. Burges, L. Bottou, Z. Ghahramani, & K. Weinberger (Eds.), Advances in Neural Information Processing Systems 26 (NIPS 2013) (pp. 288-296). Red Hook, NY, USA: Curran.

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 Creators:
Savin, C, Author
Dayan, P1, Author              
Lengyel, M, Author
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1External Organizations, ou_persistent22              

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 Abstract: It has long been recognised that statistical dependencies in neuronal activity need to be taken into account when decoding stimuli encoded in a neural population. Less studied, though equally pernicious, is the need to take account of dependencies between synaptic weights when decoding patterns previously encoded in an auto-associative memory. We show that activity-dependent learning generically produces such correlations, and failing to take them into account in the dynamics of memory retrieval leads to catastrophically poor recall. We derive optimal network dynamics for recall in the face of synaptic correlations caused by a range of synaptic plasticity rules. These dynamics involve well-studied circuit motifs, such as forms of feedback inhibition and experimentally observed dendritic nonlinearities. We therefore show how addressing the problem of synaptic correlations leads to a novel functional account of key biophysical features of the neural substrate.

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 Dates: 2014
 Publication Status: Published in print
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Title: Twenty-Seventh Annual Conference on Neural Information Processing Systems (NIPS 2013)
Place of Event: Lake Tahoe, NV, USA
Start-/End Date: 2013-12-05 - 2013-12-10

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Title: Advances in Neural Information Processing Systems 26 (NIPS 2013)
Source Genre: Proceedings
 Creator(s):
Burges, CJC, Editor
Bottou, L, Editor
Ghahramani, Z, Editor
Weinberger, KQ, Editor
Affiliations:
-
Publ. Info: Red Hook, NY, USA : Curran
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 288 - 296 Identifier: ISBN: 978-1-63266-024-4