English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Correlations strike back (again): the case of associative memory re-trieval

Savin, C., Dayan, P., & lengyel, M. (2013). Correlations strike back (again): the case of associative memory re-trieval. Poster presented at Computational and Systems Neuroscience Meeting (COSYNE 2013), Salt Lake City, UT, USA.

Item is

Files

show Files

Locators

show
hide
Description:
-
OA-Status:

Creators

show
hide
 Creators:
Savin, C, Author
Dayan, P1, Author           
lengyel, M, Author
Affiliations:
1External Organizations, ou_persistent22              

Content

show
hide
Free keywords: -
 Abstract: It has long been recognised that statistical dependencies in neuronal activity need to be taken into account whendecoding stimuli encoded in a neural population. It is far less well appreciated that the same decoding challengesarise in the context of autoassociative memory, when retrieving information stored in correlated synapses. Suchcorrelations have been well documented experimentally (Song et al, 2005); here we show how they can arisebetween synapses that share pre- or post-synaptic partners when any of several well-known additive (Hopfield,1982) or metaplastic (Fusi et al, 2005) learning rules is applied. To assess the importance of these dependen-cies for recall, we adopt the strategy of comparing the performance of decoders which either do, or do not, takethem into account, but are otherwise optimal, showing that ignoring synaptic correlations has catastrophic conse-quences for retrieval. We therefore study how recurrent circuit dynamics can implement decoding that is sensitiveto correlations. Optimal retrieval dynamics in the face of correlations require substantial circuit complexities. Bycontrast, we show that it is possible to construct approximately optimal retrieval dynamics that are biologicallyplausible. The difference between these dynamics and those that ignore correlations is a set of non-linear circuitmotifs that have been suggested on experimental grounds, including forms of feedback inhibition and experimen-tally observed dendritic nonlinearities (Branco et al, 2011). We therefore show how assuaging an old enemy leadsto a novel functional account of key biophysical features of the neural substrate.

Details

show
hide
Language(s):
 Dates: 2013-03
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: -
 Degree: -

Event

show
hide
Title: Computational and Systems Neuroscience Meeting (COSYNE 2013)
Place of Event: Salt Lake City, UT, USA
Start-/End Date: 2013-02-28 - 2013-03-03

Legal Case

show

Project information

show

Source 1

show
hide
Title: Computational and Systems Neuroscience Meeting (COSYNE 2013)
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: I-11 Start / End Page: 51 Identifier: -