Literature DB >> 19187979

Associative memory models: from the cell-assembly theory to biophysically detailed cortex simulations.

Anders Lansner1.   

Abstract

The second half of the past century saw the emergence of a theory of cortical associative memory function originating in Donald Hebb's hypotheses on activity-dependent synaptic plasticity and cell-assembly formation and dynamics. This conceptual framework has today developed into a theory of attractor memory that brings together many experimental observations from different sources and levels of investigation into computational models displaying information-processing capabilities such as efficient associative memory and holistic perception. Here, we outline a development that might eventually lead to a neurobiologically grounded theory of cortical associative memory.

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Year:  2009        PMID: 19187979     DOI: 10.1016/j.tins.2008.12.002

Source DB:  PubMed          Journal:  Trends Neurosci        ISSN: 0166-2236            Impact factor:   13.837


  46 in total

Review 1.  Neural syntax: cell assemblies, synapsembles, and readers.

Authors:  György Buzsáki
Journal:  Neuron       Date:  2010-11-04       Impact factor: 17.173

2.  Endogenous sequential cortical activity evoked by visual stimuli.

Authors:  Luis Carrillo-Reid; Jae-Eun Kang Miller; Jordan P Hamm; Jesse Jackson; Rafael Yuste
Journal:  J Neurosci       Date:  2015-06-10       Impact factor: 6.167

3.  The brain's connective core and its role in animal cognition.

Authors:  Murray Shanahan
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2012-10-05       Impact factor: 6.237

Review 4.  Optimal cue combination and landmark-stability learning in the head direction system.

Authors:  Kate J Jeffery; Hector J I Page; Simon M Stringer
Journal:  J Physiol       Date:  2016-10-05       Impact factor: 5.182

5.  Neurofibromin and amyloid precursor protein expression in dopamine D3 receptor knock-out mice brains.

Authors:  Alessandro Castorina; Gian Marco Leggio; Salvatore Giunta; Gaetano Magro; Giovanni Scapagnini; Filippo Drago; Velia D'Agata
Journal:  Neurochem Res       Date:  2010-12-19       Impact factor: 3.996

6.  Attractor Dynamics in Networks with Learning Rules Inferred from In Vivo Data.

Authors:  Ulises Pereira; Nicolas Brunel
Journal:  Neuron       Date:  2018-06-14       Impact factor: 17.173

7.  An Associative Memory Model for Integration of Fragmented Research Data and Identification of Treatment Correlations in Breast Cancer Care.

Authors:  Ashis Gopal Banerjee; Mridul Khan; John Higgins; Annarita Giani; Amar K Das
Journal:  AMIA Annu Symp Proc       Date:  2015-11-05

8.  Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition.

Authors:  Johannes Bill; Lars Buesing; Stefan Habenschuss; Bernhard Nessler; Wolfgang Maass; Robert Legenstein
Journal:  PLoS One       Date:  2015-08-18       Impact factor: 3.240

9.  A Detailed Data-Driven Network Model of Prefrontal Cortex Reproduces Key Features of In Vivo Activity.

Authors:  Joachim Hass; Loreen Hertäg; Daniel Durstewitz
Journal:  PLoS Comput Biol       Date:  2016-05-20       Impact factor: 4.475

10.  Spike-Based Bayesian-Hebbian Learning of Temporal Sequences.

Authors:  Philip J Tully; Henrik Lindén; Matthias H Hennig; Anders Lansner
Journal:  PLoS Comput Biol       Date:  2016-05-23       Impact factor: 4.475

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