Experience-driven formation of parts-based representations in a model of layered visual memory

  • Growing neuropsychological and neurophysiological evidence suggests that the visual cortex uses parts-based representations to encode, store and retrieve relevant objects. In such a scheme, objects are represented as a set of spatially distributed local features, or parts, arranged in stereotypical fashion. To encode the local appearance and to represent the relations between the constituent parts, there has to be an appropriate memory structure formed by previous experience with visual objects. Here, we propose a model how a hierarchical memory structure supporting efficient storage and rapid recall of parts-based representations can be established by an experience-driven process of self-organization. The process is based on the collaboration of slow bidirectional synaptic plasticity and homeostatic unit activity regulation, both running at the top of fast activity dynamics with winner-take-all character modulated by an oscillatory rhythm. These neural mechanisms lay down the basis for cooperation and competition between the distributed units and their synaptic connections. Choosing human face recognition as a test task, we show that, under the condition of open-ended, unsupervised incremental learning, the system is able to form memory traces for individual faces in a parts-based fashion. On a lower memory layer the synaptic structure is developed to represent local facial features and their interrelations, while the identities of different persons are captured explicitly on a higher layer. An additional property of the resulting representations is the sparseness of both the activity during the recall and the synaptic patterns comprising the memory traces. Keywords: visual memory, self-organization, unsupervised learning, competitive learning, bidirectional plasticity, activity homeostasis, parts-based representation, cortical column

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Author:Evgueni Jitsev, Christoph von der Malsburg
Pubmed Id:https://pubmed.ncbi.nlm.nih.gov/19862345
Parent Title (English):Frontiers in computational neuroscience, 3.2009, article 15
Document Type:Article
Date of Publication (online):2009/09/29
Date of first Publication:2009/09/29
Publishing Institution:Universitätsbibliothek Johann Christian Senckenberg
Release Date:2010/09/16
Tag:activity homeostasis; bidirectional plasticity; competitive learning; self-organization; unsupervised learning; visual memory
Issue:Article 15
Copyright: © 2009 Jitsev and von der Malsburg. This is an open-access article subject to an exclusive license agreement between the authors and the Frontiers Research Foundation, which permits unrestricted use, distribution, and reproduction in any medium, provided the original authors and source are credited.
Source:Frontiers in computational neuroscience 3:15. ; doi: 10.3389/neuro.10.015.2009 ; http://www.frontiersin.org/computational_neuroscience/10.3389/neuro.10.015.2009/full
Institutes:Wissenschaftliche Zentren und koordinierte Programme / Frankfurt Institute for Advanced Studies (FIAS)
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit
Licence (German):License LogoDeutsches Urheberrecht