On the self-organization of a hierarchical memory for compositional object representation in the visual cortex ; Über die Selbstorganisation einer hierarchischen Gedächtnisstruktur für kompositionelle Objektrepräsentation im visuellen Kortex
Titel:
On the self-organization of a hierarchical memory for compositional object representation in the visual cortex ; Über die Selbstorganisation einer hierarchischen Gedächtnisstruktur für kompositionelle Objektrepräsentation im visuellen Kortex
Beteiligte:
Jitsev, Evgueni
[Verfasser:in]
Erschienen:
Publication Server of Goethe University Frankfurt am Main, 2011-01-11
Anmerkungen:
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Beschreibung:
At present, there is a huge lag between the artificial and the biological information processing systems in terms of their capability to learn. This lag could be certainly reduced by gaining more insight into the higher functions of the brain like learning and memory. For instance, primate visual cortex is thought to provide the long-term memory for the visual objects acquired by experience. The visual cortex handles effortlessly arbitrary complex objects by decomposing them rapidly into constituent components of much lower complexity along hierarchically organized visual pathways. How this processing architecture self-organizes into a memory domain that employs such compositional object representation by learning from experience remains to a large extent a riddle. The study presented here approaches this question by proposing a functional model of a self-organizing hierarchical memory network. The model is based on hypothetical neuronal mechanisms involved in cortical processing and adaptation. The network architecture comprises two consecutive layers of distributed, recurrently interconnected modules. Each module is identified with a localized cortical cluster of fine-scale excitatory subnetworks. A single module performs competitive unsupervised learning on the incoming afferent signals to form a suitable representation of the locally accessible input space. The network employs an operating scheme where ongoing processing is made of discrete successive fragments termed decision cycles, presumably identifiable with the fast gamma rhythms observed in the cortex. The cycles are synchronized across the distributed modules that produce highly sparse activity within each cycle by instantiating a local winner-take-all-like operation. Equipped with adaptive mechanisms of bidirectional synaptic plasticity and homeostatic activity regulation, the network is exposed to natural face images of different persons. The images are presented incrementally one per cycle to the lower network layer as a set of Gabor filter ...