Dynamic neural fields as a step toward cognitive neuromorphic architectures

  • Dynamic Field Theory (DFT) is an established framework for modeling embodied cognition. In DFT, elementary cognitive functions such as memory formation, formation of grounded representations, attentional processes, decision making, adaptation, and learning emerge from neuronal dynamics. The basic computational element of this framework is a Dynamic Neural Field (DNF). Under constraints on the time-scale of the dynamics, the DNF is computationally equivalent to a soft winner-take-all (WTA) network, which is considered one of the basic computational units in neuronal processing. Recently, it has been shown how a WTA network may be implemented in neuromorphic hardware, such as analog Very Large Scale Integration (VLSI) device. This paper leverages the relationship between DFT and soft WTA networks to systematically revise and integrate established DFT mechanisms that have previously been spread among different architectures. In addition, I also identify some novel computational and architectural mechanisms of DFT which may be implemented in neuromorphic VLSI devices using WTA networks as an intermediate computational layer. These specific mechanisms include the stabilization of working memory, the coupling of sensory systems to motor dynamics, intentionality, and autonomous learning. I further demonstrate how all these elements may be integrated into a unified architecture to generate behavior and autonomous learning.

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Metadaten
Author:Yulia SandamirskayaORCiDGND
URN:urn:nbn:de:hbz:294-69818
DOI:https://doi.org/10.3389/fnins.2013.00276
Parent Title (English):Frontiers in neuroscience
Publisher:Frontiers Research Foundation
Place of publication:Lausanne
Document Type:Article
Language:English
Date of Publication (online):2020/02/13
Date of first Publication:2014/01/22
Publishing Institution:Ruhr-Universität Bochum, Universitätsbibliothek
Tag:autonomous learning; cognitive neuromorphic architecture; dynamic neural fields; neural dynamics; soft winner-take-all
Volume:7
First Page:276-1
Last Page:276-13
Institutes/Facilities:Institut für Neuroinformatik, Lehrstuhl Theorie kognitiver Systeme
open_access (DINI-Set):open_access
Licence (English):License LogoCreative Commons - CC BY 3.0 Unported - Attribution 3.0 Unported