BASIC PRINCIPLES OF THE KIV MODEL AND ITS APPLICATION TO THE NAVIGATION PROBLEM
2003; Imperial College Press; Volume: 02; Issue: 01 Linguagem: Inglês
10.1142/s0219635203000159
ISSN1757-448X
Autores Tópico(s)DNA and Biological Computing
ResumoJournal of Integrative NeuroscienceVol. 02, No. 01, pp. 125-145 (2003) No AccessBASIC PRINCIPLES OF THE KIV MODEL AND ITS APPLICATION TO THE NAVIGATION PROBLEMROBERT KOZMA and WALTER J. FREEMANROBERT KOZMADivision of Computer Science, The University of Memphis, Memphis, TN 38152, USACorresponding author. and WALTER J. FREEMANDivision of Neurobiology, University of California at Berkeley, Berkeley, CA 94720-3200, USAhttps://doi.org/10.1142/S0219635203000159Cited by:52 PreviousNext AboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack CitationsRecommend to Library ShareShare onFacebookTwitterLinked InRedditEmail AbstractEEG measurements indicate the presence of common-mode, coherent oscillations shared by multiple cortical areas. In previous studies the KIII model has been introduced, which interprets the experimental observations as nonlinear, spatially distributed dynamical oscillations of locally coupled neural populations. KIII can account for the fast and robust classification and pattern recognition in sensory cortices. In order to describe selection of action, planning, and spatial orientation functions, in this paper we expand KIII into the KIV model. KIV approximates the operation of the corticostriatal-hippocampal system. KIV consists of three KI, eight KII and three KIII components, including sensory and cortical systems, as well as the hippocampus, amygdala, and the septum. KIV implements various types of dynamic neural activities. The neural activity patterns determine the emergence of global spatial encoding to implement the orientation function of a simulated animal. Our results indicate the mechanisms, which we believe support the generation of cognitive maps in the hippocampus based on the sensory input-based destabilization of cortical spatio-temporal patterns.In this paper, we describe the conceptual design of the KIV model. We outline the biological background and motivation of the basic principles that are applied to design the KIV computational model. We use the KIV model to explain how the hippocampal neural circuitry functions are constructed and controlled by the corticostriatal-hippocampal loops, supplemented with specific subcortical units. In the second part, we implement these principles using the example of the hippocampal formation as a KIII unit. We demonstrate the learning and navigation principles using the Evolving Multi-module Mobile Agent (EMMA) in 2D software environment.Keywords:Neurodynamicscortexhippocampusspatio-temporal EEGKIII and KIV modelchaos References Ankaraju P., The Hierarchy of k Sets: From Pattern Recognition to Navigation. Msc. Thesis, University of Memphis, 2002 . Google ScholarA. Arleo and W. Gerstner, Biol. Cybern. 83, 287 (2000). Crossref, Medline, ISI, Google ScholarJ. M. Barrie, W. J. Freeman and M. D. Lenhart, J. Neurophysiol. 76, 520 (1996). 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HarterImplementing reinforcement learning in the chaotic KIV model using mobile robot AIBOR. Kozina and S. Muthu Recommended Vol. 02, No. 01 Metrics History Received 9 March 2003 Revised 15 April 2003 KeywordsNeurodynamicscortexhippocampusspatio-temporal EEGKIII and KIV modelchaosPDF download
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