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Spatial memory based on an STDP driven neural network

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dc.conference.date7-9 de septiembre
dc.conference.title4th Scientific School on Dynamics of Complex Networks and their Application in Intellectual Robotics (DCNAIR)
dc.contributor.authorZharinov, Alexey
dc.contributor.authorMakarov Slizneva, Valeriy
dc.contributor.authorKazntsev, Victor B.
dc.contributor.authorLobov, Sergei
dc.date.accessioned2023-06-17T10:14:18Z
dc.date.available2023-06-17T10:14:18Z
dc.date.issued2020
dc.description.abstractWe propose a model of spatial memory implemented in a Spiking Neural Network (SNN) and test it on a robot moving in an environment with neutral and harmful regions. Neurons in the SNN play the role of place cells, and their population dynamics determines the robot movements. We show that STDP rearranges the couplings in the SNN and forms spatial memory similar to cognitive maps associated with the negative experience. Then, the robot learns to avoid harmful zones.
dc.description.departmentDepto. de Análisis Matemático y Matemática Aplicada
dc.description.facultyFac. de Ciencias Matemáticas
dc.description.refereedFALSE
dc.description.statuspub
dc.eprint.idhttps://eprints.ucm.es/id/eprint/74917
dc.identifier.urihttps://hdl.handle.net/20.500.14352/8947
dc.language.isoeng
dc.rights.accessRightsopen access
dc.subject.cdu517
dc.subject.cdu612.8
dc.subject.keywordSNN
dc.subject.keywordCognitive maps
dc.subject.keywordPlace cells
dc.subject.keywordVector field of synaptic connections
dc.subject.keywordVector field of functional connections
dc.subject.keywordNeurorobotics
dc.subject.ucmAnálisis matemático
dc.subject.ucmNeurociencias (Medicina)
dc.subject.unesco1202 Análisis y Análisis Funcional
dc.subject.unesco2490 Neurociencias
dc.titleSpatial memory based on an STDP driven neural network
dc.typeconference paper
dspace.entity.typePublication
relation.isAuthorOfPublicationa5728eb3-1e14-4d59-9d6f-d7aa78f88594
relation.isAuthorOfPublication.latestForDiscoverya5728eb3-1e14-4d59-9d6f-d7aa78f88594

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