Neural Comput - Spike-timing-dependent construction.

Tópicos

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Resumo

Spike-timing-dependent construction (STDC) is the production of new spiking neurons and connections in a simulated neural network in response to neuron activity. Following the discovery of spike-timing-dependent plasticity (STDP), significant effort has gone into the modeling and simulation of adaptation in spiking neural networks (SNNs). Limitations in computational power imposed by network topology, however, constrain learning capabilities through connection weight modification alone. Constructive algorithms produce new neurons and connections, allowing automatic structural responses for applications of unknown complexity and nonstationary solutions. A conceptual analogy is developed and extended to theoretical conditions for modeling synaptic plasticity as network construction. Generalizing past constructive algorithms, we propose a framework for the design of novel constructive SNNs and demonstrate its application in the development of simulations for the validation of developed theory. Potential directions of future research and applications of STDC for biological modeling and machine learning are also discussed.

Resumo Limpo

spiketimingdepend construct stdc product new spike neuron connect simul neural network respons neuron activ follow discoveri spiketimingdepend plastic stdp signific effort gone model simul adapt spike neural network snns limit comput power impos network topolog howev constrain learn capabl connect weight modif alon construct algorithm produc new neuron connect allow automat structur respons applic unknown complex nonstationari solut conceptu analog develop extend theoret condit model synapt plastic network construct general past construct algorithm propos framework design novel construct snns demonstr applic develop simul valid develop theori potenti direct futur research applic stdc biolog model machin learn also discuss

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