Modeling towards homeostatic plasticity in neuronal activities

The capacity to re-establish a normal rhythm after an excitation while adapting to external or internal stimuli is a process of great complexity. We propose an agent-based framework to model the homeostatic plasticity in neuronal activity incorporating the concept of selforganization. Our model prov...

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Bibliographic Details
Published inArtificial life and robotics Vol. 14; no. 2; pp. 262 - 265
Main Authors Fernando, Subha, Matsuzaki, Shuichi, Marasinghe, Ashu
Format Journal Article
LanguageEnglish
Published Japan Springer Japan 01.11.2009
Subjects
Artificial Intelligence
Computation by Abstract Devices
Computer Science
Control
Mechatronics
Original Article
Robotics
Homeostasis
Agent
Self-organization
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Summary:The capacity to re-establish a normal rhythm after an excitation while adapting to external or internal stimuli is a process of great complexity. We propose an agent-based framework to model the homeostatic plasticity in neuronal activity incorporating the concept of selforganization. Our model provides the ability for neuroagents to adapt themselves in a series of activities after the excitements of synaptic inputs in a similar way to the nervous system, hence allowing the creation of diversification and a competitive environment.
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ISSN:1433-5298
1614-7456
DOI:10.1007/s10015-009-0667-0