Abstract
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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This work was presented in part at the 14th International Symposium on Artificial Life and Robotics, Oita, Japan, February 5–7, 2009
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Fernando, S., Matsuzaki, S. & Marasinghe, A. Modeling towards homeostatic plasticity in neuronal activities. Artif Life Robotics 14, 262 (2009). https://doi.org/10.1007/s10015-009-0667-0
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DOI: https://doi.org/10.1007/s10015-009-0667-0