Adjusting Neuron Models in Neuromimetic ICs using the Differential Evolution Algorithm

Laure Buhry (1) , Sylvain Saïghi (1) , Wajdi Ben Salem (1) , And Sylvie Renaud (1)

1 IMS - Laboratoire de l'intégration, du matériau au système

This paper presents an original method to adjust parameters for a neuromimetic IC based on neuron conductance-based models (Hodgkin-Huxley formalism). To adjust the chip, we use a Metaheuristic, the Differential Evolution algorithm (DE). We detail the DE for its implementation in our hardware neural simulator. The DE estimates in the same time all the parameters of one ionic channel. We discuss about the DE performance for each channel. We conclude by mentioning the future applications of this technique in chip design and neuron modeling.

Mots clés: Neuromimetic ICs; automated tuning; Hodgkin-Huxley model; Differential Evolution algorithm

Domaines: Electronique; Optimisation et contrôle [math.OC]; Neurosciences [q-bio.NC]

Laure Buhry, Sylvain Saïghi, Wajdi Ben Salem, And Sylvie Renaud. Adjusting Neuron Models in Neuromimetic ICs using the Differential Evolution Algorithm. 4th IEEE EMBS Conference on Neural Engineering, Apr 2009, Antalya, Turkey. ISBN 978-1-4244-2073-5, pp 681-684. ⟨hal-00381814⟩