Title :
A Conductance-Based Silicon Neuron with Dynamically Tunable Model Parameters
Author :
Saïghi, S. ; Tomas, J. ; Bornat, Y. ; Renaud, S.
Author_Institution :
IXL Lab., Bordeaux I Univ., Talence
Abstract :
This paper presents an analog neuromimetic ASIC. It integrates Hodgkin-Huxley (HH) model types, computed in real-time and in analog continuous mode. We developed a library of sub-circuits calculating the elementary mathematical functions encountered in the HH models. Those sub-circuits are organized to form the model set of equations, in which all numerical parameters are dynamically tunable via a mixed analog-digital interface. Neural activity examples are presented to validate the library elements and illustrate the diversity of models simulated by a single ASIC
Keywords :
bioelectric phenomena; electric admittance; elemental semiconductors; mixed analogue-digital integrated circuits; neurophysiology; physiological models; silicon; Hodgkin-Huxley model; Si; analog neuromimetic ASIC; conductance-based silicon neuron; dynamically tunable model parameters; mixed analog-digital interface; neural activity; Analog computers; Application specific integrated circuits; Biological system modeling; Biomembranes; Equations; Integrated circuit modeling; Libraries; Neurons; Silicon; Tunable circuits and devices;
Conference_Titel :
Neural Engineering, 2005. Conference Proceedings. 2nd International IEEE EMBS Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
0-7803-8710-4
DOI :
10.1109/CNE.2005.1419613
