Neurophysiology of a VLSI Spiking Neural Network: LANN21
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 3 - Volume 3
IEEE Transactions on Neural Networks
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Electronic devices modeling the behavior of neural systems interacting with a natural environment are mainly composed of sensory devices and coupled spiking neural networks. In this context, the possibility to apply theoretical predictions on populations of analog VLSI neurons is aimed in view of their quantitative control. The purpose of this work is to state robust and scalable methods to obtain a quantitative match between experiments and theory for the spiking activity of non-interacting analog VLSI neurons. The decoupled neural dynamics is the starting point for the quantitative description of network coupled conditions. An empirical measure of the capacity, by which the VLSI neurons integrate the currents, an automatic calibration of the injected currents and few basic formulas allow the complete control of the neural dynamics.