Silicon synaptic adaptation mechanisms for homeostasis and contrast gain control

We explore homeostasis in a silicon integrate-and-fire neuron. The neuron adapts its firing rate over time periods on the order of seconds or minutes so that it returns to its spontaneous firing rate after a sustained perturbation. Homeostasis is implemented via two schemes. One scheme looks at the...

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Veröffentlicht in:IEEE transaction on neural networks and learning systems 2002-11, Vol.13 (6), p.1497-1503
Hauptverfasser: Shih-Chii Liu, Minch, B.A.
Format: Artikel
Sprache:eng
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Zusammenfassung:We explore homeostasis in a silicon integrate-and-fire neuron. The neuron adapts its firing rate over time periods on the order of seconds or minutes so that it returns to its spontaneous firing rate after a sustained perturbation. Homeostasis is implemented via two schemes. One scheme looks at the presynaptic activity and adapts the synaptic weight depending on the presynaptic spiking rate. The second scheme adapts the synaptic "threshold" depending on the neuron's activity. The threshold is lowered if the neuron's activity decreases over a long time and is increased for prolonged increase in postsynaptic activity. The presynaptic adaptation mechanism models the contrast adaptation responses observed in simple cortical cells. To obtain the long adaptation timescales we require, we used floating-gates. Otherwise, the capacitors we would have to use would be of such a size that we could not integrate them and so we could not incorporate such long-time adaptation mechanisms into a very large-scale integration (VLSI) network of neurons. The circuits for the adaptation mechanisms have been implemented in a 2-/spl mu/m double-poly CMOS process with a bipolar option. The results shown here are measured from a chip fabricated in this process.
ISSN:1045-9227
2162-237X
1941-0093
2162-2388
DOI:10.1109/TNN.2002.804224