Bio-inspired, bio-compatible, reconfigurable analog CMOS circuits
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This work details CMOS, bio-inspired, bio-compatible circuits which were used as synapses between an artificial neuron and a living neuron and between two living neurons. An intracellular signal from a living neuron was amplified, an integrate-and-fire neuron was used as a simple processing element to detect the spikes, and an artificial synapse was used to send outputs to another living neuron. The key structure is an electronic synapse which is based around a floating-gate pFET. The charge on the floating-gate is analogous to the synaptic weight and can be modified. This modification can be viewed as similar to long-term potentiation and long-term depression. The modification can either be programmed (supervised learning) or can adapt to the inputs (unsupervised learning). Since the technology to change the floating-gate weight has greatly improved, these weights can be set quickly and accurately. Intrinsic floating-gate learning rules were explored and the ability to change the synaptic weight was shown.