Silicon synapse implements multiple neural computational primitives

Synapses are highly specialized structures that transmit information between neurons. When an action potential generated by a neuron reaches a presynaptic terminal, a cascade of events produces a flow of ionic currents into or out of the postsynaptic neuron’s membrane, with a characteristic time course that can last up to several hundreds of milliseconds.1 Modeling the detailed dynamics of postsynaptic currents can be a crucial step for learning neural codes and encoding spatio-temporal patterns of spikes.2 However, both software computational models and VLSI (very large silicon integration) implementations of neural systems have often neglected the dynamic aspects of synaptic currents. Modeling the temporal dynamics of each individual synapse in a network of integrate and fire (I&F) neurons can be very onerous in terms of silicon real-estate for dedicated VLSI implementations. A compromise between highly detailed models of synaptic dynamics and no dynamics at all is to use computationally efficient models that account for the basic macroscopic properties of synaptic transmission. We recently proposed a novel VLSI synaptic circuit, the differential-pair integrator (DPI),3 that implements one of these efficient models based on exponentials4 and supports a wide range of synaptic properties. The design of the DPI synapse was inspired by a series of similar circuits proposed in the literature: these collectively share many of the advantages of our solution but individually lack one or more of the features of our design.3 Figure 1 shows the schematic diagram of the silicon synapse. The basic DPI block reproduces the functionality of ligandgated AMPA (α-amino-3-hydroxy-5-methylisoxazole-4propionic acid) receptors. Assuming subthreshold operation and Figure 1. The schematic diagram of the silicon synapse is shown above. The functional parts of the circuit implement exponential ligand-gated postsynaptic current generation (DPI), short term depression (STD), NMDA (N-methyl-D-aspartate) postsynaptic-receptor voltage gating and conductance-based functionality (G).