VLSI implementation of a conductance-based multi-synapse using switched-capacitor circuits

For neuromorphic ICs, the implemented synaptic dynamics play an important role in the complexity achievable when running networks on the overall IC. One of these ingredients for realistic dynamics are conductance-based synapses, which in contrast to current-based synapses let a neuron adapt in various ways to its input characteristics. Another ingredient is classical neuronal spike-frequency adaptation. Both are usually realized in fully-analog subthreshold circuits, making them hard to port to modern sub-100nm technologies. In contrast, we present a compact switched-capacitor (SC) model of a conductance-based synapse that can be widely configured to accurately depict e.g. NMDA, GABA or AMPA type synapses. The SC approach is inherently easy to port between technologies and its digital part benefits fully from technology scaling. We show how this synapse circuit can also be utilized to endow a neuron with spike-frequency adaptation (SFA).