Neuromodulation of Neuromorphic Circuits
This work addresses the challenge of precise control in neuromorphic circuits for applications in brain-inspired computing, though it appears incremental as it builds on existing neuromorphic principles.
The authors tackled the problem of controlling neuromorphic circuits by developing a novel methodology that uses parallel voltage-controlled current sources to shape I-V curves, enabling robust and accurate control that mimics biological neuromodulation, as demonstrated in SPICE simulations.
We present a novel methodology to enable control of a neuromorphic circuit in close analogy with the physiological neuromodulation of a single neuron. The methodology is general in that it only relies on a parallel interconnection of elementary voltage-controlled current sources. In contrast to controlling a nonlinear circuit through the parameter tuning of a state-space model, our approach is purely input-output. The circuit elements are controlled and interconnected to shape the current-voltage characteristics (I-V curves) of the circuit in prescribed timescales. In turn, shaping those I-V curves determines the excitability properties of the circuit. We show that this methodology enables both robust and accurate control of the circuit behavior and resembles the biophysical mechanisms of neuromodulation. As a proof of concept, we simulate a SPICE model composed of MOSFET transconductance amplifiers operating in the weak inversion regime.