2018/05/31 by Luka Ribar, Rodolphe Sepulchre · 39 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Engineering · Neuroscience · Physics and Astronomy · #Advanced Memory and Neural Computing #Amplifier #Circuit design #Electrical element #Electronic circuit #Interconnection #Neuromodulation #Neuromorphic engineering #Neuroscience and Neural Engineering #Nonlinear system #Spice #Transconductance #cs.NE #cs.SY #eess.SY #q-bio.NC #stochastic dynamics and bifurcation
paper · pdf · doi:10.1109/tcsi.2019.2907113
published in IEEE Transactions on Circuits and Systems I Regular Papers 66(8), 3028-3040 (Institute of Electrical and Electronics Engineers)
openalex created_date 2018/11/02 · arxiv created 2019/03/21 · openalex publication_date 2019/04/24 · arxiv updated 2020/11/19 · openalex updated_date 2026/08/05
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-Vcurves) of the circuit in prescribed timescales. In turn, shaping thoseI-Vcurves 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.