An accurate and flexible analog emulation of AdEx neuron dynamics in silicon

2022/09/19 by Sebastian Billaudelle, Billaudelle, Sebastian, Johannes Weis +5 · 2 citations
Computer Science · Engineering · #Advanced Memory and Neural Computing #CCD and CMOS Imaging Sensors #FOS: Computer and information sciences #Neural Networks and Reservoir Computing #Neural and Evolutionary Computing (cs.NE)

paper · pdf · doi:10.48550/arxiv.2209.09280

openalex publication_date 2022/09/19 · openalex created_date 2022/09/23 · openalex updated_date 2026/08/01

Abstract

Analog neuromorphic hardware promises fast brain emulation on the one hand and an efficient implementation of novel, brain-inspired computing paradigms on the other. Bridging this spectrum requires flexibly configurable circuits with reliable and reproducible dynamics fostered by an accurate implementation of the targeted neuron and synapse models. This manuscript presents the analog neuron circuits of the mixed-signal accelerated neuromorphic system BrainScaleS-2. They are capable of flexibly and accurately emulating the adaptive exponential leaky integrate-and-fire model equations in combination with both current- and conductance-based synapses, as demonstrated by precisely replicating a wide range of complex neuronal dynamics and firing patterns.

Cited by

• The BrainScaleS-2 multi-chip system: Interconnecting continuous-time neuromorphic compute substrates
• A Linear Implementation of an Analog Resonate-and-Fire Neuron

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