# An auto-scaling wide dynamic range current to frequency converter for real-time monitoring of signals in neuromorphic systems

## TL;DR

This paper introduces a compact, auto-scaling current-to-frequency converter for real-time monitoring of neuromorphic system signals, covering a wide dynamic range from pico-Amps to micro-Amps, and demonstrated through experimental CMOS implementation.

## Contribution

It presents a novel self-timed asynchronous circuit that automatically adjusts its scale for linear, wide-range current measurement in neuromorphic systems.

## Key findings

- Successfully measured neural dynamics with the circuit
- Demonstrated linear frequency response over 6 decades of current
- Implemented and tested in 180 nm CMOS process

## Abstract

Neuromorphic systems typically employ current-mode circuits that model neural dynamics and produce output currents that range from few pico-Amperes to hundreds of micro-Amperes. On-line real-time monitoring of the signals produced by these circuits is crucial, for prototyping and debugging purposes, as well as for analyzing and understanding the network dynamics and computational properties. To this end, we propose a compact on-chip auto-scaling Current to Frequency Converter (CFC) for real-time monitoring of analog currents in mixed-signal/analog neuromorphic electronic systems. The proposed CFC is a self-timed asynchronous circuit that has a wide dynamic input range of up to 6 decades, ranging from pico-Amps to micro-Amps, with high current measurement sensitivity. To produce a linear output frequency response, while properly covering the wide dynamic input range, the circuit automatically detects the scale of the input current and adjusts the scale of its output firing rate accordingly. Here we describe the proposed circuit and present experimental results measured from multiple instances of the circuit, implemented using a standard 180 nm CMOS process, and interfaced to silicon neuron and synapse circuits for real-time current monitoring. We demonstrate how the circuit is suitable for measuring neural dynamics by showing the converted response properties of the chip silicon neurons and synapses as they are stimulated by input spikes.