Neuromorphic Silicon Neuron Circuits
University of Zurich · ETH Zurich · +18 more institutions
Abstract
Hardware implementations of spiking neurons can be extremely useful for a large variety of applications, ranging from high-speed modeling of large-scale neural systems to real-time behaving systems, to bidirectional brain-machine interfaces. The specific circuit solutions used to implement silicon neurons depend on the application requirements. In this paper we describe the most common building blocks and techniques used to implement these circuits, and present an overview of a wide range of neuromorphic silicon neurons, which implement different computational models, ranging from biophysically realistic and conductance-based Hodgkin-Huxley models to bi-dimensional generalized adaptive integrate and fire…
Citation impact
- FWCI
- 81.88
- Percentile
- 100%
- References
- 119
Authors
20- GIGiacomo IndiveriCorresponding
University of Zurich, ETH Zurich, SIB Swiss Institute of Bioinformatics
- BLB. Linares-Barranco
Centro Nacional de Microelectrónica, Instituto de Microelectrónica de Sevilla
- TJTara Julia Hamilton
UNSW Sydney
- AVAndré van Schaik
University of Sydney
- RERalph Etienne‐Cummings
Johns Hopkins University
Topics & keywords
- Neuromorphic engineering
- Computer science
- Ranging
- Very-large-scale integration
- Electronic circuit
- Implementation
- Range (aeronautics)
- Computer architecture