Silicon-Neuron Design: A Dynamical Systems Approach
John V. Arthur,Kwabena Boahen +1 more
Reads0
Chats0
TLDR
A circuit design example, a positive-feedback integrate-and-fire neuron fabricated in 0.25-μm CMOS, is presented, and it is demonstrated that it can be configured to exhibit desired behaviors, including spike-frequency adaptation and two forms of bursting.Abstract:
We present an approach to design spiking silicon neurons based on dynamical systems theory. Dynamical systems theory aids in choosing the appropriate level of abstraction, prescribing a neuron model with the desired dynamics while maintaining simplicity. Further, we provide a procedure to transform the prescribed equations into subthreshold current-mode circuits. We present a circuit design example, a positive-feedback integrate-and-fire neuron, fabricated in 0.25-μm CMOS. We analyze and characterize the circuit, and demonstrate that it can be configured to exhibit desired behaviors, including spike-frequency adaptation and two forms of bursting.read more
Citations
More filters
Journal ArticleDOI
Neurogrid: A Mixed-Analog-Digital Multichip System for Large-Scale Neural Simulations
Ben Varkey Benjamin,Peiran Gao,Emmett McQuinn,Swadesh Choudhary,Anand R. Chandrasekaran,Jean-Marie Bussat,Rodrigo Alvarez-Icaza,John V. Arthur,Paul A. Merolla,Kwabena Boahen +9 more
TL;DR: Neurogrid as discussed by the authors is a real-time neuromorphic system for simulating large-scale neural models in real time using 16 Neurocores, including axonal arbor, synapse, dendritic tree, and soma.
Journal ArticleDOI
A scalable neuristor built with Mott memristors
TL;DR: A neuristor built using two nanoscale Mott memristors, dynamical devices that exhibit transient memory and negative differential resistance arising from an insulating-to-conducting phase transition driven by Joule heating exhibits the important neural functions of all-or-nothing spiking with signal gain and diverse periodic spiking.
Posted Content
A Survey of Neuromorphic Computing and Neural Networks in Hardware.
Catherine D. Schuman,Thomas E. Potok,Robert M. Patton,J. Douglas Birdwell,Mark Edward Dean,Garrett S. Rose,James S. Plank +6 more
TL;DR: An exhaustive review of the research conducted in neuromorphic computing since the inception of the term is provided to motivate further work by illuminating gaps in the field where new research is needed.
Journal ArticleDOI
Recent Advances in Transistor-Based Artificial Synapses
TL;DR: A review of recent advances in transistor‐based artificial synapses is presented to give a guideline for future implementation of synaptic functions with transistors and the main challenges and research directions of transistor‐ based artificial synapse are presented.
Journal ArticleDOI
Physics for neuromorphic computing
TL;DR: Striking results that leverage physics to enhance the computing capabilities of artificial neural networks, using resistive switching materials, photonics, spintronics and other technologies are reviewed.
References
More filters
Journal ArticleDOI
A quantitative description of membrane current and its application to conduction and excitation in nerve
A. L. Hodgkin,A. F. Huxley +1 more
TL;DR: This article concludes a series of papers concerned with the flow of electric current through the surface membrane of a giant nerve fibre by putting them into mathematical form and showing that they will account for conduction and excitation in quantitative terms.
Book
Nonlinear dynamics and Chaos
TL;DR: The logistic map, a canonical one-dimensional system exhibiting surprisingly complex and aperiodic behavior, is modeled as a function of its chaotic parameter, and the progression through period-doubling bifurcations to the onset of chaos is considered.
Book
Dynamical Systems in Neuroscience
TL;DR: This book explains the relationship of electrophysiology, nonlinear dynamics, and the computational properties of neurons, with each concept presented in terms of both neuroscience and mathematics and illustrated using geometrical intuition, providing a link between the two disciplines.
Book
Analog VLSI and Neural Systems
TL;DR: This chapter discusses a simple circuit that can generate a sinusoidal response and calls this circuit the second-order section, which can be used to generate any response that can be represented by two poles in the complex plane, where the two poles have both real and imaginary parts.
Journal ArticleDOI
Which model to use for cortical spiking neurons
TL;DR: The biological plausibility and computational efficiency of some of the most useful models of spiking and bursting neurons are discussed and their applicability to large-scale simulations of cortical neural networks is compared.
Related Papers (5)
A quantitative description of membrane current and its application to conduction and excitation in nerve
A. L. Hodgkin,A. F. Huxley +1 more
A million spiking-neuron integrated circuit with a scalable communication network and interface
Paul A. Merolla,John V. Arthur,Rodrigo Alvarez-Icaza,Andrew S. Cassidy,Jun Sawada,Filipp Akopyan,Bryan L. Jackson,Nabil Imam,Chen Guo,Yutaka Nakamura,Bernard Brezzo,Ivan Vo,Steven K. Esser,Rathinakumar Appuswamy,Brian Taba,Arnon Amir,Myron D. Flickner,William P. Risk,Rajit Manohar,Dharmendra S. Modha +19 more