MCP and VLSI Neuron - Introduction

In 1943 Warren S. McCulloch, a neuroscientist, and Walter Pitts, a logician, published "A logical calculus of the ideas immanent in nervous activity" in the Bulletin of Mathematical Biophysics 5:115-133. In this paper McCulloch and Pitts tried to understand how the brain could produce highly complex patterns by using many basic cells that are connected together. These basic brain cells are called neurons, and McCulloch and Pitts gave a highly simplified model of a neuron in their paper. The McCulloch and Pitts model of a neuron, which we will call an MCP neuron for short, has made an important contribution to the development of artificial neural networks -- which model key features of biological neurons. - Wikipedia

VLSI

Analog implementations of neurons in Very Large Scale Integrated (VLSI) silicon technology are a recent development (initially suggested by Mead, 1989), and dedicated analog VLSI implementations of neural circuits have several merits:

A first merit of a silicon neuron is as a neural prosthesis, interfacing with biological neural tissue. Dedicated VLSI implementations (particularly analog VLSI) normally operate in real-time.
A second merit is as a modeling tool. Silicon implementations can run very rapidly (and often in real time), enabling them to work directly with external devices generating signals.
A third merit of a silicon neuron is as a cell in a larger network for neural computation. Again, real-time operation is possible, enabling direct interfacing (and hence real-time interaction) with devices like cameras or sound acquisition devices. - http://www.scholarpedia.org/article/S...

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