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17
BIOMIMETIC CORTICAL
NANOCIRCUITS
Alice C. Parker, Aaron K. Friesz, and Ko-Chung Tseng
This chapter describes a study of the feasibility of artificial brains in the future and
emphasizes the necessity of using novel nanotechnologies in their implementation.
The focus here is on biomimetic neural models and electronic circuits that
implement those models, considering complexities in modeling biological neural
tissue. Many problems present themselves when considering construction of a
synthetic cortex, the most prominant being capturing biomimetic behavior;
accomodating the scale of neurons, synapses, and axons; emulating the intercon-
nectivity; and modeling the plasticity that underlies learning. Nanotechnologies
offer not only the obvious advantages of scale and complexity, but exhibit the
potential to support interconnectivity due to the inherent 3D nature of some
nanotechnologies. Early experiments demonstrating the potential for self-assembly
and reconfiguration of nanotechnologies provide some evidence that plasticity
might be possible. We have designed an electronic synapse based on carbon
nanotubes and elaborate on our simulation studies that demonstrate the range of
behavior of the synapse. Estimates are given for the size of artificial neural systems
based on CMOS technology in 2021. We predict some upper bounds on neural
interconnections using CMOS nanotechnology.
17.1. INTRODUCTION AND MOTIVATION
Since the early days of vacuum tube and relay electronics, researchers have been
developing electronic neurons designed to emulate neural behavior with electrical
signals that mimic the measured potentials of biological neurons. However, in
the past, the size and cost of available electronics made construction of complex
brain-like structures infeasible due to the scale of
the modeling problem.
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