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Title

Neuromorphing-Building Brains in Silicon
Author

Dr. Kwabena Boahen
Organization: University of Pennsylvania
Department: Bioengineering
Education level

Graduate
Objectives

The following objectives are achieved through analytical (deriving mathematical solutions), computational (simulating device and circuit behavior), and experimental (testing fabricated chips) exercises:

* introduce neurobiologists to the physical constraints on neural computation-like noise, wiring, and energy;

* introduce engineers to the unrivaled performance of biological systems-achieved despite physical constraints;

* develop physical models of neural computation by emulating the structure as well as the function of the nervous system
Materials

The following books are augmented by relevant journal articles, and by write-ups prepared by the instructor:

* Analog VLSI and Neural Systems by Mead * From Neuron to Brain by Kuffler Nicholls and Martin
Description

We recreate the structure and function of neural systems in silicon using very large scale integration (VLSI) complementary metal-oxide-semiconductor (CMOS) technology. To build these neuromorphic systems, we proceed from the device level, through the circuit level, to the system level. At the device level, we mimic electrodiffusion of ions through membrane channels with electrodiffusion of electrons through transistor channels. At the circuit level, we derive minimal implementations of synaptic interaction, dendritic integration, and active membrane behavior. At the system level, we synthesize the spatiotemporal dynamics of the cochlea, the retina, and early stages of cortical processing. This course is intended to draw advanced students from multiple disciplines with an interest in multidisciplinary approaches. Students are encouraged to pool their expertise in different areas by working in a group.

Topics: Overview / VLSI CMOS Technology: From Transistors to Chips / Systems Neuroscience: From Ion-Channels to Microcircuits / Electrodiffusion / Ion-Channels-The Nernst-Planck Equation / Transistors-The Drift-Diffusion Equation / Parallels between Ion-Channels and Transistors / Single-Cell Model: Satisfying the Goldman-Hodgkin-Katz Equation / Synaptic Interaction / Single-Transistor Gap Junctions / Single-Transistor Chemical Synapses / Temporal and Spatial Integration / Dendrite/Soma Model: Nonlinear Diode-Capacitor Dynamics / Cell-Syncytium Model: Satisfying Laplace's Equation / Active Membrane Properties / Spike-Generation Mechanism: Modeling Fast Na- and K-Channels / Spike Frequency Adaptation: Modeling Ca-dependent K-Channels / Spatiotemporal Dynamics / Finite-Element Analog of Basilar Membrane and Cochlear Fluid / Reciprocally-Connected Two-Layer Model of Outer Retina / Single-Chip Systems / A Cochlea on a Chip / A Retina on a Chip / Multichip Systems / Interchip Communication Using Addressed Pulses / A Silicon Optic Nerve / Virtual Wiring for Receptive Fields and Projective Fields
Subject

*Engineering
URL

http://www.neuroengineering.upenn.edu/curriculum/be526.htm