The term “neuron” comes from the name used to describe the conducting nerve cell of the brain, spinal cord, and nerves. Human neurons consist of a cell body containing a nucleus, several nerve processes, and an axon or nerve fiber. The association between the Neuron Chip and the human nerve cell is the similarity of the three parts of a human nerve cell and the Neuron transistor
ip’s three, 8-bit CPUs. One C P U handles protocol for communication to and from the chip, another handles the application progr
am, and a third handles input/output information.
1- Neuron :
A neuron (pronounced /ˈnjʊərɒn/ N(Y)OOR-on, also known as a neurone or nerve cell) is an excitable cell in the nervous system that processes and transmits information by electrochemical signaling. Neurons are the core components of the brain, the vertebrate spinal cord, theinvertebrate ventral nerve cord, and the peripheral nerves. A number of specialized types of neurons exist: sensory neurons respond to touch, sound, light and numerous other stimuli affecting cells of the sensory organs that then send signals to the spinal cord and brain. Motor neuronsreceive signals from the brain and spinal cord and cause muscle contractions and affect glands. Interneurons connect neurons to other neurons within the same region of the brain or spinal cord. Neurons respond to stimuli, and communicate the presence of stimuli to the central nervous system, which processes that information and sends responses to other parts of the body for action. Neurons do not go through mitosis, and usually cannot be replaced after being destroyed, although astrocytes have been observed to turn into neurons as they are sometimespluripotent.
Source : http://en.wikipedia.org/wiki/Neuron
2- Transistor :
A transistor is a semiconductor device commonly used to amplify or switch electronic signals. A transistor is made of a solid piece of asemiconductor material, with at least three terminals for connection to an external circuit. A voltage or current applied to one pair of the transistor’s terminals changes the current flowing through another pair of terminals. Because the controlled (output) power can be much more than the controlling (input) power, the transistor provides amplification of a signal. Some transistors are packaged individually but most are found in integrated circuits.
The transistor is the fundamental building block of modern electronic devices, and its presence is ubiquitous in modern electronic
strategy in building artificial neurons. Rather than attempt to determine every aspect of how neurons communicate, he’s chosen to emulate their behavior, bombarding live neurons from rat hippocampus tissue with every conceivable type of electrical input, and observe what output emerges from the cell.
The neuron is a complex system, and each cortical neuronis itself complex. The scale of the cortex is immense, withan estimated 100 billion neurons interconnected by trillionsof synapses. In addition, each neuron performs nonlinear,location-specific dendritic computations on the potentials gen-erated at each synapse. Much of the complexity of the neuralbehavior is due to the computations involving the post-synapticpotentials arising from the stimulation of excitatory andinhibitory synapses . These potentials combine on the den-dritic arbor in complex ways. Dendritic computations includelinear, sublinear and superlinear additions and subtractionsof postsynaptic potentials depending on the relative locationsand nature of the synapses, affecting the probability and thefrequency of neural firing.The complexity of these neural computations presents en-gineering challenges to the construction of a future syntheticcortex. Of course, a future intelligent synthetic cortex builtwith neuronal circuits that captured every detail of a biolog-ical neuron’s physiology would be impractical. Nevertheless,certain aspects of synaptic and dendritic behavior contributein an important way to learning via short and long-termmechanisms. Capturing those aspects might make it possibleto construct a future intelligent synthetic cortex.A nanotechnological solution could allow the constructionof a synthetic cortex containing trillions of synapses. Carbonnanotubes that can behave as metallic wires as well as FETsare a promising technological option. Carbon nanotubes maysupport the scale of a synthetic cortex, being extremely small(a few nm. in diameter). Current flow is largely ballistic (com-parable to the flow of electrons in free space), capacitances arein attofarads, and rise and fall times in picoseconds.
The bath was contacted with a 3 3 30 mm platinum electrode. An ACvoltage from a function generator (model 33120A, Hewlett-Packard,Böblingen, Germany) with an amplitude V0 STIM was applied to the chip against the bath potential. It was superposed by a DC bias to the chip of 1 V1 2 V0 STIM. The frequency was chosen near the presumed characteristic frequency fJ. In some experiments we applied a train of rectangular voltagepulses with an amplitude of V0 STIM ž ĸ6 V, a chip bias of 17 V, and a pulse duration of 4 ms
NEURON TRANSISTOR PROJECT ABSTRACT THIS PROJECT INVOLVES DESIGNING ELECTRONICS FOR IN-VITRO NEURAL RECORDING SYSTEMS.