While some analytic mathematic expressions for nerve (and muscle) membrane properties preceded the monumental work of Hodgkin & Huxley, it was their equations for the ionic channels in the membrane of the giant axon of the squid which set computational neuroscience in motion. Since then not only have variations of sodium and potassium channels been described but many other types of ion channels have been found. Today molecular neurobiologist are making a great variety of hybrid and "designer" channels, leading to great strides in understanding the molecular features underlying their properties.
In this period our knowledge of the detailed morphology of many nerve cells has been vastly increased by an array of technological improvements. Video techniques have revived light microscopy by improving contrast and "resolution". This, along with computer databases of geometric details for components of neurons, allows a full 3-dimension reconstruction, including the location of dendritic spines and synaptic inputs. Electron microscopy can provide finer details where necessary.
More recently, the speed and memory capacity and the availability of desktop computers has been exploding. The technological advances in the manufacture of their components has helped reduce their price and the resulting increase in purchases has driven automation of high volume chips; the resulting positive feedback allows further cost reduction.
Concurrent with these developments in hardware, computer software has been
advancing rapidly because the volume of sales has allowed the investment in powerful
programming tools. This, in turn, with the large volume of sales allows the price of software to
be reduced. The net result is a very rapid growth in the power and speed of computer programs.
For the presently very limited field of computation neuroscience the emergence of the software
development tools has allowed the construction of several powerful simulation tools. A group of
neural simulators were demonstrated in an exhibit booth at the 1993 meeting of the Society of
DSTOOL by John Guckenheimer, Cornell Univ., dynamical systems on Unix machines
GENESIS by Jim Bower, Cal. Tech., general purpose simulator for neural systems on Unix machines
NBC by Jean-Francois Vibert, Fac. de Med. St-Antoine, Paris, Network simulation and analysis on Unix and VMS machines
NEMOSYS by John Tromp, Univ. Cal., Berkeley, complex single neurons on Unix machines
NEUROGRAPH by Peter Wilke, Univ. Erlangen, Germany, Simulation of artificial neural networks on Unix, DOS, VMS machines
NEURON by Michael Hines, Duke Univ., Simulations of biologically realistic single neurons and small networks on PCs and Unix machines
NEURONC by Rob Smith, Univ. Penn., compartmental simulations of large neural circuits on Unix machines
NODUS by Eric De Schutter, Univ. Antwerp, Belgium, simulation of small networks of neurons on Macintosh machines
NSL by Alfredo Weitzenfeld, Univ. Sou. Cal., simulation of large networks on Unix machines
SNNAP by John Byrne, Univ. Texas, Houston, Simulator for neural networks on Unix machines
SWIM by Orjan Ekeberg, Royal Inst. Tech., Stockholm, simulation of network of few compartment model neurons on Unix machines
Now, at the time of this writing, the early 1990s, we see that the convergence of software
tools, computer power, morphology, and ionic channel data can allow us to carry out
meaningful simulations of full neurons. Actually the present computer and software power are
sufficient to carry out simulations of nerve networks in great detail. The morphological detail of
several neuron types is available. The major problem in making definitive simulations is the lack
the necessary detailed information on the locations and densities of the various types of
channels and other membrane mechanisms. Thus the only way to proceed is to employ
informed guesses and to attempt to fit electrical records from different kinds of experiments
(e.g. voltage clamp, current clamp of the soma, orthodromic stimuli, antidromic invasion).
A graphical representation of my perception of the history of the increase in knowledge of ionic channels and neuron morphology overlaid with that of computer hardware and software.
It seems to me that we are on the verge of new era of insight into the functioning of nerve cells and networks thereof which will be gained by using all of these tools in an environment of tight coupling between experimentation and modeling. The purpose of the development of the simulation program NEURON and the writing of this manual is to make a contribution to this effort.