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This book opens up new possibilities. It includes a basically simple Graphical User Interface (GUI) that can be used in Microsoft Windows (and in fact uses it for the examples). I rate it with 4 stars instead of 5, because the instructions in the examples are for those experienced with NEURON. For beginners like myself, it would help to say which buttons should be clicked and which keys pressed.

This book describes the NEURON simulation system, which can be accessed for installation and instructions at the NEURON web site. Simulation implies using the realistic Hodgkin-Huxley neuron. NEURON was initially for individual neurons, but it has now been extended to networks.

For those who believe in the classical physical science of the 19th century, including physics, chemistry, thermodynamics, and the differential equations in which they are expressed, NEURON has a special meaning. The Hodgkin-Huxley neuron extended classical physical science to a wide range of neuron types and species. The reductionist work of Eric Kandel explained many types of synapses at the molecular level, and therefore explains the connection of neurons in a network in terms of classical physical science.

Our special interest is in networks of interneurons. The most accessible mammalian networks are those in the olfactory bulb of the rat. For this special class, classical physical science, using NEURON, extends into neurobiology. It DEFINES a physically possible network structure. It is likely that evolution will have exploited at least part of this structure to extend order. This possibility is there. It is real. And it is begging for study.

This work will not require a supercomputer. From the deterministic point of view of classical physical science, there is no magic in statistically large numbers of cells. Two dozen or less should be enough to display emerging order.

The NEURON Book Overview

Assuming no previous knowledge of computer programming or numerical methods, The NEURON Book provides practical advice on how to get the most out of the NEURON software program. Although written primarily for neuroscientists, teachers and students, readers with a background in the physical sciences or mathematics and some knowledge about brain cells and circuits, will also find it helpful. Covering details of NEURON's inner workings, and practical considerations specifying anatomical and biophysical properties to be represented in models, this book uses a problem-solving approach that includes many examples to challenge readers.

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