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Foundations of Cellular Neurophysiology (MIT Press), by Daniel Johnston, Samuel Miao-Sin Wu
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with simulations and illustrations by Richard Gray Problem solving is an indispensable part of learning a quantitative science such as neurophysiology. This text for graduate and advanced undergraduate students in neuroscience, physiology, biophysics, and computational neuroscience provides comprehensive, mathematically sophisticated descriptions of modern principles of cellular neurophysiology. It is the only neurophysiology text that gives detailed derivations of equations, worked examples, and homework problem sets (with complete answers).Developed from notes for the course that the authors have taught since 1983, Foundations of Cellular Neurophysiology covers cellular neurophysiology (also some material at the molecular and systems levels) from its physical and mathematical foundations in a way that is far more rigorous than other commonly used texts in this area.
- Sales Rank: #761985 in Books
- Published on: 1994-11-02
- Ingredients: Example Ingredients
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x 1.80" w x 8.00" l, 3.58 pounds
- Binding: Hardcover
- 710 pages
Review
This book is a treasure. It offers lucid, quantitative treatments of many key topics in cellular neurophysiology. It will be an invaluable source for students as well as workers in the field.
(Denis Baylor, MD, Professor and Chairman, Department of Neurobiology, Stanford University School of Medicine)Cellular neurophysiology is a field of biophysics, and must be studied in a quantitative manner, Foundations of Cellular Neurophysiology by Daniel Jonston and Samuel Wu offers an excellent guide to those who want to study neurophysiology quantitatively. By introducing calculus and simple mathematics in small steps, the authors describe neuronal events in an accurate yet understandable way.
(Akimichi Kaneko, MD, Professor, Department of Physiology, Keio University School of Medicine) About the Author
All of the authors teach at Baylor College of Medicine. Daniel Johnston is Professor and Director of Graduate Studies in the Division of Neurosciences; he is also Professor in the Department of Neurology and Molecular Physiology and Biophysics. Samuel Miao-Sin Wu is Professor of Opthalmology, Molecular Physiology and Biophysics, and Neuroscience. Richard Gray is Research Assistant Professor in the Division of Neuroscience.
Most helpful customer reviews
6 of 6 people found the following review helpful.
This book is terrible.
By Harrisonized
In fact, it was so terrible I felt motivated to write a review for it. There are several things that you should be aware of before buying this book.
1. In the introduction, the authors state, "The only prerequisite we have found necessary is for the student to have had (fairly recently) a calculus course that includes some differential equations." This is a straight up lie. What the author actually meant is, "For our own convenience, we've removed every derivation and reasoning that involves math beyond the level of differential equations." For example, they briefly throw a surface integral early on and then it's never mentioned again. Why did they even bother? I come from a physics background, and I've seen my fair share of math. A lot of stuff is missing. The derivation of Fick's law that comes from vector calculus is omitted. For an infinite cable with current impulse at x=0, t=0, the derivation requires Fourier transforms. Hence, it was omitted. They didn't even MENTION that you should set the cable equation equal to I_0 δ(x), and they called it a current STEP. It's really sloppy, especially when they omit where they obtained their boundary conditions.
2. Also in the introduction, "A major problem we encountered when writing this book was in choosing the proper nomenclature... We tried where possible to use the practice that is common in physics and engineering..." This is another lie. The book is so confusing to read precisely because their choices of units are out of whack. The surface integral I mentioned earlier is ∫E.dA = 4πq. So the authors seriously thought standard units are Gaussian units? The authors also make some serious flaws in choosing their variables. For example, on page 62, they define I_m = I_0/4πa^2, where 4πa^2 is the surface area of a sphere, and I_0 is a current injection (charge/time). Hence, I_m now has the units of current density (current/area). WHY DID YOU PICK THE SAME VARIABLE TO REPRESENT TWO DIFFERENT THINGS? There are further problems with definitions. In the derivation of the cable equation, r_in and r_out are meant to have the units of resistance/length, and r_m are meant to have units of resistance*length. With these units in place, λ = sqrt(r_m/(r_in+r_out)) would have the correct unit of length, appropriate because exponentials be unitless functions. Then, later in the book I see these variables arbitrarily defined as R_in = πa^2 _in and R_m = 2πa r_m. Under this definition, the length constant would have units of sqrt(length). That makes absolutely no sense. Normally, one would include a constant as a scaling factor when making these unfounded definitions (unfounded because the authors never explained where these definitions came from).
3. A lot of the more complex steps in the derivations are annoying to read. Some areas of sloppiness include omitting variables (like r_out) that they say they could "just add back later." Why don't they just do the derivation with the extra variable, and then if they don't need it, throw it away? It makes it so much more confusing to read when they add back the extra term seemingly out of nowhere. Also, they make a lot of pointless replacement variables everywhere without actually showing an equation defining the variable (they just stick the replacement into the equation and explain it in words instead). They use * (usually used for complex conjugates) when they actually meant the value at t=0 or the value at x=0. They make pointless switches like μ to u and back. There are long stretches of unnecessary algebraic manipulation, because the author doesn't seem to have ever learned how to group together variables that always appear together. For example, in the appendix section about op amps, they take eight lines to finally figure out that V_out = -R_f/R_1 Vin, when it could have taken as few as three steps. In the Goldman-Hodkin-Katz derivation, they favor separation of variables over integrating factors when the latter takes far fewer steps and is easier to remember. They also never explain how they chose their limits of integration.
4. They waste a lot of space explaining unnecessary things like hyperbolic trig functions and voltage as a "driving force". One could argue that this is meant for the layman who doesn't have a physics background, but someone who doesn't understand voltage shouldn't be reading this book anyway, and they won't learn what a voltage is by reading the crappy explanation provided by this book.
Unfortunately, I can't say whether or not this book is bad because all of its competitors are worse, or because it's just bad. I haven't seen other textbooks, but seriously this book is terrible. I've been relying mostly on internet sources so far, but finding them is cumbersome, and then I have to write what I found into my book so I can actually read it. I paid so much for this book. I only have it because it's the recommended text and the professor doesn't teach at all. I can't imagine how the other biology majors without the math backgrounds are getting on in this course.
I'm giving it two stars. One for the fact that the content is there, despite how crappy it is, and the other having good print quality.
14 of 17 people found the following review helpful.
Dense and confusing
By Arnie Layne
This book covers a lot of material. The quality varies from chapter to chapter. Figures are sprinkled here and there with very little explanation of what they mean. Additionally, there is not much consistency between figures. This book might be serve as a good companion to a course, but it's virtually useless for self study.
My background is engineering and neuroscience, but I still found the math to be poorly explained. If you're trying to learn about biophysics and cellular neurophysiology, pick another book. If you're unfortunate enough to have this book assigned to you for a class, make sure you attend the lectures.
The index is also terrible and virtually useless for anything that I've tried to look up. The only good thing about the book is that it references a lot of stuff, so you know where to look.
One star is for the breadth of topics covered and one is for the references. The Matisse drawing on the cover is also a nice touch.
7 of 11 people found the following review helpful.
Understand the biophysics of excitable cells
By A Customer
You don't really have to hold a degree in mathematics or physics to understand cellular biophysics quantitavely; at least not with this book.
Clearly written, concise, self-contained, begins with the very basic knowledge of ion transport through semi-permeable membranes, moves to electrical properties of membranes, and then to passive and active properties of neuronal membranes, all in a very didactic and intuitive approach.
Of special interest are the chapters on stochastic analysis and formulation of single channel function, and on the relationship between calcium dynamics and transmitter release.
This text is essential for students interested in pursuing graduate studies in electrophysiology, cellular neuroscience, and in computational neuroscience.
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