The Neuron Book

by Nicholas T. Carnevale , Michael L. Hines

• ISBN13: 9780521843218
• ISBN10: 0521843219
• Edition: 1st
• Format: Hardcover
• Copyright: 2006-02-06
• Publisher: Cambridge University Press

Summary

The authoritative reference on NEURON, the simulation environment for modeling biological neurons and neural networks that enjoys wide use in the experimental and computational neuroscience communities. This book shows how to use NEURON to construct and apply empirically based models. Written primarily for neuroscience investigators, teachers, and students, it assumes no previous knowledge of computer programming or numerical methods. Readers with a background in the physical sciences or mathematics, who have some knowledge about brain cells and circuits and are interested in computational modeling, will also find it helpful. The NEURON Book covers material that ranges from the inner workings of this program, to practical considerations involved in specifying the anatomical and biophysical properties that are to be represented in models. It uses a problem-solving approach, with many working examples that readers can try for themselves.

Table of Contents

Preface	xvii
Acknowledgments	xix
A tour of the Neuron simulation environment	1	(31)
Modeling and understanding	1	(1)
Introducing Neuron	1	(1)
State the question	2	(1)
Formulate a conceptual model	3	(2)
Implement the model in Neuron	5	(13)
Starting and stopping Neuron	6	(1)
Bringing up a CellBuilder	6	(2)
Entering the specifications of the model cell	8	(1)
Topology	8	(2)
Subsets	10	(2)
Geometry	12	(1)
Biophysics	13	(3)
Saving the model cell	16	(1)
Executing the model specification	16	(2)
Instrument the model	18	(3)
Signal sources	18	(2)
Signal monitors	20	(1)
Set up controls for running the simulation	21	(1)
Save model with instrumentation and run control	21	(2)
Run the simulation experiment	23	(1)
Analyze results	24	(8)
References	30	(2)
The modeling perspective	32	(4)
Why model?	32	(1)
From physical system to computational model	33	(3)
Conceptual model: a simplified representation of a physical system	33	(1)
Computational model: an accurate representation of a conceptual model	33	(1)
An Example	34	(2)
Expressing conceptual models in mathematical terms	36	(19)
Chemical reactions	36	(8)
Flux and conservation in kinetic schemes	37	(2)
Stoichiometry, flux, and mole equivalents	39	(2)
Compartment size	41	(2)
Scale factors	43	(1)
Electrical circuits	44	(6)
Cables	50	(5)
References	54	(1)
Essentials of numerical methods for neural modeling	55	(35)
Spatial and temporal error in discretized cable equations	56	(6)
Analytic solutions: continuous in time and space	56	(1)
Spatial discretization	57	(3)
Adding temporal discretization	60	(2)
Numerical integration methods	62	(21)
Forward Euler: simple, inaccurate and unstable	62	(2)
Numerical instability	64	(2)
Backward Euler: inaccurate but stable	66	(2)
Crank-Nicholson: stable and more accurate	68	(2)
Efficient handling of nonlinearity	70	(2)
Adaptive integration: fast or accurate, occasionally both	72	(1)
Implementational considerations	73	(2)
The user's perspective	75	(5)
Local variable time step method	80	(3)
Discrete event simulations	83	(1)
Error	83	(3)
Summary of NEURON's integration methods	86	(4)
Fixed time step integrators	86	(1)
Default: backward Euler	86	(1)
Crank--Nicholson	86	(1)
Adaptive integrators	87	(1)
CVODE	88	(1)
DASPK	88	(1)
References	88	(2)
Representing neurons with a digital computer	90	(38)
Discretization	90	(2)
How Neuron separates anatomy and biophysics from purely numerical issues	92	(6)
Sections and section variables	92	(1)
Range and range variables	93	(2)
Segments	95	(1)
Implications and applications of this strategy	96	(1)
Spatial accuracy	96	(1)
A practical test of spatial accuracy	97	(1)
How to specify model properties	98	(3)
Which section do we mean?	98	(1)
Dot notation	99	(1)
Section stack	99	(1)
Default section	100	(1)
How to set up model topology	101	(2)
Loops of sections	101	(1)
A section may have only one parent	101	(1)
The root section	101	(1)
Attach sections at 0 or 1 for accuracy	102	(1)
Checking the tree structure with topology ( )	102	(1)
Viewing topology with a Shape plot	103	(1)
How to specify geometry	103	(8)
Stylized specification	104	(1)
3-D specification	105	(2)
Avoiding artifacts	107	(1)
Beware of zero diameter	107	(1)
Stylized specification may be reinterpreted as 3-D specification	108	(3)
How to specify biophysical properties	111	(6)
Distributed mechanisms	111	(1)
Point processes	112	(1)
User-defined mechanisms	113	(1)
Working with range variables	114	(1)
Iterating over nodes	114	(1)
Linear taper	115	(1)
How changing nseg affects range variables	115	(2)
Choosing a spatial grid	117	(11)
A consideration of intent and judgment	118	(3)
Discretization guidelines	121	(1)
The d_lambda rule	122	(4)
References	126	(2)
How to build and use models of individual cells	128	(29)
Graphical user interface vs. hoc code: which to use, and when?	128	(1)
Hidden secrets of the GUI	129	(1)
Implementing a model with hoc	130	(9)
Topology	130	(2)
Geometry	132	(1)
Biophysics	133	(1)
Testing the model implementation	133	(2)
An aside: how does our model implementation in hoc compare with the output of the Cell Builder?	135	(4)
Instrumenting a model with hoc	139	(1)
Setting up simulation control with hoc	139	(2)
Testing simulation control	141	(1)
Evaluating and using the model	141	(1)
Combining hoc and the GUI	141	(13)
No Neuron Main Menu toolbar?	142	(1)
Default section? We ain't got no default section!	142	(2)
Strange Shapes?	144	(1)
The barbed wire model	144	(4)
The case of the disappearing section	148	(3)
Graphs don't work?	151	(1)
Conflicts between hoc code and GUI tools	152	(2)
Elementary project management	154	(3)
Iterative program development	155	(1)
Reference	156	(1)
How to control simulations	157	(26)
Simulation control with the graphical user interface	157	(2)
The standard run system	159	(5)
An outline of the standard run system	160	(1)
Fadvance ( )	160	(1)
advance ( )	161	(1)
step ( )	161	(1)
steprun ( ) and continuerun ( )	162	(1)
run ( )	163	(1)
Details of fadvance ( )	164	(15)
The fixed step methods: backward Euler and Crank--Nicholson	165	(6)
Adaptive integrators	171	(2)
Local time step integration with discrete events	173	(6)
Global time step integration with discrete events	179	(1)
Incorporating Graphs and new objects into the plotting system	179	(4)
References	181	(2)
How to initialize simulations	183	(24)
State variables and STATE variables	183	(2)
Basic initialization in NEURON: finitialize ( )	185	(2)
Default initialization in the standard run system: stdinit ( ) and init ( )	187	(8)
Initial blocks in NMODL	188	(2)
Default vs. explicit initialization of STATEs	190	(1)
Ion concentrations and equilibrium potentials	190	(5)
Examples of custom initializations	195	(12)
Initializing to a particular resting potential	195	(2)
Initializing to steady state	197	(1)
Initializing to a desired state	198	(1)
Initializing by changing model parameters	199	(1)
Details of the mechanism	200	(2)
Initializing the mechanism	202	(4)
Reference	206	(1)
How to expand NEURON's library of mechanisms	207	(58)
Overview of NMODL	207	(1)
Example 9.1: A passive ``leak'' current	208	(6)
The Neuron block	210	(1)
Variable declaration blocks	211	(1)
The PARAMETER block	212	(1)
The ASSIGNED block	212	(1)
Equation definition blocks	213	(1)
The BREAKPOINT block	213	(1)
Usage	214	(1)
Example 9.2: A localized shunt	214	(3)
The Neuron block	215	(1)
Variable declaration blocks	215	(1)
Equation definition blocks	216	(1)
The Breakpoint block	216	(1)
Usage	217	(1)
Example 9.3: An intracellular stimulating electrode	217	(3)
The Neuron block	218	(1)
Equation definition blocks	218	(1)
The Breakpoint block	218	(1)
The Initial block	219	(1)
Usage	219	(1)
Example 9.4: A voltage-gated current	220	(8)
The Neuron block	222	(1)
The Units block	222	(1)
Variable declaration blocks	222	(1)
The Assigned block	222	(1)
The State block	223	(1)
Equation definition blocks	223	(1)
The Breakpoint block	223	(1)
The Initial block	224	(1)
The Derivative block	225	(1)
The Function block	226	(1)
Usage	227	(1)
Example 9.5: A calcium-activated. voltage-gated current	228	(5)
The Neuron block	230	(1)
The Units block	231	(1)
Variable declaration blocks	231	(1)
The Assigned block	231	(1)
The State block	232	(1)
Equation definition blocks	232	(1)
The Breakpoint block	232	(1)
The Derivative block	232	(1)
The Function and Procedure blocks	232	(1)
Usage	233	(1)
Example 9.6: Extracellular potassium accumulation	233	(5)
The Neuron block	235	(1)
Variable declaration blocks	236	(1)
The Parameter block	236	(1)
The State block	236	(1)
Equation definition blocks	236	(1)
The Breakpoint block	236	(1)
The Initial block	236	(1)
The Derivative block	237	(1)
Usage	237	(1)
General comments about kinetic schemes	238	(2)
Example 9.7: Kinetic scheme for a voltage-gated current	240	(5)
The Neuron block	242	(1)
Variable declaration blocks	242	(1)
The State block	242	(1)
Equation definition blocks	243	(1)
The Breakpoint block	243	(1)
The Initial block	243	(1)
The Kinetic block	243	(1)
The Function_Tables	244	(1)
Usage	245	(1)
Example 9.8: Calcium diffusion with buffering	245	(10)
Modeling diffusion with kinetic schemes	246	(4)
The Neuron block	250	(1)
The Units block	250	(1)
Variable declaration blocks	250	(1)
The Assigned block	250	(1)
The State block	250	(1)
Local variables declared outside of equation definition blocks	251	(1)
Equation definition blocks	251	(1)
The Initial block	251	(1)
Procedure factors ( )	252	(1)
The Kinetic block	252	(2)
Usage	254	(1)
Example 9.9: A calcium pump	255	(5)
The Neuron block	255	(1)
The Units block	256	(1)
Variable declaration blocks	256	(1)
The Parameter block	256	(1)
The Assigned block	257	(1)
The Constant block	257	(1)
The State block	257	(1)
Equation definition blocks	257	(1)
The Breakpoint block	257	(1)
The Initial block	258	(1)
The Kinetic block	259	(1)
Usage	260	(1)
Models with discontinuities	260	(3)
Discontinuities in Parameters and Assigned variables	260	(1)
Discontinuities in States	261	(2)
Event handlers	263	(1)
Time-dependent Parameter changes	263	(2)
References	264	(1)
Synaptic transmission and artificial spiking cells	265	(41)
Modeling communication between cells	266	(23)
Example 10.1: Graded synaptic transmission	266	(2)
The Neuron block	268	(1)
The Breakpoint block	269	(1)
Usage	269	(2)
Example 10.2: A gap junction	271	(1)
Usage	272	(1)
Modeling spike-triggered synaptic transmission: an event-based strategy	272	(1)
Conceptual model	273	(1)
The Net Con class	274	(3)
Example 10.3: Synapse with exponential decay	277	(1)
The Breakpoint block	278	(1)
The Derivative block	278	(1)
The Net_Receive block	278	(1)
Usage	278	(2)
Example 10.4: Alpha function synapse	280	(1)
Example 10.5: Use-dependent synaptic plasticity	281	(2)
The Net_Receive block	283	(1)
Example 10.6: Saturating synapses	284	(3)
The Parameter block	287	(1)
The State block	287	(1)
The Initial block	287	(1)
The Breakpoint and Derivative blocks	288	(1)
The Net_Receive block	288	(1)
Artificial spiking cells	289	(17)
Example 10.7: IntFirel, a basic integrate and fire model	290	(1)
The Neuron block	291	(1)
The Net_Receive block	292	(1)
Enhancements to the basic mechanism	292	(5)
Example 10.8: IntFire2, firing rate proportional to input	297	(1)
Implementation in NMODL	298	(3)
Example 10.9: IntFire4, different synaptic time constants	301	(3)
Other comments regarding artificial spiking cells	304	(1)
References	305	(1)
Modeling networks	306	(37)
Building a simple network with the GUI	307	(1)
Conceptual model	308	(1)
Adding a new artificial spiking cell to Neuron	309	(2)
Creating a prototype net with the GUI	311	(13)
Define the types of cells	311	(1)
Create each cell in the network	312	(3)
Connect the cells	315	(1)
Setting up network architecture	315	(1)
Specifying delays and weights	316	(2)
Set up instrumentation	318	(1)
Set up controls for running simulations	319	(3)
Run a simulation	322	(1)
Caveats and other comments	322	(1)
Changing the properties of an existing network	322	(1)
A word about cell names	323	(1)
Combining the GUI and programming	324	(19)
Creating a hoc file from the NetWork Builder	324	(2)
NetGUI default section	326	(1)
Network cell templates	326	(1)
Network specification interface	327	(1)
Network instantiation	328	(1)
Exploiting the reusable code	328	(13)
References	341	(2)
hoc, NEURON's interpreter	343	(20)
The interpreter	344	(1)
Adding new mechanisms to the interpreter	345	(1)
The stand-alone interpreter	346	(4)
Starting and exiting the interpreter	346	(2)
Error handling	348	(2)
Syntax	350	(13)
Names	350	(1)
Keywords	350	(3)
Variables	353	(1)
Expressions	354	(1)
Statements	355	(1)
Comments	355	(1)
Flow control	356	(1)
Functions and procedures	357	(1)
Arguments	358	(1)
Call by reference vs. call by value	359	(1)
Local variables	360	(1)
Recursive functions	360	(1)
Input and output	361	(1)
Editing	362	(1)
Reference	362	(1)
Object-oriented programming	363	(15)
Object vs. class	363	(1)
The object model in hoc	364	(1)
Objects and object references	364	(8)
Declaring an object reference	364	(1)
Creating and destroying an object	365	(1)
Using an object reference	366	(1)
Passing objrefs (and objects) to functions	366	(1)
Defining an object class	367	(1)
Direct commands	368	(1)
Initializing variables in an object	368	(1)
Keyword names	369	(1)
Object references vs. object names	370	(1)
An example of the didactic use of object names	371	(1)
Using objects to solve programming problems	372	(4)
Dealing with collections or sets	372	(1)
Array of objects	372	(1)
List of objects	373	(2)
Encapsulating code	375	(1)
Polymorphism and inheritance	376	(2)
Reference	377	(1)
How to modify Neuron itself	378	(21)
A word about graphics terminology	378	(1)
Graphical interface programming	378	(21)
General issues	380	(1)
A pattern for defining a GUI tool template	381	(2)
Enclosing the GUI tool in a single window	383	(2)
Saving the window to a session	385	(4)
Tool-specific development	389	(1)
Plotting	389	(3)
Handling events	392	(3)
Finishing up	395	(4)
Appendix A1 Mathematical analysis of IntFire 4	399	(7)
Proof that the estimate is never later than the true firing time	401	(5)
Part 1: If m0 ≤ 0, then m(t)remains < 1	402	(2)
Part 2: If m' > 0, (1 -- m)/m' underestimates the firing time	404	(2)
Appendix A2 Neuron's built-in editor	406	(6)
Starting and stopping	407	(1)
Switching from hoc to emacs	407	(1)
Returning from emacs to hoc	407	(1)
Killing the current command	407	(1)
Moving the cursor	407	(1)
Modes	408	(1)
Deleting and inserting	408	(1)
Blocks of text: marking, cutting, and pasting	408	(1)
Searching and replacing	409	(1)
Text formatting and other tricks	409	(1)
Buffers and file I/O	409	(1)
Windows	410	(1)
Macros and repeating commands	411	(1)
References	411	(1)
Epilogue	412	(1)
Index	413