NEUR 634 Computer Modeling of Neurons and Networks

Spring 2009

Tues/Thurs, 12 - 1:15 PM

Innovation Hall, Room 330

Instructor: Dr. Kim L. Blackwell

Office Location: Krasnow Institute, Room 105

Office Hours: 2-3 pm or by appointment

Course Objectives: To introduce the objectives, philosophy and methodology of neuronal modeling and computational neurophysiology. Topics include how to create models of membrane channels and neurons; how to create networks by connecting neuron models, and how to run simulations of their activity and behavior. The course instructs students in the use and syntax of some of the more popular neural modeling software packages. The computational neuroanatomy component will include up to three modules: one for morphological tracing, one for morphological analysis, and one for morphological simulations and/or network connectivity. Creating and simulating neural models reinforces the concepts learned in NEUR 602, by illustrating how activity patterns are modulated by different types of membrane channels or different types of neuron connections.

Format: The course meets three hours a week, in a combination of lecture and electronic laboratory. The first part of each class will consist of a brief lecture on the neuronal component to be modeled. The lecture for the remaining class will describe how those components are modeled, including specific syntax and interaction with other neuronal components. Each student is expected to repeat on their own computers the modeling commands demonstrated by the instructor.


Required: The Book of GENESIS. Free Internet Edition (2003) Bower and Beeman (free online pdf), The NEURON Book (2006) Carnevale and Hines

Assignments and Grading:

In class model construction (20%): At the end of the class period a copy of the practice commands will be turned in to the instructor.

Homework (40%): Homework will consist of using the commands and components to create novel models or simulations.

Final project (40%): development of a model using one of the software packages presented in class. The student is required to develop the model, run simulations, and write a report describing the model and the simulation results. Projects will be presented orally on the last day of class, or on Tuesday, May 12 (during Final exam period). 

Grading policy: A score of 90 or above generally results in a grade of A- or above, 80 or above corresponds to a B- or above, and 70 or above results in C- or above. The numerical score is only a guideline, and is not absolute. The final grades may be determined on a curve if this is to the students favor and justified in the opinion of the instructor.

Policy regarding missed assignments: Homework may be turned in at most one week late, but there will be an automatic penalty of 10% deducted from the score. If an absence from class is anticipated, homework may be emailed, faxed, or sent in on-time with another student. Make-up exams are not allowed, unless the student has written medical documentation for absence from an exam.

No extra credit will be given.

Honor Code All exams and homework assignments must follow the guidelines of the GMU Honor Code as described in the GMU catalog. Students may use books, notes, and other sources in preparing for exams and homework. However, when taking exams, no books, notes, or student interaction is allowed. Students may work together on homework, but each student must contribute and copying is not allowed. Students may not work together on projects.

If you are a student with a disability and you need academic accommodations, please see me and contact the Office of Disability Resources at 703.993.2474. All academic accommodations must be arranged through that office.          

Syllabus Draft

Homework assignments, and readings for last half of the class will be added later

January 22,27

Overview: Goals of neuronal modeling, Unix operating system

Reading: BoG Chapter 1-3, Tutorials/unixhelp/unixhelp.html, genprog/tutorial1.html, genesis-overview.html



January 29, Feb 3

GENESIS. Creating single compartment models

Reading: /genprog/tut1-lite.html, BoG Chapter 11-13



February 5, 10

GENESIS. Membrane channels and action potentials

BoG: Chapter 4, 14, genprog/tut3-4-lite.html, genprog/chantut.html, cnslecs/cns1.html#HHmodel

tutorial3.g, newtutorial3.g


February 12, 17, 19

GENESIS. Multi-compartment models and using the cell reader

BoG Chapter 5, 15.1, 16, genprog/simplecell-tut.html, cnslecs/cns2a.html#dendrites (up to Modeling Synapses), cnslecs/Cabletut.html



February 24, 26

GENESIS. Synapses

BoG Chapter 6, 15.2, 15.3, genprog/synchan-tut.html, cnslecs/cns2a.html#dendrites (from Modeilng Synapses)



March 3, 5

GENESIS: Neuronal Networks (Rodrigo Oliveira)

BoG Chapter 18, genprog/net-tut.html, Rsnet.g

Include gap junctions? Or time table for “realistic” input spike trains?


Mar 17, 19

GENESIS/Kinetikit/NeuroRD. Plasticity and Signaling pathways

BoG Chapter 10, 15.4, 19, include Hebbsynchans?


March 24, 26

NEURON. Graphical Interface and Multi-compartment models

March 31, April 2

NEURON. Simulation control, graphs, etc

April 7, 9

Morphology: Analyzing neuronal morphology using L-measure (Sridevi Polavaram)


Morphology: Getting neurons from (Maryam Halavi)

April 14, 16

NEURON. Membrane channels (Wonryull Koh)


April 21, 23

NEURON. Synapses


April 28, 30

Automatic parameter searching using Neuron (multiple run-fitter) and Genesis (optimization)

Finish topics listed above, OR

OR, networks using neuron? OR Hebbsynchans? OR time table

May 5