Please note that it is my professional obligation and responsibility to report any academic misconduct to the Dean of Students Office. Any student found in violation of the code by cheating, plagiarizing or using any online software inappropriately will result in disciplinary action. This may include a failing grade of F, and/or suspension or dismissal from the university. If you have any questions about the code of Academic Integrity, please contact the Dean of Students Office at dos@njit.edu.
NJIT HONOR CODE:
Academic Integrity is the cornerstone of higher education and is central to the ideals of this course and the university. Cheating is strictly prohibited and devalues the degree that you are working on. As a member of the NJIT community, it is your responsibility to protect your educational investment by knowing and following the academic code of integrity policy that is found at:
Academic Honor Code - University Policy on Academic Integrity.
Instructor:
Horacio G. Rotstein
E-mail:
horacio at njit edu
A mathematical and computational introduction to the biophysical mechanisms
that underlie physiological functions of single neurons and synapses.
Topics include voltage-dependent channel gating mechanisms, the Hodgkin-Huxley
model for membrane excitability, repetitive and burst firing, nerve impulse
propagation in axons and dendrites, single- and multi-compartmental modeling,
synaptic transmission, calcium handling dynamics and calcium dependent
currents and processes, dynamical systems tools for the analysis of mechanisms
of neural activity.
Textbook:
"An Introductory Course in Computational Neuroscience", by P. Miller - MIT PRess (2018), 1st edition, ISBN: 978-0260238256.
Recommended Books:
"Mathematical Foundations of Neuroscience", by G. B. Ermentrout & D. H. Terman - Springer (2010), 1st edition. ISBN 978-0-387-87707-5.
"Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting",
by Eugene M. Izhikevich. The MIT Press, 2007. ISBN 0-262-09043-8
"Foundations of Cellular Neurophysiology", by Daniel Johnston and Samuel M.-S.
Wu. The MIT Press, 1995. ISBN 0-262-10053-3.
"Biophysics of Computation - Information processing in single neurons", by
Christof Koch. Oxford University Press, 1999. ISBN 0-19-510491-9.
"Theoretical Neuroscience: Computational and Mathematical Modeling of Neural
Systems", by Peter Dayan and Larry F. Abbott. The MIT Press,2001.
ISBN 0-262-04199-5
Class meets:
Tue: 6:00pm - 8:50pm
Midterm project presenttions:
TBA (in class)
Office hours:
Homework, quizzes & class participation: ..................
40%
Projects / Presentations: ..............................................
30%
Midterm exam: .............................................................
30%
Biol432 & Math430 (Undergraduate):
Homework, quizzes & class participation: ..................
40%
Midterm exam: ..............................................................
30%
Final Exam: ..................................................................
30%
.
Please note that the University Drop Date deadline will be
strictly enforced
TBA / By appointment (Also available in Webex, Zoom & Slack)
Grading Policy:
Biol635 & Math635 (Graduate):
Homework Policy
Homework will consist of modeling and simulations exercises on the topics discussed in class. Homework assignments will be posted on this course website (see below).
A number of assignments will be given out during the semester
Assignments must be submitted on canvas
Late homework will not be accepted
The source code used in your calculations MUST accompany the submitted homework
Upon request, students must be able to explain their results and codes
Class Policies:
Absences from class will inhibit your ability to fully participate in class discussions and problem solving sessions and, therefore, affect your grade
Tardiness to class is very disruptive to the instructor and students and will not be tolerated
Chatting in class using electronic devices will not be tolerated.
Week | Topics of the Class | Notes | |
|
|
Introduction to the course
Introduction to Computational Neuroscience and neural dynamics Passive membrane properties - The passive membrane equation | LN-01 |
|
|
Ordinary differential equations (ODEs) - Review of analytical methods
Ordinary differential equations (ODEs) - Review of numerical methods |
LN-04
|
|
| Dynamics of the passive membrane equation | LN-05 |
|
|
Integrate-and-fire models
The Hodgkin-Huxley model I | |
|
|
The Hodgkin-Huxley model II
The cable equation | LN-08 |
|
|
The cable equation II
Introduction to dynamical systems methods for neural models Reduced one- and two-dimensional neural models |
LN-09
|
|
| One-dimensional neural models: Phase-space analysis I | LN-10 |
|
| Two-dimensional neural models: Phase-space analysis I | LN-11 |
|
| Two-dimensional neural models: Phase-space analysis II | LN-11 |
|
|
Subthreshold oscillations: Two- and three-dimensional models
and Subthreshold and suprathreshold resonance | |
|
| Bursting: three-dimensional models | LN-12 |
|
|
Synaptic Dynamics
Network Dynamics | LN-13 |
|
| Project Presentations | |
|
| Project Presentations | |
|
| Project Presentations |
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Department of Mathematical Sciences(DMS).