AdvancedCompNeuro (Biol636, Biol436)

Advanced Computational Neuroscience

Biol 636 / Biol 436

Spring 2019

NJIT HONOR CODE:

All Students should be aware that the Department of Mathematical Sciences takes the NJIT Academic Honor Code very seriously and enforces it strictly. This means there must not be any forms of plagiarism, i.e., copying of homework, class projects, or lab assignments, or any form of cheating in quizzes and exams. Under the Honor Code, students are obligated to report any such activities to the Instructor.
Please re-read Article III of the Academic Honor Code, which describes conducts that are considered unacceptable (cheating, violating the US Copyright law, etc).

Instructor: Horacio G. Rotstein

E-mail: horacio at njit edu

Course Description:

Modeling and computational analysis of biological neuronal networks and related topics including analysis of neural data and paramter estimation of neuronal models. The course consists of lectures, scientific paper presentations and computational work. Students are expected to develop an independent modeling/computational project by the end of the semester. This course is a continuation of "Introduction to Computational Neuroscience".

Reference books:

“Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems” by P. Dayan & L. Abbott – The MIT Press (2001) , 1st edition– ISBN: 0-262-04199-5.
"An Introduction to Modeling Neuronal Dynamics" by C. Borgers - Springer (2017), 1st edition - ISBN 978-3-319-51171-9
“Dynamical Systems in Neuroscience: The Geometry of Excitability and Bursting” by E. M. Izhikevich – The MIT Press (2007), 1st edition – ISBN: 0-262-09043-8.
"Mathematical Foundations of Neuroscience", by G. B. Ermentrout & D. H. Terman - Springer (2010), 1st edition. ISBN 978-0-387-87707-5.

Class meets:

Mon & Wed: 11:30 - 12:50 CKB 212

Office hours:

TBA / By appointment

Grading Policy:

Midterm projects: ................................................. 40%
Class participation: .............................................. 20%

Final project / presentation: ................................ 40%

Please note that the University Drop Date deadline will be strictly enforced

Project Policy
Projects will consist of modeling and simulation work on the topics discussed in class. The goal of the project is to learn new material. Project assignments will be posted on this course website (see below).

A number of project assignments will be given out during the semester

Projects will be distributed taking into account the interests of the participants (students)

Projects reports will be handed in on the published due date.

Project presentations are expected to be brief and convey the main ideas about the topic, the results and the implications.

Late project reports will not be accepted

The source code used in all the computations related ot the project MUST accompany the submitted report.

Upon request, students must be able to explain their results and codes

Class Policies:

Attendance and Participation:

Students must attend all classes.
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

Makeup Policy: There will be no make up projects, except in rare and extenuating situations where the student has a legitimate reason for missing a project presentation. Students that are unable to satisfy any of the requirements of the course for legitimate reasons must present written verifiable proof of the reason for missing component of the course (e.g., a doctor's note, police report, court notice), clearly stating the date AND times of mitigating problem. This should be accompanied by a request and certification by the Dean of Students.

Cellular Phones: All cellular phones, beepers and other electronic devices must be switched off during class and exam times (except when specifically allowed by the instructor).

Chatting in class using electronic devices will not be tolerated.

Course Material

Projects

Course Outline:

Week Topics of the Class Notes

1
Introduction
Brief review of single cell dynamics

2
Models of Synaptic Dynamics
Basic models of Network Dynamics
LN-13
LN-14
LN-15

3
Data analysis and spike-train statistics

4
Data analysis and spike-train statistics

5
Firing rate models of neuronal networks

6
Response of neurons to periodic inputs: resonance and entrainment

7
Synchronization

8
Neuronal oscillations

9
Neuronal oscillations

10
Response of neurons to periodic inputs: resonance and entrainment

11
Central pattern generators

12
Synaptic plasticity

13
Project Presentations

14
Project Presentations

15
Project Presentations

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Federated Department of Biological Sciences.
New Jersey Institute of Technology (NJIT) / Rutgers University.

Horacio
Last modified: Sun Oct 31 13:16:02 EDT 2010

*Week*	*Topics of the Class*	*Notes*
1	Introduction Brief review of single cell dynamics
2	Models of Synaptic Dynamics Basic models of Network Dynamics	LN-13 LN-14 LN-15
3	Data analysis and spike-train statistics
4	Data analysis and spike-train statistics
5	Firing rate models of neuronal networks
6	Response of neurons to periodic inputs: resonance and entrainment
7	Synchronization
8	Neuronal oscillations
9	Neuronal oscillations
10	Response of neurons to periodic inputs: resonance and entrainment
11	Central pattern generators
12	Synaptic plasticity
13	Project Presentations
14	Project Presentations
15	Project Presentations