Course Identification

Title:

Mathematical Topics in Neuroscience

Code:

20193442

Lecturers and Teaching Assistants

Lecturers:

Prof. Nachum Ulanovsky, Prof. Michail Tsodyks, Dr. Alon Rubin, Dr. Shai Bagon, Prof. David Peleg, Prof. Omri Barak, Prof. Miriam Zacksenhouse

TA's:

Dr. Meytar Zemer Schocken

Course Schedule and Location

Year:

2019

Semester:

Second Semester

When / Where:

Wednesday, 11:15 - 13:00, FGS, Rm C

First Lecture:

27/03/2019

Field of Study, Course Type and Credit Points

Life Sciences: Lecture; Elective; Regular; 2.00 points
Life Sciences (Brain Sciences: Systems, Computational and Cognitive Neuroscience Track): Lecture; Elective; Regular; 2.00 points

Comments

No lecture on June 5th.

Prerequisites

No

Restrictions

Participants:

100

Language of Instruction

English

Attendance and participation

Required in at least 80% of the lectures

Grade Type

Pass / Fail

Grade Breakdown (in %)

Interim:

40%

Final:

60%

Evaluation Type

Other

Scheduled date 1

Date / due date

N/A

Location

N/A

Time

-

Remarks

N/A

Estimated Weekly Independent Workload (in hours)

1

Syllabus

This course will provide a brief and basic introduction to the following mathematical topics that are useful for Systems Neuroscience:

-Dynamical systems (2 lessons, Prof. Misha Tsodyks)

- Dimensionality reduction (2 lessons, Dr. Alon Rubin)

- Control theory (1 lesson, Prof. Miriam Zacksenhouse)

- Recurrent networks (2 lessons, Prof. Omri Barak)

- Graph theory (3 lessons, Prof. David Peleg)

- Deep learning (3 lessons, Dr. Shai Bagon)

Learning Outcomes

Upon successful completion of the course, students:

Will gain familiarity with a number of mathematical topics that are relevant for Systems Neuroscience.

Reading List

None.

Website

N/A