CISC 3250: Systems Neuroscience
Class times: Monday and Thursday, 10:00 – 11:15am, John Mulcahy Hall (JMH) 342
Instructor: Prof. Daniel D. Leeds (my homepage)
Office: JMH 328A
E-mail: 
Office hours: Tuesday 2 – 3pm, Thursday 12:00 – 1:00pm, and by appointment
Course website: http://storm.cis.fordham.edu/leeds/cisc3250/
Suggested text: "Fundamentals of Computational Neuroscience", T.P. Trappenberg, Second edition, 2010.
While the Trappenberg text is quite good, it also uses a lot more
math than we will require in the course. Throughout the semester, I
will highlight and explain the equations to study, and focus on
conceptual understandings of what these equations are trying to
capture.
Further optional text: "Computational Cognitive Neuroscience", R.C. O'Reilly, 2012.
The O'Reilly text provides another set of perspectives and
illustrations on several (but not all) important topics we will cover
throughout the semester. It is conveniently available for free online
in its entirety.
Course description: This course studies information
processing in biological neural systems from computational and
anatomical perspectives. Components of natural intelligence, such as
visual perception, learning, memory, and motion, are modeled as
achieved in the brain. Artificial and biological neural networks are
considered and compared, spanning from tens of neurons to networks of
regions collaborating across the brain. Data analysis methods also are
pursued, to quantify the activities of neural systems and to connect
to the growing field of brain-machine interfaces.
Objectives: To understand information processing in
biological neural systems from computational and anatomical
perspectives. A student who successfully completes this course will be
able to:
- Identify the functions of key components of the nervous system
- Model how neurons interact with one another
- Use computational tools to examine neural data
Software: Assignments will include the use of Scilab, an
environment for numeric analyses and computational modeling. It will
be available in the computer lab and is free for download at
http://www.scilab.org. We will
learn how to use this program in class.
Attendance and class participation: It is important to
attend every class, and to arrive on time. One unexcused/unexplained
absence is permitted for the semester. Attendance will be taken
regularly. Please actively participate in class since this will make
the course more interesting for everyone! Ask questions if you are
unsure about something.
Laptop policy: I generally encourage students to avoid using laptops during class — the temptation for distraction can be hard to fight. That said, I do presently allow laptops to be used for note-taking or reading online course materials.
Course assignments: There will be 4 – 6 homeworks
assigned for the course. The homeworks usually will be announced at
least 4 days before they are due, e.g., a homework announced on
Thursday may be due the following Monday. All assignments must be
turned in on time.
Academic honesty: All work produced in this course should
be your own unless it is specifically stated that you may work with
others. You may discuss the assignment problems with other students
generally, but may not provide complete solutions to one
another. Copying of assignments is never acceptable and will be
considered a violation of Fordham's academic integrity
policy. Violations of this policy will be handled in accordance with
university policy which can include automatic failure of the
assignment and/or failure of the
course. See Fordham's
Undergraduate Policy on Academic Integrity for more information.
Exams: There will be two mid-term exams – one in
February, one in April – the exact dates will be announced at
least 3 weeks in advance of the exam. There will be a final in the
week of May 4th.
Timing conflicts: If you have a significant issue and
cannot complete an assignment on time, or cannot attend class on a
certain day, whenever feasible let me know beforehand – I tend to
be reasonable in such cases. Examples of significant issues include
personal illness (with doctor's note) or a religious holiday on an
announced exam day. In general, let me know of any significant issues
that affect your performance early on.
Grading: The percentages given below are guidelines for
both the student and instructor and may be changed as needed to
reflect circumstances in the course. Any changes that occur during the
semester will be minor.
| Participation | 10% |
| Homeworks | 25% |
| Mid-terms | 40% |
| Final exam | 25% |
Overview of topics:
- Philosophy of neural modeling
- The neuron — biology and input/output behavior
- Learning in the neuron
- Neural systems and neuroanatomy
- Information representation with features in computer science
- Representations in the brain
- Perception
- Memory/learning
- Motor control