CISC 3250: Systems Neuroscience



Class times: Monday and Thursday, 10:00 – 11:15am, Keating Hall (KE) 114
Instructor: Prof. Daniel D. Leeds (my homepage)
Office: JMH 332
E-mail:
Office hours: Mon 12-1pm, Thurs 12-1pm

Full syllabus is available here
Course announcements and assignments will be posted over the course of the semester.

Course text: No good book for our course. "Fundamentals of Computational Neuroscience" (suggested); "Computational Cognitive Science" (suggested)

Matlab: We will be introduced to the Matlab computing environment in this course and use it selectively in homework assignments across the semester. You may use the copy available in the JMH 302 computer lab, but it also would be beneficial for you to download the Student license for $50 from Mathworks.

Sections below:

  1. Announcements
  2. Supplemental readings
  3. Slides
  4. Resources
  5. Assignments

Announcements:
May 4, 10:30am: Office hours today, 12-1pm, on our Google Hangouts
Apr 22, 3:15pm: As announced in class, the final will be May 7 (Thursday) 10am-noon. It will be cumulative and in the same format as Quiz 2.
Apr 20, 1:15am: No class April 16; Quiz 2 will be Apr 20.
Mar 30, 1:15am: No class April 16; Quiz 2 will be Apr 20.
Mar 17, 1:15am: As announced by Fordham, we will be meeting online throughout the rest of the semester. Keep your eyes on your e-mails. Generally we will meet through Blackboard Collaborate, with phone callin option. Notes and audio will be posted after each class.
Mar 17, 1:15am: As announced by Fordham, we will be meeting online throughout the rest of the semester. Keep your eyes on your e-mails. Generally we will meet through Blackboard Collaborate, with phone callin option. Notes and audio will be posted after each class.
Supplemental readings:
All readings are in Trappenberg, and they are optional.
TopicReadingEquations
Philosophy of neural modelingChapter 1: all (predominantly for perspective)
The neuron — biology and input/output behaviorChapter 2: 2.1, 2.2 (through 2.2.2);
Chapter 3: 3.1 (through 3.1.2), 3.3, 3.4.1, 3.4.5, 3.5		 3.1-3.4; 3.33, 3.35; 3.44; 3.45, 3.46
Learning in the neuronChapter 4: 4.1, 4.3 (through page 101), 4.4.3 4.3, 4.8, 4.10; 4.24, 4.27, 4.28, 4.29
Neural systems and neuroanatomyChapter 5: 5.1
Representations in the brainChapter 7: 7.1, 7.5.1, 7.5.4 7.25-7.28, 7.40-7.42
Motor control9.5, 9.6 (particularly 9.6.4)
Perception(Chapter 10: 10.1 ... optional, we will cover a simpler model in class)
Attention-related cellular mechanisms: 3.5.1, 3.5.3
Online chapter 6		 3.45


Slides:
Check slides after each lecture - I sometimes update the slides with additional content based on class discussion

Lecture 1, The neuron biology and behavior.
Animation: movement of action potential down the axon
Lecture M, Intro Matlab; spikeExample.mat; spikePlot.m
Lecture 2, Learning in the neuron
Lecture 3, Cortical organization and data formats
Lecture M2, Vector/matrix data in Matlab; S1_brain2019.mat
Lecture 4, Representations in the Brain
Feb 25th lecture audio and digital white board 1 2 3 4 5
Updated lecture slides after Feb 26th class
Lecture 5, Motor control
Updated lecture slides after Mar 23

Lecture M3, Functions
Updated lecture slides after Mar 12 (function answers now posted!!)

Lecture on Mar 12: audio, "white board"
Lecture on Mar 23: audio, "white board"
Lecture 6, Memory
Updated lecture slides after Mar 23
Updated lecture slides after Mar 26
Updated lecture slides after Mar 30
Updated lecture slides after Apr 2

Lecture on Mar 26: audio, "white board"
Lecture on Mar 30: audio, "white board"
Lecture M4. Projection/correlation analyses S11_localizer.mat
Updated lecture slides after Apr 2
Updated lecture slides after Apr 6

Lecture on Apr 2: audio, video "white board"
Lecture on Apr 6: Video link was sent out by e-mail, "white board"
Lecture 7, Perception
Updated lecture slides after Apr 20
Updated lecture slides after Apr 23
Updated lecture slides after Apr 27

Lecture on Apr 20: Video link was sent out by e-mail, "white board"
Lecture on Apr 23: Video link was sent out by e-mail, "white board"
Lecture on Apr 27: Video link will be made Apr 27 night I hope, "white board"
Lecture 8, The Big Picture
Lecture on Apr 30: Video link will be made Apr 30 night I hope, "white board"

Resources:
Practice Materials
Quiz 1 practice questions and answers


Below are exam 1 practice questions! Questions are randomly color-coded. I recommend trying to answer one set of colored questions first (for example, red questions), review the answers to those questions, and then move on to another set of colored questions (for example, green).
Note: The term "template recognition" used in one of the practice questions is synonymous with the term "prototype recognition."


Below are final exam practice questions

Assignments:
Homework 1 - due Feb 3 (In Q1, updated so now τ=0.1 ; In Q5, I made a few corrections to the code, made in red.)
HW1 Answers
87-96.5 A range
77.5-87 B range
68-77.5 C range
58.5-67 D range

Homework 2 - due Feb 24, Matlab data: BrainData.mat
HW2 answers

Quiz 1 answers
31.5-35 A range
27-31.5 B range
22.5-27 C range
18-22.5 D range


Homework 3 - due Mar 26; submit by blackboard!

HW3 answers
No curve needed; 90-100 A range, 80-90 B range, etc

Midterm answers
69-79 A range
60-69 B range
50.5-60 C range
40.5-50.5 D range


Homework 4 - due Apr 6 (MS Word version); submit by blackboard! Question 5 now posted too!

HW4 answers - corrections to 2b made on April 17 afternoon; correction to 1b made on April 18 evening
No curve needed; 90-100 A range, 80-90 B range, etc


Homework 5 - due never, recommend you complete by Apr 30 for your own edification; S1pic.mat MAT file fMRI data
HW 5 answers

Quiz 2 answers coming soon (link not yet active)
38-43 A range
33-38 B range
27-33 C range
21-27 D range
Out of 45 points
lateral weights-and-neural dynamics question asked for extra insights beyond what was covered in class, students not penalized for missing that insight (max grade put down to 43)