EE585 Spring 2015: Neural Computation


Announcements
  • Final project presentations are scheduled for T Jun 9 13:30-16:00
  • Final exam will be on Th June 4
Assignments
Lectures
  • Download the DyKnow Client onto your personal Windows machine.
  • Lecture 1 (Apr. 2): Defining neural computation.
  • Lecture 2 (Apr. 7): Electrical signalling in the nervous system + characterizing neural firing.
  • Lecture 3 (Apr. 9): Characterizing neural firing.
  • Lecture 4 (Apr. 14): Sensory mapping
  • Lecture 5 (Apr. 21): Sensory encoding / receptive fields.
  • Lecture 6 (Apr 23): Tuning curves and population vector.
  • Lecture 7 (Apr 30): Population vector.
  • Lecture 8 (May 5): Optimal linear filter.
  • Lecture 9 (May 12): Optimal linear filter + midterm review.
  • Lecture 10 (May 14): Optimal linear filter
  • Lecture 11 (May 19): Optimal linear filter
  • Lecture 12 (May 21): Kalman filter overview
  • Lecture 13 (May 26): Kalman filter derivation and implementation
  • Lecture 14 (May 28): Principal component analysis
Supplementary
Data
Other useful links
  • MATLAB Tutorial
    Under "Tutorial Options", go through the following
    • MATLAB examples -> Getting Started with MATLAB
    • MATLAB examples -> Working in The Development Environment
    • MATLAB examples -> Writing a MATLAB program
    • MATLAB examples -> Basic Matrix Operations
    • Getting Started with MATLAB (User's Guide)

Course outline

Date Topic Reading Related Assignment
Th Apr 2 Defining neural computation and biomedical applications of neural computation Nicolelis 2003 - skim sections; Giszter et al. - abstract + skim over section headings; Simeral et al. - abstract + skim over section headings and figures; Supplement on Electrophysiology (Purves et al.); PS 1
T Apr 7 Electrical signalling in the nervous system; Characterizing neuron firing - part I Supplement on Electrophysiology (Purves et al.); Dayan and Abbott 5.1 - 5.3; Dayan and Abbott 1.1­-1.4, 2.2, 7.2 PS 1
Th Apr 9 Characterizing neuron firing Dayan and Abbott 1.1­ - 1.4, 2.2, 7.2 PS 2
T Apr 14 Modelling neuron output; Anatomical mapping of sensory spaces Somatosensory encoding supplement; Visual encoding supplement PS 2
Th Apr 16 Journal article selection, partner selection for end-of-quarter presentation Journal article presentation
T Apr 21 Anatomical mapping of sensory spaces; tuning curves. Dayan and Abbott 1.1­-1.4, 2.2, 7.2; Georgopoulos et al PS 2
Th Apr 23 Tuning curves and population vectors. Dayan and Abbott 1.2, 3.3; Georgopoulos et al PS 3
T Apr 28 Population vectors. Dayan and Abbott 1.2, 3.3; Georgopoulos et al PS 3
Th May 3 Population vectors. Dayan and Abbott 1.2, 3.3; Georgopoulos et al PS 3
T May 5 Optimal linear filtering Dayan and Abbott 2.2, 2.9; Wessberg and Nicolelis PS 4
Th May 7 Midterm exam
T May 12 Optimal linear filtering Dayan and Abbott 2.2, 2.9; Wessberg and Nicolelis PS 4
Th May 14 Optimal linear filtering Dayan and Abbott 2.2, 2.9; Wessberg and Nicolelis PS 4
T May 19 Optimal linear filtering Dayan and Abbott 2.2, 2.9; Wessberg and Nicolelis PS 4
Th May 21 Kalman filtering Kim et al. 2011; Schiff et al. 2008 PS 5
T May 26 Kalman filtering Kim et al. 2011; Schiff et al. 2008 PS 5
Th May 28 Principal component analysis J. Schlens
T June 2 Principal component analysis; information theory J. Schlens; Fellous et al. 2004; Reich et al. 2001