CSULA EE585, Won

EE585 Spring 2012: Neural Computation

Announcements	On TUE JUNE 5 ONLY, meet in ET B10 (old classroom). Meet in ET C255-E starting Tue May 22, and please BE ON TIME. Midterm exam solutions have been posted. PS3 solutions and solution code have been posted.
Assignments	Problem Set 1: Neural communication and biomedical applications Problem Set 1 Solutions: Neural communication and biomedical applications Problem Set 2: Sensory encoding and neuron firing Problem Set 2 Solutions: Sensory encoding and neuron firing Problem Set 3: Decoding motor information from neural signals. Problem Set 3 Solutions: Decoding motor information from neural signals. Problem Set 3 Solutions: Linear prediction model code. Problem Set 3 Solutions: Linear prediction code. Midterm Exam Solutions
Lectures	Download the DyKnow Client onto your personal Windows machine. Lecture 1 (Apr. 3): Defining neural computation. Lecture 2 (Apr. 5): Electrical signalling in the nervous system + neural computation in the retinal and cochlear prostheses. Lecture 3 (Apr. 10): Intro to computational algorithms - Point and click cursor control. Lecture 4 (Apr. 12): Intro to computational algorithms - Kalman filter and MIMO model. Lecture 5 (Apr. 17): Modelling neuron output + sensory encoding. Lecture 6 (Apr. 19): Sensory encoding / receptive fields. Lecture 7 (Apr. 24): Applications of sensory encoding in the retinal and cochlear prostheses; characterizing neuron firing dynamics. Lecture 8 (Apr. 26): Tuning curves + review of PSTH, firing rate, receptive fields. Lecture 9 (May 1): Population vector. Lecture 10 (May 3): Population vector. Lecture 11 (May 8): Optimal linear filter. Lecture 12 (May 10): Optimal linear filter + midterm review.
Supplementary	Class Syllabus Perspective on BMIs Nicolelis 2003 Biomimetic robotics Giszter et al. BMI neuromotor prosthesisSimeral et al. Retinal prosthesis image processing Asher et al. Memory prosthesis Berger et al. Purves et al. Electrophysiology section 1 Purves et al. Electrophysiology section 2 Purves et al. Electrophysiology section 3 More on BMI decoders Sample papers from the Nicolelis, Donoghue, Schwartz, and Wolpaw groups Visual encoding part I: Purves et al. pp. 179-186 Visual encoding part II: Purves et al. pp. 199-211 Visual encoding part III: Kuffler 1953 Somatosensory encoding: Zhu & Connors 1999 Somatosensory encoding + information theory: von Heimendah et al. 2007 Temporal encoding in visual system + information theory: Reich et al. 2001 (temporal coding of contrast) Temporal encoding: Fellous et al. 2004 Motor encoding: Georgopoulos et al. 1988 Motor decoding: Wessberg et al. 2004 Motor decoding: Schiff et al. 2008 Memory prosthesis Berger et al. 2011 Code for tuning curves: Tuning curve / population vector MATLAB code Supplement on PCA: J. Schlens Muscle synergies: Kutch JJ & Valero-Cuevas FJ 2012 Muscle redundancy: Kutch JJ & Valero-Cuevas FJ 2011 Muller cones in the retina (re-engineering the retina): Lee et al. 2011 Lecture slides on re-engineering the retina: Norberto's lecture slides
Data	Population Vector (PS 3) Data: motorcx_data_forPS3.mat Population Vector (PS 3) Data: continuous_tracking.mat Linear Filter (PS 3) Data: au032003b_bin100.mat Linear Filter (PS 3) Code: linmodel_blanks.m Linear Filter (PS 3) Code: linpred_blanks.m
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
Tu Apr 3	Defining neural computation and biomedical applications of neural computation	Nicolelis 2003; Giszter et al.; Simeral et al.	PS 1
Th Apr 5	Electrical signalling in the nervous system; neural computation applications	Supplement on Electrophysiology (Purves et al.); Dayan and Abbott 5.1-5.3; Nicolelis 2003 (Perspective on BMIs supplement)	PS 1
Tu Apr 10	An introduction to computational algorithms used in neural prostheses	Giszter et al.; Simeral et al.; Berger et al.; Asher et al.	PS 1
Th Apr 12	An introduction to computational algorithms used in neural prostheses	Simeral et al; Berger et al.	PS1
T Apr 17	Modelling neuron output; Anatomical mapping of sensory spaces	Somatosensory encoding supplement; Visual encoding supplement	PS 2
Th Apr 19	Anatomical mapping of sensory spaces; characterizing neuron firing	Somatosensory encoding supplement; Visual encoding supplement; Dayan and Abbott 1.1-1.4, 2.2, 7.2	PS 2
T Apr 24	Characterizing neuron firing	Dayan and Abbott 1.1-1.4, 2.2, 7.2	PS 2
Th Apr 26	Characterizing neuron firing, tuning curves.	Dayan and Abbott 1.1-1.4, 2.2, 7.2; Georgopoulos et al	PS 2
T May 1	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 8	Optimal linear filtering	Dayan and Abbott 2.2, 2.9; Wessberg and Nicolelis	PS 3
Th May 10	Optimal linear filtering	Dayan and Abbott 2.2, 2.9; Wessberg and Nicolelis	PS 3
T May 15	Midterm exam
Th May 17	Detecting spike patterns	Fellous et al. 2004; Supplement on PCA by J. Schlens	PS 4
T May 22	Guest lecture by Prof. Gerald Loeb on neuromuscular control and spinal regulators
Th May 24	Guest lecture by Prof. Jim Weiland on the retinal prosthesis
T May 29	Guest lecture by Prof. Francisco Valero-Cuevas on muscle synergies and redundancy	Kutch & Valero-Cuevas 2011; Kutch & Valero-Cuevas 2012
Th May 31	Guest lecture by Prof. Norberto Grzywacz on re-engineering the retina		Lee et al. 2011
T June 5	Detecting spike patterns	Fellous et al. 2004; Supplement on PCA by J. Schlens
Th June 7	Journal paper presentations