Psychology 448A Topics in Vision

Psychology 448A

Topics in Vision

Autumn 2008

Course Announcements

Papers and projects due Thursday, December 4th

Get a zipped file containing the current matlab code for the course here!

The following scripts are available. They're written to be run cell-by-cell, rather than just running the whole thing at once.

11/18
RustMT.m                               Generates figures based on the model of MT by Rust et al.
predRestMT.m                        Actual implemenation of Nicole Rust's MT model
StimulusSpace.m                     Shows a movie of the two-component plaid stimulus space in the Rust et al. paper
ShowHyperplaid.m                 Animates a six-component hyperplaid as an example stimulus for the Rust et al. paper

11/12
AdelsonBergen.m                    Demonstrates how to generate a space-time oriented filter and make a motion detector.

11/4
PlaidDemo.m                           Lets the user see the direction of moving plaids and the 'intersection of constraints' model.

10/13
GeislerAlbrecht.m                     Generates some of the figures for the paper by Geisler and Albrecht

10/10
LinearDemo.m                          Generates some of the images for the notes on the Linear Model of the Receptive Field
LinearNonlinearModelDemo    Generates some of the images for the notes on the Linear-Nonlinear Model
Priebe.m                                 Implements some of Priebe's ideas about nonlinearites and tuning of V1 cells
SpikeTriggeredAverageDemo   Demonstrates the reconstruction of the linear RF using spike triggered averaging
EnergyModelDemo                  Generates a 'Quadrature Pair' set of linear RF's to create a model complex cell (See Heeger's paper)
HeegerNormalizationModel      Implements David Heeger's contrast normalization model and generates figures similar to his paper.

More to come...

All other functions are support functions for the programs above. They're worth looking at for a better understanding of the programs.

Time:	Tuesdays, Thursdays, 11:30-1:20
Location:	Guthrie 211
Instructor:	Geoff Boynton
Office:	Guthrie 233A
Office Hours:	by appointment.
email:	gboynton@u.washington.edu

Course Objectives

This course will explore the physiological properties of neurons in early stages of visual cortex, and how they relate to the way we perceive the world. The main objective of this course is to familairize you with the field of visual science through a thorough discussion of classic and current research articles. A list of articles can be found in the Course Schedule section below.

There will be three main sections of the course. The first section will discuss how neurons in the primary visual cortex represent the properties of visual stimuli, such as contrast, orientation and spatial frequency. The second section will cover how these V1 responses can predict performance on some simple visual tasks. The third section will focus on the perception of motion in the primate visual cortex.

Each research article addresses one of the three questions:

(1) How do neurons respond to a given set of visual stimuli?
(2) Can we summarize these response properties with a mathematical model?
(3) How can these models predict performance in a visual task?

Grading

Students will be required to complete either a project or a written paper due at the end of the quarter. The project can be an implementation of a computational model discussed in class, or from a paper not discussed in class, or even better, a model of your own. Students completing a project will present their work in class at the end of the quarter.

Students who write a paper can work with me on the topic, scope and length.

Readings

Most weeks will include a discussion of one or two important papers in the field. These will be provided as pdf documents downloadable from the course schedule. I'll assign a student to each paper ahead of time to help lead the discussion on the paper but of course, I expect all of you to have read the papers before the class meets.

Course Schedule

Week	Topic	Readings/Downloads
Thu 9/25	Introduction
Tue 9/30	Section 1: Primary Visual Cortex Early history of electrophysiological recordings in the primary visual cortex	Hubel, D.H.W., T. N. (1962). Receptive field, binocular interactions and functional architecture in the cat’s visual cortex. J. Physiol. (Lond.), 160, 106–154. Hubel, D.H., & Wiesel, T.N. (1998). Early exploration of the visual cortex. Neuron, 20 (3), 401-412. Movies: LGN on cell, LGN off cell, Simple cell, Complex cell, Directional cell, Binocular cell Lecture Notes: Linear Model of the Receptive Field
Thu 10/2	Journal Club	Priebe, N.J., & Ferster, D. (2008). Inhibition, spike threshold, and stimulus selectivity in primary visual cortex. Neuron, 57 (4), 482-497.
Tue 10/7	Modern methods of electrophysiological recordings in the primary visual cortex	Ringach, D.L. (2004). Mapping receptive fields in primary visual cortex. J Physiol, 558 (Pt 3), 717-728. Lecture Notes: Linear-Nonlinear Model
Thu 10/9	The Normalization Model of the primary visual cortex	Heeger, D.J. (1992). Normalization of cell responses in cat striate cortex. Vis Neurosci, 9 (2), 181-197. Lecture Notes: Normalization Model
Tue 10/14	Section 2: Predicting behavior from neuronal responses in V1	Geisler, W.S., & Albrecht, D.G. (1997). Visual cortex neurons in monkeys and cats: detection, discrimination, and identification. Vis Neurosci, 14 (5), 897-919. Lecture Notes: GeislerAlbrecht
Thu 10/16	Journal Club	Special Guest Lecture: Greg Horwitz on Spike-Triggered Covariance and Color Vision in V1 Relevant paper: Horwitz, G.D., Chichilnisky, E.J., & Albright, T.D. (2005). Blue-yellow signals are enhanced by spatiotemporal luminance contrast in macaque V1. J Neurophysiol, 93 (4), 2263-2278.
Tue 10/21	Contrast discrimination thresholds and V1 responses	Heeger, D.J., Huk, A.C., Geisler, W.S., & Albrecht, D.G. (2000). Spikes versus BOLD: what does neuroimaging tell us about neuronal activity? Nat Neurosci, 3 (7), 631-633. Legge, G.E., & Foley, J.M. (1980). Contrast masking in human vision. J Opt Soc Am, 70 (12), 1458-1471. Boynton, G.M., Demb, J.B., Glover, G.H., & Heeger, D.J. (1999). Neuronal basis of contrast discrimination. Vision Res, 39 (2), 257-269. Lecture Notes: Contrast Discrimination
Thu 10/23	Psychophysical models of stimulus detection: predicting MODELFEST stimulus detection data	Watson, A.B. (2000). Visual detection of spatial contrast patterns: evaluation of five simple models. Opt Express, 6 (1), 12-33. Supplemental reading: Watson, A.B., & Ahumada, A.J., Jr. (2005). A standard model for foveal detection of spatial contrast. J Vis, 5 (9), 717-740. Lecture Notes: ModelFest
Tue 10/28	Adaptation to spatial frequency: psychophysics and physiology	Blakemore, C., & Campbell, F.W. (1969). On the existence of neurones in the human visual system selectively sensitive to the orientation and size of retinal images. J Physiol, 203 (1), 237-260. Duong, T., & Freeman, R.D. (2007). Spatial frequency-specific contrast adaptation originates in the primary visual cortex. J Neurophysiol, 98 (1), 187-195. Lecture Notes: SpatialFrequencyAdaptation
Thu 10/30	Journal Club	Kay, K.N., Naselaris, T., Prenger, R.J., & Gallant, J.L. (2008). Identifying natural images from human brain activity. Nature, 452 (7185), 352-355.
Tue 11/4	Section 3: Motion processing Electrophysiological responses in area MT (Part 1)	Born, R.T., & Bradley, D.C. (2005). Structure and function of visual area MT. Annu Rev Neurosci, 28, 157-189. Lecture Notes: MT
Thu 11/6	Electrophysiological responses in area MT (Part 2)	Pack, C.C., & Born, R.T. (2001). Temporal dynamics of a neural solution to the aperture problem in visual area MT of macaque brain. Nature, 409 (6823), 1040-1042. Kohn, A., & Movshon, J.A. (2003). Neuronal adaptation to visual motion in area MT of the macaque. Neuron, 39 (4), 681-691.
Tue 11/11	Veteran's Day Holiday
Thu 11/13	Models of MT neurons (Part 1)	Adelson, E.H., & Bergen, J.R. (1985). Spatiotemporal energy models for the perception of motion. J Opt Soc Am A, 2 (2), 284-299. Lecture Notes: Motion
Tue 11/18	Models of MT neurons (Part 2)	Rust, N.C., Mante, V., Simoncelli, E.P., & Movshon, J.A. (2006). How MT cells analyze the motion of visual patterns. Nat Neurosci, 9 (11), 1421-1431.
Thu 11/20	Jack Werner Seminar and Lunch with Students
Tue 11/25	The perception of speed	Stocker, A.A., & Simoncelli, E.P. (2006). Noise characteristics and prior expectations in human visual speed perception. Nat Neurosci, 9 (4), 578-585.
Thu 11/27	Thanksgiving Holiday
Tue 12/2	Student Presentations
Thu 12/4	Student Presentations