PSY 628: Perceptual Processes
Fall 2024
TTh 12:00 pm-1:15 pm
Peirce Hall, Room 255
Instructor:
Please contact me (email is best) if you cannot visit during office hours to schedule an alternative time to meet.
This course explores various aspects of perception. It covers some of the neurophysiological underpinnings of perception, methods of investigating perceptual processes, major theories of perception, and empirical findings. Because it is the easiest to present, we will mostly focus on visual perception, but we will also explore some aspects of audition and other sensory systems.
Materials (lectures, readings, datasets, code):
This material can be downloaded from the class website at http://www2.psych.purdue.edu/~gfrancis/Classes/PSY628/indexF24.html
- Psychometric functions. PPT slides for Lecture 1, Linares and Lopez-Moliner (2019), MLTBTData.csv, PsychometricFunction.R.
- Physiology of perceptual processing. PPT slides for Lecture 2, PPT slides for Lecture 3, PPT slides for Lecture 4, PPT slides for Lecture 5, PPT slides for Lecture 6
- Fourier analysis. PPT slides for Lecture 7, PPT slides for Lecture 8
- Processing streams and neural codes. PPT slides for Lecture 9, PPT slides for Lecture 10 (Rotating mask illusion), PPT slides for Lecture 11.
- Signal Detection Theory. PPT slides for Lecture 12, PPT slides for Lecture 12b, PPT slides for Lecture 12c (Weber's law).
- Gestalt Psychology and Objects. PPT slides for Lecture 13, PPT slides for Lecture 14.
- Color Perception. PPT slides for Lecture 15, PPT slides for Lecture 16.
- Constancies, size, depth, distance. PPT slides for Lecture 17, PPT slides for Lecture 18, PPT slides for Lecture 19, PPT slides for Lecture 20, PPT slides for Lecture 21
- Motion perception. PPT slides for Lecture 22, PPT slides for Lecture 23, PPT slides for Lecture 24
- Action and perception. PPT slides for Lecture 25
- Experimental design. PPT slides for Lecture 26, PPT slides for Lecture 27
- Hearing. PPT slides for Lecture 28, PPT slides for Lecture 29, PPT slides for Lecture 30, PPT slides for Lecture 31, Stereo Sound Localization Experiment PPT slides for Lecture 32
- Chemosensation. PDF slides for Lecture
- Touch. PPT slides for Lecture 3, PPT slides for Lecture 34
Class home page: The home page for this course is http://www.psych.purdue.edu/~gfrancis/Classes/PSY628/indexF24.html From this page you can download lecture notes, view the class schedule, view current grades, and connect to the various homework assignments.
Homework: Assignments will be due approximately every two weeks. The intention is to use the homework assignments as a way of practicing the concepts we discuss in class. They will be graded to insure that students actively participate.
- Homework 1 (Due: Tuesday, September 3): as PDF, as MS Word, Local Experiment. Some students reported not being able to get the experiment to run on their computer. Following this link should allow you to run it in your computer.
- Homework 2 (Due: Tuesday, September 17): as PDF, as MS Word, Convolutions.R, square.jpg, Mountains.jpeg.
- Homework 3 (Due: Tuesday, October 1): as PDF, as MS Word, Fourier Transform Playground, Gabor0.png, Gabor32.png, Gabor64.png, Gabor90.png, square.jpg, Mountains.jpeg, GappedVerticalLine.jpg.
- Homework 4 (Due: Tuesday, October 15): as PDF, as MS Word, experiment link
- Homework 5 (Due: Thursday, November 7): as PDF, as MS Word, Ongchoco & Schall (2019), online app for converting t-values to power (and other statistics)
Project: In the last two weeks, students will present a perception-related investigation. This could be an experiment or it could be modeling. There is a lot of flexibility in the project, but I have provided some suggestions and a few details (as PDF, as MS Word.)
Assumed background:
- It would be nice, but not necessary, if you had some previous exposure to calculus.
- Most perceptual experiments are created with computer programs. Different programming languages are used for different purposes. Many researchers like to use MatLab with the Psychophysics Toolbox. Other people like to use Python with PsychoPy. If you don't need precise control of timing and stimuli, you can run experiments in a web browser using Javascript. Examples of this approach will be provided in class. You do not need to be an expert programmer, but if you have little programming experience, you will have some catching up to do.
- Students should have experience with typical statistical methods (t-test, ANOVA, regression).