Department of Psychology
Queen's University 
Currently Offered Courses
Below is a list of courses currently offered. Note, that for some of the course only generic and relatively non-specific titles and course description are listed in the Graduate calendar. The specific contents depends on who teaches them and may change slightly. For these courses, we are here offering a more specific course descriptions provided by the instructor who teaches the course.
Fall 2011
Psyc811: BBCS Graduate Seminar
Instructor: The entire BBCS faculty
Time: Mondays 9:00 – 11:00
Location: Hum 223
Many of the questions we are researching today are not new. They are motivated by other peoples work and they are rooted in the history of our discipline. In this year's BBCS seminar, we want to learn about a number of personalities which were particularly influential in shaping Experimental Psychology over the last century. Every student in the course will present one scientist. We want to learn about his/her work, how it was motivated, and what kind of influences it had on their scientific environment. We will provide an extensive list of personalities from which you can pick your choice.
Psyc801: Design of Experiments
Instructor: Mark Sabbagh
Time: Thursday, 11:00am-12:30pm; Friday, 9:00am-10:30am.
Location: Hum 219
Lab Time: Tuesday, 3:30pm-5:00pm
Lab Location: Hum 219
Topics include: The logic of the test for significance and controversies concerning it; ANOVA and its underlying linear model for between- subject, within-subject and split-plot designs; orthogonal comparisons for trend analysis and for special contrasts; restricted randomization and the randomized-block design; partial confounding in latin-squares; balancing conditions against trend; hierarchical designs; ANOVA and multiple correlation; designs including organismic variables; random- effect models and the fixed-effect fallacy; data transformations and non-parametric tests.
Psyc 921: Visual and Auditory Processes
Instructor: Niko Troje
Time: Thursday, 9:00am-11:00am
Location: Hum 326
We will be looking into mechanisms and computational approaches to understand a number of core low-level visual processes: Spatial vision, lightness and colour vision, visual motion and optic flow, stereopsis, shape from shading. For every one of these areas we will study the physical processes that determine how objects and events of the world project onto our sensory systems, and we will explore the inverse process, that is, how our visual system attempts to recover from these sensations properties of the objects and events that caused them. We will read a number of seminal papers in the field and we will learn about algorithms and models at a level at which we would eventually be able to implement them ourselves.
The seminar will have the format of a workshop. Topics will be introduced with a short lecture given by myself. Led by one of the participants and centred around one or two papers which everyone has to read before class, we will then work on an in-depth understanding of concepts and algorithms. Rather than listening to (or giving) PowerPoint presentations, we will have to use the black board, paper and pencil, and maybe a bit of Matlab programming to get a hands-on grasp of some of the most basic concepts in quantitative vision research.
Instructor: Niko Troje
Time: Thursday, 9:00am-11:00am
Location: Hum 326
We will be looking into mechanisms and computational approaches to understand a number of core low-level visual processes: Spatial vision, lightness and colour vision, visual motion and optic flow, stereopsis, shape from shading. For every one of these areas we will study the physical processes that determine how objects and events of the world project onto our sensory systems, and we will explore the inverse process, that is, how our visual system attempts to recover from these sensations properties of the objects and events that caused them. We will read a number of seminal papers in the field and we will learn about algorithms and models at a level at which we would eventually be able to implement them ourselves.
The seminar will have the format of a workshop. Topics will be introduced with a short lecture given by myself. Led by one of the participants and centred around one or two papers which everyone has to read before class, we will then work on an in-depth understanding of concepts and algorithms. Rather than listening to (or giving) PowerPoint presentations, we will have to use the black board, paper and pencil, and maybe a bit of Matlab programming to get a hands-on grasp of some of the most basic concepts in quantitative vision research.
Winter 2012
Psyc 931: Neuroplasticity and Behaviour
Instructor: Hans Dringenberg
Time: Monday, 1:00pm-3:00pm
Location: Hum 326
Changes at the synaptic level in structure and neurochemistry including protein synthesis associated with sensory/perceptual development, learning and memory. Coverage will include in vitro and in vivo approaches. Data from vertebrates and invertebrates will be included. Discussing the topics of metaplasticity, development, and aging; memory and plasticity; clinical and societal implications.
Psyc 971: Advanced Special Topics in Cognitive Science:
Time series analysis and the use of Matlab
Instructor: Randy Flanagan
Time: Tuesday, 10:00am-11:30am
Location: Hum 223
Lab Times: Monday, 11:30am-1:00pm; Thursday, 1:00pm-2:30pm
Lab Location: Hum 219
Time: Tuesday, 10:00am-11:30am
Location: Hum 223
Lab Times: Monday, 11:30am-1:00pm; Thursday, 1:00pm-2:30pm
Lab Location: Hum 219
Focus on specific issues within the cognitive science area. The objective of this course is to (1) introduce the student to basic techniques for the quantitative analysis of time-varying signals and (2) teach the student how to apply these techniques using MATLAB, the most commonly used high-level computing language used in science and engineering. Emphasis will be placed on methods appropriate to the psychological research environment. The theoretical background for each technique will be presented briefly, but the major stress will be on the application to practical problems. This will be achieved partially by the demonstration of typical analysis procedures. More importantly, students will be required to undertake assignments involving the analysis of simulated and actual psychological data. Expertise in MATLAB or signal processing is not required.