To see a complete list of recently offered courses and their descriptions, visit the online course catalog.
The courses listed below are provided by Student Information Services (SIS). This listing provides a snapshot of immediately available courses within this department and may not be complete. Course registration information can be found on the SIS website.
Column one has the course number and section. Other columns show the course title, days offered, instructor's name, room number, if the course is cross-referenced with another program, and a option to view additional course information in a pop-up window.
Course # (Section)
Title
Day/Times
Instructor
Room
PosTag(s)
Info
AS.050.116 (01)
Visual Cognition
TTh 12:00PM - 1:15PM
Li, Donald
Krieger 111
COGS-COGPSY, COGS-COMPCG, COGS-NEURO
Visual Cognition AS.050.116 (01)
How do humans make sense of the visual world around them? This course will provide an introductory survey of current research, methods, and theories in visual cognition. We will draw upon topics in cognitive psychology, cognitive neuroscience, cognitive neuropsychology, and artificial intelligence.
Credits: 3.00
Level: Lower Level Undergraduate
Days/Times: TTh 12:00PM - 1:15PM
Instructor: Li, Donald
Room: Krieger 111
Status: Waitlist Only
Seats Available: 1/25
PosTag(s): COGS-COGPSY, COGS-COMPCG, COGS-NEURO
AS.050.202 (01)
Introduction to Computational Cognitive Science
MW 3:00PM - 4:15PM
Rawlins, Kyle
Krieger 111
COGS-COMPCG
Introduction to Computational Cognitive Science AS.050.202 (01)
How does the mind work? Cognitive science addresses this question from a multidiscliplinary perspective, drawing upon methods and ideas from psychology, neurophysiology, neuroscience, philosophy, linguistics, and computer science. Within this framework, computational cognitive science has two related goals. The first is to create computational models of human cognition, computer programs that simulate certain aspects of the mind. The second is to understand how to produce intelligent behavior in machines, taking cues from humans. The computational frameworks we will discuss include symbolic structured representations, probabilistic inference and artificial neural networks, as applied to concept learning, language and vision. While this class does not have formal prerequisites, some programming experience (e.g., AS 250.205 Introduction to Computing or equivalent) and mathematical preparation (e.g., AS.110.107 Calculus II or equivalent) are essential.
An optional, hands-on lab (AS.050.212) is offered to supplement this course. It is highly recommended that students with less extensive computational and mathematical experience register for this lab.
Credits: 3.00
Level: Lower Level Undergraduate
Days/Times: MW 3:00PM - 4:15PM
Instructor: Rawlins, Kyle
Room: Krieger 111
Status: Open
Seats Available: 13/40
PosTag(s): COGS-COMPCG
AS.050.203 (01)
Neuroscience: Cognitive
TTh 10:30AM - 11:45AM
Bonner, Mick
Mudd 26
COGS-COGPSY, COGS-NEURO
Neuroscience: Cognitive AS.050.203 (01)
This course surveys theory and research concerning how mental processes are carried out by the human brain. Currently a wide range of methods of probing the functioning brain are yielding insights into the nature of the relation between mental and neural events. Emphasis will be placed on developing an understanding of both the physiological bases of the techniques and the issues involved in relating measures of brain activity to cognitive functioning. Methods surveyed include electrophysiological recording techniques such as EEG, ERP, single/multiple unit recording and MEG; functional imaging techniques such as PET and fMRI; and methods that involve lesioning or disrupting neural activity such as cortical stimulation, animal lesion studies, and the study of brain-damaged individuals. Also offered as AS.050.603.
It’s strongly recommended that students have background in one of the following courses: AS.050.105 OR AS.200.141.
Credits: 3.00
Level: Lower Level Undergraduate
Days/Times: TTh 10:30AM - 11:45AM
Instructor: Bonner, Mick
Room: Mudd 26
Status: Open
Seats Available: 39/250
PosTag(s): COGS-COGPSY, COGS-NEURO
AS.050.206 (01)
Bilingualism
TTh 1:30PM - 2:45PM
Yarmolinskaya, Julia S
Krieger 111
COGS-COGPSY, COGS-LING
Bilingualism AS.050.206 (01)
Do children get confused when they grow up exposed to more than one language? Is it possible to forget one’s native language? Are the first and second language processed in different areas of the brain? How does brain damage impact the different languages of a polyglot? Does knowing a second language affect non-linguistic cognitive processing? This course will address questions such as these through an exploration of mental and neural processes underlying bilingual and multilingual language processing. Also offered as AS.050.606.
Credits: 3.00
Level: Lower Level Undergraduate
Days/Times: TTh 1:30PM - 2:45PM
Instructor: Yarmolinskaya, Julia S
Room: Krieger 111
Status: Waitlist Only
Seats Available: 0/25
PosTag(s): COGS-COGPSY, COGS-LING
AS.050.212 (01)
Introduction to Computational Cognitive Science Lab
F 3:00PM - 4:15PM
Rawlins, Kyle
Krieger 111
Introduction to Computational Cognitive Science Lab AS.050.212 (01)
This course is a hands-on lab supplement for AS.050.202 Introduction to Computational Cognitive Science. While this lab is optional, it is highly recommended to students with less extensive computational and mathematical experience.
Credits: 0.50
Level: Lower Level Undergraduate
Days/Times: F 3:00PM - 4:15PM
Instructor: Rawlins, Kyle
Room: Krieger 111
Status: Open
Seats Available: 27/40
PosTag(s): n/a
AS.050.320 (01)
Syntax I
TTh 12:00PM - 1:15PM
Legendre, Geraldine
Krieger 134A
COGS-LING
Syntax I AS.050.320 (01)
Introduces the basic methods and means of analysis used in contemporary syntax investigations, practicing with data from different languages. Also offered as AS.050.620.
Credits: 3.00
Level: Upper Level Undergraduate
Days/Times: TTh 12:00PM - 1:15PM
Instructor: Legendre, Geraldine
Room: Krieger 134A
Status: Open
Seats Available: 5/20
PosTag(s): COGS-LING
AS.050.325 (01)
Phonology I
MW 1:30PM - 2:45PM
Wilson, Colin
Krieger 111
BEHB-SOCSCI, COGS-LING
Phonology I AS.050.325 (01)
An introduction to the basic principles underlying the mental representation and manipulation of language sounds and their relation to human perception and vocal articulation: how units of sound are both decomposable into elementary features and combined to form larger structures like syllables and words. The role of rules and constraints in a formal theory of phonological competence and in accounting for the range of variation among the world’s languages. Also offered as AS.050.625.
Credits: 3.00
Level: Upper Level Undergraduate
Days/Times: MW 1:30PM - 2:45PM
Instructor: Wilson, Colin
Room: Krieger 111
Status: Open
Seats Available: 4/40
PosTag(s): BEHB-SOCSCI, COGS-LING
AS.050.326 (01)
Foundations of Cognitive Science
MW 3:00PM - 4:15PM
Smolensky, Paul
Krieger 134A
NEUR-CG, NEUR-CP, COGS-COMPCG, COGS-PHLMND
Foundations of Cognitive Science AS.050.326 (01)
This course explores general issues and methodologies in cognitive science through the reading of classic works (from Plato and Kant through Skinner and Turing) and recent research articles to begin construction of a coherent picture of many seemingly divergent perspectives on the mind/brain. Recent brain-based computational models serve to focus discussion. Also offered as AS.050.626. Recommended Course Background: at least one course at the 300-level or higher in cognitive science, computer science, neuroscience, philosophy, or psychology.
Reading the Mind: Computational Cognitive Neuroscience of Vision
TTh 9:00AM - 10:15AM
Li, Donald
Krieger 108
COGS-COMPCG, COGS-NEURO, NEUR-CG, NEUR-CP
Reading the Mind: Computational Cognitive Neuroscience of Vision AS.050.337 (01)
Recent advancements in neuroscience, computational cognitive science and machine learning have led to new possibilities for understanding the mind and brain. With the current neural network modelling and artificial intelligence (AI) techniques, scientists are able to decode neural representation to understand one’s internal mental state. In this course, we will discuss how to utilize the latest technologies, including voxel-wise encoding models, convolutional neural networks (CNNs), generative adversarial networks (GANs) and transformers, to model neural representations with a focus on vision. Students will read latest primary research articles and gain hands-on neural modelling experience. Also offered as AS.050.637
This is a survey course in developmental psychology designed for individuals with some basic background in psychology or cognitive science, but little or none in development. The course is strongly theoretically oriented, with emphasis on issues of nature, and development psychology as well as relevant empirical evidence. The principle focus will be early development, i.e., from conception through middle childhood. The course is organized topically, covering biological and prenatal development, perceptual and cognitive development, the nature and development of intelligence, and language learning. Also offered as AS.050.639.
First language acquisition is natural and seemingly effortless. The situation is reversed when one tries to learn another language. This course discusses in what ways first and second language acquisition (SLA) differ and how individual differences of the learners as well as external factors contribute to the variability observed in rates and ultimate proficiency of second language learning in children and adults. We will discuss such topics as Universal Grammar access in early and late SLA, first language influence, critical periods, possibility of native-like attainment, and language attrition. Also offered as AS.050.649.
Credits: 3.00
Level: Upper Level Undergraduate
Days/Times: TTh 3:00PM - 4:15PM
Instructor: Yarmolinskaya, Julia S
Room: Krieger 111
Status: Open
Seats Available: 1/25
PosTag(s): COGS-LING, COGS-COGPSY
AS.050.353 (01)
Cognitive Science in Artificial Intelligence
MW 1:30PM - 2:45PM
Lopez-Gonzalez, Monica
Krieger 134A
COGS-COGPSY, COGS-NEURO, COGS-COMPCG, BEHB-SOCSCI
Cognitive Science in Artificial Intelligence AS.050.353 (01)
As a myriad of artificial intelligence enabled autonomous systems enter into our lives and change how we live, we must ask: can we trust these systems? In this course we will take a human-centered perspective on assured autonomy and identify why and how insights from human perception and cognition can guide solutions for reliable, resilient, and robust autonomous systems. We will address bias, ethics, explanability, and safety by focusing on specific case studies from autonomous vehicles, cybersecurity, healthcare, fashion, law enforcement, and military systems. Students will apply learned material to a semester-long group research project on a topic of their choice. Also offered as AS.050.653.
