Cognitive Science

Overview | Requirements | Courses | Faculty


Cognitive Science is the science of the mind. Drawing on the fields of mathematics, philosophy, psychology, neurobiology, computer science and linguistics, Cognitive Science studies the nature of consciousness, the interaction of mind and matter, and the relationship between thought and language. Cognitive Science addresses long-standing questions about the nature of thought, intelligence, perception, emotion, and other aspects of our mental life by employing the methodologies of the contributing disciplines mentioned above, including philosophical reflection and argument, experimental psychology, the modeling of intelligence with machines, and the investigation of the biological basis of cognition.




A total of at least 48 units to be distributed as follows:

Fundamental courses:

  1. Cognitive Science 101: Introduction to Cognitive Science
  2. Cognitive Science 242: Computational Approaches to Cognition
  3. Philosophy 225: Formal Logic
  4. Psychology 306: Cognitive Psychology
  5. Cognitive Science 201: Research Methods in Cognitive Science
  6. At least one of the following: Cognitive Science 104: Introduction to Neuroscience, Cognitive Science 320: Cognitive Neuroscience
  7. At least one of the following: Cognitive Science 330: Linguistics for Cognitive Science, Linguistics 301: Introduction to Linguistics, Linguistics 350: Psycholinguistics
  8. At least one of the following: Philosophy 360: Philosophy of Mind, Philosophy 365: Philosophy of Science, Philosophy 370: Philosophy of Language, Philosophy 375: Theory of Knowledge, Philosophy 380: Wittgenstein
  9. Cognitive Science 490: Senior Seminar in Cognitive Science

Elective courses: 

Electives can be drawn from the list above, can be a course cross-listed with cognitive science, or can come from the list below. A total of 4 units can be applied to the major from either directed research or independent study.

All students are encouraged to take a statistics course from the list below (e.g., Biology 268, Mathematics 146, or Psychology 201). Those students intending to do an empirical project for their senior comprehensives or who intend to go on to graduate school in cognitive science are strongly encouraged to take one of these statistics courses. Students who intend to go to graduate school in cognitive science or in a related field should discuss course choices with their advisor.

Cognitive Science
Cognitive Science 210: Artificial Intelligence
Cognitive Science 230: Mind, Brain, and Behavior
Cognitive Science 241: Cognition of Music and Sound
Cognitive Science 292: Brain Plasticity
Cognitive Science 295: Topics in Cognitive Science
Cognitive Science 301. Applied Cognitive Science & Education
Cognitive Science 343: Probabilistic Models of Cognition

Biology 240: Vertebrate Physiology
Biology 268: Biostatistics
Biology 320: Developmental Biology
Biology 333: Neurobiology
Biology 340: Advanced Animal Physiology
Biology 378: Animal Behavior

Computer Science
Computer Science 311: Data Structures and Algorithms
Computer 353: Information Theory

Economics 305: Game Theory
Economics 340: Behavioral Economics

English Writing
English and Rhetoric (WRD) 401: Science Writing

Kinesiology 301: Human Anatomy II (nervous system)
Kinesiology 307: Human Physiology
Kinesiology 310: Motor Learning and Control

Linguistics 355: Sociolinguistics

Mathematics 146: Statistics
Mathematics 150: Data Analysis
Mathematics 186: Network Models
Mathematics 330: Probability
Mathematics 350: Mathematical Logic
Mathematics 352: Computability and Complexity
Mathematics 354: Set Theory and Foundations of Mathematics
Mathematics 370: Numerical Analysis
Mathematics 392: Mathematical Models in Biology

Philosophy 250: Bioethics
Philosophy 305: Topics in Modern Philosophy
Philosophy 325: Metalogic
Philosophy 355: Philosophy of Space and Time

Psychology 111: Origins of Knowledge
Psychology 201: Statistics in Psychological Science
Psychology 302: Perception
Psychology 322(L): Physiological Psychology
Psychology 403: Psychophysiology
Psychology 444: Thinking and Reasoning

Writing Requirement: To pass the departmental writing requirement students must attain a B- or better in a 300-level fundamental course or 300-level cognitive science class by the end of their junior year.

Comprehensive Requirement: In the senior year the student carries out a project or writes a thesis on a topic in Cognitive Science related to their prior coursework. The project or thesis is coordinated with the work of the Cognitive Science Senior Seminar. All majors take the Senior Seminar in the fall semester of the senior year.

Honors: Honors in Cognitive Science may be awarded to graduating seniors who demonstrate excellence in their course work and distinction in their senior comprehensive project. To be eligible, students must have a 3.5 grade point average in the major and a 3.25 overall grade point average. In addition, the comprehensive project or thesis must be judged as a "pass with distinction."

Minor: A total of 24 units, including Cognitive Science 101 and five other courses any of which can come from the list of fundamental courses or have a cognitive science designation. One of these can be a course without a cognitive science designation from the list of electives for the major.


101 - Introduction to Cognitive Sciences

An interdisciplinary introduction to the discovery of the mind through philosophical texts, psychological experiments, artificial intelligence, the study of nerve cells and neural networks and investigations into language. The purpose of the course is to foster an appreciation of the wonder and complexity of minds and brains, both human and otherwise. Not open to seniors in spring semester.

104 - Introduction to Neuroscience

This course provides a basic introduction to the nervous system [for students with little or no experience in this area].  It will include an introduction to how nerve and glial cells contribute to different brain functions.  Brain structures and systems and how they act to produce sensory experience, thought, emotion, and memory will also be covered.  Other topics might include: factors that affect embryonic development of the nervous system, and the effect of drugs, environment, stress, education, and age on the brain.  This course is not open to students who have taken Biology 333, Cognitive Science 320, Kinesiology 301 or Psychology 322.

201 - Empirical Methods in Cognitive Science

This course provides students with a foundation to think critically about research in cognitive science and lays the groundwork for the original research that will be done in the senior year. We will examine primary literature, considering carefully the processes involved in moving from a general idea to a specific research question. We will consider the strengths and weaknesses of a range of approaches to studying cognition with a focus on experimental design. Laboratory sessions will introduce students to basic research tools and data collection. The course will culminate in an original research proposal. Prerequisite: Cognitive Science 101 Corequisite: COGS 310L

210 - Introduction to Artificial Intelligence

Can one create intelligent machines-machines capable of posing and solving problems and of interacting effectively with a complex and dynamic environment? If so, how? And what insights into natural cognition do we gain through efforts to create artificial intelligence? Fundamental principles, architectures, and algorithms for machine perception, control, and problem-solving will be addressed. We will also look in detail at strategies for developing intelligent machines, including traditional Artificial Intelligence and the more recent perspectives of situated and embodied cognition. The laboratory component of the course will involve computing and simple robotic devices. Prerequisite: COGS 242, or MATH 186, or MATH 210, or permission
of instructor


220 - Animal Cognition

Are earthworms capable of making decisions? How do ants navigate their environment? Do dogs have an understanding of fairness? Questions about the mental states and processes possessed by nonhuman animals present particular problems of study: how do we determine whether and to what extent animals possess such abilities? This course will study the evidence for cognitive states and processes in nonhuman animals, focusing on careful and critical attention to the methods and techniques used to gather that evidence, and on the considerations that go into interpreting that evidence.

230 - Mind, Brain, and Behaviour

This course addresses the question: how can we understand the mind scientifically? We will explore answers to this question via a critical survey of neural and behavioral evidence bearing on the nature of core cognitive capacities, including perception, memory, emotion, decision-making, rationality, and consciousness. We will explore these sources of evidence in a comparative perspective, drawing on evidence of both human and (non-human) animal cognition to more adequately characterize the nature of cognition generally.

241 - Cognition of Music and Sound

As part of human cognition, our perception, production, and understanding of music has elicited many questions: What is music in relation to "sound"? Is music an evolutionary adaptation? What is the relationship of music and emotions, or memory? Can music influence perception in other modalities? What is the meaning of music? Can music make us smarter? Is music a language? What is biological and what is cultural in the esthetics of music? This course will reframe many of these questions from the interdisciplinary standpoint of cognitive science, acoustics, music theory, and semiotics to explore music as a cognitive process Topics will include the perception of pitch, timbre, rhythm, and localization; music and the brain; cognitive aspect of the esthetics of music; the relationship between music and language in terms of their structures and neurological processing; music and memory; music and emotions; music and meaning. We will also discuss the role music plays in cross-modal interactions, either in the real world, or in films and multimedia art works.  Same as MUSC 241. Prerequisite: Any Cognitive Science class or Music class, or instructor's approval

242 - Computational Approaches to Cognition

Computational modeling provides important insights into how the mind/brain may work. We will examine three different approaches that have been used to provide insights into cognition: symbolic methods, connectionism, and probabilistic methods. We will use computer software to explore how these approaches work in practice. Specific applications such as perception, language, and memory will be covered. The assumptions and limitations of each approach, as well as the metaphor of mind/brain as a computer, will be critically considered. This course has a mandatory laboratory component which will include both experimentation and computer programming. No previous programming background is required.  Prerequisite: Cog Sci 101 as prereq or coreq
OR prereq of Phil 225, Math 186, 210, 214, 252, or CS 157, 161, 165, or 211 OR permission of instructor


250 - Multisensory Perception and Cognition

Traditionally, the senses have been thought to operate independently. However, there is increasing evidence that the brain is fundamentally multisensory. This course will explore how the brain encodes input from each of the senses, and how it integrates this information to create our perceptions of the world. We will consider converging evidence from methodologies such as psychophysics, neuroimaging, neural recording, and neurology. The laboratory component of the class will include experiments within individual senses as well as those that explore integration of the senses. Prerequisite: Cognitive Science 101, Cognitive Science 104, Psychology 302, or permission of instructor. Prerequisite: Cog Sci 101, Cog Sci 104, Psych 302, or permission of instructor.

255 - Data Analysis and Visualization

The primary goal of this course is twofold: 1) to provide students from a wide range of disciplines with hands-on training to analyze a variety of datasets relevant to their course of study, and 2) to provide them with the tools to understand the rhetorical form and function of different types of data visualizations. Students will consider how questions can be answered using data, learn how to analyze data appropriately, learn to design and present graphs that tell an easy-to-understand visual story, have high impact, and are memorable, and critically consider the assumptions underlying accurate interpretation of analyses and visualizations. Students from any major are welcome.

290 - Open Science: Collaborative Research

Open Science: Collaborative Research. This course introduces students conducting directed research with a faculty member in the Cognitive Science Department to the practice of “open notebook science”, intended to make the research process (hypothesis generation, data collection, dissemination) transparent and accessible to anyone, researchers and public alike. Students will use the Open Science Framework either to undertake new research or to replicate a recent experiment within the cognitive sciences using the Open Science Framework. Students are expected to commit to a minimum of 8 hours of course-work each week including a 1.5 hour course meeting, assigned group work, readings, and independent research. COGS 295 can be repeated for credit. Prerequisites: COGS 101, COGS 201 (currently 310), and instructor approval. Prerequisite: Cog Sci 101, Cog Sci 201 (currently 310), instructor permission
2 unit graded CR/NC

292 - Brain Plasticity

Mechanisms of brain development, growth, neurogenesis, maturation, and changes that occur during life. Emphasis will be placed on current literature and studies done in nonhuman animals and humans. We will also talk about what it takes to maintain a healthy brain. Prerequisite: CogSci 101, 104, or permission of instructor.

295 - Topics in Cognitive Science

Intelligent Agents.This course explores the some of the issues in the nature of intelligent agents: Concepts are the building blocks of thoughts; they are what allow intelligent agents to think about, reason about, and understand the world around them. This course will explore major theories of the nature of concepts from philosophy, psychology, linguistics, neuroscience, and related fields. The goal will be to gain a better appreciation of what concepts are, and how the study of concepts ties together different fields in the study of cognition. Pre-req: Any cog sci course or permission of instructor.

301 - Applied Cognitive Science and Education

This course will address current cognitive science research as applied to learning and education. The concept of multiple intelligences, as well as strengths and weaknesses of individuals in acquisition of information will be emphasized. We will also cover specific learning disabilities/differences and cognitive styles. Prerequisite: Cognitive Science 101, declared minor in Education, or permission of instructor.

320 - Cognitive Neuroscience

This course will introduce students to the biology of the mind. It will provide an overview of neuroanatomy and characterize the neural mechanisms supporting complex cognitive processes including vision, attention, consciousness, language, memory, learning, emotion, and action. We will also emphasize the importance of converging methodologies in studying the link between the mind, brain, and behavior. Methodologies we consider include behavioral measures of cognition, neuropsychology, electrophysiology, anatomical and functional neuroimaging, single-cell recordings, and computational modeling. Laboratory sessions will allow students get hands-on experience with these methodologies, as well as arm them with the tools to understand and evaluate primary research in cognitive neuroscience. Prerequisite: Cognitive Science 101, Biology 130, or Psychology 322, or permission of the instructor. Co-requisite: Cognitive Science 320L.

325 - Topics in Artificial Intelligence

Although modern artificial intelligence no longer resembles cognitive science, many of the underlying ideas take inspiration from and share parallels with descriptions of human intelligence. This course aims to look at some of these topics through both lenses, as well as consider other topics in AI that may be trivial by human standards, but remain open problems in computer science. Prerequisite: Cog Sci 101, Comp Sci 210 or 211 or instructor permission

330 - Linguistics for Cognitive Science

Language and cognition are intimately related. For this reason Linguistics has had an extremely strong influence on Cognitive Science. This course studies language and linguistics in the context of Cognitive Science. We will address such questions as how are language and thought related? How is language represented in the brain? How do we process language? To what extent is the human capacity for language innate? Is there a language of thought? What are the best ways to model language acquisition and language processing? We will cover some topics in traditional linguistics, and we will look at current research on connectionist and traditional artificial intelligence approaches to modeling language. Reading will include work by Chomsky, Pinker, McClelland, Rumelhart, Fodor and Elman. Prerequisite: Cognitive Science 101 or LING 301.

340 - Human-Computer Interaction

What factors contribute to making a website easy to use versus frustrating to navigate? How can we apply what we know about the mind to design technologies that foster positive user experiences? We will apply cognitive science findings about attention, perception, memory, and more to study how humans interact with technology. Prerequisite: Cognitive Science 310.

343 - Probabilistic Models of Cognition

Probabilistic models have increasingly been applied to understand how the mind works across domains such as motor control, decision-making, and causal inference. We will learn how such models work, learning the mathematical tools necessary to implement them, such as Bayesian inference, graphical models, and Markov models. We will consider both how human cognition can inform machine learning and how computational approaches can lead to new ideas about cognition.
Prerequisite: Cognitive Science 242, Co-requisite: Cognitive Science 343L

350 - Experimental Philosophy

Experimental philosophy is the project of using the methods of experimental psychology to inform questions of traditional philosophical concern, typically by using surveys or other instruments to evaluate whether philosophers' intuitions and judgments accurately represent generally held beliefs. In this class we will discuss the historical antecedents for, contemporary practice of, and critical reactions to the project of experimental philosophy, via study and discussion of central works in the field. We will be concerned with questions such as: what do the tools of experimental philosophy reveal about the practice and content of traditional philosophy? To what extent are these tools valid for drawing conclusions about philosophical claims, arguments, and disputes? Can the methods of experimental philosophy supplement, or even potentially replace, traditional methods of doing philosophy? Prerequisite:One previous class in either Cognitive Science or Philosophy. Same as PHIL 390

395 - Directed Research in Cognitive Science

Directed research with a faculty member.
Prerequisite: COGS 101 or permission of instructor
2 or 4 

397 - Independent Study in Cognitive Science

Prerequisite: permission of instructor.
2 or 4 units

490 - Senior Seminar in Cognitive Science

This course will support senior cognitive science majors as they conduct original research as part of their senior comprehensive requirement. Prerequisite: Cognitive Science 101 and senior standing in Cognitive Science. Prerequisite: Cognitive Science 101, senior standing in Cognitive Science; or permission of instructor


Regular Faculty

Andrew Shtulman, chair

Associate Professor, Cognitive Science; Psychology

B.A., Princeton University; Ph.D., Harvard University

Carolyn Brighouse

Associate Dean of the College for Core Curriculum and Student issues, Professor, Cognitive Science, Philosophy

B.A., University of Liverpool; M.A., Ph.D., University of Southern California

Alan Knoerr

Associate Professor, Mathematics, Cognitive Science

B.A., Oberlin College; Sc.M., Ph.D., Brown University

Carmel Levitan

Associate Professor, Cognitive Science; Advisory Committee, Neuroscience

B.A., Stanford University; Ph.D., UC Berkeley

Justin Li

Assistant Professor, Cognitive Science

Ph.D, University of Michigan

Diana Card Linden

Professor, Cognitive Science; Advisory Committee, Neuroscience

A.B., M.A., Ph.D., University of California, Los Angeles

Michael Shelton

Associate Professor, Spanish and French Studies; Cognitive Science; Affiliated Faculty, Linguistics; Affiliated Faculty, Latino/a and Latin American Studies; Advisory Committee, Group Language

B.S., St. Cloud State University; M.A., Ph.D., Pennsylvania State University

Aleksandra Sherman

Assistant Professor, Cognitive Science; Advisory Committee, Neuroscience

B.A., Rutgers University; Ph.D., Northwestern University

Saul Traiger

Professor, Cognitive Science, Philosophy

B.A., State University of New York, Binghamton M.A., Ph.D., University of Pittsburgh

On Special Appointment

Dylan Sabo

Non-Tenure Track Assistant Professor, Philosophy

Ph.D., University of North Carolina, Chapel Hill