Introductory Courses

The two introductory courses in the Cognitive Science major serve two purposes.

• They introduce students to the empirical questions, theoretical concepts, and analytical methodologies that led to the emergence of Cognitive Science as a distinct field of study and continue to drive contemporary research.
• They highlight these issues in the core disciplines of Cognitive Science—computer science, linguistics, neuroscience, philosophy, and psychology—and the ways that inquiries into central questions about the nature of the mind have been shaped and informed by interactions, conversations, and collaborations across the disciplines.

COGS 20001 Mind, Brain, and Meaning

What is the relationship between physical processes in the brain and body and the processes of thought and consciousness that constitute our mental life? Philosophers and others have puzzled over this question for millennia. In recent decades, the field of cognitive science has proposed a new way to answer. The driving idea is that the interaction of the mental and the physical may be understood via a third level of analysis: the computational. This course offers a critical introduction to the elements of this approach, including some of the alternative models and theories that fall within it. Readings are drawn from a range of historical and contemporary sources in philosophy, psychology, linguistics, and computer science.

Offered in Autumn, Spring of AY 2024-2025

COGS 20002 Cognitive Models

A foundational principle of cognitive science is that the workings of cognitive systems—whether biological, mechanical, or digital—can be productively represented by the operation of formal computational models. This course provides a survey of popular modeling frameworks (Bayesian rational agents, connectionist networks, dynamical systems) as well as the cognitive phenomena that these models have been used to simulate. We will discuss the theoretical commitments of these models, assess strengths and weaknesses of each framework for addressing different types of cognitive questions, and analyze the implications of these models’ successes and failures for our understanding of the mind.

Offered in Winter, Spring of AY 2024-2025

Advanced Courses In Cognitive Science

In addition to the two introductory courses, the Cognitive Science major also offers several advanced courses, which can be used to fulfill elective requirements of the major. These courses generally provide an in-depth exploration of a topic within cognitive science from a multidisciplinary perspective, often with a foundation in the methods or theories of a core discipline while invoking the insights of other fields. Advanced Cognitive Science courses are designed by cognitive science faculty for the major but are NOT required for completion of the major.

COGS 20100 Perspectives on large language models: computational, cognitive, social

In this interdisciplinary course, students will delve into the multifaceted world of large language models (LLMs), investigating their computational, cognitive, and social dimensions. The course covers an array of topics, such as the history and evolution of LLMs, computational underpinnings like neural networks and training methodologies, cognitive aspects of human-like language understanding, communication, and creativity, as well as crucial ethical and social considerations, encompassing fairness, transparency, trustworthiness, and privacy. Through both lectures and discussions, we will examine the scientific and practical applications and limitations of LLMs across diverse domains and contemplate the future prospects and challenges LLMs pose for science, technology, and society. Through critical discourse, hands-on exercises, and case studies, our goal is to foster a comprehensive understanding of LLMs, empowering students to critically assess these models and contribute to ongoing dialogues regarding their broader implications. Prior experience in computer science or cognitive science is beneficial but not mandatory. Note: this course primarily focuses on cultivating reflective thinking about LLMs, rather than programming or implementation. Students with programming skills are, however, encouraged to utilize them to facilitate their learning. 

Counts toward Linguistics and Computer Science Depth requirements. 

COGS 24001 Prediction in Language Comprehension

Language tends to follow predictable patterns, from what sounds and words are about to be uttered, to what grammatical structures are likely, to be used to what broader implications are about to be suggested, and more. One prevailing hypothesis is that the human mind can take advantage of this predictability to help maintain the rapid pace of language comprehension. This course will explore critical questions surrounding the nature of prediction processes during language comprehension. What do people predict? How are their predictions constrained? How can we study the inherently internal process(es) of prediction? What are the consequences of prediction? Perhaps most importantly, what do the answers to these questions suggest about the mechanisms and computations of prediction? Readings will primarily consist of contemporary articles from peer-reviewed journals, and class meetings will be a mix of lectures and student-led discussions.

Counts toward Linguistics and Psychology Depth requirements. 

COGS 25001 Foundations of Neurolinguistics

This course will explore the cognitive and neural bases underlying language comprehension and production. Class topics will draw on historic and contemporary research invoking a range of neuroimaging techniques to examine how sound, meaning, and structure are processed in the brain. Students will also explore how theories about the computations and representations underlying human language can inform, and be informed by, the biological constraints imposed by the nervous system. Prior knowledge of neuroscience is not required, but familiarity with linguistic and psychological concepts may be beneficial.

Counts toward Linguistics, Psychology, and Neuroscience Depth requirements.

COGS 26200 Artificial Intelligence, Human Condition, Human Capacities

This seminar course will engage students from multiple disciplines in critically reflecting upon the current advancements in artificial intelligence with their implications for the human condition and human capabilities. The first group of readings will incorporate classical works by thinkers such as Hanna Arendt, Norbert Wiener, and Karl Jaspers on the human condition, and Amartya Sen and Martha Nussbaum’s works on human capacities. The second group of readings will include contemporary research papers from computer science, cognitive science, linguistics, anthropology, economics, and philosophy. Students will be asked to develop their own perspective and methodology to engage with and relate the two groups of readings, further develop their literature on the topic, and write a final research paper on the human condition in the age of AI.

Counts toward Extra-Disciplinary requirements.