Global Arc

This course will be an upper level seminar that will attempt to synthesize research from multiple disciplines on how faces are represented in cognitive, computational, and neural systems. The material covered will include work on the role played by face perception in social cognition. The methods used in the research to be discussed include cognitive-behavioral measures, functional brain imaging, electro- and magnetoencephalography, single cell recording, lesion studies, and computer vision. The reading will include review articles and research reports.

In this course, we will examine how the nervous system controls movements, how the brain handles enormous computational complexities of movement, how motor skills are learned and consolidated, and how the motor system influences cognition.

Understanding inter-group conflict is a central topic across the social sciences. What are its antecedents? How does it evolve and becomes intractable? How can it be stopped once triggered? This course is aimed at providing a framework for integrating different approaches to intergroup conflict, from psychology (social-interactionism) to sociology (social network analysis) to political science (nationalism studies). Various inter-group conflicts are discussed (e.g., the Former Yugoslavian Republics, Israel-Palestine, Northern Ireland) with the goal of assessing the validity of the interdisciplinary framework proposed herein.

Seminar designed to expose students to current research on the cellular and molecular bases of learning and memory, providing an up-to-date analysis of what is, and is not, known about the neurobiology of learning and memory. We begin with a review of the model systems used to study learning and memory, including an analysis of the translational validity of certain model systems. We then deal with different forms of plasticity (synaptic and structural) as they pertain to learning and memory during development and adulthood. Finally, we apply some of these findings to evaluate the current status of research on aging and Alzheimer's.

A fundamental property of human action is its orientation toward specific desired outcomes or goals. Understanding the computations and neural mechanisms underlying this goal-directedness stands as a central challenge for both psychology & neuroscience. We will review major theories characterizing the role of goals in behavior, from cognitive, social & developmental psychology, animal behavior research, & artificial intelligence. We'll then review a wide range of neuroscientific data in an effort to sketch out the neural substrates of goal-directed behavior, considering the neural basis of goal evaluation, selection, representation & pursuit.

Neuroethics concerns ethical issues arising from neuroscience, the study of the brain and behavior. Some of these issues come from the introduction of new technologies, such as brain imaging and brain stimulation. Others come from the development of new drugs that may affect memory, mood and thought. Others are older questions, such as when does human life end and what type of experiments should be done on human and animals subjects. We will consider these and other ethical problems that have been, or are likely to be, raised from developments in neuroscience.

This course will provide an overview of several theoretical orientations to psychotherapy and critically evaluate how the effects of therapies are measured and studied. Cognitive-behavioral approaches to psychotherapy will be explored in depth. Application of research findings to clinical practice will be examined closely, including issues related to psychotherapy integration and the treatment of diverse populations in various settings. The course will also include reviews of the current state of psychotherapy research for a number of psychological disorders and consider current controversies in the area of treatment outcome research.

This seminar explores parallels between human cognition and ideas in probability and statistics, with an emphasis on statistical machine learning. Minds and machines face similar computational problems, meaning that we can develop new hypotheses about human cognition by seeing how those problems are solved in computer science and statistics and find new challenges for AI and machine learning by studying human cognition.

An overview of research topics and methods in quantitative biology through reading and discussion of primary literature. Students read two papers weekly, each showcasing how modern experimental and analytical techniques are applied to address basic questions in biology with a strong focus on big data. Students examine the achievements and impact of each study, present context and background, dissect experimental and analytical approaches, and highlight remaining challenges. Topics range from gene regulation and organellar dynamics to virology and cancer genomics. Prereqs: MOL 214 or equivalent or permission of the instructors.

Advances in molecular biology and computation have propelled the study of genomics forward, including how genes are organized and how their regulation manifests complex phenotypes. A hallmark of genomics is the production and analysis of large data sets. This course will pair an overview of genomics with practical instruction in the analytical techniques required to use it in research and medicine. We will start with a primer on genetics and an introduction to programming using Python. The goal of this course is to provide a foundation for understanding the data heavy experiments that are increasingly common in biomedical research.