Psychology

Introduction to the techniques of research employed in the study of human behavior. Students gain experience in the conduct of research, including design of simple experiments, observation and measurement techniques, and the analysis of behavioral data.

An introduction to basic concepts in cognitive psychology. Topics include theories and
phenomena in areas such as attention, memory, concepts and categories, language, reasoning,
decision making, and consciousness.

Prerequisites: PSYC UN1001 An introduction to the analysis of psychological issues by anatomical, physiological, and pharmacological methods. Topics include neurons, neurotransmitters, neural circuits, human neuroanatomy, vision, learning, memory, emotion, and sleep and circadian rhythms.

Prerequisites: PSYC UN1001 or equivalent Traditional psychologists have focused primarily on answering “how?” questions regarding the mechanisms that underlie behavior (i.e. How does the system work?). In contrast, evolutionary psychologists focus primarily on answering “why?” questions (i.e. Why does this system exist, and why does it have the form it does?). This course is designed to apply our knowledge of evolutionary theory to psychology in order to answer such questions.

Prerequisites: PSYC W1001 or PSYC W1010 or the instructor's permission. An examination of definitions, theories, and treatments of abnormal behavior.

Surveys important methods, findings, and theories in the study of social influences on behavior. Emphasizes different perspectives on the relation between individuals and society.

A seminar for advanced undergraduate students exploring different areas of clinical psychology. The specific focus within clinical psychology may differ each time the course is offered, so it is possible for the course to be retaken for additional credit.

Prerequisites: the instructor's permission required; contact emccaski@barnard.edu. An introductory course in neuroscience like PSYC 1001 or PSYC 2450. Analysis of the assessment of physical and psychiatric diseases impacting the central nervous system, with emphasis on the relationship between neuropathology and cognitive and behavioral deficits.

This seminar will survey historical and modern developments in machine intelligence from fields
such as psychology, neuroscience, and computer science, and from approaches such as
cybernetics, artificial intelligence, machine learning, robotics, connectionism, neural networks,
and deep learning. The emphasis is on the conceptual understanding of topics. The course does
not include, nor require a background in, computer programming and statistics. The overall goal
is for students to become informed consumers of applications of artificial intelligence.