Print Settings
 

PSYCH 1: Introduction to Psychology

An introduction to the science of how people think, feel, and behave. We will explore such topics as intelligence, perception, memory, happiness, personality, culture, social influence, development, emotion, and mental illness. Students will learn about classic and cutting edge research, a range of methods, and discover how psychology informs our understanding of what it means to be human, addresses other fields, and offers solutions to important social problems. Psych 1 fulfills the SI Way, and, effective Autumn 2018, the SMA Way. For more information on PSYCH 1, visit http://psychone.stanford.edu
Terms: Aut, Win, Spr | Units: 5 | UG Reqs: GER:DB-SocSci, WAY-SI, WAY-SMA | Grading: Letter or Credit/No Credit

PSYCH 10: Introduction to Statistical Methods: Precalculus (STATS 60, STATS 160)

Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of hypotheses, t-tests, correlation, and regression. Possible topics: analysis of variance and chi-square tests, computer statistical packages.
Terms: Aut, Win, Spr, Sum | Units: 5 | UG Reqs: GER:DB-Math, WAY-AQR, WAY-FR | Grading: Letter or Credit/No Credit

PSYCH 30: Introduction to Perception

Behavioral and neural aspects of perception focusing on visual and auditory perception. Topics include: scientific methods for studying perception, anatomy and physiology of the visual and auditiory systems, color vision, depth perception, motion perception, stereopsis, visual recognition, pitch and loudness perception, speech perception, and reorganization of the visual system in the blind.
Terms: Aut | Units: 4 | UG Reqs: GER: DB-NatSci, WAY-SI, WAY-SMA | Grading: Letter or Credit/No Credit
Instructors: ; Grill-Spector, K. (PI)

PSYCH 45: Introduction to Learning and Memory

The literature on learning and memory including cognitive and neural organization of memory, mechanisms of remembering and forgetting, and why people sometimes falsely remember events that never happened. Cognitive theory and behavioral evidence integrated with data from patient studies and functional brain imaging. Required prerequisite: PSYCH 1.
Terms: alternate years, given next year | Units: 3 | UG Reqs: WAY-SI | Grading: Letter or Credit/No Credit

PSYCH 50: Introduction to Cognitive Neuroscience

How does our brain give rise to our abilities to perceive, act and think? Survey of the basic facts, empirical evidence, theories and methods of study in cognitive neuroscience exploring how cognition is instantiated in neural activity. Representative topics include perceptual and motor processes, decision making, learning and memory, attention, reward processing, reinforcement learning, sensory inference and cognitive control.
Terms: Win | Units: 4 | UG Reqs: GER: DB-NatSci, WAY-SI, WAY-SMA | Grading: Letter or Credit/No Credit
Instructors: ; Gardner, J. (PI)

PSYCH 60: Introduction to Developmental Psychology

Psychological development from birth to adulthood, emphasizing infancy and the early and middle childhood years. The nature of change during childhood and theories of development. Recommended: PSYCH 1.
Terms: Aut | Units: 3 | UG Reqs: GER:DB-SocSci, WAY-SI | Grading: Letter or Credit/No Credit

PSYCH 60A: Introduction to Developmental Psychology Section

Guided observation of children age 2-5 at Bing Nursery School. Corequisite: 60.
Terms: Aut | Units: 2 | Grading: Letter or Credit/No Credit

PSYCH 80: Introduction to Personality and Affective Science

How do we measure personality and emotion? What parts of your personality and emotions are set at birth? What parts of your personality and emotions are shaped by your sociocultural context? Can your personality and emotions make you sick? Can you change your personality and emotions? These are questions we begin to address in this introductory course on personality and emotion. Prerequisite: Psych 1.
Terms: Spr | Units: 3 | UG Reqs: GER:DB-SocSci, WAY-SI | Grading: Letter or Credit/No Credit

PSYCH 90: Introduction to Clinical Psychology

History of clinical psychology, models and assessment of personality, behavior, cognition, psychopathology, and approaches to the treatment of abnormal behavior. Emphasis is on current theory, research, issues in, and the role of clinical psychology in contemporary society. Recommended: 1.
Terms: not given this year | Units: 3 | UG Reqs: GER:DB-SocSci, WAY-SI | Grading: Letter (ABCD/NP)

PSYCH 95: Introduction to Abnormal Psychology

Theories of and approaches to understanding the phenomenology, etiology, and treatment of psychological disorders among adults and children. Research findings and diagnostic issues. Recommended: PSYCH 1.
Terms: Spr | Units: 3 | UG Reqs: GER:DB-SocSci, WAY-SI | Grading: Letter or Credit/No Credit

PSYCH 102S: Introduction to Neuroscience

Introduction to structure and function of the nervous system. The course first surveys neuroscience research methods, physiology, and gross anatomy. We then study the brain systems which produce basic functions such as perception and motion, as well as complex processes like sleep, memory, and emotion. Finally, we examine these principles in cases of neurological and psychiatric disorders.
Terms: Sum | Units: 3 | Grading: Letter or Credit/No Credit

PSYCH 104S: Affective Science

This course will provide an introduction to a growing field known as affective science, which focuses on the study of emotion and other related phenomena (i.e., motivation, pain, etc.). We will explore core questions in affective science, including: 1) What is emotion and why is it useful? 2) How do emotions influence the way we perceive, attend to, and understand the world? 3) How do emotions become dysfunctional, and how can individuals control them? We will attempt to approach these questions from multiple perspectives, including i) neurobiological ii) behavioral, and iii) sociocultural perspectives.
Terms: not given this year | Units: 3 | Grading: Letter or Credit/No Credit

PSYCH 108S: Introduction to Social Psychology

This course aims to blend a comprehensive overview of social psychology with in-depth lectures exploring the history of the field, reviewing major findings and highlighting areas of current research. The course will focus on classic studies that have profoundly changed our understanding of human nature and social interaction, and, in turn, have triggered significant paradigm shifts within the field. Some of the topics covered in this class will include: individuals and groups, conformity and obedience, attraction, intergroup relations, and judgment and decision-making. The course, overall, will attempt to foster interest in social psychology as well as scientific curiosity in a fun, supportive and intellectually stimulating environment.
Terms: Sum | Units: 3 | Grading: Letter or Credit/No Credit

PSYCH 109: An introduction to computation and cognition

How does the mind process information in order to choose good actions given the tangle of experience? The studies of computation and cognition synergise in diverse and powerful ways, from precise models of thinking to analysis of large behavioral data sets. In this course we will investigate questions of information representation and processing through a combination of lectures, hands-on (`flipped classroom') exercises, and extended homework assignments. We will explore method for psychological data analysis and three of the main computational approaches to modeling the mind: reinforcement learning, neural networks, and Bayesian inference. Using these tools we will explore human abilities such as reasoning and social cognition. Pre-requisites: Psych 1 and CS 106a (or consent of instructor).
Terms: not given this year | Units: 4 | Grading: Letter or Credit/No Credit

PSYCH 111S: Abnormal Psychology

This course will provide an introduction to abnormal psychology. It will be targeted towards students who have had little or no exposure to coursework on mental disorders. The course will have three core aims: 1) Explore the nature of mental disorders, including the phenomenology, signs/symptoms, and causal factors underlying various forms of mental illness, 2) Explore conventional and novel treatments for various mental disorders, 3) Develop critical thinking skills in the theory and empirical research into mental disorders. The course will explore a wide range of mental disorders, including depression, anxiety, schizophrenia, addiction, eating disorders, and personality disorders.
Terms: not given this year | Units: 3 | Grading: Letter or Credit/No Credit

PSYCH 140: Introduction to Psycholinguistics (LINGUIST 145, LINGUIST 245A)

How do people do things with language? How do we go from perceiving the acoustic waves that reach our ears to understanding that someone just announced the winner of the presidential election? How do we go from a thought to spelling that thought out in a sentence? How do babies learn language from scratch? This course is a practical introduction to psycholinguistics -- the study of how humans learn, represent, comprehend, and produce language. The course aims to provide students with a solid understanding of both the research methodologies used in psycholinguistic research and many of the well-established findings in the field. Topics covered will include visual and auditory recognition of words, sentence comprehension, reading, discourse and inference, sentence production, language acquisition, language in the brain, and language disorders. Students will conduct a small but original research project and gain experience with reporting and critiquing psycholinguistic research.
Terms: Aut | Units: 4 | Grading: Letter or Credit/No Credit

PSYCH 147S: Introduction to the Psychology of Emotion

What are emotions? What purpose do they serve? How do we measure them? Can we control them? In this course, we will explore some of the most interesting questions in psychology: questions about emotion. Emotions shape our perceptions of the world, influence critical life decisions, and allow us to connect with others. This seminar will provide a selective review of the scientific study of emotion in Affective Science. The first unit of the course will focus on the theoretical foundations, the basic science of emotion, and methods for measuring emotions. In the second unit of the course, we will discuss topics at the intersection of motivation and emotion, such as decision-making and self-control. In the third unit, we will delve into the social function of emotions. In the fourth unit of the course, we will study the ways people succeed and fail at controlling their emotions. In the fifth unit, we will discuss a variety of additional topics such as how emotions change across the lifespan, how emotions can be harnessed to engineer behavior change, as well as emotions and artificial intelligence. My goal is that you will leave this course with a scientifically-informed understanding of your own and others' emotions as well as strategies for how to effectively use and manage your feelings in daily life.
Terms: Sum | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: ; O'Leary, D. (PI)

PSYCH 155: Introduction to Comparative Studies in Race and Ethnicity (CSRE 196C, ENGLISH 172D, SOC 146, TAPS 165)

How different disciplines approach topics and issues central to the study of ethnic and race relations in the U.S. and elsewhere. Lectures by senior faculty affiliated with CSRE. Discussions led by CSRE teaching fellows. Includes an optional Haas Center for Public Service certified Community Engaged Learning section.
Terms: Spr | Units: 5 | UG Reqs: GER:DB-SocSci, GER:EC-AmerCul, WAY-ED, WAY-SI | Grading: Letter (ABCD/NP)

PSYCH 221: Image Systems Engineering

This course is an introduction to digital imaging technologies. We focus on the principles of key elements of digital systems components; we show how to use simulation to predict how these components will work together in a complete image system simulation. The early lectures introduce the software environment and describe options for the course project. The following topics are covered and software tools are introduced:n- Basic principles of optics (Snell's Law, diffraction, adaptive optics).n- Image sensor and pixel designsn- Color science, metrics, and calibrationn- Human spatial resolutionn- Image processing principlesn- Display technologiesnA special theme of this course is that it explains how imaging technologies accommodate the requirements of the human visual system. The course also explains how image systems simulations can be useful in neuroscience and industrial vision applications.nThe course consists of lectures, software tutorials, and a course project. Tutorials and projects include extensive software simulations of the imaging pipeline. Some background in mathematics (linear algebra) and programming (Matlab) is valuable.nPre-requisite: EE 261 or equivalent. Or permission of instructor required.
Terms: Aut | Units: 1-3 | Grading: Letter or Credit/No Credit

PSYCH 249: Large-Scale Neural Network Modeling for Neuroscience (CS 375)

Introduction to designing, building, and training neural networks for modeling brain and behavioral data, including: deep convolutional neural network models of sensory systems (vision, audition, somatosensation); recurrent neural networks for dynamics, memory and attention; integration of variational and generative methods for cognitive modeling; and methods and metrics for comparing such models to real-world neural data. Attention will be given both to established methods as well as cutting-edge techniques. Students will learn conceptual bases for deep neural network models, and will also implement learn to implement and train large-scale models in Tensorflow using GPUs. Requirements: Fluency in Unix shell and Python programming, familiarity with differential equations, linear algebra, and probability theory, and one or more courses in cognitive or systems neuroscience.
Terms: Aut | Units: 1-3 | Grading: Letter or Credit/No Credit

PSYCH 253: High-Dimensional Methods for Behavioral and Neural Data

Introduction to high-dimensional data analysis and machine learning methods for use in the behavioral and neurosciences, including: supervised methods such as SVMs, linear and nonlinear regression and classifiers, and regularization techniques; statistical methods such as bootstrapping, signal detection, factor analysis, and reliability theory; metrics for model/data comparison such as representational similarity analysis; and unsupervised methods such as clustering. Students will learn how to both use existing statistical data analysis packages (such as scikit-learn) as well to build, optimize, and estimate their own custom models using an optimization framework (such as Tensorflow or Pytorch). Requirement: Psych 251. Familiarity with python programming and multivariable calculus and linear algebra (Math 51) highly recommended.
Terms: Spr | Units: 3 | Grading: Letter (ABCD/NP)
© Stanford University | Terms of Use | Copyright Complaints