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11 - 20 of 21 results for: PSYCH 1: Introduction to Psychology

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

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.
Last offered: Summer 2015

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

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).

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.
Last offered: Summer 2018

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

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
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

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

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
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