Winter 2021

Permission forms will be accepted for Winter 2021 courses beginning on July 8, 2020.  Note that all the PSYC courses listed below are accepted towards the Psychology major, but only some are accepted towards the Neuroscience major.

PSYC 60

Principles of Human Brain Mapping with fMRI

In 21W, Remote with synchronous components in the K block, Emily Finn

This course is designed to introduce students to the theoretical and practical issues involved in conducting functional magnetic resonance imaging (fMRI) experiments of cognitive and behaviorally-related brain activity. Participants will gain an understanding of the physiological principles underlying the fMRI signal change, as well as the considerations for experimental design. The course will include firsthand exposure to the scanning environment and data collection procedures. Participants will be provided conceptual and hands-on experience with image processing and statistical analysis. At the completion of this course, it is expected that participants will be prepared to critique, design and conduct fMRI studies; appreciate limitations and potentials of current fMRI methods and techniques; and better understand the broad range of expertise required in an fMRI research program. The course is designed to provide the participant with intensive, hands-on instruction. As a result, enrollment in the course will be limited to 12 people. Knowledge of MR physics, signal processing, or the UNIX/Linux operating system is not a prerequisite.

Approved course for the Neuroscience major/minor.
Prerequisite: Instructor permission via the department website.

PSYC 80.02

Neuroeconomics

In 21W, Remote with synchronous components in the J block, Alireza Soltani

Neuroeconomics is an emerging field in which a combination of methods from neuroscience, psychology, and economics is used to better understand how we make decisions. In this seminar course, we learn about economic and psychological theories that are used to investigate and interpret choice behavior, and mental and neural processes that underlie decision making. We also examine how recent neurobiological discoveries are used to refine decision theories and models developed in psychology and economics. During this course, students will read and discuss the most current research findings in neuroeconomics. They will also learn to develop new ideas/hypotheses and design experiments to test those ideas/hypotheses, or to use their knowledge to inform society about the implications of findings in the field of neuroeconomics. 

Approved course for the Neuroscience major/minor.
Prerequisite: Instructor permission via the department website

PSYC 81.11

Real World Scene Perception

In 21W, in the J block, Caroline Robertson

We experience our visual environment as a seamless, immersive panorama. Yet, each view of this environment is discrete and fleeting, separated by expansive eye movements and discontinuous views of our surroundings. How does the brain build a unified representation of an immersive, real-world visual environment? This course will discuss the scientific literature of real-world visual scene understanding.  The topics we will cover in this course cut across human, animal, and computational studies, addressing questions such as: What are the circuits and mechanisms that enable the recognition of a visual scene from just one glance? How are the representational dimensions of visual scenes mapped onto the surface of the brain? How can our understanding of human scene perception guide machine vision systems?

Approved course for the Neuroscience major/minor.
Prerequisite: One of PSYC 6, PSYC 21, or PSYC 28 and instructor permission via the department website.

PSYC 81.12

Using Naturalistic Stimuli, Brain Imaging, and Big Data Methods to Understand Human Cognition

In 21W, Remote with synchronous components in the E block, James Haxby

Natural human experience involves a continuous stream of incoming stimuli in a rich context of prior knowledge and expectations.  Traditionally, experimental psychology attempts to reduce this complexity using controlled experiments that vary a single, experimental variable and hold other, control variables constant.  Human cognition, however, develops to extract information and guide behavior based on uncontrolled, naturalistic stimuli in an ecologically rich environment.  In this seminar we will examine a new approach to experimental cognitive research that uses uncontrolled, naturalistic stimuli and discovers structure and meaning in the brain activity and behavioral responses they evoke using advanced computational methods from machine learning and big data analysis.  We will discuss the advantages of this new approach for studying complex and ecological cognition and the limitations of the current state-of-the-art.  Throughout the course we will consider future directions and challenges for extending this approach into new domains of cognition, developing richer naturalistic stimulation paradigms, and developing more powerful methods for discovering the structure of information in real world events and environments.

Approved course for the Neuroscience major/minor.
Prerequisite: Permission of instructor.  Background in psychological and brain imaging research methods, computer science, and machine learning will be helpful, but students need not have background in all of these areas.

PSYC 70 and PSYC 88-91

Independent and Honors Research

See Independent Research for more info on PSYC 70 (Neuroscience Research), PSYC 88 (Independent Psychology Research) and PSYC 90 (Independent Neuroscience Research).

See Psychology Honors for more info on PSYC 89 (Honors Psychology Research)

See Neuroscience Honors for more info on PSYC 91 (Honors Neuroscience Research)