PSY208 Principles of Experimental Design
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Knowledge acquired through scientific research is bounded by the conditions under which the research is carried out. Consequently, informed consumers of information must understand how scientific research is carried out in order to decide what is true and what is not. This course provides an introduction to research methods in psychological science, experimental design, and data interpretation. Students will develop an appreciation for the methods involved in carrying out research on issues in psychology and, hopefully, will become critical – but not cynical – consumers of scientific results, learning to distinguish sound conclusions from those based on faulty reasoning or flawed experiments. Students in this course will gain real experience by working in a small group to design and conduct an experiment of their own, present their results as a group, and write up the results individually in an APA-style research paper.
PSY225 Cognitive Psychology
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This course is an introduction to cognitive psychology. The fundamental goal of this area of study is to understand the nature of human thought processes and how they work. Some of the issues we will examine include: How do we perceive objects and events in the world? What are the processes involved in learning and remembering? How is knowledge organized in memory and how do we access that knowledge? What are the processes involved in problem solving, decision making, and reasoning? What is the nature of expertise? What is creativity? What is intelligence? How do we understand and produce spoken and written language? Are there unconscious thought processes? What areas of the brain are involved in various cognitive processes? How does brain damage effect cognition?
PSY276 Knowledge, Brain, and Culture
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Human conceptual knowledge arises from an interaction of mind, brain, and culture. To understand the nature of conceptual knowledge, we will be examining a variety of findings from psychology (mind), neuroscience (brain), and anthropology (culture). We will examine how conceptual knowledge is organized in the human mind, whether some kinds of knowledge might be innate and some kinds of knowledge might learned, how conceptual knowledge might be acquired from the world around us, how knowledge is acquired by children, how conceptual knowledge is similar and how it varies across cultures, and how knowledge is processed and represented by the human brain. This course will be structured as a seminar, with some of the time devoted to class discussion of original research papers and some of the time devoted to lectures on related materials.
PSY300 Research Seminar
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This is the required seminar for all first-year graduate students in Psychological Sciences. The courses gives an introduction to the various program areas at Vanderbilt, provides a forum for students to discuss their first year research projects, introduces students to the grant writing process, and discusses scientific and professional ethics.
PSY351 Models of Categorization
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This course will investigate how we recognize objects, how we place objects into learned categories, and how these abilities change as we gain expertise in recognizing and classifying objects. Until quite recently, research on object recognition, categorization, and perceptual expertise have remained largely independent lines of investigation. The goal of this graduate seminar is to attempt to bridge between these various domains both empirically and theoretically. Indeed, the motivation for this course is not simply to convey the contemporary body of knowledge in each of these areas, but also to understand why some of these issues have been studied in isolation from one another and to achieve an understanding of what may have been overlooked because of that isolation and what may be gained by considering these domains together. We hope that the group effort in this seminar will generate ideas for new empirical investigation and new theoretical integration. We will be reading a wide variety of original research articles investigating behavioral studies of normal individuals, behavioral studies of brain-damaged individuals, brain imaging studies, single-unit recordings of awake behaving primates, and formal computational models. Course requirements will focus on readings, discussion, and very short reaction papers.
PSY351 Object Recognition, Categorization, and Perceptual Expertise
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This course will investigate how we recognize objects, how we place objects into learned categories, and how these abilities change as we gain expertise in recognizing and classifying objects. Until quite recently, research on object recognition, categorization, and perceptual expertise have remained largely independent lines of investigation. The goal of this graduate seminar is to attempt to bridge between these various domains both empirically and theoretically. Indeed, the motivation for this course is not simply to convey the contemporary body of knowledge in each of these areas, but also to understand why some of these issues have been studied in isolation from one another and to achieve an understanding of what may have been overlooked because of that isolation and what may be gained by considering these domains together. We hope that the group effort in this seminar will generate ideas for new empirical investigation and new theoretical integration. We will be reading a wide variety of original research articles investigating behavioral studies of normal individuals, behavioral studies of brain-damaged individuals, brain imaging studies, single-unit recordings of awake behaving primates, and formal computational models. Course requirements will focus on readings, discussion, and very short reaction papers.
PSY351 Computational Modeling
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This course will provide an overview of the how-to’s and the why’s of computational modeling. This course is not intended to be a general survey of computational models of human cognition. Instead, we will talk about how to implement a model, how to fit a model to data, how to evaluate the fit of a model, how to compare and contrast competing models, how to evaluate special cases of a model, and how to develop and test new models. We will primarily talk about models that account for response probabilities, response times, and neurophysiology in a few selected domains. We will also talk about why we develop and test models, when it is appropriate and inappropriate to test models, what are the best ways to use modeling most effectively, and what we can learn from models. This course complements the Computational Cognitive Neuroscience course that David Noelle teaches, so there will be little discussion of neural network models or connectionist learning algorithms. However, all of the tools and techniques that we will go over in this course can be applied to evaluating neural network models as well.