Duke University 2008-2009 - Office of the Registrar - Duke University

across a variety of research techniques. Consent of instructor required. Instructor: Cabeza,
Labar, Purves, or Woldorff. 3 units. C-L: Neurobiology 349S, Philosophy 359S
360S. Principles in Cognitive Neuroscience II. Introduction to the cognitive neuroscience
of emotion, social cognition, executive function, development, and consciousness. Topics
also include cognitive disorders, and computer modeling. Highlights current theories,
methodological advances, and controversies. Students evaluate and synthesize findings
across a variety of research techniques. Consent of instructor required. Instructor: Cabeza,
Labar, Purves, or Woldorff. 3 units. C-L: Neurobiology 350S, Philosophy 360S
362. Functional Magnetic Resonance Imaging. The course covers all aspects of functional
magnetic resonance imaging, from its basic principles in physics, engineering, biophysics,
and physiology; through computational, analytic, and signal processing issues; to its
applications in neurobiology and cognitive neuroscience. The course will consist of weekly
lectures and integrated laboratory sessions. Lectures will be given by BIAC faculty, and will
incorporate primary readings in the field to encourage discussion. The laboratory sessions
will involve analysis of fMRI data sets that illustrate issues discussed in the lectures.
Students will gain experience both in the theoretical principles of fMRI and in the practical
aspects of experimental design and data analysis. Instructor: Huettel. 3 units. C-L:
Neurobiology 381
363S. Psychology and Neuroscience First Year Seminar I. Analysis and discussion of
current models and research in psychology and neuroscience. Focus is on theories and
research in brain-behavior relations, particularly those relevant for perception, memory, and
attention in humans and animals. Instructor: Staff. 1.5 units.
364S. PBS First Year Seminar II. Analysis and discussion of current models and research
in psychological and brain sciences. Focus is on theories and research in brain-behavior
relations, particularly those relevant for perception, memory, and attention in humans and
animals. Instructor: Staff. 1.5 units.
366. Applied Analysis of Variance. Application of analysis of variance typical in
psychology and related disciplines. Introduction to the general linear model. Foundations of
experimental design, probability, inference. Topics include: one factor ANOVA, factorial
ANOVA with two- and three-way interactions, trend analysis, within-subjects designs,
analysis of covariance, effect size and power estimation. Equips students to apply, interpret,
and report results of ANOVA. Training in the use of SAS statistical computing system.
Mandatory weekly lab sessions. Assumes undergraduate statistics course; understanding of
basic statistical concepts. Consent of instructor required. Instructor: Staff. 3 units.
367. Applied Correlation and Regression Analysis. Applications of correlation and
regression analysis typical in psychology and related disciplines. Correlation topics include:
computing, testing, and comparing zero-order, partial, and semi-partial correlation
coefficients. Regression topics include: logic of model comparison, hierarchical analysis,
effect and dummy coding, interaction effects, curvilinear effects, diagnostics, and power
estimation. Equips students to apply, interpret, and report results of correlation and multiple
regression analyses. Training in the use of the SAS statistical computing system. Mandatory
weekly lab sessions. Assumes prior graduate training in general linear model. Consent of
instructor required. Instructor: Staff. 3 units.
368. Applied Structural Equation Modeling. Applications of structural equation
modeling typical in psychology and related disciplines. Topics include: notation, path
diagrams, specification and identification, estimation, modification, power estimation,
measurement models, multivariate regression models, panel models, growth models.
Emphasis on model comparisons, limits on causal inference. Equips students to apply,
interpret, and reports results of structural equation modeling analyses. Training in the use of
relevant software. Mandatory weekly lab sessions. Prerequisite: Psychology 274 or
equivalent. Consent of instructor required. Instructor: Staff. 3 units.
369. Research Synthesis and Meta-Analysis (G). 3 units. C-L: see Education 369
Courses of Instruction 258