This course will explore the relations between brain activity and cognitive function in mammals. Aspects of cognition investigated will include (but will not be restricted to) working memory, attention, decision processing, executive function, categorization, planning, and sequence processing. Each subtopic will be approached from behavioral and physiological perspectives, linking characteristics of psychophysical performance at a behavioral level to neurophysiological events at cellular and systems levels. Disruption of cognitive function following brain damage will be addressed. The course will draw on both current texts and current research literature investigating the cellular bases of cognitive operations and provide a critical examination of techniques presently in use, including extracellular recording of single neuron activity in nonhuman primates, as well as functional neuroimaging and magnetoencephalography in humans. Students will be required to engage in critical discussions of recent studies and will gain an appreciation for the state and direction of the field from an experimental perspective.

Cognitive science is the interdisciplinary study of the mind. In this course, we will explore fundamental issues in cognitive science. For example, what is cognitive science, and what is its history? What is the mind? How is the mind related to the brain? How do the mind and brain represent and process information? How is language related to thought? How do emotion and subjectivity fit into the science of cognition? How do the sciences, e.g. genetics and neuroscience, challenge free will and our sense of self? Is the scientific study of consciousness possible?

Present-day views about what underlies the language faculty are largely concentrated at two extremes, presuming either a rich, sui-generis UG and not much else, or broadly general principles of cognition and perception and not much else. In Analogy as Structure and Process, the central text for this course, author Esa Itkonen takes a middle way, in which a not so rich but still sui-generis UG works in concert with general principles of cognition and perception, with a central position accorded to analogy on the general-principles side. In this course we will examine and evaluate his case for this position. If time permits we will also take up his treatment of analogy outside the domain of linguistics.

Requirements: Students in both courses will be required to write a paper on a relevant topic; students in 8900 will additionally be required to do an oral presentation.

The course will be in journal club format, in which participants present and discuss recent original research papers. The topic for this semester will be "Predictive Coding."

Sensory systems are faced with a constant onslaught of signals occurring over a wide range of signal intensities. To make efficient use of their limited capacity, these systems use predictive coding to filter out predictable elements and only convey the most interesting and potentially informative information. The classic form of predictive coding is adaptation, but recently far more sophisticated adjustments to input statistics have be found, including coding changes according higher-order statistics, such as temporal sequences,and cross-modal regularities. This semester will examine experimental papers from a variety of sensory modalities including touch, taste, audition, and vision, as well as theoretical papers considering mechanisms underlying these higher forms of adaptation and their behavioral and perceptual relevance.

All interested students, faculty members, and postdocs are encouraged to attend. The course typically attracts participants from a variety of departments and perspectives. Students enrolled in the course will be expected to lead the discussion of 2 papers each session. The initial meeting will held on Tuesday, Jan 22. At this meeting I will go over course requirements, and we will discuss the following paper:

• Spontaneous cortical activity reveals hallmarks of an optimal internalmodel of the environment P. Berkes and G. Orbán and M. Lengyel and J. Fiser Science 331 83-7 (2011)

The tentative reading list for the semester can be seen at:
http://www.ghoselab.cmrr.umn.edu/Classes/8217/PredictiveCoding.html

This lecture, discussion, and presentation-based class examines the different ways that theoretical neuroscience has attempted to integrate experimental results. Topics range from single-cell models to information-processing, network, system, and decision-making models, with an emphasis on the relation between theory and experiment.

Signal Detection Theory (SDT) is a broad set of concepts and tools that have found wide application in areas of psychology, neuroscience, medicine, and in many other fields. In psychology its contributions are both methodological and theoretical. Its methodological contributions are a set of procedures that enable distinction between "sensitivity" and "bias" and, more generally, techniques for analyzing behavioral data in both laboratory and practical settings. The theoretical contributions are that SDT provides a sophisticated framework for thinking about and describing behavior, especially perceptual behavior.

This lecture course is an introduction to SDT. Although the emphasis is on applications in psychology, the basic concepts and tools readily generalize to many other areas. The course involves mathematics, especially elementary probability theory. The necessary mathematical skills will be reviewed during the first 2 weeks. The text is Wickens, T.D., Elementary Signal Detection Theory, Oxford Univ. Press, 2002. There will be additional readings, problem sets, and a final paper.

Questions? Contact me at nfv@umn.edu, 625-4024