Courses tagged with "Information control" (69)

This course deals with the application of structure and theory to the study of organic reaction mechanisms: Stereochemical features including conformation and stereoelectronic effects; reaction dynamics, isotope effects and molecular orbital theory applied to pericyclic and photochemical reactions; and special reactive intermediates including carbenes, carbanions, and free radicals.

This course deals with the biology of cells of higher organisms: The structure, function, and biosynthesis of cellular membranes and organelles; cell growth and oncogenic transformation; transport, receptors, and cell signaling; the cytoskeleton, the extracellular matrix, and cell movements; chromatin structure and RNA synthesis.

Provides a comprehensive introduction to key issues and findings in object recognition in experimental, neural, computational, and applied domains. Emphasizes the problem of representation, exploring the issue of how 3-D objects should be encoded so as to efficiently recognize them from 2-D images. Second half focuses on face recognition, an ecologically important instance of the general object recognition problem. Describes experimental studies of human face recognition performance and recent attempts to mimic this ability in artificial computational systems.

Parkinson's disease (PD) is a chronic, progressive, degenerative disease of the brain that produces movement disorders and deficits in executive functions, working memory, visuospatial functions, and internal control of attention. It is named after James Parkinson (1755-1824), the English neurologist who described the first case.

This six-week summer workshop explored different aspects of PD, including clinical characteristics, structural neuroimaging, neuropathology, genetics, and cognitive function (mental status, cognitive control processes, working memory, and long-term declarative memory).  The workshop did not take up the topics of motor control, nondeclarative memory, or treatment. 

This course covers central topics in language processing, including: the structure of language; sentence, discourse, and morphological processing; storage and access of words in the mental dictionary; speech processing; the relationship between the computational resources available in working memory and the language processing mechanism; and ambiguity resolution. The course also considers computational modeling, including connectionist models; the relationship between language and thought; and issues in language acquisition including critical period phenomena, the acquisition of speech, and the acquisition of words. Experimental methodologies such as self-paced reading, eye-tracking, cross-modal priming, and neural imaging methods are also examined.

What are the circuits, mechanisms and representations that permit the recognition of a visual scene from just one glance? In this one-day seminar on Scene Understanding, speakers from a variety of disciplines - neurophysiology, cognitive neuroscience, visual cognition, computational neuroscience and computer vision - will address a range of topics related to scene recognition, including natural image categorization, contextual effects on object recognition, and the role of attention in scene understanding and visual art. The goal is to encourage exchanges between researchers of all fields of brain sciences in the burgeoning field of scene understanding.

This course provides an introduction to important philosophical questions about the mind, specifically those that are intimately connected with contemporary psychology and neuroscience. Are our concepts innate, or are they acquired by experience? (And what does it even mean to call a concept 'innate'?) Are 'mental images' pictures in the head? Is color in the mind or in the world? Is the mind nothing more than the brain? Can there be a science of consciousness? The course will include guest lectures by Professors.

This course emphasizes statistics as a powerful tool for studying complex issues in behavioral and biological sciences, and explores the limitations of statistics as a method of inquiry. The course covers descriptive statistics, probability and random variables, inferential statistics, and basic issues in experimental design. Techniques introduced include confidence intervals, t-tests, F-tests, regression, and analysis of variance. Assignments include a project in data analysis.

Survey and special topics designed for students in Brain and Cognitive Sciences. Emphasizes ethological studies of natural behavior patterns and their analysis in laboratory work, with contributions from field biology (mammology, primatology), sociobiology, and comparative psychology. Stresses human behavior but also includes major contributions from studies of other animals.

5.33 focuses on advanced experimentation, with particular emphasis on chemical synthesis and the fundamentals of quantum chemistry, illustrated through molecular spectroscopy. The written and oral presentation of experimental results is also emphasized in the course.

Acknowledgements

The materials for 5.33 reflect the work of many faculty members associated with this course over the years.