Courses tagged with "Information environments" (48)

Probability theory captures a number of essential characteristics of human cognition, including aspects of perception, reasoning, belief revision, and learning. Expressions of degree of belief were used in language long before people began codifying the laws of probability theory. This course explores the history and debates over codifying the laws of probability, how probability theory applies to specific cognitive processes, how it relates to the human understanding of causality, and how new computational approaches to causal modeling provide a framework for understanding human probabilistic reasoning.

This class is suitable for advanced undergraduates or graduate students specializing in cognitive science, artificial intelligence, and related fields.

This course covers the principles of materials science and cell biology underlying the design of medical implants, artificial organs, and matrices for tissue engineering. Methods for biomaterials surface characterization and analysis of protein adsorption on biomaterials. Molecular and cellular interactions with biomaterials are analyzed in terms of unit cell processes, such as matrix synthesis, degradation, and contraction. Mechanisms underlying wound healing and tissue remodeling following implantation in various organs. Tissue and organ regeneration. Design of implants and prostheses based on control of biomaterials-tissue interactions. Comparative analysis of intact, biodegradable, and bioreplaceable implants by reference to case studies. Criteria for restoration of physiological function for tissues and organs.

This course is a seminar in real-time language comprehension. It considers models of sentence and discourse comprehension from the linguistic, psychology, and artificial intelligence literature, including symbolic and connectionist models. Topics include ambiguity resolution and linguistic complexity; the use of lexical, syntactic, semantic, pragmatic, contextual and prosodic information in language comprehension; the relationship between the computational resources available in working memory and the language processing mechanism; and the psychological reality of linguistic representations.

Lectures and discussions in this course cover the clinical, behavioral, and molecular aspects of the brain aging processes in humans. Topics include the loss of memory and other cognitive abilities in normal aging, as well as neurodegenerative conditions such as Parkinson's and Alzheimer's diseases. Discussions based on readings taken from primary literature explore the current research in this field.

Lectures, reading, and discussion of current theory and data concerning the psychology and biology of language acquisition. Emphasizes learning of syntax and morphology, together with some discussion of phonology, and especially research relating grammatical theory and learnability theory to empirical studies of children.

Numerical methods for solving problems arising in heat and mass transfer, fluid mechanics, chemical reaction engineering, and molecular simulation. Topics: numerical linear algebra, solution of nonlinear algebraic equations and ordinary differential equations, solution of partial differential equations (e.g. Navier-Stokes), numerical methods in molecular simulation (dynamics, geometry optimization). All methods are presented within the context of chemical engineering problems. Familiarity with structured programming is assumed. The examples will use MATLAB®.

Acknowledgements

The instructor would like to thank Robert Ashcraft, Sandeep Sharma, David Weingeist, and Nikolay Zaborenko for their work in preparing materials for this course site.

An advanced seminar on issues of current interest in human and machine vision. Topics vary from year to year. This year, the class will involve studying the perception of materials. Participants discuss current literature as well as their ongoing research. Topics are tackled from multiple standpoints, including optics, psychophysics, computer graphics and computer vision.

5.451 is a half-semester introduction to natural product biosynthetic pathways. The course covers the assembly of complex polyketide, peptide, terpene and alkaloid structures. Discussion topics include chemical and biochemical strategies used to elucidate natural product pathways.

The goal of this course is to teach both the fundamentals of nuclear cell biology as well as the methodological and experimental approaches upon which they are based. Lectures and class discussions will cover the background and fundamental findings in a particular area of nuclear cell biology. The assigned readings will provide concrete examples of the experimental approaches and logic used to establish these findings. Some examples of topics include genome and systems biology, transcription, and gene expression.

The course includes survey and special topics designed for graduate students in the brain and cognitive sciences. It emphasizes ethological studies of natural behavior patterns and their analysis in laboratory work, with contributions from field biology (mammology, primatology), sociobiology, and comparative psychology. It stresses mammalian behavior but also includes major contributions from studies of other vertebrates and of invertebrates. It covers some applications of animal-behavior knowledge to neuropsychology and behavioral pharmacology.

The course focuses on the problem of supervised learning within the framework of Statistical Learning Theory. It starts with a review of classical statistical techniques, including Regularization Theory in RKHS for multivariate function approximation from sparse data. Next, VC theory is discussed in detail and used to justify classification and regression techniques such as Regularization Networks and Support Vector Machines. Selected topics such as boosting, feature selection and multiclass classification will complete the theory part of the course. During the course we will examine applications of several learning techniques in areas such as computer vision, computer graphics, database search and time-series analysis and prediction. We will briefly discuss implications of learning theories for how the brain may learn from experience, focusing on the neurobiology of object recognition. We plan to emphasize hands-on applications and exercises, paralleling the rapidly increasing practical uses of the techniques described in the subject.

This series of research talks by members of the Department of Brain and Cognitive Sciences introduces students to different approaches to the study of the brain and mind.

Topics include:

• From Neurons to Neural Networks
• Prefrontal Cortex and the Neural Basis of Cognitive Control
• Hippocampal Memory Formation and the Role of Sleep
• The Formation of Internal Modes for Learning Motor Skills
• Look and See: How the Brain Selects Objects and Directs the Eyes
• How the Brain Wires Itself