This course examines the philosophical and theoretical foundations of constructionism as a paradigm for formulating and evaluating new theories for learning and approaches to education. One of the goals of this course is to help new learning researchers situate their work within the constructionist framework through readings and projects that will focus on the rich interplay between the process of knowledge construction and the development and co-evolution of ideas, learners, tools, and contexts.

This course is an introduction to problems about creativity as it pervades human experience and behavior. Questions about imagination and innovation are studied in relation to the history of philosophy as well as more recent work in philosophy, affective psychology, cognitive studies, and art theory. Readings and guidance are aligned with the student's focus of interest.

Uses sources from the time and historians' interpretations to analyze National Socialism in Germany. Topics include: the history of racist thought and policy in Germany before Nazism; the Nazi movement during the Weimar Republic; the structure of the Nazi state; Nazi policy against Jews and other groups between 1933 and 1939; Nazi economic policy; mobilization for war and the war experience in central Europe; the Holocaust; and the political roles of Nazism and the Holocaust in post-Nazi Germany.

This graduate level course presents theories, methodologies, and applications of seismic imaging for solving the shallow near-surface (0 - 500 m) effects on the seismic data processing for oil and gas exploration on land. It introduces both conventional and advanced imaging technologies that have been developed in academia and the seismic industry.

Negotiation and Conflict Management presents negotiation theory -- strategies and styles -- within an employment context. 15.667 meets only eleven times, with a different topic each week, which is why students should commit to attending all classes. In addition to the theory and exercises presented in class, students practice negotiating with role-playing simulations that cover a range of topics. Students also learn how to negotiate in difficult situations, which include abrasiveness, racism, sexism, whistle-blowing, and emergencies. The course covers conflict management as a first party and as a third party: third-party skills include helping others deal directly with their conflicts, mediation, investigation, arbitration, and helping the system change as a result of a dispute.

Investigates social conflict and distributional disputes in the public sector. While theoretical aspects of conflict are considered, focus is on the practice of dispute resolution. Comparisons between unassisted and assisted negotiation are reviewed along with the techniques of facilitation, negotiation, and nonbinding arbitration.

This course is a graduate subject in the theory and practice of network flows and its extensions. Network flow problems form a subclass of linear programming problems with applications to transportation, logistics, manufacturing, computer science, project management, and finance, as well as a number of other domains. This subject will survey some of the applications of network flows and focus on key special cases of network flow problems including the following: the shortest path problem, the maximum flow problem, the minimum cost flow problem, and the multi-commodity flow problem. We will also consider other extensions of network flow problems.

This course provides a deep understanding of engineering systems at a level intended for research on complex engineering systems. It provides a review and extension of what is known about system architecture and complexity from a theoretical point of view while examining the origins of and recent developments in the field. The class considers how and where the theory has been applied, and uses key analytical methods proposed. Students examine the level of observational (qualitative and quantitative) understanding necessary for successful use of the theoretical framework for a specific engineering system. Case studies apply the theory and principles to engineering systems.

Networks are a ubiquitous way to represent complex systems, including those in the social and economic sciences. The goal of the course is to equip students with conceptual tools that can help them understand complex systems that emerge in both nature and social systems. This is a course intended for a general audience and will discuss applications of networks and complexity to diverse systems, including epidemic spreading, social networks and the evolution of economic development.

This course will highlight common principles that permeate the functioning of networks and how the same issues related to robustness, fragility and interlinkages arise in several different types of networks. It will both introduce conceptual tools from dynamical systems, random graph models, optimization and game theory, and cover a wide variety of applications.

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 course highlights the interplay between cellular and molecular storage mechanisms and the cognitive neuroscience of memory, with an emphasis on human and animal models of hippocampal mechanisms and function. Class sessions include lectures and discussion of papers.

Surveys general principles and specific examples of motor control in biological systems. Emphasizes the neural mechanisms underlying different aspects of movement and movement planning. Covers sensory reception, reflex arcs, spinal cord organization, pattern generators, muscle function, locomotion, eye movement, and cognitive aspects of motor control. Functions of central motor structures including cerebellum, basal ganglia, and cerebral cortex considered. Cortical plasticity, motor learning and computational approaches to motor control, and motor disorders are discussed.

Understanding the brain's remarkable ability for visual object recognition is one of the greatest challenges of brain research. The goal of this course is to provide an overview of key issues of object representation and to survey data from primate physiology and human fMRI that bear on those issues. Topics include the computational problems of object representation, the nature of object representations in the brain, the tolerance and selectivity of those representations, and the effects of attention and learning.

Neural structures and mechanisms mediating the detection, localization, and recognition of sounds. Discussion of how acoustic signals are coded by auditory neurons, the impact of these codes on behavorial performance, and the circuitry and cellular mechanisms underlying signal transformations. Topics include temporal coding, neural maps and feature detectors, learning and plasticity, and feedback control. General principles are conveyed by theme discussions of auditory masking, sound localization, musical pitch, speech coding, and cochlear implants, and auditory scene analysis.

Roles of neural plasticity in learning and memory and in development of invertebrates and mammals. An in-depth critical analysis of current literature of molecular, cellular, genetic, electrophysiological, and behavioral studies. Discussion of original papers supplemented by introductory lectures.

Lectures and discussions explore the clinical, behavioral, and molecular aspects of brain aging processes in humans. Topics include: loss of memory and other cognitive abilitites in normal aging; neurodegenerative conditions such as Parkinson's and Alzheimer's diseases. Based on lectures, readings taken from the primary literature, and discussions. Students are expected to present topics based on their readings. One written mid-term test and one final examination. Alternate years.

The neuropharmacology course will discuss the drug-induced changes in functioning of the nervous system. The specific focus of this course will be to provide a description of the cellular and molecular actions of drugs on synaptic transmission. This course will also refer to specific diseases of the nervous system and their treatment in addition to giving an overview of the techniques used for the study of neuropharmacology. This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

Relation of structure and function at various levels of neuronal integration. Topics include: functional neuroanatomy and neurophysiology, sensory and motor systems, centrally programmed behavior, sensory systems, sleep and dreaming, motivation and reward, emotional displays of various types, "higher functions" and the neocortex, and neural processes in learning and memory. In order to improve writing skills in describing experiments and critiquing published research in neuroscience, students are required to complete four homework assignments and one literature review with revision.

This course explores the social relevance of neuroscience, considering how emerging areas of brain research at once reflect and reshape social attitudes and agendas. Topics include brain imaging and popular media; neuroscience of empathy, trust, and moral reasoning; new fields of neuroeconomics and neuromarketing; ethical implications of neurotechnologies such as cognitive enhancement pharmaceuticals; neuroscience in the courtroom; and neuroscientific recasting of social problems such as addiction and violence. Guest lectures by neuroscientists, class discussion, and weekly readings in neuroscience, popular media, and science studies.