In this activity, students look at census records from antebellum Five Points and compare them to depictions of the neighborhood and its residents. Students will evaluate whether observers described Five Points as a neighborhood or slum. The activity includes a Smartboard file, but can be completed without this technology.

After more than 30 years in prison and an historic election that for the first time in the nation's history included all citizens regardless of race, Nelson Rolihlahla Mandela became President of the Republic of South Africa on May 10, 1994. This Teacher's Guide includes resources for teaching about the brutality of apartheid, the resilience of the nation's people, the leadership of Nelson Mandela, and primary source materials that will inform discussion about the country's emergence in the world.

This art history video discussion looks at the Human-headed Winged Lion and Bull (Lamassu), 883--859 B.C.E., Neo-Assyrian period, reign of Ashurnasirpal II, excavated at Nimrud (ancient Kalhu), northern Mesopotamia (Metropolitan Museum of Art).

Produce light by bombarding atoms with electrons. See how the characteristic spectra of different elements are produced, and configure your own element's energy states to produce light of different colors.

This lesson describes the function and components of the human nervous system. It helps students understand the purpose of our brain, spinal cord, nerves and the five senses. How the nervous system is affected during spaceflight is also discussed in this lesson.

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.

Stimulate a neuron and monitor what happens. Pause, rewind, and move forward in time in order to observe the ions as they move across the neuron membrane.

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.