Students learn about the similarities between the human brain and its engineering counterpart, the computer. Since students work with computers routinely, this comparison strengthens their understanding of both how the brain works and how it parallels that of a computer. Students are also introduced to the "stimulus-sensor-coordinator-effector-response" framework for understanding human and robot actions.

This course has been designed as a seminar to give students an understanding of how scientists with medical or scientific degrees conduct research in both hospital and academic settings. There will be interactive discussions with research clinicians and scientists about the career opportunities and research challenges in the biomedical field, which an MIT student might prepare for by obtaining an MD, PhD, or combined degrees. The seminar will be held in a case presentation format, with topics chosen from the radiological sciences, including current research in magnetic resonance imaging, positron emission tomography and other nuclear imaging techniques, and advances in radiation therapy. With the lectures as background, we will also examine alternative and related options such as biomedical engineering, medical physics, and medical engineering. We'll use as examples and points of comparisons the curriculum paths available through MIT's Department of Nuclear Science and Engineering. In past years we have given very modest assignments such as readings in advance of or after a seminar, and a short term project.

Students continue their exploration of the human senses and their engineering counterparts, focusing on the auditory sense. Working in small groups, students design, create and run programs to control the motion of LEGO® TaskBots. By doing this, they increase their understanding of the use and function of sound sensors, gain experience writing robot programs, and reinforce their understanding of the sensory process.

Students gain a deeper understanding of how sound sensors work through a hands-on design challenge involving LEGO MINDSTORMS(TM) NXT taskbots and sound sensors. Student groups each program a robot computer to use to the sound of hand claps to control the robot's movement. They learn programming skills and logic design in parallel. They experience how robots can take sensor input and use it to make decisions to move and turn, similar to the human sense of hearing. A PowerPoint® presentation and pre/post quizzes are provided.

Students' understanding of how robotic ultrasonic sensors work is reinforced in a design challenge involving LEGO MINDSTORMS(TM) NXT robots and ultrasonic sensors. Student groups program their robots to move freely without bumping into obstacles (toy LEGO people). They practice and learn programming skills and logic design in parallel. They see how robots take input from ultrasonic sensors and use it to make decisions to move, resulting in behavior similar to the human sense of sight but through the use of sound sensors, more like echolocation. Students design-test-redesign-retest to achieve successful programs. A PowerPoint® presentation and pre/post quizzes are provided.

Students' understanding of how robotic light sensors work is reinforced in a design challenge involving LEGO MINDSTORMS(TM) NXT robots and light sensors. Working in pairs, students program LEGO robots to follow a flashlight as its light beam moves around. Students practice and learn programming skills and logic design in parallel. They see how robots take input from light sensors and use it to make decisions to move, similar to the human sense of sight. Students also see how they perform the steps of the engineering design process in the course of designing and testing to achieve a successful program. A PowerPoint® presentation and pre/post quizzes are provided.

Advances in cognitive science have resolved, clarified, and sometimes complicated some of the great questions of Western philosophy: what is the structure of the world and how do we come to know it; does everyone represent the world the same way; what is the best way for us to act in the world. Specific topics include color, objects, number, categories, similarity, inductive inference, space, time, causality, reasoning, decision-making, morality and consciousness. Readings and discussion include a brief philosophical history of each topic and focus on advances in cognitive and developmental psychology, computation, neuroscience, and related fields. At least one subject in cognitive science, psychology, philosophy, linguistics, or artificial intelligence is required. An additional project is required for graduate credit.

Emphasis will be placed upon application of psychological knowledge to daily situations, and upon accessing and assessing information from a variety of sources about behavior. Skills in scientific reasoning and critical thinking will be developed during this course. Areas of psychology to be included are: research methods, neuroscience, human development, perception, consciousness, learning, memory, intelligence, motivation, emotion, personality, psychological disorders, psychotherapy, stress and health, and social psychology.Login: guest_oclPassword: ocl

Students learn about the anatomy of the ear and how the ears work as a sound sensor. Ear anatomy parts and structures are explained in detail, as well as how sound is transmitted mechanically and then electrically through them to the brain. Students use LEGO® robots with sound sensors to measure sound intensities, learning how the NXT brick (computer) converts the intensity of sound measured by the sensor input into a number that transmits to a screen. They build on their experiences from the previous activities and establish a rich understanding of the sound sensor and its relationship to the TaskBot's computer.

This lesson highlights the similarities between human sensors and their engineering counterparts. Taking this approach enables students to view the human body as a system, that is, from the perspective of an engineer. Humans have recreated most human sensors in robots – eyes, ears and sensors for temperature, touch and smell. The lesson inculdes a PowerPoint file that is programmed to run a Jeopardy-style game as a fun assessment tool.

Students learn more about how light sensors work, reinforcing their similarities to the human sense of sight. They look at the light sensing process incoming light converted to electrical signals sent to the brain through the human eye anatomy as well as human-made electrical light sensors. A mini-activity, which uses LEGO MINDSTORMS(TM) NXT intelligent bricks and light sensors gives students a chance to investigate how light sensors function in preparation for the associated activity involving the light sensors and taskbots. A PowerPoint® presentation explains stimulus-to-response pathways, sensor fundamentals, and details about the LEGO light sensor, including its two modes of gathering data and what its numerical value readings mean. Students take pre/post quizzes and watch a short online video. This lesson and its associated activity enable students to gain a deeper understanding of how robots can take sensor input and use it to make decisions via programming.

Students learn about how sound sensors work, reinforcing their similarities to the human sense of hearing. They look at the hearing process sound waves converted to electrical signals sent to the brain through human ear anatomy as well as sound sensors. A mini-activity, which uses LEGO MINDSTORMS(TM) NXT intelligent bricks and sound sensors gives students a chance to experiment with the sound sensors in preparation for the associated activity involving the sound sensors and taskbots. A PowerPoint® presentation explains stimulus-to-response pathways, sensor fundamentals, the unit of decibels, and details about the LEGO sound sensor, including how readings are displayed and its three modes of programming sound input. Students take pre/post quizzes and watch a short online video. This lesson and its associated activity enable students to appreciate how robots can take sensor input and use it to make decisions to via programming.

Students learn about how touch sensors work, while reinforcing their similarities to the human sense of touch. They look at human senses and their electronic imitators, with special focus on the nervous system, skin and touch sensors. A PowerPoint® presentation explains stimulus-to-response pathways, how touch sensors are made and work, and then gives students a chance to handle and get familiar with the LEGO touch sensor, including programming LEGO MINDSTORMS(TM) NXT robots to use touch sensor input to play music. Students take pre/post quizzes and watch a short online video. The mini-activities prepare students for the associated activity. This lesson and its associated activity enables students to appreciate how robots can take input from sensors, and use that to make decisions to move.

Students learn about how ultrasonic sensors work, reinforcing the connection between this sensor and how humans, bats and dolphins estimate distance. They learn the echolocation process sound waves transmitted, bounced back and received, with the time difference used to calculate the distance of objects. Two mini-activities, which use LEGO MINDSTORMS(TM) NXT robots and ultrasonic sensors, give students a chance to experiment with ultrasonic sensors in preparation for the associated activity. A PowerPoint® presentation explains stimulus-to-response pathways, sensor fundamentals, and details about the LEGO ultrasonic sensor. Pre/post quizzes are provided. This lesson and its associated activity enable students to gain a deeper understanding of how robots can take sensor input and use it to make decisions via programming.

Students are provided with a rigorous background in human "sensors" (including information on the main five senses, sensor anatomies, and nervous system process) and their engineering equivalents, setting the stage for three associated activities involving sound sensors on LEGO® robots. As they learn how robots receive input from sensors, transmit signals and make decisions about how to move, students reinforce their understanding of the human body's sensory process.

Students' understanding of how robotic touch sensors work is reinforced through a hands-on design challenge involving LEGO MINDSTORMS(TM) NXT intelligent bricks, motors and touch sensors. They learn programming skills and logic design in parallel as they program robot computers to play sounds and rotate a wheel when a touch sensor is pressed, and then produce different responses if a different touch sensor is activated. Students see first-hand how robots can take input from sensors and use it to make decisions to move as programmed, including simultaneously moving a motor and playing music. A PowerPoint® presentation and pre/post quizzes are provided.

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.

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.

Students learn about the human body's system components, specifically its sensory systems, nervous system and brain, while comparing them to robot system components, such as sensors and computers. The unit's life sciences-to-engineering comparison is accomplished through three lessons and five activities. The important framework of "stimulus-sensor-coordinator-effector-response" is introduced to show how it improves our understanding the cause-effect relationships of both systems. This framework reinforces the theme of the human body as a system from the perspective of an engineer. This unit is the second of a series, intended to follow the Humans Are Like Robots unit.

Vision is the primary sense of many animals and much is known about how vision is processed in the mammalian nervous system. One distinct property of the primary visual cortex is a highly organized pattern of sensitivity to location and orientation of objects in the visual field. But how did we learn this? An important tool is the ability to design experiments to map out the structure and response of a system such as vision. In this activity, students learn about the visual system and then conduct a model experiment to map the visual field response of a Panoptes robot. (In Greek mythology, Argus Panoptes was the "all-seeing" watchman giant with 100 eyes.) A simple activity modification enables a true black box experiment, in which students do not directly observe how the visual system is configured, and must match the input to the output in order to reconstruct the unseen system inside the box.