In this lesson on the brain's neural networks, students investigate the structure and function of the neuron. They discover ways in which engineers apply this knowledge to the development of devices that can activate neurons. After a review of the nervous system specifically its organs, tissue, and specialized cells, called neurons students learn about the parts of the neuron. They explore the cell body, dendrites, axon and axon terminal, and learn how these structures enable neurons to send messages. They learn about the connections between engineering and other fields of study, and the importance of research, as they complete the lesson tasks.

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.

Through six lesson/activity sets, students learn about the functioning of sensors, both human and robotic. In the activities, student groups use LEGO MINDSTORMS(TM) NXT robots and components to study human senses (sight, hearing, smell, taste, touch) in more detail than in previous units in the series. They also learn about the human made rotation, touch, sound, light and ultrasonic sensors. "Stimulus-sensor-coordinator-effector-response" pathways are used to describe the processes as well as similarities between human/animal and robotic equivalent sensory systems. The important concept of sensors converting/transducing signals is emphasized. Through assorted engineering design challenges, students program the LEGO robots to respond to input from various LEGO sensors. The overall framework reinforces the theme of the human body as a system with sensors that is, from an engineering perspective. PowerPoint® presentations, quizzes and worksheets are provided throughout the unit.

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.

Four lessons related to robots and people present students with life sciences concepts related to the human body (including brain, nervous systems and muscles), introduced through engineering devices and subjects (including computers, actuators, electricity and sensors), via hands-on LEGO® robot activities. Students learn what a robot is and how it works, and then the similarities and differences between humans and robots. For instance, in lesson 3 and its activity, the human parts involved in moving and walking are compared with the corresponding robot components so students see various engineering concepts at work in the functioning of the human body. This helps them to see the human body as a system, that is, from the perspective of an engineer. Students learn how movement results from 1) decision making, such as deciding to walk and move, and 2) implementation by conveying decisions to muscles (human) or motors (robot).

Students learn about complex networks and how to use graphs to represent them. They also learn that graph theory is a useful part of mathematics for studying complex networks in diverse applications of science and engineering, including neural networks in the brain, biochemical reaction networks in cells, communication networks, such as the internet, and social networks. Students are also introduced to random processes on networks. An illustrative example shows how a random process can be used to represent the spread of an infectious disease, such as the flu, on a social network of students, and demonstrates how scientists and engineers use mathematics and computers to model and simulate random processes on complex networks for the purposes of learning more about our world and creating solutions to improve our health, happiness and safety.

This course is an introduction to many of the central issues in a branch of philosophy called philosophy of mind.

This course will consider the degree and nature of the modular organization of the mind and brain. We will focus in detail on the domains of objects, number, places, and people, drawing on evidence from behavioral studies in human infants, children, normal adults, neurological patients, and animals, as well as from studies using neural measures such as functional brain imaging and ERPs. With these domains as examples, we will address broader questions about the role of domain-general and domain-specific processing systems in mature human performance, the innateness vs. plasticity of encapsulated cognitive systems, the nature of the evidence for such systems, and the processes by which people link information flexibly across domains.

This activity helps students understand the significance of programming and also how the LEGO MINDSTORMS(TM) NXT robot's sensors assist its movement and make programming easier. Students compare human senses to robot sensors, describing similarities and differences.

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.

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 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.

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.

Building on their understanding of graphs, students are introduced to random processes on networks. They walk through an illustrative example to see how a random process can be used to represent the spread of an infectious disease, such as the flu, on a social network of students. This demonstrates how scientists and engineers use mathematics to model and simulate random processes on complex networks. Topics covered include random processes and modeling disease spread, specifically the SIR (susceptible, infectious, resistant) model.