Biology is designed for multi-semester biology courses for science majors. It is grounded on an evolutionary basis and includes exciting features that highlight careers in the biological sciences and everyday applications of the concepts at hand. To meet the needs of today’s instructors and students, some content has been strategically condensed while maintaining the overall scope and coverage of traditional texts for this course. Instructors can customize the book, adapting it to the approach that works best in their classroom. Biology also includes an innovative art program that incorporates critical thinking and clicker questions to help students understand—and apply—key concepts.

By the end of this section, you will be able to:List and describe the functions of the structural components of a neuronList and describe the four main types of neuronsCompare the functions of different types of glial cells

What does the brain look like? As engineers, how can we look at neural networks without invasive surgery? In this activity, students design and build neuron models based on observations made while viewing neurons through a microscope. The models are used to explain how each structure of the neuron contributes to the overall function. Students share their models with younger students and explain what a neuron is, its function, and how engineers use their understanding of the neuron to make devices to activate neurons.

Students learn about complex networks and how to represent them using graphs. They also learn that graph theory is a useful mathematical tool for studying complex networks in diverse applications of science and engineering, such as neural networks in the brain, biochemical reaction networks in cells, communication networks, such as the internet, and social networks. Topics covered include set theory, defining a graph, as well as defining the degree of a node and the degree distribution of a graph.

Students build small-sized prototypes of mountain rescue litters rescue baskets for use in hard-to-get-to places, such as mountainous terrain to evacuate an injured person (modeled by a potato) from the backcountry. Groups design their litters within constraints: they must be stable, lightweight, low-cost, portable and quick to assemble. Students demonstrate their designs in a timed test during which they assemble the litter and transport the rescued person (potato) over a set distance.

Like transistors in a computer, synapses perform complex computations and connect the brain's non-linear processing elements (neurons) into a functional circuit. Understanding the role of synapses in neuronal computation is essential to understanding how the brain works. In this course students will be introduced to cutting-edge research in the field of synaptic neurophysiology. The course will cover such topics as synapse formation, synaptic function, synaptic plasticity, the roles of synapses in higher cognitive processes and how synaptic dysfunction can lead to disease. This course is one of many Advanced Undergraduate Seminars offered by the Biology Department at MIT. These seminars are tailored for students with an interest in using primary research literature to discuss and learn about current biological research in a highly interactive setting. Many instructors of the Advanced Undergraduate Seminars are postdoctoral scientists with a strong interest in teaching.

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.

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 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.

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.

Psychology is designed to meet scope and sequence requirements for the single-semester introduction to psychology course. The book offers a comprehensive treatment of core concepts, grounded in both classic studies and current and emerging research. The text also includes coverage of the DSM-5 in examinations of psychological disorders. Psychology incorporates discussions that reflect the diversity within the discipline, as well as the diversity of cultures and communities across the globe.Senior Contributing AuthorsRose M. Spielman, Formerly of Quinnipiac UniversityContributing AuthorsKathryn Dumper, Bainbridge State CollegeWilliam Jenkins, Mercer UniversityArlene Lacombe, Saint Joseph's UniversityMarilyn Lovett, Livingstone CollegeMarion Perlmutter, University of Michigan

By the end of this section, you will be able to:Identify the basic parts of a neuronDescribe how neurons communicate with each otherExplain how drugs act as agonists or antagonists for a given neurotransmitter system