Barbara Oakley

Beth Rogowsky

Terrence J. Sejnowski

A groundbreaking guide to improve teaching based on the latest research in neuroscience, from the bestselling author of A Mind for Numbers. Neuroscientists and cognitive scientists have made enormous strides in understanding the brain and how we learn, but little of that insight has filtered down to the way teachers teach. Uncommon Sense Teaching applies this research to the classroom for teachers, parents, and anyone interested in improving education. Topics include: * keeping students motivated and engaged, especially with online learning * helping students remember information long-term, so it isn't immediately forgotten after a test * how to teach inclusively in a diverse classroom where students have a wide range of abilities Drawing on research findings as well as the authors' combined decades of experience in the classroom, Uncommon Sense Teaching equips readers with the tools to enhance their teaching, whether they're seasoned professionals or parents trying to offer extra support for their children's education.

Practical Insights in Brain Science to Help Students Learn

Uncommon Sense Teaching

How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.

The Deep Learning Revolution

Steven R. Quartz

This book combines cutting-edge findings in neuroscience with examples from history and the headlines to introduce the new science of cultural biology, born of advances in brain imaging, computer modeling, and genetics. Doctors Quartz and Sejnowski show how both our noblest and darkest traits are rooted in brain systems so ancient that we share them with insects. They then demystify the dynamic engagement between brain and world that makes us something far beyond the sum of our parts. The authors show how our humanity unfolds in precise stages as brain and world engage on increasingly complex levels. Their discussion embraces shaping forces as ancient as climate change over millennia and events as recent as the terrorism and heroism of September 11, and offers intriguing answers to some of our most enduring questions, including why we live together, love, kill -- and sometimes lay down our lives for others.

What the New Brain Science Reveals About How We Become Who We Are

Liars, Lovers, and Heroes

Patricia S. Churchland

An anniversary edition of the classic work that influenced a generation of neuroscientists and cognitive neuroscientists. Before The Computational Brain was published in 1992, conceptual frameworks for brain function were based on the behavior of single neurons, applied globally. In The Computational Brain, Patricia Churchland and Terrence Sejnowski developed a different conceptual framework, based on large populations of neurons. They did this by showing that patterns of activities among the units in trained artificial neural network models had properties that resembled those recorded from populations of neurons recorded one at a time. It is one of the first books to bring together computational concepts and behavioral data within a neurobiological framework. Aimed at a broad audience of neuroscientists, computer scientists, cognitive scientists, and philosophers, The Computational Brain is written for both expert and novice. This anniversary edition offers a new preface by the authors that puts the book in the context of current research. This approach influenced a generation of researchers. Even today, when neuroscientists can routinely record from hundreds of neurons using optics rather than electricity, and the 2013 White House BRAIN initiative heralded a new era in innovative neurotechnologies, the main message of The Computational Brain is still relevant.

The Computational Brain, 25th Anniversary Edition

J. Leo van Hemmen

The complexity of the brain and the protean nature of behavior remain the most elusive area of science, but also the most important. van Hemmen and Sejnowski invited 23 experts from the many areas--from evolution to qualia--of systems neuroscience to formulate one problem each. Although each chapter was written independently and can be read separately, together they provide a useful roadmap to the field of systems neuroscience and will serve as a source of inspirations for future explorers of the brain.

23 Problems in Systems Neuroscience

Wolf Singer

Pasko Rakic

Experts review the latest research on the neocortex and consider potential directions for future research. Over the past decade, technological advances have dramatically increased information on the structural and functional organization of the brain, especially the cerebral cortex. This explosion of data has radically expanded our ability to characterize neural circuits and intervene at increasingly higher resolutions, but it is unclear how this has informed our understanding of underlying mechanisms and processes. In search of a conceptual framework to guide future research, leading researchers address in this volume the evolution and ontogenetic development of cortical structures, the cortical connectome, and functional properties of neuronal circuits and populations. They explore what constitutes “uniquely human” mental capacities and whether neural solutions and computations can be shared across species or repurposed for potentially uniquely human capacities. Contributors Danielle S. Bassett, Randy M. Bruno, Elizabeth A. Buffalo, Michael E. Coulter, Hermann Cuntz, Stanislas Dehaene, James J. DiCarlo, Pascal Fries, Karl J. Friston, Asif A. Ghazanfar, Anne-Lise Giraud, Joshua I. Gold, Scott T. Grafton, Jennifer M. Groh, Elizabeth A. Grove, Saskia Haegens, Kenneth D. Harris, Kristen M. Harris, Nicholas G. Hatsopoulos, Tarik F. Haydar, Takao K. Hensch, Wieland B. Huttner, Matthias Kaschube, Gilles Laurent, David A. Leopold, Johannes Leugering, Belen Lorente-Galdos, Jason N. MacLean, David A. McCormick, Lucia Melloni, Anish Mitra, Zoltán Molnár, Sydney K. Muchnik, Pascal Nieters, Marcel Oberlaender, Bijan Pesaran, Christopher I. Petkov, Gordon Pipa, David Poeppel, Marcus E. Raichle, Pasko Rakic, John H. Reynolds, Ryan V. Raut, John L. Rubenstein, Andrew B. Schwartz, Terrence J. Sejnowski, Nenad Sestan, Debra L. Silver, Wolf Singer, Peter L. Strick, Michael P. Stryker, Mriganka Sur, Mary Elizabeth Sutherland, Maria Antonietta Tosches, William A. Tyler, Martin Vinck, Christopher A. Walsh, Perry Zurn

The Neocortex

Barbara Oakley, PhD

Beth Rogowsky EdD

Top 10 Pick for Learning Ladders’ Best Books for Educators Summer 2021 A groundbreaking guide to improve teaching based on the latest research in neuroscience, from the bestselling author of A Mind for Numbers. Neuroscientists and cognitive scientists have made enormous strides in understanding the brain and how we learn, but little of that insight has filtered down to the way teachers teach. Uncommon Sense Teaching applies this research to the classroom for teachers, parents, and anyone interested in improving education. Topics include: • keeping students motivated and engaged, especially with online learning • helping students remember information long-term, so it isn't immediately forgotten after a test • how to teach inclusively in a diverse classroom where students have a wide range of abilities Drawing on research findings as well as the authors' combined decades of experience in the classroom, Uncommon Sense Teaching equips readers with the tools to enhance their teaching, whether they're seasoned professionals or parents trying to offer extra support for their children's education.

Terrence J. Sejnowski

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