Stanislas Dehaene Libri

“There are words that are so familiar they obscure rather than illuminate the thing they mean, and ‘learning’ is such a word. It seems so ordinary, everyone does it. Actually it’s more of a black box, which Dehaene cracks open to reveal the awesome secrets within.”--The New York Times Book Review An illuminating dive into the latest science on our brain's remarkable learning abilities and the potential of the machines we program to imitate them The human brain is an extraordinary learning machine. Its ability to reprogram itself is unparalleled, and it remains the best source of inspiration for recent developments in artificial intelligence. But how do we learn? What innate biological foundations underlie our ability to acquire new information, and what principles modulate their efficiency? In How We Learn, Stanislas Dehaene finds the boundary of computer science, neurobiology, and cognitive psychology to explain how learning really works and how to make the best use of the brain’s learning algorithms in our schools and universities, as well as in everyday life and at any age.

An illuminating dive into the latest science on our brain's remarkable learning abilities and the potential of the machines we program to imitate them The human brain is an extraordinary machine. Its ability to process information and adapt to circumstances by reprogramming itself is unparalleled and it remains the best source of inspiration for recent developments in artificial intelligence. In How We Learn, Stanislas Dehaene decodes the brain's biological mechanisms, delving into the neuronal, synaptic, and molecular processes taking place. He explains why youth is such a sensitive period, during which brain plasticity is maximal, but assures us that our abilities continue into adulthood and that we can enhance our learning and memory at any age. We can all learn to learn by taking maximal advantage of the four pillars of the brain's learning algorithm: attention, active engagement, error feedback, and consolidation. The exciting advancements in artificial intelligence of the last twenty years reveal just as much about our remarkable abilities as they do about the potential of machines. How We Learn finds the boundary of computer science, neurobiology, and cognitive psychology to explain how learning really works and how to make the best use of the brain's learning algorithms, in our schools and universities, as well as in everyday life.

'Absorbing, mind-enlarging, studded with insights ... This could have significant real-world results' Sunday Times Humanity's greatest feat is our incredible ability to learn. Even in their first year, infants acquire language, visual and social knowledge at a rate that surpasses the best supercomputers. But how, exactly, do our brains learn? In How We Learn, leading neuroscientist Stanislas Dehaene delves into the psychological, neuronal, synaptic and molecular mechanisms of learning. Drawing on case studies of children who learned despite huge difficulty and trauma, he explains why youth is such a sensitive period, during which brain plasticity is maximal, but also assures us that our abilities continue into adulthood. We can all enhance our learning and memory at any age and 'learn to learn' by taking maximal advantage of the four pillars of the brain's learning algorithm: attention, active engagement, error feedback and consolidation. The human brain is an extraordinary machine. Its ability to process information and adapt to circumstances by reprogramming itself is unparalleled, and it remains the best source of inspiration for recent developments in artificial intelligence. How We Learn finds the boundary of computer science, neurobiology, cognitive psychology and education to explain how learning really works and how to make the best use of the brain's learning algorithms - and even improve them - in our schools and universities as well as in everyday life.

WINNER OF THE 2014 BRAIN PRIZE From the acclaimed author of Reading in the Brain and How We Learn, a breathtaking look at the new science that can track consciousness deep in the brain How does our brain generate a conscious thought? And why does so much of our knowledge remain unconscious? Thanks to clever psychological and brain-imaging experiments, scientists are closer to cracking this mystery than ever before. In this lively book, Stanislas Dehaene describes the pioneering work his lab and the labs of other cognitive neuroscientists worldwide have accomplished in defining, testing, and explaining the brain events behind a conscious state. We can now pin down the neurons that fire when a person reports becoming aware of a piece of information and understand the crucial role unconscious computations play in how we make decisions. The emerging theory enables a test of consciousness in animals, babies, and those with severe brain injuries. A joyous exploration of the mind and its thrilling complexities, Consciousness and the Brain will excite anyone interested in cutting-edge science and technology and the vast philosophical, personal, and ethical implications of finally quantifying consciousness.

Fifteen of the foremost scientists in this field presented testable theoretical models of consciousness and discussed how our understanding of the role that consciousness plays in our cognitive processes is being refined with some surprising results.

Humanity's greatest feat is our incredible ability to learn. Even in their first year, infants acquire language, visual and social knowledge at a rate that surpasses the best supercomputers. But how, exactly, do our brains learn? In How We Learn, leading neuroscientist Stanislas Dehaene delves into the psychological, neuronal, synaptic and molecular mechanisms of learning. Drawing on case studies of children who learned despite huge difficulty and trauma, he explains why youth is such a sensitive period, during which brain plasticity is maximal, but also assures us that our abilities continue into adulthood. We can all enhance our learning and memory at any age and 'learn to learn' by taking maximal advantage of the four pillars of the brain's learning algorithm: attention, active engagement, error feedback and consolidation. The human brain is an extraordinary machine. Its ability to process information and adapt to circumstances by reprogramming itself is unparalleled, and it remains the best source of inspiration for recent developments in artificial intelligence. How We Learn finds the boundary of computer science, neurobiology, cognitive psychology and education to explain how learning really works and how to make the best use of the brain's learning algorithms - and even improve them - in our schools and universities as well as in everyday life.

"Brings together the cognitive, the cultural, and the neurological in an elegant, compelling narrative. A revelatory work."--Oliver Sacks, M.D. The act of reading is so easily taken for granted that we forget what an astounding feat it is. How can a few black marks on white paper evoke an entire universe of meanings? It's even more amazing when we consider that we read using a primate brain that evolved to serve an entirely different purpose. In this riveting investigation, Stanislas Dehaene, author of How We Learn, explores every aspect of this human invention, from its origins to its neural underpinnings. A world authority on the subject, Dehaene reveals the hidden logic of spelling, describes pioneering research on hiw we process languages, and takes us into a new appreciation of the brain and its wondrous capacity to adapt.

Featuring stunning brain scan imagery, this coffee table book combines visual art with insightful essays by a renowned cognitive neuroscientist. It explores the intricacies of the human brain, offering a unique blend of science and aesthetics that invites readers to reflect on cognitive processes and the mysteries of the mind.

Odkrywcze spojrzenie na badania nad fenomenalnymi zdolnościami mózgu do nauki a także nad potencjałem imitujących je programów komputerowych. Ludzki mózg jest rewelacyjnym urządzeniem. Posiada nadzwyczajną zdolność do przeprogramowywania się, która stanowi niewyczerpane źródło inspiracji dla dzisiejszych twórców sztucznej inteligencji. Jak się uczymy? Jakie wrodzone biologiczne fundamenty leżą u podstaw naszych zdolności do przyswajania informacji? Dlaczego w ogóle ewolucja wymyśliła proces nauki? Sięgając do najnowszych odkryć z zakresu informatyki, neurobiologii, psychologii poznawczej i pedagogiki, Stanislas Dehaene prezentuje, jak naprawdę przebiega proces nauki oraz w jaki sposób można maksymalnie wykorzystać a nawet wzmocnić algorytmy mózgu do uczenia się: w szkołach i na uniwersytetach oraz na co dzień, niezależnie od wieku. Autor uczy nas, jak się uczyć dzięki prostym rozwiązaniom dotyczącym zabawy, ciekawości, kontekstu społecznego, koncentracji a także snu. Nader treściwa książka dla pedagogów, rodziców i innych zainteresowanych tym, jak najefektywniej wspomagać dążenie do wiedzy Publishers Weekly

Wir sind von Zahlen umgeben, die unser Leben dominieren – sei es auf Kreditkarten, Münzen, Schecks oder in digitalen Tabellen. Sie sind das Fundament unserer Technologie und ermöglichen es uns, Raketen zu starten, Brücken zu bauen, Güter auszutauschen und Rechnungen zu begleichen. In gewisser Weise sind Zahlen kulturelle Erfindungen, die in ihrer Bedeutung nur mit der Landwirtschaft oder dem Rad vergleichbar sind. Ihre Wurzeln reichen tief: Bereits vor Tausenden von Jahren nutzten babylonische Wissenschaftler Zahlzeichen für präzise astronomische Berechnungen. Noch viel früher, in der Steinzeit, schufen Menschen die ersten geschriebenen Zahlenreihen, indem sie Knochen einkerbten oder Punkte auf Höhlenwände malten. Es wird sogar argumentiert, dass Tiere schon vor Millionen von Jahren einfache Rechnungen anstellten. Sind Zahlen also fast so alt wie das Leben selbst? Sind sie in der Struktur unseres Gehirns verankert? Besitzen wir einen Zahlensinn, eine Intuition, die uns hilft, Zahlen und Mathematik zu verstehen? Vor fünfzehn Jahren, während meiner Ausbildung zum Mathematiker, entdeckte ich meine Faszination für die abstrakten Objekte, mit denen ich arbeitete, insbesondere für die einfachsten von ihnen – die Zahlen.