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Essentials of cognitive neuroscience /
~
Postle, Bradley R.
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Essentials of cognitive neuroscience /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Essentials of cognitive neuroscience // Bradley R. Postle.
作者:
Postle, Bradley R.
出版者:
Hoboken, NJ :Wiley, : c2020.,
面頁冊數:
xx, 512, 9, 11 p. :ill. (some col.) ;26 cm.
標題:
Cognitive neuroscience - Textbooks. -
ISBN:
9781119674153
Essentials of cognitive neuroscience /
Postle, Bradley R.
Essentials of cognitive neuroscience /
Bradley R. Postle. - 2nd ed. - Hoboken, NJ :Wiley,c2020. - xx, 512, 9, 11 p. :ill. (some col.) ;26 cm.
Includes bibliographical references and index.
"Revisions for the second edition include adding a new chapter on methodology in the first section of the book per recommendation from reviewers and "common" practice. This will make the book seem more inviting to a wider swath of the undergraduate market. The current editions "Methodology Box" content from throughout the text will be retained and repurposed as instructor resource material. This is the case with much of the other boxed material as well; Thought; Research Spotlight; Tips, Real- World Applications. It will either be incorporated into the main text or lifted and repurposed as Instructor Materials. In some cases this will allow us to replace a high-cost image with a bibliographic reference to that image. Building on the repurposed box content, instructor resources will be overhauled and include a more robust test bank and how-to instructions for incorporating the principles of "test-enhanced learning" into online quizzes that provide real-time feedback for students (implementable with canvas, moodle, and other Web-based course management systems). Other revision work will focus on updated to critical areas to bring the book current with the science, including: Scientific ideas: predictive coding; dynamical systems framing of motor control and its generalization to cognitive control; reinforcement learning; machine learning with an emphasis on deep learning; divisive normalization as a canonical neural computation and its relevance for understanding attention, decision making, and neurological disease (including Autism Spectrum Disorder, epilepsy, etc.). Methodological advances: graph theoretical analyses, resting state functional connectivity, there's also considerable overlap with computational approaches informed by dynamical systems and reinforcement learning perspectives"--
ISBN: 9781119674153US120.95
LCCN: 2020001686Subjects--Topical Terms:
609203
Cognitive neuroscience
--Textbooks.
LC Class. No.: QP360 / .P675 2020
Dewey Class. No.: 612.8/233
Essentials of cognitive neuroscience /
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"Revisions for the second edition include adding a new chapter on methodology in the first section of the book per recommendation from reviewers and "common" practice. This will make the book seem more inviting to a wider swath of the undergraduate market. The current editions "Methodology Box" content from throughout the text will be retained and repurposed as instructor resource material. This is the case with much of the other boxed material as well; Thought; Research Spotlight; Tips, Real- World Applications. It will either be incorporated into the main text or lifted and repurposed as Instructor Materials. In some cases this will allow us to replace a high-cost image with a bibliographic reference to that image. Building on the repurposed box content, instructor resources will be overhauled and include a more robust test bank and how-to instructions for incorporating the principles of "test-enhanced learning" into online quizzes that provide real-time feedback for students (implementable with canvas, moodle, and other Web-based course management systems). Other revision work will focus on updated to critical areas to bring the book current with the science, including: Scientific ideas: predictive coding; dynamical systems framing of motor control and its generalization to cognitive control; reinforcement learning; machine learning with an emphasis on deep learning; divisive normalization as a canonical neural computation and its relevance for understanding attention, decision making, and neurological disease (including Autism Spectrum Disorder, epilepsy, etc.). Methodological advances: graph theoretical analyses, resting state functional connectivity, there's also considerable overlap with computational approaches informed by dynamical systems and reinforcement learning perspectives"--
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