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020 ▼a 9781003410980 ▼q (electronic bk.)
020 ▼a 1003410987 ▼q (electronic bk.)
020 ▼a 1000908852 ▼q (electronic bk. : EPUB)
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035 ▼a 3619669 ▼b (N$T)
035 ▼a (OCoLC)1376457171 ▼z (OCoLC)1380744743 ▼z (OCoLC)1380744916
037 ▼a 9781003410980 ▼b Taylor & Francis
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1001 ▼a Jia, Huijue, ▼e author.
24510 ▼a NEUROSCIENCE FOR ARTIFICIAL INTELLIGENCE.
264 1 ▼a [Place of publication not identified] : ▼b JENNY STANFORD PUB, ▼c 2023.
300 ▼a 1 online resource : ▼b illustrations.
336 ▼a text ▼b txt ▼2 rdacontent
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5050 ▼a Cover -- Half Title -- Title Page -- Copyright Page -- Table of Contents -- Preface -- Acknowledgments -- Chapter 1: Evolving under Constraints -- 1.1: An Evolutionary Continuum -- 1.2: Overall Structure of the Brain -- 1.3: Number of Neurons and Their Connections -- 1.4: Fuel for the Brain -- 1.5: Summary -- Chapter 2: The Senses as Basic Input -- 2.1: Olfaction -- 2.1.1: Prioritizing with Separation and Tagging? -- 2.1.2: The Spatiotemporal Resolution of Olfaction -- 2.2: Taste -- 2.3: Hearing -- 2.4: Visual Signal Processing in Each Cell -- 2.5: Sensing Mechanical Forces -- 2.6: Summary
5058 ▼a Chapter 3: Changing Priorities with Age -- 3.1: Growing and Learning with the Cerebellum -- 3.2: A Cortical Network that Ripens with Age -- 3.3: Summary -- Chapter 4: Memory in Cells -- 4.1: Engrams: Single-Cell Basis of Memory -- 4.2: To Engage More Cells for a Stronger Memory? -- 4.3: Competition for Allocation into a Memory Engram -- 4.4: Memory Consolidation in View of Hashing -- 4.5: Combining Old and New -- 4.6: Summary -- Chapter 5: Memory in Dendritic Spines -- 5.1: Spiny Neurons -- 5.2: Local Spine Dynamics -- 5.2.1: Memory Decay Down to Individual Spines -- 5.2.2: New and Leaky
5058 ▼a 5.2.3: Thin and Learning Fast -- 5.3: Memory Replays at Synapses -- 5.4: Sharp-Wave Ripples-Weights of Dendritic Spines in Action -- 5.5: Gated Storage of New Details -- 5.6: Summary -- Chapter 6: Sleeping and Dreaming -- 6.1: Non-Rapid Eye Movement Sleep-Flushing Waste Out of the Brain and Stock-Up -- 6.2: The Alternating and Progressing Phases of Sleep -- 6.3: Interneurons-Global or Local Patterning with Brain-Wide Oscillations -- 6.4: Evolutionarily Ancient Circuits Tapping into Our Dreams? -- 6.5: Rapid Eye Movement Sleep -- 6.6: Daydreaming and the Refreshing Effect of Switching Tasks
5058 ▼a 6.7: Summary -- Chapter 7: Mastering Space and Time -- 7.1: Place Cells and Grid Cells -- 7.2: Stellate Neurons and Pyramidal Neurons for Objects and Grids? -- 7.3: Time or Rhythm? -- 7.4: Sensing Speed and Acceleration -- 7.5: The Vestibular System for Sensing Self-Motion -- 7.6: Vector Information from Other Cells Around the Hippocampus -- 7.7: Goal-Directed Vector Navigation -- 7.8: A More Versatile Generative Adversarial Network in the Brain? -- 7.9: Social Navigation -- 7.10: Summary -- Chapter 8: Arithmetics, Talking and Reading -- 8.1: A Distributed Network That Works Together
5058 ▼a 8.2: Object Tracking for Low Numbers -- 8.3: Torus and the Number of Functional Domains on the Hippocampus? -- 8.4: Analog Representation of Numbers in Humans and Animals -- 8.5: Abstract Representation of Numbers and Arithmetic Operations -- 8.6: Multi-Module Coordination during Singing -- 8.7: Talking or Reading -- 8.7.1: Hippocampus-Dependent Procedural Memory for Speaking -- 8.7.2: Reading from Grids to Details? -- 8.8: Summary -- Chapter 9: Causality and Cognitive Exploration -- 9.1: To Explore or Not -- 9.2: Expected or Unexpected
520 ▼a The ongoing boom of applications for artificial intelligence (AI) is based on algorithms that were inspired by neuroscience discoveries in the 1960s. This is a timely book to introduce the new discoveries and ideas in neuroscience, for the next wave of more powerful AI. AI researchers are all interested in the human brain, which is more capable and energy-efficient, but do not have good reading materials from the rather separate subfields of neuroscience, all with plenty of jargons. Based on hundreds of publications from top journals, the book fills in the gap between existing computational hardware/algorithms and emerging knowledge from neuroscience.
5450 ▼a Huijue Jia received her BS at Fudan University, China, and PhD at Case Western Reserve University, USA, with Dr. Eckhard Jankowsky. After being a postdoc with Dr. Yi Zhang (now at Boston Children's Hospital and Harvard Medical School),she hasserved as scientific editor of Nature Communications and has contributed to reviews, commentaries, and other book projects, especially a recent book on the human microbiome. Dr. Jia is currently a principal investigator at Fudan University and Greater Bay Area Institute of Precision Medicine, China. With many publications on bioinformatic analyses of omics data, including metagenomic studies on neuropsychiatric diseases, she is uniquely positioned to bridge the myriad of neuroscience publications and the booming field of artificial intelligence, for the next wave of more powerful algorithms.
5880 ▼a Print version record.
590 ▼a Added to collection customer.56279.3
650 0 ▼a Artificial intelligence.
650 0 ▼a Neurosciences.
650 6 ▼a Intelligence artificielle.
650 6 ▼a Neurosciences.
650 7 ▼a artificial intelligence. ▼2 aat
650 7 ▼a PSYCHOLOGY / Neuropsychology ▼2 bisacsh
650 7 ▼a MATHEMATICS / Probability & Statistics / General ▼2 bisacsh
650 7 ▼a Artificial intelligence ▼2 fast
650 7 ▼a Neurosciences ▼2 fast
77608 ▼i Print version: ▼a JIA, HUIJUE. ▼t NEUROSCIENCE FOR ARTIFICIAL INTELLIGENCE. ▼d [Place of publication not identified] : JENNY STANFORD PUB, 2023 ▼z 9814968781 ▼w (OCoLC)1369313565
85640 ▼3 EBSCOhost ▼u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=3619669
938 ▼a EBSCOhost ▼b EBSC ▼n 3619669
990 ▼a 관리자
994 ▼a 92 ▼b N$T