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.
Author(s): Huijue Jia
Publisher: Jenny Stanford Publishing
Year: 2023
Language: English
Pages: 249
City: Singapore
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
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
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
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
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
9.3: Path Diagrams and Counterfactuals in View of Navigation
9.4: Summary
Index
