Artificial Intelligence and Brain Research: Neural Networks, Deep Learning and the Future of Cognition

Preface
Contents
1 Introduction
	ChatGPT Passes the Turing Test
	The Next Affront
	Artificial Intelligence and Brain Research
	Too Blind to See the Elephant
	Brain-Computer Analogy
	Computationalism
	Functionalism
	Conclusion
	References
Part I Brain Research
2 The Most Complex System in the Universe
	The Brain in Numbers
	How Many Different Brains Can There Be?
	How Many Different Mental States are Possible?
	Conclusion
	References
3 Building Blocks of the Nervous System
	Neurons and Synapses
	Neuroplasticity
	Glia Cells
	Conclusion
	References
4 Organization of the Nervous System
	Modularity of the Nervous System
	Spinal Cord and Brainstem
	The Thalamus
	The Cortex
	The Hippocampus
	The Basal Ganglia
	The Cerebellum
	Conclusion
	References
5 Organization of the Cortex
	Division of the Cortex into Hemispheres and Lobes
	Columns: The Radial Organization of the Cortex
	Layers: The Vertical Organization of the Cortex
	Brodmann Areas
	Maps in the Head
	The Canonical Circuit of the Cortex
	Hierarchy of Cortical Areas
	Conclusion
	References
6 Methods of Brain Research
	Imaging Techniques: Watching the Brain Think
	CT
	PET
	MRI
	EEG and MEG
		Event-related Potentials and Fields
	Intracranial EEG
	Conclusion
	References
7 Memory
	Memory as an Information Processing System
	Sensory Memory
	Short-term Memory
	Working Memory
	Long-term Memory
	Conclusion
	References
8 Language
	How does Man Come to Language?
	Noam Chomsky’s Universal Grammar
	Cognitive Linguistics: Usage-Based Approaches
	Language in the Brain
	Conclusion
	References
9 Consciousness
	An age-old mystery
	Monism and Dualism
	What is it Like to be a Bat?
	Consciousness as a Useful Illusion?
	Limits of the Philosophy of Mind
	Neural Correlates of Consciousness
	Integrated Information Theory
	Is the Brain a Quantum Computer?
	Global Workspace Theory
	The feeling of what happens!—Damasio’s Model of Consciousness
		Emotions and Feelings
		Hierarchies of Consciousness
		Explanatory Power of Damasio’s Model
	Conclusion
	References
10 Free Will
	Is Free will Just a Pious Wish?
	The Libet Experiment
	Conclusion
	References
Part II Artificial Intelligence
11 What is Artificial Intelligence?
	History of AI
	Concept Clarification
	Machine Learning and Pattern Recognition
	Deep Learning
	Conclusion
	References
12 How Does Artificial Intelligence Learn?
	Artificial Neuron
	Artificial Neural Networks
	Supervised Learning
	Unsupervised Learning
	Self-supervised Learning
		Neurons for Cats and Jennifer Aniston
	Reinforcement Learning
	Conclusion
	References
13 Game-playing Artificial Intelligence
	Video Games
	Go and Chess
	AlphaGo Achieves the Breakthrough
	Conclusion
	References
14 Recurrent Neural Networks
	Recurrence in the Brain
	Recurrence in Artificial Neural Networks
	LSTMs
	Elman Networks
	Highly Recurrent Neural Networks
	Difficulty in Training Recurrent Networks
	Conclusion
	References
15 Creativity: Generative Artificial Intelligence
	What is Creativity?
	Deep Dreaming: When the Input is Trained, Not the Network
	Style Transfer
	Generative Adversarial Networks
	Diffusion Models
	Conclusion
	References
16 Talking AI: ChatGPT and Co.
	A Brief History of Natural Language Processing
	Word Vectors
	Transformer
	The GPT Series
	ChatGPT
	Speech Interfaces
	Conclusion
	References
17 What are AI Developers Researching Today?
	Learning to Learn
	Few-Shot Learning
	One-Shot Learning
	Zero-Shot Learning
	Transfer Learning
	Meta-Learning
	Hybrid Machine Learning
	Conclusion
	References
Part III Challenges
18 Challenges of AI
	It’s All About the Data
		Hallucinating Chatbots
	Dangerous Stickers and Other Attacks
	Alchemy, Reproducibility, and Black Boxes
	A Critical Appraisal
	Conclusion
	References
19 Challenges of Brain Research
	Three Major Challenges
	Can a Biologist Fix a Radio?
	The Story of the Neuroscientists and the Alien Computer
	Could a Neuroscientist Understand a Microprocessor?
	Conclusion: What Does It Mean to Understand a System?
	References
Part IV Integration
20 AI as a Tool in Brain Research
	Big Data in Brain Research
	Analysis and Visualization of Sleep Stages
	Narratives, Audiobooks, and Mind Reading
	Inception Loops
	Conclusion
	References
21 AI as a Model for the Brain
	Cognitive Computational Neuroscience
	Visual Processing
	Spatial Navigation and Language Processing
	Conclusion
	References
22 Understanding AI Better with Brain Research
	Neuroscience 2.0
	Lesions
	Visualization
		Network Visualization
		Feature Visualization
	Conclusion
	References
23 The Brain as a Template for AI
	Neuroscience-Inspired AI
	Noise in Networks
	Random Connections and Architectures
	Conclusion
	References
24 Outlook
	Conscious Machines?
	The Turing Test
	The Chinese Room
	The Grounding Problem
	Conclusion: Do we even want conscious machines?
	AI Apocalypse
	Who is Training Whom Here?
	Outlook: Singularity, Uploads, Holodecks
	References
Glossary