book_contents.md

Programming for and Computational Approaches to the Brain and Cognitive Sciences

Part 0: About This Book

0.0) Guide to the Book

Part 1: Python Crash Course

0. Installing and Using Python
1. Basic Python Commands
2. Loops, Sequences, and IO
3. Functions
4. Dictionaries and Sets
5. Modules (especially Numpy)
6. Classes and OOP
7. Advanced Topics
8. Good Programming Techniques
9. Testing, Debugging, and Exceptions
10. GitHub and Version Control

Part 2: Applications to Brain and Cognitive Science

11. Graphical User Interfaces
12. Games and Simulations
13. Programming Experiments
14. Data Science
15. Data Visualization
16. Statistical Inference
17. Machine Learning
18. Natural Language Processing
19. Computational Modeling
20. Web Programming

Part 3: Computational Paradigms in Brain and Cognitive Science

21. Symbolic Computation
22. Information Processing
23. Connectionism and Neural Networks
24. Bayesian Inference
25. Dynamical Systems
26. Evolution and Genetics
27. Computational Neuroscience
28. Network Science
29. Mathematical Models
30. Learning Theories and Behaviorism

Part 4: Applications in Brain and Cognitive Science

31. Object and Scene Perception
32. Speech Perception
33. Attention
34. Episodic Memory
35. Semantic Memory
36. Concepts
37. Action and Embodied Cognition
38. Language Models
39. Reasoning
40. Decision-making
41. Intelligence