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Computational Cognitive Neuroscience

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Computational Cognitive Neuroscience

The content is organized into chapters, but also massively hyperlinked, and the content can go very "deep" while also enabling a very quick and relatively high-level of information that captures the key points, suitable for college undergraduates or even high school curricula. The main page for a given chapter provides a complete high-level pass through the material that stands alone, and is highly accessible. Everything else should be a subtopic page under the main page.

NeuroscienceMedicine
Author
O'Reilly, Munakata, Hazy & Frank
Publisher
University of Colorado Boulder & Brown University
Source
LibreTexts
License
CC BY-SA
Language
EN
Category
Basic Sciences
Read online Download PDF (open licence)
Contents· 83 sections
  1. 01: Introduction
  2. 1.01: Introduction
  3. 1.02: Some Phenomena We'll Explore
  4. 1.03: The Computational Approach
  5. 1.04: Emergent Phenomena
  6. 1.05: Why Should We Care about the Brain
  7. 1.06: How to Read this Book
  8. 02: Neuron
  9. 2.01: Introduction
  10. 2.02: Basic Biology of a Neuron as Detector
  11. 2.03: Dynamics of Integration- Excitation vs. Inhibition and Leak
  12. 2.04: Computing Activation Output
  13. 2.05: Mathematical Formulations
  14. 2.06: Exploration of the Individual Neuron
  15. 2.07: Back to the Detector
  16. 2.08: SubTopics
  17. 2.09: Explorations
  18. 03: Networks
  19. 3.01: Introduction
  20. 3.02: Biology of the Neocortex
  21. 3.03: Categorization and Distributed Representations
  22. 3.04: Bidirectional Excitatory Dynamics and Attractors
  23. 3.05: Inhibitory Competition and Activity Regulation
  24. 3.06: SubTopics and Explorations
  25. 04: Learning Mechanisms
  26. 4.01: Introduction
  27. 4.02: Biology of Synaptic Plasticity
  28. 4.03: The eXtended Contrastive Attractor Learning (XCAL) Model
  29. 4.04: When Exactly is there an Outcome that should Drive Learning
  30. 4.05: The Leabra Framework
  31. 4.06: SubTopics and Explorations
  32. 4.07: References
  33. 05: Brain Areas
  34. 5.01: Introduction
  35. 5.02: Navigating the Functional Anatomy of the Brain
  36. 5.03: Preception and Attention- What vs. Where
  37. 5.04: Motor Control- Parietal and Motor Cortex Interacting with Basal Ganglia and Cerebellum
  38. 5.05: Learning and Memory- Temporal Cortex and the Hippocampus
  39. 5.06: Language- All Together Now
  40. 5.07: Executive Function- Prefrontal Cortex and Basal Ganglia
  41. 06: Preception and Attention
  42. 6.01: Introduction
  43. 6.02: Biology of Preception
  44. 6.03: Oriented Edge Detectors in Primary Visual Cortex
  45. 6.04: Invariant Object Recognition in the What Pathway
  46. 6.05: Spatial Attention and Neglect in the Where How Pathway
  47. 6.06: Explorations
  48. 07: Motor Control and Reinforcement Learning
  49. 7.01: Introduction
  50. 7.02: Basal Ganglia Action Selection and Reinforcement Learning
  51. 7.03: Dopamine and Temporal Difference Reinforcement Learning
  52. 7.04: Cerebellum and Error-Driven Learning
  53. 7.05: SubTopics and Explorations
  54. 08: Learning and Memory
  55. 8.01: Introduction
  56. 8.02: Episodic Memory
  57. 8.03: Familiarity and Recognition Memory
  58. 8.04: Priming- Weight and Activation-Based
  59. 8.05: SubTopics and Explorations
  60. 09: Language
  61. 9.01: Introduction
  62. 9.02: Biology of Language
  63. 9.03: Reading and Dyslexia in the Triangle Model
  64. 9.04: Spelling to Sound Mappings in Word Reading
  65. 9.05: Latent Semantics in Word Co-Occurrence
  66. 9.06: Syntax and Semantics in a Sentence Gestalt
  67. 9.07: Next Steps in Language Modeling of Sentences and Beyond
  68. 9.08: SubTopics and Explorations
  69. 10: Executive Function
  70. 10.01: Introduction
  71. 10.02: Biology of PFC BG and Dopamine Supporting Robust Active Maintenance
  72. 10.03: The PBWM Computational Model
  73. 10.04: Top-down Cognitive Control from Sustained PFC Firing- The Stroop Model
  74. 10.05: Development of PFC Active Memory Strength and the A-not-B Task
  75. 10.06: Dynamic Updating of PFC Active Memory- The SIR Model
  76. 10.07: More Complex Dynamic Updating of PFC Active Memory- The N-Back Task
  77. 10.08: Hierarchical Organization of PFC- Subtasks Goals Cognitive Sequencing
  78. 10.09: Affective Influences over Executive Function- Roles of the OFC and ACC
  79. 10.10: Other Executive Functions
  80. 10.11: Alternative Frameworks and Modeling Approaches
  81. 10.12: Summary of Key Points
  82. 10.13: SubTopics and Explorations
  83. 10.14: External Resources