Nguồn ngoài

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.

Neuroscience Medicine

Tác giả: O'Reilly, Munakata, Hazy & Frank
Nhà xuất bản: University of Colorado Boulder & Brown University
Nguồn: LibreTexts
Giấy phép: CC BY-SA
Ngôn ngữ: EN
Danh mục: Khoa học cơ bản

Đọc trực tuyến Tải PDF (nguồn mở)

Mục lục· 83 mục

01: Introduction
1.01: Introduction
1.02: Some Phenomena We'll Explore
1.03: The Computational Approach
1.04: Emergent Phenomena
1.05: Why Should We Care about the Brain
1.06: How to Read this Book
02: Neuron
2.01: Introduction
2.02: Basic Biology of a Neuron as Detector
2.03: Dynamics of Integration- Excitation vs. Inhibition and Leak
2.04: Computing Activation Output
2.05: Mathematical Formulations
2.06: Exploration of the Individual Neuron
2.07: Back to the Detector
2.08: SubTopics
2.09: Explorations
03: Networks
3.01: Introduction
3.02: Biology of the Neocortex
3.03: Categorization and Distributed Representations
3.04: Bidirectional Excitatory Dynamics and Attractors
3.05: Inhibitory Competition and Activity Regulation
3.06: SubTopics and Explorations
04: Learning Mechanisms
4.01: Introduction
4.02: Biology of Synaptic Plasticity
4.03: The eXtended Contrastive Attractor Learning (XCAL) Model
4.04: When Exactly is there an Outcome that should Drive Learning
4.05: The Leabra Framework
4.06: SubTopics and Explorations
4.07: References
05: Brain Areas
5.01: Introduction
5.02: Navigating the Functional Anatomy of the Brain
5.03: Preception and Attention- What vs. Where
5.04: Motor Control- Parietal and Motor Cortex Interacting with Basal Ganglia and Cerebellum
5.05: Learning and Memory- Temporal Cortex and the Hippocampus
5.06: Language- All Together Now
5.07: Executive Function- Prefrontal Cortex and Basal Ganglia
06: Preception and Attention
6.01: Introduction
6.02: Biology of Preception
6.03: Oriented Edge Detectors in Primary Visual Cortex
6.04: Invariant Object Recognition in the What Pathway
6.05: Spatial Attention and Neglect in the Where How Pathway
6.06: Explorations
07: Motor Control and Reinforcement Learning
7.01: Introduction
7.02: Basal Ganglia Action Selection and Reinforcement Learning
7.03: Dopamine and Temporal Difference Reinforcement Learning
7.04: Cerebellum and Error-Driven Learning
7.05: SubTopics and Explorations
08: Learning and Memory
8.01: Introduction
8.02: Episodic Memory
8.03: Familiarity and Recognition Memory
8.04: Priming- Weight and Activation-Based
8.05: SubTopics and Explorations
09: Language
9.01: Introduction
9.02: Biology of Language
9.03: Reading and Dyslexia in the Triangle Model
9.04: Spelling to Sound Mappings in Word Reading
9.05: Latent Semantics in Word Co-Occurrence
9.06: Syntax and Semantics in a Sentence Gestalt
9.07: Next Steps in Language Modeling of Sentences and Beyond
9.08: SubTopics and Explorations
10: Executive Function
10.01: Introduction
10.02: Biology of PFC BG and Dopamine Supporting Robust Active Maintenance
10.03: The PBWM Computational Model
10.04: Top-down Cognitive Control from Sustained PFC Firing- The Stroop Model
10.05: Development of PFC Active Memory Strength and the A-not-B Task
10.06: Dynamic Updating of PFC Active Memory- The SIR Model
10.07: More Complex Dynamic Updating of PFC Active Memory- The N-Back Task
10.08: Hierarchical Organization of PFC- Subtasks Goals Cognitive Sequencing
10.09: Affective Influences over Executive Function- Roles of the OFC and ACC
10.10: Other Executive Functions
10.11: Alternative Frameworks and Modeling Approaches
10.12: Summary of Key Points
10.13: SubTopics and Explorations
10.14: External Resources