Cracking the Code - Neuronal Networks in the Brain

Overview

Explore cutting-edge techniques for studying biological neural networks, their efficient encoding solutions, and how they inspire AI algorithms for learning and navigation. Discover similarities between artificial and live brain behavior.

Syllabus

• Introduction to Biological Neural Networks
Overview of Neurons and Synapses
Brain Structure and Function
Techniques for Studying the Brain
• Encoding in Biological Neural Networks
Principles of Neural Encoding
Information Encoding and Efficiency
Neuronal Coding Strategies
• Biological Inspiration for AI
Comparison of Biological and Artificial Neural Networks
Concepts of Learning and Adaptation
Inspiration and Implementation in AI
• Advanced Topics in Neuronal Networks
Neural Plasticity and Learning
Emergent Properties and Complex Behavior
Pattern Recognition and Prediction
• Navigation and Spatial Learning in the Brain
Mechanisms of Spatial Representation
Path Integration and Cognitive Maps
Neural Pathways for Navigational Accuracy
• Translating Biological Networks to AI
Case Studies: From Biological Insights to AI Models
Algorithm Design Inspired by the Brain
Challenges and Future Directions
• Similarities and Differences: Live versus Artificial Networks
Comparative Analysis of Network Architecture
Behavioral Observations in Humans and Machines
Limits of Current AI Inspired by Neural Biology
• Conclusion
Recap of Key Concepts
Emerging Trends and Research Directions
Integration of Biological Insights into AI Development

Subjects

Conference Talks