Cracking the Code - Neuronal Networks in the Brain

Overview

Delve into the world of neuronal networks with our event, "Cracking the Code - Neuronal Networks in the Brain." This fascinating exploration provides an in-depth look at the cutting-edge techniques used to study biological neural networks. Learn about their efficient encoding solutions and how these innovations are influencing AI algorithms, particularly in areas of learning and navigation.

During this insightful event, you will discover the remarkable similarities between artificial and live brain behavior.

The knowledge gained here not only advances your understanding of AI but also showcases the incredible complexities and efficiencies found within biological systems.

Hosted on YouTube, this event is a must-attend for those interested in artificial intelligence courses and conference talks that bridge the gap between technology and neuroscience.

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

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Subjects

Conference Talks