EPFLx: Computational Neuroscience: Neuronal Dynamics of Cognition

This course explains the mathematical and computational models that are used in the field of theoretical neuroscience to analyze the collective dynamics of thousands of interacting neurons.

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Course Insight

Designed for advanced/expert practitioners. Designed for experienced practitioners. We recommend having a solid grasp of Biology & Life Sciences fundamentals before starting this specialization.

Advanced LevelCertification IncludedSelf-Paced Learning

SKILLS TO
MASTER

Biology & Life Sciences Basics
Fundamental principles and concepts
Practical ApplicationTrending
Real-world project implementation
Best Practices
Industry standard workflows and guidelines
Problem Solving
Core Concepts
Implementation
Workflow Integration
Optimization
Careers:Relevant for professionals pursuing roles within Biology & Life Sciences.

Quick Facts

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What You’ll Learn

What happens in your brain when you make a decision? And what happens if you recall a memory from your last vacation? Why is our perception of simple objects sometimes strangely distorted? How can millions of neurons in the brain work together without a central control unit?

This course explains the mathematical and computational models that are used in the field of theoretical neuroscience to answer the above questions. The core of the answer to cognition may lie in the collective dynamics of thousands of interacting neurons - and these dynamics are mathematically analyzed in this course using methods such as mean-field theory and non-linear differential equations.

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Outcomes

  • Analyze connected networks in the mean-field limit.
  • Formalize biological facts into mathematical models.
  • Understand a simple mathematical model of memory formation in the brain.
  • Understand a simple mathematical model of decision processes.
  • Understand cortical field models of perception.
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EPFLx: Computational Neuroscience: Neuronal Dynamics of Cognition
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