Computational Neuroscience: Bridging Biology and AI
“A 4-week intensive roadmap to understand how biological neurons process information and how these principles relate to Artificial Neural Networks, focusing on modeling and simulation. This curriculum aims to build a foundational understanding of neuronal dynamics, network behavior, and information encoding.”
The Neuron as a Computational Unit
By the end of this module you will be able to describe the biophysical properties of neurons and implement basic models of neuronal excitability.
Topics
Synapses, Networks, and Learning Rules
By the end of this module you will be able to model synaptic transmission and plasticity, and simulate small neural networks exhibiting basic dynamic behaviors.
Encoding Information in Neural Activity
By the end of this module you will be able to analyze neural data to understand how sensory information is encoded and decode simple stimuli from population activity.
From Biological Neurons to Artificial Intelligence
By the end of this module you will be able to identify the parallels and differences between biological and artificial neural networks and explore advanced topics in computational neuroscience.
References
Week 1: The Neuron as a Computational Unit
Week 2: Synapses, Networks, and Learning Rules
Week 3: Encoding Information in Neural Activity
Week 4: From Biological Neurons to Artificial Intelligence
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