Computational Neuroscience

Computational Neuroscience: Bridging Biology and AI

4 weeks
10 Learners
eulerfold
Apr 6

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.

Model how neurons process information. This is the bridge between biological brains and Artificial Neural Networks.

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W1

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.

2 videos50m
3 readings
3 topics
1 task
Learn

Topics

1.1
Introduction to Computational Neuroscience
40 minutes
1.2
Neuronal Biophysics
10 minutes
1.3
Basic Neuron Models
W2

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.

3 videos76m
3 readings
3 topics
1 task
Learn
W3

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.

2 videos27m
3 readings
3 topics
1 task
Learn
W4

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.

1 video19m
3 readings
3 topics
1 task
Learn
01

Learn

Watch curated videos and read study resources

02

Practice

Practice what you learned

03

Build Projects

Build projects using your new gained knowledge

04

Submit & Verify

Submit your project and get verified by our system

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