Beginner Python for Computational Modeling of Neural Networks
Learn to build and simulate neural networks using Python, bridging the gap between neuroscience and programming for computational modeling.
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Python Fundamentals for Neural Modeling
Unit 1: Python Basics for Scientific Computing
Intro to Python & SciComp
Data Types: The Building Blocks
Lists: Data Structure Basics
Dictionaries: Key-Value Pairs
Tuples and Sets
Unit 2: Control Flow and Functions
Conditional Statements
Looping with For Loops
Looping with While Loops
Defining Functions
Lambda Functions
Unit 3: NumPy for Numerical Computing
NumPy Arrays: The Basics
Array Operations
Linear Algebra with NumPy
Random Number Generation
Array Reshaping and Combining
Unit 4: Data Visualization with Matplotlib
Plotting Basics
Scatter Plots
Histograms
Subplots
Saving Figures
Simulating Neuron Models with Python
Unit 1: Introduction to Neuron Modeling
What is a Neuron Model?
The Integrate-and-Fire
NumPy for Neurons
Coding I&F in Python
I&F Model Parameters
Unit 2: Numerical Methods for Neuron Dynamics
Why Numerical Methods?
Euler's Method Explained
Euler for I&F Neurons
Step Size Matters!
Beyond Euler: Other Methods
Unit 3: Visualizing Neuron Activity
Matplotlib Basics
Plotting Membrane Potential
Spike Raster Plots
Histograms of Firing Rates
Plotting I-V Curves
Introduction to Neural Networks with TensorFlow/PyTorch
Unit 1: Neural Network Fundamentals
What are Neural Networks?
Perceptrons Explained
Activation Functions
Layers and Architectures
Forward Propagation
Unit 2: Introduction to TensorFlow/PyTorch
TensorFlow vs. PyTorch
Tensor Basics
Automatic Differentiation
Building a Simple Model
Loss Functions
Unit 3: Training and Evaluation
Optimizers
The Training Loop
Evaluating Performance
Overfitting and Underfitting
Putting it All Together
Optimization and Analysis of Neural Networks
Unit 1: Gradient Descent Optimization
Intro to Optimization
Understanding Gradients
Gradient Descent: The Math
GD in Python: A Simple Case
GD: Challenges & Solutions
Unit 2: Analyzing Spiking Neural Networks
Intro to Spiking Networks
Simulating SNNs in Python
Feature Extraction: Firing Rate
Feature Extraction: ISI
Spike Train Correlations
Unit 3: Version Control with Git
Intro to Version Control
Git: Installation & Setup
Basic Git Workflow
Branching and Merging
Collaborating with GitHub
