Artem Kirsanov Courses

Brain Criticality - Optimizing Neural Computations

1 rating

Explore how the brain optimizes information processing by operating near critical points, examining phase transitions, neuronal avalanches, and scale-free properties in neural networks.

• YouTube
• 37 minutes
• Self-Paced
• Free Video

Self-Study Computational Neuroscience - Coding, Textbooks, Math

1 rating

Comprehensive guide to starting computational neuroscience: programming languages, coding practice, textbooks, math resources, project ideas, and datasets for self-study and skill development.

• YouTube
• 21 minutes
• Self-Paced
• Free Video

Building Blocks of Memory in the Brain

Explore engrams, the fundamental units of memory in the brain. Learn about memory allocation, storage, and linking, as well as the role of immediate-early genes and neuronal excitability in memory formation.

• YouTube
• 28 minutes
• Self-Paced
• Free Video

The Most Important Algorithm in Machine Learning - Backpropagation Explained

Explore backpropagation's fundamentals, from curve fitting to gradient descent, chain rule, and computational graphs. Gain insights into this crucial machine learning algorithm's principles and applications.

• YouTube
• 40 minutes
• Self-Paced
• Free Video

The Physics of Associative Memory - Exploring Hopfield Networks

Explore Hopfield networks, a foundational model of associative memory in neuroscience and machine learning. Learn about network architecture, inference, learning, and limitations.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

How I Make Science Animations

Neuroscience PhD student shares creative process, software tools, and techniques for making science animations, including mathematical visualizations, 3D neuron activity, and brain models.

• YouTube
• 44 minutes
• Self-Paced
• Free Video

Understanding the Free Energy Principle in Brain Function and World Models

Explore the Free Energy Principle in neuroscience and understand how the brain builds predictive models of the world, from generative models to optical illusions and sensory processing.

• YouTube
• 20 minutes
• Self-Paced
• Free Video

The Hodgkin-Huxley Model - Understanding Neural Electrical Signals

Dive into the Nobel Prize-winning Hodgkin-Huxley model to understand how neurons generate electrical signals, exploring membrane voltage, ion channels, and the biophysical principles of neural computation.

• YouTube
• 23 minutes
• Self-Paced
• Free Video

Elegant Geometry of Neural Computations - Understanding Phase Portraits and Bifurcations

Explore the geometric principles behind neural computations, from phase portraits to bifurcations, understanding how neurons achieve excitability, bistability, and resonant oscillations through mathematical modeling.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

The Key Equation Behind Probability - Entropy, Cross-Entropy, and KL Divergence

Explore probability theory fundamentals, from surprise to entropy, cross-entropy, and KL divergence. Learn key concepts applicable to neuroscience and machine learning.

• YouTube
• 26 minutes
• Self-Paced
• Free Video

Boltzmann Machines - The Grandfather of Generative Models

Explore Boltzmann Machines, early generative models learning data probability distributions using stochastic rules and latent representations. Understand their goals, distribution, update rules, and evolution to Restricted Boltzmann Machines.

• YouTube
• 33 minutes
• Self-Paced
• Free Video

Differential Equations: The Language of Change

Explore dynamical systems and differential equations through intuitive examples. Learn key concepts like state variables, phase portraits, and limit cycles to understand how systems change over time.

• YouTube
• 23 minutes
• Self-Paced
• Free Video

How Your Brain Chooses What to Remember - Understanding Memory Selection and Sharp-Wave Ripples

Discover how your brain selects and consolidates memories through hippocampal sharp-wave ripples, exploring neural mechanisms and experimental findings in memory formation and retention.

• YouTube
• 17 minutes
• Self-Paced
• Free Video

Predictive Coding: A Biologically Plausible Alternative to Backpropagation

Explore Predictive Coding, a biologically plausible alternative to backpropagation for neural networks, derived from first principles and explained through energy formalism, update rules, and neural connectivity.

• YouTube
• 27 minutes
• Self-Paced
• Free Video

Why Different Neuron Parts Learn Differently - Compartmentalized Plasticity in Pyramidal Neurons

Explore how pyramidal neurons use distinct plasticity rules in different compartments, revealing compartmentalized learning mechanisms in apical vs basal dendrites.

• YouTube
• 24 minutes
• Self-Paced
• Free Video