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Lesson title:

Approaching neural systems from an evolutionary perspective

Difficulty level: Beginner
Duration: 1:29:38
Speaker: : Gilles Laurent
Lesson title:

This lecture describes non-spiking simple neuron models used in artificial neural networks and machine learning.

Difficulty level: Beginner
Duration: 8:23
Speaker: : Geoffrey Hinton
Lesson title:

This lecture covers an Introduction to neuron anatomy and signaling, and different types of models, including the Hodgkin-Huxley model.

Difficulty level: Beginner
Duration: 1:23:01
Speaker: : Gaute Einevoll
Lesson title:

This lecture describes non-spiking simple neuron models used in artificial neural networks and machine learning.

Difficulty level: Beginner
Duration: 8:23
Speaker: : Geoffrey Hinton
Lesson title:

Introduction to simple spiking neuron models.

Difficulty level: Beginner
Duration: 48 Slides
Speaker: : Zubin Bhuyan
Lesson title:

Forms of plasticity on many levels - short-term, long-term, metaplasticity, structural plasticity. With examples related to modelling of biochemical networks. 

[NB: The sound uptake is a bit noisy the first few minutes, but gets better from about 5 mins in]

 

Difficulty level: Beginner
Duration: 1:11:29
Speaker: : Upi Bhalla
Lesson title:

Introduction to modelling of chemical computation in the brain

Difficulty level: Beginner
Duration: 1:00:11
Speaker: : Upi Bhalla
Lesson title:

Introduction to the role of models in theoretical neuroscience

Difficulty level: Beginner
Duration: 19:26
Speaker: : Jakob Macke
Lesson title:

Different types of models, model complexity, and how to choose an appropriate model.

Difficulty level: Beginner
Duration: 39:09
Speaker: : Astrid Prinz
Lesson title:

Balanced E-I networks, stability and gain modulation

Difficulty level: Beginner
Duration: 1:22:11
Speaker: : Kenneth Miller
Lesson title:

Methods for dimensionality reduction of data, with focus on factor analysis.

Difficulty level: Beginner
Duration: 1:16:47
Speaker: : Byron Yu
Lesson title:

Methods for dimensionality reduction of data, with focus on factor analysis.

Difficulty level: Beginner
Duration: 1:39:32
Lesson title:

Spiking neuron networks and linear response models.

Difficulty level: Beginner
Duration: 1:24:22
Lesson title:

Bayesian neuron models and parameter estimation.

Difficulty level: Beginner
Duration: 1:12:38
Speaker: : Jakob Macke
Lesson title:

Bayesian memory and learning, how to go from observations to latent variables.

Difficulty level: Beginner
Duration: 1:33:34
Speaker: : Máté Lengyel
Lesson title:

Constraints can help us understand how the brain works.

Difficulty level: Beginner
Duration: 1:34:42
Speaker: : Simon Laughlin
Lesson title:

Approaching neural systems from an evolutionary perspective

Difficulty level: Beginner
Duration: 1:29:38
Speaker: : Gilles Laurent
Lesson title:

The probability of a hypothesis, given data.

Difficulty level: Beginner
Duration: 7:57
Speaker: : Barton Poulson
Lesson title:

Why math is useful in data science.

Difficulty level: Beginner
Duration: 1:35
Speaker: : Barton Poulson
Lesson title:

Why statistics are useful for data science.

Difficulty level: Beginner
Duration: 4:01
Speaker: : Barton Poulson