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Part 1 of 2 of a tutorial on statistical models for neural data

Difficulty level: Beginner
Duration: 1:45:48
Speaker: : Jonathan Pillow

Part 2 of 2 of a tutorial on statistical models for neural data.

Difficulty level: Beginner
Duration: 1:50:31
Speaker: : Jonathan Pillow

Introduction to simple spiking neuron models.

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

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

Introduction to the course Cellular Mechanisms of Brain Function.

Difficulty level: Beginner
Duration: 12:20
Speaker: : Carl Petersen

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

Introduction to modelling of chemical computation in the brain

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

Conference presentation on computationally demanding studies of synaptic plasticity on the molecular level

Difficulty level: Advanced
Duration: 15:44

Introduction to the role of models in theoretical neuroscience

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

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

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

Balanced E-I networks, stability and gain modulation

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

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

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

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

Difficulty level: Beginner
Duration: 1:39:32

Spiking neuron networks and linear response models.

Difficulty level: Beginner
Duration: 1:24:22

Bayesian neuron models and parameter estimation.

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

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

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

Constraints can help us understand how the brain works.

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

Approaching neural systems from an evolutionary perspective

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

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

A short reel on who we are, what we're doing and why we're doing it

Difficulty level: Beginner
Duration: 2:38
Speaker: :