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This tutorial demonstrates how to work with neuronal data using MATLAB, including actional potentials and spike counts, orientation tuing curves in visual cortex, and spatial maps of firing rates.

Difficulty level: Intermediate
Duration: 5:17
Speaker: : Mike X. Cohen

This lesson instructs users on how to import electrophysiological neural data into MATLAB, as well as how to convert spikes to a data matrix.

Difficulty level: Intermediate
Duration: 11:37
Speaker: : Mike X. Cohen

In this lesson, users will learn how to appropriately sort and bin neural spikes, allowing for the generation of a common and powerful visualization tool in neuroscience, the histogram. 

Difficulty level: Intermediate
Duration: 5:31
Speaker: : Mike X. Cohen

Followers of this lesson will learn how to compute, visualize and quantify the tuning curves of individual neurons. 

Difficulty level: Intermediate
Duration: 13:48
Speaker: : Mike X. Cohen

This lesson demonstrates how to programmatically generate a spatial map of neuronal spike counts using MATLAB.

Difficulty level: Intermediate
Duration: 12:16
Speaker: : Mike X. Cohen

In this lesson, users are shown how to create a spatial map of neuronal orientation tuning. 

Difficulty level: Intermediate
Duration: 13:11
Speaker: : Mike X. Cohen

This lesson provides an introduction to biologically detailed computational modelling of neural dynamics, including neuron membrane potential simulation and F-I curves. 

Difficulty level: Intermediate
Duration: 8:21
Speaker: : Mike X. Cohen

In this lesson, users learn how to use MATLAB to build an adaptive exponential integrate and fire (AdEx) neuron model. 

Difficulty level: Intermediate
Duration: 22:01
Speaker: : Mike X. Cohen

In this lesson, users learn about the practical differences between MATLAB scripts and functions, as well as how to embed their neuronal simulation into a callable function.  

Difficulty level: Intermediate
Duration: 11:20
Speaker: : Mike X. Cohen

This lesson teaches users how to generate a frequency-current (F-I) curve, which describes the function that relates the net synaptic current (I) flowing into a neuron to its firing rate (F). 

Difficulty level: Intermediate
Duration: 20:39
Speaker: : Mike X. Cohen

This lecture presents the Medical Informatics Platform's data federation in epilepsy.

Difficulty level: Intermediate
Duration: 27:09
Speaker: : Philippe Ryvlin

This lesson breaks down the principles of Bayesian inference and how it relates to cognitive processes and functions like learning and perception. It is then explained how cognitive models can be built using Bayesian statistics in order to investigate how our brains interface with their environment. 

This lesson corresponds to slides 1-64 in the PDF below. 

Difficulty level: Intermediate
Duration: 1:28:14

This is a tutorial on designing a Bayesian inference model to map belief trajectories, with emphasis on gaining familiarity with Hierarchical Gaussian Filters (HGFs).

 

This lesson corresponds to slides 65-90 of the PDF below. 

Difficulty level: Intermediate
Duration: 1:15:04
Speaker: : Daniel Hauke

This lecture aims to help researchers, students, and health care professionals understand the place for neuroinformatics in the patient journey using the exemplar of an epilepsy patient. 

Difficulty level: Intermediate
Duration: 1:32:53

This lesson provides an overview of the current status in the field of neuroscientific ontologies, presenting examples of data organization and standards, particularly from neuroimaging and electrophysiology. 

Difficulty level: Intermediate
Duration: 33:41

This lesson continues from part one of the lecture Ontologies, Databases, and Standards, diving deeper into a description of ontologies and knowledg graphs. 

Difficulty level: Intermediate
Duration: 50:18
Speaker: : Jeff Grethe

This lesson provides an introduction to modeling single neurons, as well as stability analysis of neural models.

Difficulty level: Intermediate
Duration: 1:26:06
Speaker: : Bard Ermentrout

This lesson continues a thorough description of the concepts, theories, and methods involved in the modeling of single neurons. 

Difficulty level: Intermediate
Duration: 1:25:38
Speaker: : Bard Ermentrout

In this lesson you will learn about fundamental neural phenomena such as oscillations and bursting, and the effects these have on cortical networks. 

Difficulty level: Intermediate
Duration: 1:24:30
Speaker: : Bard Ermentrout

This lesson continues discussing properties of neural oscillations and networks. 

Difficulty level: Intermediate
Duration: 1:31:57
Speaker: : Bard Ermentrout