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Introduction to EEG in MATLAB
Course:
Module 2: EEG

In this module, you will work with human EEG data recorded during a steady-state visual evoked potential study (SSVEP, aka flicker). You will learn about spectral analysis, alpha activity, and topographical mapping. The MATLAB code introduces functions, sorting, and correlation analysis.

Difficulty level: Intermediate
Duration: 8:51
Speaker: : Mike X. Cohen
Electrode positions in 2D and 3D
Course:
Module 2: EEG

In this module, you will work with human EEG data recorded during a steady-state visual evoked potential study (SSVEP, aka flicker). You will learn about spectral analysis, alpha activity, and topographical mapping. The MATLAB code introduces functions, sorting, and correlation analysis.

Difficulty level: Intermediate
Duration: 12:16
Speaker: : Mike X. Cohen
Spectral analysis in one channel
Course:
Module 2: EEG

In this module, you will work with human EEG data recorded during a steady-state visual evoked potential study (SSVEP, aka flicker). You will learn about spectral analysis, alpha activity, and topographical mapping. The MATLAB code introduces functions, sorting, and correlation analysis.

Difficulty level: Intermediate
Duration: 13:39
Speaker: : Mike X. Cohen
Spectral power from all channels
Course:
Module 2: EEG

In this module, you will work with human EEG data recorded during a steady-state visual evoked potential study (SSVEP, aka flicker). You will learn about spectral analysis, alpha activity, and topographical mapping. The MATLAB code introduces functions, sorting, and correlation analysis.

Difficulty level: Intermediate
Duration: 12:34
Speaker: : Mike X. Cohen
Topographical maps of steady-state visual evoked potential study (SSVEP)
Course:
Module 2: EEG

In this module, you will work with human EEG data recorded during a steady-state visual evoked potential study (SSVEP, aka flicker). You will learn about spectral analysis, alpha activity, and topographical mapping. The MATLAB code introduces functions, sorting, and correlation analysis

Difficulty level: Intermediate
Duration: 9:10
Speaker: : Mike X. Cohen
Endogenous alpha
Course:
Module 2: EEG

 

In this module, you will work with human EEG data recorded during a steady-state visual evoked potential study (SSVEP, aka flicker). You will learn about spectral analysis, alpha activity, and topographical mapping. The MATLAB code introduces functions, sorting, and correlation analysis.

Difficulty level: Intermediate
Duration: 13:23
Speaker: : Mike X. Cohen
Correlate alpha with steady-state visual evoked potential (SSVEP)
Course:
Module 2: EEG

In this module, you will work with human EEG data recorded during a steady-state visual evoked potential study (SSVEP, aka flicker). You will learn about spectral analysis, alpha activity, and topographical mapping. The MATLAB code introduces functions, sorting, and correlation analysis.

Difficulty level: Intermediate
Duration: 12:36
Speaker: : Mike X. Cohen
European Academy of Neurology: Why data sharing in clinical neurosciences
Course:
The future of medical data sharing in clinical neurosciences

This lecture discusses the the importance and need for data sharing in clinical neuroscience.

Difficulty level: Intermediate
Duration: 25:22
Speaker: : Thomas Berger
The present and future model of MIP data privacy
Course:
The future of medical data sharing in clinical neurosciences

This lecture gives insights into the Medical Informatics Platform's current and future data privacy model.

Difficulty level: Intermediate
Duration: 17:29
Speaker: : Yannis Ioannidis
European Health Data Space: The future of data sharing in Europe
Course:
The future of medical data sharing in clinical neurosciences

This lecture gives an overview on the European Health Dataspace. 

Difficulty level: Intermediate
Duration: 26:33
Speaker: : Licino Kustra Mano
Single neuron models - I
Course:
Dynamical neural systems

Introduction to stability analysis of neural models

Difficulty level: Intermediate
Duration: 1:26:06
Speaker: : Bard Ermentrout
Single Neuron Models - II
Course:
Dynamical neural systems

Introduction to stability analysis of neural models

Difficulty level: Intermediate
Duration: 1:25:38
Speaker: : Bard Ermentrout
Neural oscillations, weak coupling and networks
Course:
Dynamical neural systems

Oscillations and bursting

Difficulty level: Intermediate
Duration: 1:24:30
Speaker: : Bard Ermentrout
Neural oscillations and networks II
Course:
Dynamical neural systems

Oscillations and bursting

Difficulty level: Intermediate
Duration: 1:31:57
Speaker: : Bard Ermentrout
Oscillatory networks and the Ott Antonsen theory
Course:
Dynamical neural systems

Weakly coupled oscillators

Difficulty level: Intermediate
Duration: 1:26:02
Speaker: : Bard Ermentrout
Oscillatory networks II
Course:
Dynamical neural systems

Continuation of coupled oscillators

Difficulty level: Intermediate
Duration: 1:24:44
Speaker: : Bard Ermentrout
Firing rate models - networks
Course:
Dynamical neural systems

Firing rate models.

Difficulty level: Intermediate
Duration: 1:26:42
Speaker: : Bard Ermentrout
Spatiotemporal dynamics, waves, pattern formation
Course:
Dynamical neural systems

Pattern generation in visual system hallucinations.

Difficulty level: Intermediate
Duration: 1:20:42
Speaker: : Bard Ermentrout
Single neuron models - I
Course:
Introduction to computational neuroscience

Introduction to stability analysis of neural models

Difficulty level: Intermediate
Duration: 1:26:06
Speaker: : Bard Ermentrout
Single Neuron Models - II
Course:
Introduction to computational neuroscience

Introduction to stability analysis of neural models

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

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