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Learn how to build and share extensions in NWB

Difficulty level: Advanced
Duration: 20:29
Speaker: : Ryan Ly

Learn how to build custom APIs for extension

Difficulty level: Advanced
Duration: 25:40
Speaker: : Andrew Tritt

Learn how to handle writing very large data in PyNWB

Difficulty level: Advanced
Duration: 26:50
Speaker: : Andrew Tritt

Learn how to handle writing very large data in MatNWB

Difficulty level: Advanced
Duration: 16:18
Speaker: : Ben Dichter

The goal of this module is to work with action potential data taken from a publicly available database. You will learn about spike counts, orientation tuning, and spatial maps. The MATLAB code introduces data types, for-loops and vectorizations, indexing, and data visualization.

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

The goal of this module is to work with action potential data taken from a publicly available database. You will learn about spike counts, orientation tuning, and spatial maps. The MATLAB code introduces data types, for-loops and vectorizations, indexing, and data visualization.

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

The goal of this module is to work with action potential data taken from a publicly available database. You will learn about spike counts, orientation tuning, and spatial maps. The MATLAB code introduces data types, for-loops and vectorizations, indexing, and data visualization.

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

The goal of this module is to work with action potential data taken from a publicly available database. You will learn about spike counts, orientation tuning, and spatial maps. The MATLAB code introduces data types, for-loops and vectorizations, indexing, and data visualization.

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

The goal of this module is to work with action potential data taken from a publicly available database. You will learn about spike counts, orientation tuning, and spatial maps. The MATLAB code introduces data types, for-loops and vectorizations, indexing, and data visualization.

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

The goal of this module is to work with action potential data taken from a publicly available database. You will learn about spike counts, orientation tuning, and spatial maps. The MATLAB code introduces data types, for-loops and vectorizations, indexing, and data visualization.

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

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

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

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

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

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

 

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

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

This module introduces computational neuroscience by simulating neurons according to the AdEx model. You will learn about generative modeling, dynamical systems, and FI curves. The MATLAB code introduces Live Scripts and functions.

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

This module introduces computational neuroscience by simulating neurons according to the AdEx model. You will learn about generative modeling, dynamical systems, and FI curves. The MATLAB code introduces Live Scripts and functions.

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

This module introduces computational neuroscience by simulating neurons according to the AdEx model. You will learn about generative modeling, dynamical systems, and FI curves. The MATLAB code introduces Live Scripts and functions.

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