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Difficulty level

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: 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: 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

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: 11:20
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: 20:39
Speaker: : Mike X. Cohen

This module covers fMRI data, including creating and interpreting flat maps, exploring variability and average responses, and visual eccentricity. You will learn about processing BOLD signals, trial-averaging, and t-tests. The MATLAB code introduces data animations, multicolor visualizations, and linear indexing.

Difficulty level: Intermediate
Duration: 7:15
Speaker: : Mike X. Cohen

This module covers fMRI data, including creating and interpreting flatmaps, exploring variability and average responses, and visual eccentricity. You will learn about processing BOLD signals, trial-averaging, and t-tests. The MATLAB code introduces data animations, multicolor visualizations, and linear indexing.

Difficulty level: Intermediate
Duration: 12:15
Speaker: : Mike X. Cohen

This module covers fMRI data, including creating and interpreting flatmaps, exploring variability and average responses, and visual eccentricity. You will learn about processing BOLD signals, trial-averaging, and t-tests. The MATLAB code introduces data animations, multicolor visualizations, and linear indexing.

Difficulty level: Intermediate
Duration: 12:05
Speaker: : Mike X. Cohen

This module covers fMRI data, including creating and interpreting flatmaps, exploring variability and average responses, and visual eccentricity. You will learn about processing BOLD signals, trial-averaging, and t-tests. The MATLAB code introduces data animations, multicolor visualizations, and linear indexing.

Difficulty level: Intermediate
Duration: 20:12
Speaker: : Mike X. Cohen