Skip to main content

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

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: 12:52
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: 13:39
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: 17:54
Speaker: : Mike X. Cohen

You will learn about working with calcium imaging data, including image processing to remove background "blur," identifying cells based on thresholded spatial contiguity, time series filtering, and principal components analysis (PCA). The MATLAB code shows data animations, capabilities of the image processing toolbox, and PCA.

Difficulty level: Intermediate
Duration: 5:02
Speaker: : Mike X. Cohen

You will learn about working with calcium imaging data, including image processing to remove background "blur," identifying cells based on thresholded spatial contiguity, time series filtering, and principal components analysis (PCA). The MATLAB code shows data animations, capabilities of the image processing toolbox, and PCA.

Difficulty level: Intermediate
Duration: 15:01
Speaker: : Mike X. Cohen

You will learn about working with calcium imaging data, including image processing to remove background "blur," identifying cells based on thresholded spatial contiguity, time series filtering, and principal components analysis (PCA). The MATLAB code shows data animations, capabilities of the image processing toolbox, and PCA.

Difficulty level: Intermediate
Duration: 5:15
Speaker: : Mike X. Cohen

You will learn about working with calcium imaging data, including image processing to remove background "blur," identifying cells based on thresholded spatial contiguity, time series filtering, and principal components analysis (PCA). The MATLAB code shows data animations, capabilities of the image processing toolbox, and PCA.

Difficulty level: Intermediate
Duration: 17:08
Speaker: : Mike X. Cohen

You will learn about working with calcium imaging data, including image processing to remove background "blur," identifying cells based on thresholded spatial contiguity, time series filtering, and principal components analysis (PCA). The MATLAB code shows data animations, capabilities of the image processing toolbox, and PCA.

Difficulty level: Intermediate
Duration: 11:23
Speaker: : Mike X. Cohen

You will learn about working with calcium imaging data, including image processing to remove background "blur," identifying cells based on thresholded spatial contiguity, time series filtering, and principal components analysis (PCA). The MATLAB code shows data animations, capabilities of the image processing toolbox, and PCA.

Difficulty level: Intermediate
Duration: 22:41
Speaker: : Mike X. Cohen

You will learn about working with calcium imaging data, including image processing to remove background "blur," identifying cells based on thresholded spatial contiguity, time series filtering, and principal components analysis (PCA). The MATLAB code shows data animations, capabilities of the image processing toolbox, and PCA.

Difficulty level: Intermediate
Duration: 17:19
Speaker: : Mike X. Cohen

This lecture covers NeuronUnit, a library that builds upon SciUnit and integrates with several existing neuroinformatics resources to support validating single-neuron models using data gathered by neurophysiologists.

Difficulty level: Intermediate
Duration: 17:21
Speaker: : Richard Gerkin

An introduction to the NeuroElectro project, which aims to organize information on cellular neurophysiology. Speaker: Shreejoy Tripathy

Difficulty level: Intermediate
Duration: 17:41

Simultaneously recorded neurons in non-human primates coordinate their spiking activity in a sequential manner that mirrors the dominant wave propagation directions of the local field potentials.

Difficulty level: Intermediate
Duration: 26:54

This talk covers statistical analysis of spike train data, the modeling approach GLM, and the problem of assessing neural synchrony.

Difficulty level: Intermediate
Duration: 25:17
Speaker: : Rob Kass

This talk covers statistical methods for characterizing neural population responses and extracting structure from high-dimensional neural data.

Difficulty level: Intermediate
Duration: 26:15
Speaker: : Jonathan Pillow

This presentation covers research to understand the activity of single neurons and populations of neurons in the visual system.

Difficulty level: Intermediate
Duration: 28:23
Speaker: : Matteo Carandini