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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 and tutorial focuses on measuring human functional brain networks. The lecture and tutorial were part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Intermediate
Duration: 50:44
Speaker: : Caterina Gratton

This lecture was part of the 2018 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Intermediate
Duration: 1:25:05
Speaker: : Satrajit Ghosh

A short reel on who we are, what we're doing and why we're doing it

Difficulty level: Beginner
Duration: 2:38
Speaker: :

In this webinar, educators currently implementing collaborative annotation in their classrooms discuss their experiences with collaborative annotation and using Hythothes.is and Canvas App.

Difficulty level: Beginner
Duration: 53:14
Speaker: : Jeremy Dean

Tutorial that provides an overview of how to use the feature of Hypothes.is.

Difficulty level: Beginner
Duration: 09:30
Speaker: :

A brief overview of the Hypothesis functionality from an end user's perspective.

Difficulty level: Beginner
Duration: 5:36
Speaker: : Heather Staines