This tutorial demonstrates to users the conventional preprocessing steps when working with BOLD signal datasets from fMRI. 

In this tutorial, users will learn how to create a trial-averaged BOLD response and store it in a matrix in MATLAB. 

This tutorial teaches users how to create animations of BOLD responses over time, to allow researchers and clinicians to visualize time-course activity patterns.

This tutorial demonstrates how to use MATLAB to create event-related BOLD time courses from fMRI datasets. 

In this tutorial, users learn how to compute and visualize a t-test on experimental condition differences.

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.

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.

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.

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.

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.

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.

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.

This is a tutorial introducing participants to the basics of RNA-sequencing data and how to analyze its features using Seurat. 

This lesson breaks down the principles of Bayesian inference and how it relates to cognitive processes and functions like learning and perception. It is then explained how cognitive models can be built using Bayesian statistics in order to investigate how our brains interface with their environment. 

This lesson corresponds to slides 1-64 in the PDF below. 

This is a tutorial on designing a Bayesian inference model to map belief trajectories, with emphasis on gaining familiarity with Hierarchical Gaussian Filters (HGFs).

This lesson corresponds to slides 65-90 of the PDF below. 

Tutorial on how to simulate brain tumor brains with TVB (reproducing publication: Marinazzo et al. 2020 Neuroimage). This tutorial comprises a didactic video, jupyter notebooks, and full data set for the construction of virtual brains from patients and health controls. Authors: Hannelore Aerts, Michael Schirner, Ben Jeurissen, DIrk Van Roost, Eric Achten, Petra Ritter, Daniele Marinazzo

Tutorial on collaborating with Git and GitHub. This tutorial was 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.