Course:

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

Difficulty level: Intermediate

Duration: 20:12

Speaker: : Mike X. Cohen

Course:

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

Difficulty level: Intermediate

Duration: 12:52

Speaker: : Mike X. Cohen

Course:

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

Difficulty level: Intermediate

Duration: 13:39

Speaker: : Mike X. Cohen

Course:

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

Difficulty level: Intermediate

Duration: 17:54

Speaker: : Mike X. Cohen

Course:

This lesson introduces various methods in MATLAB useful for dealing with data generated by calcium imaging.

Difficulty level: Intermediate

Duration: 5:02

Speaker: : Mike X. Cohen

Course:

This tutorial demonstrates how to use MATLAB to generate and visualize animations of calcium fluctuations over time.

Difficulty level: Intermediate

Duration: 15:01

Speaker: : Mike X. Cohen

Course:

This tutorial instructs users how to use MATLAB to programmatically convert data from cells to a matrix.

Difficulty level: Intermediate

Duration: 5:15

Speaker: : Mike X. Cohen

Course:

In this tutorial, users will learn how to identify and remove background noise, or "blur", an important step in isolating cell bodies from image data.

Difficulty level: Intermediate

Duration: 17:08

Speaker: : Mike X. Cohen

Course:

This lesson teaches users how MATLAB can be used to apply image processing techniques to identify cell bodies based on contiguity.

Difficulty level: Intermediate

Duration: 11:23

Speaker: : Mike X. Cohen

Course:

This tutorial demonstrates how to extract the time course of calcium activity from each clusters of neuron somata, and store the data in a MATLAB matrix.

Difficulty level: Intermediate

Duration: 22:41

Speaker: : Mike X. Cohen

Course:

This lesson demonstrates how to use MATLAB to implement a multivariate dimension reduction method, PCA, on time series data.

Difficulty level: Intermediate

Duration: 17:19

Speaker: : Mike X. Cohen

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

Difficulty level: Intermediate

Duration: 1:19:17

Speaker: : Sonny Chen

This lesson continues from part one of the lecture *Ontologies, Databases, and Standards*, diving deeper into a description of ontologies and knowledg graphs.

Difficulty level: Intermediate

Duration: 50:18

Speaker: : Jeff Grethe

This lecture focuses on ontologies for clinical neurosciences.

Difficulty level: Intermediate

Duration: 21:54

Speaker: : Martin Hofmann-Apitius

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.

Difficulty level: Intermediate

Duration: 1:28:14

Speaker: : Andreea Diaconescu

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.

Difficulty level: Intermediate

Duration: 1:15:04

Speaker: : Daniel Hauke

Course:

This lesson describes the principles underlying functional magnetic resonance imaging (fMRI), diffusion-weighted imaging (DWI), tractography, and parcellation. These tools and concepts are explained in a broader context of neural connectivity and mental health.

Difficulty level: Intermediate

Duration: 1:47:22

Speaker: : Erin Dickie and John Griffiths

Course:

This tutorial introduces pipelines and methods to compute brain connectomes from fMRI data. With corresponding code and repositories, participants can follow along and learn how to programmatically preprocess, curate, and analyze functional and structural brain data to produce connectivity matrices.

Difficulty level: Intermediate

Duration: 1:39:04

Speaker: : Erin Dickie and John Griffiths

In this lesson, you will hear about some of the open issues in the field of neuroscience, as well as a discussion about whether neuroscience works, and how can we know?

Difficulty level: Intermediate

Duration: 6:54

Speaker: : Marcus Ghosh

This is a hands-on tutorial on PLINK, the open source whole genome association analysis toolset. The aims of this tutorial are to teach users how to perform basic quality control on genetic datasets, as well as to identify and understand GWAS summary statistics.

Difficulty level: Intermediate

Duration: 1:27:18

Speaker: : Dan Felsky

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- Clinical neuroscience (20)
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- (-) General neuroinformatics (1)
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