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This lesson introduces users to MATLAB live scripts; interactive documents that combine MATLAB code with formatted text, equations, and images in a single environment. 

Difficulty level: Intermediate
Duration: 13:11
Speaker: : Mike X. Cohen

In this lesson, users learn how to use MATLAB to build an adaptive exponential integrate and fire (AdEx) neuron model. 

Difficulty level: Intermediate
Duration: 22:01
Speaker: : Mike X. Cohen

In this lesson, users learn about the practical differences between MATLAB scripts and functions, as well as how to embed their neuronal simulation into a callable function.  

Difficulty level: Intermediate
Duration: 11:20
Speaker: : Mike X. Cohen

This lesson teaches users how to generate a frequency-current (F-I) curve, which describes the function that relates the net synaptic current (I) flowing into a neuron to its firing rate (F). 

Difficulty level: Intermediate
Duration: 20:39
Speaker: : Mike X. Cohen

This lecture introduces neuroscience concepts and methods such as fMRI, visual respones in BOLD data, and the eccentricity of visual receptive fields. 

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

This tutorial walks users through the creation and visualization of activation flat maps from fMRI datasets. 

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

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

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

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

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

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

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

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

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

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

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

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

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

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 briefly goes over the outline of the Neuroscience for Machine Learners course. 

Difficulty level: Intermediate
Duration: 3:05
Speaker: : Dan Goodman