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This lecture presents an overview of functional brain parcellations, as well as a set of tutorials on bootstrap agregation of stable clusters (BASC) for fMRI brain parcellation.

Difficulty level: Advanced
Duration: 50:28
Speaker: : Pierre Bellec
Course:

Neuronify is an educational tool meant to create intuition for how neurons and neural networks behave. You can use it to combine neurons with different connections, just like the ones we have in our brain, and explore how changes on single cells lead to behavioral changes in important networks. Neuronify is based on an integrate-and-fire model of neurons. This is one of the simplest models of neurons that exist. It focuses on the spike timing of a neuron and ignores the details of the action potential dynamics. These neurons are modeled as simple RC circuits. When the membrane potential is above a certain threshold, a spike is generated and the voltage is reset to its resting potential. This spike then signals other neurons through its synapses.

Neuronify aims to provide a low entry point to simulation-based neuroscience.

Difficulty level: Beginner
Duration: 01:25
Speaker: : Neuronify

This lecture covers the linking neuronal activity to behavior using AI-based online detection. 

Difficulty level: Beginner
Duration: 30:39

This lesson provides a hands-on, Jupyter-notebook-based tutorial to apply machine learning in Python to brain-imaging data.

Difficulty level: Beginner
Duration: 02:13:53
Speaker: : Jake Vogel

This lesson from freeCodeCamp introduces Scikit-learn, the most widely used machine learning Python library.

Difficulty level: Beginner
Duration: 02:09:22
Speaker: :

Overview of Day 2 of this course.

Difficulty level: Beginner
Duration: 00:03:28
Speaker: : Tristan Shuman

This talk compares various sensors and resolutions for in vivo neural recordings.

Difficulty level: Beginner
Duration: 00:24:03

This hands-on tutorial explains how to run your own Minion session in the MetaCell cloud using jupityr notebooks.

Difficulty level: Beginner
Duration: 01:28:03

In this hands-on analysis tutorial, users will mimic a kernel crash and learn the steps to restore inputs in such a case.

Difficulty level: Beginner
Duration: 00:20:34
Speaker: : Phil Dong

This lesson will go through how to extract cells from video that has been cleaned of background noise and motion.

Difficulty level: Beginner
Duration: 01:49:40
Speaker: : Phil Dong

This final hands-on analysis tutorial walks users through the last visualization steps in the cellular data.

Difficulty level: Beginner
Duration: 00:27:23
Speaker: : Phil Dong

This lecture covers infrared LED oblique illumination for studying neuronal circuits in in vitro block-preparations of the spinal cord and brain stem.

Difficulty level: Beginner
Duration: 25:16
Speaker: : Péter Szucs

This lecture covers the application of diffusion MRI for clinical and preclinical studies.

Difficulty level: Beginner
Duration: 33:10
Speaker: : Silvia de Santis

This tutorial walks participants through the application of dynamic causal modelling (DCM) to fMRI data using MATLAB. Participants are also shown various forms of DCM, how to generate and specify different models, and how to fit them to simulated neural and BOLD data.

 

This lesson corresponds to slides 158-187 of the PDF below. 

Difficulty level: Advanced
Duration: 1:22:10

In this hands-on session, you will learn how to explore and work with DataLad datasets, containers, and structures using Jupyter notebooks. 

Difficulty level: Beginner
Duration: 58:05

This video shows how to use the brainlife.io interface to edit the participants' info file. This file is the ParticipantInfo.json file of the Brain Imaging Data Structure (BIDS).

Difficulty level: Beginner
Duration: 0:34
Speaker: :

This quick video presents some of the various visualizers available on brainlife.io

Difficulty level: Beginner
Duration: 1:11
Speaker: :

This video demonstrates each required step for preprocessing T1w anatomical data in brainlife.io.

Difficulty level: Beginner
Duration: 3:28
Speaker: :
Course:

BioImage Suite is an integrated image analysis software suite developed at Yale University. BioImage Suite has been extensively used at different labs at Yale since about 2001.

Difficulty level: Beginner
Duration: 01:47
Speaker: : BioImage Suite
Course:

Fibr is an app for quality control of diffusion MRI images from the Healthy Brain Network, a landmark mental health study that is collecting MRI images and other assessment data from 10,000 New York City area children. The purpose of the app is to train a computer algorithm to analyze the Healthy Brain Network dataset. By playing fibr, you are helping to teach the computer which images have sufficiently good quality and which images do not. 

Difficulty level: Beginner
Duration: 02:26
Speaker: : Ariel Rokem