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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

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 gives an in-depth introduction of ethics in the field of artificial intelligence, particularly in the context of its impact on humans and public interest. As the healthcare sector becomes increasingly affected by the implementation of ever stronger AI algorithms, this lecture covers key interests which must be protected going forward, including privacy, consent, human autonomy, inclusiveness, and equity. 

Difficulty level: Beginner
Duration: 1:22:06
Speaker: : Daniel Buchman

This lesson describes a definitional framework for fairness and health equity in the age of the algorithm. While acknowledging the impressive capability of machine learning to positively affect health equity, this talk outlines potential (and actual) pitfalls which come with such powerful tools, ultimately making the case for collaborative, interdisciplinary, and transparent science as a way to operationalize fairness in health equity. 

Difficulty level: Beginner
Duration: 1:06:35
Speaker: : Laura Sikstrom

This lesson provides an overview of self-supervision as it relates to neural data tasks and the Mine Your Own vieW (MYOW) approach.

Difficulty level: Beginner
Duration: 25:50
Speaker: : Eva Dyer

This lesson provides a conceptual overview of the rudiments of machine learning, including its bases in traditional statistics and the types of questions it might be applied to. The lesson was presented in the context of the BrainHack School 2020.

Difficulty level: Beginner
Duration: 01:22:18
Speaker: : Estefany Suárez

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 presents advanced machine learning algorithms for neuroimaging, while addressing some real-world considerations related to data size and type.

Difficulty level: Beginner
Duration: 01:17:14
Speaker: : Gael Varoquaux

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