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In this third and final hands-on tutorial from the Research Workflows for Collaborative Neuroscience workshop, you will learn about workflow orchestration using open source tools like DataJoint and Flyte. 

Difficulty level: Intermediate
Duration: 22:36
Speaker: : Daniel Xenes

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 lesson contains practical exercises which accompanies the first few lessons of the Neuroscience for Machine Learners (Neuro4ML) course. 

Difficulty level: Intermediate
Duration: 5:58
Speaker: : Dan Goodman

This lesson introduces some practical exercises which accompany the Synapses and Networks portion of this Neuroscience for Machine Learners course. 

Difficulty level: Intermediate
Duration: 3:51
Speaker: : Dan Goodman

In this lesson, you will learn how to train spiking neural networks (SNNs) with a surrogate gradient method. 

Difficulty level: Intermediate
Duration: 11:23
Speaker: : Dan Goodman

This video provides a very quick introduction to some of the neuromorphic sensing devices, and how they offer unique, low-power applications.

Difficulty level: Intermediate
Duration: 2:37
Speaker: : Dan Goodman

In this tutorial, you will learn how to use TVB-NEST toolbox on your local computer.

Difficulty level: Beginner
Duration: 2:16

This tutorial provides instruction on how to perform multi-scale simulation of Alzheimer's disease on The Virtual Brain Simulation Platform.

Difficulty level: Beginner
Duration: 29:08

This tutorial provides instruction on how to simulate brain tumors 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.

Difficulty level: Intermediate
Duration: 10:01

The tutorial on modelling strokes in TVB includes a didactic video and jupyter notebooks (reproducing publication: Falcon et al. 2016 eNeuro).

Difficulty level: Intermediate
Duration: 7:43
Course:

The goal of computational modeling in behavioral and psychological science is using mathematical models to characterize behavioral (or neural) data. Over the past decade, this practice has revolutionized social psychological science (and neuroscience) by allowing researchers to formalize theories as constrained mathematical models and test specific hypotheses to explain unobservable aspects of complex social cognitive processes and behaviors. This course is composed of 4 modules in the format of Jupyter Notebooks. This course comprises lecture-based, discussion-based, and lab-based instruction. At least one-third of class sessions will be hands-on. We will discuss relevant book chapters and journal articles, and work with simulated and real data using the Python programming language (no prior programming experience necessary) as we survey some selected areas of research at the intersection of computational modeling and social behavior. These selected topics will span a broad set of social psychological abilities including (1) learning from and for others, (2) learning about others, and (3) social influence on decision-making and mental states. Rhoads, S. A. & Gan, L. (2022). Computational models of human social behavior and neuroscience - An open educational course and Jupyter Book to advance computational training.  ​​​Journal of Open Source Education5(47), 146. https://doi.org/10.21105/jose.00146

 

Difficulty level: Intermediate
Duration:
Speaker: :

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

In this workshop talk, you will receive a tour of the Code Ocean ScienceOps Platform, a centralized cloud workspace for all teams. 

Difficulty level: Beginner
Duration: 10:24
Speaker: : Frank Zappulla

This talk describes approaches to maintaining integrated workflows and data management schema, taking advantage of the many open source, collaborative platforms already existing.

Difficulty level: Beginner
Duration: 15:15
Speaker: : Erik C. Johnson

This lesson provides an introduction to the DataLad, a free and open source distributed data management system that keeps track of your data, creates structure, ensures reproducibility, supports collaboration, and integrates with widely used data infrastructure.

Difficulty level: Beginner
Duration: 22:56

This lesson introduces several open science tools like Docker and Apptainer which can be used to develop portable and reproducible software environments. 

Difficulty level: Beginner
Duration: 17:22
Speaker: : Joanes Grandjean

This lecture provides a detailed description of how to incorporate HED annotation into your neuroimaging data pipeline. 

Difficulty level: Beginner
Duration: 33:36
Speaker: : Dung Truong

This lecture describes how to build research workflows, including a demonstrate using DataJoint Elements to build data pipelines.

Difficulty level: Intermediate
Duration: 47:00
Speaker: : Dimitri Yatsenko

This video will teach you the basics of navigating the Open Science Framework and creating your first projects.

Difficulty level: Beginner
Duration: 2:11
Speaker: :

This webinar walks you through the basics of creating an OSF project, structuring it to fit your research needs, adding collaborators, and tying your favorite online tools into your project structure.

Difficulty level: Beginner
Duration: 55:02
Speaker: : Ian Sullivan