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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

This lightning talk describes an automated pipline for positron emission tomography (PET) data. 

Difficulty level: Intermediate
Duration: 7:27

This lecture goes into detailed description of how to process workflows in the virtual research environment (VRE), including approaches for standardization, metadata, containerization, and constructing and maintaining scientific pipelines. 

Difficulty level: Intermediate
Duration: 1:03:55
Speaker: : Patrik Bey

This lesson is the first of three hands-on tutorials as part of the workshop Research Workflows for Collaborative Neuroscience. This tutorial goes over how to visualize data with Scanpy, a scalable toolkit for analyzing single-cell gene expression. 

Difficulty level: Intermediate
Duration: 25:26

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 lecture, you will learn about current methods, approaches, and challenges to studying human neuroanatomy, particularly through the lense of neuroimaging data such as fMRI and diffusion tensor imaging (DTI). 

Difficulty level: Intermediate
Duration: 1:35:14
Speaker: : Matt Glasser

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 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 lesson delves into the human nervous system and the immense cellular, connectomic, and functional sophistication therein. 

Difficulty level: Intermediate
Duration: 8:41
Speaker: : Marcus Ghosh

This lecture highlights the importance of correct annotation and assignment of location, and updated atlas resources to avoid errors in navigation and data interpretation.

Difficulty level: Intermediate
Duration: 22:04
Speaker: : Trygve Leergard

We are at the exciting technological stage where it has become feasible to represent the anatomy of an entire human brain at the cellular level. This lecture discusses how neuroanatomy in the 21st Century has become an effort towards the virtualization and standardization of brain tissue.

Difficulty level: Intermediate
Duration: 25:27
Speaker: : Jacopo Annese

This lecture covers essential features of digital brain models for neuroinformatics, particularly NeuroMaps. 

Difficulty level: Intermediate
Duration: 22:26
Speaker: : Douglas Bowden

This presentation covers the neuroinformatics tools and techniques used and their relationship to neuroanatomy for the Allen Institute's atlases of the mouse, developing mouse, and mouse connectional atlas.

Difficulty level: Intermediate
Duration: 23:41
Speaker: : Mike Hawrylycz

This tutorial covers the fundamentals of collaborating with Git and GitHub.

Difficulty level: Intermediate
Duration: 2:15:50
Speaker: : Elizabeth DuPre

This lesson provides an overview of Jupyter notebooks, Jupyter lab, and Binder, as well as their applications within the field of neuroimaging, particularly when it comes to the writing phase of your research. 

Difficulty level: Intermediate
Duration: 50:28
Speaker: : Elizabeth DuPre

This lecture gives an overview of how to prepare and preprocess neuroimaging (EEG/MEG) data for use in TVB.  

Difficulty level: Intermediate
Duration: 1:40:52
Speaker: : Paul Triebkorn

This talk presents state-of-the-art methods for ensuring data privacy with a particular focus on medical data sharing across multiple organizations.

Difficulty level: Intermediate
Duration: 22:49

The Medical Informatics Platform (MIP) is a platform providing federated analytics for diagnosis and research in clinical neuroscience research. The federated analytics is possible thanks to a distributed engine that executes computations and transfers information between the members of the federation (hospital nodes). In this talk the speaker will describe the process of designing and implementing new analytical tools, i.e. statistical and machine learning algorithms.  Mr. Sakellariou will further describe the environment in which these federated algorithms run, the challenges and the available tools, the principles that guide its design and the followed general methodology for each new algorithm. One of the most important challenges which are faced is to design these tools in a way that does not compromise the privacy of the clinical data involved. The speaker will show how to address the main questions when designing such algorithms: how to decompose and distribute the computations and what kind of information to exchange between nodes, in order to comply with the privacy constraint mentioned above. Finally, also the subject of validating these federated algorithms will be briefly touched.

Difficulty level: Intermediate
Duration: 20:26
Speaker: : Jason Skellariou

This lecture discusses risk-based anonymization approaches for medical research.

Difficulty level: Intermediate
Duration: 15:43
Speaker: : Fabian Prasser