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Digital Health for Mental Health

Krembil Centre for Neuroinformatics

As technological improvements continue to facilitate innovations in the mental health space, researchers and clinicians are faced with novel opportunities and challenges regarding study design, diagnoses, treatments, and follow-up care. This course includes a lecture outlining these new developments, as well as a workshop which introduces users to Synapse, an open-source platform for collaborative data analysis. 

 

Foundations of Machine Learning in Python

NeurotechEU

Course designed for advanced learners interested in understanding the foundations of Machine Learning in Python.

General: The course consists of 15 lectures (ca. 1-2 hours each) and 15 exercise sheets (for ca. 6 hours of programming each).

Institution: High-Performance Computing and Analytics Lab, University of Bonn

 

INCF Assembly 2022 - Day 3 Sessions

INCF

Sessions from the INCF Neuroinformatics Assembly 2022 Day 3. 

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FAIR neuroscience and EBRAINS tools for data sharing, analysis, and simulation

INCF

This workshop provides an opportunity to explore the advanced tools and techniques for data sharing, analysis, visualization, and simulation.

 
INCF TrainingSpace

Introduction to EEGLAB

Swartz Center for Computational Neuroscience

EEGLAB is an interactive MATLAB toolbox for processing continuous and event-related EEG, MEG, and other electrophysiological data. In this course, you will learn about features incorporated into EEGLAB, including independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data. EEGLAB runs under Linux, Unix, Windows, and Mac OS X.

 

INCF Assembly 2022 - Training Day 2

INCF

This course contains sessions from the second day of INCF's Neuroinformatics Assembly 2022.

 

Versioning & Containerization

This course outlines how versioning code, data, and analysis software is crucially important to rigorous and open neuroscience workflows that maximize reproducibility and minimize errors.Version control systems, code-capable notebooks, and virtualization containers such as Git, Jupyter, and Docker, respectively, have become essential tools in data science.

 

Simulating Brain Microcircuit Activity and Signals in Mental Health

Krembil Centre for Neuroinformatics

This course offers lectures on the origin and functional significance of certain electrophysiological signals in the brain, as well as a hands-on tutorial on how to simulate, statistically evaluate, and visualize such signals. Participants will learn the simulation of signals at different spatial scales, including single-cell (neuronal spiking) and global (EEG), and how these may serve as biomarkers in the evaluation of mental health data.

 

INCF Assembly 2022 - Day 2 Sessions

INCF

Sessions from the INCF Neuroinformatics Assembly 2022 day 2. 

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Bayesian Models of Learning and Integration of Neuroimaging Data

Krembil Centre for Neuroinformatics

Bayesian inference (using prior knowledge to generate more accurate predictions about future events or outcomes) has become increasingly applied to the fields of neuroscience and neuroinformatics. In this course, participants are taught how Bayesian statistics may be used to build cognitive models of processes like learning or perception. This course also offers theoretical and practical instruction on dynamic causal modeling as applied to fMRI and EEG data.

 

INCF Assembly 2022 - Day 1 Sessions

INCF

Sessions from the INCF Neuroinformatics Assembly 2022 day 1. 

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Population-Based Data Resources & Integrative Research Methods

Krembil Centre for Neuroinformatics

As research methods and experimental technologies become ever more sophisticated, the amount of health-related data per individual which has become accessible is vast, giving rise to a corresponding need for cross-domain data integration, whole-person modelling, and improved precision medicine. This course provides lessons describing state of the art methods and repositories, as well as a tutorial on computational methods for data integration. 

 

INCF/OCNS Working Group on Computational Neuroscience Software

INCF

This working group is a collaboration between OCNS and INCF. The group focuses on evaluating and testing computational neuroscience tools; finding them, testing them, learning how they work, and informing developers of issues to ensure that these tools remain in good shape by having communities looking after them. Since many members of the WG are themselves tool developers, we will also learn from each other and will work towards improving interoperability between related tools.

 
INCF TrainingSpace

Session 9: Event Annotation in Neuroimaging Using HED: From Experiment to Analysis

INCF

This workshop delves into the need for, structure of, tools for, and use of hierarchical event descriptor (HED) annotation to prepare neuroimaging time series data for storing, sharing, and advanced analysis. HED are a controlled vocabulary of terms describing events in a machine-actionable form so that algorithms can use the information without manual recoding.

 

FAIR neuroscience and EBRAINS tools for data sharing, analysis, and simulation

INCF

This workshop provides an opportunity to explore the advanced tools and techniques for data sharing, analysis, visualization, and simulation.

 

INCF Assembly 2022 - Day 1 Sessions

INCF

Sessions from the INCF Neuroinformatics Assembly 2022 day 1. 

VIEW THE PROGRAM

 

The Virtual Brain (TVB) on EBRAINS

The Virtual Brain

In this course we present the TVB-EBRAINS integrated workflows that have been developed in the Human Brain Project in the third funding phase (“SGA2”) in the Co-Design Project 8 “The Virtual Brain”. 

 

INCF Assembly 2022 - Day 3 Sessions

INCF

Sessions from the INCF Neuroinformatics Assembly 2022 Day 3. 

VIEW THE PROGRAM

 

INCF Assembly 2022 - Day 1 Sessions

INCF

Sessions from the INCF Neuroinformatics Assembly 2022 day 1. 

VIEW THE PROGRAM

 

Notebooks

Notebook systems are proving invaluable to skill acquisition, research documentation, publication, and reproducibility.  This series of presentations introduces the most popular platform for computational notebooks, Project Jupyter, as well as other resources like Binder and NeuroLibre.