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INCF Assembly 2022 - Day 2 Sessions

INCF

Sessions from the INCF Neuroinformatics Assembly 2022 day 2. 

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INCF TrainingSpace

Deep Learning: Parameters Sharing

NYU Center for Data Science

This course covers the concepts of recurrent and convolutional nets (theory and practice), natural signals properties and the convolution, and recurrent neural networks (vanilla and gated, LSTM).

 

Enabling Multi-Scale Data Integration: Turning Data to Knowledge

NFDI Neuroscience

This workshop is organized by the German National Research Data Infrastructure Initiative Neuroscience (NFDI-Neuro). The initiative is community driven and comprises around 50 contributing national partners and collaborators. NFDI-Neuro partners with EBRAINS AISB, the coordinating entity of the EU Human Brain Project and the EBRAINS infrastructure. We will introduce common methods that enable digital reproducible neuroscience.

 

Fundamental Methods for Single-Cell Transcriptome Analysis

Krembil Centre for Neuroinformatics

This course, consisting of one lecture and two workshops, is presented by the Computational Genomics Lab at the Centre for Addiction and Mental Health and University of Toronto. The lecture deals with single-cell and bulk level transciptomics, while the two hands-on workshops introduce users to transcriptomic data types (e.g., RNAseq) and how to perform analyses in specific use cases (e.g., cellular changes in major depression). 

 

Dynamical Neural Systems

ICTS

This course consists of several introductory lectures on different aspects of biochemical models. The lectures cover topics such as stability analysis of neural models, oscillations and bursting, and weakly coupled oscillators. You will learn about modeling various scales and properties of neural mechanisms, from firing-rate models of single neurons to pattern generation in visual system hallucinations. 

 
INCF TrainingSpace

Session 4: "Is This FAIR?": Transparency in EDI, Career Development, & Management

INCF

There is a growing recognition and adoption of open and FAIR science practices in neuroscience research. This is predominately regarded as scientific progress and has enabled significant opportunities for large, collaborative, team science. The efforts and practical work that go into creating an open and FAIR landscape extend far beyond just the science.

 
INCF TrainingSpace

Session 1: A FAIR Roadmap for Knowledge Graphs and Ontologies

INCF

This course corresponds to the first session of talks given at INCF's Neuroinformatics Assembly 2023. The sessions consists of several lectures, focusing on using the principles of FAIR (findability, accessibility, interoperability, and reusability) to inform future directions in neuroscience and neuroinformatics. In particular, these talks deal with the development of knowledge graphs and ontologies. 

 

OpenNeuro.org Tutorials

OpenNeuro.org

This course consists of brief tutorials on OpenNeuro.org, a free and open platform for analyzing and sharing neuroimaging data. During this course, you will learn how to deal with your neuroscientific datasets using OpenNeuro.org for operations such as uploading and version control, as well as how to analyze and share your data. 

 

INCF Assembly 2022 - Day 3 Sessions

INCF

Sessions from the INCF Neuroinformatics Assembly 2022 Day 3. 

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The Virtual Brain Education Pack (TVB EduPack)

The Virtual Brain

The Virtual Brain EduPack provides didactic use cases for The Virtual Brain (TVB). Typically a use case consists of a jupyter notebook and a didactic video. EduPack use cases help the user to reproduce TVB-based publications or to get started quickly with TVB.

 

INCF Assembly 2022 - Day 3 Sessions

INCF

Sessions from the INCF Neuroinformatics Assembly 2022 Day 3. 

VIEW THE PROGRAM

 

Foundations of Data Science

Datalabcc

Data science relies on several important aspects of mathematics. In this course, you'll learn what forms of mathematics are most useful for data science, and see some worked examples of how math can solve important data science problems.

 

INCF Short Course: Introduction to Neuroinformatics

INCF

The emergence of data-intensive science creates a demand for neuroscience educators worldwide to deliver better neuroinformatics education and training in order to raise a generation of modern neuroscientists with FAIR capabilities, awareness of the value of standards and best practices, knowledge in dealing with big datasets, and the ability to integrate knowledge over multiple scales and methods.

 
INCF TrainingSpace

Session 2: FAIR Sharing, Integration, & Analysis of Neuroscience Data

INCF

This course corresponds to the second session of INCF's Neuroinformatics Assembly 2023. This series of talks continues a discussion of FAIR principles from the first session, with a greater emphasis on brain data (humans and animals) atlases for data analysis and integation. 

 
INCF TrainingSpace

Neuromorphic Computing and Challenges

INCF

Future computing systems will capitalize on our increased understanding of the brain through the use of similar architectures and computational principles. During this workshop, we bring together recent developments in this rapidly developing field of neuromorphic computing systems, and also discuss challenges ahead.

 
INCF TrainingSpace

INCF Assembly 2023 - Lightning Talks (Day 2)

INCF

This course consists of several lightning talks from the second day of INCF's Neuroinformatics Assembly 2023. Covering a wide range of topics, these brief talks provide snapshots of various neuroinformatic efforts such as brain-computer interface standards, dealing with multimodal animal MRI datasets, distributed data management, and several more. 

 

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 2 Sessions

INCF

Sessions from the INCF Neuroinformatics Assembly 2022 day 2. 

VIEW THE PROGRAM

 

Fundamental Methods for Genomic Analysis

Krembil Centre for Neuroinformatics

This course includes both lectures and tutorials around the management and analysis of genomic data in clinical research and care. Participants are led through the basics of genome-wide association studies (GWAS), genotypes, and polygenic risk scores, as well as novel concepts and tools for more sophisticated consideration of population stratification in GWAS.

 
INCF TrainingSpace

Standards and Best Practices

INCF

Standards and best practices make neuroscience a data-centric discipline and are key for integrating diverse data and for developing a robust, effective, and sustainable infrastructure to support open and reproducible neuroscience. This study track provides an introduction to standards and best practices that support the FAIR Principles.