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INCF Assembly 2023 - Transparency in FAIR Neuroinformatics

INCF Assembly 2023 - Transparency in FAIR Neuroinformatics

This collection contains the the four sessions of talks and one series of lightning talks which took place virtually at INCF's Neuroinformatics Assembly 2023. This year's Assembly was themed around "Transparency in FAIR Neuroinformatics". The material in this collection therefore caters to two main groups:  

 
Essentials of Neuroscience With MATLAB

Essentials of Neuroscience With MATLAB

The Essentials of Neuroscience With MATLAB course was developed to provide advanced undergraduates and early graduate students with a basic familiarity with MATLAB programming with an opportunity to deepen their expertise in neuroscience data analysis using MATLAB. Each module covers a range of specific data processing, analysis, and visualization skills that neuroscientists often need.

 
INCF Neuroinformatics Assembly 2022

INCF Neuroinformatics Assembly 2022

The INCF Assembly is a unique venue where neuroscience standards developers, infrastructure providers, and software developers have the opportunity to interact with the research community to share the latest advancements in neuroinformatics. INCF Assembly 2022 was hosted on the Gather platform. This collection contains recordings of the sessions from the Assembly 2022.

 
INCF Neuroinformatics Assembly 2021

INCF Neuroinformatics Assembly 2021

The objective of the 2021 INCF Neuroinformatics Assembly was to provide a forum in which the neuroscience community can learn about the latest advancements in the application of the FAIR Guiding Principles in neuroscience and attend tutorials on the latest tools, methods, and neuroinformatics approaches that promote open, FAIR, and citable neuroscience. 

 
Yann LeCun's Deep Learning Course at CDS

Yann LeCun's Deep Learning Course at CDS

This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition. The prerequisites include: introduction to data science or a graduate-level machine learning course.

 
Neurodata Without Borders (NWB)

Neurodata Without Borders (NWB)

The objective of this collection of tutorials is to provide an introduction to neuroscientist interested in converting their neurophysiology data to NWB, a unified, extensible, open-source data format for cellular-based neurophysiology data, as well as to present the major tools that are NWB-enabled.

 

 
Neuromatch Academy 2020

Neuromatch Academy 2020

Neuromatch Academy aims to introduce traditional and emerging tools of computational neuroscience to trainees. The collection is intended for participant populations ranging from undergraduates to faculty in academic settings as well as industry professionals. In addition to teaching the technical details of computational methods, the curriculum is centered on modern neuroscience concepts taught by leading professors along with explicit…

 
The Virtual Brain Simulation Platform

The Virtual Brain Simulation Platform

The Virtual Brain takes a network approach on the largest scale: By manipulating network parameters, in particular the brain’s connectivity, The Virtual Brain simulates its behavior as it is commonly observed in clinical scanners (e.g. EEG, MEG, fMRI).