This lecture provides a history of data management, recent developments data management, and a brief description of scientific data management.
This lesson gives a presentation on computationally demanding studies of synaptic plasticity on the molecular level.
This talk presents several computationally demanding studies of synaptic plasticity on the molecular level.
In this lesson you will hear about several computationally demanding studies of synaptic plasticity on the molecular level.
This lecture presents an overview of functional brain parcellations, as well as a set of tutorials on bootstrap agregation of stable clusters (BASC) for fMRI brain parcellation.
This lesson provides instructions on how to build and share extensions in NWB.
Learn how to build custom APIs for extension.
This lesson provides instruction on advanced writing strategies in HDF5 that are accessible through PyNWB.
This lesson provides a tutorial on how to handle writing very large data in MatNWB.
This lesson provides an introduction to biologically detailed computational modelling of neural dynamics, including neuron membrane potential simulation and F-I curves.
In this lesson, users learn how to use MATLAB to build an adaptive exponential integrate and fire (AdEx) neuron model.
In this lesson, users learn about the practical differences between MATLAB scripts and functions, as well as how to embed their neuronal simulation into a callable function.
This lesson teaches users how to generate a frequency-current (F-I) curve, which describes the function that relates the net synaptic current (I) flowing into a neuron to its firing rate (F).
This lecture discusses the the importance and need for data sharing in clinical neuroscience.
This lecture gives insights into the Medical Informatics Platform's current and future data privacy model.
This lecture gives an overview on the European Health Dataspace.
This lesson is a general overview of overarching concepts in neuroinformatics research, with a particular focus on clinical approaches to defining, measuring, studying, diagnosing, and treating various brain disorders. Also described are the complex, multi-level nature of brain disorders and the data associated with them, from genes and individual cells up to cortical microcircuits and whole-brain network dynamics. Given the heterogeneity of brain disorders and their underlying mechanisms, this lesson lays out a case for multiscale neuroscience data integration.
This is the first of two workshops on reproducibility in science, during which participants are introduced to concepts of FAIR and open science. After discussing the definition of and need for FAIR science, participants are walked through tutorials on installing and using Github and Docker, the powerful, open-source tools for versioning and publishing code and software, respectively.
This lesson describes the fundamentals of genomics, from central dogma to design and implementation of GWAS, to the computation, analysis, and interpretation of polygenic risk scores.
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.