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Research Resource Identifiers (RRIDs) are ID numbers assigned to help researchers cite key resources (antibodies, model organisms and software projects) in the biomedical literature to improve transparency of research methods.

Difficulty level: Beginner
Duration: 1:01:36
Speaker: : Maryann Martone

The Brain Imaging Data Structure (BIDS) is a standard prescribing a formal way to name and organize MRI data and metadata in a file system that simplifies communication and collaboration between users and enables easier data validation and software development through using consistent paths and naming for data files.

Difficulty level: Beginner
Duration: 0:56

Neurodata Without Borders (NWB) is a data standard for neurophysiology that provides neuroscientists with a common standard to share, archive, use, and build common analysis tools for neurophysiology data.

Difficulty level: Beginner
Duration: 1:11
Speaker: : Ben Dichter

The Neuroimaging Data Model (NIDM) is a collection of specification documents that define extensions the W3C PROV standard for the domain of human brain mapping. NIDM uses provenance information as means to link components from different stages of the scientific research process from dataset descriptors and computational workflow, to derived data and publication.

Difficulty level: Beginner
Duration: 0:53

Neuroscience Information Exchange (NIX) Format data model allows storing fully annotated scientific datasets, i.e. the data together with rich metadata and their relations in a consistent, comprehensive format. Its aim is to achieve standardization by providing a common data structure and APIs for a multitude of data types and use cases, focused on but not limited to neuroscience. In contrast to most other approaches, the NIX approach is to achieve this flexibility with a minimum set of data model elements.

Difficulty level: Beginner
Duration: 1:03
Speaker: : Thomas Wachtler

Computational models provide a framework for integrating data across spatial scales and for exploring hypotheses about the biological mechanisms underlying neuronal and network dynamics. However, as models increase in complexity, additional barriers emerge to the creation, exchange, and re-use of models. Successful projects have created standards for describing complex models in neuroscience and provide open source tools to address these issues. This lecture provides an overview of these projects and make a case for expanded use of resources in support of reproducibility and validation of models against experimental data.

Difficulty level: Beginner
Duration: 1:00:39
Speaker: : Sharon Crook
Course:

KnowledgeSpace is a community-based encyclopedia that links brain research concepts to data, models, and literature. It provides users with access to anatomy, gene expression, models, morphology, and physiology data from over 15 different neuroscience data/model repositories, such as Allen Institute for Brain Science and the Human Brain Project.

Difficulty level: Beginner
Duration: 0:58
Speaker: : Tom Gillespie

The Identifiers.org system is a central infrastructure for findable, accessible, interoperable and re-usable (FAIR) data. It provides a range of services to generate, resolve and validate persistent Compact Identifiers to promote the citability of individual data providers and integration with e-infrastructures.

Difficulty level: Beginner
Duration: 36:41

Introduction to the FAIR Principles and examples of applications of the FAIR Principles in neuroscience. This lecture was part of the 2019 Neurohackademy, a 2-week hands-on summer institute in neuroimaging and data science held at the University of Washington eScience Institute.

Difficulty level: Beginner
Duration: 55:57

The probability of a hypothesis, given data.

Difficulty level: Beginner
Duration: 7:57
Speaker: : Barton Poulson

Why math is useful in data science.

Difficulty level: Beginner
Duration: 1:35
Speaker: : Barton Poulson

Why statistics are useful for data science.

Difficulty level: Beginner
Duration: 4:01
Speaker: : Barton Poulson

Statistics is exploring data.

Difficulty level: Beginner
Duration: 2:23
Speaker: : Barton Poulson

Graphical data exploration

Difficulty level: Beginner
Duration: 8:01
Speaker: : Barton Poulson

Numerical data exploration

Difficulty level: Beginner
Duration: 5:05
Speaker: : Barton Poulson

Simple description of statistical data.

Difficulty level: Beginner
Duration: 10:16
Speaker: : Barton Poulson

Basics of hypothesis testing.

Difficulty level: Beginner
Duration: 06:04
Speaker: : Barton Poulson

In this lecture, the speaker demonstrates Neurokernel's module interfacing feature by using it to integrate independently developed models of olfactory and vision LPUs based upon experimentally obtained connectivity information.

Difficulty level: Intermediate
Duration: 29:56
Speaker: : Aurel A. Lazar

Enabling neuroscience research using high performance computing

Difficulty level: Beginner
Duration: 39:27
Speaker: : Subha Sivagnanam

This primer on optogenetics primer discusses how to manipulate neuronal populations with light at millisecond resolution and offers possible applications such as curing the blind and "playing the piano" with cortical neurons.

Difficulty level: Beginner
Duration: 59:06
Speaker: : Clay Reid