This lesson provides a quick tour of some data repositories and how to download and manipulate data from them.
KnowledgeSpace (KS) is a data discoverability portal and neuroscience encyclopedia that was developed to make it easier for the neuroscience community to find publicly available datasets that adhere to the FAIR Principles and to provide an integrated view of neuroscience concepts found in Wikipedia and NeuroLex linked with PubMed and 17 of the world's leading neuroscience repositories. In short, KS provides a single point of entry where reseaerchers can search for a neuroscience concept of interest and receive results that include: i. a description of the term found in Wikipedia/NeuroLex, ii. links to publicly available datasets related to the concept of interest, and iii. up-to-date references that support the concept of interests found in PubMed. APIs are available so that developers of other neuroscience research infrastructures can integrate KS components in their infrastructures. If your repository or your favorite repository is not indexed in KS, please contact us.
In this lesson, attendees will learn about the data structure standards, specifically the Brain Imaging Data Structure (BIDS), an INCF-endorsed standard for organizing, annotating, and describing data collected during neuroimaging experiments.
This lesson gives an introduction to the Mathematics chapter of Datalabcc's Foundations in Data Science series.
This lesson serves a primer on elementary algebra.
This lesson provides a primer on linear algebra, aiming to demonstrate how such operations are fundamental to many data science.
In this lesson, users will learn about linear equation systems, as well as follow along some practical use cases.
This talk gives a primer on calculus, emphasizing its role in data science.
This lesson clarifies how calculus relates to optimization in a data science context.
This lesson covers Big O notation, a mathematical notation that describes the limiting behavior of a function as it tends towards a certain value or infinity, proving useful for data scientists who want to evaluate their algorithms' efficiency.
This lesson serves as a primer on the fundamental concepts underlying probability.
Serving as good refresher, this lesson explains the maths and logic concepts that are important for programmers to understand, including sets, propositional logic, conditional statements, and more.
This compilation is courtesy of freeCodeCamp.
This lesson provides a useful refresher which will facilitate the use of Matlab, Octave, and various matrix-manipulation and machine-learning software.
This lesson was created by RootMath.
This brief talk goes into work being done at The Alan Turing Institute to solve real-world challenges and democratize computer vision methods to support interdisciplinary and international researchers.
This lecture covers the history of behaviorism and the ultimate challenge to behaviorism.
This lecture covers various learning theories.
How does the brain learn? This lecture discusses the roles of development and adult plasticity in shaping functional connectivity.
In this lightning talk, you will learn about BrainGlobe, an initiative which exists to facilitate the development of interoperable Python-based tools for computational neuroanatomy.
In this short talk you will learn about The Neural System Laboratory, which aims to develop and implement new technologies for analysis of brain architecture, connectivity, and brain-wide gene and molecular level organization.
This video demonstrates each required step for preprocessing T1w anatomical data in brainlife.io.