In this lesson, while learning about the need for increased large-scale collaborative science that is transparent in nature, users also are given a tutorial on using Synapse for facilitating reusable and reproducible research.
This lesson contains the first part of the lecture Data Science and Reproducibility. You will learn about the development of data science and what the term currently encompasses, as well as how neuroscience and data science intersect.
In this second part of the lecture Data Science and Reproducibility, you will learn how to apply the awareness of the intersection between neuroscience and data science (discussed in part one) to an understanding of the current reproducibility crisis in biomedical science and neuroscience.
The lecture provides an overview of the core skills and practical solutions required to practice reproducible research.
This lecture provides an introduction to reproducibility issues within the fields of neuroimaging and fMRI, as well as an overview of tools and resources being developed to alleviate the problem.
This lecture provides a historical perspective on reproducibility in science, as well as the current limitations of neuroimaging studies to date. This lecture also lays out a case for the use of meta-analyses, outlining available resources to conduct such analyses.
This workshop will introduce reproducible workflows and a range of tools along the themes of organisation, documentation, analysis, and dissemination.
This lecture covers the description and characterization of an input-output relationship in a information-theoretic context.
This lesson is part 1 of 2 of a tutorial on statistical models for neural data.
This lesson is part 2 of 2 of a tutorial on statistical models for neural data.
From the retina to the superior colliculus, the lateral geniculate nucleus into primary visual cortex and beyond, this lecture gives a tour of the mammalian visual system highlighting the Nobel-prize winning discoveries of Hubel & Wiesel.
From Universal Turing Machines to McCulloch-Pitts and Hopfield associative memory networks, this lecture explains what is meant by computation.
In this lesson you will learn about ion channels and the movement of ions across the cell membrane, one of the key mechanisms underlying neuronal communication.
This lecture provides an introduction to Plato’s concept of rationality and Aristotle’s concept of empiricism, and the enduring discussion between rationalism and empiricism to this day.
This lecture goes into further detail about the hard problem of developing a scientific discipline for subjective consciousness.
This video gives a brief introduction to the second session of talks from INCF's Neuroinformatics Assembly 2023.
This talk describes the challenges to sustained operability and success of consortia, why many of these groups flounder after just a few years, and what steps can be taken to mitigate such outcomes.
In this lesson, you will learn about approaches to make the field of neuroscience more open and fair, particularly regarding the integration of equality, diversity, and inclusion (EDI) as guiding principles for team collaboration.
This lesson discusses the topic of credit and contribution in open and FAIR neuroscience, looking through the respective lenses of systems, teams, and people.
This talk describes how to use DataLad for your data management and curation techniques when dealing with animal datasets, which often contain several disparate types of data, including MRI, microscopy, histology, electrocorticography, and behavioral measurements.