Neuromatch Academy: Teaching Computational Neuroscience with Global Accessibility

Neuromatch Academy (NMA) designed and ran a fully online 3-week Computational Neuroscience Summer School for 1757 students with 191 teaching assistants (TAs) working in virtual inverted (or flipped) classrooms and on small group projects. Fourteen languages, active community management, and low cost allowed for an unprecedented level of inclusivity and universal accessibility

Neuromatch Academy: a 3-week, online summer school in computational neuroscience

Neuromatch Academy (https://academy.neuromatch.io; (van Viegen et al., 2021)) was designed as an online summer school to cover the basics of computational neuroscience in three weeks. The materials cover dominant and emerging computational neuroscience tools, how they complement one another, and specifically focus on how they can help us to better understand how the brain functions. An original component of the materials is its focus on modeling choices, i.e. how do we choose the right approach, how do we build models, and how can we evaluate models to determine if they provide real (meaningful) insight. This meta-modeling component of the instructional materials asks what questions can be answered by different techniques, and how to apply them meaningfully to get insight about brain function

NeuroAI

This component contains data for NeuroAI course

CompToolsClimate

Holds Data and Presentation Slides for Computational Tools for Climate Science

Projects 2023

Project Data and Slides for 2023 course iteratio

Tutorials

Data and Slides for Tutorial

Reliability of histologic assessment in patients with eosinophilic oesophagitis

Background: The validity of the eosinophilic oesophagitis (EoE) histologic scoring system (EoEHSS) has been demonstrated, but only preliminary reliability data exist. Aim: Formally assess the reliability of the EoEHSS and additional histologic features. Methods: Four expert gastrointestinal pathologists independently reviewed slides from adult patients with EoE (N = 45) twice, in random order, using standardised training materials and scoring conventions for the EoEHSS and additional histologic features agreed upon during a modified Delphi process. Intra- and inter-rater reliability for scoring the EoEHSS, a visual analogue scale (VAS) of overall histopathologic disease severity, and additional histologic features were assessed using intra-class correlation coefficients (ICCs). Results: Almost perfect intra-rater reliability was observed for the composite EoEHSS scores and the VAS. Inter-rater reliability was also almost perfect for the composite EoEHSS scores and substantial for the VAS. Of the EoEHSS items, eosinophilic inflammation was associated with the highest ICC estimates and consistent with almost perfect intra- and inter-rater reliability. With the exception of dyskeratotic epithelial cells and surface epithelial alteration, ICC estimates for the remaining EoEHSS items were above the benchmarks for substantial intra-rater, and moderate inter-rater reliability. Estimation of peak eosinophil count and number of lamina propria eosinophils were associated with the highest ICC estimates among the exploratory items. Conclusion: The composite EoEHSS and most component items are associated with substantial reliability when assessed by central pathologists. Future studies should assess responsiveness of the score to change after a therapeutic intervention to facilitate its use in clinical trials