A5028993013- Big Data and Business Intelligence
- Scientific Computing and Data Management
- Research Data Management Practices
- Functional Brain Connectivity Studies
- Distributed and Parallel Computing Systems
- Cell Image Analysis Techniques
- Mental Health Research Topics
- Cholinesterase and Neurodegenerative Diseases
- Neural and Behavioral Psychology Studies
- Alzheimer's disease research and treatments
- Neural dynamics and brain function
- Neurological Disorders and Treatments
- Biomedical and Engineering Education
- Memory and Neural Mechanisms
- Genomics and Rare Diseases
- Cloud Computing and Resource Management
- EEG and Brain-Computer Interfaces
- Neuroscience and Neuropharmacology Research
Forschungszentrum Jülich
2021-2024
Alzheimer’s Disease Neuroimaging Initiative
2023
Union Bank of Switzerland
2023
DataLad is a Python-based tool for the joint management of code, data, and their relationship, built on top versatile system data logistics (git-annex) most popular distributed version control (Git).It adapts principles open-source software development distribution to address technical challenges management, sharing, digital provenance collection across life cycle objects.DataLad aims make as easy managing code.It streamlines procedures consume, publish, update any size or type, link them...
Abstract Large-scale datasets present unique opportunities to perform scientific investigations with unprecedented breadth. However, they also pose considerable challenges for the findability, accessibility, interoperability, and reusability (FAIR) of research outcomes due infrastructure limitations, data usage constraints, or software license restrictions. Here we introduce a DataLad-based, domain-agnostic framework suitable reproducible processing in compliance open science mandates. The...
Naturalistic viewing (NV) is currently considered a promising paradigm for studying individual differences in functional brain organization. While whole connectivity (FC) under NV has been relatively well characterized, so far little work done on network level. Here, we extend current knowledge by characterizing the influence of FC fourteen meta-analytically derived networks considering three different movie stimuli comparison to resting-state (RS). We show that increases identifiability...
Abstract INTRODUCTION Hippocampal local and network dysfunction is the hallmark of Alzheimer's disease (AD). METHODS We characterized spatial patterns hippocampus differentiation based on brain co‐metabolism in healthy elderly participants demonstrated their relevance to study metabolic changes associated pathological aging. RESULTS The can be differentiated into anterior/posterior dorsal cornu ammonis (CA)/ventral (subiculum) subregions. While CA show with different regions subcortical...
Abstract Research data management has become an indispensable skill in modern neuroscience. Researchers can benefit from following good practices as well having proficiency using particular software solutions. But these domain-agnostic skills are commonly not included domain-specific graduate education, community efforts increasingly provide early career scientists with opportunities for organised training and materials self-study. Investing effort user documentation interacting the base...
OHBM Brainhack 2022 took place in June 2022. The first hybrid hackathon, it had an in-person component taking Glasgow and three hubs around the globe to improve inclusivity fit as many timezones possible. In buzzing setting of Queen Margaret Union virtual platform, 23 projects were presented after development. Following are reports 14 those, well a recapitulation organisation event.
Abstract Functional connectivity analyses have given considerable insights into human brain function and organization. As research moves towards clinical application, test-retest reliability has become a main focus of the field. So far, majority studies relied on resting-state paradigms to examine connectivity, based its low demand ease implementation. However, measures is mostly moderate, potentially due unconstrained nature. Recently, naturalistic viewing gained popularity because they...
Abstract Objectives Normal sleep is crucial for brain health. Recent studies have reported robust associations between disturbance and various structural functional traits. However, the complex interplay health macro-scale organization remains inconclusive. In this study, we aimed to uncover links imaging features diverse health-related characteristics by means of Machine Learning (ML). Methods We used 28,088 participants from UK Biobank calculate 4677 neuroimaging markers. Then, employed...
Abstract Large-scale datasets present unique opportunities to perform scientific investigations with un-precedented breadth. However, they also pose considerable challenges for the findability, accessibility, interoperability, and reusability (FAIR) of research outcomes due infrastructure limitations, data usage constraints, or software license restrictions. Here we introduce a DataLad-based, domain-agnostic framework suitable reproducible processing in compliance open science mandates. The...