Publications by authors named "Franklin Feingold"
Article Synopsis
- The Brain Imaging Data Structure (BIDS) is a community-created standard for organizing neuroscience data and metadata, helping researchers manage various modalities efficiently.
- The paper discusses the evolution of BIDS, including the guiding principles, extension mechanisms, and challenges faced during its development.
- It also highlights key lessons learned from the BIDS project, aiming to inspire and inform researchers in other fields about effective data organization practices.
Article Synopsis
- The Brain Imaging Data Structure (BIDS) is a collaborative standard designed to organize various neuroscience data and metadata.
- The paper details the history, principles, and mechanisms behind the development and expansion of BIDS, alongside the challenges it faces as it evolves.
- It also shares lessons learned from the project to help researchers in other fields apply similar successful strategies.
The Brain Imaging Data Structure (BIDS) established community consensus on the organization of data and metadata for several neuroimaging modalities. Traditionally, BIDS had a strong focus on functional magnetic resonance imaging (MRI) datasets and lacked guidance on how to store multimodal structural MRI datasets. Here, we present and describe the BIDS Extension Proposal 001 (BEP001), which adds a range of quantitative MRI (qMRI) applications to the BIDS.
View Article and Find Full Text PDFReplicability and reproducibility of scientific findings is paramount for sustainable progress in neuroscience. Preregistration of the hypotheses and methods of an empirical study before analysis, the sharing of primary research data, and compliance with data standards such as the Brain Imaging Data Structure (BIDS), are considered effective practices to secure progress and to substantiate quality of research. We investigated the current level of adoption of open science practices in neuroimaging and the difficulties that prevent researchers from using them.
View Article and Find Full Text PDFThe Brain Imaging Data Structure (BIDS) is a standard for organizing and describing neuroimaging datasets, serving not only to facilitate the process of data sharing and aggregation, but also to simplify the application and development of new methods and software for working with neuroimaging data. Here, we present an extension of BIDS to include positron emission tomography (PET) data, also known as PET-BIDS, and share several open-access datasets curated following PET-BIDS along with tools for conversion, validation and analysis of PET-BIDS datasets.
View Article and Find Full Text PDFThe sharing of research data is essential to ensure reproducibility and maximize the impact of public investments in scientific research. Here, we describe OpenNeuro, a BRAIN Initiative data archive that provides the ability to openly share data from a broad range of brain imaging data types following the FAIR principles for data sharing. We highlight the importance of the Brain Imaging Data Structure standard for enabling effective curation, sharing, and reuse of data.
View Article and Find Full Text PDFVascular endothelial growth factor (VEGF) is a complex signaling protein that supports vascular and neuronal function. Alzheimer's disease (AD) -neuropathological hallmarks interfere with VEGF signaling and modify previously detected positive associations between cerebral spinal fluid (CSF) VEGF and cognition and hippocampal volume. However, it remains unknown 1) whether regional relationships between VEGF and glucose metabolism and cortical thinning exist, and 2) whether AD-neuropathological hallmarks (CSF Aβ, t-tau, p-tau) also modify these relationships.
View Article and Find Full Text PDFArticle Synopsis
- The article by Lee et al. (2019) discusses concerns about reproducibility in cognitive science research, especially regarding model-based approaches.
- The authors emphasize that improving research practices is key to enhancing model robustness, while also advocating for transparent sharing of model specifications and their results.
- They outline efforts within the Brain Imaging Data Structure community to create standards for sharing computational model structures and outputs to boost reproducibility.
White matter hyperintensities (WMHs) are brain white matter lesions that are hyperintense on fluid attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) scans. Larger WMH volumes have been associated with Alzheimer's disease (AD) and with cognitive decline. However, the relationship between WMH volumes and cross-sectional cognitive measures has been inconsistent.
View Article and Find Full Text PDFPurpose: To demonstrate that a "5DCT" technique which utilizes fast helical acquisition yields the same respiratory-gated images as a commercial technique for regular, mechanically produced breathing cycles.
Methods: Respiratory-gated images of an anesthetized, mechanically ventilated pig were generated using a Siemens low-pitch helical protocol and 5DCT for a range of breathing rates and amplitudes and with standard and low dose imaging protocols. 5DCT reconstructions were independently evaluated by measuring the distances between tissue positions predicted by a 5D motion model and those measured using deformable registration, as well by reconstructing the originally acquired scans.