The real-time fMRI neurofeedback based stratification of Default Network Regulation Neuroimaging data repository.

This data descriptor describes a repository of openly shared data from an experiment to assess inter-individual differences in default mode network (DMN) activity. This repository includes cross-sectional functional magnetic resonance imaging (fMRI) data from the Multi Source Interference Task, to assess DMN deactivation, the Moral Dilemma Task, to assess DMN activation, a resting state fMRI scan, and a DMN neurofeedback paradigm, to assess DMN modulation, along with accompanying behavioral and cognitive measures. We report technical validation from n=125 participants of the final targeted sample of 180 participants.

A Tool for Interactive Data Visualization: Application to Over 10,000 Brain Imaging and Phantom MRI Data Sets.

In this paper we propose a web-based approach for quick visualization of big data from brain magnetic resonance imaging (MRI) scans using a combination of an automated image capture and processing system, nonlinear embedding, and interactive data visualization tools. We draw upon thousands of MRI scans captured via the COllaborative Imaging and Neuroinformatics Suite (COINS). We then interface the output of several analysis pipelines based on structural and functional data to a t-distributed stochastic neighbor embedding (t-SNE) algorithm which reduces the number of dimensions for each scan in the input data set to two dimensions while preserving the local structure of data sets.

COINS Data Exchange: An open platform for compiling, curating, and disseminating neuroimaging data.

Neuroimaging data collection is inherently expensive. Maximizing the return on investment in neuroimaging studies requires that neuroimaging data be re-used whenever possible. In an effort to further scientific knowledge, the COINS Data Exchange (DX) (http://coins.

Harnessing modern web application technology to create intuitive and efficient data visualization and sharing tools.

Neuroscientists increasingly need to work with big data in order to derive meaningful results in their field. Collecting, organizing and analyzing this data can be a major hurdle on the road to scientific discovery. This hurdle can be lowered using the same technologies that are currently revolutionizing the way that cultural and social media sites represent and share information with their users.

Automated collection of imaging and phenotypic data to centralized and distributed data repositories.

Accurate data collection at the ground level is vital to the integrity of neuroimaging research. Similarly important is the ability to connect and curate data in order to make it meaningful and sharable with other investigators. Collecting data, especially with several different modalities, can be time consuming and expensive.

In vivo differentiation of complementary contrast media at dual-energy CT.

Purpose: To evaluate the feasibility of using a commercially available clinical dual-energy computed tomographic (CT) scanner to differentiate the in vivo enhancement due to two simultaneously administered contrast media with complementary x-ray attenuation ratios.

Materials And Methods: Approval from the institutional animal care and use committee was obtained, and National Institutes of Health guidelines for the care and use of laboratory animals were observed. Dual-energy CT was performed in a set of iodine and tungsten solution phantoms and in a rabbit in which iodinated intravenous and bismuth subsalicylate oral contrast media were administered.

COINS: An Innovative Informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets.

The availability of well-characterized neuroimaging data with large numbers of subjects, especially for clinical populations, is critical to advancing our understanding of the healthy and diseased brain. Such data enables questions to be answered in a much more generalizable manner and also has the potential to yield solutions derived from novel methods that were conceived after the original studies' implementation. Though there is currently growing interest in data sharing, the neuroimaging community has been struggling for years with how to best encourage sharing data across brain imaging studies.

Single electron transfer-promoted photocyclization reactions of linked acceptor-polydonor systems: effects of chain length and type on the efficiencies of macrocyclic ring-forming photoreactions of tethered alpha-silyl ether phthalimide substrates.

Results of an investigation, aimed at gaining information about the factors governing the efficiencies of single electron transfer (SET)-promoted photocyclization reactions of linked acceptor-polydonor systems, are described. One set of substrates used in this effort includes alpha-trimethylsilyl ether terminated, polymethylene- and polyethylenoxy-tethered phthalimides and 2,3-naphthalimides. Photocyclization reactions of the polyethylenoxy-linked phthalimides and naphthalimides were observed to take place in higher chemical yields and with larger quantum efficiencies than those of analogs containing polymethylene tethers of near equal length.

Beta-lactam-forming photochemical reactions of N-trimethylsilylmethyl- and N-tributylstannylmethyl-substituted alpha-ketoamides.

Two mechanisms have been proposed for the beta-lactam-forming photochemical reactions of alpha-ketoamides. One, suggested by Aoyama, involves excited-state H-atom abstraction while the other, put forth by Whitten, follows a sequential SET-proton-transfer route. The photochemical properties of N-trimethylsilylmethyl- and N-tributylstannylmethyl-substituted alpha-ketoamides were explored in order to gain information about the mechanism of this process and to develop a regioselective method for beta-lactam formation.