Sensitivity to the KARMEN Timing Anomaly at MiniBooNE

We present sensitivities for the MiniBooNE experiment to a rare exotic pion decay producing a massive particle, Q^0. This type of decay represents one possible explanation for the timing anomaly reported by the KARMEN collaboration. MiniBooNE will be able to explore an area of the KARMEN signal that has not yet been investigated

Constraints on a Massive Dirac Neutrino Model

We examine constraints on a simple neutrino model in which there are three massless and three massive Dirac neutrinos and in which the left handed neutrinos are linear combinations of doublet and singlet neutrinos. We examine constraints from direct decays into heavy neutrinos, indirect effects on electroweak parameters, and flavor changing processes. We combine these constraints to examine the allowed mass range for the heavy neutrinos of each of the three generations.Comment: latex, 29 pages, 7 figures (not included), MIT-CTP-221

Search for a 33.9 MeV/c^2 Neutral Particle in Pion Decay

The E815 (NuTeV) neutrino experiment has performed a search for a 33.9 MeV/c^2 weakly-interacting neutral particle produced in pion decay. Such a particle may be responsible for an anomaly in the timing distribution of neutrino interactions in the KARMEN experiment. E815 has searched for this particle's decays in an instrumented decay region; no evidence for this particle was found. The search is sensitive to pion branching ratios as low as 10^-13.Comment: 4 pages; 5 figure

A scheme with two large extra dimensions confronted with neutrino physics

We investigate a particle physics model in a six-dimensional spacetime, where two extra dimensions form a torus. Particles with Standard Model charges are confined by interactions with a scalar field to four four-dimensional branes, two vortices accommodating ordinary type fermions and two antivortices accommodating mirror fermions. We investigate the phenomenological implications of this multibrane structure by confronting the model with neutrino physics data.Comment: LATEX, 24 pages, 9 figures, minor changes in the tex

Spinal cord grey matter segmentation challenge

An important image processing step in spinal cord magnetic resonance imaging is the ability to reliably and accurately segment grey and white matter for tissue specific analysis. There are several semi- or fully-automated segmentation methods for cervical cord cross-sectional area measurement with an excellent performance close or equal to the manual segmentation. However, grey matter segmentation is still challenging due to small cross-sectional size and shape, and active research is being conducted by several groups around the world in this field. Therefore a grey matter spinal cord segmentation challenge was organised to test different capabilities of various methods using the same multi-centre and multi-vendor dataset acquired with distinct 3D gradient-echo sequences. This challenge aimed to characterize the state-of-the-art in the field as well as identifying new opportunities for future improvements. Six different spinal cord grey matter segmentation methods developed independently by various research groups across the world and their performance were compared to manual segmentation outcomes, the present gold-standard. All algorithms provided good overall results for detecting the grey matter butterfly, albeit with variable performance in certain quality-of-segmentation metrics. The data have been made publicly available and the challenge web site remains open to new submissions. No modifications were introduced to any of the presented methods as a result of this challenge for the purposes of this publication

Clinically Feasible Microstructural MRI to Quantify Cervical Spinal Cord Tissue Injury Using DTI, MT, and T2*-Weighted Imaging:Assessment of Normative Data and Reliability

Forty healthy subjects underwent T2WI, DTI, magnetization transfer, and T2*WI at 3T in BACKGROUND AND PURPOSE: DTI, magnetization transfer, T2*-weighted imaging, and cross-sectional area can quantify aspects of spinal cord microstructure. However, clinical adoption remains elusive due to complex acquisitions, cumbersome analysis, limited reliability, and wide ranges of normal values. We propose a simple multiparametric protocol with automated analysis and report normative data, analysis of confounding variables, and reliability. MATERIALS AND METHODS: Forty healthy subjects underwent T2WI, DTI, magnetization transfer, and T2*WI at 3T in RESULTS: T2*WI WM/GM showed lower intersubject coefficient of variation (3.5%) compared with magnetization transfer ratio (5.8%), fractional anisotropy (6.0%), and cross-sectional area (12.2%). Linear correction of cross-sectional area with cervical cord length, fractional anisotropy with age, and magnetization transfer ratio with age and height led to decreased coefficients of variation (4.8%, 5.4%, and 10.2%, respectively). Acceptable reliability was achieved for all metrics/levels (test-retest coefficient of variation <5%), with T2*WI WM/GM comparing favorably with fractional anisotropy and magnetization transfer ratio. DTI with and without cardiac triggering showed no significant differences for fractional anisotropy and test-retest coefficient of variation. CONCLUSIONS: Reliable multiparametric assessment of spinal cord microstructure is possible by using clinically suitable methods. These results establish normalization procedures and pave the way for clinical studies, with the potential for improving diagnostics, objectively monitoring disease progression, and predicting outcomes in spinal pathologies

Brainhack: a collaborative workshop for the open neuroscience community

International audienceBrainhack events offer a novel workshop format with participant-generated content that caters to the rapidly growing open neuroscience community. Including components from hackathons and unconferences, as well as parallel educational sessions, Brainhack fosters novel collaborations around the interests of its attendees. Here we provide an overview of its structure, past events, and example projects. Additionally, we outline current innovations such as regional events and post-conference publications. Through introducing Brainhack to the wider neuroscience community, we hope to provide a unique conference format that promotes the features of collaborative, open science

Brainstem and spinal cord MRI identifies altered sensorimotor pathways post-stroke

Damage to the corticospinal tract is widely studied following unilateral subcortical stroke, whereas less is known about changes to other sensorimotor pathways. This may be due to the fact that many studies investigated morphological changes in the brain, where the majority of descending and ascending brain pathways are overlapping, and did not investigate the brainstem where they separate. Moreover, these pathways continue passing through separate regions in the spinal cord. Here, using a high-resolution structural MRI of both the brainstem and the cervical spinal cord, we were able to identify a number of microstructurally altered pathways, in addition to the corticospinal tract, post stroke. Moreover, decreases in ipsi-lesional corticospinal tract integrity and increases in contra-lesional medial reticulospinal tract integrity were correlated with motor impairment severity in individuals with stroke

An analysis-ready and quality controlled resource for pediatric brain white-matter research

We created a set of resources to enable research based on openly-available diffusion MRI (dMRI) data from the Healthy Brain Network (HBN) study. First, we curated the HBN dMRI data (N = 2747) into the Brain Imaging Data Structure and preprocessed it according to best-practices, including denoising and correcting for motion effects, susceptibility-related distortions, and eddy currents. Preprocessed, analysis-ready data was made openly available. Data quality plays a key role in the analysis of dMRI. To optimize QC and scale it to this large dataset, we trained a neural network through the combination of a small data subset scored by experts and a larger set scored by community scientists. The network performs QC highly concordant with that of experts on a held out set (ROC-AUC = 0.947). A further analysis of the neural network demonstrates that it relies on image features with relevance to QC. Altogether, this work both delivers resources to advance transdiagnostic research in brain connectivity and pediatric mental health, and establishes a novel paradigm for automated QC of large datasets