Faster Family-wise Error Control for Neuroimaging with a Parametric Bootstrap

In neuroimaging, hundreds to hundreds of thousands of tests are performed across a set of brain regions or all locations in an image. Recent studies have shown that the most common family-wise error (FWE) controlling procedures in imaging, which rely on classical mathematical inequalities or Gaussian random field theory, yield FWE rates that are far from the nominal level. Depending on the approach used, the FWER can be exceedingly small or grossly inflated. Given the widespread use of neuroimaging as a tool for understanding neurological and psychiatric disorders, it is imperative that reliable multiple testing procedures are available. To our knowledge, only permutation joint testing procedures have been shown to reliably control the FWER at the nominal level. However, these procedures are computationally intensive due to the increasingly available large sample sizes and dimensionality of the images, and analyses can take days to complete. Here, we develop a parametric bootstrap joint testing procedure. The parametric bootstrap procedure works directly with the test statistics, which leads to much faster estimation of adjusted \emph{p}-values than resampling-based procedures while reliably controlling the FWER in sample sizes available in many neuroimaging studies. We demonstrate that the procedure controls the FWER in finite samples using simulations, and present region- and voxel-wise analyses to test for sex differences in developmental trajectories of cerebral blood flow

Generalized hardi invariants by method of tensor contraction

pre-printWe propose a 3D object recognition technique to construct rotation invariant feature vectors for high angular resolution diffusion imaging (HARDI). This method uses the spherical harmonics (SH) expansion and is based on generating rank-1 contravariant tensors using the SH coefficients, and contracting them with covariant tensors to obtain invariants. The proposed technique enables the systematic construction of invariants for SH expansions of any order using simple mathematical operations. In addition, it allows construction of a large set of invariants, even for low order expansions, thus providing rich feature vectors for image analysis tasks such as classification and segmentation. In this paper, we use this technique to construct feature vectors for eighth-order fiber orientation distributions (FODs) reconstructed using constrained spherical deconvolution (CSD). Using simulated and in vivo brain data, we show that these invariants are robust to noise, enable voxel-wise classification, and capture meaningful information on the underlying white matter structure

hi2-1, A QTL which improves harvest index, earliness and alters metabolite accumulation of processing tomatoes

Harvest index, defined as the ratio of reproductive yield to total plant biomass, and early ripening are traits with important agronomic value in processing tomatoes. The Solanum pennellii introgression-line (IL) population shows variation for harvest index and earliness. Most of the QTL mapped for these traits display negative agronomic effects; however, hi2-1 is a unique QTL displaying improved harvest index and earliness. This introgression was tested over several years and under different genetic backgrounds. Thirty-one nearly isogenic sub-lines segregating for the 18 cM TG33–TG276 interval were used for fine mapping of this multi-phenotypic QTL. Based on this analysis the phenotypic effects for plant weight, Brix, total yield and earliness were co-mapped to the same region. In a different mapping experiment these sub-lines were tested as heterozygotes in order to map the harvest index QTL which were only expressed in the heterozygous state. These QTL mapped to the same candidate region, suggesting that hi2-1 is either a single gene with pleiotropic effects or represents linked genes independently affecting these traits. Metabolite profiling of the fruit pericarp revealed that a number of metabolic QTL co-segregate with the harvest index trait including those for important transport assimilates such as sugars and amino acids. Analysis of the flowering pattern of these lines revealed induced flowering at IL2-1 plants, suggest that hi2-1 may also affect harvest index and early ripening by changing plant architecture and flowering rate

Shell we cook it? An experimental approach to the microarchaeological record of shellfish roasting

In this paper, we investigate the microarchaeological traces and archaeological visibility of shellfish cooking activities through a series of experimental procedures with direct roasting using wood-fueled fires and controlled heating in a muffle furnace. An interdisciplinary geoarchaeological approach, combining micromorphology, FTIR (in transmission and ATR collection modes), TGA and XRD, was used to establish a baseline on the mineralogical transformation of heated shells from aragonite to calcite and diagnostic sedimentary traces produced by roasting fire features. Our experimental design focused on three main types of roasting procedures: the construction of shallow depressions with heated rocks (pebble cuvette experiments), placing shellfish on top of hot embers and ashes (fire below experiment), and by kindling short-lived fires on top of shellfish (fire above experiments). Our results suggest that similar shellfish roasting procedures will largely create microstratigraphic signatures of anthropogenically reworked combusted material spatially “disconnected” from the actual combustion locus. The construction of shallow earth ovens might entail an increased archaeological visibility, and some diagnostic signatures of in situ hearths can be obtained by fire below roasting activities. We also show that macroscopic visual modifications and mineralogical characterization of discarded shellfish might be indicative of specific cooking activities versus secondary burning