Inverse transformed encoding models - A solution to the problem of correlated trial-by-trial parameter estimates in fMRI decoding

Techniques of multivariate pattern analysis (MVPA) can be used to decode the discrete experimental condition or a continuous modulator variable from measured brain activity during a particular trial. In functional magnetic resonance imaging (fMRI), trial-wise response amplitudes are sometimes estimated from the measured signal using a general linear model (GLM) with one onset regressor for each trial. When using rapid event-related designs with trials closely spaced in time, those estimates are highly variable and serially correlated due to the temporally extended shape of the hemodynamic response function (HRF). Here, we describe inverse transformed encoding modelling (ITEM), a principled approach of accounting for those serial correlations and decoding from the resulting estimates, at low computational cost and with no loss in statistical power. We use simulated data to show that ITEM outperforms the current standard approach in terms of decoding accuracy and analyze empirical data to demonstrate that ITEM is capable of visual reconstruction from fMRI signals

A comparison between the MEXE and Pippard's methods of assessing the load carrying capacity of masonry arch bridges

The Military Engineering eXperimental Establishment (MEXE) method is a long established system of masonry arch load carrying capacity assessment. It has been subject to review in recent years and some shortcomings have been identified. There is now growing consensus that the current version of MEXE overestimates the load carrying capacity of short span bridges, but for spans over 12m it becomes increasingly conservative. In this paper Pippard’s elastic method and the MEXE method are used to investigate the significance of factors such as fill cover, ring thickness and effective width of arch barrel, and their effect upon the load-carrying capacity predictions in short and long span arches. Conclusions are drawn which establish directions of new research and offer guidance to assessors of short and long span masonry arch bridges

Ultrasonic scanning system for in-place inspection of brazed tube joints

A miniaturized ultrasonic scanning system for nondestructive in-place, non-immersion testing of brazed joints in stainless-steel tubing is described. The system is capable of scanning brazed tube joints, with limited clearance access, in 1/4 through 5/8 inch union, tee, elbow and cross configurations. The system has the capability to detect defective conditions now associated with material density changes in addition to those which are depended upon density variations. The system includes a miniaturized scanning head assembly that fits around a tube joint and rotates the transducer around and down the joint in a continuous spiral motion. The C-scan recorder is similar in principle to conventional models except that it was specially designed to track the continuous spiral scan of the tube joint. The scanner and recorder can be operated with most commercially available ultrasonic flaw detectors

Ultrasonic scanning system for in-place inspection of brazed-tube joints

System detects defects of .051 cm in diameter and larger. System incorporates scanning head assembly including boot enclosed transducer, slip ring assembly, drive mechanism, and servotransmitter. Ultrasonic flaw detector, prototype recorder, and special recorder complete system

Morphology and the gradient of a symmetric potential predicts gait transitions of dogs

Gaits and gait transitions play a central role in the movement of animals. Symmetry is thought to govern the structure of the nervous system, and constrain the limb motions of quadrupeds. We quantify the symmetry of dog gaits with respect to combinations of bilateral, fore-aft, and spatio-temporal symmetry groups. We tested the ability of symmetries to model motion capture data of dogs walking, trotting and transitioning between those gaits. Fully symmetric models performed comparably to asymmetric with only a 22% increase in the residual sum of squares and only one-quarter of the parameters. This required adding a spatio-temporal shift representing a lag between fore and hind limbs. Without this shift, the symmetric model residual sum of squares was 1700% larger. This shift is related to (linear regression, n = 5, p = 0.0328) dog morphology. That this symmetry is respected throughout the gaits and transitions indicates that it generalizes outside a single gait. We propose that relative phasing of limb motions can be described by an interaction potential with a symmetric structure. This approach can be extended to the study of interaction of neurodynamic and kinematic variables, providing a system-level model that couples neuronal central pattern generator networks and mechanical models

How to avoid mismodelling in GLM-based fMRI data analysis: cross-validated Bayesian model selection

Voxel-wise general linear models (GLMs) are a standard approach for analyzing functional magnetic resonance imaging (fMRI) data. An advantage of GLMs is that they are flexible and can be adapted to the requirements of many different data sets. However, the specification of first-level GLMs leaves the researcher with many degrees of freedom which is problematic given recent efforts to ensure robust and reproducible fMRI data analysis. Formal model comparisons that allow a systematic assessment of GLMs are only rarely performed. On the one hand, too simple models may underfit data and leave real effects undiscovered. On the other hand, too complex models might overfit data and also reduce statistical power. Here we present a systematic approach termed cross-validated Bayesian model selection (cvBMS) that allows to decide which GLM best describes a given fMRI data set. Importantly, our approach allows for non-nested model comparison, i.e. comparing more than two models that do not just differ by adding one or more regressors. It also allows for spatially heterogeneous modelling, i.e. using different models for different parts of the brain. We validate our method using simulated data and demonstrate potential applications to empirical data. The increased use of model comparison and model selection should increase the reliability of GLM results and reproducibility of fMRI studies

The validity and reliability of the my jump 2 app for measuring the reactive strength index and drop jump performance

BACKGROUNDː This is the first study to independently assess the concurrent validity and reliability of the My Jump 2 app for measuring drop jump performance. It is also the first to evaluate the app’s ability to measure the reactive strength index (RSI). METHODSː Fourteen male sport science students (age: 29.5 ± 9.9 years) performed three drop jumps from 20 cm and 40 cm (totalling 84 jumps), assessed via a force platform and the My Jump 2 app. Reported metrics included reactive strength index, jump height, ground contact time, and mean power. Measurements from both devices were compared using the intraclass correlation coefficient (ICC), Pearson product moment correlation coefficient (r), Cronbach’s alpha (α), coefficient of variation (CV) and Bland-Altman plots. RESULTSː Near perfect agreement was seen between devices at 20 cm for RSI (ICC = 0.95) and contact time (ICC = 0.99) and at 40 cm for RSI (ICC = 0.98), jump height (ICC = 0.96) and contact time (ICC = 0.92); with very strong agreement seen at 20 cm for jump height (ICC = 0.80). In comparison with the force plate the app showed good validity for RSI (20 cm: r = 0.94; 40 cm; r = 0.97), jump height (20 cm: r = 0.80; 40 cm; r = 0.96) and contact time (20 cm = 0.96; 40 cm; r = 0.98). CONCLUSIONSː The results of the present study show that the My Jump 2 app is a valid and reliable tool for assessing drop jump performance

EarthN: A new Earth System Nitrogen Model

The amount of nitrogen in the atmosphere, oceans, crust, and mantle have important ramifications for Earth's biologic and geologic history. Despite this importance, the history and cycling of nitrogen in the Earth system is poorly constrained over time. For example, various models and proxies contrastingly support atmospheric mass stasis, net outgassing, or net ingassing over time. In addition, the amount available to and processing of nitrogen by organisms is intricately linked with and provides feedbacks on oxygen and nutrient cycles. To investigate the Earth system nitrogen cycle over geologic history, we have constructed a new nitrogen cycle model: EarthN. This model is driven by mantle cooling, links biologic nitrogen cycling to phosphate and oxygen, and incorporates geologic and biologic fluxes. Model output is consistent with large (2-4x) changes in atmospheric mass over time, typically indicating atmospheric drawdown and nitrogen sequestration into the mantle and continental crust. Critical controls on nitrogen distribution include mantle cooling history, weathering, and the total Bulk Silicate Earth+atmosphere nitrogen budget. Linking the nitrogen cycle to phosphorous and oxygen levels, instead of carbon as has been previously done, provides new and more dynamic insight into the history of nitrogen on the planet.Comment: 36 pages, 12 figure