NeuroNorm:An R package to standardize multiple structural MRI

Preprocessing of structural MRI involves multiple steps to clean and standardize data before further analysis. Typically, researchers use numerous tools to create tailored preprocessing workflows that adjust to their dataset. This process hinders research reproducibility and transparency. In this paper, we introduce NeuroNorm, a robust and reproducible preprocessing pipeline that addresses the challenges of preparing structural MRI data. NeuroNorm adapts its workflow to the input datasets without manual intervention and uses state-of-the-art methods to guarantee high-standard results. We demonstrate NeuroNorm’s strength by preprocessing hundreds of MRI scans from three different sources with specific parameters on image dimensions, voxel intensity ranges, patients characteristics, acquisition protocols and scanner type. The preprocessed images can be visually and analytically compared to each other as they share the same geometrical and intensity space. NeuroNorm supports clinicians and researchers with a robust, adaptive and comprehensible preprocessing pipeline, increasing and certifying the sensitivity and validity of subsequent analyses. NeuroNorm requires minimal user inputs and interaction, making it a userfriendly set of tools for users with basic programming experience

Brain-Inspired Intelligent Systems for Daily Assistance

The fields of machine learning and cognitive computing have been in the last decade revolutionised with neural-inspired algorithms (e.g., deep ANNs and deep RL) and brain-intelligent systems that assist in many real-world learning tasks from robot monitoring and interaction at home to complex decision-making about emotions and behaviours in humans and animals. While there are remarkable advances in these brain-inspired algorithms and systems, they need to be trained with huge data sets, and their results lack flexibility to adapt to diverse learning tasks and sustainable performance over long periods of time. To address these challenges, it is essential to gain an analytical understanding of the principles that allow biological inspired intelligent systems to leverage knowledge and how they can be translated to hardware for daily assistance and practical applications. This special issue brings researchers from interdesciplinary domains to report their latest research work on algorithms and neural-inspired systems that flexibly adapt to new learning tasks, learn from the environment using multimodal signals (e.g., neural, physiological, and kinematic), and produce autonomous adaptive agencies, which utilise cognitive and affective data, within a social neuroscientific framework. In this special issue, we have selected five papers out of fourteen high-quality papers after a careful reviewing process, which brings the acceptance rate to 35.7 percent. The five papers are representative of the current state-of-the-art in this area

Stable vortex and dipole vector solitons in a saturable nonlinear medium

We study both analytically and numerically the existence, uniqueness, and stability of vortex and dipole vector solitons in a saturable nonlinear medium in (2+1) dimensions. We construct perturbation series expansions for the vortex and dipole vector solitons near the bifurcation point where the vortex and dipole components are small. We show that both solutions uniquely bifurcate from the same bifurcation point. We also prove that both vortex and dipole vector solitons are linearly stable in the neighborhood of the bifurcation point. Far from the bifurcation point, the family of vortex solitons becomes linearly unstable via oscillatory instabilities, while the family of dipole solitons remains stable in the entire domain of existence. In addition, we show that an unstable vortex soliton breaks up either into a rotating dipole soliton or into two rotating fundamental solitons.Comment: To appear in Phys. Rev.

Evaluation of different chrominance models in the detection and reconstruction of faces and hands using the growing neural gas network

Physical traits such as the shape of the hand and face can be used for human recognition and identification in video surveillance systems and in biometric authentication smart card systems, as well as in personal health care. However, the accuracy of such systems suffers from illumination changes, unpredictability, and variability in appearance (e.g. occluded faces or hands, cluttered backgrounds, etc.). This work evaluates different statistical and chrominance models in different environments with increasingly cluttered backgrounds where changes in lighting are common and with no occlusions applied, in order to get a reliable neural network reconstruction of faces and hands, without taking into account the structural and temporal kinematics of the hands. First a statistical model is used for skin colour segmentation to roughly locate hands and faces. Then a neural network is used to reconstruct in 3D the hands and faces. For the filtering and the reconstruction we have used the growing neural gas algorithm which can preserve the topology of an object without restarting the learning process. Experiments conducted on our own database but also on four benchmark databases (Stirling’s, Alicante, Essex, and Stegmann’s) and on deaf individuals from normal 2D videos are freely available on the BSL signbank dataset. Results demonstrate the validity of our system to solve problems of face and hand segmentation and reconstruction under different environmental conditions

Inflation on Fractional Branes: D--Brane Inflation as D--Term Inflation

We describe a D--brane inflation model which consists of two fractional D3 branes separated on a transverse $T^2 \times K3$. Inflation arises due to the resolved orbifold singularity of $K3$ which corresponds to an anomalous D--term on the brane. We show that D--brane inflation in the bulk corresponds to D--term inflation on the brane. The inflaton and the trigger field parametrize the interbrane distances on $T^2$ an $K3$ respectively. After inflation the branes reach a supersymmetric configuration in which they are at the origin of $T^2$ but separated along the $K3$ directions.Comment: 15 pages in phyzzx.tex; minor corrections including all factors of 2\pi; v3: more minor correction

Three-Neutrino Mixing after the First Results from K2K and KamLAND

We analyze the impact of the data on long baseline \nu_\mu disappearance from the K2K experiment and reactor \bar\nu_e disappearance from the KamLAND experiment on the determination of the leptonic three-generation mixing parameters. Performing an up-to-date global analysis of solar, atmospheric, reactor and long baseline neutrino data in the context of three-neutrino oscillations, we determine the presently allowed ranges of masses and mixing and we consistently derive the allowed magnitude of the elements of the leptonic mixing matrix. We also quantify the maximum allowed contribution of \Delta m^2_{21} oscillations to CP-odd and CP-even observables at future long baseline experiments.Comment: Some typos correcte

Probing neutrino non-standard interactions with atmospheric neutrino data

We have reconsidered the atmospheric neutrino anomaly in light of the laetst data from Super-Kamiokande contained events and from Super-Kamiokande and MACRO up-going muons. We have reanalysed the proposed solution to the atmospheric neutrino anomaly in terms of non-standard neutrino-matter interactions (NSI) as well as the standard nu_mu -> nu_tau oscillations (OSC). Our statistical analysis shows that a pure NSI mechanism is now ruled out at 99%, while the standard nu_mu -> nu_tau OSC mechanism provides a quite remarkably good description of the anomaly. We therefore study an extended mechanism of neutrino propagation which combines both oscillation and non-standard neutrino-matter interactions, in order to derive limits on flavour-changing (FC) and non-universal (NU) neutrino interactions. We obtain that the off-diagonal flavour-changing neutrino parameter epsilon and the diagonal non-universality neutrino parameter epsilon' are confined to -0.03 < epsilon < 0.02 and |epsilon'| < 0.05 at 99.73% CL. These limits are model independent and they are obtained from pure neutrino-physics processes. The stability of the neutrino oscillation solution to the atmospheric neutrino anomaly against the presence of non-standard neutrino interactions establishes the robustness of the near-maximal atmospheric mixing and massive-neutrino hypothesis. The best agreement with the data is obtained for Delta_m^2 = 2.3*10^{-3} eV^2, sin^2(2*theta) = 1, epsilon = 6.7*10^{-3} and epsilon' = 1.1*10^{-3}, although the chi^2 function is quite flat in the epsilon and epsilon' directions for epsilon, epsilon' -> 0.Comment: 26 pages, LaTeX file using REVTeX4, 1 table and 12 figures included. Added a revised analysis which takes into account the new 1489-day Super-Kamiokande and final MACRO data. The bound on NSI parameters is considerably improve

WMAP constraints on scalar-tensor cosmology and the variation of the gravitational constant

We present observational constraints on a scalar-tensor gravity theory by $\chi^2$ test for CMB anisotropy spectrum. We compare the WMAP temperature power spectrum with the harmonic attractor model, in which the scalar field has its harmonic effective potential with curvature $\beta$ in the Einstein conformal frame and the theory relaxes toward Einstein gravity with time. We found that the present value of the scalar coupling, i.e. the present level of deviation from Einstein gravity $(\alpha_0^2)$, is bounded to be smaller than $5\times 10^{-4-7\beta}$ ($2\sigma$), and $10^{-2-7\beta}$ ($4\sigma$) for $0< \beta<0.45$. This constraint is much stronger than the bound from the solar system experiments for large $\beta$ models, i.e., $\beta> 0.2$ and 0.3 in $2\sigma$ and $4\sigma$ limits, respectively. Furthermore, within the framework of this model, the variation of the gravitational constant at the recombination epoch is constrained as $|G(z=z_{rec})-G_0|/G_0 < 0.05(2\sigma)$, and $0.23(4\sigma)$.Comment: 7 page

Confusing non-standard neutrino interactions with oscillations at a neutrino factory

Most neutrino mass theories contain non-standard interactions (NSI) of neutrinos which can be either non-universal (NU) or flavor-changing (FC). We study the impact of such interactions on the determination of neutrino mixing parameters at a neutrino factory using the so-called ``golden channels'' \pnu{e}\to\pnu{\mu} for the measurement of \theta_{13}. We show that a certain combination of FC interactions in neutrino source and earth matter can give exactly the same signal as oscillations arising due to \theta_{13}. This implies that information about \theta_{13} can only be obtained if bounds on NSI are available. Taking into account the existing bounds on FC interactions, this leads to a drastic loss in sensitivity in \theta_{13}, at least two orders of magnitude. A near detector at a neutrino factory offers the possibility to obtain stringent bounds on some NSI parameters. Such near site detector constitutes an essential ingredient of a neutrino factory and a necessary step towards the determination of \theta_{13} and subsequent study of leptonic CP violation.Comment: 23 pages, 5 figures, improved version, accepted for publication in Phs. Rev. D, references adde

Improved myocardial scar visualization with fast free-breathing motion-compensated black-blood T₁-rho-prepared late gadolinium enhancement MRI.

Clinical guidelines recommend the use of bright-blood late gadolinium enhancement (BR-LGE) for the detection and quantification of regional myocardial fibrosis and scar. This technique, however, may suffer from poor contrast at the blood-scar interface, particularly in patients with subendocardial myocardial infarction. The purpose of this study was to assess the clinical performance of a two-dimensional black-blood LGE (BL-LGE) sequence, which combines free-breathing T &lt;sub&gt;1&lt;/sub&gt; -rho-prepared single-shot acquisitions with an advanced non-rigid motion-compensated patch-based reconstruction. Extended phase graph simulations and phantom experiments were performed to investigate the performance of the motion-correction algorithm and to assess the black-blood properties of the proposed sequence. Fifty-one patients (37 men, 14 women; mean age, 55 ± 15 [SD] years; age range: 19-81 years) with known or suspected cardiac disease prospectively underwent free-breathing T &lt;sub&gt;1&lt;/sub&gt; -rho-prepared BL-LGE imaging with inline non-rigid motion-compensated patch-based reconstruction at 1.5T. Conventional breath-held BR-LGE images were acquired for comparison purposes. Acquisition times were recorded. Two readers graded the image quality and relative contrasts were calculated. Presence, location, and extent of LGE were evaluated. BL-LGE images were acquired with full ventricular coverage in 115 ± 25 (SD) sec (range: 64-160 sec). Image quality was significantly higher on free-breathing BL-LGE imaging than on its breath-held BR-LGE counterpart (3.6 ± 0.7 [SD] [range: 2-4] vs. 3.9 ± 0.2 [SD] [range: 3-4]) (P &lt;0.01) and was graded as diagnostic for 44/51 (86%) patients. The mean scar-to-myocardium and scar-to-blood relative contrasts were significantly higher on BL-LGE images (P &lt; 0.01 for both). The extent of LGE was larger on BL-LGE (median, 5 segments [IQR: 2, 7 segments] vs. median, 4 segments [IQR: 1, 6 segments]) (P &lt; 0.01), the method being particularly sensitive in segments with LGE involving the subendocardium or papillary muscles. In eight patients (16%), BL-LGE could ascertain or rule out a diagnosis otherwise inconclusive on BR-LGE. Free-breathing T &lt;sub&gt;1&lt;/sub&gt; -rho-prepared BL-LGE imaging with inline motion compensated reconstruction offers a promising diagnostic technology for the non-invasive assessment of myocardial injuries