Complex network modeling of EEG band coupling in dyslexia: An exploratory analysis of auditory processing and diagnosis

Complex network analysis has an increasing relevance in the study of neurological disorders, enhancing the knowledge of brain’s structural and functional organization. Network structure and efficiency reveal different brain states along with different ways of processing the information. This work is structured around the exploratory analysis of the brain processes involved in low-level auditory processing. A complex network analysis was performed on the basis of brain coupling obtained from electroencephalography (EEG) data, while different auditory stimuli were presented to the subjects. This coupling is inferred from the Phase-Amplitude coupling (PAC) from different EEG electrodes to explore differences between control and dyslexic subjects. Coupling data allows the construction of a graph, and then, graph theory is used to study the characteristics of the complex networks throughout time for control and dyslexic subjects. This results in a set of metrics including clustering coefficient, path length and small-worldness. From this, different characteristics linked to the temporal evolution of networks and coupling are pointed out for dyslexics. Our study revealed patterns related to Dyslexia as losing the small-world topology. Finally, these graph-based features are used to classify between control and dyslexic subjects by means of a Support Vector Machine (SVM).Spanish Government PGC2018-098813-B-C32Junta de Andalucia UMA20-FEDERJA-086European CommissionNVIDIA CorporationMinistry of Science and Innovation, Spain (MICINN) Spanish GovernmentEuropean CommissionUniversidad de Malaga/CBU

Inter-channel Granger Causality for Estimating EEG Phase Connectivity Patterns in Dyslexia

Methods like Electroencephalography (EEG) and magnetoencephalogram (MEG) record brain oscillations and provide an invaluable insight into healthy and pathological brain function. These signals are helpful to study and achieve an objective and early diagnosis of neural disorders as Developmental Dyslexia (DD). An atypical oscillatory sampling could cause the characteristic phonological difficulties of dyslexia at one or more temporal rates; in this sense, measuring the EEG signal can help to make an early diagnosis of DD. The LEEDUCA study conducted a series of EEG experiments on children listening to amplitude modulated (AM) noise with slow-rhythmic prosodic (0.5–1 Hz) to detect differences in perception of oscillatory ampling that could be associated with dyslexia. The evolution of each EEG channel has been studied in the frequency domain, obtaining the analytical phase using the Hilbert transform. Subsequently, the cause-effect relationships between channels in ach subject have been reflected thanks to Granger causality, obtaining matrices that reflect the interaction between the different parts of the brain. Hence, each subject was classified as belonging or not to the control group or the experimental group. For this purpose, two ensemble classification algorithms were compared, showing that both can reach acceptable classifying erformance in delta band with an accuracy up to 0.77, recall of 0.91 and AUC of 0.97 using Gradient Boosting classifier.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Enhancing Multimodal Patterns in Neuroimaging by Siamese Neural Networks with Self-Attention Mechanism.

The combination of different sources of information is currently one of the most relevant aspects in the diagnostic process of several diseases. In the field of neurological disorders, different imaging modalities providing structural and functional information are frequently available. Those modalities are usually analyzed separately, although a joint of the features extracted from both sources can improve the classification performance of Computer-aided diagnosis (CAD) tools. Previous studies have computed independent models from each individual modality and combined then in a subsequent stage, which is not an optimum solution. In this work, we propose a method based on the principles of siamese neural networks to fuse information from Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET). This framework quantifies the similarities between both modalities and relates them with the diagnostic label during the training process. The resulting latent space at the output of this network is then entered into an attention module in order to evaluate the relevance of each brain region and modality at different stages of the development of Alzheimer’s disease. The excellent results obtained and the high flexibility of the method proposed allows fusing more than two modalities, leading to a scalable methodology that can be used in a wide range of contexts.This work was supported by projects PGC2018- 098813-B-C32 and RTI2018-098913-B100 (Spanish “Ministerio de Ciencia, Innovación y Universidades”), UMA20-FEDERJA-086, A-TIC-080- UGR18 and P20 00525 (Consejería de economía y conocimiento, Junta de Andalucía) and by European Regional Development Funds (ERDF); and by Spanish “Ministerio de Universidades” through Margarita-Salas grant to J.E. Arco

EEG Interchannel Causality to Identify Source/Sink Phase Connectivity Patterns in Developmental Dyslexia

While the brain connectivity network can inform the understanding and diagnosis of developmental dyslexia, its cause-effect relationships have not yet enough been examined. Employing electroencephalography signals and bandlimited white noise stimulus at 4.8 Hz (prosodic-syllabic frequency), we measure the phase Granger causalities among channels to identify differences between dyslexic learners and controls, thereby proposing a method to calculate directional connectivity. As causal relationships run in both directions, we explore three scenarios, namely channels’ activity as sources, as sinks, and in total. Our proposed method can be used for both classification and exploratory analysis. In all scenarios, we find confirmation of the stablished right-lateralized Theta sampling network anomaly, in line with the assumption of the temporal sampling framework of oscillatory differences in the Theta and Gamma bands. Further, we show that this anomaly primarily occurs in the causal relationships of channels acting as sinks, where it is significantly more pronounced than when only total activity is observed. In the sink scenario, our classifier obtains 0.84 and 0.88 accuracy and 0.87 and 0.93 AUC for the Theta and Gamma bands, respectively

Simulador de dispositivos SLM basados en cristal líquido

En este trabajo, se presenta un simulador de modulación de fase espacial para su uso en comunicaciones ópticas de espacio libre. El simulador está basado en dispositivos TNLCD (Twisted Nematic Liquid Crystal Display). En primer lugar, se examinan las características y propiedades de los cristales líquidos como medios uniáxicos birrefrigentes. Posteriormente, mediante un modelo analítico simple, se caracterizan los diferentes elementos ópticos de un modulador espacial de luz (SLM) en términos de sus correspondientes matrices de Jones. Las expresiones deducidas en esta caracterización se utilizan en la herramienta de simulación para obtener la diferencia de fase espacial y la transmitancia producida por el SLM. Finalmente, el funcionamiento del simulador se ha verificado comparando resultados teóricos y de simulación para diferentes excitaciones de pruebaUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Performance study of a 3 x 1 x 1 m(3) dual phase liquid Argon Time Projection Chamber exposed to cosmic rays

This work would not have been possible without the support of the Swiss National Science Foundation, Switzerland; CEA and CNRS/IN2P3, France; KEK and the JSPS program, Japan; Ministerio de Ciencia e Innovacion in Spain under grants FPA2016-77347-C2, SEV-2016-0588 and MdM-2015-0509, Comunidad de Madrid, the CERCA program of the Generalitat de Catalunya and the fellowship (LCF/BQ/DI18/11660043) from "La Caixa" Foundation (ID 100010434); the Programme PNCDI III, CERN-RO, under Contract 2/2020, Romania; the U.S. Department of Energy under Grant No. DE-SC0011686. This project has received funding from the European Union's Horizon 2020 Research and Innovation program under Grant Agreement no. 654168. The authors are also grateful to the French government operated by the National Research Agency (ANR) for the LABEX Enigmass, LABEX Lyon Institute of Origins (ANR-10-LABX-0066) of the Universite de Lyon for its financial support within the program "Investissements d'Avenir" (ANR-11-IDEX-0007).We report the results of the analyses of the cosmic ray data collected with a 4 tonne (3x1x1 m(3)) active mass (volume) Liquid Argon Time-Projection Chamber (TPC) operated in a dual-phase mode. We present a detailed study of the TPC's response, its main detector parameters and performance. The results are important for the understanding and further developments of the dual-phase technology, thanks to the verification of key aspects, such as the extraction of electrons from liquid to gas and their amplification through the entire one square metre readout plain, gain stability, purity and charge sharing between readout views.Swiss National Science Foundation (SNSF)French Atomic Energy CommissionCentre National de la Recherche Scientifique (CNRS)High Energy Accelerator Research Organization (KEK)Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT)Japan Society for the Promotion of ScienceSpanish Government FPA2016-77347-C2 SEV-2016-0588MdM-2015-0509Comunidad de MadridCERCA program of the Generalitat de CatalunyaLa Caixa Foundation LCF/BQ/DI18/11660043 100010434Programme PNCDI III, RomaniaCERN-RO, Romania 2/2020United States Department of Energy (DOE) SC0011686European Commission 654168Universite de Lyon ANR-10-LABX-0066 ANR-11-IDEX-000

Long-baseline neutrino oscillation physics potential of the DUNE experiment

The sensitivity of the Deep Underground Neutrino Experiment (DUNE) to neutrino oscillation is determined, based on a full simulation, reconstruction, and event selection of the far detector and a full simulation and parameterized analysis of the near detector. Detailed uncertainties due to the flux prediction, neutrino interaction model, and detector effects are included. DUNE will resolve the neutrino mass ordering to a precision of 5σ, for all ΑCP values, after 2 years of running with the nominal detector design and beam configuration. It has the potential to observe charge-parity violation in the neutrino sector to a precision of 3σ (5σ) after an exposure of 5 (10) years, for 50% of all ΑCP values. It will also make precise measurements of other parameters governing long-baseline neutrino oscillation, and after an exposure of 15 years will achieve a similar sensitivity to sin22θ13 to current reactor experiments

First results on ProtoDUNE-SP liquid argon time projection chamber performance from a beam test at the CERN Neutrino Platform

The ProtoDUNE-SP detector is a single-phase liquid argon time projection chamber with an active volume of 7.2× 6.1× 7.0 m3. It is installed at the CERN Neutrino Platform in a specially-constructed beam that delivers charged pions, kaons, protons, muons and electrons with momenta in the range 0.3 GeV/c to 7 GeV/c. Beam line instrumentation provides accurate momentum measurements and particle identification. The ProtoDUNE-SP detector is a prototype for the first far detector module of the Deep Underground Neutrino Experiment, and it incorporates full-size components as designed for that module. This paper describes the beam line, the time projection chamber, the photon detectors, the cosmic-ray tagger, the signal processing and particle reconstruction. It presents the first results on ProtoDUNE-SP\u27s performance, including noise and gain measurements, dE/dx calibration for muons, protons, pions and electrons, drift electron lifetime measurements, and photon detector noise, signal sensitivity and time resolution measurements. The measured values meet or exceed the specifications for the DUNE far detector, in several cases by large margins. ProtoDUNE-SP\u27s successful operation starting in 2018 and its production of large samples of high-quality data demonstrate the effectiveness of the single-phase far detector design

Prospects for Beyond the Standard Model Physics Searches at the Deep Underground Neutrino Experiment

The Deep Underground Neutrino Experiment (DUNE) will be a powerful tool for a variety of physics topics. The high-intensity proton beams provide a large neutrino flux, sampled by a near detector system consisting of a combination of capable precision detectors, and by the massive far detector system located deep underground. This configuration sets up DUNE as a machine for discovery, as it enables opportunities not only to perform precision neutrino measurements that may uncover deviations from the present three-flavor mixing paradigm, but also to discover new particles and unveil new interactions and symmetries beyond those predicted in the Standard Model (SM). Of the many potential beyond the Standard Model (BSM) topics DUNE will probe, this paper presents a selection of studies quantifying DUNE's sensitivities to sterile neutrino mixing, heavy neutral leptons, non-standard interactions, CPT symmetry violation, Lorentz invariance violation, neutrino trident production, dark matter from both beam induced and cosmogenic sources, baryon number violation, and other new physics topics that complement those at high-energy colliders and significantly extend the present reach