427 research outputs found
Multidimensional Dynamic Analysis of Human Brain Connectivity
No full textThe human brain is one of the most complex system existing in nature. The emergence of cognitive and physiological phenomena is the outcome of a complex series of interactions that occur hierarchically. Hence, explaining cognition is not possible just by taking into account the single parts the brain is composed of, but a comprehensive view of the collective behaviours of its constituents and the interactions with its environment should be considered to study the global system behaviour. A network formulation simplifies the analysis of a complex system by providing mathematical tools able to capture different aspects of its organization in a compact manner. Graph theoretical methods have been extensively applied to many neuroimaging datasets in order to describe the topological properties of both functional and structural brain networks. Although these methods have become a gold standard for analysing the complex behaviour of the human brain, several important issues related to the identification of the networks, their temporal evolution and new complex metrics for their topological description need to be further explored in order to provide a general and comprehensive analysis framework. Indeed, the human brain is a highly flexible dynamic system: executing both complex and simple functions requires the ongoing reconfiguration of the connections among the general- and specific-domain subsystems. In this work, some methodological procedures are proposed to address the outlined issues. Firstly, a new synchronization-based metric is developed to assess the functional connectivity in human brain
through functional magnetic resonance imaging (fMRI). In details, the whole brain volume is partitioned into regions of interest (ROIs) and a phase-space framework is used to map pairs of signals of each region of interest, in their reconstructed phase space, i.e. a topological representation of their behaviour under all possible initial conditions. Cross recurrence plots (CRPs) are then employed to reduce the dimensionality of the phase space and compare the trajectories of the interacting systems. The synchronization metric is then extracted from the cross recurrence to assess the coupling behaviour of the time series. The proposed metric is a generalized synchronization measure that takes into account both the amplitude and phase coupling between pairs of fMRI series. It differs from the correlation measures used in the literature, as it seems to be more sensitive to nonlinear coupling phenomena between time series and it is more robust against the physiological noise. Then an extended multidimensional framework is presented to describe completely the functional interactions of couples of signals in the phase space. More specifically, a set of metrics is extracted from the CRP of each couple of signals to form a multilayer connectivity matrix in which each layer is related to a specific complex phenomenon occurring in phase space. Hence, machine-learning algorithms are used to identify markers of the dynamic states in brain activity to characterize pathological conditions in a clinical context. Finally, a new perspective to characterize node centrality in complex networks is discussed and some preliminary results of the application of a new resilience index are shown.
This metric quantifies the importance of the node in relation to its survival rate for progressive removal of links in the network and can be useful for identifying the most persistent nodes in a network
Topological measurements of DWI tractography for Alzheimer's disease detection
No full textNeurodegenerative diseases affect brain morphology and connectivity, making complex networks a suitable tool to investigate andmodel their effects. Because of its stereotyped pattern Alzheimer’s disease (AD) is a natural benchmark for the study of novelmethodologies. Several studies have investigated the network centrality and segregation changes induced by AD, especially with asingle subject approach. In this work, a holistic perspective based on the application of multiplex network concepts is introduced.We define and assess a diagnostic score to characterize the brain topology and measure the disease effects on a mixed cohort of 52normal controls (NC) and 47 AD patients, from Alzheimer’s Disease Neuroimaging Initiative (ADNI). The proposed topologicalscore allows an accurate NC-AD classification: the average area under the curve (AUC) is 95% and the 95% confidence interval is 92% – 99%. Besides, the combination of topological information and structural measures, such as the hippocampal volumes, wasalso investigated. Topology is able to capture the disease signature of AD and, as the methodology is general, it can find interestingapplications to enhance our insight into disease with more heterogeneous patterns
Explainable Deep Learning for Personalized Age Prediction with Brain Morphology
No full textPredicting brain age has become one of the most attractive challenges in computational neuroscience due to the role of the predicted age as an effective biomarker for different brain diseases and conditions. A great variety of machine learning (ML) approaches and deep learning (DL) techniques have been proposed to predict age from brain magnetic resonance imaging scans. If on one hand, DL models could improve performance and reduce model bias compared to other less complex ML methods, on the other hand, they are typically black boxes as do not provide an in-depth understanding of the underlying mechanisms. Explainable Artificial Intelligence (XAI) methods have been recently introduced to provide interpretable decisions of ML and DL algorithms both at local and global level. In this work, we present an explainable DL framework to predict the age of a healthy cohort of subjects from ABIDE I database by using the morphological features extracted from their MRI scans. We embed the two local XAI methods SHAP and LIME to explain the outcomes of the DL models, determine the contribution of each brain morphological descriptor to the final predicted age of each subject and investigate the reliability of the two methods. Our findings indicate that the SHAP method can provide more reliable explanations for the morphological aging mechanisms and be exploited to identify personalized age-related imaging biomarker. (c) Copyright (c) 2021 Lombardi, Diacono, Amoroso, Monaco, Tavares, Bellotti and Tangaro
Summary of Section “New Accelerators, Detectors, Calculus and New Technologies”
No full textDeployment and development of advanced technologies for accelerators, detectors, electronics and computing is inherent in everyday activity of all research projects and experiments funded by INFN. However, when a part of the
research work can be clearly identified as an R&D activity aimed at the development of a new technology or procedure for specific, or a more general, application it is
worthwhile to cut it off and manage it as an independent self-consistent experiment. For many of them it is also easy to find applications in other research discipline or industry. In this case it is important to verify the potentiality of the technology, customize it and improve it, in collaboration with the end user, for the specific
application
Direct analysis of molybdenum target generated x-ray spectra with a portable device
No full textIn routine applications, information about the photon flux of x-ray tubes is obtained from exposure measurements and cataloged spectra. This approach relies mainly on the assumption that the real spectrum is correctly approximated by the cataloged one, once the main characteristics of the tube such as voltage, target material, anode angle, and filters are taken account of. In practice, all this information is not always available. Moreover, x-ray tubes with the same characteristics may have different spectra. We describe an apparatus that should be useful for quality control in hospitals and for characterizing new radiographic systems. The apparatus analyzes the spectrum generated by an x-ray mammographic unit. It is based on a commercial CZT produced by AMPTEK Inc. and a set of tungsten collimator disks. The electronics of the CZT are modified so as to obtain a faster response. The signal is digitized using an analog to digital converter with a sampling frequency of up to 20 MHz. The whole signal produced by the x-ray tube is acquired and analyzed off-line in order to accurately recognize pile-up events and reconstruct the emitted spectrum. The energy resolution has been determined using a calibrated x-ray source. Spectra were validated by comparison of the HVL measured using an ionization chambe
Phase retrieval for X-ray in-line phase contrast imaging
No full textA review article about phase retrieval problem in X-ray phase contrast imaging is presented. A simple theoretical framework of Fresnel diffraction imaging by X-rays is introduced. A review of the most important methods for phase
retrieval in free-propagation–based X-ray imaging and a new method developed by our collaboration are shown. The proposed algorithm, Combined Mixed Approach (CMA) is based on a mixed transfer function and transport of intensity approach, and it requires at most an initial approximate estimate of the average phase shift introduced by the object as prior knowledge. The accuracy with which this initial estimate is known determines the convergence speed of the algorithm. The new proposed algorithm is based on the retrieval of both the object phase and its complex
conjugate. The results obtained by the algorithm on simulated data have shown that the obtained reconstructed phase maps are characterized by particularly low normalized mean square errors. The algorithm was also tested on noisy experimental phase contrast data, showing a good efficiency in recovering phase information and enhancing the visibility of details inside soft tissues
Complex network modelling of origin–destination commuting flows for the COVID-19 epidemic spread analysis in Italian Lombardy Region
No full textCurrently the whole world is affected by the COVID-19 disease. Italy was the first country to be seriously affected in Europe, where the first COVID-19 outbreak was localized in the Lombardy region. The further spreading of the cases led to the lockdown of the most affected regions in northern Italy and then the entire country. In this work we investigated an epidemic spread scenario in the Lombardy region by using the origin–destination matrix with information about the commuting flows among 1450 urban areas within the region. We performed a large-scale simulation-based modeling of the epidemic spread over the networks related to three main motivations, i.e., work, study and occasional transfers to quantify the potential contribution of each category of travellers to the spread of the epidemic process. Our findings outline that the three networks are characterised by different weight dynamic growth rates and that the network “work” has a critical role in the diffusion phenomenon showing the greatest contribution to the epidemic spread
Direct analysis of molybdenum target generated x-ray spectra with a portable device
No full textIn routine applications, information about the photon flux of x-ray tubes is obtained from exposure measurements and cataloged spectra. This approach relies mainly on the assumption that the real spectrum is correctly approximated by the cataloged one, once the main characteristics of the tube such as voltage, target material, anode angle, and filters are taken account of. In practice, all this information is not always available. Moreover, x-ray tubes with the same characteristics may have different spectra. We describe an apparatus that should be useful for quality control in hospitals and for characterizing new radiographic systems. The apparatus analyzes the spectrum generated by an x-ray mammographic unit. It is based on a commercial CZT produced by AMPTEK Inc. and a set of tungsten collimator disks. The electronics of the CZT are modified so as to obtain a faster response. The signal is digitized using an analog to digital converter with a sampling frequency of up to 20 MHz. The whole signal produced by the x-ray tube is acquired and analyzed off-line in order to accurately recognize pile-up events and reconstruct the emitted spectrum. The energy resolution has been determined using a calibrated x-ray source. Spectra were validated by comparison of the HVL measured using an ionization chamber
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