124 results on '"Enrico Amico"'
Search Results
2. The arrow‐of‐time in neuroimaging time series identifies causal triggers of brain function
- Author
-
Thomas A. W. Bolton, Dimitri Van De Ville, Enrico Amico, Maria G. Preti, and Raphaël Liégeois
- Subjects
Neurology ,Radiological and Ultrasound Technology ,Radiology, Nuclear Medicine and imaging ,Neurology (clinical) ,Anatomy - Published
- 2023
- Full Text
- View/download PDF
3. Connectome embedding in multidimensional graph-invariant spaces
- Author
-
Mathieu Mach, Enrico Amico, Raphaël Liégeois, Maria Giulia Preti, Alessandra Griffa, Dimitri Van De Ville, and Mangor Pedersen
- Abstract
The topological organization of brain networks, or connectomes, can be quantified using graph theory. Here, we investigated brain networks in higher dimensional spaces defined by up to ten node-level graph theoretical invariants. Nodal invariants are intrinsic nodal properties which reflect the topological characteristics of the nodes with respect to the whole network, including segregation (e.g., clustering coefficient) and centrality (e.g., betweenness centrality) measures. Using 100 healthy unrelated subjects from the Human Connectome Project, we generated multiple types of connectomes (structural/functional networks and binary/weighted networks) and embedded the corresponding network nodes (brain regions) into multidimensional graph spaces defined by the invariants. First, we observed that nodal invariants are correlated between them (i.e., they carry similar network information) at a whole-brain and subnetwork level. Second, we conducted a machine learning analysis to test whether brain regions embedded in multidimensional graph spaces can be accurately classified into higher order (association, subcortical and cerebellar) and lower order (visual, somatomotor, attention) areas. Brain regions of higher order and lower order brain circuits were classified with an 80-87% accuracy in a 10-dimensional (10D) space. 10D graph metrics performed better than 2D and 3D graph metrics, and non-linear Gaussian kernels performed better than linear kernels. This suggests a non-linear brain network information gain in a high-dimensional graph space. Finally, we quantified the inter-subject Euclidean distance of each brain region embedded in the multidimensional graph space. The inter-individual distance was largest for regions of the default mode and frontoparietal networks, providing a new avenue for subject-specific network coordinates in a multidimensional space. To conclude, we propose a new framework for quantifying connectome features in multidimensional spaces defined by graph invariants, providing a new avenue for subject-specific network coordinates and inter-individual distance analyses.
- Published
- 2023
- Full Text
- View/download PDF
4. The unique neural signature of your trip: Functional connectome fingerprints of subjective psilocybin experience
- Author
-
Hanna M. Tolle, Juan Carlos Farah, Pablo Mallaroni, Natasha L. Mason, Johannes G. Ramaekers, and Enrico Amico
- Abstract
The emerging neuroscientific frontier of brain fingerprinting has recently established that human functional connectomes (FCs) exhibit ‘fingerprint-like’ idiosyncratic features, which map onto heterogeneously distributed behavioural traits. Here we harness brain-fingerprinting tools to extract FC features that predict subjective drug experience induced by the psychedelic psilocybin. Specifically, in neuroimaging data of healthy volunteers under the acute influence of psilocybin or a placebo, we show that, post-psilocybin administration, FCs become more idiosyncratic due to greater inter-subject dissimilarity. Moreover, whereas in placebo subjects idiosyncratic features are primarily found in the frontoparietal network, in psilocybin subjects they concentrate in the default-mode network (DMN). Crucially, isolating the latter revealed an FC pattern that predicts subjective psilocybin experience and is characterised by reduced within-DMN and DMN-limbic connectivity, as well as increased connectivity between the DMN and attentional systems. Overall, these results contribute to bridging the gap between psilocybin-mediated effects on brain and behaviour, while demonstrating the value of a brain-fingerprinting approach to pharmacological neuroimaging.
- Published
- 2023
- Full Text
- View/download PDF
5. Brain fingerprinting using EEG graph inference
- Author
-
Maliheh Miri, Vahid Abootalebi, Enrico Amico, Hamid Saeedi-Sourck, Dimitri Van De Ville, and Hamid Behjat
- Abstract
Taking advantage of the human brain functional connectome as an individual’s fingerprint has attracted great research in recent years. Conventionally, Pearson correlation between regional time-courses is used as a pairwise measure for each edge weight of the connectome. Building upon recent advances in graph signal processing, we propose here to estimate the graph structure as a whole by considering all time-courses at once. Using data from two publicly available datasets, we show the superior performance of such learned brain graphs over correlation-based functional connectomes in characterizing an individual.
- Published
- 2023
- Full Text
- View/download PDF
6. Publisher Correction: Higher-order organization of multivariate time series
- Author
-
Andrea Santoro, Federico Battiston, Giovanni Petri, and Enrico Amico
- Subjects
General Physics and Astronomy - Published
- 2023
- Full Text
- View/download PDF
7. Textbook Outcome of Laparoscopic Microwave Ablation for Hepatocellular Carcinoma
- Author
-
Jacopo Lanari, Silvia Caregari, Ilaria Billato, Enrico Gringeri, Francesco D’Amico, Giancarlo Gemo, Domenico Bassi, Francesco Enrico D’Amico, Riccardo Boetto, Alessandra Bertacco, Andrea Marchini, Sara Lazzari, Marco Brolese, Mattia Ballo, Alessandro Vitale, and Umberto Cillo
- Subjects
Cancer Research ,Oncology ,hepatocellular carcinoma ,laparoscopic ,microwave ablation ,textbook outcome - Abstract
In the context of spreading interest in textbook outcome (TO) evaluation in different fields, we aimed to investigate an uncharted procedure, that is, laparoscopic microwave ablation (MWA) for hepatocellular carcinoma (HCC). Absence of post-MWA complications, a hospital stay of three days, no mortality nor readmission within 30 days, and complete response of the target lesion at post-MWA CT scan defined TO achievement. Patients treated between January 2014 and March 2021 were retrospectively reviewed, and of the 521 patients eligible for the study, 337 (64.7%) fulfilled all the quality indicators to achieve the TO. The absence of complications was the main limiting factor for accomplishing TO. At multivariable analysis, Child–Pugh B cirrhosis, age of more than 70 years old, three nodules, and MELD score ≥ 15 were associated with decreased probabilities of TO achievement. A score based on these factors was derived from multivariable analysis, and patients were divided into three risk groups for TO achievement. At survival analysis, overall survival (OS) was significantly (p = 0.001) higher in patients who achieved TO than those who did not. Moreover, OS evaluation in the three risk groups showed a trend coherent with TO achievement probability. The present study, having assessed the first TO for laparoscopic MWA for HCC, encourages further broader consensus on its definition and, on its basis, on the development of clinically relevant tools for managing treatment allocation.
- Published
- 2023
- Full Text
- View/download PDF
8. Higher-order organization of multivariate time series
- Author
-
Andrea Santoro, Federico Battiston, Giovanni Petri, and Enrico Amico
- Subjects
topology ,architecture ,networks ,General Physics and Astronomy ,dynamics ,complex - Abstract
Time series analysis has proven to be a powerful method to characterize several phenomena in biology, neuroscience and economics, and to understand some of their underlying dynamical features. Despite a plethora of methods have been proposed for the analysis of multivariate time series, most of them neglect the effect of non-pairwise interactions on the emerging dynamics. Here, we propose a novel framework to characterize the temporal evolution of higher-order dependencies within multivariate time series. Using network analysis and topology, we show that, unlike traditional tools based on pairwise statistics, our framework robustly differentiates various spatiotemporal regimes of coupled chaotic maps, including chaotic dynamical phases and various types of synchronization. Hence, using the higher-order co-fluctation patterns in simulated dynamical processes as a guide, we highlight and quantify signatures of higher-order patterns in data from brain functional activity, financial markets, and epidemics. Overall, our approach sheds new light on the higher-order organization of multivariate time series, allowing a better characterization of dynamical group dependencies inherent to real-world data
- Published
- 2023
- Full Text
- View/download PDF
9. Ritualistic use of ayahuasca enhances a shared functional connectome identity with others
- Author
-
Pablo Mallaroni, Natasha L. Mason, Lilian Kloft, Johannes T. Reckweg, Kim van Oorsouw, Stefan W. Toennes, Hanna M. Tolle, Enrico Amico, and Johannes G. Ramaekers
- Abstract
The knowledge that brain functional connectomes are both unique and reliable has enabled behaviourally relevant inferences at a subject level. However, it is unknown whether such “fingerprints” persist under altered states of consciousness. Ayahuasca is a potent serotonergic psychedelic which elicits a widespread dysregulation of functional connectivity. Used communally in religious ceremonies, its shared use may highlight relevant novel interactions between mental state and FC inherency. Using 7T fMRI, we assessed resting-state static and dynamic FCs for 21 Santo Daime members after collective ayahuasca intake in an acute, within-subject study. Here, connectome fingerprinting revealed a shared functional space, accompanied by a spatiotemporal reallocation of keypoint edges. Importantly, we show that interindividual differences in higher-order FCs motifs are relevant to experiential phenotypes, given that they can predict perceptual drug effects. Collectively, our findings offer an example as to how individualised connectivity markers can be used to trace a subject’s functional connectome across altered states of consciousness.
- Published
- 2022
- Full Text
- View/download PDF
10. Percutaneous and Laparoscopic-Assisted Ablation of Hepatocellular Carcinoma
- Author
-
Umberto Cillo, Jacopo Lanari, Maria Masutti, Francesco Enrico D’Amico, Alessandro Vitale, and Enrico Gringeri
- Published
- 2022
- Full Text
- View/download PDF
11. The kinectome: a comprehensive kinematic map of human motion in health and disease
- Author
-
Anna Carotenuto, Marianna Liparoti, Giuseppe Sorrentino, Roberta Minino, Emahnuel Troisi Lopez, Pierpaolo Sorrentino, Enrico Amico, Università degli Studi di Napoli 'Parthenope' = University of Naples (PARTHENOPE), Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), High Speciality Hospital A. Cardarelli, Université de Genève = University of Geneva (UNIGE), and RAMOS, Giovanna
- Subjects
Movement (music) ,business.industry ,Computer science ,[SCCO.NEUR]Cognitive science/Neuroscience ,Fingerprint (computing) ,[SCCO.NEUR] Cognitive science/Neuroscience ,Pattern recognition ,Kinematics ,Variance (accounting) ,Human body ,Network dynamics ,Gait (human) ,[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] ,Artificial intelligence ,[SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] ,Set (psychology) ,business - Abstract
Effective human movement requires the coordinated participation of the whole musculoskeletal system. Here we propose to represent the human body movements as a network (that we named “kinectome”), where nodes are body parts, and edges are defined as the correlations of the accelerations between each pair of body parts during gait. We apply this framework in healthy individuals and patients with Parkinson’s disease (PD). The network dynamics in Parkinson’s display high variability, as conveyed by the high variance and the modular structure in the patients’ kinectomes. Furthermore, our analysis identified a set of anatomical elements that are specifically related to the balance impairment in PD. Furthermore, each participant could be identified based on its kinectome patterns, akin to a “fingerprint” of movement, confirming that our approach captures relevant features of gait. We hope that applying network approaches to human kinematics yields new insights to characterize human movement.
- Published
- 2022
12. On the Spatial Distribution of Temporal Complexity in Resting State and Task Functional MRI
- Author
-
Amir Omidvarnia, Raphaël Liégeois, Enrico Amico, Maria Giulia Preti, Andrew Zalesky, and Dimitri Van De Ville
- Subjects
variability ,task engagement ,time-series ,fmri ,temporal complexity ,General Physics and Astronomy ,multiscale entropy ,integration ,dynamics ,connectivity ,frequency ,entropy analysis ,functional mri ,task specificity ,ddc:510 ,graph signal processing ,resting state ,signal ,functional MRI ,Hurst exponent ,hurst exponent ,scale-free - Abstract
Measuring the temporal complexity of functional MRI (fMRI) time series is one approach to assess how brain activity changes over time. In fact, hemodynamic response of the brain is known to exhibit critical behaviour at the edge between order and disorder. In this study, we aimed to revisit the spatial distribution of temporal complexity in resting state and task fMRI of 100 unrelated subjects from the Human Connectome Project (HCP). First, we compared two common choices of complexity measures, i.e., Hurst exponent and multiscale entropy, and observed a high spatial similarity between them. Second, we considered four tasks in the HCP dataset (Language, Motor, Social, and Working Memory) and found high task-specific complexity, even when the task design was regressed out. For the significance thresholding of brain complexity maps, we used a statistical framework based on graph signal processing that incorporates the structural connectome to develop the null distributions of fMRI complexity. The results suggest that the frontoparietal, dorsal attention, visual, and default mode networks represent stronger complex behaviour than the rest of the brain, irrespective of the task engagement. In sum, the findings support the hypothesis of fMRI temporal complexity as a marker of cognition.
- Published
- 2022
- Full Text
- View/download PDF
13. Optimizing differential identifiability improves connectome predictive modeling of cognitive deficits from functional connectivity in Alzheimer's disease
- Author
-
David G. Clark, Charanya Muralidharan, John D. West, Enrico Amico, Andrew J. Saykin, Mario Dzemidzic, Diana O. Svaldi, Joaquín Goñi, Liana G. Apostolova, Shannon L. Risacher, and Kausar Abbas
- Subjects
cognition ,Male ,Computer science ,Disease ,050105 experimental psychology ,Functional networks ,03 medical and health sciences ,0302 clinical medicine ,Alzheimer Disease ,Connectome ,Humans ,0501 psychology and cognitive sciences ,Radiology, Nuclear Medicine and imaging ,Generalizability theory ,Cognitive Dysfunction ,resting state ,Research Articles ,Aged ,Aged, 80 and over ,Radiological and Ultrasound Technology ,Resting state fMRI ,Functional connectivity ,05 social sciences ,fMRI ,functional connectivity ,functional fingerprinting ,Cognition ,AD ,Alzheimer's disease ,Magnetic Resonance Imaging ,Neurology ,Identifiability ,Female ,Neurology (clinical) ,Anatomy ,Nerve Net ,Neuroscience ,predictive modeling ,030217 neurology & neurosurgery ,Research Article - Abstract
Functional connectivity, as estimated using resting state functional MRI, has shown potential in bridging the gap between pathophysiology and cognition. However, clinical use of functional connectivity biomarkers is impeded by unreliable estimates of individual functional connectomes and lack of generalizability of models predicting cognitive outcomes from connectivity. To address these issues, we combine the frameworks of connectome predictive modeling and differential identifiability. Using the combined framework, we show that enhancing the individual fingerprint of resting state functional connectomes leads to robust identification of functional networks associated to cognitive outcomes and also improves prediction of cognitive outcomes from functional connectomes. Using a comprehensive spectrum of cognitive outcomes associated to Alzheimer's disease (AD), we identify and characterize functional networks associated to specific cognitive deficits exhibited in AD. This combined framework is an important step in making individual level predictions of cognition from resting state functional connectomes and in understanding the relationship between cognition and connectivity., Using differential identifiability and connectome predictive modeling, we show that enhancing the individual fingerprint of resting state functional connectomes leads to robust identification of functional networks associated to cognitive outcomes and also improves prediction of cognitive outcomes from functional connectomes. The framework allows us to more robustly identify and characterize functional networks associated to specific cognitive outcomes exhibited in AD.
- Published
- 2021
14. A morphospace of functional configuration to assess configural breadth based on brain functional networks
- Author
-
Mario Ventresca, Joaquín Goñi, Duy Anh Duong-Tran, Mario Dzemidzic, Enrico Amico, Kausar Abbas, David A. Kareken, and Bernat Corominas-Murtra
- Subjects
Elementary cognitive task ,Theoretical computer science ,Computer science ,Functional configural breadth ,Functional reconfiguration ,Neurosciences. Biological psychiatry. Neuropsychiatry ,Task (project management) ,Artificial Intelligence ,Methods ,Entropy (information theory) ,Set (psychology) ,Episodic memory ,fluid ,Functional connectomes ,Applied Mathematics ,General Neuroscience ,Control reconfiguration ,Cognition ,intelligence ,Computer Science Applications ,optimality ,Quantitative Biology - Neurons and Cognition ,connectivity ,FOS: Biological sciences ,frontoparietal ,Neurons and Cognition (q-bio.NC) ,Granularity ,Resting-state networks ,RC321-571 - Abstract
Author Summary Understanding and measuring the ways in which human brain connectivity changes to accommodate a broad range of cognitive and behavioral goals is an important undertaking. We put forth a mesoscopic framework that captures such changes by tracking the topology and integration of information within and between functional networks (FNs) of the brain. Canonically, when FNs are characterized, they are separated from the rest of the brain network. The two metrics proposed in this work, trapping efficiency and exit entropy, quantify the topological and information integration characteristics of FNs while they are still embedded in the overall brain network. Trapping efficiency measures the module's ability to preserve an incoming signal from escaping its local topology, relative to its total exiting weights. Exit entropy measures the module's communication preferences with other modules/networks using information theory. When these two metrics are plotted in a 2D graph as a function of different brain states (i.e., cognitive/behavioral tasks), the resulting morphospace characterizes the extent of network reconfiguration between tasks (functional reconfiguration), and the change when moving from rest to an externally engaged "task-positive" state (functional preconfiguration), to collectively define network configural breadth. We also show that these metrics are sensitive to subject, task, and functional network identities. Overall, this method is a promising approach to quantify how human brains adapt to a range of tasks, and potentially to help improve precision clinical neuroscience., The quantification of human brain functional (re)configurations across varying cognitive demands remains an unresolved topic. We propose that such functional configurations may be categorized into three different types: (a) network configural breadth, (b) task-to task transitional reconfiguration, and (c) within-task reconfiguration. Such functional reconfigurations are rather subtle at the whole-brain level. Hence, we propose a mesoscopic framework focused on functional networks (FNs) or communities to quantify functional (re)configurations. To do so, we introduce a 2D network morphospace that relies on two novel mesoscopic metrics, trapping efficiency (TE) and exit entropy (EE), which capture topology and integration of information within and between a reference set of FNs. We use this framework to quantify the network configural breadth across different tasks. We show that the metrics defining this morphospace can differentiate FNs, cognitive tasks, and subjects. We also show that network configural breadth significantly predicts behavioral measures, such as episodic memory, verbal episodic memory, fluid intelligence, and general intelligence. In essence, we put forth a framework to explore the cognitive space in a comprehensive manner, for each individual separately, and at different levels of granularity. This tool that can also quantify the FN reconfigurations that result from the brain switching between mental states.
- Published
- 2021
15. The evolution of information transmission in mammalian brain networks
- Author
-
Alessandra Griffa, Mathieu Mach, Julien Dedelley, Daniel Gutierrez-Barragan, Alessandro Gozzi, Gilles Allali, Joanes Grandjean, Dimitri Van De Ville, and Enrico Amico
- Abstract
Brain communication, defined as information transmission through white-matter connections, is at the foundation of the brain’s computational capacities that virtually subtend all aspects of behavior: from sensory perception shared across mammalian species, to complex cognitive functions in humans. How did communication strategies in macroscale brain networks adapted across evolution to accomplish increasingly complex functions? By applying a novel approach to measure information transmission in mouse, macaque and human brains, we found an evolutionary gradient from selective information processing, where brain regions share information through single polysynaptic pathways, to parallel information processing, where regions communicate through multiple parallel pathways. In humans, parallel processing acts as a major connector between unimodal and transmodal systems. Communication strategies are unique to individuals across different mammalian species, pointing at the individual-level specificity of information routing architecture. Our work provides compelling evidence that different communication strategies are tied to the evolutionary complexity of mammalian brain networks.
- Published
- 2022
- Full Text
- View/download PDF
16. Uncovering differential identifiability in network properties of human brain functional connectomes
- Author
-
Joaquín Goñi, Enrico Amico, Kausar Abbas, Meenusree Rajapandian, and Mario Ventresca
- Subjects
Brain connectomics ,Computer science ,Reliability (computer networking) ,Network science ,Fingerprint ,Neurosciences. Biological psychiatry. Neuropsychiatry ,Subject identifiability ,Machine learning ,computer.software_genre ,Functional connectivity ,03 medical and health sciences ,0302 clinical medicine ,Artificial Intelligence ,Robustness (computer science) ,Sensitivity (control systems) ,Differential (infinitesimal) ,Research Articles ,030304 developmental biology ,0303 health sciences ,business.industry ,Applied Mathematics ,General Neuroscience ,Computer Science Applications ,Variety (cybernetics) ,FOS: Biological sciences ,Quantitative Biology - Neurons and Cognition ,Connectome ,Identifiability ,Neurons and Cognition (q-bio.NC) ,Artificial intelligence ,business ,computer ,030217 neurology & neurosurgery ,RC321-571 - Abstract
The identifiability framework (𝕀f) has been shown to improve differential identifiability (reliability across-sessions and -sites, and differentiability across-subjects) of functional connectomes for a variety of fMRI tasks. But having a robust single session/subject functional connectome is just the starting point to subsequently assess network properties for characterizing properties of integration, segregation, and communicability, among others. Naturally, one wonders whether uncovering identifiability at the connectome level also uncovers identifiability on the derived network properties. This also raises the question of where to apply the 𝕀f framework: on the connectivity data or directly on each network measurement? Our work answers these questions by exploring the differential identifiability profiles of network measures when 𝕀f is applied (a) on the functional connectomes, and (b) directly on derived network measurements. Results show that improving across-session reliability of functional connectomes (FCs) also improves reliability of derived network measures. We also find that, for specific network properties, application of 𝕀f directly on network properties is more effective. Finally, we discover that applying the framework, either way, increases task sensitivity of network properties. At a time when the neuroscientific community is focused on subject-level inferences, this framework is able to uncover FC fingerprints, which propagate to derived network properties., Author Summary Functional connectome (FC) fingerprinting recently became a topic of great interest in network neuroscience. We recently proposed a framework to improve brain fingerprint (i.e., identifiability) of FCs, which improves not only test-retest reliability but also the correlation of FCs with fluid intelligence. However, does this improvement in FC fingerprints propagate to the derived network measures? In this work we found that improving the fingerprint (differential identifiability) of the functional connectome also improves the “fingerprint” of its network properties. Furthermore, when using the identifiability framework on the network properties directly, certain network properties like search information and communicability add to the FC fingerprint. Finally, we show that enhancement of the fingerprint in the network measures, in a wide range of cognitive tasks, using the identifiability framework also improves task sensitivity in these measures. We show that regardless of whether you are using functional connectomes or the network properties derived from them, using the 𝕀f framework on the functional connectomes would be a beneficial first step.
- Published
- 2020
17. Characterization of gravity waves in the lower ionosphere using very low frequency observations at Comandante Ferraz Brazilian Antarctic Station
- Author
-
José Valentin Bageston, Dino Enrico D'Amico, Luis T.M. Raunheitte, and Emilia Correia
- Subjects
Atmospheric Science ,Daytime ,010504 meteorology & atmospheric sciences ,01 natural sciences ,0103 physical sciences ,Earth and Planetary Sciences (miscellaneous) ,Gravity wave ,Very low frequency ,lcsh:Science ,010303 astronomy & astrophysics ,0105 earth and related environmental sciences ,Gravitational wave ,lcsh:QC801-809 ,Airglow ,Geology ,Astronomy and Astrophysics ,Geodesy ,lcsh:QC1-999 ,lcsh:Geophysics. Cosmic physics ,Amplitude ,Space and Planetary Science ,Reflection (physics) ,lcsh:Q ,Ionosphere ,lcsh:Physics - Abstract
The goal of this work is to investigate the gravity wave (GW) characteristics in the low ionosphere using very low frequency (VLF) radio signals. The spatial modulations produced by the GWs affect the conditions of the electron density at reflection height of the VLF signals, which produce fluctuations of the electrical conductivity in the D region that can be detected as variations in the amplitude and phase of VLF narrowband signals. The analysis considered the VLF signal transmitted from the US Cutler, Maine (NAA) station that was received at Comandante Ferraz Brazilian Antarctic Station (EACF, 62.1∘ S, 58.4∘ W), with its great circle path crossing the Drake Passage longitudinally. The wave periods of the GWs detected in the low ionosphere are obtained using the wavelet analysis applied to the VLF amplitude. Here the VLF technique was used as a new aspect for monitoring GW activity. It was validated comparing the wave period and duration properties of one GW event observed simultaneously with a co-located airglow all-sky imager both operating at EACF. The statistical analysis of the seasonal variation of the wave periods detected using VLF technique for 2007 showed that the GW events occurred all observed days, with the waves with a period between 5 and 10 min dominating during night hours from May to September, while during daytime hours the waves with a period between 0 and 5 min are predominant the whole year and dominate all days from November to April. These results show that VLF technique is a powerful tool to obtain the wave period and duration of GW events in the low ionosphere, with the advantage of being independent of sky conditions, and it can be used during the whole day and year-round.
- Published
- 2020
- Full Text
- View/download PDF
18. The progressive loss of brain network fingerprints in Amyotrophic Lateral Sclerosis predicts clinical impairment
- Author
-
Antonella Romano, Emahnuel Trosi Lopez, Marianna Liparoti, Arianna Polverino, Roberta Minino, Francesca Trojsi, Simona Bonavita, Laura Mandolesi, Carmine Granata, Enrico Amico, Giuseppe Sorrentino, Pierpaolo Sorrentino, Università degli Studi di Napoli 'Parthenope' = University of Naples (PARTHENOPE), Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome] (UNIROMA), Istituto di Scienze Applicate e Sistemi Intelligenti 'Eduardo Caianiello' (ISASI), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Università degli studi della Campania 'Luigi Vanvitelli' = University of the Study of Campania Luigi Vanvitelli, University of Naples Federico II = Università degli studi di Napoli Federico II, Ecole Polytechnique Fédérale de Lausanne (EPFL), Université de Genève = University of Geneva (UNIGE), Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Consiglio Nazionale delle Ricerche (CNR), RAMOS, Giovanna, Romano, Antonella, Trosi Lopez, Emahnuel, Liparoti, Marianna, Polverino, Arianna, Minino, Roberta, Trojsi, Francesca, Bonavita, Simona, Mandolesi, Laura, Granata, Carmine, Amico, Enrico, Sorrentino, Giuseppe, and Sorrentino, Pierpaolo
- Subjects
Male ,Brain network identifiability ,Clinical connectome fingerprintFunctional connectomeBrain network identifiabilityNeurodegenerative diseasesMotor neurons diseaseMagnetoencephalography, Phase Linearity Measurement ,Cognitive Neuroscience ,disease progression ,Clinical connectome fingerprint ,Magnetoencephalography, Phase Linearity Measurement ,Connectome ,Humans ,Radiology, Nuclear Medicine and imaging ,patterns ,[SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] ,Clinical connectome fingerprintFunctional connectomeBrain network identifiabilityNeurodegenerative diseasesMotor neurons diseaseMagnetoencephalography ,dysfunction ,Motor neurons disease ,behavior ,Amyotrophic Lateral Sclerosis ,functional connectivity ,Neurodegenerative diseases ,Brain ,Magnetoencephalography ,phase linearity ,Functional connectome ,Phase Linearity Measurement ,Neurology ,Female ,[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC] ,Neurology (clinical) ,measurement - Abstract
International audience; Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease characterised by functional connectivity alterations in both motor and extra-motor brain regions. Within the framework of network analysis, fingerprinting represents a reliable approach to assess subject-specific connectivity features within a given population (healthy or diseased). Here, we applied the Clinical Connectome Fingerprint (CCF) analysis to source-reconstructed magnetoencephalography (MEG) signals in a cohort of seventy-eight subjects: thirty-nine ALS patients and thirty-nine healthy controls. We set out to develop an identifiability matrix to assess the extent to which each patient was recognisable based on his/her connectome, as compared to healthy controls. The analysis was performed in the five canonical frequency bands. Then, we built a multilinear regression model to test the ability of the "clinical fingerprint" to predict the clinical evolution of the disease, as assessed by the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-r), the King's disease staging system, and the Milano-Torino Staging (MiToS) disease staging system. We found a drop in the identifiability of patients in the alpha band compared to the healthy controls. Furthermore, the "clinical fingerprint" was predictive of the ALSFRS-r (p = 0.0397; β = 32.8), the King's (p = 0.0001; β = − 7.40), and the MiToS (p = 0.0025; β = − 4.9) scores. Accordingly, it negatively correlated with the King's (Spearman's rho =-0.6041, p = 0.0003) and MiToS scales (Spearman's rho = − 0.4953, p = 0.0040). Our results demonstrated the ability of the CCF approach to predict the individual motor impairment in patients affected by ALS. Given the subject-specificity of our approach, we hope to further exploit it to improve disease management.
- Published
- 2022
- Full Text
- View/download PDF
19. Fading of brain network fingerprint in Parkinson's disease predicts motor clinical impairment
- Author
-
Emahnuel Troisi Lopez, Roberta Minino, Marianna Liparoti, Arianna Polverino, Antonella Romano, Rosa De Micco, Fabio Lucidi, Alessandro Tessitore, Enrico Amico, Giuseppe Sorrentino, Viktor Jirsa, Pierpaolo Sorrentino, Troisi Lopez, Emahnuel, Minino, Roberta, Liparoti, Marianna, Polverino, Arianna, Romano, Antonella, De Micco, Rosa, Lucidi, Fabio, Tessitore, Alessandro, Amico, Enrico, Sorrentino, Giuseppe, Jirsa, Viktor, and Sorrentino, Pierpaolo
- Subjects
magnetoencephalography ,Radiological and Ultrasound Technology ,brain network ,Parkinson's disease ,functional connectivity ,clinical connectome fingerprint ,brain fingerprint ,motor impairment ,neurodegenerative disease ,Neurology ,mds-updrs ,Radiology, Nuclear Medicine and imaging ,progression ,Neurology (clinical) ,movement ,Anatomy ,synchronization ,time - Abstract
The clinical connectome fingerprint (CCF) was recently introduced as a way to assess brain dynamics. It is an approach able to recognize individuals, based on the brain network. It showed its applicability providing network features used to predict the cognitive decline in preclinical Alzheimer's disease. In this article, we explore the performance of CCF in 47 Parkinson's disease (PD) patients and 47 healthy controls, under the hypothesis that patients would show reduced identifiability as compared to controls, and that such reduction could be used to predict motor impairment. We used source-reconstructed magnetoencephalography signals to build two functional connectomes for 47 patients with PD and 47 healthy controls. Then, exploiting the two connectomes per individual, we investigated the identifiability characteristics of each subject in each group. We observed reduced identifiability in patients compared to healthy individuals in the beta band. Furthermore, we found that the reduction in identifiability was proportional to the motor impairment, assessed through the Unified Parkinson's Disease Rating Scale, and, interestingly, able to predict it (at the subject level), through a cross-validated regression model. Along with previous evidence, this article shows that CCF captures disrupted dynamics in neurodegenerative diseases and is particularly effective in predicting motor clinical impairment in PD.
- Published
- 2022
20. The kinectome: A comprehensive kinematic map of human motion in health and disease
- Author
-
Emahnuel Troisi Lopez, Pierpaolo Sorrentino, Marianna Liparoti, Roberta Minino, Arianna Polverino, Antonella Romano, Anna Carotenuto, Enrico Amico, and Giuseppe Sorrentino
- Subjects
impairment ,people ,variability ,General Neuroscience ,Movement ,gait analysis, movement pattern, network, Parkinson’s disease ,Acceleration ,movement pattern ,Parkinson Disease ,stability ,trunk ,General Biochemistry, Genetics and Molecular Biology ,Biomechanical Phenomena ,walking ,History and Philosophy of Science ,parkinson's disease ,gait analysis ,network ,Parkinson’s disease ,Humans ,parkinsons-disease ,progression ,Gait ,asymmetry - Abstract
Human voluntary movement stems from the coordinated activations in space and time of many musculoskeletal segments. However, the current methodological approaches to study human movement are still limited to the evaluation of the synergies among a few body elements. Network science can be a useful approach to describe movement as a whole and to extract features that are relevant to understanding both its complex physiology and the pathophysiology of movement disorders. Here, we propose to represent human movement as a network (that we named the kinectome), where nodes represent body points, and edges are defined as the correlations of the accelerations between each pair of them. We applied this framework to healthy individuals and patients with Parkinson's disease, observing that the patients' kinectomes display less symmetrical patterns as compared to healthy controls. Furthermore, we used the kinectomes to successfully identify both healthy and diseased subjects using short gait recordings. Finally, we highlighted topological features that predict the individual clinical impairment in patients. Our results define a novel approach to study human movement. While deceptively simple, this approach is well-grounded, and represents a powerful tool that may be applied to a wide spectrum of frameworks.
- Published
- 2022
21. Impact of Positive Radial Margin on Recurrence and Survival in Perihilar Cholangiocarcinoma
- Author
-
Francesco Enrico D’Amico, Claudia Mescoli, Silvia Caregari, Alessio Pasquale, Ilaria Billato, Remo Alessandris, Jacopo Lanari, Domenico Bassi, Riccardo Boetto, Francesco D’Amico, Alessandro Vitale, Sara Lonardi, Enrico Gringeri, and Umberto Cillo
- Subjects
Cancer Research ,Oncology ,margin ,major hepatectomies ,mental disorders ,cholangiocarcinoma ,extrahepatic bile duct ,perihilar cholangiocarcinoma ,resection status - Abstract
In resected perihilar cholangiocarcinoma (PHC), positive ductal margin (DM) is associated with poor survival. There is currently little knowledge about the impact of positive radial margin (RM) when DM is negative. The aim of this study was to evaluate the incidence and the role of positive RM. Patients who underwent surgery between 2005 and 2017 where retrospectively reviewed and stratified according to margin positivity: an isolated RM-positive group and DM ± RM group. Of the 75 patients identified; 34 (45.3%) had R1 resection and 17 had positive RM alone. Survival was poorer in patients with R1 resection compared to R0 (p = 0.019). After stratification according to margin positivity; R0 patients showed better survival than DM ± RM-positive patients (p = 0.004; MST 43.9 vs. 23.6 months), but comparable to RM-positive patients (p = 0.361; MST 43.9 vs. 39.5 months). Recurrence was higher in DM ± RM group compared to R0 (p = 0.0017; median disease-free survival (DFS) 15 vs. 30 months); but comparable between RM and R0 group (p = 0.39; DFS 20 vs. 30 months). In univariate and multivariate analysis, DM positivity resulted as a negative prognostic factor both for survival and recurrence. In conclusion, positive RM resections appear to have different recurrence patterns and survival rates than positive DM resections.
- Published
- 2022
22. Platinum sensitivity in patients with IDH1/2 mutated versus wild-type intrahepatic cholangiocarcinoma: a propensity score-based study
- Author
-
Monica Niger, Federico Nichetti, Andrea Casadei‐Gardini, Mario Domenico Rizzato, Chiara Pircher, Marta Bini, Andrea Franza, Margherita Rimini, Valentina Burgio, Caterina Sposetti, Lorenzo Fornaro, Ilario Giovanni Rapposelli, Francesco Enrico D'Amico, Giuseppe Aprile, Caterina Vivaldi, Giovanni Luca Frassineti, Massimo Milione, Giuseppe Leoncini, Alessandro Cappetta, Enrico Vasile, Matteo Fassan, Federica Morano, Federica Perrone, Elena Tamborini, Giancarlo Pruneri, Sara Lonardi, Vincenzo Mazzaferro, Filippo Pietrantonio, Maria Di Bartolomeo, and Filippo de Braud
- Subjects
Intrahepatic ,Cancer Research ,Settore MED/06 - Oncologia Medica ,DNA repair ,Isocitrate Dehydrogenase ,Cholangiocarcinoma ,IDH1 ,IDH2 ,cholangiocarcinoma ,homologous recombination deficiency ,Bile Ducts, Intrahepatic ,Humans ,Mutation ,Propensity Score ,Bile Duct Neoplasms ,Oncology ,Bile Ducts ,Homologous Recombination Deficiency - Abstract
Isocitrate dehydrogenase (IDH)1/2 mutations are the most frequent druggable alterations in intrahepatic cholangiocarcinoma (iCCA), reported in ~20% of cases. Preclinical evidence indicates that these mutations are associated with homologous recombination deficiency (HRD), which could be exploited as a target for platinum chemotherapy (ChT) and PARP inhibitors. However, the role of IDH1/2 mutations as surrogate biomarkers for platinum efficacy is unknown. We conducted a multicenter, propensity score-matched analysis to investigate the impact of IDH1/2 mutations on progression-free survival (PFS), overall response rate (ORR) and disease control rate (DCR) in patients with iCCA treated with platinum-based ChT. An exploratory comparison of complex HRD estimates between IDH1/2 mutated and wild-type tumors from TCGA was also performed. A total of 120 cases were matched in a 1:1 ratio (60 IDH1/2 mutant and 60 wild-type). No differences were observed for platinum-based PFS (7.7 vs 7.3 months, P = .970), DCR (66.1% vs 74.1%, P = .361) and ORR (27.8% vs 25.0%, P = .741). IDH1/2 mutations showed mutual exclusivity with genomic alterations in ATM, BRCA2, MST1R, NF1, FGFR2 and CDKN2A/B losses, respectively, with no clear survival and response differences. Among TCGA tumors, IDH1/2 mutated CCA did not show higher HRD compared to wild-type cases. IDH1/2 mutations are not associated with increased sensitivity to platinum-based ChT in iCCA patients. Deeper genomic sequencing is needed to elucidate the HRD phenotype in IDH1/2 mutant iCCA and exploit its therapeutic vulnerabilities.
- Published
- 2022
23. Evaluation of appendicitis risk prediction models in adults with suspected appendicitis
- Author
-
Luis Tallon-Aguilar, Vincenzo Vigorita, Alethea Tang, Simone Conci, VALERIA TONINI, Maria Carmela Giuffrida, JUAN-CARLOS GOMEZ-ROSADO, Mudassar Ali Ghazanfar, Francesco Fleres, Zahir Mughal, David Ambrona Zafra, Muhamed Farhan-Alanie, Gianluca Garulli, Rhiannon Harries, Michael Wilson, Chiara Listorti, Hugo Santos-Sousa, Mario Rodriguez-Lopez, Tommaso Stecca, Marco Calussi, Antonio Martino, Gianluca Pellino, Emad Aly, Giuseppe Sena, Salomone Di Saverio, Giulia Montori, Leonardo Solaini, Fabio Staderini, Juan Carlos Sebastián-Tomás, Eugenio Cucinotta, Paolo Checcacci, Richard Egan, Ana Alagoa Joao, Diego Sasia, Fady Yanni, Jorge Arredondo, Walid Mohamed, Helena Salvador Roses, Daniel Ashmore, Rachel Mahoney, Sathyan Nagendram, Daniel Ahern, Alex Boddy, FABIO CIANCHI, Pedro Villarejo campos, Victoriano Soria Aledo, Alexandros Charalabopoulos, Vania Silvestri, Kathryn Lee, Allan Golder, Margarida Ferreira, Nicholas Mowbray, Marianne Hollyman, Dennis Ho-Yin Lui, Uday Prasad, Elisa Francone, Arina Anna Tamborska, Marco Inama, Michele Ballabio, João Martins Guimarães, Marco Scatizzi, Martin Connor, Jose Luis Rodicio Miravalles, Carmen Payá-Llorente, Jonathan Shurlock, Francesco Colombo, Thomas Pinkney, Chloe Swords, Patricio Fernando Gálvez Salazar, Luigi Marano, Daniel Fernández Martínez, Andrea Pietrabissa, M. ANGELES CALVO TORRAS, Martín Bailón, Angela Belvedere, Isabel Pascual Miguelañez, Hiten Patel, Edward Balai, Leo Licari, Luca Ansaloni, Ian Daniels, Segundo Gomez-Abril, Vincenzo Lizzi, Jonathan Lund, Carmelo Mazzeo, Peter Coe, FRANCESCO ENRICO D'AMICO, Mauro Podda, Pere Planellas Giné, Peter Cay, David Merlini, Natalie Blencowe, Paola De Nardi, Giuseppe SALAMONE, Emilio Padilla, James Glasbey, Andrea Giorga, Carlos Cerdán Santacruz, Francesca Viscosi, Stefano Scabini, Maria Moreno Gijon, Nicola Cillara, Paul Glen, Sushil Maslekar, Francesco Maria Carrano, Mary Venn, Franco Marinello, Francisco Javier Redondo Calvo, James Haddow, Unai De Andres Olabarria, Frances Wensley, Munir Tarazi, Emily Farrow, Sirio Melone, Chia Yew Kong, Andrea-Pierre Luzzi, Dr Rochelle Velho MBChB MPH (Merit) BSc (Hons), Jeancarlos Trujillo Díaz, Richard Wilkin, Enrique Toledo Martínez, Noel Aruparayil, Mohamed Rabie, SAMUELE VACCARI, José Azevedo, Andrea Bondurri, Philip Herrod, Georgia Layton, Luca Ponchietti, Núria Lluís, James Olivier, Piers Boshier, Spyridon Panagiotopoulos, David Naumann, Adam Misky, Anna Maffioli, Nuno Carvalho, Daniele Delogu, Diego Coletta, Panagiotis Sgardelis, FELIPE PAREJA CIURO, Oliver Warren, Luis Eduardo Pérez-Sánchez, Neeraj Lal, Ruth Blanco-Colino, Sarah Whitehorn, Shahab Hajibandeh, Alexander Christides, Andrea Simioni, Nigel Jamieson, Navamayooran Thavanesan, Monika Rezacova, Gaetano Poillucci, Rucira Ooi, Michele Rubbini, Alessandra Marano, Eloy Espin-Basany, Emanuele Gammeri, Michele Altomare, Laura Pérez-Sánchez, James Archer, Gaetano Gallo, Chung Shen Chean, Ferdinando Agresta, Aneel Bhangu, James Kinross, Gianfranco Cocorullo, Francisco J Tejero-Pintor, Siobhan McKay, Marc Vallve-Bernal, Juan José Segura-Sampedro, and Fahad Mahmood
- Subjects
Scoring system ,business.industry ,Conflict of interest ,MEDLINE ,030230 surgery ,medicine.disease ,Risk prediction models ,GeneralLiterature_MISCELLANEOUS ,Appendicitis ,03 medical and health sciences ,0302 clinical medicine ,Medicine ,Suspected appendicitis ,Medical emergency ,Ultrasonography ,business ,Risk assessment - Abstract
Funding Information: The authors are grateful to the Birmingham Surgical Trials Consortium at the University of Birmingham for the use of their servers for secure online data collection. Disclosure: The authors declare no conflict of interest.
- Published
- 2019
- Full Text
- View/download PDF
24. Towards fingerprinting and identifiability within the Alzheimer’s continuum using resting‐state functional connectivity
- Author
-
Sara Stampacchia, Saina Asadi, Federica Ribaldi, Szymon Tomczyk, Daniele Altomare, Michela Pievani, Giovanni Frisoni, Enrico Amico, and Valentina Garibotto
- Subjects
Psychiatry and Mental health ,Cellular and Molecular Neuroscience ,Developmental Neuroscience ,Epidemiology ,Health Policy ,Neurology (clinical) ,Geriatrics and Gerontology - Published
- 2021
- Full Text
- View/download PDF
25. Colorectal Liver Metastases: A Literature Review of Viable Surgical Options with a Special Focus on Microwave Liver Thermal Ablation and Mini-Invasive Approach
- Author
-
Michele Finotti, Francesco Enrico D’Amico, Maurizio Romano, Marco Brizzolari, Michele Scopelliti, and Giacomo Zanus
- Subjects
thermal liver ablation ,microwave ablation ,Medicine (miscellaneous) ,laparoscopic liver ablation ,liver metastases ,mini invase liver surgery - Abstract
Colorectal cancer (CRC) is the third most common tumor worldwide and it is characterized in 20–30% of cases by liver involvement, which strongly affects the long-term patient outcome. There are many available therapies for liver colorectal metastases (CRLMs); the current standard of care is represented by liver resection, and when feasible, associated with systemic chemotherapy. Microwave thermal ablation (MWA) is a viable option in unresectable patients or to achieve treatment with a parenchymal spearing approach. A literature review was performed for studies published between January 2000 and July 2022 through a database search using PUBMED/Medline and the Cochrane Collaboration Library with the following MeSH search terms and keywords: microwave, ablation, liver metastases, colorectal neoplasm, and colon liver rectal metastases. The recurrence rate and overall patients’ survival were evaluated, showing that laparoscopic MWA is safe and effective to treat CRLMs when resection is not feasible, or a major hepatectomy in fragile patients is necessary. Considering the low morbidity of this procedure, it is a viable option to treat patients with recurrent diseases in the era of effective chemotherapy and multimodal treatments.
- Published
- 2022
- Full Text
- View/download PDF
26. Assessment of temporal complexity in functional MRI between rest and task conditions
- Author
-
Giulia Preti, Andrew Zalesky, Enrico Amico, Amir Omidvarnia, Raphaël Liégeois, and Dimitri Van De Ville
- Subjects
Hurst exponent ,Cingulate cortex ,Human Connectome Project ,medicine.diagnostic_test ,Resting state fMRI ,Computer science ,Working memory ,medicine ,Functional magnetic resonance imaging ,Default mode network ,Cognitive psychology ,Task (project management) - Abstract
Dynamic models of cortical activity, as measured by functional magnetic resonance imaging (fMRI), have recently brought out important insights into the organization of brain function. In terms of temporal complexity, these hemodynamic signals have been shown to exhibit critical behaviour at the edge between order and disorder. In this study, we aimed to revisit the properties and spatial distribution of temporal complexity in resting state and task fMRI of 100 unrelated subjects from the Human Connectome Project (HCP). First, we compared two common choices of complexity measures (i.e., Hurst exponent versus multiscale entropy) and reported high similarity between them. Second, we investigated the influence of experimental paradigms and found high task-specific complexity. We considered four mental tasks in the HCP database for the analysis: Emotion, Working memory, Social, and Language. Third, we tailored a recently-proposed statistical framework that incorporates the structural connectome, to assess the spatial distribution of complexity measures. These results highlight brain regions including parts of the default mode network and cingulate cortex with significantly stronger complex behaviour than the rest of the brain, irrespective of task. In sum, temporal complexity measures of fMRI are reliable markers of the cognitive status.
- Published
- 2021
- Full Text
- View/download PDF
27. When makes you unique: Temporality of the human brain fingerprint
- Author
-
Dimitri, Van De Ville, Younes, Farouj, Maria Giulia, Preti, Raphaël, Liégeois, and Enrico, Amico
- Subjects
Network Science ,SciAdv r-articles ,Research Article ,Neuroscience - Abstract
Description, Patterns of human brain activity emerge from temporally limited fMRI observations, allowing identification of individuals., The extraction of “fingerprints” from human brain connectivity data has become a new frontier in neuroscience. However, the time scales of human brain identifiability are still largely unexplored. We here investigate the dynamics of brain fingerprints along two complementary axes: (i) What is the optimal time scale at which brain fingerprints integrate information and (ii) when best identification happens. Using dynamic identifiability, we show that the best identification emerges at longer time scales; however, short transient “bursts of identifiability,” associated with neuronal activity, persist even when looking at shorter functional interactions. Furthermore, we report evidence that different parts of connectome fingerprints relate to different time scales, i.e., more visual-somatomotor at short temporal windows and more frontoparietal-DMN driven at increasing temporal windows. Last, different cognitive functions appear to be meta-analytically implicated in dynamic fingerprints across time scales. We hope that this investigation will advance our understanding of what makes our brains unique.
- Published
- 2021
28. The physics of higher-order interactions in complex systems
- Author
-
Vito Latora, Yamir Moreno, Ginestra Bianconi, Alain Barrat, Francesco Vaccarino, Giovanni Petri, Benedetta Franceschiello, Federico Battiston, Iacopo Iacopini, Enrico Amico, Sonia Kéfi, Guilherme Ferraz de Arruda, Tiago P. Peixoto, Micah M. Murray, CPT - E5 Physique statistique et systèmes complexes, Centre de Physique Théorique - UMR 7332 (CPT), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Institut des Sciences de l'Evolution de Montpellier (UMR ISEM), École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre National de la Recherche Scientifique (CNRS)-Institut de recherche pour le développement [IRD] : UR226, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-École Pratique des Hautes Études (EPHE), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Institut de recherche pour le développement [IRD] : UR226-Centre National de la Recherche Scientifique (CNRS)
- Subjects
FOS: Computer and information sciences ,Physics - Physics and Society ,Theoretical computer science ,Complex system ,FOS: Physical sciences ,General Physics and Astronomy ,reduction ,Physics and Society (physics.soc-ph) ,01 natural sciences ,010305 fluids & plasmas ,models ,Higher-order interaction systems ,0103 physical sciences ,patterns ,[PHYS.COND.CM-SM]Physics [physics]/Condensed Matter [cond-mat]/Statistical Mechanics [cond-mat.stat-mech] ,complex systems ,010306 general physics ,ComputingMilieux_MISCELLANEOUS ,symmetry ,Social and Information Networks (cs.SI) ,multilayer ,Computer Science - Social and Information Networks ,Disordered Systems and Neural Networks (cond-mat.dis-nn) ,dynamics ,Condensed Matter - Disordered Systems and Neural Networks ,Complex network ,explosive percolation ,Nonlinear Sciences - Adaptation and Self-Organizing Systems ,Order (biology) ,FOS: Biological sciences ,networks ,Quantitative Biology - Neurons and Cognition ,Neurons and Cognition (q-bio.NC) ,Pairwise comparison ,applied topology ,Adaptation and Self-Organizing Systems (nlin.AO) ,synchronization ,Higher-order interaction systems, complex systems, applied topology - Abstract
Complex networks have become the main paradigm for modelling the dynamics of interacting systems. However, networks are intrinsically limited to describing pairwise interactions, whereas real-world systems are often characterized by higher-order interactions involving groups of three or more units. Higher-order structures, such as hypergraphs and simplicial complexes, are therefore a better tool to map the real organization of many social, biological and man-made systems. Here, we highlight recent evidence of collective behaviours induced by higher-order interactions, and we outline three key challenges for the physics of higher-order systems., pre-peer-reviewed version of the Nature Physics perspective, 7 pages, 4 figures
- Published
- 2021
- Full Text
- View/download PDF
29. Clinical connectome fingerprints of cognitive decline
- Author
-
Pierpaolo Sorrentino, Emahnuel Troisi Lopez, Enrico Amico, Giuseppe Sorrentino, Marianna Liparoti, Andrea Soricelli, Carlo Cavaliere, Viktor K. Jirsa, Anna Lardone, Rosaria Rucco, Institut de Neurosciences des Systèmes (INS), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Institut National de la Santé et de la Recherche Médicale (INSERM)
- Subjects
Brain networks ,Clinical brain fingerprinting ,Cognitive impairment ,Functional connectomes ,MEG connectivity ,Brain ,Cognition ,Cognitive Dysfunction ,Humans ,Magnetoencephalography ,Nerve Net ,Neuropsychological Tests ,Connectome ,Brain activity and meditation ,Cognitive Neuroscience ,Neurosciences. Biological psychiatry. Neuropsychiatry ,Disease ,050105 experimental psychology ,03 medical and health sciences ,0302 clinical medicine ,Medicine ,0501 psychology and cognitive sciences ,Cognitive decline ,ComputingMilieux_MISCELLANEOUS ,medicine.diagnostic_test ,business.industry ,[SCCO.NEUR]Cognitive science/Neuroscience ,05 social sciences ,Human brain ,medicine.anatomical_structure ,Neurology ,Identification (biology) ,business ,Neuroscience ,030217 neurology & neurosurgery ,RC321-571 - Abstract
Brain connectome fingerprinting is rapidly rising as a novel influential field in brain network analysis. Yet, it is still unclear whether connectivity fingerprints could be effectively used for mapping and predicting disease progression from human brain data. We hypothesize that dysregulation of brain activity in disease would reflect in worse subject identification. We propose a novel framework, Clinical Connectome Fingerprinting, to detect individual connectome features from clinical populations. We show that “clinical fingerprints” can map individual variations between elderly healthy subjects and patients with mild cognitive impairment in functional connectomes extracted from magnetoencephalography data. We find that identifiability is reduced in patients as compared to controls, and show that these connectivity features are predictive of the individual Mini-Mental State Examination (MMSE) score in patients. We hope that the proposed methodology can help in bridging the gap between connectivity features and biomarkers of brain dysfunction in large-scale brain networks.
- Published
- 2021
- Full Text
- View/download PDF
30. Case Report: Liver Cysts and SARS-CoV-2: No Evidence of Virus in Cystic Fluid
- Author
-
Francesco Enrico D'Amico, Dajana Glavas, Giulia Noaro, Domenico Bassi, Riccardo Boetto, Enrico Gringeri, Maurizio De Luca, and Umberto Cillo
- Subjects
0301 basic medicine ,medicine.medical_specialty ,Abdominal pain ,RD1-811 ,viruses ,Case Report ,medicine.disease_cause ,Gastroenterology ,jaundice ,03 medical and health sciences ,0302 clinical medicine ,CoV-2 ,Internal medicine ,medicine ,Cyst ,Coronavirus ,business.industry ,fenestration cyst ,liver cyst infection ,Jaundice ,medicine.disease ,Pneumonia ,030104 developmental biology ,Nasal Swab ,030211 gastroenterology & hepatology ,Surgery ,liver benign disease ,Hepatic Cyst ,medicine.symptom ,business ,Viral load - Abstract
Background: In December 2019, an outbreak of pneumonia, caused by a new type of coronavirus, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It quickly spread worldwide, resulting in a pandemic. The clinical manifestations of SARS-CoV-2 range from mild non-specific symptoms to severe pneumonia with organ function damage. In addition, up to 60% of patients have liver impairment or dysfunction, confirmed by several studies by the presence of SARS-CoV-2 in the liver tissue.Methods: We report two cases of symptomatic liver cyst requiring fenestration after recent SARS-CoV-2 infection. Both patients had hospital admission due to documented SARS-CoV-2 infection. Recently, after the infection, they developed symptoms caused by an enlarged hepatic cyst: one had abdominal pain, and the other had jaundice. They underwent surgery after two negative swab tests for SARS-CoV-2.Results: Cystic fluid was sent for microbiological test, and real-time fluorescence polymerase chain reaction COVID-19 nucleic-acid assay of the cyst fluid was found to be negative in both cases.Discussion: Although there are no current data that can document a viral contamination of cystic fluid, there are data that document a hepatotropism of COVID-19 virus. Herein we report that after viral clearance at pharyngeal and nasal swab, there is no evidence of viral load in such potential viral reservoir.
- Published
- 2021
- Full Text
- View/download PDF
31. Centralized and distributed cognitive task processing in the human connectome
- Author
-
Enrico Amico, Joaquín Goñi, and Alex Arenas
- Subjects
Information theory ,Brain connectomics ,Computer science ,Network science ,Machine learning ,computer.software_genre ,lcsh:RC321-571 ,Task (project management) ,Functional connectivity ,03 medical and health sciences ,0302 clinical medicine ,Artificial Intelligence ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,Research Articles ,030304 developmental biology ,0303 health sciences ,Human Connectome Project ,Resting state fMRI ,business.industry ,Applied Mathematics ,General Neuroscience ,Cognition ,Human Connectome ,Computer Science Applications ,Quantitative Biology - Neurons and Cognition ,FOS: Biological sciences ,Neurons and Cognition (q-bio.NC) ,Pairwise comparison ,Artificial intelligence ,business ,Cognitive task processing ,computer ,030217 neurology & neurosurgery - Abstract
A key question in modern neuroscience is how cognitive changes in a human brain can be quantified and captured by functional connectivity (FC). A systematic approach to measure pairwise functional distance at different brain states is lacking. This would provide a straightforward way to quantify differences in cognitive processing across tasks; also, it would help in relating these differences in task-based FCs to the underlying structural network. Here we propose a framework, based on the concept of Jensen-Shannon divergence, to map the task-rest connectivity distance between tasks and resting-state FC. We show how this information theoretical measure allows for quantifying connectivity changes in distributed and centralized processing in functional networks. We study resting state and seven tasks from the Human Connectome Project dataset to obtain the most distant links across tasks. We investigate how these changes are associated with different functional brain networks, and use the proposed measure to infer changes in the information-processing regimes. Furthermore, we show how the FC distance from resting state is shaped by structural connectivity, and to what extent this relationship depends on the task. This framework provides a well-grounded mathematical quantification of connectivity changes associated with cognitive processing in large-scale brain networks., Author Summary A key question in modern neuroscience is how cognitive changes in a human brain can be quantified and captured by functional connectivity (FC). Here we propose a framework, based on Jensen-Shannon divergence, to define “connectivity distance” and to infer about brain network reconfiguration across different tasks with respect to resting state, and to explore changes in centralized and distributed processing in FCs. Three functional networks (dorsal attention, frontoparietal and DMN) showed major changes in distributed processing and minor changes in centralized processing. Changes in centralized processing depend on the underlying structural connectivity weights and structural path “hiddenness.” These findings suggest that the cognitive “switch” between resting state and task states is a complex interplay between maximally and minimally distant functional connections, and the underlying structure.
- Published
- 2019
- Full Text
- View/download PDF
32. Genetic Algorithm-based control of the wake of a bluff body
- Author
-
Enrico Amico, Domenico Di Bari, Gioacchino Cafiero, and Gaetano Iuso
- Subjects
History ,Computer Science Applications ,Education - Abstract
This work reports on the application of a Genetic Algorithm (GA)-based approach to control the wake of a bluff body. The control is achieved through the actuation of four air jets placed along the edges of the model’s base. The dependence of the population size on the convergence of the genetic code was assessed, evidencing an increase of the number of elements in the population needed to learning more complex tasks. In this case, a sum of two sine waves is considered, where frequency and amplitude of each of the two sine waves are optimised. It is demonstrated that the GA converges to a control law yielding values of the drag reduction up to 11.2% with respect to the natural case. The cost function has been defined as to minimise the drag coefficient, without accounting for the energy spent in the actuation. The proper orthogonal decomposition (POD) applied to the fluctuating pressure signals highlights the most relevant features of the wake. The results show that in the natural case nearly 80% of the modal energy is associated with the first mode. Conversely, the forced case features a more evenly distributed energy content across the POD modes. The analysis of the first two modes reveals that for both cases the wake is governed by the shedding phenomenon. Furthermore, the analysis reveals that regardless of the actuation conditions, the top-down shedding represents the most significant phenomenon for the wake dynamics.
- Published
- 2022
- Full Text
- View/download PDF
33. Brain structure-function coupling provides signatures for task decoding and individual fingerprinting
- Author
-
Van De Ville D, Alessandra Griffa, Maria Giulia Preti, Raphaël Liégeois, and Enrico Amico
- Subjects
Brain state ,Human Connectome Project ,Computer science ,business.industry ,Structure function ,Cognition ,Pattern recognition ,Artificial intelligence ,business ,Brain function ,Signature (logic) ,Decoding methods ,Biomarker (cell) - Abstract
Brain signatures of functional activity have shown promising results in both decoding brain states, meaning distinguishing between different tasks, and fingerprinting, that is identifying individuals within a large group. Importantly, these brain signatures do not account for the underlying brain anatomy on which brain function takes place. Structure-function coupling based on graph signal processing (GSP) has recently revealed a meaningful spatial gradient from unimodal to transmodal regions, on average in healthy subjects during resting-state. Here, we explore the potential of GSP to introduce new imaging-based biomarkers to characterize tasks and individuals. We used multimodal magnetic resonance imaging of 100 unrelated healthy subjects from the Human Connectome Project both during rest and seven different tasks and adopted a support vector machine classification approach for both decoding and fingerprinting, with various cross-validation settings. We found that structurefunction coupling measures allow accurate classifications for both task decoding and fingerprinting. In particular, key information for fingerprinting is found in the more liberal portion of functional signals, that is the one decoupled from structure. A network mainly involving cortico-subcortical connections showed the strongest correlation with cognitive traits, assessed with partial least square analysis, corroborating its relevance for fingerprinting. By introducing a new perspective on GSP-based signal filtering and FC decomposition, these results show that brain structure-function coupling provides a new class of signatures of cognition and individual brain organization at rest and during tasks. Further, they provide insights on clarifying the role of low and high spatial frequencies of the structural connectome, leading to new understanding of where key structure-function information for characterizing individuals can be found across the structural connectome graph spectrum.Highlights-The relation of brain function with the underlying structural wiring is complex-We propose new structure-informed graph signal processing (GSP) of functional data-GSP-derived features allow accurate task decoding and individual fingerprinting-Functional connectivity from filtered data is more unique to subject and cognition-The role of structurally aligned and liberal graph frequencies is elucidated
- Published
- 2021
- Full Text
- View/download PDF
34. Spatial patterns in functional brain connectomes reflect acute and chronic cannabis use
- Author
-
Ramaekers J, Stefan W. Toennes, Natasha L. Mason, Enrico Amico, and Eef L. Theunissen
- Subjects
Resting state fMRI ,biology ,business.industry ,Hyperconnectivity ,Cannabis use ,biology.organism_classification ,Cannabis intoxication ,Functional brain ,Connectome ,Medicine ,Cannabis ,business ,Neuroscience ,Default mode network - Abstract
Resting state fMRI has been employed to identify alterations in functional connectivity within or between brain regions following acute and chronic exposure to Δ9-tetrahydrocannabinol (THC), the psychoactive component in cannabis. Most studies focused a priori on a limited number of local brain areas or circuits, without considering the impact of cannabis on wholebrain network organization. The present study attempted to identify changes in the wholebrain human functional connectome as assessed with ultra-high field (7T) resting state scans of occasional (N=12) and chronic cannabis users (N=14) during placebo and following vaporization of cannabis. Two distinct data-driven methodologies, i.e. network-based statistics (NBS) and connICA, were used to identify changes in functional connectomes associated with acute cannabis intoxication and chronic cannabis use. Both methodologies revealed a broad state of hyperconnectivity within the entire range of major brain networks in chronic cannabis users compared to occasional cannabis users, which might be reflective of an adaptive network reorganization following prolonged cannabis exposure. The connICA methodology also extracted a distinct spatial connectivity pattern of hypoconnectivity involving the dorsal attention, limbic, subcortical and cerebellum networks and of hyperconnectivity between the default mode and ventral attention network, that was associated with the feeling of subjective high during THC intoxication across both user groups. Whole-brain network approaches identified spatial patterns in functional brain connectomes that distinguished acute from chronic cannabis use, and offer an important utility for probing the interplay between short and long-term alterations in functional brain dynamics when progressing from occasional to chronic use of cannabis.
- Published
- 2021
- Full Text
- View/download PDF
35. Exploring MEG brain fingerprints: evaluation, pitfalls, and interpretations
- Author
-
Enrico Amico, Anubha Gupta, Alessandra Griffa, Sélima Zahar, Ekansh Sareen, and Dimitri Van De Ville
- Subjects
Human Connectome Project ,genetic structures ,medicine.diagnostic_test ,business.industry ,Computer science ,Functional connectivity ,Fingerprint (computing) ,Pattern recognition ,Magnetoencephalography ,behavioral disciplines and activities ,Identification (information) ,Electrophysiology ,nervous system ,Connectome ,medicine ,Functional connectome ,Artificial intelligence ,Neuroscience research ,business ,Functional magnetic resonance imaging ,psychological phenomena and processes - Abstract
Individual characterization of subjects based on their functional connectome (FC), termed “FC fingerprinting”, has become a highly sought-after goal in contemporary neuroscience research. Recent functional magnetic resonance imaging (fMRI) studies have demonstrated unique characterization and accurate identification of individuals as an accomplished task. However, FC fingerprinting in magnetoencephalography (MEG) data is still widely unexplored. Here, we study resting-state MEG data from the Human Connectome Project to assess the MEG FC fingerprinting and its relationship with several factors including amplitude- and phase-coupling functional connectivity measures, spatial leakage correction, frequency bands, and behavioral significance. To this end, we first employ two identification scoring methods, differential identifiability and success rate, to provide quantitative fingerprint scores for each FC measurement. Secondly, we explore the edgewise and nodal MEG fingerprinting patterns across the different frequency bands (delta, theta, alpha, beta, and gamma). Finally, we investigate the cross-modality fingerprinting patterns obtained from MEG and fMRI recordings from the same subjects. We assess the behavioral significance of FC across connectivity measures and imaging modalities using partial least square correlation analyses. Our results suggest that fingerprinting performance is heavily dependent on the functional connectivity measure, frequency band, identification scoring method, and spatial leakage correction. We report higher MEG fingerprints in phase-coupling methods, central frequency bands (alpha and beta), and in the visual, frontoparietal, dorsal-attention, and default-mode networks. Furthermore, cross-modality comparisons reveal a certain degree of spatial concordance in fingerprinting patterns between the MEG and fMRI data, especially in the visual system. Finally, the multivariate correlation analyses show that MEG connectomes have strong behavioral significance, which however depends on the considered connectivity measure and temporal scale. This comprehensive, albeit preliminary investigation of MEG connectome test-retest identification offers a first characterization of MEG fingerprinting in relation to different methodological and electrophysiological factors and contributes to the understanding of fingerprinting cross-modal relationships. We hope that this first investigation will contribute to setting the grounds for MEG connectome identification.
- Published
- 2021
- Full Text
- View/download PDF
36. Clinical connectome fingerprints of cognitive decline
- Author
-
Anna Lardone, Rosaria Rucco, Marianna Liparoti, Viktor K. Jirsa, Enrico Amico, Carlo Cavaliere, Pierpaolo Sorrentino, Andrea Soricelli, Emahnuel Troisi Lopez, and Giuseppe Sorrentino
- Subjects
Brain network ,medicine.diagnostic_test ,business.industry ,Brain activity and meditation ,Magnetoencephalography ,Human brain ,Disease ,medicine.anatomical_structure ,Connectome ,Medicine ,Identification (biology) ,Cognitive decline ,business ,Neuroscience - Abstract
Brain connectome fingerprinting is rapidly rising as a novel influential field in brain network analysis. Yet, it is still unclear whether connectivity fingerprints could be effectively used for mapping and predicting disease progression from human brain data. We hypothesize that dysregulation of brain activity in disease would reflect in worse subject identification. Hence, we propose a novel framework, Clinical Connectome Fingerprinting, to detect individual connectome features from clinical populations. We show that “clinical fingerprints” can map individual variations between elderly healthy subjects and patients undergoing cognitive decline in functional connectomes extracted from magnetoencephalography data. We find that identifiability is reduced in patients as compared to controls, and show that these connectivity features are predictive of the individual Mini-Mental State Examination (MMSE) score in patients. We hope that the proposed methodology can help in bridging the gap between connectivity features and biomarkers of brain dysfunction in large-scale brain networks.
- Published
- 2020
- Full Text
- View/download PDF
37. The disengaging brain: Dynamic transitions from cognitive engagement and alcoholism risk
- Author
-
Mario Dzemidzic, David A. Kareken, Joaquín Goñi, Brandon G. Oberlin, Claire R. Carron, Jaroslaw Harezlak, and Enrico Amico
- Subjects
Adult ,Male ,Elementary cognitive task ,Time Factors ,Cognitive Neuroscience ,media_common.quotation_subject ,Stop signal ,Motor Activity ,050105 experimental psychology ,Article ,Task (project management) ,lcsh:RC321-571 ,03 medical and health sciences ,Young Adult ,0302 clinical medicine ,Reward ,Connectome ,Humans ,0501 psychology and cognitive sciences ,Genetic Predisposition to Disease ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,media_common ,Cerebral Cortex ,Addiction ,05 social sciences ,Control reconfiguration ,Cognition ,Magnetic Resonance Imaging ,Alcoholism ,Inhibition, Psychological ,Neurology ,Delay Discounting ,Female ,Nerve Net ,Psychology ,030217 neurology & neurosurgery ,Cognitive psychology ,Addiction vulnerability - Abstract
Human functional brain connectivity is usually measured either at "rest" or during cognitive tasks, ignoring life's moments of mental transition. We propose a different approach to understanding brain network transitions. We applied a novel independent component analysis of functional connectivity during motor inhibition (stop signal task) and during the continuous transition to an immediately ensuing rest. A functional network reconfiguration process emerged that: (i) was most prominent in those without familial alcoholism risk, (ii) encompassed brain areas engaged by the task, yet (iii) appeared only transiently after task cessation. The pattern was not present in a pre-task rest scan or in the remaining minutes of post-task rest. Finally, this transient network reconfiguration related to a key behavioral trait of addiction risk: reward delay discounting. These novel findings illustrate how dynamic brain functional reconfiguration during normally unstudied periods of cognitive transition might reflect addiction vulnerability, and potentially other forms of brain dysfunction.
- Published
- 2020
38. Geodesic distance on optimally regularized functional connectomes uncovers individual fingerprints
- Author
-
Luiz Pessoa, Kausar Abbas, Manasij Venkatesh, Alan D. Kaplan, Enrico Amico, Joaquín Goñi, Mario Ventresca, Mintao Liu, and Jaroslaw Harezlak
- Subjects
Geodesic ,Computer science ,Regularization (mathematics) ,050105 experimental psychology ,law.invention ,fc fingerprinting ,neuroscience ,03 medical and health sciences ,0302 clinical medicine ,project ,Cognition ,law ,individual fingerprint ,Connectome ,Humans ,0501 psychology and cognitive sciences ,brain connectomics ,Differentiable function ,geodesic distance ,human brain ,General Neuroscience ,05 social sciences ,Brain ,Function (mathematics) ,Original Articles ,Magnetic Resonance Imaging ,Data set ,regularization ,Invertible matrix ,Algebraic operation ,FOS: Biological sciences ,parcellation ,Quantitative Biology - Neurons and Cognition ,Pairwise comparison ,Neurons and Cognition (q-bio.NC) ,lipids (amino acids, peptides, and proteins) ,Algorithm ,030217 neurology & neurosurgery - Abstract
Background: Functional connectomes (FCs) have been shown to provide a reproducible individual fingerprint, which has opened the possibility of personalized medicine for neuro/psychiatric disorders. Thus, developing accurate ways to compare FCs is essential to establish associations with behavior and/or cognition at the individual level., Methods: Canonically, FCs are compared using Pearson's correlation coefficient of the entire functional connectivity profiles. Recently, it has been proposed that the use of geodesic distance is a more accurate way of comparing FCs, one which reflects the underlying non-Euclidean geometry of the data. Computing geodesic distance requires FCs to be positive-definite and hence invertible matrices. As this requirement depends on the functional magnetic resonance imaging scanning length and the parcellation used, it is not always attainable and sometimes a regularization procedure is required., Results: In the present work, we show that regularization is not only an algebraic operation for making FCs invertible, but also that an optimal magnitude of regularization leads to systematically higher fingerprints. We also show evidence that optimal regularization is data set-dependent and varies as a function of condition, parcellation, scanning length, and the number of frames used to compute the FCs., Discussion: We demonstrate that a universally fixed regularization does not fully uncover the potential of geodesic distance on individual fingerprinting and indeed could severely diminish it. Thus, an optimal regularization must be estimated on each data set to uncover the most differentiable across-subject and reproducible within-subject geodesic distances between FCs. The resulting pairwise geodesic distances at the optimal regularization level constitute a very reliable quantification of differences between subjects.
- Published
- 2020
39. Treatment with K6PC-5, a selective stimulator of SPHK1, ameliorates intestinal homeostasis in an animal model of Huntington's disease
- Author
-
Susy Giova, Vittorio Maglione, Se Kyoo Jeong, Luca Capocci, Federico Marracino, Enrico Amico, L. Del Vecchio, Bu-Mahn Park, Bu Mahn Park, A Di Pardo, and Giuseppe Pepe
- Subjects
0301 basic medicine ,HD ,Intestinal homeostasis ,Disease ,lcsh:RC321-571 ,03 medical and health sciences ,Mice ,0302 clinical medicine ,Huntington's disease ,Sphingosine ,medicine ,Animals ,Homeostasis ,Neurodegeneration ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,K6PC-5 ,Sphingolipids ,Activator (genetics) ,business.industry ,R6/2 mice ,Metabolism ,medicine.disease ,Sphingolipid ,Amides ,Intestines ,Disease Models, Animal ,Phosphotransferases (Alcohol Group Acceptor) ,030104 developmental biology ,Huntington Disease ,Neurology ,Immunology ,Lysophospholipids ,business ,030217 neurology & neurosurgery - Abstract
Emerging evidence indicates that Huntington's disease (HD) may be described as multi-organ pathology. In this context, we and others have contributed to demonstrate that the disease is characterized by an impairment of the homeostasis of gastro-intestinal (GI) tract. Sphingolipids represent a class of molecules involved in the regulation and maintenance of different tissues and organs including GI system. In this study, we investigated whether the alteration of Sphingosine-1-phosphate (S1P) metabolism, previously described in human HD brains and animal models, is also detectable peripherally in R6/2 HD mice. Our findings indicate, for the first time, that sphingolipid metabolism is perturbed early in the disease in the intestinal tract of HD mice and, its modulation by K6PC-5, a selective activator of S1P synthesis, preserved intestinal integrity and homeostasis. These results further support the evidence that modulation of sphingolipid pathways may represent a potential therapeutic option in HD and suggest that it has also the potential to counteract the peripheral disturbances which may usually complicate the management of the disease and affect patient's quality of life.
- Published
- 2020
40. GEFF: Graph Embedding for Functional Fingerprinting
- Author
-
Enrico Amico, Kausar Abbas, Diana O. Svaldi, Meenusree Rajapandian, Uttara Tipnis, Joaquín Goñi, Mintao Liu, Duy Anh Duong-Tran, Jaroslaw Harezlak, and Beau M. Ances
- Subjects
Adult ,Male ,Computer science ,Graph embedding ,Process (engineering) ,Cognitive Neuroscience ,Population ,050105 experimental psychology ,Task (project management) ,lcsh:RC321-571 ,03 medical and health sciences ,Young Adult ,0302 clinical medicine ,Cognition ,Connectome ,Image Processing, Computer-Assisted ,Humans ,0501 psychology and cognitive sciences ,education ,Representation (mathematics) ,lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry ,education.field_of_study ,business.industry ,05 social sciences ,Brain ,Pattern recognition ,Models, Theoretical ,Magnetic Resonance Imaging ,Identification (information) ,Neurology ,FOS: Biological sciences ,Quantitative Biology - Neurons and Cognition ,Embedding ,Neurons and Cognition (q-bio.NC) ,Female ,Artificial intelligence ,business ,030217 neurology & neurosurgery - Abstract
It has been well established that Functional Connectomes (FCs), as estimated from functional MRI (fMRI) data, have an individual fingerprint that can be used to identify an individual from a population (subject-identification). Although identification rate is high when using resting-state FCs, other tasks show moderate to low values. Furthermore, identification rate is task-dependent, and is low when distinct cognitive states, as captured by different fMRI tasks, are compared. Here we propose an embedding framework, GEFF (Graph Embedding for Functional Fingerprinting), based on group-level decomposition of FCs into eigenvectors. GEFF creates an eigenspace representation of a group of subjects using one or more task FCs (Learning Stage). In the Identification Stage, we compare new instances of FCs from the Learning subjects within this eigenspace (validation dataset). The validation dataset contains FCs either from the same tasks as the Learning dataset or from the remaining tasks that were not included in Learning. Assessment of validation FCs within the eigenspace results in significantly increased subject-identification rates for all fMRI tasks tested and potentially task-independent fingerprinting process. It is noteworthy that combining resting-state with one fMRI task for GEFF Learning Stage covers most of the cognitive space for subject identification. In addition to subject-identification, GEFF was also used for identification of cognitive states, i.e. to identify the task associated to a given FC, regardless of the subject being already in the Learning dataset or not (subject-independent task-identification). In addition, we also show that eigenvectors from the Learning Stage can be characterized as task-dominant, subject dominant or neither, providing a deeper insight into the extent of variance in functional connectivity across individuals and cognitive states., 30 pages; 6 figures; 5 supplementary figures
- Published
- 2020
41. Improving Functional Connectome Fingerprinting with Degree-Normalization
- Author
-
Joaquín Goñi, Enrico Amico, Frédéric Crevecoeur, Kausar Abbas, Duy Anh Duong-Tran, Benjamin Chiêm, UCL - SSS/IONS/COSY - Systems & cognitive Neuroscience, and UCL - SST/ICTM/INMA - Pôle en ingénierie mathématique
- Subjects
Normalization (statistics) ,Time Factors ,Computer science ,Fingerprint ,fingerprint ,Matching rate ,matching rate ,050105 experimental psychology ,Degree-normalization ,Functional connectivity ,03 medical and health sciences ,0302 clinical medicine ,Neuroimaging ,Connectome ,Functional connectome ,Humans ,0501 psychology and cognitive sciences ,mri ,degree-normalization ,Degree (graph theory) ,hubs ,business.industry ,Covariance matrix ,General Neuroscience ,functional connectivity ,05 social sciences ,Fingerprint (computing) ,Brain ,Pattern recognition ,Original Articles ,brain networks ,Magnetic Resonance Imaging ,3. Good health ,Benchmarking ,identifying individuals ,connectivity ,Quantitative Biology - Neurons and Cognition ,FOS: Biological sciences ,identification ,Neurons and Cognition (q-bio.NC) ,Artificial intelligence ,business ,030217 neurology & neurosurgery ,MRI - Abstract
Background: Functional connectivity quantifies the statistical dependencies between the activity of brain regions, measured using neuroimaging data such as functional magnetic resonance imaging (fMRI) blood-oxygenation-level dependent time series. The network representation of functional connectivity, called a functional connectome (FC), has been shown to contain an individual fingerprint allowing participants identification across consecutive testing sessions. Recently, researchers have focused on the extraction of these fingerprints, with potential applications in personalized medicine., Materials and Methods: In this study, we show that a mathematical operation denominated degree-normalization can improve the extraction of FC fingerprints. Degree-normalization has the effect of reducing the excessive influence of strongly connected brain areas in the whole-brain network. We adopt the differential identifiability framework and apply it to both original and degree-normalized FCs of 409 individuals from the Human Connectome Project, in resting-state and 7 fMRI tasks., Results: Our results indicate that degree-normalization systematically improves three fingerprinting metrics, namely differential identifiability, identification rate, and matching rate. Moreover, the results related to the matching rate metric suggest that individual fingerprints are embedded in a low-dimensional space., Discussion: The results suggest that low-dimensional functional fingerprints lie in part in weakly connected sub-networks of the brain and that degree-normalization helps uncovering them. This work introduces a simple mathematical operation that could lead to significant improvements in future FC fingerprinting studies.
- Published
- 2020
- Full Text
- View/download PDF
42. The longevity-associated variant of BPIFB4 improves a CXCR4-mediated striatum–microglia crosstalk preventing disease progression in a mouse model of Huntington’s disease
- Author
-
Alberto Auricchio, Francesco Montella, Annibale Alessandro Puca, Alba Di Pardo, Valentina Lopardo, Enrico Amico, Anna Maciag, Vittorio Maglione, Albino Carrizzo, Monica Cattaneo, Elena Ciaglia, Carmine Vecchione, Antonio D'Amato, Francesco Villa, Giuseppe Pepe, Federico Marracino, Anna Ferrario, Michele Madonna, Di Pardo, A., Ciaglia, E., Cattaneo, M., Maciag, A., Montella, F., Lopardo, V., Ferrario, A., Villa, F., Madonna, M., Amico, E., Carrizzo, A., Damato, A., Pepe, G., Marracino, F., Auricchio, A., Vecchione, C., Maglione, V., and Puca, A. A.
- Subjects
0301 basic medicine ,Cancer Research ,Benzylamines ,Cellular homeostasis ,Cyclams ,0302 clinical medicine ,Cell Line, Transformed ,Microglia ,Cell Death ,lcsh:Cytology ,Cell Polarity ,Huntington's disease ,Polyglutamine tract ,Cell biology ,medicine.anatomical_structure ,Huntington Disease ,Disease Progression ,Intercellular Signaling Peptides and Proteins ,Proteasome Endopeptidase Complex ,Receptors, CXCR4 ,Cell Survival ,Immunology ,Longevity ,Biology ,Motor Activity ,Neuroprotection ,Article ,Cell Line ,03 medical and health sciences ,Cellular and Molecular Neuroscience ,Immune system ,medicine ,Huntingtin Protein ,Animals ,lcsh:QH573-671 ,Neuroinflammation ,Cell Proliferation ,Inflammation ,Genetic Variation ,Cell Biology ,medicine.disease ,Phosphoproteins ,Corpus Striatum ,Disease Models, Animal ,030104 developmental biology ,Gene Ontology ,Gene Expression Regulation ,030217 neurology & neurosurgery - Abstract
The longevity-associated variant (LAV) of the bactericidal/permeability-increasing fold-containing family B member 4 (BPIFB4) has been found significantly enriched in long-living individuals. Neuroinflammation is a key player in Huntington’s disease (HD), a neurodegenerative disorder caused by neural death due to expanded CAG repeats encoding a long polyglutamine tract in the huntingtin protein (Htt). Herein, we showed that striatal-derived cell lines with expanded Htt (STHdh Q111/111) expressed and secreted lower levels of BPIFB4, when compared with Htt expressing cells (STHdh Q7/7), which correlated with a defective stress response to proteasome inhibition. Overexpression of LAV-BPIFB4 in STHdh Q111/111 cells was able to rescue both the BPIFB4 secretory profile and the proliferative/survival response. According to a well-established immunomodulatory role of LAV-BPIFB4, conditioned media from LAV-BPIFB4-overexpressing STHdh Q111/111 cells were able to educate Immortalized Human Microglia—SV40 microglial cells. While STHdh Q111/111 dying cells were ineffective to induce a CD163 + IL-10high pro-resolving microglia compared to normal STHdh Q7/7, LAV-BPIFB4 transduction promptly restored the central immune control through a mechanism involving the stromal cell-derived factor-1. In line with the in vitro results, adeno-associated viral-mediated administration of LAV-BPIFB4 exerted a CXCR4-dependent neuroprotective action in vivo in the R6/2 HD mouse model by preventing important hallmarks of the disease including motor dysfunction, body weight loss, and mutant huntingtin protein aggregation. In this view, LAV-BPIFB4, due to its pleiotropic ability in both immune compartment and cellular homeostasis, may represent a candidate for developing new treatment for HD.
- Published
- 2020
43. P1-411: COVARYING PATTERNS OF FUNCTIONAL CONNECTIVITY WITH AMYLOID AND TAU DEPOSITION IN EARLY STAGE ALZHEIMER'S DISEASE
- Author
-
Diana Otero Svaldi, Joaquín Goñi, Enrico Amico, Shannon L. Risacher, Eddie Stage, Charanya Muralidharan, John D. West, Mario Dzemidzic, Andrew J. Saykin, and Liana G. Apostolova
- Subjects
Psychiatry and Mental health ,Cellular and Molecular Neuroscience ,Developmental Neuroscience ,Epidemiology ,Health Policy ,Neurology (clinical) ,Geriatrics and Gerontology - Published
- 2019
- Full Text
- View/download PDF
44. How political choices shaped Covid connectivity: The Italian case study
- Author
-
Iulia Martina Bulai and Enrico Amico
- Subjects
RNA viruses ,European People ,Viral Diseases ,Time Factors ,Epidemiology ,Coronaviruses ,Geographical locations ,Medical Conditions ,Medicine and Health Sciences ,Ethnicities ,Centrality ,Pathology and laboratory medicine ,Multidisciplinary ,Geography ,Ecology ,Politics ,Medical microbiology ,Italian People ,Hospitalization ,Europe ,Infectious Diseases ,Italy ,Community Ecology ,Viruses ,Medicine ,SARS CoV 2 ,Pathogens ,Network Analysis ,Research Article ,Computer and Information Sciences ,SARS coronavirus ,Science ,Microbiology ,Political science ,Humans ,European Union ,Pandemics ,Community Structure ,Ecology and Environmental Sciences ,Organisms ,Viral pathogens ,COVID-19 ,Biology and Life Sciences ,Covid 19 ,Microbial pathogens ,Political economy ,People and Places ,Earth Sciences ,Population Groupings - Abstract
The importance of implementing new methodologies to study the ever-increasing amount of Covid-19 data is apparent. The aftermath analysis of these data could inform us on how specific political decisions influenced the dynamics of the pandemic outbreak. In this paper we use the Italian outbreak as a case study, to study six different Covid indicators collected in twenty Italian regions. We define a new object, the Covidome, to investigate the network of functional Covid interactions between regions. We analyzed the Italian Covidome over the course of 2020, and found that Covid connectivity between regions follows a sharp North-South community gradient. Furthermore, we explored the Covidome dynamics and individuated differences in regional Covid connectivity between the first and second waves of the pandemic. These differences can be associated to the two different lockdown strategies adopted for the first and the second wave from the Italian government. Finally, we explored to what extent Covid connectivity was associated with the Italian geographical network, and found that Central regions were more tied to the structural constraints than Northern or Southern regions in the spread of the virus. We hope that this approach will be useful in gaining new insights on how political choices shaped Covid dynamics across nations.
- Published
- 2021
- Full Text
- View/download PDF
45. Fingerprint of gait applied to Parkinson's disease
- Author
-
Enrico Amico, Marianna Liparoti, Roberta Minino, Pierpaolo Sorrentino, Antonella Romano, Emahnuel Troisi Lopez, and Giuseppe Sorrentino
- Subjects
medicine.medical_specialty ,Parkinson's disease ,Gait (human) ,Physical medicine and rehabilitation ,Neurology ,business.industry ,Fingerprint (computing) ,medicine ,Neurology (clinical) ,medicine.disease ,business - Published
- 2021
- Full Text
- View/download PDF
46. Multifaceted brain networks reconfiguration in disorders of consciousness uncovered by co-activation patterns
- Author
-
Jitka Annen, Enrico Amico, Andrea Soddu, Steven Laureys, Charlotte Martial, Carol Di Perri, Lizette Heine, Stephen Karl Larroque, and Daniele Marinazzo
- Subjects
Radiological and Ultrasound Technology ,media_common.quotation_subject ,05 social sciences ,Disorders of consciousness ,medicine.disease ,050105 experimental psychology ,Cortex (botany) ,03 medical and health sciences ,0302 clinical medicine ,Neurology ,Posterior cingulate ,medicine ,0501 psychology and cognitive sciences ,Radiology, Nuclear Medicine and imaging ,Wakefulness ,Neurology (clinical) ,Anatomy ,Consciousness ,Psychology ,Neuroscience ,Co activation ,Pathological ,030217 neurology & neurosurgery ,Default mode network ,media_common - Abstract
Introduction Given that recent research has shown that functional connectivity is not a static phenomenon, we aim to investigate the dynamic properties of the default mode network's (DMN) connectivity in patients with disorders of consciousness. Methods Resting-state fMRI volumes of a convenience sample of 17 patients in unresponsive wakefulness syndrome (UWS) and controls were reduced to a spatiotemporal point process by selecting critical time points in the posterior cingulate cortex (PCC). Spatial clustering was performed on the extracted PCC time frames to obtain 8 different co-activation patterns (CAPs). We investigated spatial connectivity patterns positively and negatively correlated with PCC using both CAPs and standard stationary method. We calculated CAPs occurrences and the total number of frames. Results Compared to controls, patients showed (i) decreased within-network positive correlations and between-network negative correlations, (ii) emergence of “pathological” within-network negative correlations and between-network positive correlations (better defined with CAPs), and (iii) “pathological” increases in within-network positive correlations and between-network negative correlations (only detectable using CAPs). Patients showed decreased occurrence of DMN-like CAPs (1–2) compared to controls. No between-group differences were observed in the total number of frames Conclusion CAPs reveal at a more fine-grained level the multifaceted spatial connectivity reconfiguration following the DMN disruption in UWS patients, which is more complex than previously thought and suggests alternative anatomical substrates for consciousness. BOLD fluctuations do not seem to differ between patients and controls, suggesting that BOLD response represents an intrinsic feature of the signal, and therefore that spatial configuration is more important for consciousness than BOLD activation itself. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc.
- Published
- 2017
- Full Text
- View/download PDF
47. Cognitive complaints in older adults at risk for Alzheimer's disease are associated with altered resting‐state networks
- Author
-
Shannon L. Risacher, Joey A. Contreras, John D. West, Olaf Sporns, Karmen K. Yoder, Mario Dzemidzic, Martin R. Farlow, Enrico Amico, Andrew J. Saykin, Brenna C. McDonald, and Joaquín Goñi
- Subjects
0301 basic medicine ,Connectomics ,Developmental psychology ,Functional connectivity ,03 medical and health sciences ,0302 clinical medicine ,Memory ,Connectome ,medicine ,PART II. State of the Field: Advances in Neuroimaging from the 2016 Alzheimer's Imaging Consortium ,Cognitive decline ,Episodic memory ,Default mode network ,Resting state fMRI ,medicine.diagnostic_test ,Mild cognitive impairment ,Cognition ,Alzheimer's disease ,Psychiatry and Mental health ,030104 developmental biology ,Subjective cognitive decline ,Neurology (clinical) ,Psychology ,Functional magnetic resonance imaging ,Neurocognitive ,030217 neurology & neurosurgery ,MRI ,Clinical psychology - Abstract
Introduction Pathophysiological changes that accompany early clinical symptoms in prodromal Alzheimer's disease (AD) may have a disruptive influence on brain networks. We investigated resting-state functional magnetic resonance imaging (rsfMRI), combined with brain connectomics, to assess changes in whole-brain functional connectivity (FC) in relation to neurocognitive variables. Methods Participants included 58 older adults who underwent rsfMRI. Individual FC matrices were computed based on a 278-region parcellation. FastICA decomposition was performed on a matrix combining all subjects' FC. Each FC pattern was then used as a response in a multilinear regression model including neurocognitive variables associated with AD (cognitive complaint index [CCI] scores from self and informant, an episodic memory score, and an executive function score). Results Three connectivity independent component analysis (connICA) components (RSN, VIS, and FP-DMN FC patterns) associated with neurocognitive variables were identified based on prespecified criteria. RSN-pattern, characterized by increased FC within all resting-state networks, was negatively associated with self CCI. VIS-pattern, characterized by an increase in visual resting-state network, was negatively associated with CCI self or informant scores. FP-DMN-pattern, characterized by an increased interaction of frontoparietal and default mode networks (DMN), was positively associated with verbal episodic memory. Discussion Specific patterns of FC were differently associated with neurocognitive variables thought to change early in the course of AD. An integrative connectomics approach relating cognition to changes in FC may help identify preclinical and early prodromal stages of AD and help elucidate the complex relationship between subjective and objective indices of cognitive decline and differences in brain functional organization.
- Published
- 2016
- Full Text
- View/download PDF
48. Flexible control of movement in plants
- Author
-
Francesco Ceccarini, Alessandro Peressotti, Umberto Castiello, Francesca Peressotti, Walter Baccinelli, Stefano Massaccesi, Enrico D’Amico, Alejandra Gómez, Silvia Guerra, and Maria Bulgheroni
- Subjects
0106 biological sciences ,0301 basic medicine ,Behavioural ecology ,Computer science ,Movement ,media_common.quotation_subject ,lcsh:Medicine ,Kinematics ,01 natural sciences ,Article ,03 medical and health sciences ,Tendril ,lcsh:Science ,Control (linguistics) ,media_common ,Cognitive science ,Multidisciplinary ,Movement (music) ,lcsh:R ,GRASP ,Peas ,Biomechanical Phenomena ,Variety (cybernetics) ,Surprise ,030104 developmental biology ,Plant signalling ,Climbing ,Darwin (ADL) ,lcsh:Q ,Anatomic Landmarks ,010606 plant biology & botany - Abstract
Although plants are essentially sessile in nature, these organisms are very much in tune with their environment and are capable of a variety of movements. This may come as a surprise to many non-botanists, but not to Charles Darwin, who reported that plants do produce movements. Following Darwin’s specific interest on climbing plants, this paper will focus on the attachment mechanisms by the tendrils. We draw attention to an unsolved problem in available literature: whether during the approach phase the tendrils of climbing plants consider the structure of the support they intend to grasp and plan the movement accordingly ahead of time. Here we report the first empirical evidence that this might be the case. The three-dimensional (3D) kinematic analysis of a climbing plant (Pisum sativum L.) demonstrates that the plant not only perceives the support, but it scales the kinematics of tendrils’ aperture according to its thickness. When the same support is represented in two-dimensions (2D), and thus unclimbable, there is no evidence for such scaling. In these circumstances the tendrils’ kinematics resemble those observed for the condition in which no support was offered. We discuss these data in light of the evidence suggesting that plants are equipped with sensory mechanisms able to provide the necessary information to plan and control a movement.
- Published
- 2019
- Full Text
- View/download PDF
49. Multi-timescale hybrid components of the functional brain connectome: A bimodal EEG-fMRI decomposition
- Author
-
Maxime Guye, Anne-Lise Giraud, Jean-Philippe Ranjeva, Enrico Amico, Sepideh Sadaghiani, Joaquín Goñi, and Jonathan Wirsich
- Subjects
Computer science ,Concurrent EEG-fMRI ,Neurosciences. Biological psychiatry. Neuropsychiatry ,Electroencephalography ,EEG-fMRI ,03 medical and health sciences ,Functional brain ,0302 clinical medicine ,Artificial Intelligence ,Component (UML) ,medicine ,Brain connectivity ,ICA ,Research Articles ,030304 developmental biology ,0303 health sciences ,Resting state fMRI ,medicine.diagnostic_test ,Applied Mathematics ,General Neuroscience ,Functional connectivity ,Human Connectome ,Independent component analysis ,Computer Science Applications ,ddc:616.8 ,Human connectome ,Connectome ,Functional magnetic resonance imaging ,Neuroscience ,030217 neurology & neurosurgery ,RC321-571 - Abstract
Concurrent electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) bridge brain connectivity across timescales. During concurrent EEG-fMRI resting-state recordings, whole-brain functional connectivity (FC) strength is spatially correlated across modalities. However, cross-modal investigations have commonly remained correlational, and joint analysis of EEG-fMRI connectivity is largely unexplored. Here we investigated if there exist (spatially) independent FC networks linked between modalities. We applied the recently proposed hybrid connectivity independent component analysis (connICA) framework to two concurrent EEG-fMRI resting-state datasets (total 40 subjects). Two robust components were found across both datasets. The first component has a uniformly distributed EEG frequency fingerprint linked mainly to intrinsic connectivity networks (ICNs) in both modalities. Conversely, the second component is sensitive to different EEG frequencies and is primarily linked to intra-ICN connectivity in fMRI but to inter-ICN connectivity in EEG. The first hybrid component suggests that connectivity dynamics within well-known ICNs span timescales, from millisecond range in all canonical frequencies of FCEEG to second range of FCfMRI. Conversely, the second component additionally exposes linked but spatially divergent neuronal processing at the two timescales. This work reveals the existence of joint spatially independent components, suggesting that parts of resting-state connectivity are co-expressed in a linked manner across EEG and fMRI over individuals., Author Summary Functional connectivity is governed by a whole-brain organization measurable over multiple timescales by functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). The relationship across the whole-brain organization captured at the different timescales of EEG and fMRI is largely unknown. Using concurrent EEG-fMRI, we identified spatially independent components consisting of brain connectivity patterns that co-occur in EEG and fMRI over subjects. We observed a component with similar connectivity organization across EEG and fMRI as well as a component with divergent connectivity. The former component governed all EEG frequencies while the latter was modulated by frequency. These findings show that part of functional connectivity organizes in a common spatial layout over several timescales, while a spatially independent part is modulated by frequency-specific information.
- Published
- 2019
- Full Text
- View/download PDF
50. Characterization of gravity waves in the lower ionosphere using VLF observations at Comandante Ferraz Brazilian Antarctic Station
- Author
-
Emilia Correia, Luis T.M. Raunheitte, José Valentin Bageston, and Dino Enrico D'Amico
- Subjects
Daytime ,Amplitude ,010504 meteorology & atmospheric sciences ,Gravitational wave ,Airglow ,Reflection (physics) ,Solstice ,Very low frequency ,Ionosphere ,Geodesy ,01 natural sciences ,Geology ,0105 earth and related environmental sciences - Abstract
The goal of this work is to investigate the gravity waves (GWs) characteristics in the low ionosphere using very low frequency (VLF) radio signals. The spatial modulations produced by the GWs affect the conditions of the electron density at reflection height of the VLF signals, which produce fluctuations of the electrical conductivity in the D-region that can be detected as variations in the amplitude and phase of VLF narrowband signals. The analysis considered the VLF signal transmitted from the US Cutler/Marine (NAA) station that was received at Comandante Ferraz Brazilian Antarctic Station (EACF, 62.1° S, 58.4° W), which is a great circle path crossing longitudinally the Drake Passage. The wave periods of the GWs detected in the low ionosphere are obtained using the wavelet analysis applied to the VLF amplitude. The use of the VLF technique was validated comparing the wave period and duration properties of one GW event observed simultaneously with a co-located airglow all-sky imager both operating at EACF. The statistical analysis of the wave periods detected using VLF technique for 2007 showed that the GW events occur almost all nights, with a higher frequency per month from March to October. The predominant wave periods are more frequent between 10 and 15 min occurring preferentially during the equinoxes, but there are some events with periods higher than 60 min appearing only in the solstices (January and July). These results show that VLF technique is a powerful tool to obtain the wave period and duration of GW events in the low ionosphere, with the advantage to be independent of sky conditions, and can be used during daytime and year-round.
- Published
- 2019
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.