A5011515080- Functional Brain Connectivity Studies
- EEG and Brain-Computer Interfaces
- Neural dynamics and brain function
- Advanced MRI Techniques and Applications
- Meta-analysis and systematic reviews
- Mental Health Research Topics
- Dementia and Cognitive Impairment Research
- Software-Defined Networks and 5G
- Heart Rate Variability and Autonomic Control
- Caching and Content Delivery
- Advanced Optical Network Technologies
- Intensive Care Unit Cognitive Disorders
- Neurological disorders and treatments
- Long-Term Effects of COVID-19
- Anomaly Detection Techniques and Applications
- Healthcare professionals’ stress and burnout
- Muscle activation and electromyography studies
- Stroke Rehabilitation and Recovery
- Time Series Analysis and Forecasting
- Network Traffic and Congestion Control
McGill University
2019-2024
Centro de Investigación Biomédica en Red de Enfermedades Respiratorias
2024
Instituto de Salud Carlos III
2024
Corporació Sanitària Parc Taulí
2024
Institute of Research and Innovation Parc Tauli
2024
Universitat Autònoma de Barcelona
2024
Centre for Interdisciplinary Research in Rehabilitation
2019-2021
Georgia Institute of Technology
2015
Abstract Background Flow starvation is a type of patient-ventilator asynchrony that occurs when gas delivery does not fully meet the patients’ ventilatory demand due to an insufficient airflow and/or high inspiratory effort, and it usually identified by visual inspection airway pressure waveform. Clinical diagnosis cumbersome prone underdiagnosis, being opportunity for artificial intelligence. Our objective develop supervised intelligence algorithm identifying deformation during square-flow...
Brain age prediction studies aim at reliably estimating the difference between chronological of an individual and their predicted based on neuroimaging data, which has been proposed as informative measure disease cognitive decline. As most previous relied exclusively magnetic resonance imaging (MRI) we hereby investigate whether combining structural MRI with functional magnetoencephalography (MEG) information improves using a large cohort healthy subjects (N = 613, 18–88 years) from Cam-CAN...
Human brain connectivity yields significant potential as a noninvasive biomarker. Several studies have used fMRI-based fingerprinting to characterize individual patterns of activity. However, it is not clear whether these mainly reflect neural activity or the effect physiological and motion processes. To answer this question, we capitalize on large data sample from Connectome Project rigorously investigate contribution aforementioned processes functional (FC) time-varying FC, well their...
Software-Defined Networking (SDN) has been recognized as the next-generation networking paradigm. It is a fast-evolving technology that decouples network control plane from data forwarding plane. A logically centralized controller responsible for all decisions and communication among elements. However, current traffic engineering techniques state-of-the-art routing algorithms do not effectively use merits of SDNs, such global visibility, decoupling, management simplification portability. In...
Abstract Motor performance decline observed during aging is linked to changes in brain structure and function, however, the precise neural reorganization associated with these remains largely unknown. We investigated neurophysiological correlates of this by quantifying functional effective network connectivity elderly individuals ( n = 11; mean age 67.5 years), compared young adults 12; 23.7 while they performed visually‐guided unimanual bimanual handgrips inside magnetoencephalography (MEG)...
Background: Intensive care unit (ICU) admission and invasive mechanical ventilation (IMV) are associated with psychological distress trauma. The COVID-19 pandemic brought it a series of additional long-lasting stressful traumatic experiences. However, little is known about comorbid depression post-traumatic stress disorder (PTSD).
Abstract Human brain connectivity yields significant potential as a noninvasive biomarker. Several studies have used fMRI-based fingerprinting to characterize individual patterns of activity. However, it is not clear whether these mainly reflect neural activity or the effect physiological and motion processes. To answer this question, we capitalize on large data sample from Connectome Project rigorously investigate contribution aforementioned processes functional (FC) time-varying FC, well...
Music-supported therapy (MST) follows the best practice principles of stroke rehabilitation and has been proven to instigate meaningful enhancements in motor recovery post-stroke. The existing literature established that efficacy specificity MST relies on reinforcement auditory-motor functional connectivity related brain networks. However, date, no study attempted evaluate underlying cortical network nodes are key In this case series, we evaluated changes within upper extremity function...
A bstract Functional brain connectivity measures extracted from resting-state functional magnetic resonance imaging (fMRI) scans have generated wide interest as potential noninvasive biomarkers. In this context, performing global signal regression (GSR) a preprocessing step remains controversial. Specifically, while it has been shown that considerable fraction of variations is associated with physiological and motion sources, GSR may also result in removing neural activity. Here, we address...
Abstract In this work, we investigated the regional characteristics of dynamic interactions between oscillatory sources ongoing neural activity obtained using electrophysiological recordings and corresponding changes in BOLD signal simultaneous EEG-fMRI measurements acquired during a motor task, as well under resting conditions. We casted problem within system-theoretic framework, where initially performed distributed EEG source space reconstruction subsequently employed block-structured...
Neural populations coordinate at fast subsecond time-scales during rest and task execution. As a result, functional brain connectivity assessed with different neuroimaging modalities (EEG, MEG, fMRI) may also change over time scales. In addition to the more commonly used sliding window techniques, General Linear Kalman Filter (GLFK) approach has been proposed estimate time-varying connectivity. present work, we propose modification of GLFK model We systematic method select hyper-parameters...
Abstract Over the last few years, an increasing body of evidence points to hemodynamic response function as important confound resting-state functional connectivity. Several studies in literature proposed using blind deconvolution fMRI data retrieve HRF, which can be subsequently used for deblurring. A basic hypothesis these is that relevant information brain dynamics condensed discrete events resulting large amplitude peaks BOLD signal. In this work, we showed activity, addition larger...
Abstract Brain age prediction studies aim at reliably estimating the difference between chronological of an individual and their predicted based on neuroimaging data, which has been proposed as informative measure disease cognitive decline. As most previous relied exclusively magnetic resonance imaging (MRI) we hereby investigate whether combining structural MRI with functional magnetoencephalography (MEG) information improves using a large cohort healthy subjects ( N =613, 18-88 yrs) from...