A5062820435- Functional Brain Connectivity Studies
- Neural dynamics and brain function
- EEG and Brain-Computer Interfaces
- Optical Imaging and Spectroscopy Techniques
- Traumatic Brain Injury and Neurovascular Disturbances
- Advanced MRI Techniques and Applications
- Heart Rate Variability and Autonomic Control
- Mathematical Biology Tumor Growth
- Cardiovascular Health and Disease Prevention
- Gene Regulatory Network Analysis
- Advanced Neuroimaging Techniques and Applications
- Control Systems and Identification
- Neuroscience of respiration and sleep
- Cancer Cells and Metastasis
- Diabetes Management and Research
- Blind Source Separation Techniques
- Neuroscience and Neural Engineering
- Neural Networks and Applications
- Cellular Mechanics and Interactions
- Diabetes and associated disorders
- Pancreatic function and diabetes
- Non-Invasive Vital Sign Monitoring
- Hemodynamic Monitoring and Therapy
- Cancer Genomics and Diagnostics
- 3D Printing in Biomedical Research
McGill University
2015-2024
Basilea Pharmaceutica (Switzerland)
2022
Laboratoire d’Imagerie Biomédicale
2022
Cell and Tissue Systems (United States)
2022
University of Cyprus
2010-2019
Zhejiang University
2019
Montreal Neurological Institute and Hospital
2018
Aristotle University of Thessaloniki
2011
Frederick University
2011
University of New Mexico
2011
Neuroscientific studies exploring real-world dynamic perception often overlook the influence of continuous changes in narrative content. In our research, we utilize machine learning tools for natural language processing to examine relationship between movie narratives and neural responses. By analyzing over 50,000 brain images participants watching Forrest Gump from studyforrest dataset, find distinct states that capture unique semantic aspects unfolding story. The default network,...
The effect of spontaneous beat-to-beat mean arterial blood pressure fluctuations and breath-to-breath end-tidal CO2 on cerebral flow velocity variations is studied using the Laguerre-Volterra network methodology for multiple-input nonlinear systems. observations made from experimental measurements ten healthy human subjects reveal that, whereas explain most high-frequency (above 0.04 Hz), as well interactions between have a considerable in lower frequencies (below Hz). They also indicate...
Abstract Introduction Recent studies related to assessing functional connectivity (FC) in resting‐state magnetic resonance imaging have revealed that the resulting patterns exhibit considerable fluctuations (dynamic FC [dFC]). A widely applied method for quantifying dFC is sliding window technique. According this method, data are divided into segments with same length (window size) and a correlation metric employed assess within these segments, whereby size often empirically chosen. Methods...
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...
The degree of motor impairment and profile recovery after stroke are difficult to predict for each individual. Measures obtained from clinical assessments, as well neurophysiological neuroimaging techniques have been used potential biomarkers recovery, with limited accuracy up date. To address this, the present study aimed develop a deep learning model based on structural brain images participants healthy volunteers. following inputs were in multi-channel 3D convolutional neural network...
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...
Abstract Background Dynamic functional connectivity (dFC) has become an important measure for understanding brain function and as a potential biomarker. However, various methodologies have been developed assessing dFC, it is unclear how the choice of method affects results. In this work, we aimed to study results variability commonly used dFC methods. Methods We implemented 7 assessment methods in Python them analyze magnetic resonance imaging data 395 subjects from Human Connectome Project....
The effects of orthostatic stress, induced by lower body negative pressure (LBNP), on cerebral hemodynamics were examined in a nonlinear context. Spontaneous fluctuations beat-to-beat mean arterial blood (MABP) the finger, flow velocity (MCBFV) middle artery, as well breath-by-breath end-tidal CO 2 concentration (Pet ) measured continuously 10 healthy subjects under resting conditions and during graded LBNP to presyncope. A two-input Laguerre-Volterra network model was employed study dynamic...
The combination of mathematical modeling and optimal control techniques holds great potential for quantitatively describing tumor progression treatment planning. Hereby, we use a Gompertz-type growth law pharmacokinetic-pharmacodynamic approach the effects drugs on in bearing mice, combine these order to design therapeutic patterns. Specifically, describe colon cancer both untreated mice as well treated with widely used anticancer agents. We also present pharmacokinetic model kinetics body...
It is well known that the blood oxygen level-dependent (BOLD) signal measured by functional magnetic resonance imaging (fMRI) influenced-in addition to neuronal activity-by fluctuations in physiological signals, including arterial CO2, respiration and heart rate/heart rate variability (HR/HRV). Even spontaneous of aforementioned signals have been shown influence BOLD fMRI a regionally specific manner. Related this, estimates connectivity between different brain regions, performed when...
We present a random forest (RF) classification and regression technique to predict, intraoperatively, the unified Parkinson's disease rating scale (UPDRS) improvement after deep brain stimulation (DBS). hypothesized that data-informed combination of features extracted from intraoperative microelectrode recordings (MERs) can predict motor patients undergoing DBS surgery. modified employed RFs account for unbalanced datasets multiple observations per patient, showed, first time, only five...
Parameters describing dynamic cerebral autoregulation (DCA) have limited reproducibility. In an international, multi-centre study, we evaluated the influence of multiple analytical methods on reproducibility DCA. Fourteen participating centers analyzed repeated measurements from 75 healthy subjects, consisting five minutes spontaneous fluctuations in blood pressure (BP) and flow velocity (CBFv) signals, based their usual analysis. DCA- were grouped into three broad categories, depending...
The immune response against a tumor is characterized by the interplay among components of system and neoplastic cells. Here, we bioprinted model with two distinct regions containing gastric cancer patient-derived organoids (PDOs) tumor-infiltrated lymphocytes (TILs). initial cellular distribution allows for longitudinal study TIL migratory patterns concurrently multiplexed cytokine analysis. chemical properties bioink were designed to present physical barriers that T-cells must breech during...