The research interest of Prof. Benali is motivated by innovative and valid methodological approaches to studying normal aging and pathological processes in the context of a variety of neurological conditions representing critical public health issues. It develops an integrated biomedical approach, ranging from the basic mathematical modelling of the brain's anatomo-functional circuits and their normal and pathological dynamics to the physiological model of brain activity observed by neuroimaging tools allowing us to translate models from normal aging to clinical populations.
Dr. Moutuou's research interests focus on the mathematical foundations of Network Neuroscience. He has used concepts from Algebraic Topology, Algebraic Quantum Mechanis, and Complex Systems to develop a novel mathematical framework and computational tools for analysing the topology and dynamics of the anatomo-functional networks of the human brain activities.
Dr. Jeancolas main project, done in collaboration with Paris Brain Institute (ICM) and IM2A, focuses on multimodal predictive modeling of Alzheimer’s disease (INSIGHT cohort). Specifically, Laetitia studies the neurovascular coupling in participants with subjective memory loss. She is also specialized in the analysis of voice impairments in neurodegenerative diseases and their use for automatic and early detection and disease monitoring. Her research interests are wide-ranging, – centering around the use of signal processing, machine learning and neuroimaging techniques for the early detection of neurodegenerative diseases and the understanding of their mechanisms.
Arsalan Rahimabadi is a Ph.D. candidate in the Electrical and Computer Engineering Department at Concordia University. His current research is focused on modeling tauopathy progression in the brain. He has expertise in dynamical systems analysis, pathological nonlinear systems, modeling, identification, control theories, and fault detection and isolation methods.
M. Sharifzadeh is currently pursuing his Ph.D. degree in Electrical and Computer Engineering with Concordia University, Montreal, QC, Canada, co-supervised by Dr. Habib Benali and Dr. Hassan Rivaz. He is a member of IMage Processing And Characterization of Tissue (IMPACT), as well as Biomedical Imaging for Healthy Aging laboratories, and his current research is mainly focused on improving the performance of the ultrasound modality for biomedical applications by employing deep learning approaches.
Neurovascular coupling and blood flow physiological mechanisms in stroke
Shima is a graduate research assistant (MASc.) at Biomedical Healthy Aging Lab. She joined the Lab in September 2021 to work on a multimodal approach for investigating motor skill learning (MSL) induced plasticity in the human brain. In this study, the relationship between MSL, spatiotemporal patterns of neural activity, and glutamate (the main excitatory transmitter in the central nervous system) activity is assessed across at least one sleep-wake cycle. Accordingly, we acquire bimodal EEG-MRS and EEG-fMRI data to establish regional relationships between glutamate concentrations as captured by MRS and changes in neural activity as captured by EEG and fMRI.
Giridhar Sunil is a MaSc candidate in the Electrical and Computer Engineering Department at Concordia University. His current research is focused on analysising the patterns in the synaptic and extrasynaptic connections of C. Elegans. He has expertise in Machine Learning and Deep learning, Software engineering, Data analysis and Computer Vision.
Kiana Ezzatdoost is a MASc student in Electrical and Computer Engineering at Concordia University under the supervision of Dr. Habib Benali. Her research revolves around investigating the brain’s various functionality patterns by processing biological signals. Kiana is currently analyzing Magnetic Resonance Spectroscopy (MRS) and Electroencephalography (EEG) signals to trace short-term memory via the metabolism in a circadian rhythm, particularly glutamate level variation, following a motor sequence learning task. In addition to biological signal processing, her other areas of interest comprise mathematical modelling and artificial intelligence..
Faezeh Sohrabi is currently a master student of Biomedical Engineering in the department of Electrical & Computer Engineering at Concordia University under supervision of Prof. Habib Benali. Her current research project is to quantify the energy metabolism of the brain using Magnetic Resonance Spectroscopy imaging, which is a non-invasive method for recording brain parameters. In this way, she analyzes and models the relationship between lactate concentration and glucose uptake in the brain under the influence of exercise.
Niusha is currently pursuing her MSc. degree in Electrical and Computer Engineering at Concordia University, Montreal, QC, Canada, under the supervision of Professor Benali. Her current research is mainly focused on the early detection of Alzheimer’s disease using speech and language impairment.
Shirin is a Master’s student in Electrical and Computer Engineering at Concordia University. She joined Professor Habib Benali’s research team in September 2020 to conduct research in “Sleep Conditions and Circadian Rhythm” subject. For this research, she should analyze data obtained from functional Magnetic Resonanse Imaging (fMRI) technique in order to investigate the relationships between different factors such as total integration, melatonin, functional connectivity, etc.
Habib Benali
Professor
Department of Electrical and Computer Engineering
Canada Research Chair in Biomedical Imaging and Healthy Aging
Member, Applied AI Institute
(514) 848-2424
habib.benali@concordia.ca