Introduction

Clyde is a MASc student who joined the Biomedical Imaging for Healthy Aging Laboratory in January 2020. He has also been part of the Image Processing and Characterization of Tissue Laboratory under the supervision of Dr. Hassan Rivaz since 2018, as an Undergraduate Research Assistant. He is currently co-supervised by Dr. Habib Benali and Dr. Hassan Rivaz. His current research project is concerned with Alzheimer disease (AD), a neurodegenerative disease that causes cognitive decline and reduces the quality of life. His work involves identifying, analyzing, and modeling the relationships between tau protein deposition in neurons and gray matter reductions in AD patients. Demystifying these relationships is conducive to developing accurate models for detecting AD at an early stage, a task that remains difficult with current diagnostic approaches.

Educational Background

Clyde received his BEng. In Electrical Engineering, with distinction, from Concordia University in 2020. Clyde currently holds multiple awards: the Alexander Graham Bell Canada Graduate Scholarship - Master’s Program award, two NSERC USRA awards, two FRQNT supplement of the NSERC awards, the Concordia Merit Scholarship, and two engineering design project awards namely the Electrical Engineering Product Design Project in 2018 (First Place) and the Undergraduate Capstone Project in 2019 (Honorable Mention).

Other Curriculum

As an undergraduate student, Clyde had involvement in various student societies in which he served as the Director of Flight Operations with UAV Concordia from 2017-2018 and as the Director of Laboratory Services with IEEE Concordia from 2019-2020. He was a student member of the PERFORM Centre Student Scientific Events Sub-Committee from 2020-2021. He was appointed as the Chair of the PERFORM Student Action Committee (PSAC) since November 2021 and is presently

Research and publications

JOURNAL PAPERS

1. N. Masoumi, C. J. Belasso, M. O. Ahmad, Y. Xiao and H. Rivaz, “Multimodal 3D ultrasound and CT in image-guided spinal surgery: public database and new registration algorithms”, in International Journal of Computer Assisted Radiology and Surgery (IJCARS), 2021, https://doi.org/10.1007/s11548-021-02323-2.

2. C. J. Belasso, B. Behboodi, H. Benali, M. Boily, H. Rivaz and M. Fortin, “LUMINOUS database: lumbar multifidus muscle segmentation from ultrasound images”, in BMC musculoskeletal disorders, 2020, https://doi:10.1186/s12891-020-03679-3.

3. M. Ashikuzzaman, C. Belasso, M. G. Kibria, A. Bergdahl, C. J. Gauthier and H. Rivaz, “Low Rank and Sparse Decomposition of Ultrasound Color Flow Images for Suppressing Clutter in Real-Time”, in IEEE Transactions on Medical Imaging (IEEE TMI, Impact factor 7.82), 2019, pp. 1073-1084, https://doi.org/10.1109/TMI.2019.2941865.

CONFERENCE PAPERS

1. B. Behboodi, M. Fortin, C. J. Belasso, R. Brooks and H. Rivaz,“Receptive Field Size as a Key Design Parameter for Ultrasound Image Segmentation with U-Net”, in IEEE Engineering in Medicine and Biology Society (EMBC), 2020, https://doi.org/10.1109/EMBC44109.2020.9175846.

2. M. Ashikuzzaman, C. Belasso, C. J. Gauthier and H. Rivaz, “Suppressing Clutter Components In Ultrasound Color Flow Imaging Using Robust Matrix Completion Algorithm: Simulation And Phantom Study”. in IEEE International Symposium on Biomedical Imaging (IEEE ISBI), 2019, pp. 745-749, https://doi.org/10.1109/TMI.2019.2941865.

Selected publications

• Topology and spectral interconnectivities of higher-order multilayer network. E. M., OBK. Ali, H. Benali, Front. Complex Syst., 2023
• Foundations of topological racks and quandles. M. Elhamdadi, E.M. Journal of Knot Theory and Its Ramifications, 2016.
• Graded Brauer groups of a groupoid with involution. E.M., 2014, Journal of Functional Analysis.

Introduction

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.

Educational Background

Faezeh received her BS.c (2018) degree in Biomedical Engineering from Hamedan University of Technology. She won first place in the IEEE Ingenious Project Competition (2018) for the B.Sc. thesis and the Best Researcher Award (2019) among all bachelor students of Hamadan University of Technology.

Selected Publications:

F. Sohrabi and M.B. Khodabakhshi, 2019. The trajectory intersection: An approach for nonlinear down-sampling. Chaos, Solitons & Fractals, v124, pp.10-17.

Contact Information:

Office-Mail: faezeh.sohrabi@concordia.ca

In a nutshell

Prof. Benali aims to develop educational programs in advanced information acquisition and processing for promoting good health.

Research interest

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.

Background

After receiving my PhD in Computer Science, Multidimensional data analysis from Rennes I University in 1985, France, I later went on to join the French National Institute of Health and Medical Research (INSERM) in 1989. From 2008 to 2013, I served as Head of the Laboratory of Functional Imaging (INSERM U678 unit with over 65 members) and Deputy Director of the Biomedical Imaging Laboratory, INSERM - The National Center for Scientific Research (CNRS) and UPMC University until 2015. Together with Dr. Julien Doyon, from the Université de Montréal (UdeM), I founded and became co-director of the International Laboratory of Neuroimaging and Modelisation of the INSERM-UPMC and UdeM administrative bodies in 2007. I have been a regular research member of the Centre de Recherche Mathématiques of UdeM since 2002 and a researcher at Centre de Recherche de l’Institut Universitaire de Gériatrie de Montréal, UdeM, since 2005. Moreover, I was co-PI of the IHU-A-ICM “Institut des Neurosciences Translationnelles de Paris” project (55M euros) which lead to the creation of one of the largest cognitive, clinical neuroscience and technology research center in France. I have established and directed a large research laboratory and have been collaborating with leaders in their fields in clinical and basic research as well as in engineering in Canada and around the world (Harvard Medical School, University of Texas at Dallas, Johns Hopkins University, National Institute of Health, UdeM, McGill, University of Liege, French Alternative Energies and Atomic Energy, CNRS and INSERM).

I am currently Scientific Director of the PERFORM Centre, NSERC CRC Tier 1 in Biomedical Imaging and Healthy Aging and Professor at the Faculty of Engineering and Computer Science at Concordia University. A natural collaborator with an extensive network world-wide, I have been instrumental in solidifying the PERFORM Centre’s role in fostering interdisciplinary research collaborations between numerous departments and faculties across Concordia University as well as with many inter-institutional research networks locally, nationally, and internationally. This served to farther solidify PERFORM’s reputation in advancing health research and fostering innovative and dynamic research collaborations thus positioning the Centre to serve as a vehicle for a School of Health created in 2023.

In the last 30 years, I have gone from starting a new neuroimaging research activity to directing a productive laboratory in France and Canada with activities that span from the development of new computational modeling and multimodal image analysis techniques to cognitive neuroscience and clinical applications. During this productive time in my scientific career, I published more than 300 papers. I supervised more than 80 students and fellows, including some that now became professors and researchers themselves and have scientific careers. In addition to my scientific work, I have also developed technology transfer activities. I have collaborated with several private companies over the past years and helped to found two start-up companies with my former students. In this regard, I have been an author on five patents on image processing devices. I have been awarded several grants from CFI-JELF, NSERC CRC Ter1, Concordia grants, CIHR, Alzheimer Research Foundation, as well as from national (France), European and international agencies, and a variety of companies. In 2019, I have been awarded the Provost‘s Circle of Distinction from Concordia University.

I am Associate Editor for Brain Imaging Methods – Frontiers in Neuroscience. I served as a member of the expert panel of FLAG-ERA, an umbrella organization that unites most funding organisations in Europe, and was an expert member of the French National Research Agency and numerous internal and external committees and boards including, Baycrest Academy for Research and Education Advisory Committee; Executive Committee of the Quebec Biomedical Imaging Network – FRQS; and Chair of the executive committee, to list but a few.

Introduction

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.

Educational background

Kiana has pursued her undergraduate studies at Sharif University of Technology. In 2018, she joined the Augmented Intelligence Research lab (AIRLab), where she conducted several research projects on the human olfactory system. Her projects included building a portable olfactometer, developing a nonlinear EEG classifier and examining the olfactory response as a biomarker for Alzheimer’s Disease (AD). Kiana currently holds the Recruitment Scholarship from Quebec Bio-Imaging Network, the In-course award and the Split Merit Scholarship from Concordia University, and two parts of an NSERC award.

Research and Publications

1. K.Ezzatdoost, H.Hojjati, H.Aghajan: “Decoding Olfactory Stimuli EEG Data Using Nonlinear Features: A Pilot Study”, Journal of Neuroscience Methods, 2020, DOI: 10.1016/j.jneumeth.2020.108780.

2. M.J.Sedghizadeh, H.Hojjati, K.Ezzatdoost, H.Aghajan, Z.Vahabi, H.Tarighatnia: “Olfactory Response as a Marker for Alzheimer’s Disease: Evidence from Perceptual and Frontal Oscillation Coherence Deficit”, PLOS One, 2020, DOI: 10.1371/journal.pone.0243535.

3. H.Hojjati, M.J.Sedghizadeh, K.Ezzatdoost, A.Afsharrad, H.Aghajan, “ An Inexpensive Portable Olfactometer for Event-Related Potential Experiments”, IEEE Austria International Biomedical Engineering Conference (AIBEC 2019), 2019, Vienna, Austria.

Useful links

For further information about Kiana's publications, visit the following link: https://Kiana’searchgate.net/profile/Kiana-Ezzatdoost Contact information Email: ki.ezzatdoost@gmail.com, kiana.ezzatdoost@mail.concordia.ca

Introduction

Laetitia Jeancolas is currently a postdoctoral fellow at Concordia University. Her 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.

Educational Background

Laetitia Jeancolas is a former student of Ecole Normale Supérieure where she attended a selective program in fundamental physics and received a Master of Science degree in cognitive science. In 2019, she obtained her PhD in signal processing at Télécom SudParis (Paris-Saclay University), in collaboration with ICM. She received the Best PhD award of the Futur & Ruptures Program by the Fondation Mines Télécom, along with several other awards during her PhD.

Professional background

During her studies, Laetitia Jeancolas worked on several research projects, such as the development of a cognition model in the University of Arizona (USA), or the study of tool use acquisition in infants, at Integrative Neuroscience and Cognition Center (former Laboratoire Psychologie de la Perception, Paris V). She did her M.S research project on brain effective connectivity in early stages of Alzheimer's disease during memory tasks, at ICM and Grenoble Institut des Neurosciences (GIN).

During her PhD, Laetitia Jeancolas worked on the early detection of Parkinson's disease (PD) using voice analysis. She designed the experimental protocol, set up the acquisition tools, collected the data and conducted the analyses. One of the main innovative analyses consisted in adapting a recent deep learning feature extraction technique used in speaker recognition to PD detection. Laetitia also implemented face recordings, to analyze PD hypomimia in the same cohort, as well as a task based functional MRI protocol that enables the investigation of the neural disruptions causing the early PD speech impairments.

She expanded her PhD work during a postdoc at ICM where she focused more precisely on the neural correlates of the Parkinson-related voice impairments. Since, she has continued to work in this field through several collaborations with ICM, Télécom SudParis, Lille university, McGill university and Concordia university, supervising several PhD students, and M.S. research projects, on Parkinson and Alzheimer’s speech impairments and PD hypomimia.

Selected Publications

• Jeancolas, L., et al., (2022) « Voice Characteristics from Isolated Rapid Eye Movement Sleep Behavior Disorder to Early Parkinson’s Disease ». Parkinsonism & Related Disorders 95 : 86‑91. https://doi.org/10.1016/j.parkreldis.2022.01.003.

• Jeancolas L., et al., (2021) « X-Vectors: New Quantitative Biomarkers for Early Parkinson’s Disease Detection From Speech ». Frontiers in Neuroinformatics 15. https://doi.org/10.3389/fninf.2021.578369.

• Jeancolas L., et al., (2019) « Comparison of Telephone Recordings and Professional Microphone Recordings for Early Detection of Parkinson’s Disease, Using Mel-Frequency Cepstral Coefficients with Gaussian Mixture Models ». In Interspeech 2019, 3033‑37. Graz, Austria: ISCA. https://doi.org/10.21437/Interspeech.2019-2825.

• Jeancolas L., et al., (2022) « Can Infants Generalize Tool Use From Spoon to Rake at 18 Months? » Journal of Motor Learning and Development, 2022, 1‑17. https://doi.org/10.1123/jmld.2022-0006.

Videos

• Parkinson's disease detection using voice analysis: https://www.youtube.com/watch?v=uJuBqR0duhw

• 5-min PhD summary: https://www.youtube.com/watch?v=mtt8W1wU8Ig

• Fondation Recherche Alzheimer's video on my postdoc project: https://www.youtube.com/watch?v=LXPOjGPjCoQ

Contact

Email: laetitia.jeancolas@concordia.ca

Introduction

Milad is currently a master’s student in electrical engineering program at Concordia University. He joined the lab in 2019 and since then he has been working on mathematical modeling of lactate metabolism in the brain. Particularly, his work includes developing a system of ordinary differential equations for exploring lactate dynamics, as a possible energy fuel, in the interface of neurons, astrocytes, extracellular space and capillaries and analyzing it in resting and activation.

Educational background

Milad completed his B.Sc. degree in electrical engineering (communications) at the University of Tehran in 2018. In his thesis, he investigated the possibility of predicting epileptic seizures by processing and classification of EEG signals based on their dynamical chaotic properties.

Other curriculum

Milad has been a member of the PERFORM student scientific event sub-committee since 2020.

Useful links:

Personal website https://sites.google.com/view/misoltan/home Linkedin: https://www.linkedin.com/in/milad-soltanzadeh-037300a9

Introduction

He 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.

Educational Background

He received his B.S. and M.S. (as the first-ranked student) degrees in Electrical Engineering - Communication Systems from Iran University of Science and Technology, Tehran, Iran, in 2013 and 2016, respectively, and holds the Concordia International Tuition Award of Excellence during Ph.D. M.S. Thesis: Multimodal Image Registration with Incorporating Intensity and Geometric Information of Phase. B.S. Thesis: Design and implementation of a GSM/GPRS/GPS-based vehicle tracker. Professional background – He worked for two years as a full-time Software Developer (.NET and C#)

Publications:

1. Sharifzadeh, M., Benali, H. and Rivaz, H., 2022. Investigating Shift Variance of Convolutional Neural Networks in Ultrasound Image Segmentation. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 69(5), pp.1703-1713. IEEE Xplore
2. Sharifzadeh, M., Benali, H. and Rivaz, H., 2020. Phase Aberration Correction: A Convolutional Neural Network Approach. IEEE Access, 8, pp.162252-162260. IEEE Xplore
3. Tehrani, A.K., Sharifzadeh, M., Boctor, E. and Rivaz, H., 2022. Bi-Directional Semi-Supervised Training of Convolutional Neural Networks for Ultrasound Elastography Displacement Estimation. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 69(4), pp.1181-1190. IEEE Xplore, arXiv
4. Sharifzadeh, M., Benali, H. and Rivaz, H., 2021, September. An Ultra-Fast Method for Simulation of Realistic Ultrasound Images. In 2021 IEEE International Ultrasonics Symposium (IUS) (pp. 1-4). IEEE. IEEE Xplore, arXiv
5. Sharifzadeh, M., Tehrani, A.K., Benali, H. and Rivaz, H., 2021, September. Ultrasound Domain Adaptation Using Frequency Domain Analysis. In 2021 IEEE International Ultrasonics Symposium (IUS) (pp. 1-4). IEEE. IEEE Xplore, arXiv
6. Sharifzadeh, M., Benali, H. and Rivaz, H., 2021, September. Shift-invariant segmentation in breast ultrasound images. In 2021 IEEE International Ultrasonics Symposium (IUS) (pp. 1-4). IEEE. IEEE Xplore
7. Sharifzadeh, M., Benali, H. and Rivaz, H., 2021. Abnormality Segmentation in Brain MRI: U-Net Is Not Shift-Invariant. The Organization for Human Brain Mapping (OHBM).
8. Sharifzadeh, M., Benali, H. and Rivaz, H., 2020. Skull aberration correction in ultrasound brain imaging. The Organization for Human Brain Mapping (OHBM).

Introduction

She 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.

Educational Background

She received her bachelor’s degree in Computer engineering as the third best student at Kermanshah University of Technology in 2018.

As her B.S. thesis she:

• Designed and synthesized digital circuits for a biological neuron model and CPG
• Proposed an efficient digital architecture for a biological neuron model
• Employed Verilog Hardware Description Language (HDL) to design the digital architecture
• Simulated the design using Modalism software
• Compiled and synthesized the design using Quartus Prime Altera compiler

Professional background

After her graduation she worked as a microcontroller programmer and developer in Rasa Zagros company for 2 years.

Publications

Behzad Moradi, and Majid Ahmadi. "Digital Hardware Implementation of a Biological Central Pattern Generator." 2018 IEEE 61st International Midwest Symposium on Circuits and Systems (MWSCAS). IEEE, 2018.

Introduction

Astrocytes, a major type of glia, possess assorted structural and functional properties making them inseparable from their neighbouring neurons. However, most published computational models of whole-brain activity, if not all, remain focused on neurons while ignoring astrocytes. We herewith introduce a biophysical model built upon neural network mass and compartmental modelling techniques, where large-scale astrocytic and neuronal networks couple their activity through glutamatergic and GABAergic transmission systems. We formulate a network scheme where neural dynamics are constrained by a two-layered structural network interconnecting either astrocytic or neuronal populations, and we ask how astrocytic networks contribute to whole-brain activity and emerging functional connectivity patterns. By developing a biologically plausible simulation approach based on bifurcation and multilayer network theories, we demonstrate that astrocytic and neuronal networks engage in a dialogue over fast and slow fluctuations or over phase-based and amplitude-based network connectivity. Our study is a step forward for more thoroughly investigating the role of glia alongside neurons in health or disease conditions.

Educational Background

Publications

• Ü Aydin, G Pellegrino, OBK Ali, C Abdallah, F Dubeau, JM Lina, E Kobayashi, C Grova (2020). Magnetoencephalography resting state connectivity patterns as indicatives of surgical outcome in epilepsy patients. J. Neural Eng. 17 035007

• Cross NE, Pomares FB, Nguyen A, Perrault AA, Jegou A, Uji M, K Lee, F Razavipour, OBK Ali, U Aydin, H Benali, C Grova, TT Dang-Vu (2021) An altered balance of integrated and segregated brain activity is a marker of cognitive deficits following sleep deprivation. PLoS Biol 19(11): e3001232. https://doi.org/10.1371/journal.pbio.3001232

• OBK Ali, A Vidal, C Grova, H Benali. Glial glutamate regulation, critical determinant of whole brain physiology: a computational study. Universite d’evry, France

• F Mohammadi, JP Soucy, P Rosa-Neto, TA Pascoal, OBK Ali, A Rahimabadi, M Savard, FZ Lussier, MS Kang, J Therriault, H Benali. Relationship between brain distributions of tau and atrophy to brain regional connectivity. Alzheimer's Association International Conference, 2020

• Soucy, J., Razavipour, F., Ali, O., Bin, K. B., Lee, K., Blinder, S., ... & Grova, C. (2022). Multiresolution metabolic profile of functional hubness in the resting human brain. In journal of cerebral blood flow and metabolism, vol. 42, no. 1_ suppl, pp. 157-158

Introduction

Stroke can induce irreversible lesions, disrupting cerebral blood flow (CBF) even beyond the necrotic zone: in the perilesional tissues (PLT). Neurovascular coupling is largely based on blood flow physiological mechanisms, whose estimation is crucial in the context of brain activity detection model used in functional MRI (fMRI). The presence of a chronic lesion therefore questions the detection of brain activity in PLT. In addition, brain plasticity mechanisms are playing a crucial role in post-stroke functional recovery and can occur in PLT. Former studies showed a decreased CBF in PLT, but there is no consensus about the best way to define PLT, any criteria to determine inhomogeneous properties within the PLT or either solution to include them in classical fMRI analysis. To explore these issues, the first research study, presented in this thesis, was conducted on thirteen post stroke participants in chronic phase to investigate the PLT properties through a multimodal MRI protocol. Arterial spin labeling (pcASL) was used to map CBF; fMRI was acquired at resting state, to get the spontaneous hemodynamic time courses and thereby compute brain homotopic functional connectivity. The data were processed in each patient native space. Lesions were manually demarcated, and brain parts were segmented to extract the information from regions of interest. When normalized with homologous control brain regions, results can be related to the distance from the lesion and fitted with linear model. In other words, the further the PLTs from the lesion, the better the CBF and the brain functional connectivity recovers. Moreover, we demonstrated that gradient of perfusion and gradient of homotopic connectivity are highly correlated together in approximately 80% of the remaining tissue of the ipsilateral hemisphere. Those highlighted patterns suggest that, instead of rejecting the PLT tissue, an adjustment of neurovascular model, used in fMRI, could be applied to stroke population

Educational Background

• Since 2015: PhD in BioSciences: Image processing & Computer Sciences.

• 2013-2015:Research Engineer, ICM, Paris, France

• 2013 Master degree, UPEC, honors, Signal & Image for Medicine, University Paris Est Creteil.

• 2008-2012 Engineer school, ISBS Paris. Majors: Image processing - Bio-informatics - Drug Discovery

Publications

• Berroir, P., Ghazi-Saidi, L., Dash, T., Adrover-Roig, D., Benali, H., and Ansaldo, A. I. (2016). In- terference control at the response level : Functional networks reveal higher efficiency in the bilingual brain. Journal of Neurolinguistics.

• Philippe, A.-C., Berroir, P., Bardinet, E., Vidailhet, M., and Lehericy, S. (2015). Basal ganglia func- tional parcellation into specific and overlapping territories with resting state f-mri. In Biomedical Imaging(ISBI), 2015 IEEE 12th International Symposium on, pages 1352–1355. IEEE.

• Durand, E., Berroir, P., & Ansaldo, A. I. (2018). The Neural and Behavioral Correlates of Anomia Recovery following Personalized Observation, Execution, and Mental Imagery Therapy: A Proof of Concept. Neural Plasticity, 2018, e5943759. https://doi.org/10.1155/2018/5943759

Introduction

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.

Shima is responsible for data acquisition as a protocol coordinator and data analysis of EEG-MRS where she will quantify the temporal dynamics of cortical glutamate associated with sleep-dependent consolidation of newly acquired motor memories during the first night of sleep following MSL, so as to correlate glutamate dynamics to whole-brain network dynamics across sleep stages.

Previously, Shima had 3.5 years of experience in the medical industry as a Clinical Application and Sales Specialist where she had the responsibility to introduce and demonstrate the ultrasound machines of Mindray to radiologists in different hospitals and imaging clinics in numerous cities of Iran.

She completed her B.Sc. in Science and Research Branch of Azad University in the field of Biomedical Engineering with a background in Bio-signal Processing.

Publications

• Shima Panahi Moghadam, Saeid Rashidi, "Implementation of Artificial Features in Improvement of Biometrics Based PPG", 6th International Conference on Computer and Knowledge Engineering, Ferdowsi University of Mashhad, Mashhad, Iran (accepted and indexed by IEEE).

Introduction

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.

Educational Background

Shirin has received her B.Sc. degree in Electrical Engineering – Electronics from Azad University – Central Tehran Branch in 2017. Artificial Neural Network was one of her main research interests. So, she worked on “Human Authentication based on PPG using ANN” for her B.Sc. thesis.

Professional background

Soon after graduation, she worked as an “IoT Developer” for two years for Mediana Co. and before traveling to Canada for higher education, she was hired by Niroo Research Institute and conducted research on “Battery Management Systems in Electric Vehicles”.

Other Curriculum

As she is an active person, during her bachelor studies, she joined IEEE student branch of her university and later, she became the chairwoman of the student branch and organized many educational and cultural events for the students and also, children.

In a nutshell

I am currently pursuing my BS- MS degree (2019-2024) at IISER Kolkata. I am a fourth-year student with Mathematics Major and Biology Minor. I am currently working on Neuronal Dynamics, Games and Rationality, and Epidemic spread. <

EDUCATION

1. 10th Standard: 96.4% from WBBSE (Rank-16)
2. 12th Standard: 95.4% from WBCHSE (Rank- 19)
3. CGPA- 9.13/10 (After 3rd Year)

SCHOLARSHIPS & ACHIVEMENTS

1. Gold medal at iGEM 2021 along with 4 nominations for special awards with IISER Kolkata Team(Best Diagnostics, Best Composite Part, Best Supporting Entrepreneurship, Best Inclusivity).
2. MITACS Globalink Research Fellowship
3. ANU Future Research Talent Awardee
4. INSPIRE Scholarship
5. JBNSTS Junior Scholarship (Rank- 14)

SKILLS

Python, MATLAB, GNU plot, Latex, Photoshop, Gephi

INTERNSHIPS & PROJECTS

1. WinterReading Project2019on“Non-linear Dynamics and Fractal Geometry” under Prof. Soumitra Banerjee, IISER Kolkata
2. SummerProject2020on“PropagationofCOVID-19cases and future prediction” under Prof. Ranjit Kumar Upadhyay, IIT Dhanbad
3. SummerProject2021on“Higher Order Interaction inSpecies Stabilization and Perturbation Effect in species” under Prof. Chittaranjan Hens, ISI Kolkata
4. Summer Project 2022 on “Change in Network structure with respect to Mutualism and Antagonism” under Prof. Jordi Bascompte, University of Zurich

PUBLICATIONS

1. Upadhyay, R.K., Chatterjee, S. et al. “Age-group targeted testing for COVID-19asa new prevention strategy” NonlinearDynamics (Springer-Nature)(2020),DOI:10.1007/s11071-020-05879-x

2. Upadhyay, R.K., Chatterjee, S. et al. “Combating COVID-19 crisis and predicting the second wave in Europe: an Age-structured modeling”Journal of Applied Mathematics and Computing (Springer- Nature)(2022),DOI: 10.1007/s12190-022-01723-0

3. Chatterjee, S. et al. “Controlling species densities in structurally perturbed intransitive cycles with higher-order interactions”CHAOS, DOI: 10.1063/5.0102599