Jean Chen

At a Glance

• Quantitative functional MRI: mapping human brain metabolism and vascular integrity

• Mapping brain networks using functional MRI, diffusion MRI and EEG

• MRI of age-related brain degeneration and neurological diseases

• Using imaging and data science to understand and predict treatment outcomes for brain diseases

Short Bio

Dr. Chen received her MSc (2004) in Electrical Engineering from the University of Calgary, and her PhD (2009) in Biomedical Engineering from McGill University. She completed her postdoctoral work on multimodal MRI of brain aging at the Martinos Center for Biomedical Imaging, Harvard Medical School (2011), and joined MBP as faculty in 2011. She is a Senior Scientist at the Rotman Research Institute and Tier II Canada Research Chair in Neuroimaging of Aging. She currents heads the Chen Lab (Research in Advanced Neuroimaging using MRI). Her research is funded by the CIHR, NSERC and the Heart and Stroke Foundation.

Research Synopsis

Quantitative fMRI: mapping human brain metabolism and vascular health. The blood-oxygenation level specific (BOLD) effect is the foundation of the functional MRI (fMRI) technique, but there remain many open questions about the interpretation of BOLD fMRI, which impairs clinical translation for monitoring disease progression. We are using advanced fMRI techniques to map brain blood flow, blood volume and blood oxygen saturation, which are key building blocks of the BOLD effect and critical for the clinical translation of quantitative fMRI. 

Mapping brain networks using advanced resting-state fMRI. We use a combination of functional MRI and structural MRI as well as electroencephalography to map brain networks, incorporating knowledge about metabolic and vascular dynamics. We also used state-of-the-art ultra-fast fMRI acquisition techniques with multivariate physiological monitoring to investigate the brain-body connection in brain networks. 

MRI of age-related brain degeneration and neurological diseases. While neuronal integrity is irrevocably tied to neurovascular health, the neurovascular mechanism underlying this structural decline has remained unknown. Structural changes in the brain have long been observed as part of aging and neurodegenerative diseases. We are investigating the temporal relationship between neurovascular and structural variations in healthy brain aging. 

Using imaging and data science to understand and predict treatment outcomes for brain diseases. We are using functional MRI to imaging the brain before, during and after treatments to understand the dosage and physiological determinants of treatment outcome across different patients. We are investigating cognitive behavioural therapy, low-level light therapy amongst others. We are also using big data and data science to understand the molecular and genetic factors influencing brain-imaging outcomes. The goal of this work is to provide a scientific approach to treatment optimization in brain diseases.

Recent Publications

Teller N., Chad J. A., Wong A., Gunraj H., Gilboa A., Roudaia E., Sekuler A., Gao F., Jegatheesan A., Masellis M., Goubran M., Rabin J. S., Lam B., Cheng I., Fowler R., Heyn C., Black S. E., MacIntosh B. J., Ji X., Graham S. J. and Chen J. J. Feasibility comparison of diffusion-tensor and correlated-diffusion imaging for studying white-matter abnormalities: application to COVID-19.Hum Brain Mapp. 2023; 44: 3998-4010. 

Han A., Chad J. A., Dhollander T., Chen J. J. Fixel-based analysis of aging white matter reveals selective fibre-specific degeneration. Neurobiol Aging 2023. In press. (Senior responsible author).

69        Srisaikaew P., Chad J. A., Mahakkanukrauh P., Anderson N. and Chen J. J. Effect of sex on the APOE4-aging interaction in the white matter microstructure of cognitively normal older adults using the novel orthogonal-tensor decomposition DTI.  Front Neurosci 2023; 17: 1049609.(Senior responsible author)

 Agrawal V., Zhong X. Z. and Chen J. J.  Generating dynamic carbon dioxide traces from respiratory-volume recordings: Feasibility using neural networks and application in functional magnetic resonance imaging. Front Neuroimaging 2023. Epub ahead of print doi: 10.3389/fnimg.2023.1119539 (Senior responsible author)

Patel A., Chad J. A., Chen J. J. Is adiposity associated with white matter health and intelligence equally in men and women? J Obesity 2023; 31: 1011-1023. Selected as Editor’s Choice. 

Shams S., Prokopiou P., Esmaelbeigi A., Mitsis G, Chen J. J. Model-based deconvolution methods for estimating the carbon-dioxide response function in fMRI. Neuroimage 2022; 265: 119758.  

Tan J. L., Ragot D. M. and Chen J. J. Characterization of the echo-time dependence of spin-echo EPI BOLD contrast at 3 Tesla in grey and white matter. J Neuromethods 2022. 381: 109691

Taha H., Chad J. A. and Chen J. J. DKI enhances the sensitivity and interpretability of age-related DTI patterns in the white matter of UK Biobank participants. Neurobiol Aging 2022; 115: 35-45. PMID: 35468551. 

Zhong X. Z., and Chen J. J. Resting-state fMRI signal variations in aging: The role of neural activity. Hum Brain Mapp 2022; 43: 2880-2897. PMID: 35293656 (Senior responsible author)

Attarpour A., Ward J. and Chen J. J.Vascular origins of low-frequency oscillations in the cerebrospinal fluid signal in resting-state fMRI: validation using photoplethysmography. Hum Brain Mapp 2021; 42: 2606-2622. PMID: 33638224. 

Chad J. A., Pasternak O. and Chen J. J. Orthogonal diffusion tensor decomposition reveals age-related degeneration patterns in complex fibre architecture.  Neurobiol Aging 2021; 101: 151-159. PMID: 33610963. 

Shams S. M., Levan P. and Chen J. J.Neuronal associations of respiratory-volume variations.NeuroImage 2021; 230: 117783. PMID: 33516896.

Hussein A., Matthews J. L., Symes C., Macgowan, C, MacIntosh B. J., Shirzadi Z., Pausova Z., Paus T. and Chen J. J.The association between aortic pulse-wave velocity and resting-state fMRI. Hum Brain Mapp 2020; doi:10.1002/hbm.24934. PMID: 32034832. 

Yuen N. H., Osachoff N. and Chen J. J.. Intrinsic frequencies of the resting-state fMRI signal: the frequency dependence of functional connectivity and the effect of mode mixing. Front Neurosci 2019; 4: 900. PMID: PMC6738198.

Graduate Students

Xiaole Zhong
Yutong Sun