Associate Professor

Jamie Near

PhD, University of Western Ontario

Sunnybrook Health Sciences Centre
2075 Bayview Avenue, S6 60, Toronto, Ontario Canada M4N 3M5
Research Interests
Biomedical Imaging, Neuroscience

At a Glance

  • Non-invasive assessment of brain chemistry and metabolism using in-vivo magnetic resonance spectroscopy (MRS)
  • Development of advanced techniques for single-voxel and multi-voxel MRS data acquisition
  • Development of software tools for MRS data processing, analysis and simulation.
  • Application of MRS to study brain chemistry and metabolism in mental illness and neurological conditions.
  • Application in both humans and animal models of disease.

Short Bio

Dr. Jamie Near completed his undergraduate degree in Engineering Physics at Queen’s University (2000-2004) followed by a PhD in Medical Biophysics at Western University (2004-2009), and a postdoc at the University of Oxford (2009-2012).  From 2012-2021, Dr. Near was as an Assistant Professor in the McGill University Department of Psychiatry.  He now joins the Physical Sciences Platform at Sunnybrook Research Institute as a Research Scientist.  His program of research involves 1) the development and implementation of in-vivo magnetic resonance spectroscopy methods; and 2) the application of these methods to study brain chemistry and metabolism in neuroscientific and mental health research.

Research Synopsis

Q: Are altered brain chemistry and metabolism key underlying features of neurological and neuropsychiatric conditions such as Alzheimer’s Disease, Depression, Bipolar Disorder and Schizophrenia?

Q: Can we detect these neurochemical and neurometabolic alterations non-invasively?

Q: By studying and understanding these alterations, can we devise more effective treatments against neurological and neuropsychiatric disorders?

These are a few of the overarching questions that guide and motivate the research in Jamie Near's Lab. Yes, altered brain chemistry and metabolism are in fact key features of many neurological and neuropsychiatric conditions. And yes, we can quantify these changes non-invasively using in vivo magnetic resonance spectroscopy (MRS), a technique closely related to MRI.

Jamie’s research is focused on 1) developing new MRS techniques for characterizing brain chemistry and metabolism, and 2) applying these tools towards the study of mental health and brain disorders in both humans and rodent models of disease. The goal of Jamie's research is to develop a better understanding of the underlying neurochemistry of brain health and disease, leading to improved therapy and prevention of brain disorders.

Recent Publications

Fowler C, Madularu D, Dehghani M, Devenyi GA, Near J. Longitudinal Quantification of Metabolites and Macromolecules Reveals Age- and Sex-Related Changes in the Healthy Fischer 344 Rat Brain. Neurobiology of aging 2021; 101: 109-122.

Dehghani M, Zhang S, Kumaragamage C, Rosa-Neto P, Near J. Dynamic H-MRS for detection of C-labeled glucose metabolism in the human brain at 3T. Magnetic resonance in medicine 2020; 84(3): 1140-51.

Goerzen D, Fowler C, Devenyi GA, Germann J, Madularu D, Chakravarty MM, Near J. An MRI-Derived Neuroanatomical Atlas of the Fischer 344 Rat Brain. Scientific reports 2020; 10(1): 6952.

Near J, Harris AD, Juchem C, Kreis R, Marjańska M, Öz G, Slotboom J, Wilson M, Gasparovic C. Preprocessing, analysis and quantification in single-voxel magnetic resonance spectroscopy: experts' consensus recommendations. NMR in Biomedicine 2020; e4257.

Dhamala E, Abdelkefi I, Nguyen M, Hennessy TJ, Nadeau H, Near J. Validation of in vivo MRS measures of metabolite concentrations in the human brain. NMR in Biomedicine 2019; 32(3): e4058.

Simpson R, Devenyi GA, Jezzard P, Hennessy TJ, Near J. Advanced processing and simulation of MRS data using the FID appliance (FID-A)-An open source, MATLAB-based toolkit. Magnetic Resonance in Medicine 2017; 77(1): 23-33.

Near J, Edden R, Evans CJ, Paquin R, Harris A, Jezzard P. Frequency and phase drift correction of magnetic resonance spectroscopy data by spectral registration in the time domain. Magnetic Resonance in Medicine 2015; 73(1): 44-50.