Dr. Aristotle Voineskos, M.D., Ph.D
Dr. Aristotle Voineskos is the Koerner New Scientist, and Head of the Kimel Family Translational Imaging-Genetics Laboratory at CAMH. He is Assistant Professor in the Department of Psychiatry, Faculty of Medicine at the University of Toronto.
Dr. Voineskos’s work combines multi-modal neuroimaging and genetics approaches to map gene effects in the brain with a view to discovering vulnerability pathways for severe mental illness. This will aid in early identification of at-risk individuals and disease prevention. Currently, his neuroimaging approaches include MRI techniques known as diffusion tensor imaging and cortical thickness mapping. Disease populations currently under study include schizophrenia, bipolar disorder and Alzheimer’s disease, as well as studying healthy individuals and healthy aging.
Another area of Dr. Voineskos’s work includes understanding genetic and structural brain determinants of brain function by combining the approaches described above with transcranial magnetic stimulation (TMS). He is also using brain imaging to understand the effects of existing and novel treatments on brain structure and function.
Dr. Colin Hawco, Ph.D
Dr. Hawco (PhD, Neuroscience, McGill University) is an independent scientist at CAMH’s Brain Health Imaging Centre. He develops new approaches to uncover meaningful patterns of individual variability in complex neuroimaging data. He hopes this work will lead to better understanding of biological variability in patient samples, and inform personalized medicine approaches in psychiatry. In 2018, Dr. Hawco was appointed to the Department of Psychiatry.Dr. Hawco also was a co-Principal Investigator on grant funded by the National Institute of Mental Health in the US, using brain imaging to better understand magnetic seizure therapy, a new and powerful treatment for depression.
Dr. Erin W. Dickie, Ph.D
Dr. Erin Dickie (PhD, Neurological Sciences, McGill University) is a Project Scientist. Dr. Dickie’s research focus is personalized connectomics, or the ability to map brain organization at the level of the individual. Dr. Dickie received a NARSAD Young Investigator Award to investigate how personalized mapping may be a critical first step for the design of targets for neurostimulation therapy. Dr. Dickie founded the “ciftify” open software framework for surface-based analyses of MR data, collaborating with the Human Connectome Project. A paper describing this technique was recently published in NeuroImage. This year, Dr. Dickie was appointed to the Department of Psychiatry as Assistant Professor as well as a cross-appointment with the Krembil Centre for Neuroinformatics. She is an invited instructor and member of international initiatives for education and best scientific practices.
Dr. Nicholas Neufeld, M.D., M.Sc
Nicholas Neufeld (MD, University of Toronto; MSc, University College London) is an Assistant Professor in the Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, and Clinician Scientist at the Centre for Addiction and Mental Health (CAMH). The core mission of Dr Neufeld’s research program is to investigate the neurobiology of severe mental illness across the lifespan and develop biomarkers, with a specific focus on schizophrenia and depression. Dr Neufeld’s research philosophy centres on integrating multimodal neuroimaging measures within clinical research to develop a comprehensive and impactful understanding of the mechanisms underlying treatment trajectories. An example of this work is the Magnetic Seizure Therapy for Schizophrenia – Neurocircuitry (MAST-Neuro) study funded by a NARSAD Young Investigator Grant (PI: Nicholas Neufeld). This study is embedded within the MAST-Trial, a federally funded clinical trial that compares electroconvulsive therapy and magnetic seizure therapy for Clozapine and non-Clozapine treatment augmentation in patients with treatment resistant-schizophrenia. MAST-Neuro aims to identify neuroimaging biomarkers of therapeutic effects and cognitive side effects in the ongoing MAST-Trial. Fundamentally, the MAST-Trial is positioned to lead to an indication for MST as a next-generation therapy for treatment-resistant schizophrenia, thereby increasing the number of therapeutic options available to the most severely ill patients with schizophrenia. MAST-Neuro is poised to improve our mechanistic understanding of the risks and benefits of this novel brain stimulation intervention and bring the field one step closer to personalized medicine.
Dr. Lindsay Oliver, Ph.D
Dr. Lindsay Oliver (PhD, Neuroscience, Western University; MSc, Human Cognitive Neuropsychology, University of Edinburgh) is a postdoctoral fellow. Lindsay works with data from the SPINS project, exploring the neural circuitry and behavioural correlates of social cognition across people with schizophrenia spectrum disorders (SSDs) and healthy individuals. She has been using advanced statistical analyses to detect brain networks involved in social cognition and examine their interaction during naturalistic social processing as a function of lower-level (e.g., emotion recognition) and higher-level (e.g., inferring others’ intentions) social abilities. Her overall goal is to identify biomarkers of social cognitive impairment to inform intervention and targeted treatment options for individuals affected by these debilitating symptoms.
Dr. Peter Zhukovsky, Ph.D
Dr. Peter Zhukovsky (PhD, Experimental Psychology and Psychiatry, University of Cambridge, UK) is a postdoctoral fellow. Peter’s work focuses on the neurobiological mechanisms of major depressive disorder, particularly on late-life treatment resistant depression. In particular, he uses whole brain structural and functional connectivity to identify depression “biotypes” in large scale databases (UK Biobank) and predict cognitive outcomes in a depression treatment trial (OPTIMUM dataset). He combines functional connectivity measures from resting-state fMRI and structural connectivity measures from morphometric similarity mapping and diffusion weighted images with advanced statistical approaches such as partial least squares, clustering and deep neural networks. He hopes to reveal the associations between brain connectivity, cognition and clinical symptoms.
Hajer Nakua, BSc
Hajer Nakua (BSc. Psychology, Neuroscience, & Behaviour, McMaster University) is a second year Masters student in the lab. Her main research focuses on understanding the brain-behaviour relationship between the cortico-amygdalar network and externalizing/internalizing behaviour in children with neurodevelopmental disorders. She uses multi-modal imaging (structural, functional and diffusion) and large datasets featuring children diagnosed with many different types of neurodevelopmental disorders. She is also interested in improving quality control procedures for brain imaging acquisitions.
Dr. Iska Moxon-Emre, Ph.D
Dr. Moxon-Emre (PhD, Psychology, University of Toronto) is a postdoctoral fellow, investigating the links between brain function and behaviour, in persons with autism and schizophrenia. She is using magnetic resonance spectroscopy (MRS) and functional MRI to examine how non-invasive brain stimulation (repetitive transcranial magnetic stimulation; rTMS) alters brain metabolism, functional connectivity, and depression, in emerging adults with autism. She is also combining multi-modal neuroimaging and social cognition data, from individuals with autism and schizophrenia (SPIN-ASD dataset), to identify patterns of brain-behaviour relations that cut across these diagnoses and relate to social cognition. The overarching goal of Dr. Moxon-Emre’s research is to inform the development of targeted treatments to improve outcomes in clinical populations.
Michael Joseph, M.Sc
Joseph (BSc, Biology & Psychology, McMaster University; MSc, Physiology, University of Toronto) is a Research Analyst. He assists with improving the lab’s MRI data management and quality control software. Michael previously performed a similar role at the Ontario Brain Institute, where he specialized in neuroimaging and clinical data collection databases. To this end, Michael teaches a monthly introductory course to train the hospital’s research staff and scientists in using databases for their research projects. Michael is also involved in managing SPINS-ASD: a new study comparing autism-spectrum and schizophrenia-spectrum disorders led by lab collaborator Dr. Stephanie Ameis. Michael’s primary interests lie in developing new software to automate MRI data analysis and understanding the statistical techniques involved.
Jerrold Jeyachandra, M.Sc
Jeyachandra (M.Sc, Science, Queens University) joined the lab as a Research Analyst. He is responsible for maintaining and expanding upon the lab’s computational pipelines for processing imaging data. In addition, he manages the analysis of phantom data, which provides critical insight into scanner performance across the many research centres involved in the lab’s studies. Jeyachandra is also interested in utilizing computational techniques to improve precision in therapeutic neurostimulation. He is the lead developer of BOONStim (Bayesian Optimization of NeuroStimulation), a pipeline utilizing cutting-edge technologies from neuroimaging and TMS electrical field modelling, to automatically calculate an optimal TMS coil position given a target region of any size or shape.
Jovanka Skocic (BA Psychology & Anthropology, University of Toronto) joined the lab as a Research Analyst in September 2019. She will be assisting in utilizing and streamlining the lab’s existing pipelines for processing multi-modal imaging data. Jovanka performed a similar role at the Hospital for Sick Children, where she explored differences in brain structure and function through Diffusion Tensor Imaging, Magnetization Transfer Imaging, Arterial Spin Labeling and Functional Magnetic Resonance Imaging. Jovanka is interested in making day to day operations more efficient and assists with training and onboarding new staff, REB applications and troubleshooting any issues as they arise. Outside of the lab, Jovanka’s interests include living an active lifestyle and you’ll find her at the yoga studio, dance studio or out for a run.
Eman Nishat, BSc
Eman Nishat (BSc Neuroscience, University of Toronto) is a second year Master’s Candidate in the Department of Physiology, under the supervision of lab alumnus Dr. Anne Wheeler and lab collaborator Dr. Stephanie Ameis. Using diffusion magnetic resonance imaging (MRI) from large datasets on brain development and child health, Eman’s project explores changes in gray and white matter microstructure following a childhood mild traumatic brain injury, and whether differences in brain microstructure are associated with performance on cognitive tests.
Kevin Witczak joined the lab in June of 2018 and works alongside Dawn Smith to run and improve the lab’s Beowulf cluster and data processing resources. His specific focus has been on the development of reproducible software systems for versioned data management, as well as broadly administering the lab’s Slurm load balancer which enables efficient high performance computing. He maintains and develops custom automation and scripting, troubleshoots computing issues, helps lead the training and development of lab members’ technical skillsets, and is involved with tracking inventory and maintaining the lab’s physical hardware.
Dr. Neda Rashidi-Ranjbar, M.D., M.Sc
Dr. Rashidi (MSc, Cognitive Science, Trento University; MD, University of Tehran) is a doctoral student. She studies brain structure and function among older adults with varying levels of risk for dementia, and examines their connections with cognitive scores. Rashidi-Ranjbar is primarily working with PACt-MD, a multi-centre clinical trial that aims to identify stepwise patterns of disease progression in older participants with depression, mild cognitive impairment, and Alzheimer’s Disease. Specifically, Rashidi-Ranjbar will use the three neuroimaging scans provided by each participant over a span of six months to identify structural and functional brain measures associated with the observed delay or prevention of dementia, as well as investigate the effect of cognitive training and brain stimulation on brain structure and function. In the coming year, Dr. Rashidi will use similarity network fusion (SNF), a modeling approach developed by lab collaborator Dr. Anna Goldenberg (SickKids), to identify similarity networks that integrate demographic, cognitive and imaging data. Rashidi anticipates that SNF will identify informative clusters of participants with similar profiles irrespective of diagnosis.
Salim Mansour, B.S.c
Salim (BSc, Computer Science, University of Toronto Scarborough) returned to the lab as a research assistant in 2020 after being a summer student the previous summer. Using his background in software engineering he works on developing and implementing pipelines for neuroimaging analysis. He has worked on a variety of pipelines in the lab including dmriprep and tractify, as well as worked on optimizing existing pipelines for more efficient preprocessing through features including containerization.
Dawn Smith, B.Sc
Dawn Smith (BSc Psychology, York University; BSc Computer Science, York University) is a Research Methods Specialist, responsible for improving existing and creating new software to manage MRI data and perform quality control. Smith also works to keep the lab’s technical systems running smoothly in the face of heavy demand and constant change. Smith’s primary interest is in developing and deploying new tools to automate common preprocessing and quality control tasks, and make the computational aspects of imaging analysis easier for the lab’s scientists. Recently, her focus has been on updating the quality control dashboard and its underlying code, and she presented on this facilitated review process at INCF.
Justin Ng, B.Sc.H
Justin Ng (BScH, Life Sciences, Queen’s University) is in his first year of the MSc program at the Institute of Medical Science under Dr. Hawco’s supervision. His main interests are in the bases of general cognitive ability. His thesis examines the relationship between fMRI dynamic functional connectivity measures of network flexibility in the brain and general cognitive factors (e.g. g-factor, fluid intelligence, crystallized intelligence) using data from healthy young adults in the HCP project. Understanding the link between neurobiology and cognitive ability might one day allow the pursuit of the ultimate goal in this field: amelioration of deficits across psychological disorders, and even enhancement.
Grace Jacobs, B.Sc
Grace Jacobs (BSc, Biomedical Science, University of Ottawa) is in her fourth year of the PhD program at the Institute of Medical Science under Dr. Voineskos’ supervision. She recently published her work (Jacobs et al, Neuropsychopharmacology) using structural and functional MRI data to better understand the neural mechanisms of psychosis symptom development in youth, including sex and age dependent differences. Jacobs is currently studying neurodevelopmental disorders ADHD, ASD, and OCD, which have many overlaps in symptoms, genetic risk, and neurobiology as well as tremendous variation in presentation within disorder. Her work focuses on integrating behavioural and multimodal structural neuroimaging measures from these three groups to identify data-driven subgroups that cut across diagnoses and have distinct biological profiles. Potentially, this can one day change how we define diagnostic labels altogether.
Thomas Tan (Bsc, Psychology & Neuroscience, University of Toronto) returned to the lab as a Research Assistant. He assists with improving the lab’s functional MRI processing pipelines and quality control for several studies in the lab. He has been especially worked with Dr. Ameis and Dr. Hawco to analyze resting and functional MRI scans of rTMS ASD study. He is also involved in managing and analyzing fMRI scans for SPINS study. He is interested in functional networks and hopes to investigate psychiatric disorders by using multimodality imaging techniques.
Dr. Christin Schifani, Ph.D
Dr. Schifani (PhD, Neuroscience, Ruprecht-Karls University of Heidelberg) joined the lab in September 2018. She used advanced MRI techniques to work with data from the rTMS-WM study. Schifani’s work explored the impact of rTMS on the structure of the cortex, using a cutting-edge method called Neuritic Orientation Dispersion and Density Imaging (NODDI). Dr. Schifani now works as a Project Scientist in the CAMH PET Centre, collaborating with Dr. Neil Vasdev.
Anagha (BSc- Molecular Biology and Biotechnology, University of Toronto Scarborough, expected 2021) joined the lab as a co-op student for the September to December 2019 term. Under the supervision of Dr. Hawco she will be working on data analysis and quality control of the NEUR study, which involves analyzing TMS-fMRI data collected from both healthy participants and participants with Schizophrenia. The goal is to be able to create an “Open Science” framework where the data can be uploaded to a repository and shared with other researchers.
Sonja Stojanovski, B.Sc.
Sonja Stojanovski (BSc Neuroscience, Psychology, & Physiology, University of Toronto) is a second-year Doctoral Candidate in the Department of Physiology working with lab alumnus Dr. Anne Wheeler. Over the past year, Stojanovski collaborated with current lab members and lab alumnus Dr. Arash Nazeri’s to apply his Superficial White Matter methods to identify how TBI affects these structures in youth and the elderly. Recently, Stojanovski collaborated with the lab to explore how traumatic brain injuries (TBI) affects the etiology of ADHD. The paper reporting her findings features many Kimel Lab members as coauthors, and was recently published at Biological Psychiatry. Stojanovski recently won the Margaret & Howard GAMBLE Research Grant for three consecutive terms starting this fall, and holds Sickkids Restracomp scholarship for the rest of her degree. Stojanovski looks forward to continued collaboration with the lab.
Julia Galluci, HBSc
Julia (HBSc major in Neuroscience & Psychology, minor in Biology) is entering the second year of an MSc at the Institute of Medical Science, under the supervision of Dr. Colin Hawco. Her thesis work aims to examine individual variability in functional brain activity during working memory performance in those with Schizophrenia Spectrum Disorders (SSD). The intent of this project is to make a clinical impact by improving our ability to understand neurocognitive heterogeneity within SSD. Enhancing the field’s understanding of the neurobiological diversity in patients with SSD may have implications for the identification of treatment-relevant ‘biotypes’, targeted interventions, and individualized treatment.
Navona Calarco, B.A.H.
Calarco (BA Philosophy, University of Toronto; BA Cognitive Science, York University) is entering the second year of an MSc in the Institute of Medical Science program, under the direction of Dr. Voineskos. Her thesis work supports Dr. Voineskos’ OMHF-funded longitudinal study examining the neurobiology of persistent negative symptoms (PNS) in first-episode psychosis. Specifically, Navona is working to describe disruptions in white matter network circuitry, and test if these disruptions can be used by a machine-learning classifier to accurately predict who will go on to develop PNS. If successful, this work will advance early identification and inform intervention efforts. This project was funded by OGS and a Cleghorn Award for Schizophrenia Research. Navona is also working as an RA for lab alumnus Dr. Yuliya Nikolova, on a project aiming to test the usefulness of neuromelanin as a biomarker of depression in older adults.
Judy Kwan, B.Sc.
Judy Kwan (BSc., Animal Physiology, University of Toronto) is a Research Analyst working on both SPINS and STOP-PD. For both studies, she takes the lead collecting neuropsychological and social cognitive assessments from research participants, and coordinating shared visits for the sample collection lab and MRI. Kwan is also responsible for providing training to new study staff.
Dielle Miranda, MA (Clin Psy)
Dr. Natalie Forde, Ph.D
Dr. Forde (BSc Chemistry, University College Cork, Ireland; MSc Neuropharmacology, National University of Ireland, Galway; PhD Psychiatry, University of Groningen, the Netherlands) joined the lab in January 2018 as a post-doctoral research fellow. Dr. Forde is interested in symptoms that appear across different neurodevelopmental disorders and investigates their neural correlates by integrating imaging data from multiple modalities. Forde uses the uniquely large Province of Ontario Neurodevelopmental Disorders (POND) Network dataset of children and adolescents with various neurodevelopmental disorders to identify biomarkers that relate to symptoms across disorders. In the future, this may help design targeted interventions like transcranial magnetic stimulation to improve cross disorder symptoms and long-term outcomes for those with neurodevelopmental disorders.
Gabrielle Herman, B.Sc
Herman (BSc Psychology, Neuroscience, & Behaviour, McMaster University, 2018) joined the lab in May as a research analyst. She assists with data management and quality control for several studies in the lab. She has been especially involved in the OPTIMUM study on late-life depression, and has created a number of tools to track study recruitment. She also manages twice-yearly uploads of imaging and clinical data for the lab’s two NIH R01-funded studies (OPTIMUM and SPINS). Herman has also contributed code to various analysis and data management pipelines. She is interested in neurocognitive predictors of brain activity, and hopes to investigate brain networks and network flexibility.
Dr. John Anderson, Ph.D
Depression is known to be a significant risk factor for conversion from healthy aging to mild cognitive impairment (MCI), and from MCI to Alzheimer’s Disease (AD). The pathways affected by depression and dementia are thought to overlap; however, evidence linking the two is tenuous. At the Kimel lab at CAMH, I am exploring how depression affects grey and white matter microstructure across the spectrum of healthy aging to dementia using multi-shell DWI acquisitions. We hope that by identifying common pathways underlying depression and dementia, we can identify individuals at-risk for dementia earlier, and perhaps prevent conversion by treating the depressive symptoms.
Dr. Hideaki Tani, MD, Ph.D
Dr. Tani (MD, PhD in Medicine, Keio University School of Medicine, Japan) joined the lab in April 2019 as a postdoctoral fellow. Dr. Tani studies the effect of antipsychotics on brain metabolite change compared with placebo using proton magnetic resonance spectroscopy (1H-MRS) in patients with psychotic depression. He also investigates the neural correlates between neurochemical findings and structural connectivity assessed with diffusion tensor imaging (DTI). These works will contribute to our knowledge on the biological effects of antipsychotics on the brain, as well as improve the neuroscientific understanding of how antipsychotic medication change brain function and structure in treatment response.
Mathuvanthi (Mathu) Manogaran
Manogaran (BSc Computer Science, University of Toronto Scarborough, expected 2021) joined the lab as a co-op student for the January - May term, and enjoyed it so much she stayed for an additional co-op term until August 2018. In collaboration with Dawn Smith and Dr. Erin Dickie, she supported many aspects of the lab’s computational infrastructure and contributed to software development. She is responsible for creating a program that can convert the lab’s native directory structure to a new reproducible data format (BIDS), and created several portable Docker images for Dr. Dickie’s Ciftify program. Manogaran also upgraded DTI processing pipelines and made several contributions to the lab’s quality control interface.
Wiljer (BSc Molecular Biology and Genetics, expected 2021) returned to the lab for a third year as a summer student. Under the supervision of Dr. Dickie, she performed an investigation of population anatomical variability within and between a set of brain atlases frequently used in clinical resting state studies. She analysed cortical folding and sulcal depth patterns in these atlases using the publically available Human Connectome Project (HCP) dataset. She evaluated the degree of similarity from correlation matrices of individual participants across atlases. Wiljer looks forward to publishing her findings in a paper currently in preparation.
Mulsant (BSc Pharmacology, McGill, expected 2022) joined the lab as a summer student in 2019. She worked with Dr. Dickie to organize the data and learn coding skills. She aided with quality control for multiple lab datasets, primary for STOP-PD under the supervision of Dr. Nick Neufeld.
Sinead Ramsaroop (BA, Psychology, York University, expected 2017) spends two days each week with the lab to provide administrative support to its students, staff, and Dr. Voineskos. She appreciates that her role affords her an inside view of hospital bureaucracy, academic administration, and the scientific process. Ramsaroop is also very committed to community advocacy, and outside of the lab, runs her own charity called Project Reset, which helps facilitate a psycho-education treatment program for women accessing city shelters.
Rutwik Bangali (BEng Electrical Engineering, University of Toronto, expected 2019) returned as a summer student for the second year. Bangali analyzed metabolite concentrations in the dorsolateral prefrontal cortex (dlPFC) and the subgenual anterior cingulate cortex (sgACC) using magnetic resonance spectroscopy (MRS) data from the STOPPD dataset. Bangali worked closely with Dr. Nick Neufeld, Dr. Sofia Chavez, and Joseph Viviano to ensure his data analysis and processing scripts could be applied to the study’s multiple data-collection sites, and also worked to automate the entire pipeline to ensure ease of future use.
Lauren Liu (BEng Electrical and Biomedical Engineering, McMaster University, expected 2019) joined the lab as a summer student. In collaboration with Joseph Viviano, Liu analyzed the relationships between structural topology and brain dynamics at rest, among participants with schizophrenia and healthy control populations. She tested various diffusion tractography algorithms and parameters in order to tackle the challenge of quantifying structural connectivity strength between brain regions. Liu subsequently developed a processing pipeline to produce ROI-to-ROI connectivity matrices for various structural metrics to use in conjunction with functional MRI correlation matrices, which will soon be adopted into the lab’s larger processing pipelines system. Combining multimodal neuroimaging techniques - in this case structural and functional - allows for a more comprehensive characterization of global brain networks, an essential first step to future interventions.
Dayton Miranda (BSc Life Sciences, Western University, expected 2020) returned as a summer student for the second year. In collaboration with Dr. Erin Dickie and Saba Sahab, Miranda analyzed structural and functional MRI data from patients with schizophrenia and healthy controls in an effort to identify between-group structural differences in the cortex, which in turn might contribute to an explanation of the functional disconnectivity observed in schizophrenia. Further understanding of the structural features and markers of schizophrenia might allow the illness to be identified and perhaps predicted using structural as opposed to functional scans, which are quicker and therefore cheaper to collect. Miranda is continuing to analyze incoming data for this project, and looks forward to reporting his results in an upcoming paper.
Laagi Yoganathan (BSc Psychology, Neuroscience & Behaviour, McMaster University) returned as a summer student for the second year. Under the supervision of Drs. Stephanie Ameis and Colin Hawco, he worked on a project investigating the efficacy of rTMS treatment in individuals who have high functioning autism and comorbid executive functioning (EF) deficits. Yoganathan analyzed cognitive assessment and task-based fMRI data to determine if there are any changes on EF performance or in the brain networks involved with EF following rTMS treatment. He is now pursuing an MSc in Psychology at McMaster University.
Erika Ziraldo (BEng AREA, University of Guelph, expected 2018) joined the lab as a summer student. With support from Dr. Dickie and Joseph Viviano, Ziraldo developed a cleaning pipeline to remove artifacts from spiral resting state functional MRI scans. Thorough testing and application of the pipeline to multiple datasets has demonstrated improved brain connectivity in expected regions. The pipeline has been made publicly available for other researchers at CAMH. Ziraldo will be returning to the Kimel lab for another student term this fall.
Dr. Yuliya Nikolova, Ph.D
Dr. Yuliya Nikolova (BA, Psychology, Harvard University; PhD, Psychology & Neuroscience, Duke University) completed her training as a Banting Postdoctoral Fellow in Dr. Etienne Sibille’s Neurobiology of Depression and Aging lab. Throughout her postdoctoral work she collaborated with Dr. Voineskos on projects aiming to accelerate the translation of basic preclinical research to human neuroimaging and clinical applications. In her most recent project, Dr. Nikolova developed a novel transcriptome-based polygenic risk score for depression, which maps onto cognitive brain function and performance, as well as stress-related depressive symptoms. Over the past year, Dr. Nikolova received two prestigious conference travel awards to present her work at the annual meetings of the American College of Neuropsychopharmacology and the Society of Biological Psychiatry. She was recently appointed the next Koerner New Scientist at CAMH and will continue her collaborative work with Dr. Voineskos.
Laura Stefanik, M.Sc
Laura Stefanik (BA, Psychology, Queen’s University; MSc, Institute of Medical Science, University of Toronto) recently graduated under the supervision of Dr. Voineskos. Stefanik’s work focuses on the application of novel data aggregation algorithms for social cognitive, neurocognitive, and neuroimaging data in an effort to identify impairment-specific markers of illness across adolescents and young adults with autism spectrum, schizophrenia spectrum and bipolar disorder. The goal of this work is to enhance disease subtyping and to identify treatment targets to improve social functioning. During her graduate studies, Stefanik had authorship on five peer reviewed scientific publications and her work was presented at a number of local and international academic conferences. Stefanik recently accepted a Research Analyst position with the Slaight Family Centre for Youth in Transition and Child, Youth and Emerging Adult Programs.
Saba Shahab, M.Sc
Saba Shahab (BSc, Neuroscience, University of Toronto) completed her MSc under the supervision of Dr. Voineskos. Over the past year, she collaborated with Dr. Dickie to apply a tool developed in-lab to a replication dataset in an effort understand how the brains of individuals with schizophrenia differ in their functional organization from those of neurotypical adults. Identifying abnormalities in functional organization in the brains of schizophrenia patients may lead to a better understanding of the disease process, and illuminate new targets for future treatment interventions. Shahab also conducted a systematic review and meta analysis examining sex-based differences in white matter microstructure in schizophrenia, which was recently published in Schizophrenia Bulletin. Shahab completed her degree in June 2017, and is now a first-year medical student at Western University.
Dr. Tom Wright, Ph.D
Dr. Tom Wright (PhD Neurophysiology, Gothenborg University, Sweden) is a Research Methods Specialist, who works mainly on the lab’s MRI quality control metrics. Most notably, Dr. Wright developed an in-house interactive ‘dashboard’ interface that allows staff to easily examine individual participant data, seamlessly observe and track longitudinal trends across participants, sites, and scan types, and communicate issues with relevant parties. Additionally, Dr. Wright regularly consulted with the lab’s students and scientists to support the computational requirements of their projects, and worked with the lab’s staff to strengthen its general computational infrastructure. Dr. Wright recently accepted a position as a Senior Research Associate (Electrophysiology) at the Kensington Vision & Research Centre.
Dawson Overton, M.Sc
Dawson Overton (BSc, Computer Science, University of Toronto, MSc, Cognitive Neuroscience, University of Toronto) is interested in the characterization and identification of psychosis spectrum disorders using the BOLD signal and ASL neuroimaging data, especially using predictive computational techniques, such as support vector machines, neural networks, and other machine learning models. He most recently worked in the lab in summer 2019 as a research student, and is in his third year of medical school at the Schulich School of Medicine in London ON.
Daniel Felsky, Ph.D
Dr. Daniel Felsky (PhD, Institute of Medical Science, University of Toronto) completed his doctoral training under Dr. Voineskos in 2016, and has since completed a productive first year of his postdoctoral fellowship at Brigham and Women’s Hospital and Harvard Medical School, and recently transitioned to a postdoctoral scientist position in the newly founded Center for Translational and Computational Neuroimmunology at Columbia University Medical Center. In addition, Dr. Felsky is continuing his investigations into the complex genomic foundations of aging and Alzheimer’s disease as an associate scientist at the Broad Institute of MIT and Harvard. Since starting his fellowship, Dr. Felsky has published four peer-reviewed articles, been invited to speak at three national and international conferences, and, in 2016, was awarded the CIHR Institute of Aging Fellowship Prize of Excellence in Research on Aging. Recently, Dr. Felsky has returned to CAMH as the Head of Whole Person Modeling at the Krembil Centre for Neuroinformatics.
Julie Winterburn, M.Sc
Julie is a student in the second year of her Master’s degree with the Institute of Biomaterials and Biomedical Engineering at the University of Toronto. Her thesis focuses on comparing machine learning techniques reported in the magnetic resonance imaging literature for schizophrenia/control classification. Her previous work includes atlasing the hippocampus on high-resolution magnetic resonance images. Julie has been with the Kimel Family lab group since 2012. In her spare time, she can be found baking delicious treats, eating said baking, or out rowing on Lake Ontario.
Dr. Mallar Chakravarty, Ph.D
Magnetic resonance imaging (MRI) is one of the tools of choice for the analysis of the brain in normally functioning and diseased states. Different MRI acquisition protocols provide excellent contrast and resolution and can be analyzed using automated techniques. The goal of Dr. Chakravarty’s work is to develop and use computational neuroanatomical techniques to understand how the structure of the brain is altered in psychiatric disorders. These techniques include the automated identification of structures and computational metrics that quantify their shape. He is currently working on adding information from diffusion tensor imaging in order to describe inter-structural connectivity. Many of these techniques can be used to elucidate phenotypes that can help describe how known risk genes may be affecting brain anatomy and ultimately increasing susceptibility to psychiatric illness. This work will aid in the early identification and treatment of those at high-risk of developing severe forms of mental illness.
Dr. Tristram Lett, Ph.D
Dr. Anne Wheeler, Ph.D
Anne is a new Catalyst Scholar in traumatic brain injury (TBI) at SickKids Hospital.
David Rotenberg, M.Sc
David is now the Manager of Scientific Computing at CAMH.
Mikko Mason, B.Sc
As a relatively new member of the Kimel Lab, I am excited to work with so many bright, engaged individuals. My role as a study RA challenges me to apply my psychometric experience to a research setting, and I am constantly amazed by the resilience with which our patients meet mental health challenges. I plan to further my education and combine research, clinical work, and teaching in the future.
On a more personal level, I feel like a Finn when in Canada and a Canadian when in Finland. I have a soft spot for old novels and the CBC. I believe in free time the way I believe in unicorns, but find sanctuary in wild places. I am happiest in woods or water or on a bike.
Tina Behdinan, MSc
Tina is now persuing her MD at the Schulich School of Medicine & Dentistry.
Robert S.C. Amaral, B.Sc
Matt Park, B.Sc
Matt is now pursuing his MD at the Schulich School of Medicine & Dentistry.
Jon Pipitone, M.Sc
Jon is now pursuing his MD at the Queen’s School of Medicine.
Dr. Mélissa Lévesque, Ph.D
Melissa did a BSc in Psychology at McGill University, followed by an MSc in Neuroscience, also at McGill. During her Master’s degree she studied the function of the serotonin 1A receptor following acute administration of fluoxetine, using positron emission tomography (PET) with [18F]MPPF in healthy populations of both rats and humans. Then, during her PhD in Biomedical Sciences in the Department of Psychiatry at the University of Montreal, she studied the long-term impacts of prenatal and early postnatal adversity on brain development using MRI and fMRI, and epigenetic mechanisms, specifically DNA methylation, in a cohort of adolescent monozygotic twins followed since birth.
At CAMH, she is now working on testing the accelerated aging hypothesis of schizophrenia using both DTI and peripheral markers in young and old schizophrenia patients and controls. Her interests lie in uncovering the biomarkers of vulnerability for mental illness using a combination of neuroimaging and molecular strategies.
Dr. Arash Nazeri, M.D.
Dr. Arash Nazeri (MD, Tehran University of Medical Sciences) completed a postdoctoral fellowship under the mentorship of Dr. Voineskos in 2016, and has since started his residency in Diagnostic Radiology at Washington University in St. Louis. Dr. Nazeri has maintained his collaboration with the lab from long distance and continues his research on gray matter tissue microstructure in brain health and disease using diffusion-weighted MRI. He has also recently joined Chen Ultrasound Laboratory in St. Louis as where he works on applications of focused ultrasound on the brain. His primary goal is to developing novel neuro-therapeutic and neuro-diagnostic approaches using focused ultrasound.
Dr. Tina Roostaei, M.D., M.P.H.
Dr. Tina Roostaei (MD, Tehran University of Medical Sciences) completed a postdoctoral fellowship in imaging-genetics in neurodegenerative disorders under the mentorship of Dr. Voineskos in 2016. She has now joined the Center for Translational and Computational Neuroimmunology, Columbia University, New York, as a postdoctoral research scientist. Tina is continuing her studies on the genetic basis of susceptibility and progression of brain neurodegenerative disorders, with focus on the functional genomics of Multiple Sclerosis and Alzheimer’s disease. Her goal is to contribute to the advancement of understanding of the pathophysiology of these brain disorders and to find targets for their treatment and prevention.
Nikhil Bhagwat, M.Sc
Currently I am working on developing novel biomakers and diagnostic applications for neurodegenerative disorders using machine-learning techniques. My research interest include, computational neuroscience, machine-learning, signal processing and related areas.
Amy Miles, MA
Amy Miles (BA, Psychology & French Language and Literature, University of Maryland; MA Developmental Psychology, Columbia) is a fifth year PhD candidate under the supervision of Drs. Allan Kaplan and Aristotle Voineskos. She is interested in the neurobiological underpinnings and developmental trajectories of eating disorders and has designed a structural MRI study to explore the neuroanatomical correlates of risk for and manifestation of Anorexia Nervosa (AN). Ultimately, Amy hopes to use this information to identify novel therapeutic targets for AN, the most fatal psychiatric disorder and one for which there are currently no evidence-based treatments.
Vincent Man, BSc
Joseph Viviano, M.Sc
Joseph Viviano (BA, Psychology, Queens University; MSc, Biology, York University) is responsible for the design and implementation of a data management platform used by researchers in the lab and beyond, as well as the lab’s general computational infrastructure. Viviano’s role also involves the design and implementation of analytic code used by the lab’s scientists, and the development of novel prognostics tools utilizing MRI scans to guide patient-specific treatment. Over the past year, Viviano has worked to develop a fully-automated method for identifying patients with schizophrenia and comorbid severe cognitive impairment, as well as a method for predicting Alzheimer’s onset.