New Recruit Start-Up Supplements Program

Launched in 2017, Healthy Brains, Healthy Lives' New Recruit Start-Up Supplements program provides start-up supplementary funding to hiring faculties at McGill University for the recruitment of new standout faculty members whose research aligns with HBHL's scientific priorities. With these funds, the hiring faculties are able to compete with other institutions on a global level to bring fresh talent to McGill.

The following 14 new recruits have joined McGill's faculty as a result of the program's efforts so far, with HBHL contributing funding ranging from $200,000 - $400,000 in each case. Grants are awarded based on an application from the Dean of the hiring faculty. The amount is negotiated between the hiring faculty and the candidate. The HBHL portion of the start-up grant listed below may not constitute the full amount of the recipient's start-up funding.

 


Pouya Bashivan

Computational modeling of visual perception and working memory in primates

Headshot of Pouya Bashivan.Research area: Computational systems neuroscience
HBHL Research Theme: Neuroinformatics and Computational Modelling (Theme 1)
Hiring department and faculty: Department of Physiology, Faculty of Medicine
HBHL funding: $212,087
HBHL award start date: August 1, 2020

My lab seeks to develop computational models and algorithms that can explain, predict and regulate the brain’s neural responses and consequent behaviors during visual tasks,
especially ones that require short- and longterm memorization. Our research builds on various tools and theories developed in machine learning, neuroscience and cognitive science.

Danilo Bzdok

Studying human-defining cognition in the higher association cortex from a big-data perspective

Headshot of Danilo Bzdok.Research area: Computational neuroscience
HBHL Research Theme: Neuroinformatics and Computational Modelling (Theme 1)
Research keywords: Machine learning, default mode network, population neuroscience
Hiring department and faculty: Biomedical Engineering, Faculty of Medicine
HBHL funding: $400,000
HBHL award start date: November 1, 2019

Drawing on a background in medicine, neuroscience and machine learning, my lab will explore, formalize and predict brain phenotypes of hidden population variation. To do this, we will capitalize on different data sources to tackle questions in systems neuroscience in an approach that also paves new ways for computational psychiatry.

Xiaoqian Chai

Development of memory networks in the human brain

Headshot of Xiaoqian ChaiResearch area: Plasticity and learning
HBHL Research Theme: Applied Cognitive Neuroscience of Brain Plasticity (Theme 3)
Research keywords: Brain development, networks, memory, learning, fMRI
Hiring department and faculty: Neurology and Neurosurgery, Faculty of Medicine
HBHL funding: $325,000
HBHL award start date: August 1, 2019

My lab’s highly interdisciplinary research program combines brain imaging techniques with novel behavioral and computational
methods to investigate memory processes in children. The first five years of the program will focus on outlining the relationship between the maturation of brain networks and memory development in neurotypical children and children with autism. In addition, the program investigating brain abnormalities in children who are at high risk for depression using publicly available datasets.

Bruce Doré

Neural mechanisms of effective mental health messaging

Headshot of Bruce DoreResearch area: Marketing & Social Neuroscience
HBHL Research Theme: Population Neuroscience and Brain Health (Theme 4)
Hiring department and faculty: Desautels Faculty of Management
HBHL funding: $381,855
HBHL award start date: January 1, 2021

My lab’s research program aims to identify brain mechanisms engaged by communications that successfully inform people of mental health topics and promote access and use of mental health services. Additionally, we aim to construct computational models that estimate the causal role of brain activity in translating these communications into behavior change. Achieving these goals may advance theory and facilitate the dissemination of more effective messaging across initiatives in brain health and well-being.

Manuela Ferrari

2.0 mental health services for healthy brains and healthy lives

Headshot of Manuela FerrariResearch area: Digital mental health
HBHL Research Theme: Population Neuroscience and Brain Health (Theme 4)
Hiring department and faculty: Department of Psychiatry, Douglas Mental Health University Institute and Faculty of Medicine
HBHL funding: $360,636
HBHL award start date: November 1, 2019

By enhancing the use of electronic mental health technologies in mental health services, my research program aims to overcome barriers limiting the availability of quality care in the mental health sector. Three areas make up the core of my lab’s program: e-mental health assessment and monitoring, e-treatment and web-based training.

Yasser Iturria-Medina

The Neuroinformatics for Personalized Medicine Lab

Headshot of Yasser Itturia-Medina.Research area: Computational neuroscience
HBHL Research Theme: Neuroinformatics and Computational Modelling (Theme 1)
Research keywords: Personalized Medicine, Neuroinformatics, Neurodegeneration
Hiring department and faculty: Neurology and Neurosurgery, Faculty of Medicine
HBHL funding: $300,000
HBHL award start date: August 1, 2018

This lab aims to define and apply complex brain models to better understand neurological disorders and identify effective personalized treatments for patients. To do this, we combine molecular, neuroimaging and cognitive data using mathematical modeling, which allows us to create brain models based on individuals and populations, which are then validated in different neurodegenerative diseases and real clinical scenarios.

Yue Li

Computational methods to dissect the genetic, transcriptomic, and phenotypic complexity of the human brain

Headshot of Yue Li.Research area: Computational neuroscience
HBHL Research Theme: Neuroinformatics and Computational Modelling (Theme 1)
Research keywords: Polygenic, regulatory genomics, neurogenetics, machine learning, statistics
Hiring department and faculty: Computer Science, Faculty of Science
HBHL funding: $162,500
HBHL award start date: January 1, 2019

Magnetic resonance imaging (MRI) has enormous potential for early diagnosis of brain diseases; but, because of the high cost of these machines, scans are expensive, and access is limited. Using DNA, cellular, molecular, neuroimaging, clinical and behavioural data from hundreds of individuals, we will train a machine learning model to predict what an individual’s MRI scan and brain-specific gene expression would look like given only their DNA sample. An individual’s risk of brain disease can then be predicted from this information.

Michael MacKenzie

Transactional processes in early trauma and child welfare

Headshot of Michael MacKenzieResearch area: Social neuroscience
HBHL Research Theme: Population Neuroscience and Brain Health (Theme 4)
Research keywords: Trauma, stress, child maltreatment, epigenetics, psychopathology
Hiring department and faculty: Social Work, Faculty of Arts
HBHL funding: $349,255
HBHL award start date: March 1, 2019

My research program seeks to inform both our understanding of normative development and barriers to well-being and mental health for more vulnerable populations of children. My work combines efforts to clarify how children experience adversity and instability with a focus on using basic developmental research to design and test more effective interventions. The program is pursued in partnership with governmental child welfare agencies in Canada and the United States, as well as provider agencies offering a range of services from in-home support to out-of-home placement.

Romina Mizrahi

Molecular imaging young brains

Headshot of Romina Mizrahi.Research area: Computation modeling of visual perception and working memory in primates
HBHL Research Theme: Applied Cognitive Neuroscience of Brain Plasticity (Theme 3), Population Neuroscience and Brain Health (Theme 4)
Hiring department and faculty: Department of Psychiatry, Douglas Mental Health University Institute
HBHL funding: $396,630
HBHL award start date: September 1, 2020

My lab will build a program for accelerating translation of preclinical and postmortem research into innovative treatments for young people in Canada. Specifically, I propose the development of a Center for Clinical and Translational Sciences, which will aim to develop a recruitment core and clinical research infrastructure integrated into the Douglas for translational research activities, establish a new neuroimaging PET infrastructure, establish a new clinical trial unit, and support trainees through the development of a mentoring program.

Jean-Baptiste Poline

Methodological aspects of neuroimaging and imaging genetics, reproducibility and neuroinformatics

Research area: Neuroinformatics
HBHL Research Theme: Neuroinformatics and Computational Modelling (Theme 1)
Research keywords: Data analysis, Neuroimaging, Reproducibility, Publication platforms
Hiring department and faculty: Neurology and Neurosurgery, Faculty of Medicine
HBHL funding: $200,000
HBHL award start date: August 1, 2018

My laboratory research program is organized around three main areas. First, to better understand brain systems and their relation to causes of brain disease, we are developing statistical and machine learning methods and tools to analyze neuroimaging and genetics data in relation to demographic, behavioural or clinical variables using large databases (e.g. the UK BioBank). Second, we are working to produce and encourage more reproducible, FAIR and open science in the fields of neuroimaging and imaging genetics, and more generally in the neurosciences, life sciences, and data science. We work on developing training material, designing and performing meta analyses, and engaging in the evolution of 'what' and 'how' we publish research. Related to this, our third area of focus is the development of neuroinformatics tools to equip neuroscientists with the necessary infrastructures to more easily disseminate, document and combine datasets, and generate re-usable pipelines and analysis methods (HBHL NeuroHub, Canadian Open Neuroscience Platform). We are also working to make these research objects publishable and acknowledged in the traditional academic system through projects such as Aperture and NeuroLibre.

Jean-Francois Poulin

Mapping dopamine neuronal Circuits in health and disease

Headshot of Jean-Francois Poulin.Research area: Cellular and tissue models
HBHL Research Theme: Mechanistic Models of Neurodegenerative Disorders (Theme 2)
Research keywords: Dopamine, Parkinson's disease, Autism spectrum disorder, circuits, animal models
Hiring department and faculty: Neurology and Neurosurgery, Faculty of Medicine
HBHL funding: $400,000
HBHL award start date: August 1, 2019

My lab has developed novel transgenic approaches to demonstrate that different subtypes of dopamine neurons display distinct axonal projections, and has also shown that
one particular subtype is more vulnerable to Parkinson’s disease. These findings strongly suggest that each subtype is potentially associated with a specific circuit, function and/or disease. Our future research aims to investigate how dopamine circuits are altered in transgenic mouse models of neurodevelopmental and neurodegenerative disorders.

Rachel Rabin

Neural correlates of social cognitive deficits in schizophrenia patients with and without cannabis use

Headshot of Rachel Rabin.Research area: Addictions
HBHL Research Theme: Applied Cognitive Neuroscience of Brain Plasticity (Theme 3)
Research keywords: Cannabis, addiction, social cognition, schizophrenia, hippocampus
Hiring department and faculty: Department of Psychiatry, Douglas Mental Health University Institute
HBHL funding: $185,860
HBHL award start date: January 1, 2020

To examine the effects of chronic cannabis use on social cognition and underlying brain structure, my lab compares social cognitive performance in cannabis-using patients with schizophrenia and non-cannabis using patients with matched controls. Brain imaging scans are also completed to assess brain health in regions with high concentrations of cannabinoid receptors that also facilitate social processing. Findings from this study will highlight factors that contribute to social dysfunction and help identify therapeutic targets to improve treatments for individuals suffering from schizophrenia and/or cannabis addiction.

Blake Richards

Towards general principles of intelligence

Headshot of Blake Richards.Research area: Computational neuroscience
HBHL Research Theme: Neuroinformatics and Computational Modelling (Theme 1)
Research keywords: Machine learning, neural computation, learning algorithms, reinforcement learning, imaging
Hiring department and faculty: Neurology and Neurosurgery, Faculty of Medicine
HBHL funding: $250,000
HBHL award start date: August 1, 2019

My research program’s central goal is to understand the general principles of intelligence and learn how those apply to both natural and artificial agents (i.e. humans and machines). This research program is cyclical, as we first use experimental data on learning in human neural circuits to inform the design of new machine learning systems. In turn, we use machine learning to help us analyze and understand learning algorithms in the real brain. The program’s long-term goal is to map neural circuit functions to behaviour and cognition.

Aparna Suvrathan

The cerebellum in health and disease: from synapses to behavior

Research area: Plasticity and learning
HBHL Research Theme: Applied Cognitive Neuroscience of Brain Plasticity (Theme 3)
Research keywords: Synapse, synaptic plasticity, learning, cerebellum, autism
Hiring department and faculty: Neurology and Neurosurgery, Faculty of Medicine
HBHL funding: $229,500
HBHL award start date: November 1, 2018

My lab aims to identify how brain plasticity at the synaptic, cellular and circuit levels results in learned behavior. We can bridge these levels of analysis by investigating the cerebellum, which is critical for a range of functions. We use electrophysiology, imaging, behavioral analysis and molecular-genetic tools in rodents to understand learning in the normal brain. Using this framework, we then determine how cerebellar function may be different in autism spectrum disorders. As a result, our research will lead to new insight that is necessary for reducing the devasting effects of autism spectrum disorders and disorders of brain plasticity.

Yang Zhou

Genetic dissections of neurological disorders

Research area: Animal models
HBHL Research Theme: Mechanistic Models of Neurodegenerative Disorders (Theme 2)
Research keywords: Autism, Genetic engineering, Neural circuit, Animal behavior
Hiring department and faculty: Neurology and Neurosurgery, Faculty of Medicine
HBHL funding: $350,000
HBHL award start date: May 1, 2019

My lab is developing and applying technologies to engineer genetic mutations associated with neurological disorders in order to better understand how these mutations impact the neural circuits and behavior in model organisms. This research will identify causes of disease and allow the testing of genetic-based therapeutic approaches, as well as investigations into how genetic disturbances of neural circuits influence learning and cognition.

Back to top