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The MiND Lab pursues basic and clinical science research questions that strive to create quantitative PET/MRI tools for understanding the neurobiology of degenerative diseases that drive disorders of cognition and behavior.

We develop, translate, and implement PET and MR imaging solutions that enable cognitive neuroscience investigations, globally. We are interested in PET and MRI techniques for population cognitive neuroscience and for understanding mind-brain-body and environment interactions. We use physics-informed computational techniques to improve image resolution and sensitivity and develop imaging biomarkers for early detection of changes in brain physiology, neurochemistry, and macrostructure.

Dr Douglas Arnold is a neurologist with special expertise in MRI. His personal research interests are centered on the use of advanced neuro-imaging techniques to assess the pathological evolution of multiple sclerosis and Alzheimer's disease and to quantify the effects of therapy on these diseases.

Dr Arnold's MRS Lab uses conventional Magnetic Resonance Imaging (MRI), Magnetic Resonance Spectroscopy (MRS) and other advanced imaging techniques such as Magnetization Transfer Imaging (MTI) to gain a better understanding of the nature, evolution, and response to therapy of neurological disorders -- particularly multiple sclerosis (MS). Increasingly, the laboratory is focusing on the development and use of advanced image processing of MRI data in order to probe more deeply into the pathogenesis of disease and how this is affected by therapeutic interventions.

’s broad objective is to comprehend the nature and macroscopic mechanisms of large-scale, network brain activity — how they enable complex behavior, how they are altered in disease.

We don’t specialize in specific brain functions or syndromes. We want to find their common denominator.

nurtures in computational and empirical approaches to systems neuroscience — with a blend of imaging, multi-scale electrophysiology, cognitive and clinical neuropsychology, biophysics, computer and data science.

We also provide support and expertise to investigators interested in using MEG for their cognitive and clinical neuroscience research. The MEG core unit at McGill’s Montreal Neurological Institute is part of the McConnell Brain Imaging Centre, and is an open platform for academic and industry researchers.

The research activity of NOELÌýis centered on the development of advanced magnetic resonance imaging (MRI) techniques to better understand causes, consequences and mechanisms responsible for epilepsy.

In the spirit of The Neuro, an integrated hospital and research facility, the NOEL provides a unique multidisciplinary environment for graduate students and postdoctoral fellows in Neuroscience, Biomedical Engineering, Computer Science and Neurology.

Our ultimate goal is to demonstrate that advanced MRI techniques may lead to major improvements in the quality of care of epileptic patients, particularly those with pharmacoresistant forms that are candidate for epilepsy surgery.

Boris Bernhardt is a cognitive scientist with expertise in neuroimaging, network neuroscience, and statistical learning. He joined McGill as Assistant Professor of Neurology and Neurosurgery in 2016 and heads the Multimodal Imaging and Connectome Analysis Lab.

His group develops integrative analytics to study large-scale brain organization, connectivity, and neurodevelopment. One focus is the study of individual differences in connectome architecture in developing and adult populations, and the relation to variability in high-level cognition and socio-affective competences. His team studies healthy and diseased populations, notably drug-resistant epilepsy and autism spectrum disorders, two common and persistent conditions of early onset.

There is now increasing momentum in data sharing, open access, and data collection consortia that build richly annotated "big data" repositories for brain and behavior. This unprecedented data setting creates a rapidly growing potential to provide principled answers to human brain organization and its disturbances in brain disease. Dr Bzdok will take the opportunity to explore, formalize, and predict brain phenotypes of hidden population variation by capitalising on heterogeneous data sources to tackle open questions in systems neuroscience in a way that also paves new ways for precision medicine in brain health.

One of the least expected discoveries that emerged from imaging neuroscience is the "default network". This macroscopical brain network in the recently evolved association cortex probably has a highest metabolic consumption and features the perhaps highest neuronal baseline activity. Functional processing in this network is associated with a diversity of human-defining psychological processes: complex social cognition, such as perspective-taking, language and moral judgment, as well as the imagination of events and places in future and past. At the same time, the default network has been linked to a range of neurodegenerative and psychiatric disorders, including dementia and schizophrenia. Despite its significance for human intelligence, the physiological purpose of this network remains essentially unknown.

His research group is dedicated to such interdisciplinary challenges in a domain-agnostic approach (especially high- but also low-level cognitive processes) leveraging several recently emerged population datasets (such as UK Biobank, HCP, CamCAN, ABCD) across levels of observation (brain structure and function, consequences from brain lesion, or common-variant genetics) using a broad toolkit of bioinformatic methods (machine-learning, high-dimensional statistics, and probabilistic Bayesian hierarchical modeling).

The overarching goal of our research is to understand the relation between brain organization and cognitive development. We examine how large-scale brain networks support learning, memory and language. We are particularly interested in the neural developmental processes underlying these cognitive functions from children to adults, and how experience and disease can alter brain organization. Our research methodology includes behavioral, brain imaging (fMRI, resting-state fMRI, DTI) and computational approaches.Ìý

Justine Cléry is studying which and how brain networks support cognitive processing such as sensory processes and social cognition, and how they are established and modulated across our lifespan. Her lab uses neuroimaging techniques (functional and structural magnetic resonance imaging, diffusion, microstructural imaging) and behavioural measurements (eye-tracking, touchscreen-based tasks, reaction times, observation) in nonhuman primate models (macaques and marmosets). In addition, her lab investigates these brain mechanisms in control and autistic subjects.

The Neuro Imaging and Surgical Technologies Laboratory develops computer vision image processing algorithms for analysis of medical images that are focused on registration and segmentation. These techniques are applied to different research projects that include image guided neurosurgery and disease diagnosis, prognosis and quantification for diseases such as multiple sclerosis, epilepsy, schizophrenia and degenerative diseases such as Alzheimer’s dementia.

In the Neuro Imaging and Surgical Technologies Lab of the Brain Imaging Centre of , our team develops computerized image processing techniques such as non-linear image registration, model-based segmentation and appearance-based segmentation to automatically identify, quantify and characterize structures within the human brain. These techniques are applied to large databases of magnetic resonance (MR), computed tomography (CT) and ultrasound (US) data from normal subjects to quantify anatomical variability and to characterize the morphological changes associated disease. The data derived can be used for diagnosis and prognosis and to help study natural history of disease and to improve understanding of disease pathology. In image-guided neurosurgery (IGNS), these techniques provide the surgeon with computerized tools to assist in integrating and interpreting anatomical, functional and vascular imaging data, permitting the effective planning and execution of minimally invasive neurosurgical procedures. Our research has been supported by grants from , , FQRNT, , and .

Dr Dagher is a neurologist specializing in movement disorders and functional brain imaging. His research aims at understanding the function of the basal ganglia, with a particular emphasis on appetitive behaviours. This involves studying how we learn about rewards and punishments, and become motivated to engage in reward seeking behaviours. The two main techniques used are positron emission tomography (PET) targeting the dopamine system, and functional magnetic resonance imaging (fMRI). The research focuses on Parkinson’s disease, stress, drug addiction (notably cigarette smoking), pathological gambling, and obesity. Dr Dagher is funded by CIHR, FRSQ, NIDA, the Parkinson Society of Canada, The Institute for Research on Pathological Gambling and Related Disorders, and Unilever PLC.

The Human Dopamine Neuroimaging Laboratory examines various pathological states that are related to a disruption in dopamine function. These range from motor disease (Parkinson’s) to addictive disorders (gambling, smoking, obesity). We are currently employing various neuroimaging techniques, including functional MRI, PET and rTMS; in concert with these types of data we are also investigating some of the behavioral, endocrine and metabolic correlates of these syndromes so that we may gain a better and more thorough understanding into the complexities of these disease states.

Research in our laboratory is structured around two poles: a fundamental research pole that is focused on theÌýneuroscience of learning and memoryÌýand an applied research pole that seeks to apply the knowledge gained therein inÌýneurodegenerative and neurological diseases, such as Parkinson’s and amyotrophic lateral sclerosis.

In our basic research work, we use multi-modal imaging techniques (MRI, EEG) and multi-disciplinary approaches to investigate the way people acquire motor skills, and to characterize the brain and spinal cord neuroplasticity specific to motor learning at different time scales. We also investigate the role of sleep in the consolidation of both procedural (i.e. motor skills) and declarative (i.e. information about facts and events) memories and the neurophysiological mechanisms underlying this phenomenon.

In our applied research work, we seek to understand how aging and disease impact the cerebro-spinal neuroplasticity associated with motor learning and we use state-of-the-art neuroimaging techniques that we pioneered in the last 7 years to develop cerebro-spinal biomarkers of Parkinson’s disease that could be used for early screening and diagnosis, as well as for disease progression monitoring.

The FTD & Neuropsychiatry Lab led by Dr Simon Ducharme aims to develop clinical and therapeutic tools for neuropsychiatric disorders, focusing on major neurocognitive disorders. We are conducting translational studies using structural and functional imaging in frontotemporal dementia (FTD) to improve early diagnostic markers for this devastating disease. Our group is involved in several national and international neuroimaging studies on dementia, in addition to innovative clinical trials on Alzheimer’s disease and FTD.

ACELab was established in 1984, when Dr Evans moved to the Montreal Neurological Institute (MNI) at McGill University to continue his PET research. The lab has made pioneering contributions to multi-modal brain imaging with PET and MRI, image processing and large-scale brain database analysis and cutting edge 3D computer imaging techniques, and continues to foster a research and training environment to use these methods and address long-standing questions about brain development and neurodegenerative diseases.

Some of the globally important achievements of the ACElab include:
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Recently, the ACElab has received support to launch The McGill Centre for Integrative Neuroscience (MCIN), which constitutes the neuroinformatics component of the Ludmer Centre for Neuroinformatics and Mental Health. The MCIN aims to be an international leader in the integration of imaging and genetics via information sciences, providing a platform for advances in basic neuroscience and clinical care.

The MCIN builds on 30 years of research in the ACElab at the McConnell Brain Imaging Centre in Montreal Neurological Institute, to continue computationally-intensive brain research using innovative mathematical and statistical approaches. Research at the ACElab involves developingÌý,Ìý, as well asÌýÌýin large-scale cohort studies.

The ACElab continues to develop computational and analytical infrastructure and platforms to integrate clinical, psychological or neuroimaging phenotypes with genotypic information.

Richard Hoge is an Associate Professor in the Department of Neurology and Neurosurgery, and Director of the Human Magnetic Resonance (MRI) Program. Hoge is a physicist who develops new brain imaging technology that is used to examine cognitive processes in the elderly. He creates programs for functional MRI and advanced positron emission tomography (PET) to study the state of brain function in both healthy and pathological subjects. He comes to The Neuro from the Université de Montréal, where he was associate director of the Functional Neuroimaging Unit CRIUGM and an associate professor at the Institute of Biomedical Engineering.

The NIL develops new MRI technologies for imaging vascular and metabolic function in the brain. The methods developed are applied to better understand the physiological events accompanying brain activation, and the changes that underly cognitive deficits seen during aging and dementia. We also study respiratory physiology and blood gas transport in the context of brain function.Ìý Ìý

Dr Yasser Iturria Medina, a Canada Research Chair Tier-2 on Multimodal Data Integration in Neurodegeneration, is an Assistant Professor in the Department of Neurology and Neurosurgery. He is also an associate member of the Ludmer Centre for Neuroinformatics and Mental Health and the McConnell Brain Imaging Centre. Yasser received his undergraduate degree in Nuclear Engineering from the Higher Institute for Nuclear Sciences and Technology, Cuba, in 2004, and his Master’s degree in Neurophysics and Neuroengineering from the Cuban Neuroscience Center in 2006. He then completed his PhD in Neuroimaging and Neuroinformatics at the National Center for Scientific Research and Havana’s University of Medical Science in 2013. He came to the MNI/BIC as a postdoctoral student in 2013, before being appointed as an Assistant Professor in 2018.

Research
Yasser's lab pursues primarily the goal of making precision medicine in Neurology a reality. It focuses on defining and implementing multiscale and multifactorial brain models for understanding neurological disorders and identifying effective personalized interventions. His research has spanned neurodegeneration modelling, brain multimodal connectivity estimation, and statistical analysis for characterizing/predicting abnormal brain states. He currently is focusing on the creation, validation and open-access sharing of integrative molecular, neuroimaging, and computational tools for understanding complex causal interactions among ageing, neurodegeneration and different therapeutic conditions.

The Radiochemistry and PET Tracers Development Laboratory develops and adopts the synthesis of novel positron emission tomography (PET) radiotracers to directly study expression of various molecular biomarkers in healthy and pathological CNS. We are now focused on exploring neurotrophin regulation and signalling via different receptors including p75NTR, Trk and sortilin. We are also interested in studying the regulation of neuropeptide Y transmission system through the development of ligands for Y2 receptors.

In addition, we are developing new and improved radiolabeling procedures for more time, labor and cost efficient synthesis of many clinically relevant PET tracers. Our approach allows for high yielding tracer syntheses with significantly reduced radiation burden on the radiochemistry lab personnel. Finally, we are studying a relative timeline of emergence of various biomarkers in patients with a history of repetitive brain traumas using recently developed PET tracers of neuroinflammation and misfolded protein accumulation

Dr Leyton is a Full Professor in McGill University’s Department of Psychiatry, a past-President of the Canadian College of Neuropsychopharmacology (CCNP), and a founding member of the Scientific Advisory Council to the Canadian Centre for Substance use and Addictions (CCSA). The focus of his research is the neurobiology of addictions and addiction related disorders. Dr Leyton received his B.Sc. from Memorial University of Newfoundland (MUN), and his M.A. and Ph.D. degrees at Concordia University’s Center for Studies in Behavioral Neurobiology (CSBN). As a graduate student, he studied the neurobiology of reward-seeking behaviors in laboratory animals. As a post-doctoral fellow, he learned the tools of clinical neuroscience and developed a research program designed to test these ideas in humans. During the past 25 years, he has produced a translational research program, developing new methods for manipulating neurotransmitter function and mapping the neurobiology of substance use in humans.

Dr Massarweh's group focuses on cutting-edge developments in radiochemistry along the following principal axes of research:

• Neurodegenerative diseases: The development and in-vivo evaluation of novel PET radiotracers for Alzheimer’s and Parkinson’s diseases to target β–Amyloid plaques, Tau protein and α–Synuclein protein using fluorine-18 and carbon-11;
• Oncology, cancer: The development and evaluation in vivo and in vitro of novel PET radiotracers to target brain, breast and prostate cancer;
• Radiolabeling methods: The development of novel synthetic methods using organic and inorganic catalysts for rapid radiolabeling of organic compounds;
• Radiometal complexes: The development of radiometal complexes for diagnostic and therapeutic applications in oncology. The development includes metal complex synthesis and radiochemical synthesis.

Bratislav Misic leads the Network Neuroscience Lab and investigates how cognitive operations and complex behaviour emerge from the connections and interactions among brain areas.

The goal of this research is to quantify the effects of disease on brain structure and function. His research program emphasizes representations and models that not only embody the topological organization of the brain, but also capture the complex multi-scale relationships that link brain network topology to dynamic biological processes, such as neural signalling and disease spread. Misic's research lies at the intersection of network science, dynamical systems and multivariate statistics, with a focus on complex data sets involving multiple neuroimaging modalities, including fMRI, DWI, MEG/EEG and PET.

Our aim is to produce and promote open and reproducible neuroimaging research, with a focus on neuroimaging data science and neuroinformatics. ORIGAMI stands for Open & Reproducible Imaging Genetics and Applied Machine Intelligence.

Our laboratory research program has two main axes. Fist, in order to better understand brain systems and their relation to brain pathologies, we are developing methods and tools to best analyse neuroimaging and genetics data in relation to omics, demographic, behavioural or clinical variables using large databases (e.g., the UK Biobank). Second, in relation with this first goal, we work to produce or foster more reproducible and replicable science in the field of neuroimaging genetics, and more generally in the life sciences. To this end, we use open science principles, and study how research is performed and published in our domain.

We also participate in the construction of tools and infrastructures to more easily disseminate, document, and harmonize datasets and generate re-usable pipelines and analysis methods. We exchange ideas and work with our colleagues in theÌýMcConnell Brain Imaging CentreÌýand theÌý. We are grateful for funding from Canadian Open Neuroscience Platform (), the National Institutes of Health (), and Healthy Brains for Health Lives (HBHL).

Translational Neuroimaging Laboratory (TNL) develops neuroimaging techniques and analytical frameworks for modeling neurodegenerative processes including deposition of protein aggregates, metabolic abnormalities, cell transport systems and neuroreceptors dysfunction. The laboratory encompasses a cohesive multidisciplinary team conducting integrative and multimodal neuroimaging research in human disease as well as disease models. TNL collaborates with an extensive network of laboratories and is committed to scientific training in the field of neuroimaging.

Our Mission:
• Advance methodologies for quantifying neurodegenerative processes using Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI).
• Develop analytical frameworks to interface animal and human neuroimaging.
• Enable preclinical diagnosis of dementing diseases by using imaging techniques.
• TNL welcomes young scientists and physicians interested in cutting edge integrative neuroimaging of neurodegenerative processes.

TNL is a member of the (Neuroinformatic Unit), the and the (Human Neuroreceptor Autoradiography Laboratory). TNL is affiliated with the McConnell Brain Imaging Centre (PET / Short-Lived Radioisotopes), the (MRI), and the (Fluid biomarker unit).

David Rudko is an Assistant Professor in the Departments of Neurology and Neurosurgery and Biomedical Engineering at the Montreal Neurological Institute of McGill University. Prof Rudko completed his PhD in Physics with a specialization in ultra-high field MRI under the supervision of Dr Ravi Menon at the University of Western Ontario.

The overall focus of his lab is the application of novel high-field MRI methodology in conjunction with biophysical modelling to augment the current understanding of brain anatomy and physiology. One of his specific goals is to extend magnetic susceptibility and relaxometry-based MRI models of brain tissue microstructure to develop atlases applicable to neurological disease. He has applied MRI physics techniques to research in animal models and human neurological diseases at field strengths of 3 T, 7 T and 9.4 T. His recent work has centred on quantification of cortical demyelination in MS patients using surface-based 3 T magnetization transfer imaging combined with ultra-high resolution 7 T structural imaging.

The research in our laboratory is focused on two goals. The first is to understand the neuronal mechanisms that underlie functional brain imaging signals, and to evaluate the degree to which these signals reflect the locally measured neuronal activity. The second is to elucidate the principles and processes used by the cerebral cortex to analyze visual information and to create coherent visual perception.

Our laboratory employs an integrative approach, using a combination of imaging and electrical recording techniques. These include functional Magnetic Resonance Imaging (fMRI), optical imaging using intrinsic signals and voltage sensitive dyes, multi-channel neurophysiological recordings, and neurophysiology simultaneously with fMRI. Together, these techniques encompass multiple levels of spatial and temporal resolution. Brain activity signals obtained by large scale non-invasive imaging methods are compared to the activity of ensembles of neurons imaged optically, and to electrically-recorded activity obtained from groups of neurons and single neurons.

Dana M Small is the Canada Excellence Research Chair in Metabolism and the Brain. She holds primary appointments in Neurology and Neurosurgery and in Internal Medicine. Professor Small received her PhD in Clinical Psychology from McGill University in 2001 and subsequently established her , where she was on faculty for 20 years. Her research combines neuroimaging and metabolic measurements to understand how the brain and body integrate signals from the external environment and the internal milieu to optimize behaviour and metabolism. Her laboratory also studies how dysregulation of these body-brain axes contribute to the development of obesity, diabetes, cognitive impairment and psychiatric disorders.

Jean-Paul Soucy, MD, M.Sc., is Unit Director, Positron Emission Tomography, at the McConnell Brain Imaging Centre of the Montreal Neurological Institute. He is a physician with primary training is in nuclear medicine and he has an MSc in Neuroscience. He completed a fellowship at Service Hospitalier Frédéric-Joliot, Orsay, France, working on the evaluation of brain perfusion in the acute phase of strokes.

Dr Soucy has expertise in the human applications of methods for the measurement of cerebral blood flow (absolute quantification) with SPECT, which he uses both clinically and in different research settings.

Most of his research and clinical work however has been in PET Neuroimaging. For instance, he has validated techniques to quantify monoaminergic innervations in vitro with the goal of transferring these approaches to in vivo use with PET. He is working on quantification of cholinergic systems using a PET ligand of the vesicular transporter for that transmitter. He has been active in amyloid and tau imaging research as he concentrated his activities in the field of imaging of neurodegenerative conditions. He is also involved in different projects applying signal enhancement techniques to nuclear-medicine-based neuroimaging.

On the clinical front, Dr Soucy has taken part in the definition of national practice norms for PET neurological metabolic and amyloid imaging in Canada and for SPECT imaging of dopaminergic systems in movement disorders.

Dr Soucy has participated in writing over 125 articles, 300 abstracts for research presented at national and international meetings, and has authored/co-authored 11 book chapters.

Nathan Spreng is studying how brain networks support various cognitive processes such as remembering information, and how we use this knowledge to influence our decisions. His lab examines large-scale brain network dynamics and their role in cognition. Currently, we investigate attention, memory, cognitive control, and social cognition, and the interacting brain networks that support them. We are also actively involved in the development and implementation of multivariate and network-based statistical approaches to assess brain structure, connectivity and activity. In doing so, we aim to better understand the properties of brain networks underlying cognitive processes as they change across the lifespan in health and disease.

Dr Christine Tardif is an Assistant Professor in the Department of Neurology and Neurosurgery and the Department of Biomedical Engineering. She is also a member of the magnetic resonance imaging (MRI) core of the McConnell Brain Imaging Centre.

The lab develops novel MRI techniques to generate high-resolution quantitative MR images of the brain in-vivo, and relates them to microstructural features of the tissue. Methodological developments include novel image acquisition techniques, multi-modal biophysical modelling, and high-resolution cortical modelling. The lab has a translational approach, working on both small animal (7 Tesla) and human (3 and 7 Tesla) MRI systems.

Dr Tardif’s research has focused on MRI-based investigations of myelin, a lipid-rich cellular membrane that forms an insulating sheath around axons to achieve and maintain the rapid conduction and synchronous timing of neural networks. Myelination is a lifelong dynamic process of forming and modulating myelin sheaths. It underlies key mechanisms of brain plasticity and higher order cognitive functions. In addition to demyelinating diseases such as multiple sclerosis, there is accumulating evidence that dysmyelination contributes to psychiatric disorders as well. Dr Tardif’s lab investigates myelination (in both white and grey matter) using multiple MRI techniques such as relaxometry, magnetization transfer and diffusion-weighted imaging.

The Villeneuve Lab is interested in how the brain ages, with a specific focus on factors that modify the association between brain lesions and cognitive performance. Our research is motivated by the fact that more than 25% of older adults are considered cognitively normal despite the presence of beta-amyloid in their brain, a hallmark of Alzheimer’s disease. This fact suggests that other factors interact with beta-amyloid to trigger cognitive deficits in Alzheimer’s disease. It also suggests that actions can be taken to prevent or postpone disease-related symptoms. The main focus of the Villeneuve Lab’s research is therefore to examine the factors that protect against, or worsen, the development of cognitive deficits in age-related neurodegenerative diseases.

Robert Zatorre is a cognitive neuroscientist at the Montreal Neurological Institute of McGill University. He was born and raised in Buenos Aires, Argentina, and carried out his doctoral studies at Brown University with the late Peter Eimas, followed by postdoctoral work with Brenda Milner. He currently holds a Canada Research Chair at the Montreal Neurological Institute of McGill University. In 2006 he became the founding co-director, with Isabelle Peretz, of the international laboratory for Brain, Music, and Sound research (BRAMS). His work has been recognized with several awards including the IPSEN foundation prize in neuronal plasticity in 2011, the Knowles prize in hearing research from Northwestern University in 2013, election to the Royal Society of Canada in 2017, and the de Carvalho-Heineken prize in cognitive science from the Netherlands Academy of Arts and Sciences in 2020. He is also a fellow of the Canadian Institute for Advanced Research.Ìý

Dr Zatorre’s lab studies the neural substrates of auditory cognition, with special emphasis on two complex and characteristically human abilities: speech and music. With his collaborators and students Dr Zatorre has published over 300 scientific papers on topics including pitch and melody perception, auditory imagery, music production, brain plasticity in musicians, and the role of the dopaminergic reward circuitry in mediating musical pleasure. His research spans all aspects of human auditory processing, from the functional and anatomical properties of auditory cortex and its connectivity, to how these properties differ between the hemispheres, and how they change with training or sensory loss.

Examples of recent research projects include: using graph theory models to understand anatomical connectivity of the auditory cortex from MR diffusion data (Misic et al,ÌýCereb Cortex, 2018); using MEG to track the cortical and subcortical responses to periodicity (Coffey et alÌýNature Comm, 2016, 2019); applying machine learning algorithms to fMRI to investigate reward-related brain activity to music (Gold et al,ÌýPNAS, 2019); demonstrating hemispheric asymmetries in fMRI activity to speech and melody in relation to spectrotemporal modulations (Albouy et al,ÌýScience, 2020); and application of brain stimulation paradigms to enhance auditory working memory (Albouy et al,ÌýNeuron, 2017) and to modify hedonic responses to music (Mas-Herrero et al,ÌýNature Hum Beh, 2018;ÌýJ NeurosciÌý2021). Dr Zatorre's activities are funded by CIHR, NSERC, CFREF and CIFAR.