PRiME, at the University of Toronto is delighted to welcome Shahar Arzy from the Hebrew University of Jerusalem (HUJI) as the Connaught Global Speaker, in partnership with T-CAIREM.
PRiME Connaught Global Speaker: AI/ML - Driven Precision Aging
Shahar Arzy, MD, PhD
Professor of Medical Neurosciences
Dr Ernest and Dr Mona Spiegel Chair in Neurophysiology
Faculty of Medicine & Department of Cognitive and Brain Sciences
Neuropsychiatry Clinic, Hadassah Medical Center, Jerusalem Israel
Keynote talk title: "The past and future of Alzheimer’s Disease: From a deterministic disease to a heterogeneous disorder"
Abstract
Critical for studying Alzheimer disease (AD), understanding it, and developing treatment, its definition along the years keep changing. Dr. Arzy will first review the different definitions proposed for AD from its original characterization by Kraepelin in 1908, to the recent National Institute on Aging and Alzheimer’s Association revised criteria 2024. He will describe these definitions in parallel to the new knowledge gained, demonstrating how they alternate from restricted and circumscribed clinicopathological characterizations to wide open clinical and pathological ones. Then, he will detail a multiarray of AD as a heterogeneous, multifactorial and multifaceted disorder, associated with neurological, psychiatric, and systemic comorbidities, implying a network-based approach to the pathological progression of the disease. These include the cognitive-behavioral symptomatology and clinical profiles associated with AD, the various pathological mechanisms involved, brain changes and genetic variability. I suggest that these diverse changes give rise to several definable phenotypes of the disease. Finally, he will draw a computational framework that may enable us to deal with the richness and complexity of the different characteristics and domains in the individual patient level. Shahar and his lab speculate that the computational and data revolutions may help to expose this richness through at-scale ecological evaluations, large databases, computational modeling and novel hypothesis-free analyses.
Following his keynote talk, Shahar Arzy will be joined by Michael Brudno and Bradley Buchsbaum for a panel discussion on the role of Al/ML in precision aging and cognitive health, moderated by Allison Sekuler.
Panel discussion: Role of AI/ML in precision aging and cognitive health
About our speakers:
Shahar Arzy is the Director of the Computational Neuropsychiatry Lab (CNP Lab) at the Faculty of Medicine, The Hebrew University of Jerusalem, and the lead neurologist of the Neuropsychiatry Clinic at Hadassah Medical Center, affiliated with the Hebrew University of Jerusalem. He received his medical degree and master’s in cognitive science from the Hebrew University of Jerusalem and PhD from the Swiss Institute of Technology and the University of Geneva under Prof. Olaf Blanke. Following, he specialized in Neurology at Hadassah Medical Center (Prof. Tamir Ben-Hur) and in Cognitive Neurology in Geneva University Hospital (Prof. Theodor Landis). Shahar also trained in memory research at Harvard University under the mentorship of Prof. Dan Schacter. Shahar profits much from close collaborations and continuous discussions with exceptional researchers and friends worldwide.
Shahar’s main interest is the human self and its relations to the surrounding world – the space in which we live, the river of time who carries our memories and future plans and imagination, and people around us, as well as more conceptual frameworks. To this aim he apply tools from cognitive neuroscience, functional neuroimaging, virtual-reality and computational neuroscience. As an active clinician he is interested in the way in which these relations are disturbed in neuropsychiatry, and especially in Alzheimer’s disease.
Allison Sekuler (FSEP, FPS, FAPS) is the Sandra A. Rotman Chair in Cognitive Neuroscience and Vice-President Research at Baycrest Health Sciences. Dr. Sekuler holds faculty positions in the Department of Psychology, Neuroscience & Behaviour at McMaster University and the Department of Psychology at the University of Toronto. Her research uses behavioural and neuroimaging approaches to understand how the brain processes visual information, with specific interests in face perception, motion processing, perceptual learning, neural plasticity, aging, and neurotechnology. Her research was the first to show conclusively that older brains “rewire” themselves to compensate for functional changes. Her clinical and translational research aims to develop methods to prevent, detect, and treat age-related sensory and cognitive decline. She has scientific and industry collaborations across North America, the EU, and Asia, and her work has been published in leading international journals, including Nature, Current Biology, and the Journal of Neuroscience.
Michael Brudno is a Professor in the Department of Computer Science at the University of Toronto and the Chief Data Scientist at the University Health Network (UHN). He is also a faculty member at the Vector Institute for Artificial Intelligence and the Scientific Director of HPC4Health, a private computing cloud for Ontario hospitals. Michael’s primary area of interest for his research is the development of computational methods for the analysis of clinical and genomic datasets, especially the capture of precise clinical data from clinicians using effective user interfaces and its utilization in the automated analysis of genomes. His work focuses on the capture of structured phenotypic data from clinical encounters, using both refined user interfaces, and mining of unstructured data (based on machine learning methodology), and the analysis of omics data (genome, transcriptome, epigenome) in the context of the structured patient phenotypes.
Michael received a BA in Computer Science and History from UC Berkeley and later received his Ph.D. from the Computer Science Department of Stanford University, working on algorithms for whole-genome alignments. He completed a postdoctoral fellowship at UC Berkeley and was a Visiting Scientist at MIT. He is the recipient of the Ontario Early Researcher Award and the Sloan Fellowship, as well as the Outstanding Young Canadian Computer Scientist Award.
Bradley Buchsbaum studies how we consciously remember the past—why some memories are vivid and others vague—and how these experiences are reflected in brain activity. His lab uses functional MRI and machine learning to decode the content and quality of memory from neural patterns, with a focus on how memory changes with aging. They are also developing AI-based diagnostic tools for detecting mild cognitive impairment and Alzheimer’s disease from figure drawing tasks such as the clock drawing test. These methods offer promising, accessible avenues for early screening and precision assessment of cognitive decline.