Dynamic multivariate task fMRI analysis using Partial Least Squares in Matlab
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- Опубликовано: 22 авг 2024
- An IDRE-sponsored event at UCLA on September 18, 2023 @ 11:00 AM (PST).
Speaker: Prof. Nathan Spreng
James McGill Professor of Neurology and Neurosurgery, McGill University
Director, Laboratory of Brain and Cognition, Montreal Neurological Institute.
Abstract: Dynamic multivariate task fMRI analysis using Partial Least Squares in Matlab: Whole brain imaging provides extraordinary opportunities to identify coherent patterns in the spatial structure and spatiotemporal functioning of cortical and subcortical brain regions. This has led to an explosion of network neuroscience research over the past two decades. Initially, network studies adopted a general linear modelling (GLM) approach, following the early structural and functional activation studies. However, fMRI data is more amenable to multivariate approaches that consider dynamic aspects of brain function given its high dimensionality, temporal complexity, and the issue of multiple statistical comparisons. In this workshop, I will review a dynamic multivariate approach for task based fMRI data, Partial Least Squares (PLS). In this workshop, I will review practical aspects of PLS statistical modelling and analyses, introduce the PLS GUI interface in Matlab, and include key elements of analysis implementation and results interpretation.
About Speaker: Dr. Nathan Spreng is the James McGill Professor of Neurology and Neurosurgery at McGill University, and director of the Laboratory of Brain and Cognition at the Montreal Neurological Institute. His research examines large-scale brain network dynamics and their role in cognition. Currently, he is investigating the links between memory, attention, cognitive control, and social cognition and the interacting brain networks that support them. He is also actively involved in the development and implementation of novel multivariate statistical approaches to assess activity and interactivity of large scale brain networks. His work adopts a network neuroscience approach to investigating complex cognitive processes as they change across the lifespan, both in normal aging and brain disease.