Abstract #3346

Precision neuroimaging and connectomics: individual human brain at ultra-high fields

Donna Gift Castro Cabalo¹, Ilana Ruth Leppert², Risa Thevakumaran², Shahin Tavakol¹, Jessica Royer¹, Jordan DeKraker¹, Youngeun Hwang¹, Valeria Kebets¹, Yezhou Wang¹, Oualid Benkarim¹, Nicole Eichert³, Casey Paquola⁴, Sofie Valk⁵, Jonathan Smallwood⁶, Christine Lucas Tardif², David Rudko², Raul Rodriguez-Cruces¹, and Boris Bernhardt¹

¹Montreal Neurological Institute, McGill University, Montreal, QC, Canada, ²McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, Montreal, QC, Canada, ³University of Oxford, Oxford, UK, Oxford, United Kingdom, ⁴Institute for Neuroscience and Medicine (INM-7), Forschungszentrum Juelich, Juelich, Germany, ⁵Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, ⁶Queens University, Kingston, ON, Canada

Synopsis

Keywords: Data Acquisition, Precision & Accuracy, Quantitative Imaging, fMRI (resting state), fMRI (task based)

Motivation: Traditional MRI methods often includes averaging data from brief scanning sessions, which limits specificity and reliability.

Goal(s): Our goal is to improve understanding of brain structure-function relationships in the individual human brain.

Approach: We used 7 Tesla MRI to scan 10 healthy participants over three sessions (4.5 h of scan time/subject). We derived measures of anatomy, microstructure and multi-state functional MRI, to capture brain network interactions and reconfigurations during rest, memory tasks and movie-watching.

Results: We release the multimodal Precision Neuroimaging and Connectomics (PNI) dataset for open research.

Impact: Our PNI dataset offers openly accessible, ultra-high resolution 7T MRI data across multiple sessions, enabling researchers to explore structure-function relationships in the brain with unprecedented detail and supporting reproducible neuroscience research.

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