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Updated: Jul 16, 2025

Network Analysis of the Default Mode Network Using Functional Connectivity MRI in Temporal Lobe Epilepsy
Published on: August 5, 2014
A state-of-the-art review on deep learning for estimating eloquent cortex from resting-state fMRI
Daniel A Di Giovanni1, D Louis Collins2
1Integrated Program in Neuroscience at McGill University, Montreal, Canada. daniel.digiovanni@mail.mcgill.ca.
Abstract:
Deep learning algorithms have greatly improved our ability to estimate eloquent cortex regions from resting-state brain scans for patients about to undergo neurosurgery. The use of deep learning has the potential to fully automate functional mapping of cortex in this context. We present a highly focused state-of-the-art review on current technology for estimating eloquent cortex from resting-state functional magnetic resonance scans and identify potential paths to meet this goal in the future.
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