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Ep. 33: Brain Imaging of Chronic Pain with Anton Rogachov and Connor Wander

The Straight from a Scientist Podcast

Release Date: 09/02/2018

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More Episodes

This week we talked with Anton Rogachov, a 5th year PhD student in Dr. Karen Davis’s Lab at the University of Toronto.  The Davis Lab focuses on using brain imaging like resting-state fMRI to understand functional abnormalities in the brains of chronic pain patients.  The majority of Dr. Davis’s work looks at the functional communication between different brain regions and networks in order to understand how these communications break down in chronic pain.  In comparison, Anton's research looks at regional brain oscillation and fluctuations an alternative approach to studying mechanistic brain function.

Listen in to hear us discuss Anton's recent paper, Abnormal Low-Frequency Oscillations Reflect Trait-Like Pain Ratings in Chronic Pain Patients Revealed through a Machine Learning Approach.  This research discovered that chronic pain patients do indeed have functional abnormalities in pain-related brain networks, but more importantly it showed that these abnormalities can be used to make inferences about the degree of pain the patients experience on a weekly basis.  We cover what it's like to work directly with patients and to both administer and be tested via fMRI.  We also talk about important caveats and considerations with work such as ours.

More information

Read Anton’s recent paper on abnormal low-frequency oscillations

Learn more in another publication by Anton on regional brain signal variability

Check out a related episode on the molecular side of pain research, Ep. 30: Breaking the Vicious Cycle of Pain and Addiction with Waylin Yu.

Listen to the Raw Talk Podcast run by scientists and medical students at the University of Toronto.

Watch the TED Ed. video from Anton's supervisor Dr. Karen Davis on how your brain responds to pain.

Thanks to Leigh at BrainPost for connecting us with Anton!

Any other questions?  Let us know!  We appreciate your feedback.

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