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SUMMARY:Leveraging large-scale datasets in boutique MEG studies - Chetan G
 ohil\, University of Oxford\, UK.
DTSTART:20260209T123000Z
DTEND:20260209T133000Z
UID:TALK243244@talks.cam.ac.uk
CONTACT:Dace Apšvalka
DESCRIPTION:*Speaker (visiting in person):* Chetan Gohil\, University of O
 xford\, UK.\n\n*Title:* Leveraging large-scale datasets in boutique MEG st
 udies\n\n*Abstract:*\nMany MEG studies focus on specific clinical groups o
 r carefully designed tasks and consequently are based on relatively small 
 datasets. While these studies are well targeted\, drawing robust conclusio
 ns can be difficult when sample sizes are limited. At the same time\, larg
 e public MEG datasets are becoming increasingly available. Under the assum
 ption that features (such as spatiotemporal patterns) of brain activity ar
 e shared across populations and tasks\, these datasets can be used to supp
 ort analyses in smaller\, boutique studies. In this talk\, I will discuss 
 ways of leveraging large-scale MEG data (e.g. Cam-CAN) to improve inferenc
 e in boutique studies\, including normative modelling\, dynamic network ap
 proaches such as the Hidden Markov Model\, and newer deep learning approac
 hes known as 'foundation models'. I will highlight how these approaches ca
 n increase statistical power and robustness\, and discuss both their poten
 tial and their limitations. \n\n*Venue*: MRC CBU West Wing Seminar Room an
 d Zoom https://us02web.zoom.us/j/82385113580?pwd=RmxIUmphQW9Ud1JBby9nTDQzR
 0NRdz09 (Meeting ID: 823 8511 3580\; Passcode: 299077)\n
LOCATION: MRC-CBU\, 15 Chaucer Road\, Cambridge
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