Chetan Gohil
@Chetan__Gohil
Data analysis is hard. We tried to make it easier (for M/EEG)! We developed a toolbox based on MNE-Python to make preprocessing, source recon, and other analysis easier, and more efficient, transparent, and reproducible. It's called osl-ephys - check it out! (links below)
🧠 Interested in brain resting-state networks (RSNs)? Check out our latest paper demonstrating that MEG and EEG offer comparable static and dynamic descriptions of RSNs: doi.org/10.1002/hbm.70… w/ my amazing mentors @mats_van_es , @markwoolrich , and @Chetan__Gohil !
How can we further the study of oscillatory responses in task ephys data? Adopt a dynamic network approach! Check out our paper illustrating the advantages of a dynamic network analysis compared to conventional time-frequency approaches: direct.mit.edu/imag/article/d…
Exciting times ahead!
MEG-UKI 2024 is coming to Birmingham! Save the date: Mon 28th - Thu 31st October We are teaming up with our colleagues in the world of OPMs to bring you four days of cutting-edge neuroscience and Magnetoencephalography. More info below, and on our site: uobevents.eventsair.com/meguki/
Our session on "Functional Connectivity Dynamics: New Approaches and Applications" was a great success! Thx everyone for attending!
@Chetan__Gohil will show how unsupervised methods enable us to capture fast phase locking networks in MEG
We are very happy to present our symposium on “Functional connectivity dynamics: new approaches and applications” at #OHBM2024 tomorrow (Tuesday) at 4 pm in the Grand Ballroom 101-102. Let me already introduce the speakers:
Next generation Dynamic Network Modes; Using deep learning to go beyond the HMM... I hope everyone is ready for this! Massive congrats to @ChetanG83095127 , Evan Roberts, @blobsonthebrain @markwoolrich and co-authors. @OxfordWIN @OxPsychiatry biorxiv.org/content/10.110…