Mainak Jas

At #SfN18 and wondering how to get started with #BIDS for #MEG/#EEG/iEEG? The first official release of mne-bids is just for you: mail.nmr.mgh.harvard.edu/pipermail//mne…. Documentation is here: mne-tools.github.io/mne-bids/ Teamwork with @teon_io, @stefanappelhoff, @choldgraf, @agramfort and others!

Do you work with OPM-MEG for neuroimaging 🧠? If you want to DIY your own PCB field nulling coils, check out our new preprint: biorxiv.org/content/10.110… With @mainakjas, Jack Kamataris, @abbas_neuro, Teppei Matsubara, @mshamalai and others from @MGHMartinos MEG.

Proud to support "MEGnificent brain discoveries" this week, championed by @mcgovernmit & @dimitrpantazis . Excellent presentations by @davidpoeppel , @leylaisi & @sylvain_baillet and #MEG Software Presentations from @mainakjas , Sylvain Baillet and @pelednoam #MIT #McGovern

Join us Tuesday March 5th, 2024 at 12 pm EDT for a joint special BrainMap/MEG Seminar Series Webinar at @MGHMartinos by Prof. Sylvain Baillet (@sylvain_baillet ) Webinar link: martinos.org/event/brainmap… Contact the organizers for more info: @_SrOsorio @abbas_neuro

To preprocess or not to preprocess your #EEG (when building #ML models) 🔮? 💫We are thrilled to share our latest #preprint, studying the challenge of learning brain-specific biomarkers from EEG 🧠📶 using #ML ⚙️🖥️: biorxiv.org/content/10.110… We compile arguments and evidence from benchmarking age- & sex-prediction on > 2600 EEGs from two large public datasets. We found that basic artifact rejection consistently led to better model performance, whereas removal of ocular and muscle artifacts hampered performance. As it turns out that those peripheral signals are predictive themselves! Our results therefore argue in favor of the need to diligently process EEG data, if the goal is to have brain-specific biomarkers (and if prediction is not the only objective). Our efforts to build more interpretable #ML models for EEG led us to extending the established Morlet wavelet methodology for spectral analysis of EEG to accommodate state-of-the-art ML models based on covariance matrices. This allowed us to perform head-to-head comparisons between classical EEG features and frequency-specific model predictions for, both, brain and artifact signals. Compared to classical band-pass filtering, wavelets even led to improvements in prediction performance. Joint work with Philipp Bomatter, @JP4illard, Pilar Garces & Jörg F Hipp.

Thrilled to announce the 0.3 release of hnn-core; a user-friendly python package for the simulation of cortical activity underlying #MEG/#EEG. This update includes a new GUI, and a revamped API to modify/record the network. `pip install hnn_core[gui]` and give it a try! 🧠🚀

@DanFeuerriegel Probably a better title would be “EEG data should be sometimes left alone.” The datasets considered were also relatively clean and thus do not require extensive preprocessing. A catch all recommendation for preprocessing is fundamentally flawed

Check out this excellent opportunity to join @MGHMartinos and investigate ASD with #MEG 👇👇👇

@gozemturan @AcademicEEG Have you looked at this tutorial by @alex_p_rockhill : #sphx-glr-auto-examples-plot-autoreject-workflow-py" target="_blank" rel="nofollow noopener">autoreject.github.io/stable/auto_ex… ?

Hey all @AcademicEEG is there anyone who uses AutoReject from @mainakjas? If yes, in which order are you using it -before and after ICA as recommended?

@HNNsolver is participating under the @INCForg umbrella this year! Reach out to us if you love #Python coding + #neuroscience 🧠👨‍💻👩‍💻 Earlier the better! Ideas page is here: github.com/jonescompneuro…

We’re excited to announce the 0.2 release of hnn-core; a python package for simulating cortical activity underlying #MEG/#EEG. This update includes LFP simulations, optimization, and an easy network modification API. `pip install hnn_core` to try it out! jonescompneurolab.github.io/hnn-core/

I am pleased to announce the publication of our manuscript in Cell Reports, check it out here: sciencedirect.com/science/articl…

@petrzzz @memming I use pyglmnet and it works great! I don't know if it has particular features for building design matrices, but it allows nice control over regularization parameters and different link functions, as well as different scoring functions. @mainakjas github.com/glm-tools/pygl…

@DirkGuetlin nice blogpost :) drive by comment ... have you compared to human annotations? decoding accuracy can be high if you have imbalanced distribution of artifacts between the classes ...

You want to apply automated cleaning to your EEG preprocessing but don't know what algorithms exist, what they do to your data, and where you can get them? Maybe this notebook could be a start: digyt.github.io/automated_EEG_… It's still far from complete, so suggestions are welcome!

‘Whole-head OPM-MEG enables noninvasive assessment of functional connectivity’ by @MainakJas, @DrStephJones & Matti Hämäläinen, @mshamalai cell.com/trends/neurosc… @TrendsNeuro ‘Spotlight’ on Boto et al., 2021 @NeuroImage_EiC, @MattBrookesMEG sciencedirect.com/science/articl…

We are happy to announce the release of MNE-Python 0.22.1!🎈 This is mainly a bugfix release 🪲🚫 but also adds support for reading the latest @eeglab2 files. All users of MNE-Python 0.22.0 are encouraged to update. mne.discourse.group/t/mne-python-0… #python #neuroimaging #meg #eeg

Just do "$ pip install hnn_core" to start modeling and testing circuit-level hypotheses on ERFs and spontaneous rhythms! Documentation is here: jonescompneurolab.github.io/hnn-core/. Feedback and critiques welcome! #brainimaging #python #neuroscience

Had an awesome time during the @mne_python code sprint this week! #OpenSource #OpenScience Pleasure to work with @alex_p_rockhill , @LibertySays , @agramfort , @mainakjas , @stefanappelhoff , @RHoechenberger , and the other mne devs. Sick package for IEEG processing!

The 2nd MNE-Python office hours are today Fri 05 Feb 16:00 UTC (In one hour). More info: mne.discourse.group/t/next-mne-pyt… See you on the MNE discord channel discord.gg/rKfvxTuATa

The problem is not people being uneducated. The problem is that people are educated just enough to believe what they have been taught, and not educated enough to question anything from what they have been taught. 🧠