Difference between revisions of "Club MEG"

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'''''Prior ML SIG topics:'''''
 
'''''Prior ML SIG topics:'''''
 
*'''03/04/2022''' Dave Dash - Decoding speech with MEG <ref>Dash D, Ferrari P, Wang J. Decoding Imagined and Spoken Phrases From Non-invasive Neural (MEG) Signals. Front Neurosci. 2020;14:290. Published 2020 Apr 7. doi:10.3389/fnins.2020.00290</ref>  <ref>Dash D, Wisler A, Ferrari P, Davenport EM, Maldjian J, Wang J. MEG Sensor Selection for Neural Speech Decoding. IEEE Access. 2020;8:182320-182337. doi:10.1109/access.2020.3028831</ref>  <ref>Dash D, Ferrari P, Dutta S, Wang J. NeuroVAD: Real-Time Voice Activity Detection from Non-Invasive Neuromagnetic Signals. Sensors (Basel). 2020;20(8):2248. Published 2020 Apr 16. doi:10.3390/s20082248</ref>  
 
*'''03/04/2022''' Dave Dash - Decoding speech with MEG <ref>Dash D, Ferrari P, Wang J. Decoding Imagined and Spoken Phrases From Non-invasive Neural (MEG) Signals. Front Neurosci. 2020;14:290. Published 2020 Apr 7. doi:10.3389/fnins.2020.00290</ref>  <ref>Dash D, Wisler A, Ferrari P, Davenport EM, Maldjian J, Wang J. MEG Sensor Selection for Neural Speech Decoding. IEEE Access. 2020;8:182320-182337. doi:10.1109/access.2020.3028831</ref>  <ref>Dash D, Ferrari P, Dutta S, Wang J. NeuroVAD: Real-Time Voice Activity Detection from Non-Invasive Neuromagnetic Signals. Sensors (Basel). 2020;20(8):2248. Published 2020 Apr 16. doi:10.3390/s20082248</ref>  
** Recording Download: [https://megcore.nih.gov/MEG/DebadattaDash_MEG-SpeechDecoding_ClubMEG_03042022.mp4]
+
** Recording Download: [https://megcore.nih.gov/MEG/DebadattaDash_MEG-SpeechDecoding_ClubMEG_03042022.mp4 Dash 03/04/22 (mp4)]
 
*'''01/28/2022''' Lina Teichmann - Bayes Factors for Time-series Decoding
 
*'''01/28/2022''' Lina Teichmann - Bayes Factors for Time-series Decoding
 
** Recording Download: [https://megcore.nih.gov/MEG/Teichmann_MEGMachineLearningSIG_BayesFactorsTimeSeriesDecoding_01282022.mp4 Teichmann 01/28/22 (mp4)]
 
** Recording Download: [https://megcore.nih.gov/MEG/Teichmann_MEGMachineLearningSIG_BayesFactorsTimeSeriesDecoding_01282022.mp4 Teichmann 01/28/22 (mp4)]

Revision as of 15:30, 7 March 2022

Club MEG is our version of a journal club. We welcome NIH MEG researchers to lead discussions on any MEG topic, including interesting papers, experiment ideas, analysis techniques, or finding from your research.

Interested in presenting a topic? Email Fred Carver at carverf@nih.gov or Jeff Stout at stoutjd@nih.gov if you would like to present.

Notifications of upcoming talks are sent to the MEG_ANNOUNCE listserv.

Upcoming Talks/Discussions

Recent Talks/Discussions

Previous Tutorials and Training

Special Interest Groups

Machine Learning Special Interest Group (ML SIG) - 4th Friday of every month 1-2pm. Contact Jeff Stout for more information on joining or presenting.
Prior ML SIG topics:

References

  1. https://www.sciencedirect.com/science/article/pii/S2211124721005398?via%3Dihub Consolidation of human skill linked to waking hippocampo-neocortical replay Ethan R. Buch, Leonardo Claudino, Romain Quentin, Marlene Bönstrup, Leonardo Cohen
  2. https://github.com/hcps-ninds/Replay ANALYSIS CODE: Consolidation of human skill linked to waking hippocampo-neocortical replay
  3. Dash D, Ferrari P, Wang J. Decoding Imagined and Spoken Phrases From Non-invasive Neural (MEG) Signals. Front Neurosci. 2020;14:290. Published 2020 Apr 7. doi:10.3389/fnins.2020.00290
  4. Dash D, Wisler A, Ferrari P, Davenport EM, Maldjian J, Wang J. MEG Sensor Selection for Neural Speech Decoding. IEEE Access. 2020;8:182320-182337. doi:10.1109/access.2020.3028831
  5. Dash D, Ferrari P, Dutta S, Wang J. NeuroVAD: Real-Time Voice Activity Detection from Non-Invasive Neuromagnetic Signals. Sensors (Basel). 2020;20(8):2248. Published 2020 Apr 16. doi:10.3390/s20082248