https://youtu.be/ivjFst1iTtA

#BCI_talks #new_BCIs #EEG #MEG #eye_tracking #youtube

Prof. Vladimir Litvak (UCL):

"Our next SPM for MEG/EEG course will take place online May 23-26. Details and registration here https://www.fil.ion.ucl.ac.uk/spm/course/london/ . Please spread the word."

"We would definitely consider waiving the registration fee for anyone affected by the ongoing conflict in Ukraine."

https://twitter.com/LitvakVladimir/status/1509085331357941762

#MEG #EEG #SPM #courses

Статья про известную базу данных в открытом доступе, содержащую ЭЭГ, записанную во время запоминания и вспоминания у тренированных испытуемых, с большим количеством повторов у каждого испытуемого:

Michael J. Kahana, ...,
Christoph T. Weidemann.The Penn Electrophysiology of Encoding and Retrieval Study.
https://psyarxiv.com/bu5x8/

"Across five PEERS experiments, 300+ subjects contributed more than 7,000 90 minute memory testing sessions with recorded EEG data. Here we tell the story of PEERS: its genesis, evolution, major findings, and the lessons it taught us about taking a big science approach to the study of memory and the human brain."

"We achieved these goals through a 10 year data collection effort"

#databases #bigdata #EEG

Рекомендации по весьма актуальному сейчас подходу к анализу ЭЭГ и МЭГ - разделению осцилляций и апериодических 1/f компонентов:

Moritz Gerster, Gunnar Waterstraat, Vladimir Litvak, Klaus Lehnertz, Alfons Schnitzler, Esther Florin, Gabriel Curio, Vadim Nikulin. Separating neural oscillations from aperiodic 1/f activity: challenges and recommendations.
Neuroinformatics.
Accepted: 25 February 2022. Published online: 07 April 2022. https://doi.org/10.1007/s12021-022-09581-8

"In this article, we scrutinize two frequently used methods, FOOOF (Fitting Oscillations & One-Over-F) and IRASA (Irregular Resampling Auto-Spectral Analysis), that are commonly used to separate the periodic from the aperiodic component. We evaluate these methods using diverse spectra obtained with electroencephalography (EEG), magnetoencephalography (MEG), and local field potential (LFP) recordings relating to three independent research datasets. Each method and each dataset poses distinct challenges for the extraction of both spectral parts. The specific spectral features hindering the periodic and aperiodic separation are highlighted by simulations of power spectra emphasizing these features. Through comparison with the simulation parameters defined a priori, the parameterization error of each method is quantified. Based on the real and simulated power spectra, we evaluate the advantages of both methods, discuss common challenges, note which spectral features impede the separation, assess the computational costs, and propose recommendations on how to use them."

#methods #EEG #MEG #guidelines

"dramatic advances in digital signal processing, biophysics, and computer science have enabled increasingly sophisticated methodology for neural time series analysis. Innovations in hardware and recording techniques have further expanded the range of tools available to researchers interested in measuring, quantifying, modeling, and altering the spectral properties of neural time series. These tools are increasingly used in the field, by a growing number of researchers who vary in their training, background, and research interests. Implementation and reporting standards also vary greatly in the published literature, causing challenges for authors, readers, reviewers, and editors alike. The present report addresses this issue by providing recommendations for the use of these methods"

Andreas Keil, Edward M. Bernat, Michael X. Cohen, Mingzhou Ding, Monica Fabiani, Gabriele Gratton, Emily S. Kappenman, Eric Maris, Kyle E. Mathewson, Richard T. Ward, Nathan Weisz. Recommendations and publication guidelines for studies using frequency domain and time-frequency domain analyses of neural time series. Psychophysiology, Volume 59, Issue 5 e14052. First published: 10 April 2022. https://doi.org/10.1111/psyp.14052 [ Free Access ]

#methods #EEG #MEG #guidelines

Olaf Hauk, Matti Stenroos, Matthias Treder. Towards an Objective Evaluation of EEG/MEG Source Estimation Methods - The Linear Approach. NeuroImage. Available online 4 April 2022, 119177. https://doi.org/10.1016/j.neuroimage.2022.119177 [Open access]

Highlights

• We provide a tutorial and evaluation of MNE-type and beamforming methods
• We highlight the importance of resolution matrix, point-spread and cross-talk
• We present intuitive resolution metrics to evaluate and compare methods
• We applied these tools to five MNE-type methods and two beamformers
• Point-spread localization error can be low but cross-talk is fundamentally limited

#methods #EEG #MEG

PsychoPy on Twitter: "We've updated our docs to include info on how to connect to a range of hardware."

🧠 #EEG (serial/parallel ports)
👀 #Eyetracking devices
🧠 #fMRI (emulated key presses +other)
💓 #Arduino boards (example for GSR/heart rate)

https://psychopy.org/hardware/index.html

Прослушанные аудиокниги проявились в снах и в сонной ЭЭГ

Participants listened to audiobooks before falling asleep. We could determine which audiobook they had studied based on dream reports collected during the night. Audiobook content was also reinstated at the neural level, in high-density EEG recordings. Brain activity during rapid eye movement sleep, particularly in the high-frequency beta range, carried information about the audiobook and simultaneously benefitted memory retention. Crucially, when the learning condition was manifest in neural activity, it also emerged in dreams. Reprocessing of daytime experiences during sleep thus shapes our brain activity, our dreams, and our memories.

Deniz Kumral, Jessica Palmieri, Steffen Gais, Monika Schoenauer. Daytime experiences shape neural activity and dream content in the sleeping brain. bioRxiv, July 29, 2023 https://doi.org/10.1101/2023.07.29.551087

Авторы почему-то связывают то, что видят в ЭЭГ, прежде всего с работой памяти, а не с восприятием контента сна, в особенности в треде в твиттере (забаненном в РФ):

Using high-density #EEG and multivariate methods, we investigated whether memory reactivation during sleep shapes the content of dreams and aids memory consolidation.

Разумеется, сначала контент аудиокниг записывается в память, затем считывается оттуда. Но исходя из того, к чему чувствительна ЭЭГ, можно с очень большой уверенностью предположить, что непосредственно воздействует на ЭЭГ активация сенсорных систем.