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Prikvačeni tweet
A classic effect in the sensorimotor cortex: event-related desynchronization. Strong mu-rhythm oscillations attenuate as soon as the participant starts to contract a muscle. Where do they go?
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end of January: spring blossom!
time to wear flip flops again! (the true Californians wear them year-round though)pic.twitter.com/ktNwlbOfUe
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Interesting new burst-detection method based on hidden Markov models, which circumvents some problems that occur when using only amplitude thresholds. But now one needs to define a good state space (or learn it?)https://link.springer.com/article/10.1007/s10548-019-00745-5 …
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Projecting signals with weights obtained by principal or independent component analysis geometrically corresponds to a rotation in an n-dimensional space, n=number of signals.
pic.twitter.com/qr9Tj2e4IPHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
a thread with beautiful images concerning interindividual differences in skull anatomy, which could influence recordings of EEG signals:https://twitter.com/ETognoli/status/1221104355929219075 …
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also, because the power spectrum is in log-space: the signal-to-noise ratio of the blue subjects is not twice as good compared to the orange subjects, but 10 times better.
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Across participants, there is a large range of measurable EEG oscillation strength. For some participants, oscillations are very pronounced, for others miniscule. One can exclude participants for the sake of good measurement, but then the generalizability suffers. Tough choice!pic.twitter.com/dXiPS5XJqP
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the fantastic kid further along in the video was perfectly able to write the equation for photosynthesis, but still struggled with understanding the correct answer. it also reminded me of the 'guessing the teacher's password' phenomenon.
(https://www.lesswrong.com/posts/NMoLJuDJEms7Ku9XS/guessing-the-teacher-s-password …)Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
interesting video shown at my teaching workshop yesterday, where graduates are asked where trees derive their biomass from and they say soil+water: https://www.youtube.com/watch?v=NJwXYZ4GryA&t=233 … I wonder what misconceptions of that kind exist in neuroscience?
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Looking for examples of alpha-oscillations across scales. I checked open ECoG data (https://elifesciences.org/articles/47035 ) over primary+secondary visual cortex (rare!). Interestingly, there is no standing out alpha-peak in the spectrum and only few bursts in alpha-frequency range.
pic.twitter.com/RidEg5r3gX
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unless you work in anthropology/geology, then you can do neat looking things like this. https://www.nature.com/articles/s41586-019-1863-2/figures/3 … I coded it as two subpanels, but remain confused.
across fields, there are very different visual cultures!pic.twitter.com/LlOprtauR8
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the number of subpanels per figure in the current issue of Nature (16 Jan). so probably start out with 9-10 subpanels and go from there, complement with insets to you don't appear light on the data side. (triggered by a recent meta-discussion)pic.twitter.com/5VWaOGlfHJ
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I really like papers with many beautiful raw traces. These are from Contreras & Steriade (1995, https://www.ncbi.nlm.nih.gov/pubmed/7823167 ) and shows simultaneous EEG&intracellular recordings in motor cortex. Cool looking bursts! (sadly, this presentation form seems to have gone a bit out of style)pic.twitter.com/FgVBfAjnFD
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Movement-related information (e.g. different movement types) can be decoded from high-frequency activity with great precision from narrow band-power in ECoG. I am wondering up to which frequency EEG/MEG are informative in some way?
(the plot is a very crude comparison)pic.twitter.com/ygtWfLA8nI
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lab complains that my surname is too complicated! The consequence is that theorems and other good things cannot be named after me. so here is some mnemonic for practicing to counter that. (americanized version, but I can live with that)pic.twitter.com/ACIkKxRQxW
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I like working with large datasets. But I find it preferable to really understand what is happening for an individual subject, to arrive at a robust prediction for this single person. Interesting paper in this realm: https://link.springer.com/article/10.3758/s13423-018-1451-8 …pic.twitter.com/VzZbjvT36f
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Reproducing really old results (~1930s): EEG visual alpha frequency increases over development. So many subjects in one scatter plot
. All of the extensive data wrangling by Voytek lab graduate rotation student Andrew Bender.pic.twitter.com/iMmuuWVdr1
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end of December in Southern California. It feels like 25°C in the sun. I already know that it will be very tough to leave this place.

pic.twitter.com/yrMrjYV49P
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I have seen this a few years ago in
@lakens fantastic 1st MOOC: https://www.coursera.org/learn/statistical-inferences … Hope to do the new 2nd one in the winter break!Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
p-values for 10000 simulated experiments comparing two conditions in 25 subjects for an increasing effect size. Starting out with a uniform distribution, the p-values shift to smaller and smaller values for increasing differences between conditions.pic.twitter.com/ynIsUr4JG3
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Inter-trial coherence measures phase-synchronization across trials. It is the circular sum of phases at a certain point in time (length of red arrow). It reaches its maximum value of 1 for perfectly phase-aligned signals and becomes 0 as the phase distribution becomes uniform.pic.twitter.com/jv2unSVC7O
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