Natalie Schaworonkow

Äquiaktivlinie 😀
very nice!!

🙂🕵️‍♀️ detective work!

aww, thank you so much for looking!! shame it wasn't there, I think I scrolled through most of the other citations given for that plot, but no luck. 😕 on the hunt, I already found this thesis, it reads super nicely, liked it a lot!
(work from Motokawa is rad, want to do more animations of it. 🙂)

I'm giving a talk there in a workshop with a really great topic:
"Same words, different worlds: Conceptual consistency in systems neuroscience" 🙂

& many other fab looking workshops! (some by my cool friends: @matteosaponati.bsky.social @rdgao.bsky.social @j-b-eppler.bsky.social 🌟)

very behind in announcing things (not sure if people read papers anymore 🙃), but this came out earlier this year from my time @ UCSD
a project that started with the sentence "Brad, I found this cool dataset, can the new rotation student look at it?" 😅 all hard work by soon graduating MJ Preston.

a seemingly general electrophysiological phenomenon: once you have to process stimuli, low-frequency rhythms disappear, spectrum becomes flatter & sometimes an increase in broadband gamma activity.
we also found this for visual memory encoding in #iEEG data: doi.org/10.1523/JNEUROSCI.2404-24.2025

presentation slide with colorful illustrations from here: https://www.youtube.com/watch?v=3ZeH_8sTyKA&t=354s

read the news about 17yr old Hannah Cairo who found a counterexample to a conjecture from harmonic analysis. love the playful presentation slide style. 🙂💕💚

#VisualizationInspo

yes have been there, especially for large prints (see image). but now I have dental instruments, which are excellent for doing this, highly recommend (sulci are deep 🙃) and it's much better with the 'tentacle' support structure option (Bambu printer), so will try the en bloc way again. 🙂

the brain was split into the two hemispheres and laid flat onto the medial surface, so there are some ugly parts in the middle.

my favorite technical staff made the connection knobs, but this takes a bit of time, so the next brain will be printed en block, let's see how this goes. 🙂

3D printed brain

making little mini brains for internal participants (who I can not pay with money) for our current experiment, using the individual structural MRIs.

#ForbiddenBubbleGum 🙃

your favorite color map 🙂

colored it for fun. 🙃

several citations were given, but seemed wrong, I think this is the right one, couldn't find the article online, if somebody can:
Motokawa K. 1944, Japanese Journal of Medical Sciences: Biophysics. III, Volume 10(1).

Black-and-white scientific illustration of the first EEG topoplot by Koiti Motokawa (1944). G = glabella P = protuberantia occipitalis externa, S = central sulcus

this figure from 1944 is cited as the first topoplot, from Koiti Motokawa. in an era where only handful of EEG channels across space were used, he measured the mean alpha amplitude for 90 points across the scalp. ❗

(compiling a presentation about the evolution of topoplots, cool stuff out there 🙂)

I asked the support about it, let's see :)

but does openalex have all data? I searched for my name and found nothing? 🤔

1) see my figure above, finer granularity is also possible by querying pubmed
2) I would guess that this is not publicly obtainable :-)

I would like to see something like how 'connected' the authors of 1 article are within the community, but I am not sure how to assess that

so the easiest metric to start with is published papers per time unit in NeuroImage, definitely in decline, here from PubMed:

also true! please someone with talent do it 🙂

four topoplots showing alpha rhythm distribution, from https://link.springer.com/chapter/10.1007/978-3-662-63267-3_4

topoplots or vintage rugs? 🙃🌈

less names that I recognize now;
but it would be very interesting to run some actual numbers, can somebody do it? :)

okay, now there is at least this thread about it! it's cool that we have so much open data flying around, some growing pains are to be expected. 🙂

our work found developmental factors influenced results more than diagnostic aspects.

nevertheless, I feel at unease reading papers ignoring this aspect. I expect them to pop-up more, also because of initiatives making the dataset more accessible (biorxiv.org/content/10.1101/2024.10.03.615261v2).

I think this has resulted in papers which do not mention the diagnostic aspect at all, or only to a limited degree (random example: pmc.ncbi.nlm.nih.gov/articles/PMC...) I believe it's fully justified for privacy reasons that the diagnostic data is not openly available (it's quite extensive).

this dataset is a transdiagnostic dataset, with many participants diagnosed with neurodevelopmental disorders. the neuroimaging part of the dataset is essentially downloadable with 1 click. but the diagnostic information is only available with a not super easy to obtain data usage agreement.

something curious I noticed when working with this dataset, related to the ease of access for different data components. I am not exactly sure what to do with this observation, but here you have it:

E/I-balance as a too simplistic construct, 1/f-exponent reflecting at least 10 different things (some of them definitely non-neural changes) ➡️ a tangled web of spurious correlations 😶‍🌫️
definitely more additional careful work needed

will you still be my friend when I write a perspective about this 😶🙃

E/I-balance as a too simplistic construct, 1/f-exponent reflecting at least 10 different things (some of them definitely non-neural changes) ➡️ a tangled web of spurious correlations 😶‍🌫️
definitely more additional careful work needed

supernice! 🥳

(now with a ton of control analyses regarding the diagnostic findings, because people don't like null results... 🙃)