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RD PascualMarqui

@pascualmarqui.bsky.social
260 followers 197 following 118 posts

KEY Inst Brain-Mind Research @UniZurich neuroscience imaging connectivity EEG MEG oscillations +LORETA+ Lagged Coherence/PhaseSynch Multivar/HiOrder InfoFlow scholar.google.com/scholar?q=pascua… www.uzh.ch/keyinst

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Reposted by RD PascualMarqui
Ben Fulcher @bendfulcher.bsky.social · 29/09/2026
Today I'm releasing the "1000×1000 collection": a unified place to learn about dynamical structure. 1000 simulated time series (1000 samples each) spanning 133 dynamical processes. Have a play? 🐛 #timeseries #dynamicalsystems #complexity #opendata dynamicsandneuralsystems.github.io/1000x1000/
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RD PascualMarqui @pascualmarqui.bsky.social · 17/09/2026
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Earl K. Miller @earlkmiller.bsky.social · 17/09/2026
With ephaptic effects, the brain contains a hidden network that includes non-spiking astrocytes. This denser network may help neurons communicate, adapt, and form new connections. Physical contact reveals a hidden layer of cortical architecture. europepmc.org/article/med/... #neuroscience
europepmc.org
Europe PMCEurope PMC
Europe PMC is an archive of life sciences journal literature.
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RD PascualMarqui @pascualmarqui.bsky.social · 12/09/2026
"While 1/f slope ... showed region and context dependencies, broadband (6-80 Hz) and high gamma (80-150 Hz) power consistently correlated with E/I ..." Measuring excitation/inhibition balance through field potentials: Rodriguez-Sanchez et al; bioRxiv; rev: 2026-09-11; doi.org/10.64898/202...
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Pieter Barkema @pieterbarkema.bsky.social · 11/09/2026
What you see right now is not a livestream, but is delayed & edited by your brain 🧠. The brain uses a short time buffer to rewrite what you thought you saw using info that comes in later (postdiction). We study how (7T fMRI, retinotopy). Read our preprint: www.biorxiv.org/content/10.6... 👀 (1/N)
biorxiv.org
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Matteo Carandini @carandinilab.net · 09/09/2026
If you thought "everything is everywhere" in the brain: inactivations reveal a clear distinction of labor. Sensory areas sense, colliculus promotes eligible actions (!), and prefrontal cortex integrates. The role of superior colliculus in a logistic decision www.biorxiv.org/content/10.6...
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Anthony Ramnauth @philoneurosci.bsky.social · 09/09/2026
New publication from @lukesjulson.bsky.social lab and collaborators! #Neocortical long-range #inhibition promotes #cortical #synchrony and #sleep doi.org/10.1038/s415...
doi.org
Neocortical long-range inhibition promotes cortical synchrony and sleep - Nature
In mice, a sparse population of sleep-active long-range inhibitory neurons in the neocortex promote widespread cortical synchronization and sleep, revealing a cortical mechanism that co...
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Reposted by RD PascualMarqui
Lina Skora @linaskora.bsky.social · 09/09/2026
Very happy to share our new results: cardiac activity around feedback dynamically reflects expectations. Led by Maria Azanova, with Alina @studenova.bsky.social , Esra Al, Vadim Nikulin and Arno Villringer www.biorxiv.org/content/10.6...
biorxiv.org
Individual heartbeats track distinct prediction processes during human probabilistic learning
Heart rate continuously adjusts to accommodate perception and action, and these shifts are frequently explained through predictive processes. Yet direct evidence that interbeat intervals exhibit grade...
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RD PascualMarqui @pascualmarqui.bsky.social · 08/09/2026
Heterogeneity of Brain Dynamics in Genetic and Psychiatric Conditions: Dubois et al bioRxiv 2026.09.01.748394; doi: doi.org/10.64898/202...
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The Transmitter @thetransmitter.bsky.social · 07/09/2026
I fear that placing too much emphasis on a specific interpretation of dimensionality, or treating dimensionality as an end-all quantification of some aspect of neural computation, may lead us down the wrong path, writes @mattperich.bsky.social. #neuroskyence www.thetransmitter.org/neural-dynam...
thetransmitter.org
Dimensionality—neuroscience’s red herring?
Placing too much emphasis on a specific interpretation of dimensionality may lead neuroscience down the wrong path.
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RD PascualMarqui @pascualmarqui.bsky.social · 28/08/2026
Dynamic cortical responses to premature contractions (PC) of the heart in humans; Reinfeld et al, 2026-08-22 doi.org/10.21203/rs.... Using ECG-EEG, eLORETA, fMRI: PC transient cortical changes: reduced insular and AC activity, followed by increased OF and cingulate responses
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bioRxiv Neuroscience @biorxiv-neursci.bsky.social · 24/08/2026
Selective gating of neural modulation through frequency- and behavior-dependent modes during cortical electrical stimulation www.biorxiv.org/content/10.64898/20…
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Michael W. Cole @mwcole.bsky.social · 19/08/2026
While I respect these authors (and traveling wave theories), I remain skeptical of these results. Nearly any basis set can be used to "explain" any complex data, including brain data. Like how a Fourier transform of time series data isn't explanatory, so this spatial decomposition isn't explanatory.
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Earl K. Miller @earlkmiller.bsky.social · 13/08/2026
Brain regions briefly sync rhythms during memory tasks, effectively linking them into a coordinated network Cross-region neuron co-firing mediated by ripple oscillations supports distributed working memory representations www.nature.com/articles/s41... #neuroscience
nature.com
Cross-region neuron co-firing mediated by ripple oscillations supports distributed working memory representations - Nature Neuroscience
The authors show that human neurons in bilateral corticolimbic sites fire together, modulated by working memory, and reinstate stimulus-selective firings when both sites briefly oscillate at 90 Hz, su...
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Kanaka Rajan @kanakarajanphd.bsky.social · 07/08/2026
(1/8) Our approach for untangling brain-wide interactions is out today in @cp-neuron.bsky.social! Current-Based Decomposition (CURBD) uses RNNs constrained by real neural data to reveal the input driving neurons, uncovering how brain regions talk to each other. doi.org/10.1016/j.ne... 🧵👇
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Alina Studenova @studenova.bsky.social · 06/08/2026
When a TMS pulse was delivered during beta ERD, EMG motor evoked potentials (MEPs) were larger than during ERS, while the immediate TMS-evoked responses (iTEPs) were smaller. This means that beta ERD was associated with decreased cortical excitability and increased cortico-spinal excitability. Odd!🤔
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Borjan (Boki) Milinković @neuromorphicboki.bsky.social · 31/07/2026
Cellular mechanisms of serotonergic psychedelics - apical hypercontextualisation
sciencedirect.com
Cellular mechanisms of serotonergic psychedelics - apical hypercontextualisation
Classical serotonergic psychedelics primarily exert their profound effects through agonism at the serotonin 2 A (5-HT2A) receptor, which is abundantly…
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Reposted by RD PascualMarqui
bioRxiv Neuroscience @biorxiv-neursci.bsky.social · 30/07/2026
From periodic/aperiodic to static/dynamic: rethinking the decomposition of neural power spectra www.biorxiv.org/content/10.64898/20…
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Trends in Neurosciences @cp-trendsneuro.bsky.social · 24/07/2026
'Brain rhythms of depression: A predictive processing perspective' by Andreas Strube @astrube.bsky.social & Diego Pizzagalli @diegopizzagalli.bsky.social www.cell.com/trends/neuro...
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RD PascualMarqui @pascualmarqui.bsky.social · 23/07/2026
NYU Professor Hong Wang Wins Fields Medal Mathematician recognized with the highest prize in mathematics for resolving a long-standing problem in harmonic analysis and geometric measure theory—the three-dimensional Kakeya conjecture www.nyu.edu/about/news-p... publication date: Jul 23, 2026
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RD PascualMarqui @pascualmarqui.bsky.social · 22/07/2026
From Subconscious to Insight: Decoding the Incubation Process in Creative Problem Solving Chatrin Phunruangsakao, Zenas C Chao bioRxiv 2026.07.15.738837; doi: doi.org/10.64898/202...
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Ben Hayden @benhayden.bsky.social · 16/07/2026
Hard to overstate the importance of this paper. Acategoricality and mixed selectivity together kill a lot of sacred cows. For starters, place cells aren't real, in that they are not a meaningful category. They are just a thing we scrape out of the data. Scientists focus on them because...
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Lorenzo Posani @lorenzoposani.com · 15/07/2026
Out today on @nature.com! Connecting neural specialization, population geometry, and their functional implications across the cortical hierarchy. So grateful for this beautiful and fun collaboration with @shuqiw.bsky.social, S Muscinelli, L Paninski, and @stefanofusi.bsky.social!
nature.com
Rarely categorical, highly separable representations along the cortical hierarchy - Nature
Cortical circuits prioritize diversity over categorical structure, supporting a computational regime geared towards high-dimensional, highly separable neural representations.
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Martin Dresler @dresler.bsky.social · 11/07/2026
Why do we forget our dreams? Dreams are the kind of experiences that in principle should stick well in memory: emotional and often bizarre. If we would encounter typical dream content during wakefulness, we would likely never forget it. Yet, we forget most dreams soon after awakening. (1/3)
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Nature @nature.com · 10/07/2026
Preprints don’t change much after peer review — and are rarely retracted. go.nature.com/4pebHmM
go.nature.com
Think preprints are unreliable? Analysis of 70,000 studies might change your mind
Preprints don’t change much after peer review — and are rarely retracted.
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Earl K. Miller @earlkmiller.bsky.social · 08/07/2026
In visual learning, slower changes come from adjustments in connections between neurons, while faster changes come from intrinsic plasticity. Together, these two learning processes help the brain efficiently adapt to familiar information over time. www.nature.com/articles/s41... #neuroscience
nature.com
Visual learning at fast and slow timescales is driven by distinct plasticity rules in primate inferotemporal cortex - Nature Communications
We rapidly distinguish familiar from novel objects, but how the brain learns this remains unclear. Using macaque inferotemporal cortex recordings and modeling, the authors show that familiarity learni...
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Roxana Zeraati @roxana-zeraati.bsky.social · 07/07/2026
Our paper "Neural timescales from a computational perspective" is finally out in @natneuro.nature.com: www.nature.com/articles/s41... We discuss how computational models and methods can distill empirical observations on neural timescales into quantitative, testable theories of brain computation.
nature.com
Neural timescales from a computational perspective - Nature Neuroscience
This review integrates computational approaches to provide a unified view on how data analysis methods, biophysical mechanistic models and machine learning approaches can help to uncover the origins a...
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pinotsislab.bsky.social @pinotsislab.bsky.social · 07/07/2026
Variability in brain oscillations can be explained by ephaptic coupling w/ @earlkmiller.bsky.social doi.org/10.1093/cerc...
doi.org
Ephaptic coupling can explain variability in neural activity
Abstract. The waxing and waning cortical oscillatory power correlates with function and disease. This cross-trial variability has been thought to be due to
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Alina Studenova @studenova.bsky.social · 07/07/2026
To be fair, Anthropic didn't say Claude is conscious. But I'm missing on the point why the found J-space is a global workspace and not just massive working memory?
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Richard Sever @richardsever.bsky.social · 06/07/2026
“move from preprint to peer-reviewed publication leaves the central claims of most abstracts intact, indicating preprints are a reliable source…papers that were never posted as preprints were retracted at roughly twice the rate of those that were…” www.biorxiv.org/content/10.6...
biorxiv.org
Tracking claim changes from preprint to publication across 72,644 biomedical studies using large language models
Preprints now disseminate a large share of biomedical research before peer review. Because they have not yet passed peer review, some scientists regard preprint claims as unverified or potentially unr...
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Andreas Strube @astrube.bsky.social · 06/07/2026
Very happy to see this Review with @diegopizzagalli.bsky.social out in @cp-trendsneuro.bsky.social www.cell.com/trends/neuro... This piece brings together a lot of what we’ve been thinking on depression, predictive processing and EEG. Many thanks for the support from @sfb-trr-289.bsky.social
cell.com
Brain rhythms of depression: A predictive processing perspective
Depression is marked by anhedonia, social withdrawal, and a diminished capacity to learn from positive experiences—features that can be framed within predictive processing. Here, we review findings fr...
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Reposted by RD PascualMarqui
jens-madsen.bsky.social @jens-madsen.bsky.social · 04/07/2026
New open dataset out in Scientific Data 🚨 We are releasing BBBD: the Brain, Body, and Behavior Dataset. Paper: www.nature.com/articles/s41... Work with @parralab.org
nature.com
The Brain, Body, and Behavior Dataset (BBBD): Multimodal Recordings during Educational Videos - Scientific Data
Scientific Data - The Brain, Body, and Behavior Dataset (BBBD): Multimodal Recordings during Educational Videos
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Stanislas Dehaene @standehaene.bsky.social · 03/07/2026
A fundamental discovery ! Immanuel Kant would have loved it.
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RD PascualMarqui @pascualmarqui.bsky.social · 03/07/2026
Judea Pearl Named AI Pioneer by Boston Global Forum in Honor of America’s 250th Anniversary samueli.ucla.edu/judea-pearl-...
samueli.ucla.edu
Judea Pearl Named AI Pioneer by Boston Global Forum in Honor of America’s 250th Anniversary
Judea Pearl, a chancellor’s professor emeritus of computer science at the UCLA Samueli School of Engineering, has been named one of 50 AI Pioneers by nonprofit think tank Boston Global Forum and its A...
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Martijn Arns @martijn-arns.bsky.social · 02/07/2026
We just released a major update to TDBRAIN V3.1: one of the largest and most well phenotyped, openly available clinical EEG datasets (>1500 EEGs).
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Alina Studenova @studenova.bsky.social · 02/07/2026
Some neurons fire during certain phases of LFP oscillations, while some fire more when LFP oscillates at certain frequencies. V. cool!🤩 I appreciated the discussion about causality: do oscillations in LFP cause increased spiking, or does the change in spiking cause changes in the spectrum of LFP?
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RD PascualMarqui @pascualmarqui.bsky.social · 29/06/2026
Brain Control of a Computer Cursor for Online Target Selection - A Non-Invasive BCI for Continuous Movement Decoding Markus Crell, Kyriaki Kostoglou, Patrick Suwandjieff, Johanna Egger, Gernot Mueller-Putz bioRxiv 2026.06.23.733968; doi: doi.org/10.64898/202... (Posted June 29, 2026)
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Darya Frank @darya-frank.bsky.social · 29/06/2026
📣 Thrilled to share our recent work in @natneuro.nature.com. Using direct recordings from the human hippocampus and visual cortex, we asked how the brain prepares to encode information when upcoming events are unpredictable, and what ripples do in that process. www.nature.com/articles/s41...
nature.com
Human hippocampal ripples tune cortical responses based on predicted uncertainty - Nature Neuroscience
Using direct recordings from the human brain, Frank et al. show that hippocampal ripples increase ahead of unpredictable events and tune the visual cortex to respond faster and more strongly to surpri...
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RD PascualMarqui @pascualmarqui.bsky.social · 25/06/2026
Connectivity- vs Scalp-Based Targeting of Accelerated Transcranial Magnetic Stimulation for Depression A Randomized Clinical Trial jamanetwork.com/journals/jam...
jamanetwork.com
Connectivity- vs Scalp-Based Targeting of Accelerated TMS for Depression
This randomized clinical trial estimates the effect size of connectivity- vs scalp-based targeting of accelerated transcranial magnetic stimulation for treatment-resistant depression.
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Eleonora Bartoli @elebartoli.bsky.social · 24/06/2026
Some neurons like to ride on slow LFP oscillations, regardless of their phase! This might represent a mechanism to coordinate neural activity and propagate information across brain circuits 🧠 amazing collaboration led by the super talented @zahrajourahmad.bsky.social and Andrew Watrous!
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Marc Slutzky @marcslutzky.bsky.social · 22/06/2026
Our paper is now in print in Nature @nature.com. If you're interested in local field potentials, especially #high-gamma activity, and/or #spikes, check it out! TL;DR: High gamma is not mainly filtered spikes, but mainly summed nearby PSPs. www.nature.com/articles/s41...
nature.com
Active dissociation of intracortical spiking and high gamma activity - Nature
A brain–machine interface is used in monkeys to investigate the biophysical underpinnings of cortical high gamma-band activity, a signal that is often studied in the context of many brain functions.
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Tahnée Engelen @tahnee-engelen.bsky.social · 23/06/2026
Your heartbeat quietly shapes how your brain processes information www.science.org/content/arti...
science.org
Your heartbeat quietly shapes how your brain processes information
Frequently ignored bodily rhythms may be skewing neuroscience experiments
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Simon Fisher @profsimonfisher.bsky.social · 18/06/2026
Researchers recorded from single neurons across frontotemporal cortex in 8 awake individuals during natural speech. They show how activities of collections of cells can capture syntactic & semantic properties of words, & also dynamically incorporate sentence context to encode combinatorial info. 🗣️🧠🧪
nature.com
Mapping the neuronal building blocks of human language with language models - Nature
Wide-scale recordings reveal neurons in the human brain that encode fundamental components of language such as the grammatical relationships between words, their parts of speech and the...
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Imaging Neuroscience @imagingneurosci.bsky.social · 18/06/2026
New paper in Imaging Neuroscience by Francesco Antonio Mallus, Thomas Wolfers, et al: From early to contemporary normative modeling: Mapping individual differences in neurophysiological signals doi.org/10.1162/IMAG...
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RD PascualMarqui @pascualmarqui.bsky.social · 17/06/2026
Spectral decompositions of neural voltage recordings are susceptible to model misspecifications that cause meaningful estimation error Patrick Francis Bloniasz, Emily Patricia Stephen bioRxiv 2026.06.12.718232; doi: doi.org/10.64898/202...
Abstract
The power spectra of neural voltage recordings vary systematically across brain states and contain both narrowband (rhythmic) and broadband components. A large class of algorithms seeks to parametrize these spectra by separating rhythms from broadband structure, enabling many robust empirical findings. Here we show that two common assumptions underlying popular spectral decomposition methods are incompatible with standard physical and statistical properties of neural recordings: (1) field potentials arise from additive (linear) superposition of biophysical processes, yet several methods implicitly impose multiplicative structure; (2) power estimates are Gamma distributed, with variance proportional to squared power (heteroscedasticity), yet many methods assume Gaussian, homoscedastic errors across frequencies. Using simulations with known ground truth, we demonstrate how these misspecifications bias estimates of rhythm amplitude and broadband height/slope, even under well-behaved conditions. We introduce a corrected decomposition framework, released as the open-source package SL_specdecomp. Relative to the most widely used method, specparam, our approach recovers rhythms and broadband parameters accurately, while specparam decompositions are biased and can confound rhythmic peaks with broadband slope. We then apply these methods to monkey electrocorticography during propofol anesthesia. SL_specdecomp estimates a substantially steeper (more negative) 40--60~Hz broadband slope during anesthesia than during wakefulness, whereas specparam shows a smaller state difference. We show using simulation that the differences in the two decompositions can arise directly from specparam's model misspecification. A formal cross-validated log likelihood to compare candidate power spectral decompositions and show that it favors SL_specdecomp. Misspecified decompositions distort broadband slope changes, and motivate use of SL_specdecomp as a more reliable decomposition tool.
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Martijn Arns @martijn-arns.bsky.social · 16/06/2026
Always wanted to open EDF/BDF files (EEG or ECG) on Apple or other platforms? We just released an online EDF and BDF viewer, you can open, apply filters, change montages, identify PQRST components in ECG data and save all changes and add ECG component annotations to EDF+ or BDF+ files.
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PessoaBrain @pessoabrain.bsky.social · 13/06/2026
𝗖𝗮𝗻 𝘀𝗼𝗺𝗲𝗼𝗻𝗲 𝗿𝗲𝗺𝗶𝗻𝗱 𝗺𝗲 𝗮𝗴𝗮𝗶𝗻 𝘄𝗵𝘆 𝘄𝗲 𝗽𝘂𝗯𝗹𝗶𝘀𝗵 𝗽𝗮𝗽𝗲𝗿𝘀 𝘁𝗵𝗲 𝘄𝗮𝘆 𝘄𝗲 𝗱𝗼 and not just deposit what we think is cool work in an archive and move on? Moving on could/should also include going back and improving the work, adding some notes about problems with previous version(s), etc. #bringfunbacktoscience
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RD PascualMarqui @pascualmarqui.bsky.social · 12/06/2026
The electro-MICA toolbox for integrating electrophysiology within multimodal imaging and connectomics workflows bioRxiv 2026.06.08.730888; doi.org/10.64898/202... von Ellenrieder, Cai, Arafat, Vavassori, Abdallah, de Kraker, Rodríguez-Cruces, Royer, Sahlas, Bautin, Pana, Aron, Frauscher, Bernhardt
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PessoaBrain @pessoabrain.bsky.social · 03/06/2026
The latent structures they champion (attractors, manifolds, subspaces) are as experimenter-relative as the "encoded messages" they reject, so I view it a bit as "relocating" the issues. Seems like @romainbrette.bsky.social 's argument cuts against their alternative no less than against encoding.
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Yohan J John @dryohanjohn.bsky.social · 03/06/2026
"The results were so divergent that one has to wonder: If we cannot agree on how to define a ripple, what else might we be getting wrong?" 🎶 Ripple in still water... www.thetransmitter.org/reproducibil...
thetransmitter.org
18 teams analyzed a neuro dataset and got different answers
Disagreement in neuroscience runs deeper than most researchers suspect—even in electrophysiology, a field that prides itself on hard data.
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