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Daniele Marinazzo

@danielemarinazzo.bsky.social
1.9K followers 2.3K following 263 posts

Computational neuroscientist and complexity scientist. Professor at Ghent University.

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Daniele Marinazzo @danielemarinazzo.bsky.social · 30/07/2026
Ditto 😁. Thanks Randy
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EBRAINS @ebrains.bsky.social · 16/07/2026
We are delighted to welcome Ghent University as an associate member at EBRAINS! The university is over 200 years old, offers more than 200 programmes and conducts research in many scientific disciplines. Read more: ebrains.eu/news-and-eve...
ebrains.eu
EBRAINS welcomes Ghent University as new associate member
EBRAINS is pleased to announce that Ghent University has joined the EBRAINS AISBL as an associate member.
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Kayson Fakhar @kayson.bsky.social · 12/03/2026
Cambridge Networks Network is back! Come have a chat if you're around. If not, you can follow us on Bluesky or even become a member (check the website). Regardless, we're looking for material to add to our resources section. Let me know if you have any.
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Daniele Marinazzo @danielemarinazzo.bsky.social · 10/03/2026
Dissecting Spectral Granger Causality through Partial Information Decomposition arxiv.org/abs/2603.07634
Dissecting Spectral Granger Causality through Partial Information Decomposition
Luca Faes, Gorana Mijatovic, Riccardo Pernice, Daniele Marinazzo, Sebastiano Stramaglia, Yuri Antonacci
Granger causality (GC), a popular statistical method for the inference of directional influences between time series measured from a complex network, is sensitive to high-order (non-pairwise) interactions which fundamentally shape the collective network dynamics. This work introduces Partial Decomposition of Granger Causality (PDGC), a tool eliciting redundant and synergistic causal interactions in the pattern of information flow between the subsystems of physiological networks. The tool exploits the framework of partial information decomposition to dissect the multivariate GC from a set of driver random processes to a target process into unique effects carried exclusively by each driver, redundant effects carried identically by more drivers, and synergistic effects carried jointly by some drivers but not by any of them individually. Computation is based on multivariate state-space models expanded in the frequency domain to assess PDGC both in specific bands of physiological interest and in the time domain after whole-band integration. The spectral PDGC was tested in physiological networks probed by measuring the variability series of arterial pressure, heart period, respiration and cerebral blood velocity in patients prone to neurally-mediated syncope compared to healthy controls. This application revealed unprecedented modes of physiological interaction, related to the sympathetic control of low-frequency cardiovascular and cerebrovascular oscillations, characterizing distinctive patterns of autonomic dysfunction. The extraction of high-order causality patterns from the spectral GC favors dissecting the mechanisms of causal influence underlying multivariate interactions among oscillatory processes in many data-driven applications of network science.
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Natalie Schaworonkow @nschawor.bsky.social · 10/02/2026
the cutoff scores for #MSCA postdoc fellowships are very high this year. has the score distribution shifted compared to previous years? I made a plot with scores from past years. if scores are at ceiling level, the process becomes essentially a lottery, because minor issues can lead to deductions.
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Omid V. Ebrahimi @omidvebrahimi.bsky.social · 02/02/2026
Thrilled to announce the Oxford Psychological Networks Summer School (OxPNS)! This is the first-ever psychological network analysis workshop in the UK, to be held in magical Oxford from June 22-26, 2026. To apply and for more information, please visit: oxfordpns.com A brief thread 🧵
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INCF @incforg.bsky.social · 28/01/2026
Reminder for mentors: Full project descriptions for INCF’s Google Summer of Code 2026 are due 1 February 2026. Submit your neuroscience-focused proposal, especially aligned with INCF standards: docs.google.com/form... #GSoC #OpenSource #Neuroscience #INCF
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Daniele Marinazzo @danielemarinazzo.bsky.social · 22/01/2026
"ripples" are by definition transient. And what does a transient become in the spectrum? Surprise: 1/f. Poteto potato.
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Daniele Marinazzo @danielemarinazzo.bsky.social · 20/01/2026
OHBM asking to review up to 30 more abstracts (I did 42 already) due to lack of reviewers seems like a serious structural problem. An incentive could be a reduction or waiwer of the exorbitant registration fee. Just saying.
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Adrien Peyrache @apeyrache.bsky.social · 19/01/2026
"The time for passive consumption has expired. Every scholar should begin contributing their expertise to Wikipedia — not as charity, but as a core duty" www.nature.com/articles/d41...
nature.com
The academic community failed Wikipedia for 25 years — now it might fail us
Artificial-intelligence systems are feeding on Wikipedia without giving back, and academic indifference is threatening the survival of what is arguably the most widely used reference work on the plane...
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Daniele Marinazzo @danielemarinazzo.bsky.social · 19/01/2026
Great work Max!
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Felipe Fontana Vieira @felipefv.bsky.social · 12/01/2026
Come and be my PhD colleague: www.ugent.be/en/work/scie...
ugent.be
Doctoral fellow
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Anil Seth @anilseth.bsky.social · 09/01/2026
1/🧵 NEW PREPRINT! Granger Causality Maps for Langevin Systems – new preprint from the incomparable Lionel Barnett, w/ Benjamin Wahl, Nadine Spychala, and me – a Sussex Centre for Consciousness Science production. Link at end of thread.
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Eiko Fried @eikofried.bsky.social · 07/01/2026
After 5 years of data collection, our WARN-D machine learning competition to forecast depression onset is now LIVE! We hope many of you will participate—we have incredibly rich data. If you share a single thing of my lab this year, please make it this competition. eiko-fried.com/warn-d-machi...
eiko-fried.com
WARN-D machine learning competition is live » Eiko Fried
If you share one single thing of our team in 2026—on social media or per email with your colleagues—please let it be this machine learning competition. It was half a decade of work to get here, especi...
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Daniele Marinazzo @danielemarinazzo.bsky.social · 07/01/2026
A hitchhiker’s guide to information theoretical measures in psychology by @nielsvs.bsky.social with me and Yves Rosseel authors.elsevier.com/c/1mOwr53na-... osf.io/preprints/ps...
A hitchhiker’s guide to information theoretical measures in psychology

Niels van Santen, Yves Rosseel, Daniele Marinazzo


https://doi.org/10.1016/j.jmp.2025.102969

Highlights
• Information theory and psychology have a rich history
• Information theoretical measures can be disconnected from information theory
• These measures complement variance-based measures of variability and association
• They are more general with respect to interpretation and possible data types
• There are many extensions towards the investigation of higher-order interactions.

Abstract
In psychology, as in other sciences, information theory can be used as a tool to complement more standard regression-based methods of data analysis. It is important to see the potential of information theoretical measures as statistical tools without implying a connection to their origins in communication theory and engineering. The use of these measures may provide us with additional insights due to their sensitivity to non-linear relationships, their flexibility to the mixing of data types, and their more straightforward generalization towards investigating higher-order interactions. We briefly reintroduce information theory and compare several measures such as mutual information and co-information with correlation and regression-based methods for the investigation of variable dependence.
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Micah G. Allen @micahgallen.com · 28/12/2025
And like, all these posts about how the “story makes so much sense” and “resonates with what patients say”. I’m an ADHD person who takes stims and a neuroscientist and I find all of this totally incredulous.
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Daniele Marinazzo @danielemarinazzo.bsky.social · 26/12/2025
"drug for disorder which isn't a disorder doesn't act on a brain network (which isn't a network) called as the thing in the name of said not-disorder, according to increased signal detected by a method in which increased signal possibly doesn't indicate increased activation"
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practiCal fMRI @practicalfmri.bsky.social · 23/12/2025
...defining voxels by their response (-ve) implies reduced activity but doesn't prove it, and I'd prefer a principled neuroanatomical basis, or EEG, etc., which leaves me assuming a lot of vascular physio artifacts are going to be interpreted. A case for subject-specific HRF, not canonical, perhaps!
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Fleur Zeldenrust @fleurzeldenrust.bsky.social · 23/12/2025
Out now in PLOS CB: a wonderful study by @nishantjoshi.bsky.social, together with Tansu Celikel and Sven van der Burg: journals.plos.org/ploscompbiol... Nishant shows here how classifying neurons based on electrophysiological properties depends critically on the input you give these neurons.
lnkd.in
LinkedIn
This link will take you to a page that’s not on LinkedIn
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Stefan Haufe @sparsity.bsky.social · 12/12/2025
Thank you for the great work @willenjoy.bsky.social ! An important step towards understanding and correcting bias in source localizations and functional connectivity due to source leakage.
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Benedikt Ehinger @benediktehinger.bsky.social · 08/12/2025
Can we stop our #EEG experiments after 5 trials? Thought provoking paper: www.arxiv.org/abs/2511.23162 tldr: n=5 trials gave better cvR² than n=100% on average Kudos to the authors who went far beyond many other EEG papers in terms of additional tests & baselines (openreview.net/forum?id=c6L...)
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Tiago Peixoto @tiago.skewed.de · 04/12/2025
I wrote a blog post about the often stated but never explained assumption that communities in graphs should always be connected. This is inconsistent with statistical significance and null models that underlie the most widely employed methods. skewed.de/lab/posts/co...
skewed.de
The perplexing “connected cluster axiom” – Inverse Complexity Lab
Research group on inverse problems in complex systems and network science.
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The Viking (Gunnar Blohm) @gunnarblohm.bsky.social · 01/12/2025
👏
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Adeel Razi @adeelrazi.bsky.social · 27/11/2025
📢Generative Models in Neuroimaging Survey We’re running a short survey on how neuroimaging (aka #OHBM) community defines, uses & evaluates generative models, from biophysical simulations to ML-based approaches 👉 t.co/lRQj4qmknO @ohbmofficial.bsky.social @ohbmtrainees.bsky.social
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Gang Chen @gangchen6.bsky.social · 18/11/2025
And the next step? Full voxel-level modeling. Recent numerical advances cracked the scalability barrier. Voxel-level hierarchical modeling is now feasible, revealing just how punishing traditional multiple-comparison adjustments really are. arxiv.org/abs/2511.12825
arxiv.org
SIMBA: Scalable Image Modeling using a Bayesian Approach, A Consistent Framework for Including Spatial Dependencies in fMRI Studies
Bayesian spatial modeling provides a flexible framework for whole-brain fMRI analysis by explicitly incorporating spatial dependencies, overcoming the limitations of traditional massive univariate app...
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Daniele Marinazzo @danielemarinazzo.bsky.social · 30/10/2025
Combo of two papers on partial information rate decomposition now out! journals.aps.org/prl/abstract... journals.aps.org/pre/abstract... Mini thread below 👇
journals.aps.org
Partial Information Rate Decomposition
Partial information decomposition (PID) is a principled and flexible method to unveil complex high-order interactions in multiunit network systems. Though being defined exclusively for random variable...
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Natalie Schaworonkow @nschawor.bsky.social · 16/10/2025
ok, imagine you have an oscillation that is not symmetric around 0 (small direct current shift) with some amplitude modulation, for instance with 1/f-dynamics. ➡️ then these 1/f-dynamics will show up in low frequency part of spectrum (red); in addition to around oscillation peak (yellow).
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Daniele Marinazzo @danielemarinazzo.bsky.social · 17/10/2025
I find this paper really confusing. There are several measures (power, coherence, network communication, information based statistical dependencies) which are all measures of the "behavior" of the system, and definitely share similarities. Yet some are considered "mechanisms" underlying the others.
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Dr Cyril Pernet @cyrilrpernet.bsky.social · 22/09/2025
arxiv.org/abs/2509.15278 check that your metadata are 'private' i.e. that they do not leak personal information -- BIDSapp available 😀
arxiv.org
Assessing metadata privacy in neuroimaging
The ethical and legal imperative to share research data without causing harm requires careful attention to privacy risks. While mounting evidence demonstrates that data sharing benefits science, legit...
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Peter Zeidman @corticalpete.bsky.social · 16/09/2025
A birthday is a good time to reflect! To mark SPM @ 30, this month's issue of Cerebral Cortex features deeply insightful commentaries on neuroimaging analysis from Ed Bullmore, Peter Bandettini, Peter Fox, Pedro Valdes-Sosa, Klaas Enno Stephan, Viktor Jirsa, et al [1/2] academic.oup.com/cercor/issue
academic.oup.com
Issues | Cerebral Cortex | Oxford Academic
Publishes papers on the development, organization, plasticity, and function of the cerebral cortex, including the hippocampus.
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BeyondTheEdge @beyondtheedge.network · 08/09/2025
BeyondTheEdge at the School of Complexity on "Higher-order interactions: mechanisms, behaviors, and networks" by our own @lordgrilo.bsky.social and @gin-bianconi.bsky.social with @aliceschwarze.bsky.social, @danielemarinazzo.bsky.social. Great perspectives! www.beyondtheedge.network/articles/bey...
beyondtheedge.network
BeyondTheEdge goes to Sicily
BeyondTheEdge researchers participated in the School of Complexity on
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Cat Hicks @grimalkina.bsky.social · 01/09/2025
I'm specifically sharing this paper because I saw a post recently that said people who think about methodology are "attacking authors"
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Daniele Marinazzo @danielemarinazzo.bsky.social · 27/08/2025
"Brief segments of neurophysiological activity enable individual differentiation", but also when the neurophysiological activity (MEG data) is identical for all the subjects, we have the same differentiation. Because of the head shape, of course. pubpeer.com/publications...
pubpeer.com
PubPeer - Brief segments of neurophysiological activity enable individ...
There are comments on PubPeer for publication: Brief segments of neurophysiological activity enable individual differentiation (2021)
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Laura Dugué @lauradugue.bsky.social · 17/08/2025
🚨New preprint from the Dugué Lab! Happy to share our last work on #attention_rhythms, co-led by @cogsenoussi.bsky.social & former Dugué Lab PhD student @lauriegalas.bsky.social, and in collab with Niko Busch 🎉 @upcite.bsky.social | @erc.europa.eu | #neuroskyence www.biorxiv.org/content/10.1...
biorxiv.org
Theta-rhythmic attentional exploration of space
Attention facilitates stimulus processing by selecting specific locations (spatial attention) or features (feature-based attention). It can be sustained on a given location or feature, or re-oriented ...
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Andrea Brovelli @brovelli.bsky.social · 10/08/2025
Finally out on Nat Comms 🚀 We show that an intrinsic motivational learning signal (information gain) is encoded through synergistic and higher-order functional brain interactions and is broadcast to prefrontal reward circuits.
t.co
https://www.nature.com/articles/s41467-025-62507-1
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Daniele Marinazzo @danielemarinazzo.bsky.social · 01/08/2025
Localizing Synergies of Hidden Factors in Complex Systems: Resting Brain Networks and HeLa Gene Expression Profile as Case Studies www.mdpi.com/1099-4300/27...
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Seyed (Yahya) Shirazi @neuromechanist.bsky.social · 15/07/2025
🧠 𝗦𝘁𝗼𝗽 𝘂𝘀𝗶𝗻𝗴 𝗿𝗮𝘄 𝗘𝗘𝗚 𝗰𝗵𝗮𝗻𝗻𝗲𝗹𝘀 - 𝗵𝗲𝗿𝗲'𝘀 𝘄𝗵𝘆⁣ ⁣ New research with 1,024 brain electrodes proves EEG channels DON'T reflect local brain activity underneath the electrode.⁣ paper: ⁣https://www.biorxiv.org/content/10.1101/2025.06.24.660870v1 ⁣ #Neuroscience #EEG #BrainResearch
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RD PascualMarqui @pascualmarqui.bsky.social · 15/07/2025
Preprint: Equations/generalizations for TC, DTC, RSI, O-information, and TSE-complexity for multivar real/cmplx data. How “connections” contribute to system inf measures. Helpful comments and reports on errors are appreciated. arXiv: 2025-07-11 doi.org/10.48550/arXiv.2507.08773
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Tiago Peixoto @tiago.skewed.de · 11/07/2025
There are some corners of the network science literature which adamantly claim that connected components *must* belong to different communities. Yet, ER networks can easily be disconnected, and the same is true for individual groups in SBM networks. There, splitting the components overfits. 1/4
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Daniele Marinazzo @danielemarinazzo.bsky.social · 08/07/2025
But are they behaviors? physics.aps.org/articles/v18...
physics.aps.org
With Behaviors Like These in Complex Systems, Who Needs Mechanisms?
A new study of complex systems supports a growing trend that focuses more on analyzing a system’s collective behavior rather than on trying to uncover the underlying interaction mechanisms.
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Cat Hicks @grimalkina.bsky.social · 28/06/2025
"The analysis of the L.L.M. users showed fewer widespread connections between different parts of their brains" This is goddamn embarrassing, man. Instructive for understanding just how bad media is on this. Like there are anatomical changes being measured. www.newyorker.com/culture/infi...
newyorker.com
A.I. Is Homogenizing Our Thoughts
Recent studies suggest that tools such as ChatGPT make our brains less active and our writing less original.
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Ginestra Bianconi @gin-bianconi.bsky.social · 24/06/2025
Fantastic collaboration with @teo121270.bsky.social L.Giambagli R.Muolo "Global Topological Dirac Synchronization": Unveiling new dynamical states of higher-order networks with the Topological Dirac operator. iopscience.iop.org/article/10.1... @ioppublishing.bsky.social
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Natalie Schaworonkow @nschawor.bsky.social · 23/06/2025
happy that our article about mu & alpha rhythm waveform shape in development is now finally out in the open: doi.org/10.1162/jocn... oscillation frequency changes across development (one of the most robust findings in the oscillation world). in this work, we also look at waveform shape changes.
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Peter Zeidman @corticalpete.bsky.social · 23/06/2025
The beta release of SPM-Python is out now! Amazing work by Johan Medrano @johmedr.bsky.social , Yael Balbastre, Yulia Bezsudnova @ybezs.bsky.social and other members of their team. A new era for SPM! #OHBM2025
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Daniele Marinazzo @danielemarinazzo.bsky.social · 21/06/2025
Sorry this is inaccurate, this is a collider, thus a synergistic case
Venn diagram of synergistic and redundant information according to partial information decomposition
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Gaute Einevoll @gauteeinevoll.bsky.social · 21/06/2025
Episode #29 in #TheoreticalNeurosciencePodcast: On the philosophy of simplification in computational neuroscience - with Mazviita Chirimuuta and Terrence Sejnowski theoreticalneuroscience.no/thn29 What are the pitfalls when simplifying? Panel debate at FENS meeting in Oslo. @fens.org
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Cat Hicks @grimalkina.bsky.social · 20/06/2025
the level of misinformation sparked because of this bananas EEG preprint is just really tragic. By the way if you think that a researcher caused cognitive decline to happen to participants in a study you should probably be freaked out by that
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Daniele Marinazzo @danielemarinazzo.bsky.social · 12/06/2025
Localizing synergies of hidden factors across complex systems: resting brain networks and HeLa gene expression profile as case studies arxiv.org/abs/2506.09053
Localizing synergies of hidden factors across complex systems: resting brain networks and HeLa gene expression profile as case studies
Marlis Ontivero-Ortega, Gorana Mijatovic, Luca Faes, Daniele Marinazzo, Sebastiano Stramaglia
Factor analysis is a well-known statistical method to describe the variability of observed variables in terms of a smaller number of unobserved latent variables called factors. Even though latent factors are conceptually independent of each other, their influence on the observed variables is often joint and synergistic. We propose to quantify the synergy of the joint influence of factors on the observed variables using the O-information, a recently introduced metrics to assess high order dependencies in complex systems, in a new framework where latent factors and observed variables are jointly analyzed in terms of their joint informational character. Two case studies are reported: analyzing resting fMRI data, we find that DMN and FP networks show the highest synergy, consistently with their crucial role in higher cognitive functions; concerning HeLa cells, we find that the most synergistic gene is STK-12 (AURKB), suggesting that this gene is involved in controlling the HeLa cell cycle. We believe that this approach, representing a bridge between factor analysis and the field of high-order interactions, will find wide application across several domains.
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Dan Goodman @neural-reckoning.org · 10/06/2025
Fusing multisensory signals across channels and time. Now published at PLOS Comp Biol! 🎉 With @swathianil.bsky.social and @marcusghosh.bsky.social. journals.plos.org/ploscompbiol... TLDR, when multisensory signals vary over time, neural architecture becomes important. Biggest not always best.
journals.plos.org
Fusing multisensory signals across channels and time
Author summary We constantly detect sensory inputs, like sights and sounds, and use combinations of these signals to guide our actions. For example, by reading someone’s lips we can better converse wi...
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Christophe Phillips @chphillips.bsky.social · 10/06/2025
Quick check of the paper mentioned here under and it's rather "opaque". 🤔 Key point IMO is confusing Maxwell's equations time dependence and brain waves time scale. Anisotropy and inhomogeneity in tissue conductivity is important but it lives very well with the "quasi-static approximation".
hdl.handle.net
ORBi: Detailed Reference
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