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Francesco Di Ciò

@fdi55.bsky.social
98 followers 170 following 0 posts

Ph.D. Candidate in the social neuroscience lab (ICN, UCL).|| Interested in social cognition, hyperscanning and group behaviour.

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Reposted by Francesco Di Ciò
Sam Gilbert @samgilbert.bsky.social · 30/09/2026
I spoke with @manymindspod.bsky.social about research into cognitive offloading, metacognition, memory, photo-taking, GPS, AI, and why there’s no such thing as “digital dementia”. Thanks so much for having me!
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Dominik Deffner @dominikdeffner.bsky.social · 24/09/2026
Now published in @natcomms.nature.com! Using a 3D immersive-reality group experiment, we show how people integrate dynamically changing personal and social cues in realistic environments, resulting in either collective intelligence or maladaptive behavior! Paper: www.nature.com/articles/s41...
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Ralf Kurvers @ralfkurvers.bsky.social · 18/09/2026
Very proud of @kirikuroda.bsky.social for preprinting this study on social influence and information cascades in experienced based decision making. osf.io/preprints/ps... @arc-mpib.bsky.social. Great collab with @simyciri.bsky.social @dirkwulff.bsky.social
osf.io
OSF
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Taiki Oka @toka-neuro.bsky.social · 03/09/2026
1/7 Excited to share our new @elife.bsky.social Reviewed Preprint! 🧠 How do higher-order cognitive processes like abstraction & metacognition map onto transdiagnostic mental health dimensions? We combined computational modeling of a RL task with symptom profiling 🔗 doi.org/10.7554/eLif...
doi.org
Mapping abstraction and metacognition onto distinct transdiagnostic symptom profiles
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Lei Zhang | 张磊 @lei-zhang.bsky.social · 02/09/2026
Very excited to share our new work (my first @arxiv-cs-ai.bsky.social!) We compared mentalising abilities across human and LLMs across two games and models. We thought the field'd re-embrace the interdisciplinarity of cognitive science. Curious? Read here! 👇 arxiv.org/abs/2608.26291
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Lucas Benjamin @lucaswbenjamin.bsky.social · 24/08/2026
Our new paper is now out in @pnas.org! How does the (baby) brain extract regularities from sequences from what-follows-what up to large-scale network structure? What if it all came from a single mechanism? www.pnas.org/doi/abs/10.1...
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Herbert Wu @herbertwu.bsky.social · 20/08/2026
First study out! Using a new cooperative paradigm and multi-agent inverse RL, we show that mice spontaneously adopt leader/follower roles, and the prefrontal cortex encodes these role dynamics and an egocentric social value map of the partner’s position. (1/3) www.nature.com/articles/s41...
nature.com
Asymmetric prefrontal representations for leader–follower dynamics - Nature
Mice spontaneously form leader and follower roles during cooperation, and the medial prefrontal cortex encodes these role dynamics and an egocentric social value map of the partner’s position.
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NetScience @netscience.bsky.social · 15/08/2026
Robustness of small networks link.aps.org/doi/10.1103/...
link.aps.org
Robustness of small networks
Modeling how networks change under structural perturbations can yield foundational insights into network robustness, which is critical in many real-world applications. The largest connected component ...
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Soroush Mirjalili @soroushmirjalili.bsky.social · 11/08/2026
🧠🚨 How can we measure the latent cognitive processes that work together during complex behavior? In our new Perspective, we propose cross-domain transfer: learning a neural signature of a cognitive process in one task and using it to track that process in another. 🧵 osf.io/preprints/ps...
osf.io
OSF
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Ryssa Moffat @ryssamoffat.bsky.social · 13/08/2026
📢 Big announcement: The InterGenSynchrony Dataset is now published! 🔗 Dataset: openneuro.org/datasets/ds0... 🔗 Dataset descriptor: doi.org/10.64898/202...
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Russ Poldrack @russpoldrack.org · 11/08/2026
Many of you will have seen the recent post about changes at OSF. If you'd like to learn more about how to use other services (particularly Zenodo) to share data and code, see my book chapter on resource sharing. bettercode-book.org/book-sharing...
bettercode-book.org
12  Sharing Research Objects – Better Code, Better Science
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Mark Thornton @markthornton.bsky.social · 03/08/2026
Very excited to share this preprint from me, @emmatempleton.bsky.social, @lindseytepfer.bsky.social & @thaliawheatley.bsky.social! "Friends and strangers engage in distinct regimes of body motion synchrony during conversation" osf.io/preprints/ps...
 Forms of body motion synchrony. A) Motion quantity synchrony – synchrony in the amount of motion (orange) people engage in over time. This form of synchrony is agnostic to the direction of this movement, may be positive or negative, occurs at varying time lags, and is not specific to matched body parts across members of the dyad. B) Pseudo-synchrony – motion quantity synchrony between people who are not actually interacting. That is, members of different conversations engaging in similar amounts of motion at similar points in the conversation relative to its initiation. And C) directional synchrony – people moving the same body parts in the same direction (or along the same axis in the opposite direction) at the same time (or at some specific time lag). Mechanisms of synchrony. A) Turn-taking, which causes increases in motion around the time of speaker role exchanges, as participants gesture to hand over or take over the floor. B) Conservation of motion in which one participant moves less when the other moves more, holding the total motion quantity relatively constant over time (note that the total amount of motion across the dyad is similar in the two panels, because one person reduces their motion to balance out the increase in the other’s motion). C) Entrainment, in which mutual following of the same conversational script leads to synchronized movement among people who are not directly interacting (i.e. pseudo-synchrony). Greeting gestures such as the handshakes depicted are one acute manifestation of this entrainment. D) Station-keeping, which maintains proxemic distance and eye level between members of the dyad. This mechanism accounts for directional synchrony, particularly between strangers who feel uncomfortable within each other’s personal space.Motion quantity synchrony among friends and strangers. A) Friends displayed significant positive synchrony in total motion quantity at short time lags (< 2.5 s) and B) this effect generalized across the majority of body part pairs (each line represents one pair). For example, one series of points might represent the synchrony between the amount of motion in one participant’s left hand and the other’s right foot. C) Strangers displayed significant positive synchrony in total motion quantity at short time lags (< 1 s) and significant negative total motion quantity synchrony at longer time lags (2.5 – 16.6 s). D) Again, this effect generalized to most body part pairs.Directional synchrony among friends and strangers. A) Among friends, we observed statistically significant directional synchrony in only two body parts (nose and eye) and only in the vertical axis. B) Among strangers, we observed statistically significant directional synchrony in a large number of body parts in the horizontal, vertical, and depth axes.
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European Research Council (ERC) @erc.europa.eu · 30/07/2026
What helps friendships form and thrive? This International Day of Friendship, discover how ERC grantee Antonia Hamilton @ucl.ac.uk is investigating the science of #friendship and how curiosity-driven research could help tackle loneliness. 🔗 buff.ly/5tNYptB @antoniahamilton.bsky.social
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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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Paul Smaldino @psmaldino.bsky.social · 30/07/2026
A Demographic Theory of Similarity-Biased Social Learning. Now out in PNAS, led by the incomparable @apvelilla.bsky.social . We use modeling to explore conditions for the (cultural) evolution of parochial (and anti-parochial) learning biases. www.pnas.org/doi/10.1073/...
Humans adapt by learning from others, but risk acquiring maladaptive behaviors when learning from individuals facing different conditions. We present an evolutionary model exploring how individuals use social identity markers to select learning targets in diverse populations. Learners evolve biases that track reliable information sources: preferring similar individuals when in-group knowledge is adaptive, and dissimilar individuals when in-group behaviors are disadvantageous. Our framework demonstrates that this adaptive bias makes social learning viable even when it is costlier than individual learning. Additionally, we show that a minimum threshold of reliable cultural information is required for social learning to spread, providing a mathematical explanation for how demographic diversity drives population-level patterns of cultural segregation and assimilation.
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Rik Henson @rhens.bsky.social · 20/07/2026
Thanks to Kshipra Guranandan, my notebook on how to design efficient fMRI experiments (for activity, connectivity and pattern analysis) is now available in Python as a Jupyter notebook (as well as previous Matlab): github.com/RikHenson/fM...
github.com
GitHub - RikHenson/fMRIefficiency
Contribute to RikHenson/fMRIefficiency development by creating an account on GitHub.
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Dr Lena Matyjek @lmatyjek.bsky.social · 16/07/2026
Our article is now published in Autism Research! onlinelibrary.wiley.com/doi/10.1002/... Aperiodic EEG slopes suggest that atypicality in autism is not about what the brain is like, but how it responds under demanding conditions. #autism #EEG
onlinelibrary.wiley.com
Task‐Related Aperiodic <fc>EEG</fc> (1/f) Activity in Autism
Autism has been hypothesized to involve atypicalities in the balance between neural excitation and inhibition (E/I). Aperiodic EEG activity, characterized by the 1/f exponent of the power spectrum, p...
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Yongzhen Xie @doryyongzhenxie.bsky.social · 10/07/2026
My fMRI study from the Mack Lab (@drmack.bsky.social) is now published on JNeuro! Here, we look into how hippocampal subfields flexibly update category knowledge representations in the face of novel exceptions. Check out the article here: doi.org/10.1523/JNEU....
doi.org
Distinct Hippocampal Subfield Representational Shifts Underlie Category Exception Learning
When we encounter an exception to our prior category knowledge, such as a leaf-like butterfly that perceptually diverges from the butterflies we commonly see, we must update our knowledge to reconcile...
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SINe Lab @sinelabdtu.bsky.social · 10/07/2026
Funded by @villumfonden.bsky.social
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Dominik Deffner @dominikdeffner.bsky.social · 10/07/2026
Learning from the most successful people makes sense? We show that social learning, and especially payoff bias, is bad when choice outcomes are dependent on prior success💰 As such "rich-get-richer" dynamics are everywhere, this shows fundamental boundary conditions for the benefits of SL!
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Manlio De Domenico @manlius.bsky.social · 09/07/2026
We search for life using categories learned from one planet A new study shows that changing gravity changes mitochondrial translation, part of biology’s functional architecture. Change the planet, change the boundary conditions of life. @ricardsole.bsky.social 🧪🌐🧬🌍 www.nature.com/articles/s41...
nature.com
Gravitational and mechanical forces shape mitochondrial translation - Nature Communications
In this study, microgravity was found to disrupt mitochondrial translation through inhibition of laminin–integrin signaling and the downstream pathway, which is usually activated by mechanical stress.
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Tiago Peixoto @tiago.skewed.de · 08/07/2026
Good news everyone! 🎉 The new version 3.0 of graph-tool is just out with major improvements! See below. graph-tool.skewed.de graph-tool is a comprehensive and efficient Python library to work with networks, including structural, dynamical, and statistical algorithms, as well as visualization. 1/N
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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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Alon Baram @alonbaram.bsky.social · 29/06/2026
How does the human brain extract abstract structure from experience? We show that sensory-independent relational representations emerge in mPFC over several days. Work with @mgarvert.bsky.social and @behrenstimb.bsky.social now out in @currentbiology.bsky.social: www.cell.com/current-biol...
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Ryssa Moffat @ryssamoffat.bsky.social · 30/06/2026
🧠 🔎 Can we consider brain plasticity during skill learning from new angles? In a new paper, @simonleipold.bsky.social and I propose an approach that puts individual people under the magnifying glass. Link to paper: www.sciencedirect.com/science/arti...
sciencedirect.com
Individual-specific precision neuroimaging of learning-related plasticity
Studying learning-related plasticity is central to understanding the acquisition of complex skills, for example learning to master a musical instrumen…
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Ketika Garg @ketikagarg.bsky.social · 30/06/2026
🚨This preprint is now out in PNAS: www.pnas.org/doi/full/10.... We combine a dyadic foraging paradigm w/ computational modeling + ABM to study how people navigate differing preferences, share responsibility for shared outcomes & what that means for the group! more in 🧵⬇️ @fearbrain.bsky.social
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Thomas F. Varley @thosvarley.bsky.social · 25/06/2026
New information theory results: Tl;dr - here are two generalizations. The first is that TC/DTC/S-info/O-info are special cases of a common form. The second allows us to move beyond Shannon info. theory for more general theory of synergy. 1/N arxiv.org/abs/2601.08030
arxiv.org
The many faces of multivariate information
Extracting higher-order structures from multivariate data has become an area of intensive study in complex systems science, as these multipartite interactions can reveal insights into fundamental feat...
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Hanlu He @hanluhe.bsky.social · 24/06/2026
Excited to share that my first paper "Heart rate synchrony as a marker of real-world social engagement" is now published in PNAS Nexus The full article can be accessed here: academic.oup.com/pnasnexus/ar... @sinelabdtu.bsky.social
academic.oup.com
Heart rate synchrony as a marker of real-world social engagement
Abstract. Human social behavior unfolds in complex real-world environments influenced by social and environmental factors, yet reliable markers of social e
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Drew Schreiner @schreinerdrew.bsky.social · 10/06/2026
1/ We work hard to factor "noise" out of behavior. But the brain doesn't. Strip away noise and you may miss what the brain evolved to do I wanted to share this pre-Bluesky paper where we found premotor (M2) corticostriatal circuits encode a broad history of behavior, beyond just action + reward 👇
nature.com
Information normally considered task-irrelevant drives decision-making and affects premotor circuit recruitment - Nature Communications
Prior experience is used by the brain to guide adaptive behaviour during decision making. Here, the authors show that mice also selectively use information learned through recent and longer-term exper...
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Imaging Neuroscience @imagingneurosci.bsky.social · 19/06/2026
New paper in Imaging Neuroscience by Massimiliano Facca, Alessandra Bertoldo, et al: Glucose metabolism echoes long-range temporal correlations in the human brain doi.org/10.1162/IMAG...
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PLOS Biology @plosbiology.org · 16/06/2026
#Aging drives changes in the #brain and #metabolism, but how independent are these effects? This study by @asafarahani.bsky.social, @misicbata.bsky.social &co identifies two axes of brain-body associations, each primarily related to age or metabolic health. 🧪#AcademicSky plos.io/4eoIu3L
A series of brain maps, showing the association between one of the identified biomarkers relating sub-regional brain features to physiological, functional, and structural factors.
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Henrik Singmann @singmann.bsky.social · 16/06/2026
Finally out in Psychological Review (psycnet.apa.org/doi/10.1037/...), our update to Signal Detection Theory. We show that contrary to the prevailing Gaussian assumption, evidence distributions in recognition memory are likely minimum extreme Gumbel!
Figure 7: Illustration of the Gumbel-min Signal Detection Model
Figure consists of three panels.
Bottom-left panel: The Gumbel-min latent-strength distributions associated with SIGNAL (old) and NOISE (new) items. Top-left panel: The log likelihood ratio (log-LR) for the two latent-strength distributions. Right panel: The receiver operating characteristic function produced by the two latent-strength distributions. pH = hit probabilities; pFA = false-alarm probabilities.
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Nature Reviews Psychology @natrevpsychol.nature.com · 12/06/2026
Human cooperation is strong among individuals but fragile between groups Perspective by Paul A. M. Van Lange & Paul K. Bergmann bit.ly/4eFHMjK #psychscisky #socialpsych
bit.ly
Human cooperation is strong among individuals but fragile between groups - Nature Reviews Psychology
There is ample empirical evidence that humans are cooperative, but there is also evidence that humans can be distrustful, hostile and aggressive. In this Review, Van Lange and Bergmann reconcile this ...
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Caroline Robertson @carolinerobertson.bsky.social · 12/06/2026
Very excited to share this paper, led by @ajhaskins.bsky.social ! We find that how people look around the world is stable and idiosyncratic — and that these gaze patterns are shaped in part by the conceptual priorities each person brings to a scene. 1/3 www.pnas.org/doi/10.1073/...
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Yu Kanazawa @knzw783.bsky.social · 07/06/2026
🧠🤖 Samiei, M., Precup, D., & Richards, B. A. (2026). The schema spectrum: Emergent structures and levels of abstraction in AI and the brain. Neuron, 114(11), 1898–1907. doi.org/10.1016/j.ne...
doi.org
The schema spectrum: Emergent structures and levels of abstraction in AI and the brain
There is a long history of interplay between the brain sciences and AI in the area of schema theory. Schemas are typically defined as abstract mental …
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Kathrin Kostorz @kathrinkostorz.bsky.social · 05/06/2026
New preprint alert! Are you interested in measuring brain synchrony? We wrote a primer for you that explains the signal processing basics, and their substantial pitfalls. And I promise it's no math (but check out the supplement if that's your thing!) but massive content! osf.io/preprints/ps... 🧠🧠
osf.io
OSF
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Sam Verschooren @samversc.bsky.social · 04/06/2026
🎉New paper out today in Nature Reviews Psychology🎉 with @mjdahl.bsky.social, @mariamaly.bsky.social, and @thiasmittner.bsky.social. We've been working on a unified framework for attentional states and the dynamics of transitions between them. 🧵
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Badr AlKhamissi @bkhmsi.bsky.social · 01/06/2026
🧠 When you watch a movie, your brain blends sight, sound, and speech into a single experience. Should models of the brain blend them too, or keep the senses separate until the very end? We built MIRAGE to find out. It sets a new SOTA for predicting whole-brain fMRI from movies. 🧵
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NetScience @netscience.bsky.social · 28/05/2026
Detecting and forecasting tipping points from sample variance alone arxiv.org/abs/2602.10817
arxiv.org
Detecting and forecasting tipping points from sample variance alone
Anticipating tipping points in complex systems is a fundamental challenge across domains. Traditional early warning signals (EWSs) based on critical slowing down, such as increasing sample variance, a...
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Philip Sulewski @psulewski.bsky.social · 26/05/2026
Now out in Nature Neuroscience: "Fixation duration on natural scenes is explained by memory encoding not processing demand". www.nature.com/articles/s41... Our eyes don't linger because recognition is hard; they linger to remember. Let me take you on a quick tour. 🧵
nature.com
Fixation duration on natural scenes is explained by memory encoding not processing demand - Nature Neuroscience
By combining magnetoencephalography and eye tracking, this study sheds light on why people fixate on some parts of natural scenes longer than others. Rather than visual complexity, fixation durations ...
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Riccardo Fusaroli @fusaroli.eurosky.social · 25/05/2026
Scale up behavioral measurement w ML& you get extra noise & bias. "Classification errors distort findings in automated speech processing," by @lucasgautheron.bsky.social, Kidd, Malko, @marvinlavechin.bsky.social & @acristia.bsky.social shows how to deal w that: pubmed.ncbi.nlm.nih.gov/42151656/ 1/
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Richard McElreath 🐈‍⬛ @rmcelreath.bsky.social · 22/03/2026
Statistical Rethinking 2026 is done: 20 new lectures emphasizing logical and critical statistical workflow, from basics of probability theory to causal inference to reliable computation to sensitivity. It's all free, made just for you. Lecture list and links: github.com/rmcelreath/s...
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Gal Rozic @galrozic.bsky.social · 19/05/2026
New preprint out!✨ Let me tell you about ‘inflation’… We introduce MAPS: a framework to code caregivers’ Mentalizing + Pedagogical Strategies when explaining abstract concepts to their child💬 Only some strategies were associated with learning. Perspective-taking may be key ➡️ osf.io/preprints/ps...
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Francisco Rodriguez-Sanchez @frodsan.bsky.social · 17/05/2026
#StatsPubs No matter how many times you read it, this paper on hierarchical GAMs keeps giving. Clear model explanations together with R code (mgcv). So useful! doi.org/10.7717/peer... Thanks for writing @ericjpedersen.bsky.social, D. Miller, @gsimpson.bsky.social @noamross.net
In this paper, we discuss an extension to two popular approaches to modeling complex structures in ecological data: the generalized additive model (GAM) and the hierarchical model (HGLM). The hierarchical GAM (HGAM), allows modeling of nonlinear functional relationships between covariates and outcomes where the shape of the function itself varies between different grouping levels. We describe the theoretical connection between HGAMs, HGLMs, and GAMs, explain how to model different assumptions about the degree of intergroup variability in functional response, and show how HGAMs can be readily fitted using existing GAM software, the mgcv package in R. We also discuss computational and statistical issues with fitting these models, and demonstrate how to fit HGAMs on example data. All code and data used to generate this paper are available at: github.com/eric-pedersen/mixed-effect-gams.
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Luigi Acerbi @lacerbi.bsky.social · 30/04/2026
1/ Wouldn't it be nice if you could perform Bayesian inference *efficiently* but also *reliably*? Amortized inference offers the former, while MCMC is often presented as the "gold standard" for accuracy and reliability. Enter the Amortized Bayesian Workflow...
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SINe Lab @sinelabdtu.bsky.social · 30/04/2026
Our paper is now published in Annals of the New York Academy of Sciences! nyaspubs.onlinelibrary.wiley.com/doi/10.1111/... @carlsbergfondet.dk See summary 👇
nyaspubs.onlinelibrary.wiley.com
NYAS Publications
When two people synchronize their breathing together, their heart rhythms also synchronize, while their intrapersonal cardiorespiratory rhythms become decoupled, with a perturbed phase-relationship b...
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Liuba Papeo @ljubapi.bsky.social · 25/04/2026
10 years ago we identified a stage in social-event processing in which perception recognizes that two social agents are connected. A new study now shows that this stage is fully encapsulated from language and semantics. Soon to appear in @APA JEP:HPP Preprint osf.io/ngjwu/files/...
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Yang Teoh @yyangteoh.bsky.social · 14/04/2026
Now out in PNAS with @jaeyoungson.bsky.social, Alice Xia, @apaxon.bsky.social & @orielf.bsky.social. Medial temporal lobe encodes predictive representations of people's real-world social networks which afford them key advantages in social navigation. www.pnas.org/doi/10.1073/... 🧵
pnas.org
Medial temporal lobe encodes cognitive maps of real-world social networks | PNAS
Humans routinely solve social problems by navigating densely interconnected networks&mdash;gossiping strategically, brokering across cliques, and coordin...
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Dr Lena Matyjek @lmatyjek.bsky.social · 25/03/2026
[Castellano abajo] Thrilled to be featured in La Vanguardia! 🧠 We discuss why research must be done with and for society— especially in cognitive neuroscience on #autism. Proud to do this research at @upf.edu @cbc-upf.bsky.social @mrgbcn.bsky.social! 🔗 [lnkd.in/duhKDuuX]
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Russ Poldrack @russpoldrack.org · 24/03/2026
Why you should be very careful installing packages from Github: github.com/BerriAI/lite...
github.com
[Security]: CRITICAL: Malicious litellm_init.pth in litellm 1.82.8 — credential stealer · Issue #24512 · BerriAI/litellm
[Security]: CRITICAL: Malicious litellm_init.pth in litellm 1.82.8 PyPI package — credential stealer Summary The litellm==1.82.8 wheel package on PyPI contains a malicious .pth file (litellm_init.p...
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