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Quentin Moreau

@quentinmoreau.bsky.social

Cognitive and Social Neuroscientist in Lyon 🧠- MEEG and Beta Bursts 💥 Postdoc at the DANC Lab 👨🏻‍🎓 - Basketball fan 🏀 https://www.danclab.com/member/member17/

30 Posts369 Follower387 Folgt
Decision, Action, and Neural Computation (DANC) lab@danclab.bsky.social · 5mo ago

We've been saying for a while now that beta bursts might be functionally heterogeneous. Check out @quentinmoreau.bsky.social's paper where we show that different types of bursts have different relationships to behavior in a sensorimotor adaptation task 👇👇👇

Quentin Moreau@quentinmoreau.bsky.social · 5mo ago

🧵1/3 New paper out! Beta bursts aren't all the same and their waveform shape are functionally meaningful ! @maciekszul.bsky.social & @danclab.bsky.social👇 www.biorxiv.org/content/10.6...

Maciek Szul@maciekszul.bsky.social · 8mo ago

An accessible overview on why beta band activity is best seen as a diverse set of events and not an oscillation, along with cortico-subcortical network responsible for specific waveform shape. @hollyrayson.bsky.social @quentinmoreau.bsky.social Solène Gailhard @danclab.bsky.social

Beta Burst Waveform Diversity: A Window onto Cortical Computation - Holly Rayson, Quentin Moreau, Solene Gailhard, Maciej J. Szul, James J. Bonaiuto, 2025

Neural activity in the beta band is increasingly recognized to occur not as sustained oscillations but as transient burst-like events. These beta bursts are div...

journals.sagepub.com

Guillaume Dumas@introspection.bsky.social · 10mo ago

New study led by @quentinmoreau.bsky.social & @vchamberland.bsky.social and @ppsp-team.bsky.social 👏 We show how brain stim can shape social inference in human–machine interaction 🧠🤖⚡ New causal evidence linking rTPJ to Theory-of-Mind & Self–Other distinction, & path towards social #neuromodulation!

@vchamberland.bsky.social · 10mo ago

📢 Our latest work at @ppsp-team.bsky.social is now available on eNeuro! Our study explores how noninvasive brain stimulation can shape social inference during human–machine interaction 🧠⚡🤖 🔗 Read it here → www.eneuro.org/content/12/1... Thread 🧶 ⤵️

@vchamberland.bsky.social · 10mo ago

5/ Results: ❌ No effect of rTPJ stimulation on motor coordination (Experiment 1 and 2). ✅ Repeated HD-tRNS sharpened detection of competitive intent and reduced humanness attribution during competitive interactions (Experiment 1 only).

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@vchamberland.bsky.social · 10mo ago

4/ Two complementary experiments: Exp1 (n=39): HD-tRNS⚡ or sham 🚫 randomized blocks Exp2 (n=40): HD-tRNS⚡ and sham 🚫 randomized trials During trials, participants synchronized finger movements with a covert virtual partner, then rated perceived cooperativeness & humanness.

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@vchamberland.bsky.social · 10mo ago

3/ We applied high-definition transcranial random noise stimulation (HD-tRNS) over the right temporoparietal junction (rTPJ) of participants interacting with the virtual partner of the HDC, aiming to probe the rTPJ’s causal role in real-time social interaction.

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@vchamberland.bsky.social · 10mo ago

2/ Our work directly builds on Dumas et al. (2020), who combined high-density EEG with the Human Dynamic Clamp (HDC) paradigm to reveal the rTPJ as a key cortical hub for integrating self–other representations.

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@vchamberland.bsky.social · 10mo ago

1/ TL;DR: High-definition transcranial random noise stimulation (⚡) over the right temporoparietal junction (🧠) sharpened detection of competitive intent during interaction with a covert virtual partner (🤖)—without affecting motor coordination.

@vchamberland.bsky.social · 10mo ago

📢 Our latest work at @ppsp-team.bsky.social is now available on eNeuro! Our study explores how noninvasive brain stimulation can shape social inference during human–machine interaction 🧠⚡🤖 🔗 Read it here → www.eneuro.org/content/12/1... Thread 🧶 ⤵️

Online HD-tRNS Over the Right Temporoparietal Junction Modulates Social Inference But Not Motor Coordination

Social interactions are fundamental to human cognition, with the right temporoparietal junction (rTPJ) playing a key role in integrating motor coordination and social inference. While transcranial ran...

eneuro.org

Decision, Action, and Neural Computation (DANC) lab@danclab.bsky.social · last yr.

It's been a while since our last laminar MEG paper, but we're back! This time we push beyond deep versus superficial distinctions and go whole hog. Check it out- lots more exciting stuff to come! 🧠📈

Maciek Szul@maciekszul.bsky.social · last yr.

🚨🚨🚨PREPRINT ALERT🚨🚨🚨 Neural dynamics across cortical layers are key to brain computations - but non-invasively, we’ve been limited to rough "deep vs. superficial" distinctions. What if we told you that it is possible to achieve full (TRUE!) laminar (I, II, III, IV, V, VI) precision with MEG!

Overview of the simulation strategy and analysis. a) Pial and white matter boundaries surfaces are extracted from anatomical MRI volumes. b) Intermediate equidistant surfaces are generated between the pial and white matter surfaces (labeled as superficial (S) and deep (D) respectively). c) Surfaces are downsampled together, maintaining vertex correspondence across layers. Dipole orientations are constrained using vectors linking corresponding vertices (link vectors). d) The thickness of cortical laminae varies across the cortical depth (70–72), which is evenly sampled by the equidistant source surface layers. e) Each colored line represents the model evidence (relative to the worst model, ΔF) over source layer models, for a signal simulated at a particular layer (the simulated layer is indicated by the line color). The source layer model with the maximal ΔF is indicated by “˄”. f) Result matrix summarizing ΔF across simulated source locations, with peak relative model evidence marked with “˄”. g) Error is calculated from the result matrix as the absolute distance in mm or layers from the simulated source (*) to the peak ΔF (˄). h) Bias is calculated as the relative position of a peak ΔF(˄) to a simulated source (*) in layers or mm.
Maciek Szul@maciekszul.bsky.social · last yr.

🚨🚨🚨PREPRINT ALERT🚨🚨🚨 Neural dynamics across cortical layers are key to brain computations - but non-invasively, we’ve been limited to rough "deep vs. superficial" distinctions. What if we told you that it is possible to achieve full (TRUE!) laminar (I, II, III, IV, V, VI) precision with MEG!

Overview of the simulation strategy and analysis. a) Pial and white matter boundaries surfaces are extracted from anatomical MRI volumes. b) Intermediate equidistant surfaces are generated between the pial and white matter surfaces (labeled as superficial (S) and deep (D) respectively). c) Surfaces are downsampled together, maintaining vertex correspondence across layers. Dipole orientations are constrained using vectors linking corresponding vertices (link vectors). d) The thickness of cortical laminae varies across the cortical depth (70–72), which is evenly sampled by the equidistant source surface layers. e) Each colored line represents the model evidence (relative to the worst model, ΔF) over source layer models, for a signal simulated at a particular layer (the simulated layer is indicated by the line color). The source layer model with the maximal ΔF is indicated by “˄”. f) Result matrix summarizing ΔF across simulated source locations, with peak relative model evidence marked with “˄”. g) Error is calculated from the result matrix as the absolute distance in mm or layers from the simulated source (*) to the peak ΔF (˄). h) Bias is calculated as the relative position of a peak ΔF(˄) to a simulated source (*) in layers or mm.
@vchamberland.bsky.social · last yr.

Our latest work at @ppsp_team is now available on @biorxivpreprint.bsky.social ⚡🧠~🤖 We tested whether online non-invasive brain stimulation could modulate real-time human~machine social interactions. 📄 Read the preprint: www.biorxiv.org/content/10.1... Thread 🧶 ⤵️

Online HD-tRNS over the right temporoparietal junction modulates social inference but not motor coordination

Social interactions are fundamental to human cognition, with the right temporoparietal junction (rTPJ) playing a key role in integrating motor coordination and social inference. Transcranial random no...

biorxiv.org