Marc Coutanche

fMRI_EPI_KspaceAcquisition_short This is a demonstration of how a single slice of functional magnetic resonance imaging (fMRI) data is collected. Before this makes any sense, you will need to understand…

Nice demo by Mark Lescroart @neuromdl.bsky.social on EPI imaging of a single #fMRI slice. Great for teaching! :)
vimeo.com/143701608?fl...

Love this article! We need more real-life memory studies.
Here is an example study and review from our lab…child development focus.

cognitiveresearchjournal.springeropen.com/articles/10....

www.sciencedirect.com/science/arti...

The idea that human cognition is, or can be understood as, a form of computation is a useful conceptual tool for cognitive science. It was a foundational assumption during the birth of cognitive science as a multidisciplinary field, with Artificial Intelligence (AI) as one of its contributing fields. One conception of Al in this context is as a provider of computational tools (frameworks, concepts, formalisms, models, proofs, simulations, etc.) that support theory building in cognitive science. The contemporary field of Al, however, has taken the theoretical possibility of explaining human cognition as a form of computation to imply the practical feasibility of realising human(-like or -level) cognition in factual computational systems; and, the field frames this realisation as a short-term inevitability. Yet, as we formally prove herein, creating systems with human(-like or -level) cognition is intrinsically computationally intractable.

🚨Our paper `Reclaiming AI as a theoretical tool for cognitive science' is now forthcoming in the journal Computational Brain & Behaviour. (Preprint: osf.io/preprints/ps...)

Below a thread summary 🧵1/n

#metatheory #AGI #AIhype #cogsci #theoreticalpsych #criticalAIliteracy

New eLife preprint from Tan Nguyen—Pattern-based functional MRI and computational modeling show evidence for multiple signals contributing to updating the brain's representations of events: elifesciences.org/reviewed-pre...

Ever wondered if your interesting brain-behavior correlation was over- or under-estimated due to head motion, but were afraid to ask? We’ve created a motion impact score for detecting spurious brain-behavior associations, now available in Nature Communications!
doi.org/10.1038/s414...

Temporal dedifferentiation of neural states with age during naturalistic viewing - Communications Biology Movie fMRI data reveals age-related lengthening of neural states in visual and prefrontal regions, reflecting reduced temporal differentiation while preserved alignment with perceived events suggests stable coarse event segmentation.

The brain represents the world around us as a series of neural states - stable patterns of activity that change as we move from one event to the next.

New paper by @selmalugtmeijer.bsky.social showing that neural states get longer as people age. #PsychSciSky

nature.com/articles/s42003-025-08792-4

🚨🚨New precision imaging study and open dataset 🚨🚨 Featuring almost 200 functional runs acquired in 3-4d intervals and behavioral manipulations focused on intraindividual study of the reward response - The Night Owls Scan Club (NOSC) With @dvsmith.bsky.social and @olinotom.bsky.social!

Authors retract Science paper on controversial fMRI method Several MRI artifacts contribute to the neuronal activity signal picked up by the method, according to a preprint the authors posted this month.

A method for capturing neuronal activity using fMRI excited the neuroimaging field but couldn’t be replicated. Today, the authors of the original paper retracted their work.

By @callimcflurry.bsky.social

#neuroskyence

www.thetransmitter.org/retraction/a...

Excited to share new work with @hleemasson.bsky.social , Ericka Wodka, Stewart Mostofsky and @lisik.bsky.social! We investigated how simultaneous vision and language signals are combined in the brain using naturalistic+controlled fMRI. Read the paper here: osf.io/b5p4n
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I am pleased to share that "the bird study" is now accepted at Psychology and Aging! A great collaboration with visiting intern Kishen Senziani, @leabartsch.bsky.social & @edamizrak.bsky.social 😀 Check out the pre-print below and a short thread on the study design and main takeaways 🧵👇

8x8 grid depicting the approach to stimulus creation. Feature pairs are on the axes and images are in the cells. The x-axis represents the high-level feature pairs: setting (green) and object (teal). For example, the first column of images all depict “truck” (object) in “field” (setting) rendered in various textures and patterns. The y-axis represents low-level feature pairs: texture (blue) and pattern (purple). For example, the first row of images all depict different objects and settings rendered as if drawn with crayon (texture) and containing large horizontal edges (pattern).

Excited to release the SPOT grid: a new image set that factorially crosses scene-object & texture-pattern pairings.

We hope these stimuli will be useful to researchers aiming to (partially) disentangle the contributions of lower- and higher-level visual features to behavior & brain activity.

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New paper alert! 🚨 We show that age-related neural dedifferentiation in scene-selective cortex is tied to changes in eye movements. Using simultaneous fMRI + eye-tracking, we found that younger adults’ fixations covary with scene specificity, but this link weakens with age.

Link in post below 👇

Natural language processing captures memory content associated with shared neural patterns at encoding People can experience the same event yet form distinct memories shaped by individual interpretations. Prior research shows that multivariate activity patterns in the Default Mode Network (DMN) are cor...

New preprint! My stellar undergrad, June Kim, & @charan-neuro.bsky.social find that intersubject pattern similarity at encoding (especially in posteromedial cortex) relates to shared/differing content between Ss at recall (measured using topic modeling) www.biorxiv.org/content/10.1...

Distributed and drifting signals for working memory load in human cortex Increasing working memory (WM) load incurs behavioral costs, and whether the neural constraints on behavioral costs are localized (i.e., emanating from the intraparietal sulcus) or distributed across ...

New pre-print day! Distributed and drifting signals for working memory load in human cortex 🧠 (with Ed Awh & @serences.bsky.social)

www.biorxiv.org/content/10.1...

This is an incredible development for all types of conditions. Including neuromodulation for depression (like TMS) which is currently largely limited to the brain's surface whereas some of the most relevant bits of the mood network lie deep in the brain (subcallosal cingulate, insula ...).

Mining the neuroimaging literature New tools for literature mining, such as automated analysis of the research literature, are accessible, scalable, and reliable.

Our latest paper outlining our ecosystem of tools for mining the neuroimaging literature, is finally officially published in eLife! doi.org/10.7554/eLif...

Complementary regulation of memory flexibility and stabilization by dentate gyrus granule cells and mossy cells Accurate memory formation requires hippocampal spatial representations to balance stability, for later recall, with flexibility, to incorporate new information. The dentate gyrus (DG) is essential to ...

www.biorxiv.org/content/10.1...

So happy to share our paper on the role of the hippocampus as a mismatch detector:
doi.org/10.1073/pnas...

We show that the hippocampus detects mismatches between ongoing experiences and episodic memories but not generalised schematic knowledge.

See 🧵for how we got here:
#neuroskyence #PsychSciSky

Science research gets more engagement on Bluesky than X, study finds Bluesky posts referencing scholarly articles ‘find substantially higher levels of interaction’ than on Elon Musk’s platform

That's why I'm here...

www.theguardian.com/technology/2...

shout out to the journal of the society (That I am a member of) that I review a bunch for charging 5200 for open access via springer nature. was a fun ride, but I am done.

Repeated Viewing of a Narrative Movie Changes Event Timescales in The Brain Many experiences occur repeatedly throughout our lives: we might watch the same movie more than once and listen to the same song on repeat. How does the brain modify its representations of events when...

How do the brain’s event representations change as we gain familiarity with an experience?

Brain regions’ representations can become coarser or finer as event familiarity increases. Fine-tuning predicts memory recall.

Excited to share this work with Narjes Al-Zahli & @chrisbaldassano.bsky.social!

Our target discussion article out in Cognitive Neuroscience! It will be followed by peer commentary and our responses. If you would like to write a commentary, please reach out to the journal! 1/18 www.tandfonline.com/doi/full/10.... @cibaker.bsky.social @susanwardle.bsky.social

Adaptive learning is coordinated across behaviour, time and neurobiology (from synapses and dendrites, to astrocytes and the systems level).

If you’ve ever wondered how noradrenaline helps shape these multiscale learning processes, you might like this: www.cell.com/trends/cogni...

Hey #memory folks, check out this new preprint by @joschadutli.bsky.social , @koberauer.bsky.social, and @leabartsch.bsky.social showing that elaboration benefits are likely driven by aiding in establishing efficient retrieval cues.

Isolated theta waves originating from the midline thalamus trigger memory reactivation during NREM sleep in mice Nature Communications - The neural mechanisms of memory consolidation during sleep are poorly understood. Here the authors show that isolated theta waves from nucleus reuniens initiate neural...

During sleep, reuniens theta synchronizes with MEC provoking memory reactivation.

rdcu.be/eCMfl

YouTube video by Frank Reynolds (Best of Its Always Sunny in Philadelphia) IASIP - Charlie's Dreambook

This was led by Heather Bruett. I'll end with my favorite examples of conceptual combination from Always Sunny: www.youtube.com/watch?v=LV0V...

So, combining concepts in new ways draws on semantic hubs (ATL, ANG) and perceptual regions (visual cortex), with variation based on the type of combination (relational vs. attributional) and how constrained its meaning is

Interestingly, the size of this shift in visual cortex was predicted by activity during the combining process itself - in two semantic hubs: Left anterior temporal lobe (ATL) and right angular gyrus (ANG)

This shift after combining wasn’t due to sensory input (participants only saw written words). Instead, it likely reflects the consequences of retrieving and manipulating different features of the conceptual space

To give the headline, we found that combining weakly-constrained concepts (like 'canary bus', which can mean a lot of different things) produced larger shifts in the multivariate activity patterns of the underlying concepts, compared to strongly-constrained concepts (like 'book string')