de Gee lab

Acetylcholine reflects uncertainty during hidden state inference To act adaptively, animals must infer features of the environment that cannot be observed directly, such as which option is currently rewarding, or which context they are in. These internal estimates,...

Congrats to Ella for her new paper! She asked a really interesting question about how the brain represents uncertainty during hidden state inference, and in a lovely crossover with theoretical work, she shows that in mice, acetylcholine dynamics play a crucial role. www.biorxiv.org/content/10.1...

Sensory expectations shape neural population dynamics in motor circuits Nature - Experiments with human volunteers and macaques show that expectations produced by probabilistic cueing of future sensory inputs shape motor circuit dynamics in order to increase the...

Thrilled that our paper is out today in Nature!
www.nature.com/articles/s4...

Regularization, Action, and Attractors in the Dynamical “Bayesian” Brain Abstract. The idea that the brain is a probabilistic (Bayesian) inference machine, continuously trying to figure out the hidden causes of its inputs, has become very influential in cognitive (neuro)sc...

🧠 Regularization, Action, and Attractors in the Dynamical “Bayesian” Brain

direct.mit.edu/jocn/article...

(still uncorrected proofs, but they should post the corrected one soon--also OA is forthcoming, for now PDF at brainandexperience.org/pdf/10.1162-...)

Contents of visual predictions oscillate at alpha frequencies Predictions of future events have a major impact on how we process sensory signals. However, it remains unclear how the brain keeps predictions online in anticipation of future inputs. Here, we combin...

@dotproduct.bsky.social's first first author paper is finally out in @sfnjournals.bsky.social! Her findings show that content-specific predictions fluctuate with alpha frequencies, suggesting a more specific role for alpha oscillations than we may have thought. With @jhaarsma.bsky.social. 🧠🟦 🧠🤖

Hierarchical interactions between sensory cortices defy predictive coding Perceptual experience depends on recurrent interactions between lower and higher cortices. One theory, predictive coding, posits that feedback from higher to lower brain regions decreases neuronal activity predicted by higher-level representations. Despite the widespread adoption of predictive coding in neuroscience, the correspondence to neurophysiological findings in sensory cortices remains elusive. Here, we review how the canonical patterns of intra- and inter-cortical interactions that occur during perception and shifts of attention deviate from those predicted by predictive coding. We argue that these circuit interactions are better captured by alternative theories, which we summarize under the umbrella term BELIEF. We review how BELIEF theories account for the inter-areal interactions during attentive perception.

Online Now: Hierarchical interactions between sensory cortices defy predictive coding

Decoding with multivariate pattern analysis is superior for optically pumped magnetometer-based magnetoencephalography compared to superconducting quantum interference device-based systems Background: Multivariate pattern analysis (MVPA) has become an increasingly important method for decoding distributed brain activity from neural electrophysiological recordings by leveraging both temp...

Decoding performance (MVPA) better for OPM-MEG than SQUID-MEG 😎. The improved spatial specificity of OPM-MEG due to the reduced brain-sensor distance is key. And more sensors (beyond 40) don't improve decoding.
Preprint from our recent @thechbh.bsky.social study: www.biorxiv.org/content/10.1...

Motivation as Neural Context for Adaptive Learning and Memory Formation Our memories shape our perception of the world and guide adaptive behavior. Rather than a veridical record of experiences, memory is selective. An accumulating body of work suggests that motivational ...

How does motivation shape learning and memory? In a new review w @ralisonadcock.bsky.social, we propose that under different motivational ‘moods', neuromodulators set distinct neural contexts to determine information processing and memory formation.
doi.org/10.1146/annu...
#psychscisky #neuroskyence

The brain is incredibly densely connected. Human cerebral cortex may have as many as *one trillion* connections.

Most of those cortical connections are recurrent, inside each area. What do they do?

New paper from me in Annual Reviews: 🧪 🧠📈 1/

www.annualreviews.org/content/jour...

Pre- and post-decision signals of certainty in changing minds In a recent study, Goueytes and colleagues combined computational modeling with intracranial recordings to dissect the neural basis of confidence and changes of mind. They reveal a temporally organize...

Our spotlight article on Goueytes et al. (2025) study is now online at Trends in Neurosciences: "Pre- and post-decision signals of certainty in changing minds", by P. Barttfeld, @ncomay.bsky.social, I. Embon & @guillermosolovey.bsky.social www.cell.com/trends/neuro...

A parabrachial hub for need-state control of enduring pain - Nature Activity in a set of parabranchial neurons in the mouse brain is increased during chronic pain, predicts coping behaviour, and can be modulated by circuits activated by survival threats.

Finally out: our recent work with Nick Betley is a view into how the brain reshapes its behavior in the face of competing survival needs- and also a potential angle on treatment targets for enduring pain.

A brief rundown...

www.nature.com/articles/s41...

Neural coding of choice and outcome are modulated by uncertainty in orbitofrontal but not secondary motor cortex - Nature Communications Neural mechanisms underlying flexible learning and decision-making are not fully understood. Using single-cell calcium imaging, authors here found that neurons in orbitofrontal and secondary motor cortex exhibit complementary roles in reward learning, with neurons in the former exerting a sustained role in conditions of uncertainty.

🎇 Excited to finally share JL Romero Sosa’s publication! Results are from single-cell imaging in different subregions of rat frontal cortex during ✨de novo learning. Spoiler: everything is not everywhere all at once www.nature.com/articles/s41...

Principles for proper peer review

For all the knucklehead reviewers out there.
Principles for proper peer review - Earl K. Miller
jocnf.pubpub.org/pub/qag76ip8...
#neuroscience

Our #sEEG study is now published in Nature Communications: rdcu.be/eIkoG! 🧠
Key finding: We discovered neural evidence accumulation for visual perception that's independent of report preparation—recorded from >3000 channels across 3 experiments!
#Neuroscience #Consciousness #OpenAccess

Curious about the human ability to extract regularities from sensory input (i.e., “statistical learning”) and individual differences therein? #CognitiveScience #Learning

Our #Consensus paper presents the collective insights of 27 researchers worldwide 🌎 💬 🌍 💬 🌏 💬:
🔗 doi.org/10.31234/osf...

With 2 postdocs moving on to faculty positions🥳, we're looking to hire someone new. If you're interested in norepinephrine and neural circuits, please apply! tinyurl.com/42bfe24k

The Hippocampus Rapidly Integrates Sequence Representations During Novel Multistep Predictions Memories for temporally extended sequences can be used adaptively to predict future events on multiple timescales, a function that relies on the hippocampus. For such predictions to be useful, they sh...

How do we update our predictions when our environment changes?

The hippocampus rapidly integrates previously distinct sequences to support updated predictions.

Proud of this work with Hannah Tarder-Stoll & @chrisbaldassano.bsky.social!

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

We are hiring for several research positions for this grant, starting early next year. Please reach out if you're interested!
More details on the jobs here: devcompsy.org/wp-content/u...

Two flagship papers from the International Brain Laboratory, now out in ‪@Nature.com‬:
🧠 Brain-wide map of neural activity during complex behaviour: doi.org/10.1038/s41586-025-09235-0
🧠 Brain-wide representations of prior information in mouse decision-making: doi.org/10.1038/s41586-025-09226-1 +

Catecholamines like dopamine and norepinephrine are key in processing info and making decisions. Our study shows these neuromodulators reduce the impact of past choices on current decisions, leading to less biased perceptual judgments. Exciting implications for brain science! #Neuroscience

🧠✨ Exciting new research alert! ✨🧠

Did you know that catecholamines can reduce choice history biases in perceptual decision-making? 🧐🔍

Paper: journals.plos.org/plosbiology/...

With @donnerlab.bsky.social and @swammerdamuva.bsky.social

Ok, but the ones I linked here are also near-threshold auditory detection. Curious to see your results at some point. :-)

Some recent examples of phasic and tonic variations in pupil size predicting choice behavior about auditory stimuli:
- https://pubmed.ncbi.nlm.nih.gov/26074005/
- https://pubmed.ncbi.nlm.nih.gov/32543372/
- https://pubmed.ncbi.nlm.nih.gov/39151432/
- https://pubmed.ncbi.nlm.nih.gov/38277436/

Tonic dopamine and biases in value learning linked through a biologically inspired reinforcement learning model Nature Communications - Accurate future predictions are essential for guiding behavior, and disruptions in this process are associated with psychiatric disorders. Here the authors show that changes...

My first paper with @naoshigeuchida.bsky.social is finally out in @natcomms.nature.com ! rdcu.be/eACGf

TL;DR: asymmetric learning rates can be induced by shifts in tonic dopamine giving rise to pessimistic/optimistic biases in agents or animals undergoing reinforcement learning .

Its a new term and a lot of us are preparing their lectures. I am a huge fan of online ways of teaching. And my student Joey Rudoler @jrudoler.bsky.social made a great online stats course. Shiny app and all. Modern take on stats. Thought some of you may appreciate.

Are you at @assc28.bsky.social #ASSC28? On Wednesday I will present a poster on the causal relationship between choice history biases and catecholamines (noradrenaline / dopamine). With @donnerlab.bsky.social et al.

Are you at @assc28.bsky.social #ASSC28? Later, @stijnnuiten.bsky.social will present exciting cross-species results on the interaction between latent behavioral states, pupil-linked arousal, and V1 activity. Great collab w/ @psterzer.bsky.social @svangaal.bsky.social @pennartz.bsky.social et al.

Discovering cognitive strategies with tiny recurrent neural networks - Nature Modelling biological decision-making with tiny recurrent neural networks enables more accurate predictions of animal choices than classical cognitive models and offers insights into the underlying cog...

Thrilled to see our TinyRNN paper in @nature! We show how tiny RNNs predict choices of individual subjects accurately while staying fully interpretable. This approach can transform how we model cognitive processes in both healthy and disordered decisions. doi.org/10.1038/s415...

Confirmation bias through selective readout of information encoded in human parietal cortex Nature Communications - People often discard incoming information when it contradicts their pre-existing beliefs about the world. Here, the authors show that this discarded information is precisely...

1/ New paper by Hame Park, (@AraziAyelet), Bharath Talluri, Marco Celotto, Stefano Panzeri, Alan Stocker & Tobias Donner published in Nature Communications – “Confirmation Bias through Selective Readout of Information Encoded in Human Parietal Cortex”: rdcu.be/etlR7. Here is a summary:

A progressive ratio task with costly resets reveals adaptive effort-delay tradeoffs The Progressive Ratio (PR) schedule is a popular test for measuring the motivational value of a reinforcer, in which subjects must exert an increasing amount of work to obtain each successive reward. ...

This is a super cool way of studying learning, effort, and foraging www.biorxiv.org/content/10.1...

Abstract rule learning promotes cognitive flexibility in complex environments across species - Nature Communications Whether neurocomputational mechanisms that speed up human learning in changing environments also exist in other species remains unclear. Here, the authors show that both rats and humans sequentially t...

Abstract rule learning promotes cognitive flexibility in complex environments across species
www.nature.com/articles/s41...
#neuroscience