Marcelo Mattar

@marcelomattar.bsky.social

Assistant professor at NYU.

Looking to work with a postdoc. Prior experience with fMRI and computational modeling required, interest in psychiatry desired. Fellowship provides three years salary plus independent travel/equipment funds. Send CV and 2-3 manuscripts (preprints OK).

During sleep, neurons in the hippocampus 'replay' past activity patterns. This is thought to underlie memory consolidation 🧠 After a busy day, how does the brain sort out what is worth replaying? 🤔 Check out this preprint 📃 from Tirole, Duvelle and Bendor for answers! doi.org/10.64898/202...

Time, but not reward, shapes replay-based episodic prioritization

Why are some experiences remembered better than others? Leading theories propose that hippocampal replay prioritizes memories for consolidation according to their expected future value. We recorded hi...

doi.org

New preprint! We show low arousal states promote hippocampal ripple genesis in sleep and wake. This bridges rodent work, where ripples predominate during sleep, with human studies reporting ripples during active behavior, identifying low arousal as a common mechanism www.biorxiv.org/content/10.6...

Arousal state modulates human hippocampal ripples

Hippocampal ripples are transient, high-frequency oscillations linked to memory replay and consolidation. Ripples are well-characterized in rodents to occur during periods of behavioral inactivity (i....

biorxiv.org

1/ 🚨 New preprint: "Closing the Loop to Discover Psychological Theories with an Automated Cognitive Scientist" Introducing AutoCog 🤖 — a fully autonomous AI system that runs the entire scientific discovery cycle in cognitive science to surface novel theories of human behavior 🧵

Only one week left until our PhD application deadline @mpicybernetics.bsky.social. If you’re interested in the intersection of RL, RNNs, and analyses of neural & behavioral data from novel, cross-species foraging experiments, make sure to submit your application by June 15! #NeuroJobs More info👇

Roxana Zeraati@roxana-zeraati.bsky.social · 3mo ago

If these research directions resonate with you and you're interested in joining our team, we now have 2 open PhD positions! More information about the positions: nextcloud.tuebingen.mpg.de/index.php/s/... More information about our research: www.kyb.tuebingen.mpg.de/906930/natur... #NeuroJobs

An illustration of different animals engaging in natural decision-making.

New preprint w/ @fredcallaway.bsky.social! How does the brain decide which computations to run? We combine rational meta-reasoning with a meta-learning algorithm to build a recurrent network that learns to select computations. www.biorxiv.org/content/10.6...

Learning to select computations in recurrent neural circuits

Two hallmarks of biological computation are its flexibility and efficiency. These features are often attributed to cognitive control processes that balance external utility against computational cost. However, how the brain could implement such adaptive control remains unknown. Here, we provide one possible answer by combining the computational theory of rational meta-reasoning with a meta-learning algorithm recently proposed as a model of prefrontal cortex. This yields a recurrent neural network model that learns to select computations. In simple choice tasks, the model approximates the algorithms and representations of optimal symbolic models and reproduces neural dynamics observed in macaque orbitofrontal cortex. In multi-step planning tasks, the model replicates key behavioral signatures of human planning strategies and captures human neural dynamics associated with step-by-step mental simulation. Our framework unifies meta-reasoning and meta-learning by showing that learning to reason can be understood as learning to learn from information generated by one’s own cognitive operations, providing a mechanistic account of how adaptive control of thought can be implemented in neural systems. ### Competing Interest Statement The authors have declared no competing interest.

biorxiv.org

Super proud to have contributed to this amazing team effort, led by @sreejan.bsky.social and @botoscsabi.bsky.social! We asked: Which AI models learn to play video games like humans, comparing both behavior and internal representations. The answer surprised us! Check out our paper and post below

Botos Csabi@botoscsabi.bsky.social · 3mo ago

Jeee 🐦‍⬛ I am very proud of our joint effort with @sreejan.bsky.social on the project "Reason to Play" LRMs show human-like rule discovery, and their hidden states predict human brain activity during gameplay 10x better than previous methods Interactive demo + paper: botcs.github.io/reason-to-pl...

Jeee 🐦‍⬛ I am very proud of our joint effort with @sreejan.bsky.social on the project "Reason to Play" LRMs show human-like rule discovery, and their hidden states predict human brain activity during gameplay 10x better than previous methods Interactive demo + paper: botcs.github.io/reason-to-pl...

Reason to Play - Behavioral and Brain Alignment

32 fMRI-scanned humans and 8 frontier open weight LLMs play ARC-AGI like games with no rules given. The reasoning models match the human learning trajectories and their hidden states predict human bra...

botcs.github.io

New Annual Review with @nathanieldaw.bsky.social: “Planning in the Brain: It's Not What You Think It Is.” We argue that the brain's 'planning' machinery is mostly used for learning from simulated experience, and that thinking prospectively at decision time is just one special case of this process.

Planning in the Brain: It's Not What You Think It Is

The neuroscience of planning has long been analogized to search algorithms in artificial intelligence (AI), which simulate future actions to guide immediate choices. We argue that advances in both neu...

annualreviews.org

News! I've joined the Astera Institute to lead its neuroscience based AGI research. Backed by $1B+ commitment over the coming decade, my team will explore novel, brain-inspired architectures and algos toward safe, efficient human-like AGI, working alongside Doris Tsao. 1/ astera.org/dileep-georg...

Dileep George joins Astera to lead its neuro-inspired AGI effort

Dileep George is joining Astera as Head of AI, leading our AGI research division. Working alongside our Chief Scientist Doris Tsao, he and the team will explore novel, brain-inspired computational arc...

astera.org