Very excited to attend #CCN2026 this week and to present various projects from my lab! Here's a list of our posters and talks in case you'd like to see what we've been up to.
Jonathan Nicholas
@jonathannicholas.bsky.social
postdoc at nyu | (episodic) memory and decision making | jonathanicholas.github.io
So thrilled to be joining the Psychology Department at @columbiauniversity.bsky.social as an assistant prof next summer! I'll be recruiting for PhD/postdoc to start in Autumn 2027, so if you're interested in using computational approaches to studying human cognition please get in touch!
(New results!) Human inference behavior varies widely across individuals and tasks. Using the information bottleneck framework, we show that two distinct axes capture a substantial amount of individual variability across two classic inference tasks. Thread below 1/
An information-bottleneck theory of suboptimal human inference
Human inference is often suboptimal in ways that vary across individuals and tasks. We propose that this variability reflects information processing limits and develop a task-general application of th...
biorxiv.org
#JNeurosci: Findings from van Geen et al. support an integrated view of decision-making where mnemonic and value-based systems interact even in basic learning contexts, and highlight age-related disruptions in the transfer of info across brain regions. https://doi.org/10.1523/JNEUROSCI.1459-25.2026
Our paper is out in @natmachintell.nature.com! We trained multiple RNNs to perform free recall. The best-performing ones learned a strategy akin to the memory palace technique. See thread below for more info. www.nature.com/articles/s42...
A neural network model of free recall learns multiple memory strategies - Nature Machine Intelligence
Li et al. show that recurrent neural networks optimized for free recall discover diverse, human-like memory strategies beyond classical temporal context models, with top models using an index-based me...
nature.com
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).
New paper out in @sfnjournals.bsky.social ! Precise memory is an often under-appreciated determinant of accurate choice - on a foraging trip, I really need to remember if the poisonous mushroom was pink or white before I choose one for dinner. How does the brain do this? doi.org/10.1523/JNEU...
The precision of hippocampal representations predicts incremental value-learning across the adult lifespan
Correctly assigning value to different options and leveraging this information to guide choice is a cornerstone of adaptive decision-making. Reinforcement learning (RL) has provided a computational fr...
jneurosci.org
We make flexible choices in new situations by knitting together information from separate relevant memories. But what governs which memories are retrieved and when? In a new preprint, we captured how people build decision variables from different memories by tracking their gaze on a blank screen.
Flexible decisions arise from resource-rational memory sampling
Flexible decision making depends on retrieving and recombining memories. Yet because this process unfolds covertly, its governing principles remain unknown. Here we use gaze reinstatement to uncover t...
biorxiv.org
Pleased to share that this work is now published in TMLR! openreview.net/forum?id=RuW...
Latent learning: episodic memory complements parametric learning by...
When do machine learning systems fail to generalize, and what mechanisms could improve their generalization? Here, we draw inspiration from cognitive science to argue that one weakness of...
openreview.net
Andrew Lampinen@lampinen.bsky.social · 11mo agoWhy does AI sometimes fail to generalize, and what might help? In a new paper (arxiv.org/abs/2509.16189), we highlight the latent learning gap — which unifies findings from language modeling to agent navigation — and suggest that episodic memory complements parametric learning to bridge it. Thread:
Nature research paper: Neural representation of action symbols in primate frontal cortex go.nature.com/4v1FDED
Neural representation of action symbols in primate frontal cortex - Nature
A drawing-like task designed to study compositional generalization identifies a specific neural population in the ventral premotor cortex in primates that encodes action symbols.
go.nature.com
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
👋 Happy to see this paper published in PNAS www.pnas.org/doi/10.1073/pnas.2529176123 Asking: is curiosity a homeostatic drive, or a policy learned through reinforcement? How can we tell, and why does it matter? 🧵👇 With Jane Mok, @chrisbaldassano.bsky.social, Caroline Marvin, and Daphna Shohamy 🙏
Learning reinforces curiosity for related information | PNAS
Human curiosity is dynamic, however the principles governing its fluctuations remain debated. Here, we test two competing hypotheses about how past...
pnas.org
Yaniv Abir@yanivabir.bsky.social · last yr.What drives human curiosity? Is it a need to balance stimulation — or something we learn over time? In our 🚨 new preprint, we show that learning reinforces curiosity, especially for related content. osf.io/9bw6j_v2 w/ Jane Mok, @chrisbaldassano.bsky.social , Caroline Marvin, Daphna Shohamy 🧵👇
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
This is finally out as Version of Record 🎉 Read to find out how and when humans strategically switch between approaching and avoiding uncertainty with Michael Shadlen and Daphna Shohamy elifesciences.org/articles/94231 🧵:
Human exploration strategically balances approaching and avoiding uncertainty
Strategic avoidance of uncertainty emerges under high cognitive demands, enabling faster decisions without impairing learning.
elifesciences.org
I am totally pumped about this new work . "Task-trained RNNs" are a powerful and influential framework in neuroscience, but have lacked a firm theoretical footing. This work provides one, and makes direct contact with the classical theory of random RNNs: www.biorxiv.org/content/10.6...
I am excited to share my first paper, showing that episodic memory formation is theta rhythmic, is now published in Nature Human Behavior! Check it out here: rdcu.be/e6pzS. Thanks to my PI, Katherine Duncan, and to my collaborators for their support on this journey! Stay tuned for iEEG follow up 🧠
Episodic memory encoding fluctuates at a theta rhythm of 3–10 Hz
Nature Human Behaviour - Biba et al. show that episodic memory encoding fluctuates at a theta rhythm of 3–10 Hz.
rdcu.be
📢New paper out today in @cognitionjournal.bsky.social! Does the value of an unchosen option — inferred through counterfactual reasoning — spread to related items in memory, similar to how the value of a chosen option — acquired through direct experience — does? In short, yes!
The inferred value of unchosen options spreads to related items in memory
Counterfactual thinking — considering what could have come of choosing the other path — can facilitate inference. Previous studies have demonstrated t…
sciencedirect.com
I'm excited to announce that I had my first (co-authored) book published today! "The Rational Use of Cognitive Resources" with Falk Lieder and Tom Griffiths (@cocoscilab.bsky.social ). You can read it for free! (see thread)
Our experiences have countless details, and it can be hard to know which matter. How can we behave effectively in the future when, right now, we don't know what we'll need? Out today in @nathumbehav.nature.com , @marcelomattar.bsky.social and I find that people solve this by using episodic memory.
Episodic memory facilitates flexible decision-making via access to detailed events - Nature Human Behaviour
Nicholas and Mattar found that people use episodic memory to make decisions when it is unclear what will be needed in the future. These findings reveal how the rich representational capacity of episod...
nature.com
Last term I tried an experiment: I walked into my Tech and Design Ethics class, admitted that I had *no idea* what to do about ChatGPT - so I would let them figure it out. As in: their first project was to decide and write the ChatGPT policy for the class. Here's what happened:
🚨New Paper Alert!🚨 Now out in Emotion! The Memory Palace Architect: Effect of Valence on Loci-Dependent Recall Performance. We ask a simple question: does the emotional tone of a memory palace matter for recall? Turns out: yes—and negative palaces work best.
APA PsycNet
doi.org
When does new learning interfere with existing knowledge in people and ANNs? Great to have this out today in @nathumbehav.nature.com Work with @summerfieldlab.bsky.social, @tsonj.bsky.social, Lukas Braun and Jan Grohn www.nature.com/articles/s41...
Humans and neural networks show similar patterns of transfer and interference during continual learning - Nature Human Behaviour
When learning new tasks, both humans and artificial neural networks face a trade-off between reusing prior knowledge to learn faster and avoiding the disruption of earlier learning. This study shows t...
nature.com
Eleanor Holton@eleanor-holton.bsky.social · last yr.New preprint out with @summerfieldlab.bsky.social! When does new learning interfere with existing knowledge? We compare continual learning in humans and artificial neural networks, revealing similar patterns of transfer & catastrophic interference (1/8) osf.io/preprints/ps...
I'm recruiting PhD students for my lab at Northwestern! I'm reviewing applications for the Department of Psychology for the Cognitive Affective Neuroscience and Clinical areas, due 12/1. 🧠 Come join the CATS Lab: nucatslab.com Learn about our latest research: iamh.northwestern.edu/research/res...
CATS Lab
Child & Adolescent Translational Science Lab at Northwestern University
nucatslab.com
I’m excited to share my recent preprint on a neural network model of free recall that learns multiple memory strategies including the memory palace! www.biorxiv.org/content/10.1...
New paper out in cognition with @arikahn.bsky.social, @nathanieldaw.bsky.social, Cate Hartley, and @katenuss.bsky.social !! We show that children 👶 use predictive representations (e.g. SR) to guide their choices, providing an account of how they can make flexible choices in a changing world
Children leverage predictive representations for flexible, value-guided choice
By harnessing a mental model of how the world works, learners can make flexible choices in changing environments. However, while children and adolesce…
sciencedirect.com
Why does AI sometimes fail to generalize, and what might help? In a new paper (arxiv.org/abs/2509.16189), we highlight the latent learning gap — which unifies findings from language modeling to agent navigation — and suggest that episodic memory complements parametric learning to bridge it. Thread:
Latent learning: episodic memory complements parametric learning by enabling flexible reuse of experiences
When do machine learning systems fail to generalize, and what mechanisms could improve their generalization? Here, we draw inspiration from cognitive science to argue that one weakness of machine lear...
arxiv.org
I’m super excited to finally put my recent work with @behrenstimb.bsky.social on bioRxiv, where we develop a new mechanistic theory of how PFC structures adaptive behaviour using attractor dynamics in space and time! www.biorxiv.org/content/10.1...
New preprint from the lab! 🧠 Led by Juliana Trach, w/ Sophia Ou Using fMRI, we discovered evidence for time-sensitive reward prediction errors (RPEs) in the human cerebellum. Builds on, and extends, recent work in both rodents and NHPs
bioRxiv Neuroscience@biorxiv-neursci.bsky.social · 11mo agoThe human cerebellum encodes temporally sensitive reinforcement learning signals https://www.biorxiv.org/content/10.1101/2025.09.06.674658v1
I'm excited to share that my new postdoctoral position is going so well that I submitted a new paper at the end of my first week! www.biorxiv.org/content/10.1... A thread below
Sensory Compression as a Unifying Principle for Action Chunking and Time Coding in the Brain
The brain seamlessly transforms sensory information into precisely-timed movements, enabling us to type familiar words, play musical instruments, or perform complex motor routines with millisecond pre...
biorxiv.org
Successful prediction of the future enhances encoding of the present. I am so delighted that this work found a wonderful home at Open Mind. The peer review journey was a rollercoaster but it *greatly* improved the paper. direct.mit.edu/opmi/article...
Successful Prediction Is Associated With Enhanced Encoding
Abstract. Forming memories requires a focus on the external world; retrieving memories requires attention to our internal world. Computational models propose that the hippocampus resolves the tension ...
direct.mit.edu
Mariam Aly@mariamaly.bsky.social · last yr.When you successfully anticipate future events, what happens to your ability to encode the present? 🤔 Successful prediction increases the likelihood of successful encoding. We speculate about how switching between distinct encoding & prediction states can produce this effect. osf.io/preprints/ps...