Philipp Paulus

Check out our latest preprint! "It’s about time: Specific and unspecific effects of episodic future thinking on farsighted decisions" with @rolandbenoit.bsky.social - osf.io/preprints/ps... 1/9

In this new preprint from our lab, we share exciting new findings on how „Sleep resolves competition between explicit and implicit memory systems!“ 🧠 💤 🚨

Kleespies, Paulus, et al.
@katjakleespies.bsky.social @philipppaulus.bsky.social

For a brief walkthrough, I refer you to Katja‘s post below!

Incorporation of complex narratives into dreaming Reactivation of waking neuronal activity during sleep holds a functional role in memory consolidation. Reprocessing of daytime memory in dreams might aid later memory performance in a similar way. Num...

New preprint from our lab on memory incorporation into dreams! 🧠 💭 💤

Palmieri et al. Incorporation of complex narratives into dreaming

doi.org/10.1101/2025...

Die amtierende Rot/Grüne BReg kann bis zur Wahl von Merz als Kanzler einen Antrag auf Verbot der AFD stellen. Es ist die letzte Chance, einen solchen Antrag ohne Mitwirkung der Union zu stellen. Damit ist es die letzte Chance, das ein Verbotsantrag überhaupt gestellt wird.

The time is now.

PLEASE SHARE: apply to my postdoc in Osaka. Comp cogneuro of learning, control, & concept representation. fMRI, cognitive models & deep nets.

Initial deadline Oct 18. The deadline will be extended once so don't worry if u need more time.

#neuroskyence #psychscisky #compneurosky

I will be recruiting 💫two PhD students💫 for my new lab! (computational learning & memory applied to individual & interactive behavior: rouhanilab.com).

Feel free to e-mail if interested and catch me at SfN!
(poster 06 at 1 PM on Wed 10/09)

Thrilled to announce that I will be joining CiNet (Center for Information and Neural Networks; cinet.jp/english/) in Osaka Japan to start my lab in April/May 2025! We have postdoc positions (1 open NOW) & PhDs (Osaka U). Details👇, pls repost! Short 🧵 1/ #neuroskyence #psychscisky #compneurosky

Job alert 📢
2 fantastic #postdocpositions in CRC/TRR393 on "Trajectories of Affective Disorders" at
Uni Marburg

1) stellenangebote.uni-marburg.de/jobposting/8...
2) stellenangebote.uni-marburg.de/jobposting/b...

@dgps.bsky.social @tudresden.bsky.social @unimuenster.bsky.social

Job alert 🎺
PhD positions on #socialcognition #emotionregulation #stress #fmri & #depression?
It's a great collaborative project on "Trajectories of Affective Disorders" @tudresden.bsky.social Marburg & Münster @katfoerster.bsky.social
@dgps.bsky.social
tu-dresden.de/vacancy/11497

Pretty slides 😍 What do those colored dotclouds represent 🤔

New paper out in PNAS!!

"Collaborative imagination synchronizes representations of the future and fosters social connection in the present"

in collaboration with Zoë Fowler, Daniela Palombo, and Brendan O’Connor

doi.org/10.1073/pnas....

The individual determinants of morning dream recall bioRxiv - the preprint server for biology, operated by Cold Spring Harbor Laboratory, a research and educational institution

New preprint from the Lab: "The individual determinants of morning dream recall". We investigated the factors that determine within- and between-subject differences in morning dream recall. https://doi.org/10.1101/2024.05.23.595531

Indeed! 📝

Our latest analyses revealed that the spatial distribution of single, simple, and easily interpretable time-series features, previously not considered in aging research, were highly predictive of individual age.

Please retweet! I am excited to share that I am looking for motivated postdocs who want to come and work with me at NYU (please apply here: apply.interfolio.com/145544) (1/3)

Wir suchen Verstärkung für unsere Hochschulambulanz für Psychotherapie. Spannende Aufgabe an der Schnittstelle von Psychotherapie, Lehre und Forschung für eine:n

Psychologische:r Psychotherapeut:in

www.psychjob.eu/de/job/psych...

We are looking for an MR physicist for our Neuroimaging Center at TU Dresden.

Please help us spread the word. Thx

www.verw.tu-dresden.de/StellAus/dow...

Ein roter Wecker vor gelbem Hintergrund.

Die Uhr tickt! ⏰

Noch bis morgen Abend 23:59 Uhr könnt ihr eure Texte und Infografiken für den KlarText-Preis 2024 einreichen. Also die letzten Korrekturen einarbeiten und ab die Post. Wir freuen uns auf eure Bewerbungen!

#WissKomm

Its a great opportunity and Philipp is phenomenal

An inductive bias for slowly changing features in human reinforcement learning Identifying goal-relevant features in novel environments is a central challenge for efficient behaviour. We asked whether humans address this challenge by relying on prior knowledge about common properties of reward-predicting features. One such property is the rate of change of features, given that behaviourally relevant processes tend to change on a slower timescale than noise. Hence, we asked whether humans are biased to learn more when task-relevant features are slow rather than fast. To test this idea, 100 human participants were asked to learn the rewards of two-dimensional bandits when either a slowly or quickly changing feature of the bandit predicted reward. Participants accrued more reward and achieved better generalisation to unseen feature values when a bandit’s relevant feature changed slowly, and its irrelevant feature quickly, as compared to the opposite. Participants were also more likely to incorrectly base their choices on the irrelevant feature when it changed slowly versus quickly. These effects were stronger when participants experienced the feature speed before learning about rewards. Modelling this behaviour with a set of four function approximation Kalman filter models that embodied alternative hypotheses about how feature speed could affect learning revealed that participants had a higher learning rate for the slow feature, and adjusted their learning to both the relevance and the speed of feature changes. The larger the improvement in participants’ performance for slow compared to fast bandits, the more strongly they adjusted their learning rates. These results provide evidence that human reinforcement learning favours slower features, suggesting a bias in how humans approach reward learning. Author Summary Learning experiments in the laboratory are often assumed to exist in a vacuum, where participants solve a given task independently of how they learn in more natural circumstances. But humans and other animals are in fact well known to “meta learn”, i.e. to leverage generalisable assumptions about how to learn from other experiences. Taking inspiration from a well-known machine learning technique known as slow feature analysis, we investigated one specific instance of such an assumption in learning: the possibility that humans tend to focus on slowly rather than quickly changing features when learning about rewards. To test this, we developed a task where participants had to learn the value of stimuli composed of two features. Participants indeed learned better from a slowly rather than quickly changing feature that predicted reward and were more distracted by the reward-irrelevant feature when it changed slowly. Computational modelling of participant behaviour indicated that participants had a higher learning rate for slowly changing features from the outset. Hence, our results support the idea that human reinforcement learning reflects a priori assumptions about the reward structure in natural environments. ### Competing Interest Statement The authors have declared no competing interest.

In a world full of noise, how do we decide what's important? Our research reveals that humans leverage a key insight: relevant signals change slowly, but noise fluctuates rapidly.
Excited to share the first project of my PhD!
🧪 🧠📈 🧠💻 #PsychSciSky (1/8)

Stellenangebote Bewerbermanagement, Max-Planck-Institutes für Kognitions- und Neurowissenschaften, MPI CBS, Stellenangebote

Dear colleagues, I am advertising two fully funded PhD positions in my new group. Topics can cover grid cells, retrosplenial cortex, head direction, subiculum and boundary coding + cog maps more generally. Please direct potential candidates to the ads: www.cbs.mpg.de/stellenmarkt...

Jobausschreibung für eine Medizinische Hilfskraft an der MSH Medical School Hamburg

Stellenausschreibung (German speakers only): Kolleg:innen suchen eine medizinische Hilfskraft 💉 zur Unterstützung eines super spannenden Projekts an Zwillingen um die Entstehung von Zwangsstörungen besser zu verstehen. Ist ein tolles Projekt und ein super Team in Hamburg. Gern teilen 🙂🙏

We are looking for a new colleague - please share 👇

Full #professorship in general #psychology at TU Dresden

It's a great psych department with fantastic resources and colleagues. Get in touch w/ questions
@dgps.bsky.social @ohbmtrainees.bsky.social @s4sn.bsky.social
tu-dresden.de/vacancy/11075

#Dresden #noAfD

Join our ERC project "INTERACT - The interplay of neural networks enabling social interaction" as PhD student or PostDoc. DM me with questions.
- Thanks for sharing -
@dgps.bsky.social @ohbmtrainees.bsky.social @s4sn.bsky.social @sansmeeting.bsky.social @tudresden.bsky.social
tud.link/uim3

So happy, our new paper is accepted! 🥳 Led by bsky-less Kim Fricke, our first "fully open" article was published: www.nature.com/articles/s41...
Preregistered, Open Code and Open Data, I am really proud of it 🤩 The article compares 3 behavioral tasks designed to measure approach-avoidance behavior.

Very happy that our work on the impact of respiration on sleep oscillations and memory reactivation is now published.
With the fabulous Marit Petzka, tobiasstaudigl@bsky.social & Bernhard Staresina. 🧠📈
www.nature.com/articles/s41...

🔥🔥🔥the vmPFC encodes a value map for decision making using a grid like code. 😍

Bild mit einer KlarText-Preisträgerin darauf und dem Aufruf sich für den KlarText-Preis 2024 zu bewerben. Einsendeschluss ist der 28.2.24

Der KlarText-Preis geht in die nächste Runde! Wir suchen Forschende, die uns in einem Artikel oder einer Infografik erklären, woran sie geforscht haben. Alle Bewerbenden dürfen an einem NaWik -Seminar teilnehmen, das heißt: Alle gewinnen!
👉 klartext-preis.de

New preprint! We show that category structure rapidly warps memory for individual object features according to their roles in the category. Features shared across exemplars pull together while unique features stay apart. With @annaschapiro.bsky.social and Cody Dong. doi.org/10.31234/osf...

So excited that this is out now! Our model of how the different pathways of the hippocampus contribute to category learning, led by Jelena Sučević!

elifesciences.org/articles/77185