Lightnews — Scholar-powered news

Constantin Rothkopf @c-rothkopf.bsky.social · 7d

If neuroscience needs behavior, then it also needs control theory ... but that's not the only reason: check out the workshop at #Bernsteinconference
bernstein-network.de/bernstein-co...

(SW2025) Control theory approaches for analysing, modeling, and manipulating brain activity and cognitive function – Bernstein Netzwerk Computational Neuroscience

bernstein-network.de

7 19

Constantin Rothkopf @c-rothkopf.bsky.social · Aug 25

Looking forward to meeting you #ECVP2025 Mainz this week, including collaborative work with @tobnie.bsky.social @dominikstrb.bsky.social @ookenfooken.bsky.social @fatatai.bsky.social @tsawallis.bsky.social @mamassian.bsky.social @guidomaiello.bsky.social @mariaeckstein.bsky.social and many others

5 15

Reposted by Constantin Rothkopf

Tobias Niehues @tobnie.bsky.social · Aug 13

I'm presenting our work "Revisiting Cost Functions in Sensorimotor Decision-Making" at #CCN2025!

Stop by our poster (@dominikstrb.bsky.social‬, @c-rothkopf.bsky.social‬) and learn more about how to rethink common modeling assumptions.

📅 When: Friday, August 15, 2pm–5pm
📍 Where: De Brug, Poster C1

Upper left sketch shows the problem description the paper tackles, which is the decision-making problem that the subject needs to solve versus the inverse problem about the behavioral parameters that the researcher wants to infer. Bottom left sketch shows probabilistic graphical model of the behavior as formalized in our framework. Right panel shows the results of the paper. From top to bottom it shows example data, results of the model comparison, inferred cost functions and inferred prior beliefs of the subject. Five tasks are organized in columns by which cost function described subjects' behavior in the respective task best. We found three different cost functions, None of which are quadratic.

2 9

Reposted by Constantin Rothkopf

Fabian Tatai @fatatai.bsky.social · Aug 2

Happy to announce that I am presenting a poster today at #CogSci25: Physical reasoning during motor learning aids people at transferring mass, but not motor control mappings.

This is joint work with Dominik Ürüm, @mariaeckstein.bsky.social and @c-rothkopf.bsky.social

Find out more at P3-T-192!

3 6

Constantin Rothkopf @c-rothkopf.bsky.social · Jul 28

Lots of trade offs in active visual behaviors, e.g. trading gaze switches for task performance www.pnas.org/doi/abs/10.1... or trading blinking for task performance www.pnas.org/doi/abs/10.1...

Learning rational temporal eye movement strategies | PNAS

During active behavior humans redirect their gaze several times every second within the visual environment. Where we look within static images is h...

www.pnas.org

3

Constantin Rothkopf @c-rothkopf.bsky.social · Jul 8

We have an open PhD position in an exciting @dfg.de - @ageinves.bsky.social project to further develop continuous psychophysics in collaboration with Joan-Lopez Moliner.

4 6

Reposted by Constantin Rothkopf

Antonia Wüst @toniwuest.bsky.social · May 2

Excited to share that our paper got accepted at #ICML2025!! 🎉

We challenge Vision-Language Models like OpenAI’s o1 with Bongard problems, classic visual reasoning challenges and uncover surprising shortcomings.

Check out the paper: arxiv.org/abs/2410.19546
& read more below 👇

1 10 24

Constantin Rothkopf @c-rothkopf.bsky.social · Apr 25

Happy to contribute to the Natural Environments Tasks and Intelligence (NETI) workshop at UT Austin with a talk on "Computational elements of goal-directed sensorimotor behavior". You can follow the live-stream at the workshop's website liberalarts.utexas.edu/cps/neti-wor...

College of Liberal Arts | The University of Texas at Austin

Liberal Arts at UT offers over 40 majors and many top-ranked graduate programs in the social sciences and humanities taught by 750 faculty.

liberalarts.utexas.edu

4

Constantin Rothkopf @c-rothkopf.bsky.social · Apr 25

Very excited to be part of the Simons collaboration on ecological neuroscience @simonsfoundation.org together with this fantastic team! Theory-driven investigation of where representations for perception, cognition, and action in ecological tasks come from. POMDPs FTW. Stay tuned for job openings...

Simons Foundation @simonsfoundation.org · Apr 24

We are excited to announce our new Simons Collaboration on Ecological Neuroscience (SCENE)! This program will unite experts in experimental and computational #neuroscience approaches to investigate how the brain represents sensorimotor interactions. www.simonsfoundation.org/2025/04/24/s... #science

Simons Foundation Launches Collaboration on Ecological Neuroscience

Simons Foundation Launches Collaboration on Ecological Neuroscience on Simons Foundation

www.simonsfoundation.org

1 7 24

Reposted by Constantin Rothkopf

Tobias Niehues @tobnie.bsky.social · Apr 23

If you wanna find out how to overcome Gaussian distribution and quadratic cost assumptions in Bayesian decision-making models AND how to perform inference over their parameters, swing by our poster at #ICLR2025 in Singapore!
📅 When: Friday, April 25, 10am–12:30pm
📍 Where: Halls 3 + 2B, Poster #61

Constantin Rothkopf @c-rothkopf.bsky.social · Feb 1

Curious to learn more? Check out our full paper to see how neural networks can transform Bayesian inference in complex decision-making models arxiv.org/abs/2409.03710

Inverse decision-making using neural amortized Bayesian actors

Bayesian observer and actor models have provided normative explanations for many behavioral phenomena in perception, sensorimotor control, and other areas of cognitive science and neuroscience. They a...

arxiv.org

1 6

Constantin Rothkopf @c-rothkopf.bsky.social · Apr 17

More work still to appear ...

Constantin Rothkopf @c-rothkopf.bsky.social · Apr 17

How to infer an individual’s knowledge about the dynamics of an environment? Approximate BAMDP planning model for uncertainty over transitions & efficient replanning, as well as an approximate knowledge inference method given the behavior of an agent based on the planning model and Gibbs sampling

1 2

Constantin Rothkopf @c-rothkopf.bsky.social · Apr 17

Straub∗, D., Schultheis∗, M., Koeppl, H., & Rothkopf, C. A. (2023). Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs. NeurIPS.

1 2

Constantin Rothkopf @c-rothkopf.bsky.social · Apr 17

Schultheis∗, M., Straub∗, D., & Rothkopf, C. A. (2021). Inverse Optimal Control Adapted to the Noise Characteristics of the Human Sensorimotor System. NeurIPS.

1

Constantin Rothkopf @c-rothkopf.bsky.social · Apr 17

How to infer model parameters in sensorimotor control tasks? Dynamics may be stochastic and non-linear, the agent’s beliefs and controls may be unobserved, and beyond costs we may want to infer perceptual noises, beliefs, dynamics, and control-- this includes partial observations and unknown plant

1

Constantin Rothkopf @c-rothkopf.bsky.social · Apr 17

M. Schultheis, C.A. Rothkopf, H. Koeppl (2022). Reinforcement learning with non-exponential discounting. NeurIPS.

1

Constantin Rothkopf @c-rothkopf.bsky.social · Apr 17

We developed a theory of continuous-time model-based reinforcement learning generalized to arbitrary discount functions. This formulation covers non-exponential random termination times and includes solving the inverse problem of learning the discount function from decision data

1

Constantin Rothkopf @c-rothkopf.bsky.social · Apr 17

How to model and estimate non-exponential time preferences? Commonly in reinforcement learning, rewards are discounted over time using an exponential function to model time preference. In contrast, in economics and psychology, it has been shown that humans often adopt a hyperbolic discounting scheme

1

Constantin Rothkopf @c-rothkopf.bsky.social · Apr 17

Matthias was co-advised together with Heinz Koeppl.

1

Constantin Rothkopf @c-rothkopf.bsky.social · Apr 17

Congratulations to Matthias Schultheis for defending his PhD thesis 'Inverse reinforcement learning for human decision-making under uncertainty' with distinction. Significant contributions to understanding bounded actors with inverse POMDPs for partial observabilities and non-stationary behavior

1 2 12

Reposted by Constantin Rothkopf

Ulrich Ettinger @ulrichettinger.bsky.social · Apr 4

Very pleased to announce the next talk in the Bonn Melbourne Seminar in Decision Making: "Eye Movements As Sequential Decision-making Under Uncertainty" by @c-rothkopf.bsky.social. DM to join us online! #DecisionMaking #EyeMovements #TheEyesHaveIt www.psychologie.uni-bonn.de/de/institut/...

Bonn Melbourne Seminar in Decision Making and Computational Psychiatry

www.psychologie.uni-bonn.de

3 4

Constantin Rothkopf @c-rothkopf.bsky.social · Mar 7

How inverse modeling can speak to algorithmic level descriptions of human behavior and the heuristics debate: What to conclude if a dynamical system model fits behavior? If it looks like online control, it is probably model-based control. Proceedings of the Annual Meeting of the Cog Sci Society

Constantin Rothkopf @c-rothkopf.bsky.social · Mar 7

Applying inverse modeling to the continuous psychophysics paradigm: Straub, D., & Rothkopf, C. A. (2022). Putting perception into action with inverse optimal control for continuous psychophysics. eLife, 11, e76635.

1 1

Constantin Rothkopf @c-rothkopf.bsky.social · Mar 7

Straub∗, D., Schultheis∗, M., Koeppl, H., & Rothkopf, C. A. (2023). Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs. NeurIPS.

1 1

Constantin Rothkopf @c-rothkopf.bsky.social · Mar 7

When dynamics and observations are non-linear, the separation principle does not hold, leading to interesting information-seeking behavior- which this method can recover! This includes partial observability from the actor's and observer's point of view, and even the dynamics can be unknown.

1