Thomas Nortmann
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thonor.bsky.social
Thomas Nortmann
@thonor.bsky.social
60 followers 130 following 11 posts
Computational neuroscience. PhD student with Friedemann Zenke at FMI, Basel. B.Sc. and M.Sc. Cognitive Science at university Osnabrück
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thonor.bsky.social
🚨 Out in Patterns!

We asked ourselves, if complex neural dynamics like predictive remapping and allocentric coding can emerge from simple physical principles, in this case Energy Efficiency. Turns out they can!
More information in the 🧵 below.

I am super excited to see this one out in the wild.
A screenshot of the article "Predictive remapping and allocentric coding as consequences of energy efficiency in recurrent neural network models of active vision". The authors are Thomas Nortmann, Philip Sulewski and Tim C. Kietzmann. Under the article heading is a section titled "The bigger picture". The section reads as follows: "We show how some of the brain’s amazing abilities, such as keeping our view of the world stable even when our eyes move, might come from simple ideas such as saving energy. Instead of assuming that the brain is wired with complex instructions for predicting what we will see next, we explored whether these skills could develop naturally from basic physical principles. We apply a computer model that mimics how our eyes move and how the brain processes visual information. This model was trained to perform eye movements while trying to use as little energy as possible by reducing unnecessary neural activity. Surprisingly, as the model learned to be more energy efficient, it started to develop a process called predictive remapping. This process is how the brain predicts what will appear in our vision after an eye movement, so our perception stays smooth and stable. Moreover, the model learned to create an internal representation that translates the position of the eyes into a more stable, environment-centered frame of reference. This internal map helps the system predict future visual input and decide when to inhibit or reduce certain signals, making the whole process more efficient. Altogether, we show that complex visual functions such as predictive remapping and creating an environment-centered reference frame can emerge naturally when a system is optimized for energy efficiency."
November 20, 2025 at 7:47 PM
Reposted by Thomas Nortmann
initself.bsky.social
Introducing CorText: a framework that fuses brain data directly into a large language model, allowing for interactive neural readout using natural language.

tl;dr: you can now chat with a brain scan 🧠💬

1/n
November 3, 2025 at 3:17 PM
Reposted by Thomas Nortmann
timkietzmann.bsky.social
Another Friday feat: Philip Sulewski's (@psulewski.bsky.social) and @thonor.bsky.social's
modelling work. Predictive remapping and allocentric coding as consequences of energy efficiency in RNN models of active vision

Time: Friday, August 15, 2:00 – 5:00 pm,
Location: Poster C112, de Brug & E‑Hall
August 8, 2025 at 2:21 PM
Reposted by Thomas Nortmann
adriendoerig.bsky.social
🚨 Finally out in Nature Machine Intelligence!!
"Visual representations in the human brain are aligned with large language models"
🔗 www.nature.com/articles/s42...
High-level visual representations in the human brain are aligned with large language models - Nature Machine Intelligence
Doerig, Kietzmann and colleagues show that the brain’s response to visual scenes can be modelled using language-based AI representations. By linking brain activity to caption-based embeddings from lar...
www.nature.com
August 7, 2025 at 1:06 PM
thonor.bsky.social
My first ever preprint is now out. We show the emergence of complex computations given only the rather simple underlying goal of energy efficiency.
timkietzmann.bsky.social Tim Kietzmann @timkietzmann.bsky.social · Jun 5
Can seemingly complex multi-area computations in the brain emerge from the need for energy efficient computation? In our new preprint on predictive remapping in active vision, we report on such a case.

Let us take you for a spin. 1/6 www.biorxiv.org/content/10.1...
June 5, 2025 at 1:41 PM