Thomas Nortmann

Thomas Nortmann

@thonor.bsky.social

Computational neuroscience. PhD student with Friedemann Zenke at FMI, Basel. B.Sc. and M.Sc. Cognitive Science at university Osnabrück

110 followers231 following12 posts

Thomas Nortmann reposted

Friedemann Zenke
@fzenke.bsky.social

1/ Why does predicting in latent space (JEPA, CPC, SimCLR...) work so well on messy data, with changing lighting, camera angles, and busy backgrounds? The usual answer: it can ignore nuisance. But that answer holds a conundrum.

Thomas Nortmann reposted

Philip Sulewski
@psulewski.bsky.social

Now out in Nature Neuroscience: "Fixation duration on natural scenes is explained by memory encoding not processing demand". www.nature.com/articles/s41... Our eyes don't linger because recognition is hard; they linger to remember. Let me take you on a quick tour. 🧵

nature.comFixation duration on natural scenes is explained by memory encoding not processing demand - Nature NeuroscienceBy combining magnetoencephalography and eye tracking, this study sheds light on why people fixate on some parts of natural scenes longer than others. Rather than visual complexity, fixation durations ...

Thomas Nortmann reposted

Daniel Anthes
@anthesdaniel.bsky.social

Excited about our new preprint: “The illusory simplicity of the feedforward pass: evidence for the dynamical nature of stimulus encoding along the primate ventral stream” arxiv.org/abs/2604.12825 Work with Sushrut Thorat, Anna Mitola, Paolo Papale, Peter König & Tim Kietzmann 🧵 thread below

arxiv.orgThe illusory simplicity of the feedforward pass: evidence for the dynamical nature of stimulus encoding along the primate ventral streamIn studying primate vision, a large body of work focuses on the first feedforward sweep. During this initial time window, information is thought to pass through ventral stream regions in a stage-like ...

Thomas Nortmann reposted

Friedemann Zenke
@fzenke.bsky.social

1/7 New paper accepted as ICML spotlight arxiv.org/abs/2605.03517! We unify self-supervised learning (SSL) algorithms (e.g., contrastive, VICReg, stopgrad) via latent distribution matching (LDM), which matches an induced latent distribution to an explicit latent model.

Thomas Nortmann reposted

Anna Vasilevskaya
@loghyr.bsky.social

Our work with @georgkeller.bsky.social on testing predictive processing (PP) models in cortex is out on biorvix now! www.biorxiv.org/content/10.6... A short thread on our findings and thoughts on where we should move on from PP below.

biorxiv.orgA functional influence based circuit motif that constrains the set of plausible algorithms of cortical functionThere are several plausible algorithms for cortical function that are specific enough to make testable predictions of the interactions between functionally identified cell types. Many of these algorithms are based on some variant of predictive processing. Here we set out to experimentally distinguish between two such predictive processing variants. A central point of variability between them lies in the proposed vertical communication between layer 2/3 and layer 5, which stems from the diverging assumptions about the computational role of layer 5. One assumes a hierarchically organized architecture and proposes that, within a given node of the network, layer 5 conveys unexplained bottom-up input to prediction error neurons of layer 2/3. The other proposes a non-hierarchical architecture in which internal representation neurons of layer 5 provide predictions for the local prediction error neurons of layer 2/3. We show that the functional influence of layer 2/3 cell types on layer 5 is incompatible with the hierarchical variant, while the functional influence of layer 5 cell types on prediction error neurons of layer 2/3 is incompatible with the non-hierarchical variant. Given these data, we can constrain the space of plausible algorithms of cortical function. We propose a model for cortical function based on a combination of a joint embedding predictive architecture (JEPA) and predictive processing that makes experimentally testable predictions. ### Competing Interest Statement The authors have declared no competing interest. Swiss National Science Foundation, https://ror.org/00yjd3n13 Novartis Foundation, https://ror.org/04f9t1x17 European Research Council, https://ror.org/0472cxd90, 865617
Thomas Nortmann
@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.

Tim Kietzmann @timkietzmann.bsky.social

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...

Thomas Nortmann reposted

Adrien Doerig
@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...

nature.comHigh-level visual representations in the human brain are aligned with large language models - Nature Machine IntelligenceDoerig, 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...
Thomas Nortmann
@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.

Tim Kietzmann @timkietzmann.bsky.social

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...

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