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Invariant inter-subject relational structures in high order human visual cortex #neuroscience

Invariant inter-subject relational structures in high order human visual cortex - Nature Communications
The neuronal coding principles that underlie inter-individual perceptual similarities remains unclear. Here, the authors compared the stability of relational similarity versus activation patterns across brains and found that relational similarity was preferentially consistent across individuals, potentially underlying shared inter-subject perception.

Convolution semigroups for automorphism dynamics
Kyle Gannon, Daniel Max Hoffmann, Krzysztof Krupi\'nski
https://arxiv.org/abs/2507.23503 https://arxiv…

Convolution semigroups for automorphism dynamics
Initially motivated by Hrushovski's paper on definability patterns, we obtain homeomorphisms between Ellis semigroups related to natural actions of the automorphism groups of first order structures and certain collections of types and Keisler measures. Thus, we can transfer the semigroup operation from these Ellis semigroups to the corresponding collections of types and Keisler measures. By generalizing this transferred product, we obtain a new convolution operation for invariant types and meas…

Symmetries of Hot SM, Magnetic Flux & Baryogenesis from Helicity Decay
Yuta Hamada, Kyohei Mukaida, Fumio Uchida
https://arxiv.org/abs/2507.01576 https…

Symmetries of Hot SM, Magnetic Flux & Baryogenesis from Helicity Decay
We revisit the electroweak crossover of the Standard Model (SM) in the early Universe, focusing on the interplay between generalized global symmetries, magnetic flux dynamics, and baryogenesis. Employing the dimensionally reduced 3d effective field theory of the SM at high temperature, we identify the symmetry structure -- including higher-form and magnetic symmetries -- and analyze their spontaneous breaking patterns across the crossover. We further define a gauge-invariant mixing angle that i…

Scale-free Points-of-Interest Distribution in a City Emerging from Homogeneous Poissonian-point Processes
Eleonora Andreotti, Ulysse Marquis, Maurizio napolitano, Riccardo Gallotti
https://arxiv.org/abs/2509.01699

Scale-free Points-of-Interest Distribution in a City Emerging from Homogeneous Poissonian-point Processes
Urban systems often exhibit scale-invariant properties, with power-law distributions observed in various spatial and temporal patterns of human behavior. A prominent example is the distribution of commercial activities and other Points of Interest (POIs) across cities. However, the mechanisms by which such heavy-tailed behaviors emerge from local urban dynamics remain poorly understood. In this work, we demonstrate that global inhomogeneity in the spatial distribution of POIs can arise from the…

Anchoring Trends: Mitigating Social Media Popularity Prediction Drift via Feature Clustering and Expansion
Chia-Ming Lee, Bo-Cheng Qiu, Cheng-Jun Kang, Yi-Hsuan Wu, Jun-Lin Chen, Yu-Fan Lin, Yi-Shiuan Chou, Chih-Chung Hsu
https://arxiv.org/abs/2507.19863

Anchoring Trends: Mitigating Social Media Popularity Prediction Drift via Feature Clustering and Expansion
Predicting online video popularity faces a critical challenge: prediction drift, where models trained on historical data rapidly degrade due to evolving viral trends and user behaviors. To address this temporal distribution shift, we propose an Anchored Multi-modal Clustering and Feature Generation (AMCFG) framework that discovers temporally-invariant patterns across data distributions. Our approach employs multi-modal clustering to reveal content structure, then leverages Large Language Models…