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q-bio.NC2026

Convergent Evolution in Neural Representation Space: Emergent Order in Deep Belief Networks

Patrick Krauss, Achim Schilling, Andreas Maier +2

Deep Belief Networks (DBNs) learn hierarchical generative models without class supervision. Here, we ask whether this purely unsupervised process nevertheless organizes internal re…

q-bio.NC2026

Convergent Evolution in Algorithmic Space

Patrick Krauss, Achim Schilling, Andreas Maier +4

In evolutionary biology, unrelated organisms can independently evolve similar structures when exposed to similar functional demands. Here we ask whether an analogous form of conver…

q-bio.NC2026

Surviving by Serving: Functional Relevance Drives Self-Organization in Complex Adaptive Systems

Claus Metzner, Ali Ghebleh, Achim Schilling +3

Complex adaptive systems often develop organized structures without centralized control. Yet the local mechanisms by which functional organization emerges and persists remain incom…

q-bio.NC2026

Are cortical microcircuits optimized for information flux? -- A simulation-based reverse engineering study

Claus Metzner, Ali Ghebleh, Karin Prebeck +4

A sufficiently large information flux in recurrent neural networks, quantified by the mutual information between successive network states, is considered a prerequisite for rich in…

q-bio.NC2026

Structural and dynamical strategies to prevent runaway excitation in reservoir computing

Claus Metzner, Achim Schilling, Andreas Maier +2

Reservoirs, typically implemented as recurrent neural networks with fixed random connection weights, can be combined with a simple trained readout layer to perform a wide range of…

q-bio.NC2026

Convergent Representations of Linguistic Constructions in Human and Artificial Neural Systems

Pegah Ramezani, Thomas Kinfe, Andreas Maier +2

Understanding how the brain processes linguistic constructions is a central challenge in cognitive neuroscience and linguistics. Recent computational studies show that artificial n…

q-bio.NC2025

The Predictive Brain: Neural Correlates of Word Expectancy Align with Large Language Model Prediction Probabilities

Nikola Kölbl, Konstantin Tziridis, Andreas Maier +4

Predictive coding theory suggests that the brain continuously anticipates upcoming words to optimize language processing, but the neural mechanisms remain unclear, particularly in…