2 citations · 12 across the 24 of their papers we have counts for
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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…
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…
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…
Ten Years of the Stochastic Resonance Model of Tinnitus: From Phantom Perception to Adaptive Sensory Optimization
Patrick Krauss, Achim Schilling
Subjective tinnitus - the perception of sound in the absence of an external acoustic stimulus - remains one of the most debated phenomena in auditory neuroscience. In 2016, the sto…
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…
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…
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…
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…
Organizational Regularities in Recurrent Neural Networks
Claus Metzner, Achim Schilling, Andreas Maier +1
Previous work has shown that the dynamical regime of Recurrent Neural Networks (RNNs) - ranging from oscillatory to chaotic and fixpoint behavior - can be controlled by the global…
Recurrence Resonance -- Noise-Enhanced Dynamics in Recurrent Neural Networks
Claus Metzner, Achim Schilling, Andreas Maier +1
In specific motifs of three recurrently connected neurons with probabilistic response, the spontaneous information flux, defined as the mutual information between subsequent states…
Multi-Modal Cognitive Maps based on Neural Networks trained on Successor Representations
Paul Stoewer, Achim Schilling, Andreas Maier +1
Cognitive maps are a proposed concept on how the brain efficiently organizes memories and retrieves context out of them. The entorhinal-hippocampal complex is heavily involved in e…