61 citations · 148 across the 34 of their papers we have counts for
5 papers · 1 filter
Stochastic resonance in three-neuron motifs
Patrick Krauss, Karin Prebeck, Achim Schilling +1
Stochastic resonance is a non-linear phenomenon, in which the sensitivity of signal detectors can be enhanced by adding random noise to the detector input. Here, we demonstrate tha…
Analysis of structure and dynamics in three-neuron motifs
Patrick Krauss, Alexandra Zankl, Achim Schilling +2
In neural networks with identical neurons, the matrix of connection weights completely describes the network structure and thereby determines how it is processing information. Howe…
Objective estimation of sensory thresholds based on neurophysiological parameters
Achim Schilling, Richard Gerum, Patrick Krauss +3
Reliable determination of sensory thresholds is the holy grail of signal detection theory. However, there exists no gold standard for the estimation of thresholds based on neurophy…
How deep is deep enough? -- Quantifying class separability in the hidden layers of deep neural networks
Achim Schilling, Claus Metzner, Jonas Rietsch +3
Deep neural networks typically outperform more traditional machine learning models in their ability to classify complex data, and yet is not clear how the individual hidden layers…
Open(G)PIAS: An open source solution for the construction of a high-precision Acoustic-Startle-Response (ASR) setup for tinnitus screening and threshold estimation in rodents
Richard Gerum, Hinrich Rahlfs, Matthias Streb +7
The acoustic startle reflex (ASR) that can be induced by a loud sound stimulus can be used as a versatile tool to, e.g., estimate hearing thresholds or identify subjective tinnitus…