Predictive coding and stochastic resonance as fundamental principles of auditory phantom perception

A Schilling, W Sedley, R Gerum, C Metzner, K Tziridis… - Brain, 2023 - academic.oup.com
Mechanistic insight is achieved only when experiments are employed to test formal or
computational models. Furthermore, in analogy to lesion studies, phantom perception may …

A survey on neuromarketing using EEG signals

V Khurana, M Gahalawat, P Kumar… - … on Cognitive and …, 2021 - ieeexplore.ieee.org
Neuromarketing is the application of neuroscience to the understanding of consumer
preferences toward products and services. As such, it studies the neural activity associated …

[HTML][HTML] Quantifying the separability of data classes in neural networks

A Schilling, A Maier, R Gerum, C Metzner, P Krauss - Neural Networks, 2021 - Elsevier
Abstract We introduce the Generalized Discrimination Value (GDV) that measures, in a non-
invasive manner, how well different data classes separate in each given layer of an artificial …

Neural network based successor representations to form cognitive maps of space and language

P Stoewer, C Schlieker, A Schilling, C Metzner… - Scientific Reports, 2022 - nature.com
How does the mind organize thoughts? The hippocampal-entorhinal complex is thought to
support domain-general representation and processing of structural knowledge of arbitrary …

Neural network based formation of cognitive maps of semantic spaces and the putative emergence of abstract concepts

P Stoewer, A Schilling, A Maier, P Krauss - Scientific Reports, 2023 - nature.com
How do we make sense of the input from our sensory organs, and put the perceived
information into context of our past experiences? The hippocampal-entorhinal complex …

Sleep state classification using power spectral density and residual neural network with multichannel EEG signals

MJ Hasan, D Shon, K Im, HK Choi, DS Yoo, JM Kim - Applied Sciences, 2020 - mdpi.com
This paper proposes a classification framework for automatic sleep stage detection in both
male and female human subjects by analyzing the electroencephalogram (EEG) data of …

[HTML][HTML] Analysis and visualization of sleep stages based on deep neural networks

P Krauss, C Metzner, N Joshi, H Schulze… - Neurobiology of sleep …, 2021 - Elsevier
Automatic sleep stage scoring based on deep neural networks has come into focus of sleep
researchers and physicians, as a reliable method able to objectively classify sleep stages …

[HTML][HTML] Will we ever have conscious machines?

P Krauss, A Maier - Frontiers in computational neuroscience, 2020 - frontiersin.org
The question of whether artificial beings or machines could become self-aware or
consciousness has been a philosophical question for centuries. The main problem is that …

EEG-based sleep staging analysis with functional connectivity

H Huang, J Zhang, L Zhu, J Tang, G Lin, W Kong, X Lei… - Sensors, 2021 - mdpi.com
Sleep staging is important in sleep research since it is the basis for sleep evaluation and
disease diagnosis. Related works have acquired many desirable outcomes. However, most …

Sleep stage classification for child patients using DeConvolutional Neural Network

X Huang, K Shirahama, F Li, M Grzegorzek - Artificial intelligence in …, 2020 - Elsevier
Studies from the literature show that the prevalence of sleep disorder in children is far higher
than that in adults. Although much research effort has been made on sleep stage …