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 …

[HTML][HTML] Linguistic signs in action: The neuropragmatics of speech acts

R Tomasello - Brain and Language, 2023 - Elsevier
What makes human communication exceptional is the ability to grasp speaker's intentions
beyond what is said verbally. How the brain processes communicative functions is one of …

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 …

[HTML][HTML] Intrinsic noise improves speech recognition in a computational model of the auditory pathway

A Schilling, R Gerum, C Metzner, A Maier… - Frontiers in …, 2022 - frontiersin.org
Noise is generally considered to harm information processing performance. However, in the
context of stochastic resonance, noise has been shown to improve signal detection of weak …

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 …

Attentional modulation of the cortical contribution to the frequency-following response evoked by continuous speech

A Schüller, A Schilling, P Krauss, S Rampp… - Journal of …, 2023 - Soc Neuroscience
Selective attention to one of several competing speakers is required for comprehending a
target speaker among other voices and for successful communication with them. It moreover …

[HTML][HTML] Recognition of grammatical class of imagined words from EEG signals using convolutional neural network

S Datta, NV Boulgouris - Neurocomputing, 2021 - Elsevier
In this paper we propose a framework using multi-channel convolutional neural network (MC–
CNN) for recognizing the grammatical class (verb or noun) of covertly-spoken words from …

[HTML][HTML] Extracting continuous sleep depth from EEG data without machine learning

C Metzner, A Schilling, M Traxdorf, H Schulze… - Neurobiology of Sleep …, 2023 - Elsevier
The human sleep-cycle has been divided into discrete sleep stages that can be recognized
in electroencephalographic (EEG) and other bio-signals by trained specialists or machine …

Word class representations spontaneously emerge in a deep neural network trained on next word prediction

K Surendra, A Schilling, P Stoewer, A Maier… - arXiv preprint arXiv …, 2023 - arxiv.org
How do humans learn language, and can the first language be learned at all? These
fundamental questions are still hotly debated. In contemporary linguistics, there are two …

Classification at the accuracy limit: facing the problem of data ambiguity

C Metzner, A Schilling, M Traxdorf, K Tziridis… - Scientific Reports, 2022 - nature.com
Data classification, the process of analyzing data and organizing it into categories or
clusters, is a fundamental computing task of natural and artificial information processing …