Predictive coding and stochastic resonance as fundamental principles of auditory phantom perception
Mechanistic insight is achieved only when experiments are employed to test formal or
computational models. Furthermore, in analogy to lesion studies, phantom perception may …
computational models. Furthermore, in analogy to lesion studies, phantom perception may …
Neural manifold analysis of brain circuit dynamics in health and disease
Recent developments in experimental neuroscience make it possible to simultaneously
record the activity of thousands of neurons. However, the development of analysis …
record the activity of thousands of neurons. However, the development of analysis …
[HTML][HTML] Quantifying the separability of data classes in neural networks
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 …
invasive manner, how well different data classes separate in each given layer of an artificial …
EEG biomarkers related with the functional state of stroke patients
Introduction Recent studies explored promising new quantitative methods to analyze
electroencephalography (EEG) signals. This paper analyzes the correlation of two EEG …
electroencephalography (EEG) signals. This paper analyzes the correlation of two EEG …
Neural network based successor representations to form cognitive maps of space and language
How does the mind organize thoughts? The hippocampal-entorhinal complex is thought to
support domain-general representation and processing of structural knowledge of arbitrary …
support domain-general representation and processing of structural knowledge of arbitrary …
Influence of language on perception and concept formation in a brain-constrained deep neural network model
MR Henningsen-Schomers… - … of the Royal …, 2023 - royalsocietypublishing.org
A neurobiologically constrained model of semantic learning in the human brain was used to
simulate the acquisition of concrete and abstract concepts, either with or without verbal …
simulate the acquisition of concrete and abstract concepts, either with or without verbal …
Neural network based formation of cognitive maps of semantic spaces and the putative emergence of abstract concepts
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 …
information into context of our past experiences? The hippocampal-entorhinal complex …
[HTML][HTML] Analysis and visualization of sleep stages based on deep neural networks
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 …
researchers and physicians, as a reliable method able to objectively classify sleep stages …
[HTML][HTML] Will we ever have conscious machines?
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 …
consciousness has been a philosophical question for centuries. The main problem is that …
Chronic back pain sub-grouped via psychosocial, brain and physical factors using machine learning
Chronic back pain (CBP) is heterogenous and identifying sub-groups could improve clinical
decision making. Machine learning can build upon prior sub-grouping approaches by using …
decision making. Machine learning can build upon prior sub-grouping approaches by using …