210 citations · 965 across the 21 of their papers we have counts for
16 papers · 1 filter
Learning sequence timing and control of replay speed in networks of spiking neurons
Melissa Lober, Younes Bouhadjar, Markus Diesmann +1
Processing sequential inputs is a fundamental brain function, underlying tasks such as sensory perception, language, and motor control. A challenge in sequence processing is to rep…
Phenomenological modeling of diverse and heterogeneous synaptic dynamics at natural density
Agnes Korcsak-Gorzo, Charl Linssen, Jasper Albers +9
This chapter sheds light on the synaptic organization of the brain from the perspective of computational neuroscience. It provides an introductory overview on how to account for em…
Coherent noise enables probabilistic sequence replay in spiking neuronal networks
Younes Bouhadjar, Dirk J. Wouters, Markus Diesmann +1
Animals rely on different decision strategies when faced with ambiguous or uncertain cues. Depending on the context, decisions may be biased towards events that were most frequentl…
A Modular Workflow for Performance Benchmarking of Neuronal Network Simulations
Jasper Albers, Jari Pronold, Anno Christopher Kurth +9
Modern computational neuroscience strives to develop complex network models to explain dynamics and function of brains in health and disease. This process goes hand in hand with ad…
Sequence learning, prediction, and replay in networks of spiking neurons
Younes Bouhadjar, Dirk J. Wouters, Markus Diesmann +1
Sequence learning, prediction and replay have been proposed to constitute the universal computations performed by the neocortex. The Hierarchical Temporal Memory (HTM) algorithm re…
Prominent characteristics of recurrent neuronal networks are robust against low synaptic weight resolution
Stefan Dasbach, Tom Tetzlaff, Markus Diesmann +1
The representation of the natural-density, heterogeneous connectivity of neuronal network models at relevant spatial scales remains a challenge for Computational Neuroscience and N…
Firing rate homeostasis counteracts changes in stability of recurrent neural networks caused by synapse loss in Alzheimer's disease
Claudia Bachmann, Tom Tetzlaff, Renato Duarte +1
The impairment of cognitive function in Alzheimer's is clearly correlated to synapse loss. However, the mechanisms underlying this correlation are only poorly understood. Here, we…
Conditions for wave trains in spiking neural networks
Johanna Senk, Karolína Korvasová, Jannis Schuecker +4
Spatiotemporal patterns such as traveling waves are frequently observed in recordings of neural activity. The mechanisms underlying the generation of such patterns are largely unkn…
Deterministic networks for probabilistic computing
Jakob Jordan, Mihai A. Petrovici, Oliver Breitwieser +4
Neural-network models of high-level brain functions such as memory recall and reasoning often rely on the presence of stochasticity. The majority of these models assumes that each…
Hybrid scheme for modeling local field potentials from point-neuron networks
Espen Hagen, David Dahmen, Maria L. Stavrinou +6
Due to rapid advances in multielectrode recording technology, the local field potential (LFP) has again become a popular measure of neuronal activity in both basic research and cli…
The effect of heterogeneity on decorrelation mechanisms in spiking neural networks: a neuromorphic-hardware study
Thomas Pfeil, Jakob Jordan, Tom Tetzlaff +4
High-level brain function such as memory, classification or reasoning can be realized by means of recurrent networks of simplified model neurons. Analog neuromorphic hardware const…
A unified view on weakly correlated recurrent networks
Dmytro Grytskyy, Tom Tetzlaff, Markus Diesmann +1
The diversity of neuron models used in contemporary theoretical neuroscience to investigate specific properties of covariances raises the question how these models relate to each o…
The correlation structure of local cortical networks intrinsically results from recurrent dynamics
Moritz Helias, Tom Tetzlaff, Markus Diesmann
The co-occurrence of action potentials of pairs of neurons within short time intervals is known since long. Such synchronous events can appear time-locked to the behavior of an ani…
Frequency dependence of signal power and spatial reach of the local field potential
Szymon Łęski, Henrik Lindén, Tom Tetzlaff +2
The first recording of electrical potential from brain activity was reported already in 1875, but still the interpretation of the signal is debated. To take full advantage of the n…
Echoes in correlated neural systems
Moritz Helias, Tom Tetzlaff, Markus Diesmann
Correlations are employed in modern physics to explain microscopic and macroscopic phenomena, like the fractional quantum Hall effect and the Mott insulator state in high temperatu…
Decorrelation of neural-network activity by inhibitory feedback
Tom Tetzlaff, Moritz Helias, Gaute T. Einevoll +1
Correlations in spike-train ensembles can seriously impair the encoding of information by their spatio-temporal structure. An inevitable source of correlation in finite neural netw…