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Found 11 papers, 4 papers with code
Assessing the similarity of real matrices with arbitrary shape
We conclude that SAS is a suitable measure for quantifying the shared structure of matrices with arbitrary shape.
Phenomenological modeling of diverse and heterogeneous synaptic dynamics at natural density
This chapter sheds light on the synaptic organization of the brain from the perspective of computational neuroscience.
Sequence learning in a spiking neuronal network with memristive synapses
In this work, we study the feasibility of using ReRAM devices as a replacement of the biological synapses in the sequence learning model.
Coherent noise enables probabilistic sequence replay in spiking neuronal networks
Animals rely on different decision strategies when faced with ambiguous or uncertain cues.
A Modular Workflow for Performance Benchmarking of Neuronal Network Simulations
Modern computational neuroscience strives to develop complex network models to explain dynamics and function of brains in health and disease.
Sequence learning, prediction, and replay in networks of spiking neurons
These subnetworks provide the substrate for a faithful propagation of sparse, synchronous activity, and, thereby, for a robust, context specific prediction of future sequence elements as well as for the autonomous replay of previously learned sequences.
Connectivity Concepts in Neuronal Network Modeling
We hope that the proposed standardizations will contribute to unambiguous descriptions and reproducible implementations of neuronal network connectivity in computational neuroscience.
Routing brain traffic through the von Neumann bottleneck: Parallel sorting and refactoring
With growing network size a compute node receives spikes from an increasing number of different source neurons until in the limit each synapse on the compute node has a unique source.
Prominent characteristics of recurrent neuronal networks are robust against low synaptic weight resolution
For networks with sufficiently heterogeneous in-degrees, the firing statistics can be preserved even if all synaptic weights are replaced by the mean of the weight distribution.
Reconciliation of weak pairwise spike-train correlations and highly coherent local field potentials across space
Based on model predictions of spiking activity and LFPs, we find that the upscaling procedure preserves the overall spiking statistics of the original model and reproduces asynchronous irregular spiking across populations and weak pairwise spike-train correlations in agreement with experimental data recorded in the sensory cortex.
LFP beta amplitude is predictive of mesoscopic spatio-temporal phase patterns
Beta oscillations observed in motor cortical local field potentials (LFPs) recorded on separate electrodes of a multi-electrode array have been shown to exhibit non-zero phase shifts that organize into a planar wave propagation.
