A spike train distance-based method to evaluate the response of mechanoreceptive afferents
Sign Up to like & getrecommendations! Published in 2018 at "Neural Computing and Applications"
DOI: 10.1007/s00521-018-3465-6
Abstract: Spike train distances have gained increasing attention in the neuroscience community and provided an important tool to quantify the similarity between spike trains. A number of comparisons of the spike train distances have been carried… read more here.
Keywords: mechanoreceptive afferents; distance; spike train; train distance ... See more keywords
Closed-form modeling of neuronal spike train statistics using multivariate Hawkes cumulants.
Sign Up to like & getrecommendations! Published in 2022 at "Physical review. E"
DOI: 10.1103/physreve.106.054410
Abstract: We derive exact analytical expressions for the cumulants of any orders of neuronal membrane potentials driven by spike trains in a multivariate Hawkes process model with excitation and inhibition. Such expressions can be used for… read more here.
Keywords: form modeling; multivariate hawkes; modeling neuronal; spike train ... See more keywords
Directed Information Between Connected Leaky Integrate-and-Fire Neurons
Sign Up to like & getrecommendations! Published in 2017 at "IEEE Transactions on Information Theory"
DOI: 10.1109/isit.2014.6875041
Abstract: The connectivity structure between neurons is useful for determining how groups of neurons perform tasks. Directed information is a measure that can be used to infer connectivity between neurons using their recorded time series. In… read more here.
Keywords: information; spike train; leaky integrate; model ... See more keywords
Automatic Identification of Individual Motor Unit Firing Accuracy From High-Density Surface Electromyograms
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Neural Systems and Rehabilitation Engineering"
DOI: 10.1109/tnsre.2019.2961680
Abstract: We introduce an algorithm for automatic identification of true positive (TP) and false positive (FP) spikes in the motor unit spike train, identified by blind source separation (BSS) of high-density surface electromyograms (HDsEMG). The algorithm… read more here.
Keywords: motor unit; spike train;
Binless Kernel Machine: Modeling Spike Train Transformation for Cognitive Neural Prostheses
Sign Up to like & getrecommendations! Published in 2020 at "Neural Computation"
DOI: 10.1162/neco_a_01306
Abstract: Modeling spike train transformation among brain regions helps in designing a cognitive neural prosthesis that restores lost cognitive functions. Various methods analyze the nonlinear dynamic spike train transformation between two cortical areas with low computational… read more here.
Keywords: binless kernel; train transformation; spike train; spike ... See more keywords
Inferring information flow in spike-train data sets using a trial-shuffle method
Sign Up to like & getrecommendations! Published in 2018 at "PLoS ONE"
DOI: 10.1371/journal.pone.0206977
Abstract: Understanding information processing in the brain requires the ability to determine the functional connectivity between the different regions of the brain. We present a method using transfer entropy to extract this flow of information between… read more here.
Keywords: trial shuffle; information; spike train; train data ... See more keywords
Thermodynamic Formalism in Neuronal Dynamics and Spike Train Statistics
Sign Up to like & getrecommendations! Published in 2020 at "Entropy"
DOI: 10.20944/preprints202010.0250.v1
Abstract: The Thermodynamic Formalism provides a rigorous mathematical framework to study quantitative and qualitative aspects of dynamical systems. At its core there is a variational principle corresponding, in its simplest form, to the Maximum Entropy principle.… read more here.
Keywords: neuronal dynamics; dynamics spike; spike train; formalism neuronal ... See more keywords
A Delay Learning Algorithm Based on Spike Train Kernels for Spiking Neurons
Sign Up to like & getrecommendations! Published in 2019 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2019.00252
Abstract: Neuroscience research confirms that the synaptic delays are not constant, but can be modulated. This paper proposes a supervised delay learning algorithm for spiking neurons with temporal encoding, in which both the weight and delay… read more here.
Keywords: spike train; delay learning; spiking neurons; train kernels ... See more keywords
Supervised Learning Algorithm Based on Spike Train Inner Product for Deep Spiking Neural Networks
Sign Up to like & getrecommendations! Published in 2023 at "Brain Sciences"
DOI: 10.3390/brainsci13020168
Abstract: By mimicking the hierarchical structure of human brain, deep spiking neural networks (DSNNs) can extract features from a lower level to a higher level gradually, and improve the performance for the processing of spatio-temporal information.… read more here.
Keywords: neural networks; deep spiking; spike train; spiking neural ... See more keywords