Pulse-frequency-dependent resonance in a population of pyramidal neuron models.
Sign Up to like & getrecommendations! Published in 2022 at "Biological cybernetics"
DOI: 10.1007/s00422-022-00925-w
Abstract: Stochastic resonance is known as a phenomenon whereby information transmission of weak signal or subthreshold stimuli can be enhanced by additive random noise with a suitable intensity. Another phenomenon induced by applying deterministic pulsatile electric… read more here.
Keywords: neuron models; resonance; frequency; pulse frequency ... See more keywords
P090 Excitation mechanisms of TMS on cortical neuron models
Sign Up to like & getrecommendations! Published in 2017 at "Clinical Neurophysiology"
DOI: 10.1016/j.clinph.2016.10.215
Abstract: Introduction Transcranial Magnetic Stimulation (TMS) is a non-invasive method for neuromodulation, with a range of clinical and research applications including the treatment of depression and functional brain mapping. TMS works by generating a time-varying magnetic… read more here.
Keywords: field; p090 excitation; neuron models; mechanisms tms ... See more keywords
Biophysically realistic neuron models for simulation of cortical stimulation.
Sign Up to like & getrecommendations! Published in 2018 at "Journal of neural engineering"
DOI: 10.1088/1741-2552/aadbb1
Abstract: OBJECTIVE We implemented computational models of human and rat cortical neurons for simulating the neural response to cortical stimulation with electromagnetic fields. APPROACH We adapted model neurons from the library of Blue Brain models to… read more here.
Keywords: stimulation; biophysically realistic; neuron models; cortical stimulation ... See more keywords
Comparison of Genomic Best Linear Unbiased Prediction and Bayesian Regularization Neural Networks for Genomic Selection
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2922006
Abstract: This study assessed the predictive ability of genomic best linear unbiased prediction (GBLUP) and Bayesian regularization for feed-forward neural networks (BRNN-s1-s3-neuron) with one to three neurons using genomic relationship based on single nucleotide polymorphisms markers.… read more here.
Keywords: genomic best; best linear; neuron models; brnn ... See more keywords
Neural Information Processing and Computations of Two-Input Synapses
Sign Up to like & getrecommendations! Published in 2022 at "Neural Computation"
DOI: 10.1162/neco_a_01534
Abstract: Abstract Information processing in artificial neural networks is largely dependent on the nature of neuron models. While commonly used models are designed for linear integration of synaptic inputs, accumulating experimental evidence suggests that biological neurons… read more here.
Keywords: information processing; two input; information; neuron models ... See more keywords
Constructing functional models from biophysically-detailed neurons
Sign Up to like & getrecommendations! Published in 2022 at "PLoS Computational Biology"
DOI: 10.1371/journal.pcbi.1010461
Abstract: Improving biological plausibility and functional capacity are two important goals for brain models that connect low-level neural details to high-level behavioral phenomena. We develop a method called “oracle-supervised Neural Engineering Framework” (osNEF) to train biologically-detailed… read more here.
Keywords: functional models; neuron models; models biophysically; constructing functional ... See more keywords
Parameter Estimation of Two Spiking Neuron Models With Meta-Heuristic Optimization Algorithms
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Neuroinformatics"
DOI: 10.3389/fninf.2022.771730
Abstract: The automatic fitting of spiking neuron models to experimental data is a challenging problem. The integrate and fire model and Hodgkin–Huxley (HH) models represent the two complexity extremes of spiking neural models. Between these two… read more here.
Keywords: spiking neuron; problem; neuron models; algorithms ... See more keywords
Beyond LIF Neurons on Neuromorphic Hardware
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Neuroscience"
DOI: 10.3389/fnins.2022.881598
Abstract: Neuromorphic systems aim to provide accelerated low-power simulation of Spiking Neural Networks (SNNs), typically featuring simple and efficient neuron models such as the Leaky Integrate-and-Fire (LIF) model. Biologically plausible neuron models developed by neuroscientists are… read more here.
Keywords: neuron; hardware; neuromorphic hardware; neuron models ... See more keywords
Impact of Cultured Neuron Models on α-Herpesvirus Latency Research
Sign Up to like & getrecommendations! Published in 2022 at "Viruses"
DOI: 10.3390/v14061209
Abstract: A signature trait of neurotropic α-herpesviruses (α-HV) is their ability to establish stable non-productive infections of peripheral neurons termed latency. This specialized gene expression program is the foundation of an evolutionarily successful strategy to ensure… read more here.
Keywords: reactivation; neuron models; cultured neuron; latency ... See more keywords
Estimation of Neuronal Dynamics of Izhikevich Neuron Models from Spike-Train Data with Particle Markov Chain Monte Carlo Method
Sign Up to like & getrecommendations! Published in 2021 at "Journal of the Physical Society of Japan"
DOI: 10.7566/jpsj.90.104801
Abstract: Many neuronal models reproducing electrical activities of neurons have been proposed. Among such neuronal models, the Izhikevich neuron model is known to reproduce various kinds of electrical respo... read more here.
Keywords: models spike; neuron models; neuronal dynamics; dynamics izhikevich ... See more keywords