Filters








229,307 Hits in 5.3 sec

Optimal parameter estimation of the Izhikevich single neuron model using experimental inter-spike interval (ISI) data

G Kumar, V Aggarwal, N V Thakor, M H Schieber, M V Kothare
<span title="">2010</span> <i title="IEEE"> Proceedings of the 2010 American Control Conference </i> &nbsp;
We propose to use the Izhikevich single neuron model to represent a motor cortex neuron for studying a control-theoretic perspective of a neuroprosthetic system.  ...  Reasonable model parameters are estimated by solving these optimization problems which may serve as a template for studying and developing a model of ensemble cortical neurons for neuroprosthesis applications  ...  These results use model generated ISIs for validating the method for model parameters estimation, where ISIs are vary in a very small range.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/acc.2010.5530803">doi:10.1109/acc.2010.5530803</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vdodt66ukrdhtlhgb5esqgmr3m">fatcat:vdodt66ukrdhtlhgb5esqgmr3m</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170809103656/http://www.dcsc.tudelft.nl/~bdeschutter/private_20100705_acc_2010/data/papers/1539.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/01/bc/01bcf452978c56a2cfc1233e1704b2089fee76e6.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/acc.2010.5530803"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Single-trial estimation of stimulus and spike-history effects on time-varying ensemble spiking activity of multiple neurons: a simulation study

Hideaki Shimazaki
<span title="2013-12-16">2013</span> <i title="IOP Publishing"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wxgp7pobnrfetfizidmpebi4qy" style="color: black;">Journal of Physics, Conference Series</a> </i> &nbsp;
We recently developed a method for estimating the dynamics of correlated ensemble activity by combining a model of simultaneous neuronal interactions (e.g., a spin-glass model) with a state-space method  ...  In this study, we develop a parametric method for simultaneously estimating the stimulus and spike-history effects on the ensemble activity from single-trial data even if the neurons exhibit dynamics that  ...  Sonja Grün for their support in construction of the original model. The author also thanks to Dr. Christopher L. Buckley and Dr. Erin Munro for critical reading of the manuscript.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1088/1742-6596/473/1/012009">doi:10.1088/1742-6596/473/1/012009</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/sqezrhe435hovd7fxmaghsgfeq">fatcat:sqezrhe435hovd7fxmaghsgfeq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191017060553/https://arxiv.org/pdf/1312.4382v1.pdf" title="fulltext PDF download [not primary version]" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <span style="color: #f43e3e;">&#10033;</span> <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/dd/bd/ddbd31b71068fe8e3660eadce86e1f05d36bf95f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1088/1742-6596/473/1/012009"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> iop.org </button> </a>

A General LSTM-based Deep Learning Method for Estimating Neuronal Models and Inferring Neural Circuitry [article]

Kaiwen Sheng, Peng Qu, Le Yang, Xiaofei Liu, Liuyuan He, Lei Ma, Kai Du
<span title="2021-03-15">2021</span> <i title="Cold Spring Harbor Laboratory"> bioRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
Computational neural models are essential tools for neuroscientists to study the functional roles of single neurons or neural circuits.  ...  Here, we present a Long Short-Term Memory (LSTM)-based deep learning method, General Neural Estimator (GNE), to fully automate the parameter tuning procedure, which can be directly applied to both single  ...  As for single neuron 777 HHIzhikevich Single-Compartment Neuron Model The HH single-compartment neuron model is defined as equation 781 (7)-(8).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/2021.03.14.434027">doi:10.1101/2021.03.14.434027</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rwipzzfsvratxlpen3fp5dbvje">fatcat:rwipzzfsvratxlpen3fp5dbvje</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210718035448/https://www.biorxiv.org/content/biorxiv/early/2021/03/15/2021.03.14.434027.full.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/37/f9/37f9f82ab3d6a7e1716a0e3beb756355e0c1531c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/2021.03.14.434027"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> biorxiv.org </button> </a>

An Integral Equation Approach to the Dynamics of L2-3 Cortical Neurons [article]

Richard Naud
<span title="2013-12-03">2013</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
The fitting method can estimate single-neuron parameters that are normally obtained either with intracellular recordings or with individual spike trains.  ...  How do neuronal populations encode time-dependent stimuli in their population firing rate?  ...  Tchumatchenko for sharing the data and to W. Gerstner for helpful suggestions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1308.5668v2">arXiv:1308.5668v2</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ik4nowuyarb5nngs5oc6se3vci">fatcat:ik4nowuyarb5nngs5oc6se3vci</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191026144310/https://arxiv.org/pdf/1308.5668v2.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f1/45/f14542b1c464436aa9782a423421d8589884a162.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1308.5668v2" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

A Probabilistic Model for Estimating the Depth and Threshold Temperature of C-fiber Nociceptors

Tara Dezhdar, Rabih A. Moshourab, Ingo Fründ, Gary R. Lewin, Michael Schmuker
<span title="2015-12-07">2015</span> <i title="Springer Nature"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/tnqhc2x2aneavcd3gx5h7mswhm" style="color: black;">Scientific Reports</a> </i> &nbsp;
However, the current state-of-the-art model to estimate temperature at the receptor suffers from the fact that it cannot account for the natural stochastic variability of neuronal responses.  ...  providing estimates of threshold and depth in cases where the classical method fails.  ...  For every potentially excluded stimulus in selection model M 2 , we estimated the ratio of the marginal likelihood for the full model M 1 over the marginal likelihood for the model M 2 without the excluded  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/srep17670">doi:10.1038/srep17670</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/26638830">pmid:26638830</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4671062/">pmcid:PMC4671062</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/n6fdyzfmjrfm7mxd2sv5o6fmqq">fatcat:n6fdyzfmjrfm7mxd2sv5o6fmqq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170926120646/https://core.ac.uk/download/pdf/30615169.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/64/0f/640fd08e2fa0195b905386520d627d4cafe50aec.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1038/srep17670"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4671062" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Prediction of single neuron spiking activity using an optimized nonlinear dynamic model

A. Mitra, A. Manitius, T. Sauer
<span title="">2012</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/i3wdcpisqrhohjypmlikfya2la" style="color: black;">2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society</a> </i> &nbsp;
In this paper we describe a new technique for optimization of a single neuron model using an experimental spike train from a biological neuron.  ...  The spiking activity is characterized using spike trains and it is essential to develop methods for parameter estimation that rely solely on the spike times or interspike intervals (ISI).  ...  Future work While our method successfully optimizes single neuron models, the objective is to characterize neuron populations and build predictors for a network of neurons interacting among themselves.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/embc.2012.6346482">doi:10.1109/embc.2012.6346482</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/23366443">pmid:23366443</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/embc/MitraMS12.html">dblp:conf/embc/MitraMS12</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/x4whqyvrlfgfbpju43ohkbklui">fatcat:x4whqyvrlfgfbpju43ohkbklui</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160422163056/http://math.gmu.edu/~tsauer/pre/anish2012.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a4/a5/a4a50b4a8b423b1e75f6a493656d8a43a7cfef43.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/embc.2012.6346482"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Inferring the collective dynamics of neuronal populations from single-trial spike trains using mechanistic models [article]

Christian Donner, Manfred Opper, Josef Ladenbauer
<span title="2019-06-14">2019</span> <i title="Cold Spring Harbor Laboratory"> bioRxiv </i> &nbsp; <span class="release-stage" >pre-print</span>
To efficiently estimate the model parameters and compare different model variants we compute the likelihood of observed single-trail spike trains by leveraging analytical methods for spiking neuron models  ...  Extensive evaluations based on simulated data show that our method correctly identifies the dynamics of the shared input process and accurately estimates the model parameters.  ...  Acknowledgments We thank Christian Pozzorini for making available the in-vitro data. CD was supported by the German Research Foundation via GRK1589/2 and CRC1295.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/671909">doi:10.1101/671909</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/wajgugbwhfdh5mwd3r6a5w6iv4">fatcat:wajgugbwhfdh5mwd3r6a5w6iv4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200306224809/https://www.biorxiv.org/content/biorxiv/early/2019/06/14/671909.full.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/08/53/0853617093c9065ff63df05ba3600f917525c163.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1101/671909"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> biorxiv.org </button> </a>

Estimating nonstationary input signals from a single neuronal spike train

Hideaki Kim, Shigeru Shinomoto
<span title="2012-11-02">2012</span> <i title="American Physical Society (APS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nuk2stxzvvhf7ljciu325kj77m" style="color: black;">Physical Review E</a> </i> &nbsp;
Although a number of mathematical methods have been developed to estimate such input parameters as the mean and fluctuation of the input current, these techniques are based on the unrealistic assumption  ...  Here, we propose tracking temporal variations in input parameters with a two-step analysis method.  ...  In this paper, we constructed a method for estimating nonstationary inputs from a single spike train.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1103/physreve.86.051903">doi:10.1103/physreve.86.051903</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/23214810">pmid:23214810</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5kfhrk7dorgyveuz2der7nisgu">fatcat:5kfhrk7dorgyveuz2der7nisgu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190502022347/https://repository.kulib.kyoto-u.ac.jp/dspace/bitstream/2433/169711/1/PhysRevE.86.051903.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ba/45/ba45e1a0a61227ed5f3dc6cd70135264b3a36d7b.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1103/physreve.86.051903"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> aps.org </button> </a>

System Identification of a Multi-timescale Adaptive Threshold Neuronal Model [article]

Amirhossein Jabalameli, Aman Behal
<span title="2018-02-23">2018</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
In this paper, the parameter estimation problem for a multi-timescale adaptive threshold (MAT) neuronal model is investigated.  ...  This linearly parametrized realizable model is then utilized inside a prediction error based framework to identify the threshold parameters with the purpose of predicting single neuron precise firing times  ...  In what follows, we develop an automatic method for estimating the MAT model parameters.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1803.04236v1">arXiv:1803.04236v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/qs5wme4yejcz7fqc6mlirnxhei">fatcat:qs5wme4yejcz7fqc6mlirnxhei</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191018202414/https://arxiv.org/pdf/1803.04236v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d3/01/d30111f71d2d0965e24b3579ed34bcd2193def6f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1803.04236v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Predicting synchronous firing of large neural populations from sequential recordings [article]

Oleksandr Sorochynskyi, Stéphane Deny, Olivier Marre, Ulisse Ferrari
<span title="2019-04-09">2019</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
A major goal in neuroscience is to understand how populations of neurons code for stimuli or actions.  ...  Here we show that we can infer the activity of a full population of retina ganglion cells from sequential recordings, using a novel method based on copula distributions and maximum entropy modeling.  ...  Tkacik for useful discussions.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1904.04544v1">arXiv:1904.04544v1</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/cy2wigeabfe5his5t7bn4pkzmm">fatcat:cy2wigeabfe5his5t7bn4pkzmm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191023052631/https://arxiv.org/pdf/1904.04544v1.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f2/b8/f2b8114f26ba3cd3445c038448b0b8c64de03f1f.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/1904.04544v1" title="arxiv.org access"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> arxiv.org </button> </a>

Dynamic State and Parameter Estimation Applied to Neuromorphic Systems

Emre Ozgur Neftci, Bryan Toth, Giacomo Indiveri, Henry D. I. Abarbanel
<span title="">2012</span> <i title="MIT Press - Journals"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rckx6fqoszfvva5c53bqivu5am" style="color: black;">Neural Computation</a> </i> &nbsp;
However, for both biological and hardware systems, it is often difficult to estimate the parameters of the model such that they are meaningful to the studied experimental system, especially when these  ...  Our results suggest that this method can become a very useful tool for model-based identification and configuration of neuromorphic multi-chip VLSI systems.  ...  Douglas for discussion and support, Shih-Chi Liu for discussion and review and the reviewers for their useful comments.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/neco_a_00293">doi:10.1162/neco_a_00293</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/22428591">pmid:22428591</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nhtx4iuuvzfwtnzlkbh2ozunli">fatcat:nhtx4iuuvzfwtnzlkbh2ozunli</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160124162705/http://scandle.eu/publications/papers/NECO-03-11-1435.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/c1/5e/c15eaabfd2bd7c560acda7dc3446798cc3428a2c.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1162/neco_a_00293"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> mitpressjournals.org </button> </a>

Trial-by-trial estimation of amplitude and latency variability in neuronal spike trains

Anil Bollimunta, Kevin H. Knuth, Mingzhou Ding
<span title="">2007</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/huhco7lwxvct3fbbxk44mmpflu" style="color: black;">Journal of Neuroscience Methods</a> </i> &nbsp;
We propose to estimate the amplitude and latency variability in single-trial neuronal spike trains on a trial-by-trial basis.  ...  Using a Bayesian inference framework we derive an iterative fixedpoint algorithm from which the single-trial amplitude scaling factors and latency shifts are estimated.  ...  However, the majority of the previously published methods for estimating single-trial parameters in neuronal spike trains have focused on either the amplitude variability or the latency variability.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.jneumeth.2006.08.007">doi:10.1016/j.jneumeth.2006.08.007</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/17000007">pmid:17000007</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/pdca64knmrfoziw6egnm7hn5vi">fatcat:pdca64knmrfoziw6egnm7hn5vi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20090116002457/http://knuthlab.rit.albany.edu/papers/Bollimunta2007.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1c/fe/1cfe7f7b82ecf8442f4cea46ae3cc43d5363f598.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.jneumeth.2006.08.007"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Role of Multiple-Scale Modeling of Epilepsy in Seizure Forecasting

Levin Kuhlmann, David B. Grayden, Fabrice Wendling, Steven J. Schiff
<span title="">2015</span> <i title="Ovid Technologies (Wolters Kluwer Health)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zopvhltxurfttc52jrpum42yp4" style="color: black;">Journal of clinical neurophysiology</a> </i> &nbsp;
Therefore, a natural question is raised: can computational models of epilepsy be used to improve these methods?  ...  Here we review the literature on the multiple-scale neural modelling of epilepsy and the use of such models to infer physiological changes underlying epilepsy and epileptic seizures.  ...  Model-based inference of physiological changes underlying epilepsy Methods for estimation of states and parameters from limited measurements often operate either by a sample-by-sample or window-by-window  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1097/wnp.0000000000000149">doi:10.1097/wnp.0000000000000149</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/26035674">pmid:26035674</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4455036/">pmcid:PMC4455036</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/oiime3h2ejdslajqib45ggqaoa">fatcat:oiime3h2ejdslajqib45ggqaoa</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200210103843/http://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC4455036&amp;blobtype=pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d6/f1/d6f15c378f26db95a2ab9000036dfe146e1b0823.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1097/wnp.0000000000000149"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4455036" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Estimation of neural network model parameters from local field potentials (LFPs)

Jan-Eirik W. Skaar, Alexander J. Stasik, Espen Hagen, Torbjørn V. Ness, Gaute T. Einevoll, Arnd Roth
<span title="2020-03-10">2020</span> <i title="Public Library of Science (PLoS)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ch57atmlprauhhbqdf7x4ytejm" style="color: black;">PLoS Computational Biology</a> </i> &nbsp;
All network parameters could be very accurately estimated, suggesting that LFPs indeed can be used for network model validation.  ...  We assessed how accurately the three model parameters could be estimated from power spectra of stationary 'background' LFP signals by application of convolutional neural nets (CNNs).  ...  trained to estimate a single parameter (single predictions).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1371/journal.pcbi.1007725">doi:10.1371/journal.pcbi.1007725</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/32155141">pmid:32155141</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iaks2ceuwjgefjirnelowlkjoq">fatcat:iaks2ceuwjgefjirnelowlkjoq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201107065839/https://www.duo.uio.no/bitstream/handle/10852/78051/Skaar+et+al.+-+2020+-+Estimation+of+neural+network+model+parameters+from+local+field+potentials+%28LFPs%29.pdf?sequence=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/80/be/80be5c554ee9beb80a43fb0470e14e7619b4bb93.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1371/journal.pcbi.1007725"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> plos.org </button> </a>

Extracting synaptic conductances from single membrane potential traces

M. Pospischil, Z. Piwkowska, T. Bal, A. Destexhe
<span title="">2009</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/l52eh66fdzhhbmbsefbbyzwkaq" style="color: black;">Neuroscience</a> </i> &nbsp;
The VmT method holds promises for extracting conductances from single-trial measurements, which has a high potential for in vivo applications.  ...  The method is illustrated using models and is tested on guinea-pig visual cortex neurons in vitro using dynamic-clamp experiments.  ...  Color codes the relative deviation between model parameters and their estimates using the method (note the different scales for means/SDs). A. Deviation in the mean of excitatory conductance (g e0 ).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.neuroscience.2008.10.033">doi:10.1016/j.neuroscience.2008.10.033</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/19027831">pmid:19027831</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7w3oeis7h5hnjavdsgcmy5yvy4">fatcat:7w3oeis7h5hnjavdsgcmy5yvy4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20191022045856/https://arxiv.org/pdf/0807.3238v1.pdf" title="fulltext PDF download [not primary version]" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <span style="color: #f43e3e;">&#10033;</span> <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/93/39/9339acbea3a6d0c8afe1512f177903f0d8e7b653.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.neuroscience.2008.10.033"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>
&laquo; Previous Showing results 1 &mdash; 15 out of 229,307 results