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Generation of Synthetic Spike Trains with Defined Pairwise Correlations

Ernst Niebur
2007 Neural Computation  
Pairs of spike trains with any pairwise correlation can be generated, and higher-order correlations are compatible with common synaptic input.  ...  Recent technological advances as well as progress in theoretical understanding of neural systems have created a need for synthetic spike trains with controlled mean rate and pairwise cross-correlation.  ...  The subject of this letter is the generation of sets of synthetic spike trains with controlled rates and cross-correlations.  ... 
doi:10.1162/neco.2007.19.7.1720 pmid:17521277 pmcid:PMC2633732 fatcat:5ph2c2keojhslcxqvfeagtmmy4

CalciumGAN: A Generative Adversarial Network Model for Synthesising Realistic Calcium Imaging Data of Neuronal Populations [article]

Bryan M. Li, Theoklitos Amvrosiadis, Nathalie Rochefort, Arno Onken
2020 arXiv   pre-print
Then, we train the model on real calcium signals recorded from the primary visual cortex of behaving mice and confirm that the deconvolved spike trains match the statistics of the recorded data.  ...  To this end, we adapt the WaveGAN architecture and train it with the Wasserstein distance.  ...  Acknowledgments and Disclosure of Funding  ... 
arXiv:2009.02707v2 fatcat:qg2cezbgwjb7rjcd6aunsv367y

Scalable and accurate method for neuronal ensemble detection in spiking neural networks

Rubén Herzog, Arturo Morales, Soraya Mora, Joaquín Araya, María-José Escobar, Adrian G. Palacios, Rodrigo Cofré, Jonathan David Touboul
2021 PLoS ONE  
To validate the performance and generality of our method, we generated synthetic data, where we found that our method accurately detects neuronal ensembles for a wide range of simulation parameters.  ...  We used spike trains of retinal ganglion cells obtained from multi-electrode array recordings under a simple ON-OFF light stimulus to test our method.  ...  With the core-cells and the activation sequence of each ensemble defined, a spike train was generated by the product c e a e (matrix) of dimension N × T.  ... 
doi:10.1371/journal.pone.0251647 pmid:34329314 pmcid:PMC8323916 fatcat:jpbhlur7xvh73ikqqbzvwejxtu

Detecting pairwise correlations in spike trains: an objective comparison of methods and application to the study of retinal waves [article]

Catherine Sarah Cutts, Stephen J Eglen
2014 biorxiv/medrxiv   pre-print
This coefficient, the correlation index and 33 other measures of correlation of spike times are blindly tested for the required properties on synthetic and experimental data.  ...  On the basis of this, we propose a measure (the Spike Time Tiling Coefficient) to replace the correlation index.  ...  The first spike train is the "master" train and the center-points of its bursts are generated according to a Poisson process with a given rate .  ... 
doi:10.1101/006635 fatcat:kwmapuasyzdddimwfcg5u2sfyy

Detecting Pairwise Correlations in Spike Trains: An Objective Comparison of Methods and Application to the Study of Retinal Waves

C. S. Cutts, S. J. Eglen
2014 Journal of Neuroscience  
This coefficient, the correlation index, and 33 other measures of correlation of spike times are blindly tested for the required properties on synthetic and experimental data.  ...  We list properties needed for a measure to fairly quantify and compare correlations and we propose a novel measure of correlation-the spike time tiling coefficient.  ...  The first spike train is the "master" train and the center-points of its bursts are generated according to a Poisson process with a given rate .  ... 
doi:10.1523/jneurosci.2767-14.2014 pmid:25339742 pmcid:PMC4205553 fatcat:vwcbgqhi3fgsxilhwad3fqkaku

Multivariate Autoregressive Modeling and Granger Causality Analysis of Multiple Spike Trains

Michael Krumin, Shy Shoham
2010 Computational Intelligence and Neuroscience  
Here, we use our recent results on correlation distortions in multivariate Linear-Nonlinear-Poisson spiking neuron models to derive generalized Yule-Walker-type equations for fitting "hidden" Multivariate  ...  The analysis of multiple neural spike train data could benefit significantly from existing methods for multivariate time-series analysis which have proven to be very powerful in the modeling and analysis  ...  Methods Synthetic Spike Train Generation.  ... 
doi:10.1155/2010/752428 pmid:20454705 pmcid:PMC2862319 fatcat:ji6t34t7q5anpeqhklw6bkppgy

Data driven generation of Purkinje cell spike train correlations to study input output relations in deep cerebellar nuclei neurons

Selva K Maran, Dieter Jaeger
2010 BMC Neuroscience  
Niebur E: Generation of synthetic spike trains with defined pairwise correlations. Neural Comput 2007, 19(7):1720-38. 2.  ...  Krumin M, Shoham S: Generation of spike trains with controlled autoand cross-correlation functions. Neural Comput 2009, 21(6):1642-64. 4. Brette R: Generation of correlated spike trains.  ...  Several analytical methods have been developed to generate sets of spike trains with specific correlations in spike times as well as spike rates [1] [2] [3] [4] .  ... 
doi:10.1186/1471-2202-11-s1-p116 pmcid:PMC3090817 fatcat:sq55ztmqsnfwxf5p3cpcqvexem

Generating Spike Trains with Specified Correlation Coefficients

Jakob H. Macke, Philipp Berens, Alexander S. Ecker, Andreas S. Tolias, Matthias Bethge
2009 Neural Computation  
Thus, for the realistic simulation and analysis of neural systems, it is essential to have efficient methods for generating artificial spike trains with specified correlation structure.  ...  Spike trains recorded from populations of neurons can exhibit substantial pairwise correlations between neurons and rich temporal structure.  ...  Generating Spike Trains with Defined Pairwise Correlation Structure 2.1 Sampling from a Multivariate Binary Distribution.  ... 
doi:10.1162/neco.2008.02-08-713 pmid:19196233 fatcat:7jrdmexqrngljlfv5ekdgzzto4

SIMNETS: a computationally efficient and scalable framework for identifying sub-networks of functionally similar neurons: Supplementary Information [article]

Jacqueline B Hynes, David M Brandman, Jonas B Zimmerman, John P Donoghue, Carlos E Vargas-Irwin
2018 bioRxiv   pre-print
the spike train outputs of each neuron across experimental conditions, before any comparisons are made between neurons.  ...  We validate the ability of our approach for detecting statistically and physiologically meaningful functional groupings in a population of synthetic neurons with known ground-truth, as well three publicly  ...  Pairwise distances are calculated between spike trains (S) generated by the same neuron using a spike train metric.  ... 
doi:10.1101/463364 fatcat:lbq3tq6agjah5oucxd2gbzzryu

Scalable and accurate automated method for neuronal ensemble detection in spiking neural networks [article]

Rubén Herzog, Arturo Morales, Soraya Mora, Joaquín Araya, María-José Escobar, Adrián G. Palacios, Rodrigo Cofré
2020 bioRxiv   pre-print
To validate the performance and generality of our method, we generated synthetic data, where we found that our method accurately detects neuronal ensembles for a wide range of simulation parameters.  ...  We used spike trains of retinal ganglion cells obtained from multi-electrode array recordings under a simple ON-OFF light stimulus to test our method.  ...  We proceeded 273 this way until reaching P E . 274 With the core-cells and the activation sequence of each ensemble defined, a spike train was generated by the product c e a e (matrix) of dimension N  ... 
doi:10.1101/2020.10.12.335901 fatcat:6gdc7rqc5fglnehjnyzafrutp4

Dimensionality Reduction on Spatio-Temporal Maximum Entropy Models of Spiking Networks [article]

Rubén Herzog, Maria-Jose Escobar, Rodrigo Cofre, Adrian G. Palacios, Bruno Cessac
2018 bioRxiv   pre-print
Here, we present a novel framework of dimensionality reduction for generalized MEM handling spatio-temporal correlations.  ...  As we show, this is quite a huge reduction compared to a randomly generated spike train, suggesting that the neuronal code, in these experiments, is highly compressible.  ...  For this raster 2 types of pairwise interactions are defined: spatial interactions (blue) and temporal interactions with R = 2, i.e. one time-step between spikes (red).  ... 
doi:10.1101/278606 fatcat:xc76sdvatbh5pfakeeunravxem

Spike Correlations – What Can They Tell About Synchrony?

Tatjana Tchumatchenko, Theo Geisel, Maxim Volgushev, Fred Wolf
2011 Frontiers in Neuroscience  
Surprisingly, despite the intense use of correlation coefficients in the design of synthetic spike trains, the construction of population models and the assessment of the synchrony level in live neuronal  ...  We showed that many features of pairwise spike correlations can be studied analytically in a tractable threshold model.  ...  Experimental assessment of pairwise subthreshold and spike correlations in vivo generally reveals a wide variety of pairwise spike correlation functions (Ts'o et al., 1986; Lampl et al., 1999; Yu and  ... 
doi:10.3389/fnins.2011.00068 pmid:21617732 pmcid:PMC3095812 fatcat:ps2affz255ejrgda6p52olokta

Clique Topology Reveals Intrinsic Geometric Structure in Neural Correlations: An Overview [article]

David Cox
2016 arXiv   pre-print
by geometric structure of hippocampal circuits, rather than being a consequence of positional coding.  ...  We highlight work done by Gusti et al. which introduces clique topology and verifies its applicability to neural feature extraction by showing that neural correlations in the rat hippocampus are determined  ...  Figure 4 : 4 Figure 4: Computation of pairwise correlation matrices from spike train data.  ... 
arXiv:1608.03463v1 fatcat:qxh6eintyjayrejifv6rfwzwkq

A Tractable Method for Describing Complex Couplings between Neurons and Population Rate

C. Gardella, O. Marre, T. Mora
2016 eNeuro  
Neurons within a population are strongly correlated, but how to simply capture these correlations is still a matter of debate.  ...  Recent studies have shown that the activity of each cell is influenced by the population rate, defined as the summed activity of all neurons in the population.  ...  These models can then be used to generate synthetic spike trains to calculate analytically response statistics, such as pairwise correlations, or to estimate the probability of particular spike trains.  ... 
doi:10.1523/eneuro.0160-15.2016 pmid:27570827 pmcid:PMC4989052 fatcat:a7a7hbixjzeyxmmhskuibonlai

Two-State Membrane Potential Fluctuations Driven by Weak Pairwise Correlations

Andrea Benucci, Paul F.M.J. Verschure, Peter König
2004 Neural Computation  
Physiological experiments demonstrate the existence of weak pairwise correlations of neuronal activity in mammalian cortex (Singer, 1993).  ...  The functional implications of this correlated activity are hotly debated (Roskies et al., 1999). Nevertheless, it is generally considered a widespread feature of cortical dynamics.  ...  The rationale behind the synthetic spike train generation algorithm is that for each pair of spike trains, there are intervals in time when the probability of correlated spiking activity is increased.  ... 
doi:10.1162/0899766041941871 pmid:15476604 fatcat:l6mfyihtljg73jo6tsyus3o7qm
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