227 related articles for article (PubMed ID: 24348527)
21. Statistical inference for assessing functional connectivity of neuronal ensembles with sparse spiking data.
Chen Z; Putrino DF; Ghosh S; Barbieri R; Brown EN
IEEE Trans Neural Syst Rehabil Eng; 2011 Apr; 19(2):121-35. PubMed ID: 20937583
[TBL] [Abstract][Full Text] [Related]
22. Spike train decoding without spike sorting.
Ventura V
Neural Comput; 2008 Apr; 20(4):923-63. PubMed ID: 18085990
[TBL] [Abstract][Full Text] [Related]
23. Model-based decoding, information estimation, and change-point detection techniques for multineuron spike trains.
Pillow JW; Ahmadian Y; Paninski L
Neural Comput; 2011 Jan; 23(1):1-45. PubMed ID: 20964538
[TBL] [Abstract][Full Text] [Related]
24. Identification of time-varying neural dynamics from spike train data using multiwavelet basis functions.
Xu S; Li Y; Guo Q; Yang XF; Chan RHM
J Neurosci Methods; 2017 Feb; 278():46-56. PubMed ID: 28062244
[TBL] [Abstract][Full Text] [Related]
25. Comparison of Different Spike Train Synchrony Measures Regarding Their Robustness to Erroneous Data From Bicuculline-Induced Epileptiform Activity.
Ciba M; Bestel R; Nick C; de Arruda GF; Peron T; Henrique CC; Costa LDF; Rodrigues FA; Thielemann C
Neural Comput; 2020 May; 32(5):887-911. PubMed ID: 32187002
[TBL] [Abstract][Full Text] [Related]
26. On the use of dynamic Bayesian networks in reconstructing functional neuronal networks from spike train ensembles.
Eldawlatly S; Zhou Y; Jin R; Oweiss KG
Neural Comput; 2010 Jan; 22(1):158-89. PubMed ID: 19852619
[TBL] [Abstract][Full Text] [Related]
27. State-space analysis of time-varying higher-order spike correlation for multiple neural spike train data.
Shimazaki H; Amari S; Brown EN; Grün S
PLoS Comput Biol; 2012; 8(3):e1002385. PubMed ID: 22412358
[TBL] [Abstract][Full Text] [Related]
28. Nonlinear point-process estimation of neural spiking activity based on variational Bayesian inference.
Xiao P; Liu X
J Neural Eng; 2022 Sep; 19(4):. PubMed ID: 35947962
[No Abstract] [Full Text] [Related]
29. Improvement of spike train decoder under spike detection and classification errors using support vector machine.
Kim KH; Kim SS; Kim SJ
Med Biol Eng Comput; 2006 Mar; 44(1-2):124-30. PubMed ID: 16929930
[TBL] [Abstract][Full Text] [Related]
30. Estimating summary statistics in the spike-train space.
Wu W; Srivastava A
J Comput Neurosci; 2013 Jun; 34(3):391-410. PubMed ID: 23053864
[TBL] [Abstract][Full Text] [Related]
31. Deconvolution of calcium imaging data using marked point processes.
Shibue R; Komaki F
PLoS Comput Biol; 2020 Mar; 16(3):e1007650. PubMed ID: 32163407
[TBL] [Abstract][Full Text] [Related]
32. Inference of neuronal network spike dynamics and topology from calcium imaging data.
Lütcke H; Gerhard F; Zenke F; Gerstner W; Helmchen F
Front Neural Circuits; 2013; 7():201. PubMed ID: 24399936
[TBL] [Abstract][Full Text] [Related]
33. Dependence of neuronal correlations on filter characteristics and marginal spike train statistics.
Tetzlaff T; Rotter S; Stark E; Abeles M; Aertsen A; Diesmann M
Neural Comput; 2008 Sep; 20(9):2133-84. PubMed ID: 18439140
[TBL] [Abstract][Full Text] [Related]
34. Spike train SIMilarity Space (SSIMS): a framework for single neuron and ensemble data analysis.
Vargas-Irwin CE; Brandman DM; Zimmermann JB; Donoghue JP; Black MJ
Neural Comput; 2015 Jan; 27(1):1-31. PubMed ID: 25380335
[TBL] [Abstract][Full Text] [Related]
35. Bayesian inference of functional connectivity and network structure from spikes.
Stevenson IH; Rebesco JM; Hatsopoulos NG; Haga Z; Miller LE; Körding KP
IEEE Trans Neural Syst Rehabil Eng; 2009 Jun; 17(3):203-13. PubMed ID: 19273038
[TBL] [Abstract][Full Text] [Related]
36. Spike sorting algorithms and their efficient hardware implementation: a comprehensive survey.
Zhang T; Rahimi Azghadi M; Lammie C; Amirsoleimani A; Genov R
J Neural Eng; 2023 Apr; 20(2):. PubMed ID: 36972585
[No Abstract] [Full Text] [Related]
37. Neural decoding with visual attention using sequential Monte Carlo for leaky integrate-and-fire neurons.
Li K; Ditlevsen S
PLoS One; 2019; 14(5):e0216322. PubMed ID: 31086375
[TBL] [Abstract][Full Text] [Related]
38. Using spike train distances to identify the most discriminative neuronal subpopulation.
Satuvuori E; Mulansky M; Daffertshofer A; Kreuz T
J Neurosci Methods; 2018 Oct; 308():354-365. PubMed ID: 30213547
[TBL] [Abstract][Full Text] [Related]
39. Bayesian decoding using unsorted spikes in the rat hippocampus.
Kloosterman F; Layton SP; Chen Z; Wilson MA
J Neurophysiol; 2014 Jan; 111(1):217-27. PubMed ID: 24089403
[TBL] [Abstract][Full Text] [Related]
40. Trial-by-trial estimation of amplitude and latency variability in neuronal spike trains.
Bollimunta A; Knuth KH; Ding M
J Neurosci Methods; 2007 Feb; 160(1):163-70. PubMed ID: 17000007
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
