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Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|June 12, 2012
Detection limit for rate fluctuations in inhomogeneous Poisson processesToshiaki Shintani, Shigeru ShinomotoNeural Networks : the Official Journal of the International Neural Network Society|May 19, 2010
Fitting a stochastic spiking model to neuronal current injection dataShigeru ShinomotoNeural Computation|September 17, 2011
Optimizing time histograms for non-Poissonian spike trainsTakahiro Omi, Shigeru ShinomotoNeuroscience Research|August 4, 2024
Inference of monosynaptic connections from parallel spike trains: A reviewRyota Kobayashi, Shigeru ShinomotoScientific Reports|March 5, 2026
Comparing effective and functional connectivityShigeru Shinomoto, Yasuhiro TsuboAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference|October 11, 2013
Estimating inputs and an internal neuronal parameter from a single spike trainShigeru Shinomoto, Hideaki KimMathematical Biosciences and Engineering : MBE|November 20, 2013
Estimating nonstationary inputs from a single spike train based on a neuron model with adaptationHideaki Kim, Shigeru ShinomotoPhysical Review. E, Statistical, Nonlinear, and Soft Matter Physics|May 16, 2014
Bursting transition in a linear self-exciting point processTomokatsu Onaga, Shigeru ShinomotoBio Systems|February 27, 2007
Inference of intrinsic spiking irregularity based on the Kullback-Leibler informationShinsuke Koyama, Shigeru ShinomotoPageof 5