| Neuronal coding and spiking randomness L Kostal, P Lansky, JP Rospars European Journal of Neuroscience 26 (10), 2693-2701, 2007 | 107 | 2007 |
| Efficient olfactory coding in the pheromone receptor neuron of a moth L Kostal, P Lansky, JP Rospars PLoS Computational Biology 4 (4), e1000053, 2008 | 53 | 2008 |
| Patterns of spontaneous activity in single rat olfactory receptor neurons are different in normally breathing and tracheotomized animals P Duchamp‐Viret, L Kostal, M Chaput, P Lánsky, JP Rospars Journal of Neurobiology 65 (2), 97-114, 2005 | 52 | 2005 |
| Measures of statistical dispersion based on Shannon and Fisher information concepts L Kostal, P Lansky, O Pokora Information Sciences 235, 214-223, 2013 | 37 | 2013 |
| Metabolic cost of neuronal information in an empirical stimulus-response model L Kostal, P Lansky, MD McDonnell Biological cybernetics 107, 355-365, 2013 | 33 | 2013 |
| Fano Factor: A Potentially Useful Information K Rajdl, P Lansky, L Kostal Frontiers in Computational Neuroscience 14, 569049, 2020 | 31 | 2020 |
| Similarity of interspike interval distributions and information gain in a stationary neuronal firing L Kostal, P Lansky Biological cybernetics 94 (2), 157-167, 2006 | 28 | 2006 |
| Information capacity in the weak-signal approximation L Kostal Physical Review E—Statistical, Nonlinear, and Soft Matter Physics 82 (2 …, 2010 | 24 | 2010 |
| Adaptive integrate-and-fire model reproduces the dynamics of olfactory receptor neuron responses in a moth M Levakova, L Kostal, C Monsempès, P Lucas, R Kobayashi Journal of the Royal Society Interface 16 (157), 20190246, 2019 | 22 | 2019 |
| Optimal decoding and information transmission in Hodgkin–Huxley neurons under metabolic cost constraints L Kostal, R Kobayashi Biosystems 136, 3-10, 2015 | 22 | 2015 |
| Classification of stationary neuronal activity according to its information rate L Kostal, P Lánský Network: Computation in Neural Systems 17 (2), 193-210, 2006 | 21 | 2006 |
| The effect of interspike interval statistics on the information gainunder the rate coding hypothesis S Koyama, L Kostal Mathematical Biosciences & Engineering 11 (1), 63-80, 2013 | 19 | 2013 |
| Moth olfactory receptor neurons adjust their encoding efficiency to temporal statistics of pheromone fluctuations M Levakova, L Kostal, C Monsempès, V Jacob, P Lucas PLOS Computational Biology 14 (11), e1006586, 2018 | 18 | 2018 |
| Statistics of inverse interspike intervals: The instantaneous firing rate revisited L Kostal, P Lansky, M Stiber Chaos: An Interdisciplinary Journal of Nonlinear Science 28 (10), 2018 | 17 | 2018 |
| Entropy factor for randomness quantification in neuronal data K Rajdl, P Lansky, L Kostal Neural Networks 95, 57-65, 2017 | 17 | 2017 |
| Variability measures of positive random variables L Kostal, P Lansky, O Pokora PloS one 6 (7), e21998, 2011 | 17 | 2011 |
| Randomness and variability of the neuronal activity described by the Ornstein–Uhlenbeck model L Kostal, P Lansky, C Zucca Network: Computation in Neural Systems 18 (1), 63-75, 2007 | 16 | 2007 |
| Information capacity and its approximations under metabolic cost in a simple homogeneous population of neurons L Kostal, P Lansky Biosystems 112 (3), 265-275, 2013 | 15 | 2013 |
| Neuronal jitter: can we measure the spike timing dispersion differently L Kostal, P Marsalek Chin J Physiol 53 (6), 454-464, 2010 | 15 | 2010 |
| Performance breakdown in optimal stimulus decoding L Kostal, P Lansky, S Pilarski Journal of neural engineering 12 (3), 036012, 2015 | 13 | 2015 |
Ryota KobayashiThe University of Tokyo在 k.u-tokyo.ac.jp 的电子邮件经过验证
