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Nebojsa Bozanic - Publications

Affiliations: 
Institute for complex systems (ISC) CNR, Florence, Italy, Firenze, Toscana, Italy 
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8 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2021 Mijatovic G, Loncar-Turukalo T, Bozanic N, Milosavljevic N, Storchi R, Faes L. A Measure of Concurrent Neural Firing Activity Based on Mutual Information. Neuroinformatics. PMID 33852134 DOI: 10.1007/s12021-021-09515-w  0.45
2017 Satuvuori E, Mulansky M, Bozanic N, Malvestio I, Zeldenrust F, Lenk K, Kreuz T. Measures of spike train synchrony for data with multiple time scales. Journal of Neuroscience Methods. PMID 28583477 DOI: 10.1016/J.Jneumeth.2017.05.028  0.647
2015 Kreuz T, Mulansky M, Bozanic N. SPIKY: a graphical user interface for monitoring spike train synchrony. Journal of Neurophysiology. 113: 3432-45. PMID 25744888 DOI: 10.1186/1471-2202-14-S1-P225  0.791
2015 Kreuz T, Bozanic N, Mulansky M. SPIKE-Synchronization: a parameter-free and time-resolved coincidence detector with an intuitive multivariate extension Bmc Neuroscience. 16. DOI: 10.1186/1471-2202-16-S1-P170  0.801
2015 Mulansky M, Bozanic N, Kreuz T. Time-resolved and parameter-free measures of spike train synchrony: properties and applications Bmc Neuroscience. 16. DOI: 10.1186/1471-2202-16-S1-P133  0.8
2015 Mulansky M, Bozanic N, Sburlea A, Kreuz T. A guide to time-resolved and parameter-free measures of spike train synchrony Proceedings of 1st International Conference On Event-Based Control, Communication and Signal Processing, Ebccsp 2015. DOI: 10.1109/EBCCSP.2015.7300693  0.794
2014 Kreuz T, Bozanic N. SPIKY: A graphical user interface for tracking spike train similarity Bmc Neuroscience. 15. DOI: 10.1186/1471-2202-15-S1-P201  0.852
2013 Kreuz T, Bozanic N. Using spike train distances to identify the most discriminative neuronal subpopulation Bmc Neuroscience. 14. DOI: 10.1186/1471-2202-14-S1-P35  0.781
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