Methods, spike detection and sorting
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Yger P, Spampinato GLB, Esposito E, Lefebvre B, Deny S, Gardella C, Stimberg M, Jetter F, Zeck G, Picaud S, Duebel J, Marre O (2016) Fast and accurate spike sorting in vitro and in vivo for up to thousands of electrodes. bioRxiv.
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Biffi E, Ghezzi D, Pedrocchi A, Ferrigno G (2010) Development and validation of a spike detection and classification algorithm aimed at implementation on hardware devices. Comput Intell Neurosci:659050.
Krumin M, Reutsky I, Shoham S (2010) Correlation-based analysis and generation of multiple spike trains using hawkes models with an exogenous input. Front Comput Neurosci 4:147.
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Gullo F, Maffezzoli A, Dossi E, Wanke E (2009) Short-latency cross- and autocorrelation identify clusters of interacting cortical neurons recorded from multi-electrode array. J Neurosci Methods 181:186-198.
Maccione A, Gandolfo M, Massobrio P, Novellino A, Martinoia S, Chiappalone M (2009) A novel algorithm for precise identification of spikes in extracellularly recorded neuronal signals. J Neurosci Methods 177:241-249.
Pasquale V, Martinoia S, Chiappalone M (2009) A self-adapting approach for the detection of bursts and network bursts in neuronal cultures. J Comput Neurosci.
Moulin C, Gliere A, Barbier D, Joucla S, Yvert B, Mailley P, Guillemaud R (2008) A new 3-D finite-element model based on thin-film approximation for microelectrode array recording of extracellular action potential. IEEE Trans Biomed Eng 55:683-692.
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Liang PJ (2006) A New Method for Multiple Spike Train Analysis Based on Information Discrepancy. LNCS 4232, pp. 30–38, 2006.
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