{"publist_id":"2482","date_created":"2018-12-11T12:04:56Z","volume":93,"oa":1,"intvolume":"        93","publisher":"Elsevier","year":"2008","status":"public","quality_controlled":0,"title":"Decoding spike timing: The differential reverse-correlation method","doi":"10.1016/j.biosystems.2008.04.011","page":"90 - 100","author":[{"orcid":"0000-0002-6699-1455","id":"3D494DCA-F248-11E8-B48F-1D18A9856A87","full_name":"Gasper Tkacik","last_name":"Tkacik","first_name":"Gasper"},{"last_name":"Magnasco","first_name":"Marcelo","full_name":"Magnasco, Marcelo O"}],"day":"01","publication":"Biosystems","type":"journal_article","date_updated":"2021-01-12T07:51:53Z","month":"07","issue":"1-2","date_published":"2008-07-01T00:00:00Z","extern":1,"citation":{"short":"G. Tkačik, M. Magnasco, Biosystems 93 (2008) 90–100.","apa":"Tkačik, G., &#38; Magnasco, M. (2008). Decoding spike timing: The differential reverse-correlation method. <i>Biosystems</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.biosystems.2008.04.011\">https://doi.org/10.1016/j.biosystems.2008.04.011</a>","ista":"Tkačik G, Magnasco M. 2008. Decoding spike timing: The differential reverse-correlation method. Biosystems. 93(1–2), 90–100.","chicago":"Tkačik, Gašper, and Marcelo Magnasco. “Decoding Spike Timing: The Differential Reverse-Correlation Method.” <i>Biosystems</i>. Elsevier, 2008. <a href=\"https://doi.org/10.1016/j.biosystems.2008.04.011\">https://doi.org/10.1016/j.biosystems.2008.04.011</a>.","ama":"Tkačik G, Magnasco M. Decoding spike timing: The differential reverse-correlation method. <i>Biosystems</i>. 2008;93(1-2):90-100. doi:<a href=\"https://doi.org/10.1016/j.biosystems.2008.04.011\">10.1016/j.biosystems.2008.04.011</a>","ieee":"G. Tkačik and M. Magnasco, “Decoding spike timing: The differential reverse-correlation method,” <i>Biosystems</i>, vol. 93, no. 1–2. Elsevier, pp. 90–100, 2008.","mla":"Tkačik, Gašper, and Marcelo Magnasco. “Decoding Spike Timing: The Differential Reverse-Correlation Method.” <i>Biosystems</i>, vol. 93, no. 1–2, Elsevier, 2008, pp. 90–100, doi:<a href=\"https://doi.org/10.1016/j.biosystems.2008.04.011\">10.1016/j.biosystems.2008.04.011</a>."},"publication_status":"published","main_file_link":[{"url":"http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2792887","open_access":"1"}],"abstract":[{"text":"It is widely acknowledged that detailed timing of action potentials is used to encode information, for example, in auditory pathways; however, the computational tools required to analyze encoding through timing are still in their infancy. We present a simple example of encoding, based on a recent model of time-frequency analysis, in which units fire action potentials when a certain condition is met, but the timing of the action potential depends also on other features of the stimulus. We show that, as a result, spike-triggered averages are smoothed so much that they do not represent the true features of the encoding. Inspired by this example, we present a simple method, differential reverse correlations, that can separate an analysis of what causes a neuron to spike, and what controls its timing. We analyze with this method the leaky integrate-and-fire neuron and show the method accurately reconstructs the model's kernel.","lang":"eng"}],"_id":"3744"}