Abstract
In Chap. 8, Günther Palm describes his joint work with his colleague, George Gerstein, on introducing and applying different measures for statistical significance of cross-correlations in multiple-neuron spike train recordings.
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References
Aertsen AM, Gerstein GL, Habib MK, Palm G (1989) Dynamics of neuronal firing correlation: modulation of “effective connectivity”. J Neurophysiol 61(5):900–917. https://doi.org/10.1152/jn.1989.61.5.900
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Martignon L, von Hasseln H, Palm G (1993) Modelling stochastic networks: data to the connectivity structure. In: Herzog O, Christaller T, Schütt D (eds) Grundlagen und Anwendungen der Künstlichen Intelligenz—17. Fachtagung für Künstliche Intelligenz, Informatik aktuell, Subreihe Künstliche Intelligenz. Springer, Berlin, pp 50–58. https://doi.org/10.1007/978-3-642-78545-0
Martignon L, von Hassein H, Grün S, Aertsen A, Palm G (1995) Detecting higher-order interactions among the spiking events in a group of neurons. Biol Cybern 73(1):69–81. https://doi.org/10.1007/BF00199057
Palm G (2012) Novelty, information and surprise. Springer, Berlin. https://doi.org/10.1007/978-3-642-29075-6
Palm G, Aertsen AMHJ, Gerstein GL (1988) On the significance of correlations among neuronal spike trains. Biol Cybern 59(1):1–11. https://doi.org/10.1007/BF00336885
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Palm, G. (2023). Significance of Spike Train Correlations. In: Aertsen, A., Grün, S., Maldonado, P.E., Palm, G. (eds) Introducing Computation to Neuroscience . Springer Series in Computational Neuroscience. Springer, Cham. https://doi.org/10.1007/978-3-030-87447-6_8
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DOI: https://doi.org/10.1007/978-3-030-87447-6_8
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