Definition
In the correlation analysis of experimentally recorded parallel spike trains, one has to thoroughly consider the statistical features of the data in order to prevent false-positive results. Surrogate data, i.e., modified versions of the original spike trains, are used to assess the significance of spike correlation. The objective of surrogate data generation is to leave all statistical features of the original experimental data intact except those one wants to test for: these are to be destroyed.
Detailed Description
Generating artificial data from experimental data as a means for implementing a null hypothesis is becoming widely used. The reason is twofold: increasing computer power now allows for this type of approach, and it has become clear that the complexity of experimental data does not in general permit an analytical formulation of the null hypothesis. This is particularly true for the correlation analysis of parallel spike trains. Neglecting statistical features of...
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References
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Grün, S. (2020). Surrogate Data for Evaluation of Spike Correlation. In: Jaeger, D., Jung, R. (eds) Encyclopedia of Computational Neuroscience. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7320-6_411-2
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DOI: https://doi.org/10.1007/978-1-4614-7320-6_411-2
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Latest
Surrogate Data for Evaluation of Spike Correlation- Published:
- 09 August 2020
DOI: https://doi.org/10.1007/978-1-4614-7320-6_411-2
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Original
Surrogate Data for Evaluation of Spike Correlation- Published:
- 14 March 2014
DOI: https://doi.org/10.1007/978-1-4614-7320-6_411-1