Encyclopedia of Computational Neuroscience

Living Edition
| Editors: Dieter Jaeger, Ranu Jung

Correlation Analysis of Parallel Spike Trains

  • Jos J. EggermontEmail author
Living reference work entry

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DOI: https://doi.org/10.1007/978-1-4614-7320-6_390-2



Cross-correlation is a measure of the similarity of two signals as a function of the time lag or lead applied to one of the signals. In case the two signals are simultaneously recorded spike trains, the cross-correlation becomes a count of the number of coincidences of firing for the two spike trains as a function of the time delay between them. If one considers one spike train as the input to a system and the other spike train as the output, then the cross-correlation function between the input and output spike trains normalized on the input autocorrelation function is equal to the impulse response of the linear part of the system. Cross-correlation can also, and in the nervous system more generally, result from common input to the two spike trains, i.e., from providing a sensory stimulus or from rhythmic or other spontaneous activity in the brain.

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Authors and Affiliations

  1. 1.Department of Physiology and PharmacologyUniversity of CalgaryCalgaryCanada
  2. 2.Department of PsychologyUniversity of CalgaryCalgaryCanada

Section editors and affiliations

  • Sonja Grün
    • 1
    • 2
  1. 1.Lab for Statistical Neuroscience, Institute of Neuroscience and Medicine (INM–6) and Institute for Advanced Simulation (IAS–6)Jülich Research Centre and JARAJülichGermany
  2. 2.Theoretical Systems NeurobiologyRWTH Aachen UniversityAachenGermany