@ARTICLE{Park2008a,
  author = {Il Park and Ant\'onio R. C. Paiva and Thomas B. DeMarse and Jos\'e
	C. Pr\'incipe},
  title = {An efficient algorithm for continuous-time cross correlogram of spike
	trains},
  journal = {Journal of Neuroscience Methods},
  year = {2008},
  volume = {168},
  pages = {514--523},
  number = {2},
  month = mar,
  abstract = {We propose an efficient algorithm to compute the smoothed correlogram
	for the detection of temporal relationship between two spike trains.
	Unlike the conventional histogram-based correlogram estimations,
	the proposed algorithm operates on continuous time and does not bin
	either the spike train nor the correlogram. Hence it can be more
	precise in detecting the effective delay between two recording sites.
	Moreover, it can take advantage of the higher temporal resolution
	of the spike times provided by the current recording methods. The
	Laplacian kernel for smoothing enables efficient computation of the
	algorithm. We also provide the basic statistics of the estimator
	and a guideline for choosing the kernel size. This new technique
	is demonstrated by estimating the effective delays in a neuronal
	network from synthetic data and recordings of dissociated cortical
	tissue.},
  doi = {10.1016/j.jneumeth.2007.10.005},
  owner = {memming},
  timestamp = {2007.10.21}
}

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