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Detecting unitary events without discretization of time.
Grin S, Diesmann M, Grammont F, Riehle A, Aertsen A.
Department of Neurophysiology, Max-Planck-Institute for Brain Research, Frankfurt/Main, Germany. gruen@mpih-frankfurt.mpg.de
In
earlier studies we developed the 'Unitary Events' analysis (Grun S.
Unitary Joint-Events in Multiple-Neuron Spiking Activity: Detection,
Significance and Interpretation. Reihe Physik, Band 60. Thun,
Frankfurt/Main: Verlag Harri Deutsch, 1996.) to detect the presence of
conspicuous spike coincidences in multiple single unit recordings and
to evaluate their statistical significance. The method enabled us to
study the relation between spike synchronization and behavioral events
(Riehle A, Grun S, Diesmann M, Aertsen A. Spike synchronization and
rate modulation differentially involved in motor cortical function.
Science 1997;278:1950-1953.). There is recent experimental evidence
that the timing accuracy of coincident spiking events, which might be
relevant for higher brain function, may be in the range of 1-5 ms. To
detect coincidences on that time scale, we sectioned the observation
interval into short disjunct time slices ('bins'). Unitary Events
analysis of this discretized process demonstrated that coincident
events can indeed be reliably detected. However, the method looses
sensitivity for higher temporal jitter of the events constituting the
coincidences (Grun S. Unitary Joint-Events in Multiple-Neuron Spiking
Activity: Detection, Significance and Interpretation. Reihe Physik,
Band 60. Thun, Frankfurt/Main: Verlag Harri Deutsch, 1996.). Here we
present a new approach, the 'multiple shift' method (MS), which
overcomes the need for binning and treats the data in their (original)
high time resolution (typically 1 ms, or better). Technically,
coincidences are detected by shifting the spike trains against each
other over the range of allowed coincidence width and integrating the
number of exact coincidences (on the time resolution of the data) over
all shifts. We found that the new method enhances the sensitivity for
coincidences with temporal jitter. Both methods are outlined and
compared on the basis of their analytical description and their
application on simulated data. The performance on experimental data is
illustrated.
PMID: 10638816 [PubMed - indexed for MEDLINE]
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