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Unitary events in multiple single-neuron spiking activity: II. Nonstationary data.
Grun S, Diesmann M, Aertsen A.
Department
of Neurophysiology, Max-Planck Institute for Brain Research, D-60528
Frankfurt/Main, Germany. gruen@mpih-frankfurt.mpg.de
In order to
detect members of a functional group (cell assembly) in simultaneously
recorded neuronal spiking activity, we adopted the widely used
operational definition that membership in a common assembly is
expressed in near-simultaneous spike activity. Unitary event analysis,
a statistical method to detect the significant occurrence of coincident
spiking activity in stationary data, was recently developed (see the
companion article in this issue). The technique for the detection of
unitary events is based on the assumption that the underlying processes
are stationary in time. This requirement, however, is usually not
fulfilled in neuronal data. Here we describe a method that properly
normalizes for changes of rate: the unitary events by moving window
analysis (UEMWA). Analysis for unitary events is performed separately
in overlapping time segments by sliding a window of constant width
along the data. In each window, stationarity is assumed. Performance
and sensitivity are demonstrated by use of simulated spike trains of
independently firing neurons, into which coincident events are
inserted. If cortical neurons organize dynamically into functional
groups, the occurrence of near-simultaneous spike activity should be
time varying and related to behavior and stimuli. UEMWA also accounts
for these potentially interesting nonstationarities and allows locating
them in time. The potential of the new method is illustrated by results
from multiple single-unit recordings from frontal and motor cortical
areas in awake, behaving monkey.
PMID: 11747535 [PubMed - indexed for MEDLINE]
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