Abstract(s)
Multielectrode array neuronal recordings in atrial ganglionated plexi
are characterized by low firing rates, marked non-stationarity, interplay with the
cardiovascular and pulmonary systems and artifacts generated by myocardial activity,
which creates challenges very different from brain recordings. To explore population
dynamics of intrinsic cardiac neurons, a jitter-based synchrony index has been defined
to quantify pairwise synchrony between neurons. In this paper, we extend this
synchrony index to multiple time series in order to monitor global (multivariate)
synchrony. Numerical techniques are developed to efficiently compute synchrony
indices and their statistical significance in a large number of time windows. A scaletime graphical representation is proposed to visualize synchrony in sliding windows of
varying lengths. This approach is validated in synthetic time series and in experimental
data sets recorded in 11 dogs. Results show the ability of the method to monitor
synchrony over time in neuron populations, between neurons and the cardiopulmonary
system and between neuron firing and electrical stimulation. These tools will facilitate
the exploration and robust quantitative analysis of multiple-hour recordings in cardiac
ganglionated plexi to efficiently identify relevant periods of activity in relation to
physiological or external stimuli and cardiac arrhythmia.