• Lawrence N Eisenman, Christine M Emnett, Jayaram Mohan, Charles F Zorumski, and Steven Mennerick.
• Department of Neurology, Washington University School of Medicine, St. Louis, Missouri; Taylor Family Institute for Innovative Psychiatric Research, Washington University School of Medicine, St. Louis, Missouri leisenman@wustl.edu.
• J. Neurophysiol. 2015 Aug 1; 114 (2): 1059-71.

AbstractIt is widely appreciated that neuronal networks exhibit patterns of bursting and synchrony that are not captured by simple measures such as average spike rate. These patterns can encode information or represent pathological behavior such as seizures. However, methods for quantifying bursting and synchrony are not agreed upon and can be confounded with spike rate measures. Previous validation has largely relied on in silico networks and single experimental conditions. How published measures of bursting and synchrony perform when applied to biological networks of varied average spike rate and subjected to varied experimental challenges is unclear. In multielectrode array recordings of network activity, we found that two mechanistically distinct drugs, cyclothiazide and bicuculline, produced equivalent increases in average spike rate but differed in bursting and synchrony. We applied several measures of bursting to the recordings (2 threshold interval methods and a surprise-based method) and found that a measure based on an average critical interval, adjusted for the array-wide spike rate, performed best in quantifying differential drug effects. To quantify synchrony, we compared a coefficient of variation-based measure, the recently proposed spike time tiling coefficient, the SPIKE-distance measure, and a global synchrony index. The spike time tiling coefficient, the SPIKE-distance measure, and the global synchrony index all captured a difference between drugs with the best performance exhibited by the global synchrony index. In summary, our exploration should aid other investigators by highlighting strengths and limitations of current methods. Copyright © 2015 the American Physiological Society.

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