title: Parameters for burst detection.
abstract: Bursts of action potentials within neurons and throughout networks are believed to serve roles in how neurons handle and store information, both in vivo and in vitro. Accurate detection of burst occurrences and durations are therefore crucial for many studies. A number of algorithms have been proposed to do so, but a standard method has not been adopted. This is due, in part, to many algorithms requiring the adjustment of multiple ad-hoc parameters and further post-hoc criteria in order to produce satisfactory results. Here, we broadly catalog existing approaches and present a new approach requiring the selection of only a single parameter: the number of spikes N comprising the smallest burst to consider. A burst was identified if N spikes occurred in less than T ms, where the threshold T was automatically determined from observing a probability distribution of inter-spike-intervals. Performance was compared vs. different classes of detectors on data gathered from in vitro neuronal networks grown over microelectrode arrays. Our approach offered a number of useful features including: a simple implementation, no need for ad-hoc or post-hoc criteria, and precise assignment of burst boundary time points. Unlike existing approaches, detection was not biased toward larger bursts, allowing identification and analysis of a greater range of neuronal and network dynamics.
authors.affiliation: Department of Biosystems Science and Engineering, ETH Zurich Basel, Switzerland ; Research Center for Advanced Science and Technology, The University of Tokyo Tokyo, Japan.
authors.forename: Douglas J
authors.initials: DJ
authors.lastname: Bakkum
authors.affiliation: Department of Biosystems Science and Engineering, ETH Zurich Basel, Switzerland.
authors.forename: Milos
authors.initials: M
authors.lastname: Radivojevic
authors.affiliation: RIKEN Quantitative Biology Center Kobe, Japan.
authors.forename: Urs
authors.initials: U
authors.lastname: Frey
authors.affiliation: Department of Biosystems Science and Engineering, ETH Zurich Basel, Switzerland.
authors.forename: Felix
authors.initials: F
authors.lastname: Franke
authors.affiliation: Department of Biosystems Science and Engineering, ETH Zurich Basel, Switzerland.
authors.forename: Andreas
authors.initials: A
authors.lastname: Hierlemann
authors.affiliation: Research Center for Advanced Science and Technology, The University of Tokyo Tokyo, Japan ; Japan Science and Technology Agency, Precursory Research for Embryonic Science and Technology Saitama, Japan.
authors.forename: Hirokazu
authors.initials: H
authors.lastname: Takahashi
keywords: burst detection; cell culture; information processing; microelectrode array; network dynamics