Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics

Abstract

In this paper we propose a firing statistics based neuronal network burst detection algorithm for neuronal networks exhibiting highly variable action potential dynamics. Electrical activity of neuronal networks is generally analyzed by the occurrences of spikes and bursts both in time and space. Commonly accepted analysis tools employ burst detection algorithms based on predefined criteria. However, maturing neuronal networks, such as those originating from human embryonic stem cells (hESCs), exhibit highly variable network structure and time-varying dynamics. To explore the developing burst/spike activities of such networks, we propose a burst detection algorithm which utilizes the firing statistics based on interspike interval (ISI) histograms. Moreover, the algorithm calculates ISI thresholds for burst spikes as well as for pre-burst spikes and burst tails by evaluating the cumulative moving average (CMA) and skewness of the ISI histogram. Because of the adaptive nature of the proposed algorithm, its analysis power is not limited by the type of neuronal cell network at hand. We demonstrate the functionality of our algorithm with two different types of microelectrode array (MEA) data recorded from spontaneously active hESC-derived neuronal cell networks. The same data was also analyzed by two commonly employed burst detection algorithms and the differences in burst detection results are illustrated. The results demonstrate that our method is both adaptive to the firing statistics of the network and yields successful burst detection from the data. In conclusion, the proposed method is a potential tool for analyzing of hESC-derived neuronal cell networks and thus can be utilized in studies aiming to understand the development and functioning of human neuronal networks and as an analysis tool for in vitro drug screening and neurotoxicity assays.

Screening for Neurotoxicity with Microelectrode Array

“…In order to compute burst organization statistics, one must define what constitutes a burst. There have been a variety of definitions describing what constitutes a burst, along with different algorithms that define these interpretations quantitatively (Gourevitch & Eggermont, 2007;Kapucu et al, 2012). The most widely used algorithm is the Poisson-Surprise method (Kapucu et al, 2012;Legendy & Salcman, 1985).…”

Is the time right for in vitro neurotoxicity testing using human iPSC-derived neurons?

“…However, as also outlined in NC3R's Neuratect Crack-it Challenge (http://www.NC3Rs.org.uk), the use of human neurons is preferred for in vitro neurotoxicity testing. Still, the use of human neurons for MEA recordings has been limited (Heikkilä et al, 2009;Ylä-Outinen et al, 2010;Kapucu et al, 2012), while there is no indication that human-derived neuronal networks will not exhibit the same properties as primary rat cortical cultures.…”

Literature review on in vitro and alternative Developmental Neurotoxicity (DNT) testing methods

“…The 'Neuronal Network Endpoints' is data-wise the weakest, yet no promising system has been identified within these studies. Yet, as mentioned earlier, a promising human ESC-based model has been established for DNT testing purposes but has not been published with compounds yet -and thus was not recognized within this systematic review (Yla-Outinen et al, 2014, Kapucu et al, 2012. Differentiation of human ESC on multi electrode arrays (MEAs) was established within this work and neuronal network activities recorded.…”

“…However, so far there is far too few chemical testing data available to answer this question. One human ESC-based model has to be mentioned at this point which has been established for DNT testing purposes but has not been published with compounds yet -and thus was not recognized within this systematic review (Kapucu et al, 2012, Yla-Outinen et al, 2014. Differentiation of human ESC on multi electrode arrays (MEAs) was established within this work and neuronal network activities recorded.…”

“…In this systematic review, only very few publications were identified measuring electrical network activity using rodent, mainly rat primary cells (record numbers 1901, 2021, 2319, 20775, 23876). However, although it seems that this important endpoint can also be measured with hESC-derived neuronal cultures (Kapucu et al, 2012, Yla-Outinen et al, 2014 it is necessary to establish standardized protocols for human-based network formation with NS/PC-based methods. Moreover, there is the urgent need to show that current human DNT compounds (Grandjean and Landrigan, 2014) are indeed able to disturb human network formation.…”