We have reached the second half of 2020 and thus arrived at the seventh edition of MaxWell Monthly Must-Reads. In the first four, we mainly highlighted scientific topics. In January we focused on Axons, in February on Retina and in March we picked Organoids as our main topic. Furthermore, during times of COVID-19 in April and May, we highlighted Neurons and Viruses and Spike Sorting! Last month, during ISSCR 2020, we highlighted Human iPSC-Derived Neurons.

For this edition we decided to focus on Burst Detection! The bursting phenomenon is a periodic increase in neuronal spiking rate. Bursting can be detected at single-cell level or at network-level among synaptically connected neurons. In vitro neuronal cell cultures often mature into synchronized bursting networks, and bursting is thought to be a highly relevant phenomenon both in-vivo and in-vitro to handle and store information. Several burst detection methods have been developed in order to automatically detect and characterize neuronal bursting. We decided to highlight the article by Matsuda et al. concerning a 4-step method to detect synchronised bursts!

Detection of synchronized burst firing in cultured human induced pluripotent stem cell-derived neurons using a 4-step method.
by Naoki Matsuda, Aoi Odawara, H.Katoh, N.Okuyama, Remi Yokoi and Ikuro Suzuki. Biochemical and Biophysical Research Communications. March 2018.

In this MMM edition, we featured the 2018 article by Matsuda N. et al. titled “Detection of synchronized burst firing in cultured human induced pluripotent stem cell-derived neurons using a 4-step method” published in Biochemical and Biophysical Research Communications. The 4-step method for burst detection is applied to micro-electrode array (MEA) data in order to isolate synchronized burst firing (SBF) events in human neuronal network. The authors focus on the extraction of SBF event rate, SBF event duration, and the number of spikes in SBF event, which are all relevant metrics to characterize the functional phenotype of neuronal cultures and to assess drug effects. The main advantages of the developed method are (1) increased separability of continuous SBF events, (2) improved detection of weak SBF events, and (3) reduction false SBV event detection.

Read the paper here.

Besides the above-mentioned paper, four other publications that are highly relevant to the topic of Burst Detection are found below:

  1. Burst Detection Methods.
    by Ellese Cotterill and Stephen Egle. In Vitro Neuronal Networks. May 2019.
    Read the paper here.
  2. Emergence of Bursting Activity in Connected Neuronal Sub-Populations.
    by Marta Bisio, Alessandro Bosca, Valentina Pasquale, Luca Berdondini and Michela Chiappalone. PLOS One. September 2014.
    Read the paper here.
  3. A comparison of computational methods for detecting bursts in neuronal spike trains and their application to human stem cell-derived neuronal networks.
    by Ellese Cotterill, Paul Charlesworth, Christopher Thomas, Ole Paulsen, and Stephen Eglen. Journal of Neurophysiology. August 2016.
    Read the paper here. 
  4. Parameters for burst detection.
    by Douglas Bakkum, Milos Radivojevic, Urs Frey, Felix Franke, Andreas Hierlemann and Hirokazu Takahashi. Frontiers in Computational Neuroscience. January 2014.
    Read the paper here.