Self-organized neuronal subpopulations and network morphology underlying superbursts

Byoungsoo Kim, Kyoung J. Lee

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


Neural bursts are an important phenomenon that needs to be understood for their relevance to many different neurological diseases as well as neural computations. While there are different types of neuronal bursts, in this study we investigate the nature of population (as opposed to intrinsic cell-level) bursts, in particular, superbursts (SBs) that are a small (∼100 ms) packet of several population bursts (PBs). It has been suggested that neuronal PBs occur when there exists a delicate balance of system-wide excitation and inhibition and when recurrent excitation loops exist in the network. However, there has been no rigorous investigation on the relation between network morphology and (super)burst dynamics. Here we investigate the important issue based on a well-established Izhikevich network model of integrate-fire neurons. We have employed the overall conduction delay as our control parameter for tuning network morphology as well as its matching burst dynamics. Interestingly, we found that initially identical neurons self-organize to develop several distinct neuronal subpopulations, which are characterized by different spike firing patterns as well as local network properties. Moreover, a few different motifs of SB emerge according to a distinct mixture of neuronal subpopulations that, on average, fire at slightly different phases. Our analyses suggest that recurring motifs of different SBs reflect complex yet organized modular structures of different subpopulations.

Original languageEnglish
Article number043047
JournalNew Journal of Physics
Issue number4
Publication statusPublished - 2022 Apr 1

Bibliographical note

Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korea Government (MEST) (No. 2019R1A2C2005989). We thank Hyun Kim and Inhe Chung for critical reading of the manuscript.

Publisher Copyright:
© 2022 The Author(s). Published by IOP Publishing Ltd on behalf of the Institute of Physics and Deutsche Physikalische Gesellschaft.


  • complex network structure
  • neural (super)burst
  • neurodynamics
  • population dynamics

ASJC Scopus subject areas

  • General Physics and Astronomy


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