Modeling driver cells in developing neuronal networks

PLoS Comput Biol. 2018 Nov 2;14(11):e1006551. doi: 10.1371/journal.pcbi.1006551. eCollection 2018 Nov.

Abstract

Spontaneous emergence of synchronized population activity is a characteristic feature of developing brain circuits. Recent experiments in the developing neo-cortex showed the existence of driver cells able to impact the synchronization dynamics when single-handedly stimulated. We have developed a spiking network model capable to reproduce the experimental results, thus identifying two classes of driver cells: functional hubs and low functionally connected (LC) neurons. The functional hubs arranged in a clique orchestrated the synchronization build-up, while the LC drivers were lately or not at all recruited in the synchronization process. Notwithstanding, they were able to alter the network state when stimulated by modifying the temporal activation of the functional clique or even its composition. LC drivers can lead either to higher population synchrony or even to the arrest of population dynamics, upon stimulation. Noticeably, some LC driver can display both effects depending on the received stimulus. We show that in the model the presence of inhibitory neurons together with the assumption that younger cells are more excitable and less connected is crucial for the emergence of LC drivers. These results provide a further understanding of the structural-functional mechanisms underlying synchronized firings in developing circuits possibly related to the coordinated activity of cell assemblies in the adult brain.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain / cytology
  • Brain / physiology*
  • Humans
  • Models, Neurological*
  • Nerve Net / physiology*
  • Neurogenesis
  • Neurons / physiology*
  • Synapses / physiology

Grants and funding

The authors acknowledge financial support from the European Commission under the program "Marie Curie Network for Initial Training", project N. 289146, "Neural Engineering Transformative Technologies (NETT)" (SL, DAG, AT), by the A*MIDEX grant (No. ANR-11-IDEX-0001-02) and by the I-Site Paris Seine Excellence Initiative (No. ANR-16-IDEX-0008), both funded by the French Government programme "Investissements d’Avenir’’ (AT and DAG), from Ikerbasque (The Basque Foundation for Science) (PB) and from the Ministerio Economia, Industria y Competitividad of Spain (grant SAF2015-69484-R (MINECO/FEDER)) (PB). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.