Temporal ordering of input modulates connectivity formation in a developmental neuronal network model of the cortex


Autoři: Caroline Hartley aff001;  Simon Farmer aff003;  Luc Berthouze aff004
Působiště autorů: Centre for Mathematics and Physics in the Life Sciences and Experimental Biology, University College London, London, United Kingdom aff001;  Department of Paediatrics, University of Oxford, Oxford, United Kingdom aff002;  Institute of Neurology, University College London, London, United Kingdom aff003;  Centre for Computational Neuroscience and Robotics, University of Sussex, Falmer, Brighton, United Kingdom aff004
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pone.0226772

Souhrn

Preterm infant brain activity is discontinuous; bursts of activity recorded using EEG (electroencephalography), thought to be driven by subcortical regions, display scale free properties and exhibit a complex temporal ordering known as long-range temporal correlations (LRTCs). During brain development, activity-dependent mechanisms are essential for synaptic connectivity formation, and abolishing burst activity in animal models leads to weak disorganised synaptic connectivity. Moreover, synaptic pruning shares similar mechanisms to spike-timing dependent plasticity (STDP), suggesting that the timing of activity may play a critical role in connectivity formation. We investigated, in a computational model of leaky integrate-and-fire neurones, whether the temporal ordering of burst activity within an external driving input could modulate connectivity formation in the network. Connectivity evolved across the course of simulations using an approach analogous to STDP, from networks with initial random connectivity. Small-world connectivity and hub neurones emerged in the network structure—characteristic properties of mature brain networks. Notably, driving the network with an external input which exhibited LRTCs in the temporal ordering of burst activity facilitated the emergence of these network properties, increasing the speed with which they emerged compared with when the network was driven by the same input with the bursts randomly ordered in time. Moreover, the emergence of small-world properties was dependent on the strength of the LRTCs. These results suggest that the temporal ordering of burst activity could play an important role in synaptic connectivity formation and the emergence of small-world topology in the developing brain.

Klíčová slova:

Network analysis – Neurons – Electroencephalography – Neural networks – Depression – Infants – Clustering coefficients – Neuronal plasticity


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