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

Caroline Hartley,Simon Farmer,Luc Berthouze,William W Lytton

doi:10.1371/journal.pone.0226772

Caroline Hartley, Simon Farmer + Show 2 more

Open Access

https://doi.org/10.1371/journal.pone.0226772

Copy DOI

Abstract

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.

Highlights

Network connectivity shapes activity and modulates information transfer in the brain
The external input which provides the long-range temporal correlations (LRTCs) within our model is on the macroscopic scale, with bursts originating from non-cortical sources such as the subplate [12, 13], our focus here is on the effect such macroscopic phenomenon has on connectivity formation at the microscopic scale
In the case where the network was driven with burst dynamics that exhibit LRTCs, the sequence of inter-burst intervals (IBIs) exhibited long-range temporal correlations with a Hurst exponent (H) greater than 0.5

Summary

Methods

Individual neuronal dynamics were modelled as leaky integrate-and-fire neurones described by the differential equation dV dt 1⁄4 À gLðV À VrÞ þ IðtÞ ð1Þ where V is the membrane potential of the neurone, Vr is the resting potential, gL is the leak conductance and I(t) is the input (both external input and input from other neurones within the system). When the neurone reaches a threshold membrane potential Vthres it fires and is reset to Vreset. For all neurones in the simulations Vthres = −54 mV, Vr = −70 mV, Vreset = −60 mV [50]. The leak conductances were randomly chosen from a normal distribution with mean 0.025 and standard deviation 0.005. This heterogeneity in the conductances leads to heterogeneity in the firing dynamics.

Results

Discussion

Conclusion