The simulation of the activity dependent neural network growth

TL;DR

This paper presents a mathematical model simulating activity-dependent neural network growth, emphasizing how external stimuli influence synaptic development and cortical connectivity through biochemical and activity-driven mechanisms.

Contribution

It introduces a set of differential equations modeling activity-dependent neural development, integrating biochemical guidance cues and neuronal activity for the first time.

Findings

Neural network development is sensitive to morpholess neurons.

Simulations show activity-dependent processes shape cortical connectivity.

Model highlights the role of calcium and neurotrophic factors in growth.

Abstract

It is currently accepted that cortical maps are dynamic constructions that are altered in response to external input. Experience-dependent structural changes in cortical microcurcuts lead to changes of activity, i.e. to changes in information encoded. Specific patterns of external stimulation can lead to creation of new synaptic connections between neurons. The calcium influxes controlled by neuronal activity regulate the processes of neurotrophic factors released by neurons, growth cones movement and synapse differentiation in developing neural systems. We propose a model for description and investigation of the activity dependent development of neural networks. The dynamics of the network parameters (activity, diffusion of axon guidance chemicals, growth cone position) is described by a closed set of differential equations. The model presented here describes the development of neural networks under the assumption of activity dependent axon guidance molecules. Numerical simulation shows that morpholess neurons compromise the development of cortical connectivity.