Synapse efficiency diverges due to synaptic pruning following over-growth

TL;DR

This paper analytically investigates how synaptic pruning after over-growth affects synapse efficiency, revealing divergence at low connection rates and identifying an optimal rate for memory performance.

Contribution

It provides an analytical understanding of synapse efficiency divergence and optimal connection rates following synaptic over-growth and pruning.

Findings

Synapse efficiency diverges as O(log c) when connection rate c is very small.

An optimal connection rate exists that maximizes memory performance under fixed synapse number.

Pruning following over-growth universally enhances synapse efficiency in brain development.

Abstract

In the development of the brain, it is known that synapses are pruned following over-growth. This pruning following over-growth seems to be a universal phenomenon that occurs in almost all areas -- visual cortex, motor area, association area, and so on. It has been shown numerically that the synapse efficiency is increased by systematic deletion. We discuss the synapse efficiency to evaluate the effect of pruning following over-growth, and analytically show that the synapse efficiency diverges as O(log c) at the limit where connecting rate c is extremely small. Under a fixed synapse number criterion, the optimal connecting rate, which maximize memory performance, exists.