Synaptic Scaling Balances Learning in a Spiking Model of Neocortex

TL;DR

This paper introduces synaptic scaling into a biologically-realistic spiking neocortex model, demonstrating its necessity for balancing learning-induced synaptic changes while preserving activity and oscillatory rhythm adaptations.

Contribution

It presents a novel integration of synaptic scaling with STDP in a detailed neocortical model, highlighting its role in maintaining activity balance during learning.

Findings

Synaptic scaling is essential for balancing potentiation and atrophy.

Scaling maintains activity levels without disrupting learning.

The model successfully adapts oscillatory rhythms through scaling.

Abstract

Learning in the brain requires complementary mechanisms: potentiation and activity-dependent homeostatic scaling. We introduce synaptic scaling to a biologically-realistic spiking model of neocortex which can learn changes in oscillatory rhythms using STDP, and show that scaling is necessary to balance both positive and negative changes in input from potentiation and atrophy. We discuss some of the issues that arise when considering synaptic scaling in such a model, and show that scaling regulates activity whilst allowing learning to remain unaltered.