Why is neural connection weight a weak predictor of correlated neural activity?

TL;DR

This paper explores why structural connectivity strength poorly predicts correlated neural activity, proposing a new framework based on network communication constraints to better understand brain dynamics.

Contribution

It introduces a novel general framework for brain network dynamics that accounts for the weak correlation between structural and functional connectivity.

Findings

Low SC-FC correlation explained by network communication constraints

Proposes a new perspective on brain network dynamics

Offers insights into the design principles of neural systems

Abstract

As the field of connectomics has matured, it has expanded from mapping the existence of connections between brain components to measuring the strength of connections. This information is increasingly accessible via methodologies such as pairing functional magnetic resonance (MR) imaging and MR tractography in the same human subject, as well as novel methods in non-human animals using optogenetics. Systems and network neuroscience have in recent years focused extensively on explaining correlation patterns of functional activity in the brain in terms of the degree of connectedness of brain components, the so-called functional connectivity-structural connectivity relationship (SC-FC). What has been surprising has been how low the SC-FC correlations are. Why is it that brain parts that are more well-connected appear not to engender more correlated activity between them? Several explanations have been proposed but one possibility has not been considered: perhaps more neural activity doesn't imply more functional involvement. This article examines this possibility and proposes a new general framework for understanding brain network dynamics based on the design constraints of large-scale network communication systems. With this new perspective, we may start to answer the article's main question, and perhaps others.