Percolation and Threshold-like Behavior in Multiple Sclerosis Progression

TL;DR

This work investigates whether Multiple Sclerosis progression, particularly the transition from RRMS to SPMS, can be described as a percolation/phase-transition process in brain networks. It synthesizes theory, cognitive-network percolation, connectomics, and clinical threshold concepts to evaluate the evidence for a percolation mechanism, identifying partial support in cognitive networks and progressive but nonthresholded hub-centric connectome changes. The findings suggest that while percolation-like dynamics are a useful lens, there is no direct evidence of a universal global percolation threshold governing RRMS-to-SPMS, and the disease more plausibly follows a continuum with domain-specific thresholds or reserve depletion. The authors propose testable predictions, including longitudinal percolation analyses, targeted lesion simulations, and high-frequency biomarker monitoring, to decisively adjudicate the role of percolation in MS progression and early-warning signaling.

Abstract

In this study we investigate the Percolation Hypothesis for Multiple Sclerosis Progression. The methodology relies on cross-reference analysis centered around a question: What is the evidence for a Percolation/phase-transition hypothesis in Multiple Sclerosis (MS), especially the idea that the RRMS dynamic balance can abruptly break akin to crossing a percolation threshold into SPMS? We identify theoretical models invoking percolation/critical thresholds, network/connectome studies assessing percolation robustness or threshold-like behavior, clinical markers showing thresholds or early-warning signals, and counter-evidence arguing for gradual/continuum transitions.