Higher-order interactions in brain microstructure reveal a redundancy-to-synergy crossover in quantitative MRI for multimodal biophysical modelling

Abstract Multi-parameter mapping (MPM) magnetic resonance imaging (MRI) provides parameters sensitive to myelin, iron and water. Conventional analyses treat these parameters individually or via pairwise correlations. We introduce O-information ( $$\\Omega$$ Ω ) as a proof-of-principle higher-order interaction framework to quantify how the three myelin-sensitive parameters (magnetisation transfer, longitudinal relaxation rate $${R}_{1}$$ R 1 and proton density) are interrelated beyond pairwise dependencies. We compute $$\\Omega$$ Ω from their joint distribution across cortical grey matter, subcortical grey matter and white-matter bundles and ask how $$\\Omega$$ Ω is modulated by the iron-sensitive transverse relaxation rate $${R}_{2}^{*}$$ R 2 ∗ in grey matter and by fibre architecture (neurite density and orientation dispersion) in white matter. In 22 healthy adults, $$\\Omega$$ Ω separates tissue classes (cortex near-balanced, subcortex mildly synergistic, white matter strongly synergistic), consistent in 21 of 22 participants. At matched voxel count per region, grey-matter $$\\Omega$$ Ω declines with $${R}_{2}^{*}$$ R 2 ∗ and changes sign from redundancy to synergy within the physiological $${R}_{2}^{*}$$ R 2 ∗ range, an effect carried by cortex. A minimal two-compartment forward model [1] ( $${R}_{2}^{*}\\propto \\left[{\\text{Fe}}\\right]$$ R 2 ∗ ∝ Fe , following Langkammer et al. 257:455–462, 2010 ) generates the same sign change using constants taken from the literature, but places it at systematically lower $${R}_{2}^{*}$$ R 2 ∗ . Fitting a single effective iron- $${R}_{1}$$ R 1 coupling closes the gap, at a value below the literature estimate. In white matter, $$\\Omega$$ Ω is only weakly coupled to $${R}_{2}^{*}$$ R 2