Template-Based Analysis of Age-Dependent Cortical Eigenmodes and Scalp EEG Forward Transfer in Infancy

Infancy poses a spatial-coordinate challenge for developmental EEG: cortical geometry, head geometry, and EEG forward propagation change rapidly, so a cortical coordinate system that is meaningful at one age may not be directly comparable at another. We addressed this question in a template-based computational analysis using age-specific infant anatomical templates distributed through MNE-Python. Specifically, we computed cortical Laplace-Beltrami (LB) eigenmodes (cortical harmonics), EEG forward models, and forward-projected eigenmode dictionaries. We asked which eigenmode orders are preferentially expressed at the scalp and whether independently computed age-specific eigenmode coordinates remain stable for cross-age comparison. Forward-projected scalp gain was concentrated in lower eigenmode orders across infancy, indicating a stable coarse-to-fine transfer profile. However, neighboring-age LB bases were only locally comparable by nominal mode index. Same-index modes showed local reordering and mode-index drift, and the same cortical pattern produced coefficient leakage into nearby modes when re-expressed in a neighboring-age basis. These template-level coordinate differences affected simulated downstream analyses: neighboring-age dictionaries were not fully substitutable in low-dimensional sensor space, and a fixed adult-derived basis was suboptimal for recovering same-index coordinates, with larger penalties in early- to mid-infancy. Sequential Procrustes tracking improved same-index consistency, supporting local alignment as a practical step toward age-aware coordinates. Because all quantitative summaries are derived from population-average templates and simulations, they should be interpreted as mechanistic evidence about coordinate-system effects rather than direct estimates of empirical EEG error. These results motivate age-parameterized or explicitly tracked cortical harmonic coordinates for longitudinal developmental EEG and related lifespan analyses.