Mapping Individualized Developmental Imbalance in Youth and Its Association with Psychopathology

preprint OA: closed
Full text JSON View at publisher

Abstract

The emergence of psychiatric symptoms during adolescence is increasingly hypothesized as arising from maturational imbalance across brain systems. However, this concept largely lacks quantitative grounding, which requires measuring fine-grained imbalance patterns that accurately capture acceleration or delay relative to normative developmental trajectories of brain regions. To address this gap, we leverage predictive normative modeling to learn models that predict chronological age from regional multivariate functional connectivity patterns. We demonstrate that these region-specific models are highly generalizable across independent cohorts and capture greater developmental effects than traditional functional connectivity metrics. From these models, we then derive a region-wise Relative Maturity (RM) index that quantifies individualized, region-specific deviations from normative development. Rigorous cross-cohort and longitudinal evaluations across four datasets show that RM maps are reproducible, subject-specific fingerprints of neurodevelopmental imbalance. These fingerprints are organized along continuous, low-dimensional axes aligned with intrinsic functional gradients and can predict dimensions of psychopathological vulnerability. Together, our findings establish RM as a robust, sensitive, and generalizable framework for quantifying individual vulnerability to psychopathology through system-level patterns of developmental imbalance.
Full text 1,548 characters · extracted from oa-doi-fallback · click to expand
Abstract The emergence of psychiatric symptoms during adolescence is increasingly hypothesized as arising from maturational imbalance across brain systems. However, this concept largely lacks quantitative grounding, which requires measuring fine-grained imbalance patterns that accurately capture acceleration or delay relative to normative developmental trajectories of brain regions. To address this gap, we leverage predictive normative modeling to learn models that predict chronological age from regional multivariate functional connectivity patterns. We demonstrate that these region-specific models are highly generalizable across independent cohorts and capture greater developmental effects than traditional functional connectivity metrics. From these models, we then derive a region-wise Relative Maturity (RM) index that quantifies individualized, region-specific deviations from normative development. Rigorous cross-cohort and longitudinal evaluations across four datasets show that RM maps are reproducible, subject-specific fingerprints of neurodevelopmental imbalance. These fingerprints are organized along continuous, low-dimensional axes aligned with intrinsic functional gradients and can predict dimensions of psychopathological vulnerability. Together, our findings establish RM as a robust, sensitive, and generalizable framework for quantifying individual vulnerability to psychopathology through system-level patterns of developmental imbalance. Competing Interest Statement The authors have declared no competing interest.

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2026) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

europepmc
last seen: 2026-05-20T01:45:00.602351+00:00