A Scalable fMRI Estimate of Basal Ganglia Brain Tissue Iron for Use in Developmental and Translational Neuroscience

preprint OA: closed
📄 Open PDF Full text JSON View at publisher
Full text 2,868 characters · extracted from oa-doi-fallback · click to expand
ABSTRACT Dopaminergic (DA) function and basal ganglia neurobiology are central to reward learning, motivation, and cognitive control, and dysregulation of these systems contributes to neuropsychiatric conditions that emerge during development. Adolescence is marked by profound reorganization of DAergic basal ganglia circuitry, yet direct in vivo assessment of the DA system remains limited in youth. Brain tissue iron is a developmentally sensitive marker of DA-related neurobiology that can be measured non-invasively via magnetic resonance imaging (MRI). Iron is an essential co-factor for DA synthesis and a foundational metabolic resource that supports cellular metabolism, myelination, and energetic demands of the basal ganglia. T2*-weighted echo-planar imaging (EPI), collected during functional MRI (fMRI), is sensitive to magnetic susceptibility of non-heme brain iron. Leveraging this property, we demonstrate the validity and broad applicability of an iron-sensitive metric that can be derived from conventional single-echo fMRI: ΔR2*. In a longitudinal developmental dataset (N = 151; age range 12–31), ΔR2* showed high reliability, strong longitudinal stability, and validity via robust convergence with established quantitative relaxometry-based iron measures (R2* and R2’). Critically, ΔR2* can be retrospectively estimated from extant fMRI data and derived in large-scale consortium data repositories, demonstrated here in the Adolescent Brain and Cognitive Development (ABCD) baseline cohort (N = 8,366; ages 9–11). We show that ΔR2* captures known age-related increases in basal ganglia iron, highlighting neurodevelopmental sensitivity at population-scale. Together, these findings establish ΔR2* as a reliable, widely accessible marker of basal ganglia iron, enabling scalable investigation of lifespan trajectories and neuropsychiatric risk in existing and future datasets. Competing Interest Statement The authors have declared no competing interest. Footnotes Funding: Collection and distribution of the ABCD data were supported by National Institutes of Health (NIH) funding U01DA041048; U01DA050989; U01DA051016; U01DA041022; U01DA051018; U01DA051037; U01DA050987; U01DA041174; U01DA041106; U01DA041117; U01DA041028; U01DA041134; U01DA050988; U01DA051039; U01DA041156; U01DA041025; U01DA041120; U01DA051038; U01DA041148; U01DA041093; U01DA041089; U24DA041123; U24DA041147 This work was supported by the National Institute of Mental Health (R00MH127293 for H.S.T, C.H., and B. Larsen; 5RO1MH080243-07 for A.C.P., F.J.C., A.O., and B. Luna), the National Institute on Drug Abuse (NIDA; K23DA057486 to B.T.C.), the Brain and Behavior Research Foundation (BBRF; to A.C.P. and B.T.C.), the Jacobs Foundation (B.T.C.), and the Staunton Farm Foundation (A.C.P., F.J.C., B.Luna). Declaration of Interests: The authors declare no competing interests.

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
unpaywall
last seen: 2026-06-16T06:25:30.133384+00:00