EigenBrain maps cortical molecular architecture from functional, geometric, and structural eigenmodes
- 1University of Geneva
Abstract
Neurotransmitter receptor and transporter distributions shape neural communication across the cortex and underpin mechanistic interpretations of brain function. Magnetic resonance imaging (MRI)-derived eigenmodes, low-dimensional spatial patterns that capture the principal axes of cortical organization, are increasingly used to reconstruct brain maps and offer a potential route to approximating molecular topographies in large cohorts where direct measurements are unavailable. Yet whether the type of MRI data used to derive these eigenmodes determines which receptor and transporter distributions can be approximated, and which molecular systems are accessible through this approach at all, remains unknown. Using a spatial reconstruction framework applied to 23 molecular systems spanning neurotransmitter, metabolic, and pathological markers, we show that eight receptor and transporter maps, spanning serotonin, dopamine, histamine, cholinergic, and opioid markers, can be selectively approximated from functional eigenmodes but not structural or geometric ones. This selectivity also reveals that functional brain organization encodes a specific subset of neuromodulatory topographies that structural and geometric organization does not. To illustrate translational potential in clinical cohorts where molecular imaging is unavailable, we applied individual-level eigenmode decompositions of MRI data projected onto the eight validated molecular systems and detected cross-sectional differences in autism and longitudinal changes in schizophrenia. Together, these findings reveal a difference in how geometric, structural, and functional brain organization relate to molecular architecture, offering a method for approximating validated molecular profiles in population neuroimaging cohorts that lack direct molecular imaging.
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BibTeX
@misc{wan2026eigenbrain,
title = {{EigenBrain maps cortical molecular architecture from functional, geometric, and structural eigenmodes}},
author = {B. Wan and P. Du and A. Ferrari and A. Saberi and A. John and J. Yan and X. Liu and J. Y. Hansen and Z.-Q. Liu and S.-J. Hong and F. Carruzzo and M. Kaliuzhna and T. Geffen and T. Katthagen and B. Misic and P. M. Thompson and D. Van De Ville and D. S. Margulies and V. Warrier and R. A. I. Bethlehem and F. Schlagenhauf and S. Kaiser and B. Bernhardt and S. L. Valk and M. Kirschner},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.27.758642},
url = {https://www.biorxiv.org/content/10.64898/2026.10.27.758642v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - EigenBrain maps cortical molecular architecture from functional, geometric, and structural eigenmodes
AU - B. Wan
AU - P. Du
AU - A. Ferrari
AU - A. Saberi
AU - A. John
AU - J. Yan
AU - X. Liu
AU - J. Y. Hansen
AU - Z.-Q. Liu
AU - S.-J. Hong
AU - F. Carruzzo
AU - M. Kaliuzhna
AU - T. Geffen
AU - T. Katthagen
AU - B. Misic
AU - P. M. Thompson
AU - D. Van De Ville
AU - D. S. Margulies
AU - V. Warrier
AU - R. A. I. Bethlehem
AU - F. Schlagenhauf
AU - S. Kaiser
AU - B. Bernhardt
AU - S. L. Valk
AU - M. Kirschner
PY - 2026
DA - 2026/10/27
PB - bioRxiv
DO - 10.64898/2026.10.27.758642
UR - https://www.biorxiv.org/content/10.64898/2026.10.27.758642v1
AB - Neurotransmitter receptor and transporter distributions shape neural communication across the cortex and underpin mechanistic interpretations of brain function. Magnetic resonance imaging (MRI)-derived eigenmodes, low-dimensional spatial patterns that capture the principal axes of cortical organization, are increasingly used to reconstruct brain maps and offer a potential route to approximating molecular topographies in large cohorts where direct measurements are unavailable. Yet whether the type of MRI data used to derive these eigenmodes determines which receptor and transporter distributions can be approximated, and which molecular systems are accessible through this approach at all, remains unknown. Using a spatial reconstruction framework applied to 23 molecular systems spanning neurotransmitter, metabolic, and pathological markers, we show that eight receptor and transporter maps, spanning serotonin, dopamine, histamine, cholinergic, and opioid markers, can be selectively approximated from functional eigenmodes but not structural or geometric ones. This selectivity also reveals that functional brain organization encodes a specific subset of neuromodulatory topographies that structural and geometric organization does not. To illustrate translational potential in clinical cohorts where molecular imaging is unavailable, we applied individual-level eigenmode decompositions of MRI data projected onto the eight validated molecular systems and detected cross-sectional differences in autism and longitudinal changes in schizophrenia. Together, these findings reveal a difference in how geometric, structural, and functional brain organization relate to molecular architecture, offering a method for approximating validated molecular profiles in population neuroimaging cohorts that lack direct molecular imaging.
ER -