Evidence map›Paper›PMID 42239131›Full record

ArticlebioRxiv : the preprint server for biology2026

Divergent scalp-to-region distance alteration patterns in autism spectrum disorders, Parkinson's disease and Alzheimer's disease.

Liqin Yang, Junhao Zhang, Junlong Wang, Hsin-Hsiung Huang, Hongbin Han, Daniel Razansky, Alzheimer’s Disease Neuroimaging Initiative, Axel Rominger, Jie Lu, Ruiqing Ni

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Liqin YangDepartment of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland.
Junhao ZhangInstitute for Biomedical Engineering, ETH Zurich & University of Zurich, 8093 Zurich, Switzerland.
Junlong WangDepartment of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland.
Hsin-Hsiung HuangDepartment of Statistics and Data Science, University of Central Florida, Orlando, FL, USA.
Hongbin HanDepartment of Radiology, Peking University Third Hospital, 10091 Beijing, China.
Daniel RazanskyInstitute for Biomedical Engineering, ETH Zurich & University of Zurich, 8093 Zurich, Switzerland.
Alzheimer’s Disease Neuroimaging Initiative
Axel RomingerDepartment of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland.ORCID 0000-0002-1954-736X
Jie LuDepartment of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China.
Ruiqing NiDepartment of Nuclear Medicine, Inselspital, Bern University Hospital, University of Bern, 3010 Bern, Switzerland.ORCID 0000-0002-0793-2113

Funding

Alzheimer's Disease Neuroimaging Initiative - SupplementU01AG024904 · NIA · NORTHERN CALIFORNIA INSTITUTE RES &EDUC · PI WEINER, MICHAEL W · 2004 to 2015
$121.0M
Translational Developmental Neuroscience of AutismK23MH087770 · NIMH · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI DI MARTINO, ADRIANA · 2010 to 2013
$644k
NIA NIH HHS U01 AG024904NIMH NIH HHS K23 MH087770
6 · The paper itself

Abstract

Brain stimulation is increasingly recognized as an effective and important therapeutic intervention for many brain diseases. Distance between the scalp and other brain regions is a pivotal variable for neurostimulation planning and the development of new techniques, but alterations in the distance between the scalp and other regions in brain diseases are largely unknown. In this study, we developed an automatic pipeline to calculate scalp-to-region distance (SRD) values from T1 MR images and applied it to a total of 1382 participants, including patients with autism spectrum disorder (ASD), Parkinson's disease (PD), Alzheimer's disease (AD), and cognitively normal controls (CNs). Cloud points were uniformly sampled on the automatically extracted scalp surface and cortex surface, on which the point-wise distance maps were generated. The brain was then coregistered with the BCI-DNI atlas, and SRD value for each brain region was extracted. Analysis of covariance (ANCOVA) was performed for SRD in each brain region, with age and sex as covariates. Compared with CNs, ASD patients showed widespread SRD decreases across the brain with prominent involvement of the frontal lobe, especially the orbitofrontal cortex and adjacent regions. In contrast, in AD patients, significantly increased SRD values were observed in various regions of the frontal gyrus. No significant SRD alteration was found in PD patients after correction. The automatic SRD calculation pipeline and the different patterns of SRD alterations in these diseases might be helpful for future neurostimulation planning in clinical practice.

Indexed as

Alzheimer’s diseaseautism spectrum disorderParkinson’s diseasescalp-to-region distance

Identifiers

PMID42239131
PMCPMC13228425

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.