Evidence map›Paper›PMID 26036935›Full record

ArticleJournal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism2015

Parkinson's disease-related spatial covariance pattern identified with resting-state functional MRI.

Tao Wu, Yilong Ma, Zheng Zheng, Shichun Peng, Xiaoli Wu, David Eidelberg, Piu Chan

Open access · bronzeAbstract read
In one paragraph

Article in Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 2 pooled it
5.7field-weighted citation impact, top 4% of its field
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

32 citing papers in PubMed, 2 syntheses or guidelines pooled it, 52 citations in OpenAlex.

  1. Functional brain changes in Parkinson's disease: a whole brain ALE study.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2022
    Pooled it
  2. Resting-state functional reorganization in Parkinson's disease: An activation likelihood estimation meta-analysis.Cortex; a journal devoted to the study of the nervous system and behavior · 2017
    Pooled it
  3. Trial
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  8. The role of neuroimaging in Parkinson's disease.Journal of neurochemistry · 2021
    Review
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  19. Magnetic resonance imaging for the diagnosis of Parkinson's disease.Journal of neural transmission (Vienna, Austria : 1996) · 2017
    Review
  20. Review
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

7 authors at 3 institutions in 2 countries.

Tao WuDepartment of Neurobiology, Beijing Institute of Geriatrics, Xuanwu Hospital, Capital Medical University, Beijing, China.
Yilong MaCenter for Neurosciences, The Feinstein Institute for Medical Research, The North Shore-Long Island Jewish Health System, Manhasset, New York, USA.
Zheng ZhengDepartment of Neurobiology, Beijing Institute of Geriatrics, Xuanwu Hospital, Capital Medical University, Beijing, China.
Shichun PengCenter for Neurosciences, The Feinstein Institute for Medical Research, The North Shore-Long Island Jewish Health System, Manhasset, New York, USA.
Xiaoli WuDepartment of Neurobiology, Beijing Institute of Geriatrics, Xuanwu Hospital, Capital Medical University, Beijing, China.
David EidelbergCenter for Neurosciences, The Feinstein Institute for Medical Research, The North Shore-Long Island Jewish Health System, Manhasset, New York, USA.
Piu ChanDepartment of Neurobiology, Beijing Institute of Geriatrics, Xuanwu Hospital, Capital Medical University, Beijing, China.
Chinese Institute for Brain Research · CNCenter for Neurosciences · USFeinstein Institute for Medical Research · US

Funding

Statistics and Data Management CoreP50NS071675 · NINDS · FEINSTEIN INSTITUTE FOR MEDICAL RESEARCH · PI EIDELBERG, DAVID · 2010 to 2014
$9.3M
NINDS NIH HHS P50 NS071675
6 · The paper itself

Abstract

In this study, we sought to identify a disease-related spatial covariance pattern of spontaneous neural activity in Parkinson's disease using resting-state functional magnetic resonance imaging (MRI). Time-series data were acquired in 58 patients with early to moderate stage Parkinson's disease and 54 healthy controls, and analyzed by Scaled Subprofile Model Principal Component Analysis toolbox. A split-sample analysis was also performed in a derivation sample of 28 patients and 28 control subjects and validated in a prospective testing sample of 30 patients and 26 control subjects. The topographic pattern of neural activity in Parkinson's disease was characterized by decreased activity in the striatum, supplementary motor area, middle frontal gyrus, and occipital cortex, and increased activity in the thalamus, cerebellum, precuneus, superior parietal lobule, and temporal cortex. Pattern expression was elevated in the patients compared with the controls, with a high accuracy (90%) to discriminate the patients from the controls. The split-sample analysis produced a similar pattern but with a lower accuracy for group discrimination in both the derivation (80%) and the validation (73%) samples. Our results showed that resting-state functional MRI can be potentially useful for identification of Parkinson's disease-related spatial covariance patterns, and for differentiation of Parkinson's disease patients from healthy controls at an individual level.

Indexed as

AgedBrainDiagnosis, DifferentialFemaleHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingMaleMiddle AgedNeural Networks, ComputerParietal LobeParkinson DiseasePrincipal Component AnalysisProspective StudiesReproducibility of Results

Identifiers

PMID26036935
PMCPMC4635231
OpenAlexW2413907949

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.