Evidence map›Paper›PMID 34951473›Full record

ArticleSchizophrenia bulletin2022

Characterization of Hemodynamic Alterations in Schizophrenia and Bipolar Disorder and Their Effect on Resting-State fMRI Functional Connectivity.

Wenjing Yan, Lena Palaniyappan, Peter F Liddle, D Rangaprakash, Wei Wei, Gopikrishna Deshpande

Open access · bronzeAbstract read
In one paragraph

Article in Schizophrenia bulletin, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.2field-weighted citation impact, top 23% 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

8 citing papers in PubMed, 14 citations in OpenAlex.

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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

6 authors at 5 institutions in 5 countries.

Wenjing YanDepartment of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, USA.
Lena PalaniyappanDepartment of Psychiatry, University of Western Ontario, London, ON, Canada.ORCID 0000-0003-1640-7182
Peter F LiddleCentre for Translational Neuroimaging, Division of Mental Health and Clinical Neuroscience, Institute of Mental Health, University of Nottingham, UK.
D RangaprakashAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
Wei WeiDepartment of Information Management, School of E-business and Logistics, Beijing Technology and Business University, Beijing, China.
Gopikrishna DeshpandeDepartment of Electrical and Computer Engineering, AU MRI Research Center, Auburn University, Auburn, AL, USA.ORCID 0000-0001-7471-5357
Beijing Technology and Business University · CNAdvanced Imaging Research (United States) · USHarvard University · USUniversity of Nottingham · GBWestern University · CA

Funding

Medical Research Council G0601442
6 · The paper itself

Abstract

Common and distinct neural bases of Schizophrenia (SZ) and bipolar disorder (BP) have been explored using resting-state fMRI (rs-fMRI) functional connectivity (FC). However, fMRI is an indirect measure of neural activity, which is a convolution of the hemodynamic response function (HRF) and latent neural activity. The HRF, which models neurovascular coupling, varies across the brain within and across individuals, and is altered in many psychiatric disorders. Given this background, this study had three aims: quantifying HRF aberrations in SZ and BP, measuring the impact of such HRF aberrations on FC group differences, and exploring the genetic basis of HRF aberrations. We estimated voxel-level HRFs by deconvolving rs-fMRI data obtained from SZ (N = 38), BP (N = 19), and matched healthy controls (N = 35). We identified HRF group differences (P < .05, FDR corrected) in many regions previously implicated in SZ/BP, with mediodorsal, habenular, and central lateral nuclei of the thalamus exhibiting HRF differences in all pairwise group comparisons. Thalamus seed-based FC analysis revealed that ignoring HRF variability results in false-positive and false-negative FC group differences, especially in insula, superior frontal, and lingual gyri. HRF was associated with DRD2 gene expression (P < .05, 1.62 < |Z| < 2.0), as well as with medication dose (P < .05, 1.75 < |Z| < 3.25). In this first study to report HRF aberrations in SZ and BP, we report the possible modulatory effect of dopaminergic signalling on HRF, and the impact that HRF variability can have on FC studies in clinical samples. To mitigate the impact of HRF variability on FC group differences, we suggest deconvolution during data preprocessing.

Indexed as

Bipolar DisorderSchizophreniaBrainHemodynamicsHumansMagnetic Resonance Imagingbipolar disorderdeconvolutionhemodynamic response function (HRF)resting-state fMRISchizophreniaseed-based functional connectivity

Identifiers

PMID34951473
PMCPMC9077436
OpenAlexW4200112863

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.