Evidence map›Paper›PMID 40487360›Full record

ArticleNetwork neuroscience (Cambridge, Mass.)2025

Multiplex connectomics reveal altered networks in frontotemporal dementia: A multisite study.

Sunil Kumar Khokhar, Manoj Kumar, Faheem Arshad, Sheetal Goyal, Megha Tiwari, Nithin Thanissery, Subasree Ramakrishnan, Chandana Nagaraj, Rajan Kashyap, Sandhya Mangalore and 4 more

Abstract read
In one paragraph

Article in Network neuroscience (Cambridge, Mass.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
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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

14 authors.

Sunil Kumar KhokharDepartment of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Manoj KumarDepartment of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Faheem ArshadDepartment of Neurology, NIMHANS, Bengaluru, India.
Sheetal GoyalDepartment of Neurology, NIMHANS, Bengaluru, India.
Megha TiwariDepartment of Neurology, NIMHANS, Bengaluru, India.
Nithin ThanisseryDepartment of Neurology, NIMHANS, Bengaluru, India.
Subasree RamakrishnanDepartment of Neurology, NIMHANS, Bengaluru, India.
Chandana NagarajDepartment of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Rajan KashyapDepartment of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Sandhya MangaloreDepartment of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
Tapan K GandhiDepartment of Electrical Engineering, Indian Institute of Technology (IIT) Delhi, New Delhi, India.
Suvarna AlladiDepartment of Neurology, NIMHANS, Bengaluru, India.
Rose Dawn BharathDepartment of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences (NIMHANS), Bengaluru, India.
frontotemporal lobar degeneration neuroimaging initiative

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A network neuroscience perspective can significantly advance the understanding of neurodegenerative disorders, particularly frontotemporal dementia (FTD). This study employed an innovative multiplex connectomics approach, integrating cortical thickness (CTH) and fluorodeoxyglucose-positron emission tomography (FDG-PET) in a dual-layer model to investigate network alterations in FTD subtypes across two geographically distinct sites. The cohort included groups of behavioral variant FTD (bvFTD), primary progressive aphasia (PPA), mild cognitive impairment (MCI), and cognitively normal (CN) individuals who were analyzed from two separate sites. Site 1 included 28 bvFTD, 20 PPA, and 27 MCI participants, whereas Site 2 included 26 bvFTD, 43 PPA, and 43 CN individuals, respectively. Utilizing CTH and FDG-PET data after standard preprocessing, a multiplex network pipeline in BRAPH2 toolbox was used to derive multiplex participation coefficient (MPC) between the groups. The analysis revealed an increase in global MPC as an indicator of disease in PPA at both sites. Additionally, nodal MPC alterations in the anterior cingulate, frontal, and temporal lobes in PPA were compared with bvFTD. Comparisons with the CN showed that nodal MPC alterations were more extensive in PPA when compared with bvFTD. These findings underscore the potential utility of multiplex connectomes for identifying network disruptions in neurodegenerative disorders, offering promising implications for future research and clinical applications.

Indexed as

ConnectomicsCortical thicknessFluorodeoxyglucose-positron emission tomographyFrontotemporal dementiaGraph theoryMultiplex

Identifiers

PMID40487360
PMCPMC12140567

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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.