Evidence map›Paper›PMID 42403484›Full record

ArticleFrontiers in neuroscience2026

Local brain connectome parameters across the spectrum of clinical cognitive decline.

Demet Yüksel Dal, Boran A Kilic, Gurur Gamgam

Abstract read
In one paragraph

Article in Frontiers in neuroscience, 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

3 authors.

Demet Yüksel DalElectrical and Electronics Engineering Department, Fatih Sultan Mehmet Vakif University, İstanbul, Türkiye.
Boran A KilicElectrical and Electronics Engineering Department, Boğaziçi University, İstanbul, Türkiye.
Gurur GamgamElectrical and Electronics Engineering Department, Boğaziçi University, İstanbul, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neurological disorders such as Alzheimer's disease, Parkinson's disease, and autism disrupt the brain's structural and functional organization, particularly in specific regions, and ultimately lead to cognitive impairments. In Alzheimer's disease-related dementia, neuronal degeneration impairs structural connectivity between brain regions, which in turn leads to functional breakdowns. This phenomenon, referred to as disconnection syndrome, manifests as connectivity breakdowns in affected regions, with these localized changes indirectly influencing the entire brain network. As the disease progresses, patterns consistent with compensatory-type reorganization have been described in the literature, accompanied by structural and functional changes that have been hypothesized to transiently mitigate cognitive decline during early stages. This study examines the structural and functional reorganization of the brain across the clinical spectrum of Alzheimer's disease by analyzing local nodal changes using measures such as degree, strength, clustering coefficient, and betweenness centrality. Our findings show that early-stage nodal patterns are consistent with this hypothesized reorganization, whereas later-stage changes are dominated by progressive structural decline alongside persistent functional reorganization. Because the present study is cross-sectional and group-level, the compensatory interpretation should be regarded as a working hypothesis rather than a confirmed mechanism, and these exploratory patterns require validation in independent and longitudinal cohorts before clinical translation.

Indexed as

Alzheimer's diseasebrain connectomedMRIfMRIstructural and functional network

Identifiers

PMID42403484
PMCPMC13328281

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.