Evidence map›Paper›PMID 42527300›Full record

ArticleeNeuro2026

Connectome-Guided Personalization of Optimal TDCS Intervention Selection in Alzheimer's Disease: A Modeling Study.

Janne J Luppi, Annel P Koomen, Cornelis J Stam, Philip Scheltens, Willem de Haan

Abstract read
In one paragraph

Article in eNeuro, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

5 authors.

Janne J LuppiAlzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Amsterdam 1081 HZ, The Netherlands j.j.luppi@amsterdamumc.nl.
Annel P KoomenAlzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Amsterdam 1081 HZ, The Netherlands.
Cornelis J StamDepartment of Clinical Neurophysiology and MEG, Amsterdam UMC, Amsterdam 1081 HZ, The Netherlands.
Philip ScheltensEQT Life Sciences Dementia Fund, Amsterdam 1071 DV, The Netherlands.
Willem de HaanAlzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Amsterdam 1081 HZ, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcranial direct current stimulation (tDCS) could reduce the neurophysiological effects in Alzheimer's disease (AD), but progress is hampered by variable outcomes across studies, likely related to both methodological and individual differences. We recently described a virtual brain network simulation method for optimizing tDCS interventions and now propose a method for further personalizing this approach. We now personalized the model for six female and four male biomarker-confirmed AD patients based on their brain structure and functional connectivity by using individual structural magnetic resonance imaging data and amplitude envelope correlation-based connectivity matrices extracted from magnetoencephalography (MEG) scans, respectively. We then assessed a set of previously established stimulation strategies based on their ability to improve relevant neurophysiological outcome parameters in each personalized model while undergoing AD damage. Personalized tDCS strategies were able to delay neurophysiological deterioration, but while the general model favored posterior anodal stimulation targeting the precuneus region, the personalized models favored frontal anodal stimulation targeting the dorsolateral prefrontal cortex region in 90% of the cases. This may be explained by higher connectivity levels of frontal regions in the personalized connectivity matrices, as anodal stimulation of highly connected regions produced more beneficial effects. In this methodological study, we propose several ways to improve personalized computational tDCS stimulation prediction modeling. We conclude that connectome-guided personalization of tDCS effects lead to different strategies with potentially better intervention outcomes. For external validation of this model-guided tDCS approach, model predictions are being tested in an ongoing clinical tDCS-MEG trial in AD patients.

Indexed as

Alzheimer DiseaseBrainConnectomeModels, NeurologicalPrecision MedicineTranscranial Direct Current StimulationAgedAged, 80 and overFemaleHumansMagnetic Resonance ImagingMagnetoencephalographyMaleAlzheimer’s diseaseneural mass modelpersonalizationtranscranial direct current stimulation

Identifiers

PMID42527300
PMCPMC13472757

What Socratic 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 Socratic graph.