Evidence map›Paper›PMID 42323655›Full record

ArticleAlzheimer's research & therapy2026

Virtual brain and electroencephalography explain the variance of memory alterations in mild cognitive impairment.

Anita Monteverdi, Matteo Cotta Ramusino, Francesca Conca, Alberto Augello, Chiara Totaro, Paolo A Grasso, Anna Castelnovo, Roberta M Lorenzi, Michele Terzaghi, Lisa M Farina and 6 more

Abstract read
In one paragraph

Article in Alzheimer's research & therapy, 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
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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

16 authors.

Anita MonteverdiDigital Neuroscience Centre, IRCCS Mondino Foundation, Pavia, Italy. anita.monteverdi01@universitadipavia.it.
Matteo Cotta RamusinoUnit of Behavioral Neurology, IRCCS Mondino Foundation, Pavia, Italy.
Francesca ConcaUniversity Institute of Advanced Studies (IUSS), Pavia, Italy.
Alberto AugelloDepartment of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
Chiara TotaroDepartment of Child Neurology and Psychiatry, IRCCS Mondino Foundation, Pavia, Italy.
Paolo A GrassoDepartment of Physics and Astronomy, University of Florence, Florence, Italy.
Anna CastelnovoSleep Medicine Unit, Neurocenter of Italian Switzerland, Ente Ospedaliero Cantonale (EOC), Lugano, Switzerland.
Roberta M LorenziDepartment of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
Michele TerzaghiDepartment of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
Lisa M FarinaAdvanced Imaging and Artificial Intelligence Center, IRCCS Mondino Foundation, Pavia, Italy.
Alfredo CostaUnit of Behavioral Neurology, IRCCS Mondino Foundation, Pavia, Italy.
Anna PichiecchioDepartment of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
Stefano F CappaUniversity Institute of Advanced Studies (IUSS), Pavia, Italy.
Claudia Gandini Wheeler-KingshottDigital Neuroscience Centre, IRCCS Mondino Foundation, Pavia, Italy.
Fulvia PalesiDigital Neuroscience Centre, IRCCS Mondino Foundation, Pavia, Italy.
Egidio D'AngeloDigital Neuroscience Centre, IRCCS Mondino Foundation, Pavia, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMild Cognitive Impairment (MCI) is a heterogeneous clinical condition characterized by a wide spectrum of cognitive and behavioural manifestations. Despite numerous studies, the link between neuropsychological performance and pathophysiological signatures of the disease-including Aβ and tau accumulation along with altered excitation/inhibition (E/I) balance and brain rhythms-remains elusive.

methodsHere Aβ/tau biomarkers were used to distinguish positive (MCI

resultsWhile virtual brain simulations did not reveal E/I differences between MCI

conclusionsThis multimodal and multiparametric analysis combining virtual brain modelling with HD-EEG and molecular data enhances the stratification of MCI patients and could be used to develop digital biomarkers of progression to dementia, opening new perspectives for personalized prognosis and treatment.

Indexed as

BrainCognitive DysfunctionElectroencephalographyMemory DisordersAgedAmyloid beta-PeptidesFemaleHumansMagnetic Resonance ImagingMaleMiddle AgedNeuropsychological Teststau ProteinsAmyloid beta-Peptidestau ProteinsElectroencephalographyExcitatory/inhibitory balanceMild cognitive impairmentResting-state networksVirtual brain modelling

Identifiers

PMID42323655
PMCPMC13613803

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.