Evidence map›Paper›PMID 37577354›Full record

ArticleFrontiers in aging neuroscience2023

Virtual brain simulations reveal network-specific parameters in neurodegenerative dementias.

Anita Monteverdi, Fulvia Palesi, Michael Schirner, Francesca Argentino, Mariateresa Merante, Alberto Redolfi, Francesca Conca, Laura Mazzocchi, Stefano F Cappa, Matteo Cotta Ramusino and 7 more

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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

17 authors.

Anita MonteverdiUnit of Digital Neuroscience, IRCCS Mondino Foundation, Pavia, Italy.
Fulvia PalesiDepartment of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
Michael SchirnerBerlin Institute of Health, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Francesca ArgentinoDepartment of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
Mariateresa MeranteDepartment of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
Alberto RedolfiLaboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
Francesca ConcaIRCCS Mondino Foundation, Pavia, Italy.
Laura MazzocchiAdvanced Imaging and Artificial Intelligence Center, IRCCS Mondino Foundation, Pavia, Italy.
Stefano F CappaIRCCS Mondino Foundation, Pavia, Italy.
Matteo Cotta RamusinoUnit of Behavioral Neurology, IRCCS Mondino Foundation, Pavia, Italy.
Alfredo CostaDepartment of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
Anna PichiecchioDepartment of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.
Lisa M FarinaIRCCS Mondino Foundation, Pavia, Italy.
Viktor JirsaInstitut de Neurosciences des Systèmes, INSERM, INS, Aix Marseille University, Marseille, France.
Petra RitterBerlin Institute of Health, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Claudia A M Gandini Wheeler-KingshottUnit of Digital Neuroscience, IRCCS Mondino Foundation, Pavia, Italy.
Egidio D'AngeloUnit of Digital Neuroscience, IRCCS Mondino Foundation, Pavia, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Neural circuit alterations lay at the core of brain physiopathology, and yet are hard to unveil in living subjects. The Virtual Brain (TVB) modeling, by exploiting structural and functional magnetic resonance imaging (MRI), yields mesoscopic parameters of connectivity and synaptic transmission. Methods: We used TVB to simulate brain networks, which are key for human brain function, in Alzheimer's disease (AD) and frontotemporal dementia (FTD) patients, whose connectivity and synaptic parameters remain largely unknown; we then compared them to healthy controls, to reveal novel Results: The pattern of simulated parameter differed between AD and FTD, shedding light on disease-specific alterations in brain networks. Individual subjects displayed subtle differences in network parameter patterns that significantly correlated with their individual neuropsychological, clinical, and pharmacological profiles. Discussion: These TVB simulations, by informing about a new personalized set of networks parameters, open new perspectives for understanding dementias mechanisms and design personalized therapeutic approaches.

Indexed as

Alzheimer’s diseasebrain dynamicsexcitatory/inhibitory balancefrontotemporal dementiaresting-state networksvirtual brain modeling

Identifiers

PMID37577354
PMCPMC10419271

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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.