Evidence map›Paper›PMID 34290585›Full record

ArticleFrontiers in neuroscience2021

Functional Imaging to Guide Network-Based TMS Treatments: Toward a Tailored Medicine Approach in Alzheimer's Disease.

Chiara Bagattini, Debora Brignani, Sonia Bonnì, Giulia Quattrini, Roberto Gasparotti, Michela Pievani

Registry-linked trialOpen access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05984446 (Targeting Default Mode Network Dysfunction in Persons At Risk of Alzheimer's Disease with Non-invasive Techniques), which is not on this map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
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.

NCT05984446 nacompletednot on this map

Targeting Default Mode Network Dysfunction in Persons At Risk of Alzheimer's Disease with Non-invasive Techniques

TypeinterventionalSponsorIRCCS Centro San Giovanni di Dio FatebenefratelliRan2019 to 2024Enrolled86ConditionsAlzheimer DiseaseArmsreal-rTMS, sham-rTMS
3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 19 citations in OpenAlex.

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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

6 authors at 4 institutions in 1 country.

Chiara BagattiniNeurophysiology Lab, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
Debora BrignaniNeurophysiology Lab, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
Sonia BonnìNon Invasive Brain Stimulation Unit/Department of Behavioral and Clinical Neurology, Santa Lucia Foundation IRCCS, Rome, Italy.
Giulia QuattriniLaboratory Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
Roberto GasparottiNeuroradiology Unit, ASST Spedali Civili Hospital, University of Brescia, Brescia, Italy.
Michela PievaniLaboratory Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy.
Centro San Giovanni di Dio Fatebenefratelli · ITFondazione Santa Lucia · ITIstituti di Ricovero e Cura a Carattere Scientifico · ITUniversity of Brescia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A growing number of studies is using fMRI-based connectivity to guide transcranial magnetic stimulation (TMS) target identification in both normal and clinical populations. TMS has gained increasing attention as a potential therapeutic strategy also in Alzheimer's disease (AD), but an endorsed target localization strategy in this population is still lacking. In this proof of concept study, we prove the feasibility of a tailored TMS targeting approach for AD, which stems from a network-based perspective. Based on functional imaging, the procedure allows to extract individual optimal targets meanwhile accounting for functional variability. Single-subject resting-state fMRI was used to extract individual target coordinates of two networks primarily affected in AD, the default mode and the fronto-parietal network. The localization of these targets was compared to that of traditional group-level approaches and tested against varying degrees of TMS focality. The distance between individual fMRI-derived coordinates and traditionally defined targets was significant for a supposed TMS focality of 12 mm and in some cases up to 20 mm. Comparison with anatomical labels confirmed a lack of 1:1 correspondence between anatomical and functional targets. The proposed network-based fMRI-guided TMS approach, while accounting for inter-individual functional variability, allows to target core AD networks, and might thus represent a step toward tailored TMS interventions for AD.

Indexed as

Alzheimer’s diseaseconnectivityfunctional brain networksrepetitive transcranial magnetic stimulationresting-state fMRItailored treatment

Identifiers

PMID34290585
PMCPMC8287201
OpenAlexW3184324954

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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.