Evidence map›Paper›PMID 26040586›Full record

ArticleMedical & biological engineering & computing2015

Evaluation of multiple comparison correction procedures in drug assessment studies using LORETA maps.

Joan Francesc Alonso, Sergio Romero, Miguel Ángel Mañanas, Mónica Rojas, Jordi Riba, Manel José Barbanoj

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Article in Medical & biological engineering & computing, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Joan Francesc AlonsoDepartment of Automatic Control, Biomedical Engineering Research Center, Universitat Politècnica de Catalunya. BarcelonaTech (UPC), Barcelona, Spain.
Sergio RomeroDepartment of Automatic Control, Biomedical Engineering Research Center, Universitat Politècnica de Catalunya. BarcelonaTech (UPC), Barcelona, Spain. sergio.romero-lafuente@upc.edu.
Miguel Ángel MañanasDepartment of Automatic Control, Biomedical Engineering Research Center, Universitat Politècnica de Catalunya. BarcelonaTech (UPC), Barcelona, Spain.
Mónica RojasDepartment of Automatic Control, Biomedical Engineering Research Center, Universitat Politècnica de Catalunya. BarcelonaTech (UPC), Barcelona, Spain.
Jordi RibaDrug Research Center, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.
Manel José BarbanojDrug Research Center, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The identification of the brain regions involved in the neuropharmacological action is a potential procedure for drug development. These regions are commonly determined by the voxels showing significant statistical differences after comparing placebo-induced effects with drug-elicited effects. LORETA is an electroencephalography (EEG) source imaging technique frequently used to identify brain structures affected by the drug. The aim of the present study was to evaluate different methods for the correction of multiple comparisons in the LORETA maps. These methods which have been commonly used in neuroimaging and also simulated studies have been applied on a real case of pharmaco-EEG study where the effects of increasing benzodiazepine doses on the central nervous system measured by LORETA were investigated. Data consisted of EEG recordings obtained from nine volunteers who received single oral doses of alprazolam 0.25, 0.5, and 1 mg, and placebo in a randomized crossover double-blind design. The identification of active regions was highly dependent on the selected multiple test correction procedure. The combined criteria approach known as cluster mass was useful to reveal that increasing drug doses led to higher intensity and spread of the pharmacologically induced changes in intracerebral current density.

Indexed as

AdultAlgorithmsAlprazolamBrainBrain MappingCentral Nervous System AgentsCluster AnalysisElectroencephalographyHumansMaleYoung AdultAlprazolamCentral Nervous System AgentsAlprazolamCluster massEEG tomographyLORETAMultiple testingNonparametric permutation test

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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.