Easy to interpret coordinate based meta-analysis of neuroimaging studies: Analysis of brain coordinates (ABC).
Autor: | Tench CR; Mental Health & Clinical Neurosciences, Clinical Neurology, University of Nottingham, Queen's Medical Centre, Nottingham, UK; NIHR Nottingham Biomedical Research Centre, Queen's Medical Centre, University of Nottingham, Nottingham, UK. Electronic address: Christopher.Tench@Nottingham.ac.uk., Tanasescu R; Mental Health & Clinical Neurosciences, Clinical Neurology, University of Nottingham, Queen's Medical Centre, Nottingham, UK. Electronic address: Radu.Tanasescu@nottingham.ac.uk., Constantinescu CS; Mental Health & Clinical Neurosciences, Clinical Neurology, University of Nottingham, Queen's Medical Centre, Nottingham, UK. Electronic address: Cris.Constantinescu@Nottingham.ac.uk., Auer DP; Radiological Sciences, University of Nottingham, Queen's Medical Centre, Nottingham, UK; NIHR Nottingham Biomedical Research Centre, Queen's Medical Centre, University of Nottingham, Nottingham, UK; Arthritis Research UK Pain Centre, University of Nottingham, Nottingham, UK; Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK. Electronic address: dorothee.auer@nottingham.ac.uk., Cottam WJ; Radiological Sciences, University of Nottingham, Queen's Medical Centre, Nottingham, UK; NIHR Nottingham Biomedical Research Centre, Queen's Medical Centre, University of Nottingham, Nottingham, UK; Arthritis Research UK Pain Centre, University of Nottingham, Nottingham, UK; Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK. Electronic address: William.cottam@nottingham.ac.uk. |
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Jazyk: | angličtina |
Zdroj: | Journal of neuroscience methods [J Neurosci Methods] 2022 Apr 15; Vol. 372, pp. 109556. Date of Electronic Publication: 2022 Mar 07. |
DOI: | 10.1016/j.jneumeth.2022.109556 |
Abstrakt: | Background: Functional MRI and voxel-based morphometry are important in neuroscience. They are technically challenging with no globally optimal analysis method, and the multiple approaches have been shown to produce different results. It is useful to be able to meta-analyse results from such studies that tested a similar hypothesis potentially using different analysis methods. The aim is to identify replicable results and infer hypothesis specific effects. Coordinate based meta-analysis (CBMA) offers this, but the multiple algorithms can produce different results, making interpretation conditional on the algorithm. New Method: Here a new model based CBMA algorithm, Analysis of Brain Coordinates (ABC), is presented. ABC aims to be simple to understand by avoiding empirical elements where possible and by using a simple to interpret statistical threshold, which relates to the primary aim of detecting replicable effects. Results: ABC is compared to both the most used and the most recently developed CBMA algorithms, by reproducing a published meta-analysis of localised grey matter changes in schizophrenia. There are some differences in results and the type of data that can be analysed, which are related to the algorithm specifics. Comparison to Other Methods: Compared to other algorithms ABC eliminates empirical elements where possible and uses a simple to interpret statistical threshold. Conclusions: There may be no optimal way to meta-analyse neuroimaging studies using CBMA. However, by eliminating some empirical elements and relating the statistical threshold directly to the aim of finding replicable effects, ABC makes the impact of the algorithm on any conclusion easier to understand. (Crown Copyright © 2022. Published by Elsevier B.V. All rights reserved.) |
Databáze: | MEDLINE |
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