Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 1 de 1
Filtrar
Mais filtros

Bases de dados
Ano de publicação
Tipo de documento
País de afiliação
Intervalo de ano de publicação
1.
Neuroimage ; 51(2): 677-83, 2010 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-20197097

RESUMO

Spatial normalization of neuroimaging data is a standard step when assessing group effects. As a result of divergent analysis procedures due to different normalization algorithms or templates, not all published coordinates refer to the same neuroanatomical region. Specifically, the literature is populated with results in the form of MNI or Talairach coordinates, and their disparity can impede the comparison of results across different studies. This becomes particularly problematic in coordinate-based meta-analyses, wherein coordinate disparity should be corrected to reduce error and facilitate literature reviews. In this study, a quantitative comparison was performed on two corrections, the Brett transform (i.e., "mni2tal"), and the Lancaster transform (i.e., "icbm2tal"). Functional magnetic resonance imaging (fMRI) data acquired during a standard paired associates task indicated that the disparity between MNI and Talairach coordinates was better reduced via the Lancaster transform, as compared to the Brett transform. In addition, an activation likelihood estimation (ALE) meta-analysis of the paired associates literature revealed that a higher degree of concordance was obtained when using the Lancaster transform in the form of fewer, smaller, and more intense clusters. Based on these results, we recommend that the Lancaster transform be adopted as the community standard for reducing disparity between results reported as MNI or Talairach coordinates, and suggest that future spatial normalization strategies be designed to minimize this variability in the literature.


Assuntos
Mapeamento Encefálico/métodos , Interpretação de Imagem Assistida por Computador/métodos , Imageamento por Ressonância Magnética , Adulto , Algoritmos , Humanos
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA