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Searchlight analysis: promise, pitfalls, and potential.

ABSTRACT: Multivariate pattern analysis (MVPA) is an increasingly popular approach for characterizing the information present in neural activity as measured by fMRI. For neuroimaging researchers, the searchlight technique serves as the most intuitively appealing means of implementing MVPA with fMRI data. However, searchlight approaches carry with them a number of special concerns and limitations that can lead to serious interpretation errors in practice, such as misidentifying a cluster as informative, or failing to detect truly informative voxels. Here we describe how such distorted results can occur, using both schematic illustrations and examples from actual fMRI datasets. We recommend that confirmatory and sensitivity tests, such as the ones prescribed here, should be considered a necessary stage of searchlight analysis interpretation, and that their adoption will allow the full potential of searchlight analysis to be realized.

SUBMITTER: Etzel JA

PROVIDER: S-EPMC3988828 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

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Searchlight analysis: promise, pitfalls, and potential.

Etzel Joset A JA Zacks Jeffrey M JM Braver Todd S TS

NeuroImage 20130401

Multivariate pattern analysis (MVPA) is an increasingly popular approach for characterizing the information present in neural activity as measured by fMRI. For neuroimaging researchers, the searchlight technique serves as the most intuitively appealing means of implementing MVPA with fMRI data. However, searchlight approaches carry with them a number of special concerns and limitations that can lead to serious interpretation errors in practice, such as misidentifying a cluster as informative, or ...[more]

PMID: 23558106

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Project description:BACKGROUND:A myositis-specific autoantibody can now be identified in the majority of patients with myositis. They identify homogeneous patient subgroups and are key tools in developing a personalized approach to disease management. There is substantial clinical interest in exploiting myositis autoantibodies as biomarkers, and consequently, a large number of commercial assays have been developed for their detection. These assays are already in widespread clinical use. In order to better understand perceived concerns from the international myositis community in relation to the reliability of these assays and how they are being used, we conducted a survey of international myositis experts, all of whom were members of the International Myositis Assessment and Clinical Studies group. RESULTS:We collected data on the types of assay used, manufacturers, and the nature of the report provided by different laboratories and received 111 complete responses. Respondents also provided information on how they used the different assays, their confidence in the results, and how this influenced their clinical practice. Enzyme immunoassay/ELISA was the most popular assay method used worldwide followed by line blot. Line blot was the most popular method used in Europe. Despite concerns from over 80% of respondents regarding false-positive and false-negative results with the assay used by their laboratory, over 80% reported that the identification of a myositis autoantibody influenced their diagnostic confidence, the information they provided to a patient, and their recommended treatment. CONCLUSIONS:In spite of ongoing concerns from the majority of users regarding the reliability of the results, myositis-specific autoantibody testing, using commercial immunoassays, is being used globally to inform clinical decision-making. These findings highlight the need for urgent guidance on the use of myositis autoantibody testing and on the interpretation of results. Knowledge of the reliability of currently available assays is essential given the importance already placed on myositis-specific autoantibodies as clinical decision-making tools.

Dataset Information

Searchlight analysis: promise, pitfalls, and potential.

Publications

Searchlight analysis: promise, pitfalls, and potential.

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