42 lines
No EOL
1.9 KiB
Markdown
42 lines
No EOL
1.9 KiB
Markdown
---
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title: The role of auxiliary parameters in evaluating voxel-wise encoding models for 3T and
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7T BOLD fMRI data
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persons:
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- michael-hanke
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- moritz-boos
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topics:
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- neuroimaging
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- predictive-data-analysis
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params:
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graphRootNodePID: xyzrins:publications/15f6113f-8ef6-403c-9618-0b35dc436866
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pid: xyzrins:publications/15f6113f-8ef6-403c-9618-0b35dc436866
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doi: 10.1101/2020.04.07.029397
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date: '2020-04-08'
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title: The role of auxiliary parameters in evaluating voxel-wise encoding models for
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3T and 7T BOLD fMRI data
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description: In neuroimaging, voxel-wise encoding models are a popular tool to predict
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brain activity elicited by a stimulus. To evaluate the accuracy of these predictions
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across multiple voxels, one can choose between multiple quality metrics. However,
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each quality metric requires specifying auxiliary parameters such as the number
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and selection criteria of voxels, whose influence on model validation is unknown.
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In this study, we systematically vary these parameters and observe their effects
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on three common quality metrics of voxel-wise encoding models in two open datasets
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of 3- and 7-Tesla BOLD fMRI activity elicited by musical stimuli. We show that such
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auxiliary parameters not only exert substantial influence on model validation, but
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also differ in how they affect each quality metric. Finally, we give several recommendations
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for validating voxel-wise encoding models that may limit variability due to different
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numbers of voxels, voxel selection criteria, and magnetic field strengths.
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kind: bibo:AcademicArticle
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author:
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- pid: xyzrins:persons/michael-hanke
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given_name: Michael
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family_name: Hanke
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- pid: xyzrins:persons/moritz-boos
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given_name: Moritz
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family_name: Boos
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topic:
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- pid: xyzrins:topics/neuroimaging
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display_label: Neuroimaging
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- pid: xyzrins:topics/predictive-data-analysis
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display_label: Predictive data analysis
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--- |