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Surface-based Group Analysis in FreeSurfer

Surface-based Group Analysis in FreeSurfer

Surface-based Group Analysis in FreeSurfer. Outline. Group Analysis Overview Theory Surface-based Intersubject Registration Surface-based Smoothing General Linear Model (GLM) Practice FSGD File Processing Stages Vertex-wise Analysis Correction for multiple comparisons

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2.02k views • 65 slides
Surface-based Exploratory Group Analysis in FreeSurfer

Surface-based Exploratory Group Analysis in FreeSurfer

Surface-based Exploratory Group Analysis in FreeSurfer. Outline. Processing Stages Command-line Stream Assemble Data Design/Contrast (GLM Theory) Analyze Visualize Interactive/Automated GUI (QDEC) Correction for multiple comparisons. Aging Exploratory Analysis.

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746 views • 52 slides
Surface-based Group Analysis in FreeSurfer

Surface-based Group Analysis in FreeSurfer

Surface-based Group Analysis in FreeSurfer. Outline. Processing Stages Command-line Stream Assemble Data Design/Contrast (GLM Theory) Analyze Visualize Interactive/Automated GUI (QDEC) Correction for multiple comparisons. Surface-based Study (Thickness). Surface-based Measures.

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480 views • 43 slides
Correction for multiple comparisons in FreeSurfer

Correction for multiple comparisons in FreeSurfer

Correction for multiple comparisons in FreeSurfer. Problem of Multiple Comparisons. p < 0.01. p < 10 -7. p < 0.10. p value is probability that a voxel is falsely activated Threshold too liberal: many false positives Threshold too restrictive: lose activation (false negatives). Clusters.

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689 views • 21 slides
Correction for multiple comparisons

Correction for multiple comparisons

Correction for multiple comparisons. Problem of Multiple Comparisons. p < 0.01. p < 10 -7. p < 0.10. p value is probability that a voxel is falsely activated Threshold too liberal: many false positives Threshold too restrictive: lose activation (false negatives). Clusters. p < 0.01.

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362 views • 21 slides
Correction for multiple comparisons

Correction for multiple comparisons

Correction for multiple comparisons. Problem of Multiple Comparisons. p < 0.01. p < 10 -7. p < 0.10. p value is probability that a voxel is falsely activated Threshold too liberal: many false positives Threshold too restrictive: lose activation (false negatives). Clusters. p < 0.01.

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391 views • 21 slides

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