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  "Description": "Performs a spatial Bayesian general linear model (GLM) for\ntask functional magnetic resonance imaging (fMRI) data on the\ncortical surface. Additional models include group analysis and\ninference to detect thresholded areas of activation. Includes\ndirect support for the 'CIFTI' neuroimaging file format. For\nmore information see A. F. Mejia, Y. R. Yue, D. Bolin, F.\nLindgren, M. A. Lindquist (2020)\n<doi:10.1080/01621459.2019.1611582> and D. Spencer, Y. R. Yue,\nD. Bolin, S. Ryan, A. F. Mejia (2022)\n<doi:10.1016/j.neuroimage.2022.118908>.",
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      "title": "BayesfMRI: Spatial Bayesian Methods for Task Functional MRI Studies",
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        "BayesfMRI"
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      "topics": [
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        "id_activations"
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      "title": "Make Mesh",
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      "topics": [
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      "title": "Scale the BOLD timeseries",
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    },
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      "title": "Summarize a '\"act_BGLM\"' object",
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        "print.summary.act_BGLM",
        "summary.act_BGLM"
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        "print.summary.BGLM",
        "summary.BGLM"
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    },
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      "title": "Summarize a '\"BGLM2\"' object",
      "topics": [
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        "print.summary.BGLM2",
        "summary.BGLM2"
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        "print.summary.fit_bglm",
        "summary.fit_bglm"
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      "page": "summary.fit_bglm2",
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        "print.summary.fit_bglm2",
        "summary.fit_bglm2"
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