Area
. | Keyword
. | Recommendation
. |
---|---|---|

Methodological | Parcellations | Test different parcellation schemes and atlases |

Test different node resolutions to explore stability of effects (currently only for Schaefer atlas possible) | ||

Preprocessing, denoising | Optimize preprocessing and denoising strategies to different types of functional connectivity indices | |

Test influence of different denoising pipelines to identify possible relationship between motion and measure of interest | ||

Exclude high motion subjects (rather strict than lenient if amount of data allows for) | ||

Sliding window technique, dynamic functional connectivity | Test different windowing schemes (e.g., size of windows, amount of overlap) | |

Use sufficient amount of data, if possible, e.g., via multiband fMRI (but take into account that acceleration decreases signal-to-noise ratio) or longer measurements | ||

Multilayer modularity | Test different parameter settings | |

Psychological | Construct of interest | Incorporate different measures for (e.g., two resilience scales) or aim for a complete characterization (i.e., all possible metrics) for the construct of interest, if possible |

Brain: construct of interest relationship/confounding variables | Motivate in/exclusion of covariates (test both if applicable) | |

Provide descriptive statistics for measures of interest | ||

Provide reliability measures (if applicable) | ||

Replications | Method section | Provide enough detail to allow for replication attempts |

Area
. | Keyword
. | Recommendation
. |
---|---|---|

Methodological | Parcellations | Test different parcellation schemes and atlases |

Test different node resolutions to explore stability of effects (currently only for Schaefer atlas possible) | ||

Preprocessing, denoising | Optimize preprocessing and denoising strategies to different types of functional connectivity indices | |

Test influence of different denoising pipelines to identify possible relationship between motion and measure of interest | ||

Exclude high motion subjects (rather strict than lenient if amount of data allows for) | ||

Sliding window technique, dynamic functional connectivity | Test different windowing schemes (e.g., size of windows, amount of overlap) | |

Use sufficient amount of data, if possible, e.g., via multiband fMRI (but take into account that acceleration decreases signal-to-noise ratio) or longer measurements | ||

Multilayer modularity | Test different parameter settings | |

Psychological | Construct of interest | Incorporate different measures for (e.g., two resilience scales) or aim for a complete characterization (i.e., all possible metrics) for the construct of interest, if possible |

Brain: construct of interest relationship/confounding variables | Motivate in/exclusion of covariates (test both if applicable) | |

Provide descriptive statistics for measures of interest | ||

Provide reliability measures (if applicable) | ||

Replications | Method section | Provide enough detail to allow for replication attempts |

*Note*: This brief list of recommendations does not
claim to be complete, but rather advocates to always aim at
incorporating the most recent findings and empirical evidence from
methodological studies.

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