ALE parameters

Configuration Parameters for ALE

This page provides a detailed explanation of the parameters available in the config.yml file. These settings control various aspects of the ALE analysis workflow. Please note: Many of these parameters are intended for advanced users. DO NOT CHANGE THESE IF YOU ARE NOT AN ALE EXPERT!

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Project Folder

The Project Folder section specifies the file paths for key project documents:

• analysis_info

  • Default: "analysis_info.xlsx"
  • Description: Excel file containing analysis-related information.

• experiment_info

  • Default: "experiment_info.xlsx"
  • Description: Excel file containing details about the experiments.

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ALE Parameters

These parameters control the main ALE analysis settings:

• pool_experiments

  • Default: True
  • Description: When enabled, multiple experiments from the same paper are pooled into a single experiment. This helps in cases where individual experiments are not statistically independent.

• tfce_enabled

  • Default: True
  • Description: Enables TFCE (Threshold-Free Cluster Enhancement) for multiple comparison correction. (See Frahm et al., 2022 for details.)

• gm_masking

  • Default: True
  • Description: If enabled, the ALE map—and all subsequent maps—will be masked by the ICBM 10% GM mask to restrict the analysis to gray matter regions.

• bin_steps

  • Default: 0.0001
  • Description: Defines the size of the bins used in the Modeled Activation (MA) histogram. Smaller steps provide a finer resolution of the histogram.

• cutoff_predict_enabled

  • Default: True
  • Description: When enabled, xgboost models are used to predict cutoff values instead of relying on monte carlo simulation. (Refer to Frahm et al., 2024.)

• significance_threshold

  • Default: 0.05
  • Description: The p-value required for significance. Important: This setting only applies if cutoff_predict_enabled is disabled.

• cluster_forming_threshold

  • Default: 0.001
  • Description: Sets the preliminary cluster forming threshold for cluster-level family-wise error correction. Important: This is only effective if cutoff_predict_enabled is disabled.

• monte_carlo_iterations

  • Default: 5000
  • Description: Number of iterations used for monte-carlo based multiple comparison correction. Note: Only applicable when cutoff_predict_enabled is disabled.

• subsample_n

  • Default: 2500
  • Description: The number of subsamples calculated for the probabilistic ALE algorithm.

• contrast_permutations

  • Default: 10000
  • Description: Specifies the number of iterations used in the classic contrast algorithm.

• contrast_correction_method

  • Default: "cFWE"
  • Options: "cFWE", "vFWE", "tfce"
  • Description: Determines the correction method for the contrast algorithm.
    • "cFWE": Cluster-level family-wise error correction (default).
    • "vFWE": Voxel-level family-wise error correction.
    • "tfce": Threshold-Free Cluster Enhancement correction.

• difference_iterations

  • Default: 1000
  • Description: Number of sub-iterations used in the balanced contrast algorithm.

• nprocesses

  • Default: 2
  • Description: Sets the number of parallel processes for various steps in the ALE algorithm. Adjust this number based on the capabilities of your machine.

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MA_Clustering Parameters

These parameters control the settings for the Modeled Activation (MA) clustering process. DO NOT CHANGE THESE IF YOU ARE NOT AN ALE EXPERT!

• max_clusters

  • Default: 10
  • Description: The maximum number of clusters allowed in the analysis.

• subsample_fraction

  • Default: 0.9
  • Description: The fraction of data used in each subsampling iteration during the clustering process.

• sampling_iterations

  • Default: 1000
  • Description: Number of iterations for subsampling in the clustering algorithm.

• null_iterations

  • Default: 5000
  • Description: Number of iterations used to generate the null distribution for statistical testing.

• correlation_type

  • Default: "spearman"
  • Options: "spearman", "pearson"
  • Description: Specifies the type of correlation coefficient used to assess similarity between clusters.

• clustering_method

  • Default: "hierarchical"
  • Options: "hierarchical", "kmeans"
  • Description: Determines the clustering method. Hierarchical clustering is the default.

• linkage_method

  • Default: "complete"
  • Options: "complete", "average", "ward"
  • Description: Defines the linkage method for hierarchical clustering.

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Important Notes

• Modifying Parameters: Changes to the config.yml file can significantly affect the outcome of your analyses. Only adjust these parameters if you fully understand their implications.
• Further Reading: For more detailed explanations and the latest updates, please refer to the ALE documentation and the cited publications (e.g., Frahm et al., 2022; Frahm et al., 2024).