Wiki Guides

Analyzer Module

The Analyzer module provides analysis capabilities for TI simulation results, supporting both mesh-based and voxel-based data analysis. It provides descriptive statistics and visualization for understanding field distributions in the brain as a whole and specific regions of interest.

Important Quantities of Interest to Recognize

  • A. Mean TImax (TInorm) Intensity in ROI: Maximal modulation depth.
  • B. Mean TImax (TInorm) Intensity in non-ROI: Could be defined as entire cortex or a specific avoidance target.
  • C. Focality: Ratio between A/B
  • D. TInormal: Normal component of TImax with respect to fifth layer of the cortex.

Overview

The Analyzer module provides a single unified Analyzer class that handles both mesh and voxel analysis, plus a run_group_analysis() function for multi-subject comparison:

  • Analyzer: Unified class that dispatches spherical and cortical ROI analyses to the appropriate mesh- or voxel-based implementation, returning a typed AnalysisResult dataclass
  • Group Analysis: Batch processing for multiple subjects via run_group_analysis()

Analyzer User Interface

Key Features

Spherical ROI Analysis

  • Analyze field data within spherical regions of interest
  • Customizable center coordinates and radius
  • Multi-sphere table: each row (x,y,z,r) runs as its own separate analysis — N rows produce N independent result sets, not a union of the spheres. Group analysis supports only one sphere row and rejects extra rows with a warning.
  • Support for subject-space and MNI coordinates (automatic transformation)
  • Dual-field analysis: TI_max and TI_normal components (mesh space)
  • Statistical metrics: mean, max, min, focality, percentiles, and area-based focality

Cortical Analysis (Region Union)

  • Analyze one or more atlas regions as a single combined ROI — passing more than one region name unions their masks into one target, and the result’s region name is the selected names joined with +
  • In mesh space, a bare region name (e.g. cuneus) expands to both hemispheres (lh.cuneus + rh.cuneus)
  • Mesh atlases: DK40, a2009s, HCP_MMP1. Voxel atlases: aparc.DKTatlas+aseg.mgz, aparc.a2009s+aseg.mgz, lh.hippoAmygLabels-T1.v22.mgz, rh.hippoAmygLabels-T1.v22.mgz, ThalamicNuclei.v13.T1.mgz, plus the subject’s own segmentation/labeling.nii.gz
  • The four bundled MNI atlases (used elsewhere for subcortical ROI targeting) are not offered by the analyzer
  • Detailed regional statistics and visualizations

Tissue Selection

  • A Tissue selector (Gray Matter / White Matter / GM + WM) applies to voxel space only — it is disabled and forced to GM whenever Space is set to Mesh
  • In voxel mode, the tissue choice selects which field file is loaded by filename prefix (grey_ for GM, white_ for WM, no prefix for GM + WM) and builds the corresponding tissue mask

Unified Mesh + Voxel Handling

  • Single Analyzer class automatically dispatches to mesh or voxel implementation based on the space parameter
  • Mesh analysis: area-weighted statistics on cortical surface meshes
  • Voxel analysis: volumetric statistics on NIfTI data with FreeSurfer atlas integration

Mesh-Based Analysis

When space="mesh", the Analyzer works with SimNIBS mesh files and provides high-resolution analysis of field data on brain surfaces.

Features

  • Surface Mesh Generation: Automatic creation of gray matter surface meshes via msh2cortex (cached per instance)
  • Atlas Integration: Support for SimNIBS native atlases (DK40, a2009s, HCP_MMP1)
  • Field Extraction: Analysis of TI_max and TI_normal fields
  • 3D Visualization: Generation of mesh files for 3D viewing

Cortical ROI Analysis

TI Max Field in ROI TInorm field distribution in ROI (Left Insula)
TI Normal Field in ROI TInormal field distribution in ROI (Left Insula)

Spherical ROI Analysis

Spherical TI_max Analysis Spherical ROI analysis showing TI_max field distribution within a 10mm radius sphere at coordinates (-31.3, 24.0, -37.0)
Spherical TI_normal Analysis Spherical ROI analysis showing TI_normal field distribution for the same target region, demonstrating directional field components

Voxel-Based Analysis

When space="voxel", the Analyzer handles NIfTI format files and integrates with FreeSurfer atlases for detailed volumetric analysis.

Features

  • NIfTI Support: Direct analysis of .nii, .nii.gz, .mgz files
  • FreeSurfer Integration: Automatic atlas region extraction and resampling
  • Visualization Overlays: Generation of ROI-specific NIfTI overlays
Spherical TI_max Analysis Right Hippocampus ROI analysis showing TI_max field distribution given a 1mA:1mA stimualtion

Statistical Analysis Visualization

ROI Histogram Region-of-interest histogram analysis for left hemisphere insula showing field distribution within target areas

AnalysisResult Fields

All analysis calls return an AnalysisResult dataclass with the following fields:

Core Identifiers:

  • field_name: Name of the field analyzed (e.g. “TI_max”)
  • region_name: Name of the ROI
  • space: “mesh” or “voxel”
  • analysis_type: “spherical” or “cortical”

TI_max Field Metrics:

  • roi_mean: Area/volume-weighted average TI_max in the ROI
  • roi_max: Peak TI_max field intensity in the ROI
  • roi_min: Minimum TI_max field intensity in the ROI
  • roi_focality: ROI mean / GM mean (selectivity measure)
  • gm_mean: Area/volume-weighted average across entire grey matter
  • gm_max: Maximum TI_max value across entire GM

TI_normal Field Metrics (mesh only):

  • normal_mean: Average TI_normal field strength in the ROI
  • normal_max: Peak TI_normal field intensity in the ROI
  • normal_focality: TI_normal ROI mean / TI_normal GM mean
  • Absent (None) for mTI simulations — see mTI Analyses below

Percentile Metrics:

  • percentile_95, percentile_99, percentile_99_9: Field value at each percentile

Focality Area Metrics:

  • focality_50_area, focality_75_area, focality_90_area, focality_95_area: Area/volume above X% of the 99.9th percentile value (in cm^2)

Size Information:

  • n_elements: Number of mesh nodes or voxels in the ROI
  • total_area_or_volume: Total area (mesh, mm^2) or volume (voxel, mm^3) of the ROI

mTI Analyses

The analyzer detects an mTI (4-pair) simulation automatically — the only signal it checks is whether {simulation}/mTI/mesh/ exists. There is no separate mode to select; the same Analyzer class and the same analyze_sphere / analyze_cortex calls are used for TI and mTI.

  • TI_max and TI_Max are treated as aliases for the same quantity — the analyzer resolves whichever spelling the detected simulation type actually wrote to disk, regardless of which alias is requested
  • TI_normal is not computed for mTI simulations, so it cannot be selected as a field, and normal_mean, normal_max, and normal_focality are always absent (None) from mTI results

See mTI for the full description of mTI simulation and search.

Group Analysis

The run_group_analysis() function enables batch processing and comparative analysis across multiple subjects and montages, returning a GroupResult object.

Flexible Group Combinations

Group analysis supports arbitrary combinations of subjects and montages:

  • Same subject x Multiple different montages: Compare different stimulation configurations within the same individual
  • Multiple subjects x Same montage: Assess inter-subject variability for a specific stimulation protocol
  • Multiple subjects x Different montages: Full factorial design comparing both subject variability and montage effects

Features

  • MNI Coordinate Support: Automatically transform MNI coordinates to each subject’s native space
  • Comprehensive Comparisons: Automatic generation of statistical comparisons, rankings, and visualizations
  • Centralized Logging: Consolidated logging across all subjects and analyses
  • Progress Tracking: Real-time progress monitoring with timing information

Mesh Analysis Quick Inspection with Gmsh Integration

The analyzer now includes direct Gmsh integration for easy visualization and inspection of mesh analysis results.

Features

  • One-Click Launch: Directly launch Gmsh from the GUI to inspect mesh analysis results
  • Automatic Mesh Detection: Automatically finds and loads mesh files (.msh) from completed analyses
  • Subject/Simulation Selection: Dropdown selectors for choosing specific subjects, simulations, and analysis types

Supported Analysis Types

The Gmsh integration works with the analyzer’s two mesh-based analysis types:

  • Spherical ROI analyses with generated mesh overlays
  • Cortical region analyses with atlas-based parcellations

There is no separate “whole head” analysis type — the Analyzer supports only analysis_type spherical and cortical. A whole-head field-distribution histogram is generated as a by-product of every analysis (mesh or voxel), alongside the ROI-specific outputs.