Tools

Everything we use to analyse our data is developed in the open at github.com/labgas. Two repositories hold the reusable methods; the rest are study-specific code released alongside papers.

Built on CANlab tools. Our neuroimaging code is a layer on top of the toolset developed by the Cognitive and Affective Neuroscience Lab (CANlab), not a replacement for it. Nothing here runs without CanlabCore and Neuroimaging_Pattern_Masks on the MATLAB path, alongside SPM12.

If you are new to this ecosystem, read the CANlab material first — the setup guide, the object-oriented analysis philosophy, the object and method docs, and the walkthroughs. Our pipeline documentation assumes it.

Who owns which layer

It is worth being explicit about where the boundary sits, because the two codebases are used together constantly.

Layer	Provided by	What it covers
Object model and core methods	CANlab — CanlabCore	`fmri_data`, `statistic_image`, `atlas`, `fmri_model` and friends; plotting, thresholding, predictive modelling machinery
Brain masks, atlases, signatures	CANlab — Neuroimaging_Pattern_Masks	Published multivariate signatures (NPS, SIIPS, PINES …), parcellations, region masks
Second-level batch pipeline & HTML reporting	CANlab, extended in our fork — CANlab_help_examples	`prep_` and `z_batch_` scripts, date-stamped report collections
Study initialisation, BIDS prep, first-level modelling	LaBGAS — LaBGAScore	Directory conventions, BIDS conversion, event timing, SPM first-level specification and diagnostics
PLS-DA / PLSR / Elastic Net neuroimaging pipelines	LaBGAS — LaBGAScore	`secondlevel/` classes, functions and scripts with their own usage guides
PET, MRS, connectivity, receptor mapping	LaBGAS — LaBGAScore	Wrappers around Osprey, CoSMoMVPA, The Decoding Toolbox, GraphVar, JuSpace

LaBGAScore

github.com/labgas/LaBGAScore · MATLAB · GPL-3.0

The core scripts — and templates for them — implementing our standard neuroimaging workflow. The repository is deliberately not a toolbox you add to your path and call. The scripts are canonical examples meant to be copied into a study-specific repository and adapted there, which keeps every project’s analysis code versioned with that project rather than drifting against a shared library.

Scripts carry numbered prefixes (s0, s1, s2 …) marking the order of the pipeline stages.

Folder	Purpose
`prep/`	BIDS conversion, directory definition, event timing files, smoothing
`firstlevel/`	SPM + CANlab GLM specification, estimation, diagnostic reports
`secondlevel/`	Group statistics and the MVPA/machine-learning pipelines, with seven usage guides
`stats_tools/`	FDR correction and related helpers in `functions/`, plus `sas_macros/` — SAS macros for effect sizes on the fixed effects of a `PROC MIXED` model
`atlas_mask_tools/`	Atlas and mask generation, plus ready-made brain templates
`pet/`	PET workflows including kinetic modelling
`mrs/`	MR spectroscopy, built on Osprey
`cosmomvpa/`	Representational similarity analysis via CoSMoMVPA
`decoding_toolbox/`	Classification accuracy via The Decoding Toolbox
`graphvar/`	Connectivity analysis inputs for GraphVar
`juspace/`	Receptor–spatial correlation via JuSpace
`power/`	Power analysis helpers
`figures/`	Plotting utilities
`clean/`	Housekeeping

A static-analysis helper, LaBGAScore_check_all_scripts.m, runs MATLAB’s Code Analyzer across every file in the repository. It catches syntax problems, but not undefined variables or logic errors — code review is still required.

Pipeline documentation

CANlab_help_examples (LaBGAS fork)

github.com/labgas/CANlab_help_examples · forked from canlab/CANlab_help_examples

Carries the batch pipeline for second-level analysis, in Second_level_analysis_template_scripts/. Its design philosophy is worth stating because it shapes how we work: interactive analysis using well-vetted, readable code, producing date-stamped HTML reports with figures and statistics that are archived as a durable record of what was run and when.

The workflow runs in five steps: create the analysis folder and run setup → edit the study configuration files (paths, conditions, contrasts, behavioural data) → load images into fmri_data objects and compute contrasts → run on-demand results scripts → run the z_batch_* publishing scripts to generate the report collection.

See the second-level documentation and the CANlab batch system pages.

Dependencies

Installed separately and added to the MATLAB path:

Required — CanlabCore, Neuroimaging_Pattern_Masks, SPM12, MATLAB with the Statistics and Machine Learning and Signal Processing toolboxes.

Per-domain — CoSMoMVPA, The Decoding Toolbox, GraphVar, JuSpace, Osprey.

Preprocessing and data management — fMRIPrep, BIDS, DataLad with GIN for data hosting.

Start with Setup & dependencies.

All repositories

Methods

Repository	Language	Description
`LaBGAScore`	MATLAB	Core scripts and templates for the LaBGAS standard neuroimaging workflow: BIDS conversion, first-level modelling, second-level and MVPA pipelines, PET, MRS, atlases and auxiliary toolkits.
`CANlab_help_examples`	HTML	LaBGAS fork of the CANlab help repository — how-to examples and the batch pipeline used for second-level neuroimaging analysis and date-stamped HTML reporting.

Study code

Code — and in some cases data — released alongside specific projects and papers.

Repository	Language	Description
`proj_threat_esophagus`	SAS	FWO post-doc project on the impact of threat on esophageal symptom perception.
`proj_bodymaps_IBS`	MATLAB	Bodily maps of emotions in irritable bowel syndrome.
`proj_pfi-x`	SAS	Data and code for the polyfoodintake-xylitol project.
`van_den_houte_fatigue_senior_postdoc_FWO`		FWO senior post-doctoral project on fatigue perception.
`proj_erythritol_2`	SAS	FWO-SNSF erythritol project, work package 2 — data and code.
`proj_erythritol_4a_code`	MATLAB	FWO-SNSF erythritol project, work package 4a — code subdataset.
`proj_bitter-reward-code`	MATLAB	Bitter tastant administration and reward sensitivity.
`proj_ncgs`	SAS	Non-coeliac gluten sensitivity gluten-challenge study analyses.
`proj_erythritol_4b-code`	MATLAB	FWO-SNSF erythritol project, work package 4b — code subdataset.
`proj_erythritol_5`	SAS	FWO-SNSF erythritol project, work package 5.
`proj_reflux_database_1`	SAS	Psychological and physiological contributors to symptom severity in refractory reflux.
`proj_erythritol_1`	SAS	FWO-SNSF erythritol project, work package 1 — data and code.
`proj_reflux_database_2`	SAS	Psychological factors across the organic-functional GERD spectrum.
`proj_CFS_treatment`	SAS	Chronic fatigue syndrome treatment-response analyses.
`proj_Rome_IV_network_analysis`	R	Network analysis of the Rome IV global epidemiology survey.
`dalile_junior_postdoc_FWO`		FWO junior post-doctoral project on short-chain fatty acids.
`proj-emosymp`	MATLAB	fMRI study of emotion-induced somatic symptoms in healthy controls and functional somatic syndrome patients.
`proj-fodmap-fmri`	SAS	FODMAP-induced gut-brain axis dysfunction in IBS.
`proj-IBS-somatization`	MATLAB	Graph-theoretical measures on brain connectivity data in IBS.
`proj_discoverie_code`		DISCOvERIE H2020 project, work package 4 — code subdataset.
`proj-whiplash`	MATLAB	fMRI study of neck pain-inducing movements.
`proj-sert-fmri`	MATLAB	Emotional modulation of esophageal pain.

This index was compiled on 2026-09-02. The organisation page at github.com/labgas is always authoritative.