Extensions

The optional extension schemas – Behaverse, OmniProcess, DataTrove, Galea – and what each provides

Studyflow elements ship in layered moddle schemas (see Authoring schemas for the authoring format). The two core schemas – core and cognitive – are always loaded and their elements are documented in Elements. This page catalogs the optional extensions.

Enabling and disabling extensions

Open Settings → Extensions in the modeler to toggle the optional schemas. Disabled schemas are excluded from the palette and not recognized when opening diagrams; reload the page to apply changes. Core schemas cannot be disabled.

Behaverse

Standardized cognitive testing with the Behaverse Unity runtime.

  • Task (Behaverse Task) – a Behaverse assessment, identified by scene (e.g. NB, UFOV) with task-specific YAML configurations. agentType selects a human or bot participant; botConfigurations configures the bot (see LLM and bot participants).

Templates: two N-Back templates – one referencing a built-in timeline by name (e.g. XCIT_NB_01), one with inline block overrides merged over the per-scene baseline at runtime (see Running a studyflow).

OmniProcess

Generic data-operation activities for preprocessing and analysis pipelines (see Model a preprocessing pipeline).

  • Transform – apply a function to each element in a data stream.
  • Map – element-wise (1 → 1) transform producing a new stream.
  • FlatMap – one-to-many transform (unnest, expand, explode).
  • Filter – drop items that fail a criterion.
  • Reduce – aggregate a stream to a single value (per group).
  • Compose – bundle several operations into one logical pipeline step.
  • PreprocessfMRI, PreprocessEEG – template-scoped preprocessing types, surfaced only via templates.

Templates: operations that are really “a generic operation plus a function” ship as prefilled templates rather than dedicated types – Group (a Map bound to python://omniprocess.group, grouping key via with), Split Data (a Transform bound to scikit-learn’s train_test_split, sizes via with), and Anonymize Data (a Map bound to python://omniprocess.anonymize); the uses function reference is a prefilled default you can repoint at your own function. Plus the neuroimaging prefabs: an fMRIPrep task (PreprocessfMRI with fMRIPrep-style parameters such as output_spaces) and an EEGPrep subprocess (PreprocessEEG with clean_artifacts/ICA parameters).

DataTrove

Large-scale text/data processing pipelines mirroring the DataTrove library.

  • Document – a single data item (text plus metadata).
  • DataFolder – a folder of documents; a dataset or collection.
  • Reader – read data from various formats and yield documents.
  • Writer – write documents to various formats.
  • Extractor – extract text content from raw formats (e.g. HTML).
  • Filter – remove documents based on rules/criteria.
  • Stats – collect statistics on the dataset.
  • Tokens – tokenize data or count tokens.
  • Dedup – deduplication blocks.

Galea

The full VR/EEG session lifecycle for the Galea headset.

  • GaleaSession – pool/container for a complete session.
  • Mount – fit the headset on the participant.
  • ImpedanceCheck – verify electrode contact quality.
  • SensorCalibration – calibrate sensors (eye tracking, EMG, …).
  • BaselineRecording – resting-state baseline (eyes open/closed).
  • GaleaTask – a VR task recorded during the session.
  • Unmount – remove the headset and end acquisition.
  • GaleaExport – export the recorded data (path templates, anonymization).
  • GaleaRecording – the multimodal dataset produced by a session; specializes studyflow:Dataset with modality lists and sampling rates.

Templates: a typical Galea session – mount → impedance → calibration → baseline → VR task → unmount → export.