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About · The Virtual Brain Ontology

An executable knowledge framework for brain-network modeling

TVB-O represents a whole-brain model and the experiment that runs it as one typed, ontology-grounded object. From that single source, one compiler generates runnable code and a methods report, and a four-domain ontology makes models comparable across the literature. It aligns to and extends the EBRAINS ecosystem rather than replacing it.

The gap

No shared representation of what a model is

A published brain model is usually bespoke code. It can drift from the equations in the paper, is often shared with missing parameters, and stays hard to run because results depend on software versions and execution environments — so results are difficult to reproduce and compare.

Underneath lies a single absence: no shared, machine-readable representation of what a model is, or of the whole simulation experiment around it — its network, inputs, execution and analyses. TVB-O supplies that representation, following the example set by SBML and BioModels in systems biology.

Anatomy of the framework

Three pillars and a platform

Pillar 01 · Metadata standard

LinkML data model

A minimal, human- and machine-readable schema for everything needed to reproduce an experiment. The typed Python classes are generated from it, so the specification and the code never diverge.

SimulationExperimentSimulationStudy DynamicsNetwork
Pillar 02 · Vocabulary

Ontology

The formal, machine-readable backbone: shared terms and logical axioms with stable identifiers under w3id.org/tvbo, aligned to external ontologies for physics, biology, anatomy and clinical domains.

OWLSHACL shapesw3id.org/tvbo
Pillar 03 · Toolbox

Python package · tvbo

Specify a model once as YAML or Python objects, load curated entries from the database, generate code across backends, then run, fit and analyse — with a CLI for HPC workflows.

pip install tvborender_code() run()CLI
Delivery · tvbo.charite.de

The platform

A web layer over the ontology and curated database: browse the knowledge graph, assemble experiments in the builder, and retrieve everything through a REST API — for people and AI agents.

Knowledge GraphExperiment BuilderREST API

Prior work

Where TVB-O fits

Capabilities read down the left; tools across the top. No existing standard fills every row — the closest come from two directions, and only TVB-O's column is complete.

full partial none

Row 4 is the crux: only TVB-O grounds a model's entities in all four domains at once — physical units, biological process, brain anatomy, and clinical disorder — and it is the only tool that is executable, whole-brain, four-domain-grounded, curated and interoperable together.

Relationship to TVB

Built with The Virtual Brain, not instead of it

TVB-O is not a fork of The Virtual Brain. It is a specification and knowledge layer that treats TVB as one of several execution backends. The same types describe any dynamical system on any network — a single Lorenz attractor, a lattice of oscillators, or a power grid — so the framework reaches beyond whole-brain simulation while remaining native to it.

It aligns to and extends EBRAINS resources such as openMINDS and the Model Catalog, and interoperates with NeuroML/LEMS, BIDS and SBML rather than competing with them.

Who builds it

Developed at Charité and the BIH

TVB-O is developed in the Brain Simulation Section at Charité — Universitätsmedizin Berlin and the Berlin Institute of Health (BIH), the group behind The Virtual Brain.

Leon Martin Konstantin Bülau Marius Pille Rico Andre Schmitt Christoph Hüttl Jil M. Meier Halgurd Taher Dionysios Perdikis Michael Schirner Petra Ritter
Funding
P.R. acknowledges support by EU Horizon Europe program Horizon EBRAINS2.0 (101147319), VirtualBrainTwin (101137289), EBRAINS-PREP 101079717, AISN 101057655, EBRAIN-Health 101058516, EIC grant PHRASE 101058240, by the Digital Europe Programme TEF-Health (101100700), Shaiped (101195135), CoordinaTEF (101168074), German Research Foundation SFB 1436 (project ID 425899996), SFB 1315 (project ID 327654276), SFB 936 (project ID 178316478), SPP Computational Connectomics RI 2073/6-1, RI 2073/10-2, RI 2073/9-1, DFG Clinical Research Group BECAUSE-Y 504745852, Berlin University Alliance OpenMake, the Virtual Research Environment at the Charité Berlin, EBRAINS Health Data Cloud, and the Berlin Institute of Health and Foundation Charité. P.R. and J.M. acknowledge additional support by the Deutsche Forschungsgemeinschaft (DFG) — Project-ID 424778381 — TRR 295.

Start with the Python package

Install with pip install tvbo, load a model from the database, and generate runnable code in a few lines.

Read the documentation
Cite the preprint The Virtual Brain Ontology: A Digital Knowledge Framework for Reproducible Brain Network Modeling Martin, L. et al. — bioRxiv, 2025 doi:10.1101/2025.11.19.689211