The Virtual Brain Ontology

tvbo is a Python library to access the knowledge representation system (i.e., ontology) and data model for the neuroinformatics platform The Virtual Brain (TVB).

🚀 Installation

pip install tvbo

Platform Notes

Intel Mac Users (x86_64): TVBO requires Python ≥3.11. On Intel Macs, the [audio] and [tvb] extras pin numba<0.60 / llvmlite<0.44 because newer llvmlite has no macosx_x86_64 wheels for Python 3.12+. JAX is also pinned to 0.4.28 (the last Intel-Mac release).

Apple Silicon Mac Users: Python ≥3.11 is supported. You'll get the latest compatible JAX version automatically.

📖 Quick Start

Example: Lorenz Attractor Simulation

name: LorenzAttractor
parameters:
    sigma:
        value: 10
        label: Prandtl number
    rho:
        label: Rayleigh number
        value: 28
    beta:
        value: 2.6666666666666665
state_variables:
    X:
        equation:
            lhs: \dot{X}
            rhs: sigma * (Y - X)
    Y:
        equation:
            lhs: \dot{Y}
            rhs: X * (rho - Z) - Y
    Z:
        equation:
            lhs: \dot{Z}
            rhs: X * Y - beta * Z

from tvbo import Dynamics, SimulationExperiment

lorenz = Dynamics(
    parameters={
        "sigma": {"value": 10.0},
        "rho": {"value": 28.0},
        "beta": {"value": 8 / 3},
    },
    state_variables={
        "X": {"equation": {"rhs": "sigma * (Y - X)"}},
        "Y": {"equation": {"rhs": "X * (rho - Z) - Y"}},
        "Z": {"equation": {"rhs": "X * Y - beta * Z"}},
    },
)

code = SimulationExperiment(dynamics=lorenz).render_code('jax')
print(code)

from tvbo import Dynamics, SimulationExperiment

lorenz = Dynamics(
    parameters={
        "sigma": {"value": 10.0},
        "rho": {"value": 28.0},
        "beta": {"value": 8 / 3},
    },
    state_variables={
        "X": {"equation": {"rhs": "sigma * (Y - X)"}},
        "Y": {"equation": {"rhs": "X * (rho - Z) - Y"}},
        "Z": {"equation": {"rhs": "X * Y - beta * Z"}},
    },
)

# Run simulation and plot results
SimulationExperiment(dynamics=lorenz).run(duration=1000).plot()

📚 Documentation

• Full Documentation
• Model Browser - Browse models, parameters, and equations
• Metadata Schema - Explore the TVB-O data model

🔬 Features

• 🧠 Access TVB ontology and knowledge base
• 📊 Define and simulate dynamical systems
• 🔄 Code generation for multiple backends (JAX, NumPy)
• 📈 Built-in visualization tools
• 🗃️ Structured metadata schema

📦 Installation Options

Standard Installation

pip install tvbo

With API Server Support

pip install tvbo[api]

With TVB Integration

pip install tvbo[tvb]

Full Installation (All Features)

pip install tvbo[all]

Note: The knowledge extra requires manual installation:

pip install git+https://github.com/neurommsig/neurommsig-knowledge.git

📄 License

Copyright © 2025 Charité Universitätsmedizin Berlin. This software is licensed under the terms of the European Union Public Licence (EUPL) version 1.2 or later.

Funding

P.R. acknowledges support by EU Horizon Europe program Horizon EBRAINS2.0 (101147319), VirtualBrainTwin(101137289), EBRAINS-PREP101079717, AISN101057655, 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 and EBRAINS Health Data Cloud and the Berlin Institute of Health and Foundation Charité. P.R. and J.M. acknowledge additionally support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project-ID 424778381 - TRR 295.