Interoperability

TVBO integrations with external tools and standards

TVBO provides seamless interoperability with various neuroimaging tools, optimization frameworks, and metadata standards. This enables researchers to leverage specialized capabilities from different ecosystems while maintaining a unified model representation.

Integration Overview

flowchart LR
    subgraph TVBO["TVBO Core"]
        D[Dynamics]
        S[SimulationExperiment]
        N[Network]
        D --> S
        N --> S
    end

    subgraph Simulation["Simulation Backends"]
        tvboptim
        ND["NetworkDynamics.jl"]
        DiffEq["DifferentialEquations.jl"]
        MTK["ModelingToolkit.jl"]
    end

    subgraph Analysis["Analysis Backends"]
        PR[PyRates]
        BK["BifurcationKit.jl"]
        PyCoBi["PyCoBi / AUTO-07p"]
    end

    subgraph Standards["Standards & Schemas"]
        BIDS
        OpenMINDS
        LEMS["NeuroML / LEMS"]
    end

    S --> Simulation
    S --> Analysis
    S --> Standards


    style TVBO fill:none,stroke:#333
    style Simulation fill:none,stroke:#333
    style Analysis fill:none,stroke:#333
    style Standards fill:none,stroke:#333

Available Integrations

Simulation Backends

Integration	Input	Direction	Description
tvboptim	SimulationExperiment	Bidirectional	JAX-compiled simulation with autodiff optimization
NetworkDynamics.jl	SimulationExperiment + Network	Export	Julia graph-based network simulation [1]
ModelingToolkit.jl	SimulationExperiment or Dynamics	Export	Symbolic ODE system via Julia MTK
DifferentialEquations.jl	SimulationExperiment	Export	Julia ODE/SDE solvers

Analysis Backends

Integration	Input	Direction	Description
PyRates	SimulationExperiment or Dynamics	Bidirectional	Dynamical systems analysis and simulation [2]
BifurcationKit.jl	Dynamics + Continuation	Export	Julia bifurcation analysis [3]
PyCoBi / AUTO-07p	Dynamics + Continuation	Export	Fortran-based numerical continuation via PyRates

Standards & Schemas

Integration	Input	Direction	Description
BIDS	SimulationExperiment	Export	Brain Imaging Data Structure [4], [5]
OpenMINDS	SimulationExperiment	Bidirectional	EBRAINS Knowledge Graph metadata (JSON-LD)
NeuroML / LEMS	Dynamics, SimulationExperiment	Export	LEMS ComponentType definitions + jNeuroML simulation [6]

Quick Start

Optimization with tvboptim

from tvbo import SimulationExperiment

# Load experiment and run optimization
exp = SimulationExperiment.from_file("experiment.yaml")
results = exp.run()

# Access optimization results
print(results.optimization.fic.history)

Analysis with PyRates

from tvbo import Dynamics

# Export TVBO model to PyRates
model = Dynamics.from_file("JansenRit.yaml")
model.to_yaml(format="pyrates")

Export to BIDS

from tvbo import SimulationExperiment

exp = SimulationExperiment.from_file("experiment.yaml")
exp.to_bids("output/bids")

Export to OpenMINDS

from tvbo import SimulationExperiment

exp = SimulationExperiment.from_file("experiment.yaml")
exp.to_openminds("output/openminds.jsonld")

References

[1]

M. Lindner et al., “NetworkDynamics.jl—composing and simulating complex networks in julia,” Chaos: An Interdisciplinary Journal of Nonlinear Science, vol. 31, no. 6, p. 063133, Jun. 2021, doi: 10.1063/5.0051387.

[2]

R. Gast, T. R. Knösche, and A. Kennedy, “PyRates—a code-generation tool for modeling dynamical systems in biology and beyond,” PLOS Computational Biology, vol. 19, no. 12, p. e1011761, Dec. 2023, doi: 10.1371/journal.pcbi.1011761.

[3]

R. Veltz, “BifurcationKit.jl.” Inria Sophia-Antipolis, Jul. 2020. Available: https://hal.archives-ouvertes.fr/hal-02902346

[4]

R. A. Poldrack et al., “The past, present, and future of the brain imaging data structure (BIDS),” Imaging Neuroscience, vol. 2, Feb. 2024, doi: 10.1162/imag_a_00103.

[5]

M. Schirner and P. Ritter, “BIDS extension proposal 034 (BEP034): BIDS computational model specification,” 2021, doi: 10.5281/ZENODO.7962031.

[6]

A. Sinha et al., “The NeuroML ecosystem for standardized multi-scale modeling in neuroscience,” Oct. 2024, doi: 10.7554/elife.95135.2.