# Enum: ModelType 




_Coarse classification of a Dynamics model by its mathematical/biological origin. Used for filtering and display in list_db()._



<div data-search-exclude markdown="1">

URI: [tvbo:enum/ModelType](https://w3id.org/tvbo/enum/ModelType)

## Permissible Values
| Value | Meaning | Description |
| --- | --- | --- |
| mean_field | None | Mathematically derived mean-field models obtained by exact reduction of spiki... |
| neural_mass | None | Phenomenological population-rate / neural-mass models that describe synaptic ... |
| phase_oscillator | None | Phase-reduced or Kuramoto-type oscillator models |
| phenomenological | None | Empirical / phenomenological models that capture macroscopic dynamics without... |
| spiking | None | Single-neuron or conductance-based spiking models (HH, AdEx, LIF, Izhikevich,... |
| generic | None | Generic / normal-form dynamical systems not specific to neural modelling (e |
| field | None | Spatially distributed neural-field models described by integro- differential ... |




## Slots

| Name | Description |
| ---  | --- |
| [model_type](../slots/model_type.qmd) | Coarse classification of this model (mean_field, neural_mass, phase_oscillato... |










## Identifier and Mapping Information





### Schema Source


* from schema: https://w3id.org/tvbo






## LinkML Source

<details>
```yaml
name: ModelType
description: Coarse classification of a Dynamics model by its mathematical/biological
  origin. Used for filtering and display in list_db().
from_schema: https://w3id.org/tvbo
rank: 1000
permissible_values:
  mean_field:
    text: mean_field
    description: 'Mathematically derived mean-field models obtained by exact reduction
      of spiking networks (Ott-Antonsen ansatz, Lorentzian heterogeneity, etc.). Examples:
      MontbrioPazoRoxin, CoombesByrne, ReducedWongWang, ZerlautAdaptationFirstOrder.'
  neural_mass:
    text: neural_mass
    description: 'Phenomenological population-rate / neural-mass models that describe
      synaptic and firing-rate dynamics without an explicit derivation from single-neuron
      statistics. Examples: JansenRit, WilsonCowan, LarterBreakspear, TsodyksMarkram.'
  phase_oscillator:
    text: phase_oscillator
    description: 'Phase-reduced or Kuramoto-type oscillator models. Examples: Kuramoto,
      SupHopf.'
  phenomenological:
    text: phenomenological
    description: 'Empirical / phenomenological models that capture macroscopic dynamics
      without direct biophysical derivation. Examples: Epileptor2D, Epileptor5D.'
  spiking:
    text: spiking
    description: Single-neuron or conductance-based spiking models (HH, AdEx, LIF,
      Izhikevich, etc.). These can be used as nodes in a network alongside mean-field
      models.
  generic:
    text: generic
    description: Generic / normal-form dynamical systems not specific to neural modelling
      (e.g. Generic2dOscillator, GenericLinear).
  field:
    text: field
    description: Spatially distributed neural-field models described by integro- differential
      or PDE formulations.

```
</details>

</div>