Enum: ModelType

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

URI: 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 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

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.