Gamma Oscillation Frequency Ranges Across Computational PV Models

Different computational models predict substantially different gamma frequency ranges depending on the balance of ING vs PING mechanisms, brain region, and model complexity. This highlights that 'gamma' is not a single phenomenon but spans a wide frequency range (30-140 Hz) with distinct mechanistic regimes.

{
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    {
      "n": 0,
      "doi": "10.1523/ENEURO.0452-25.2026",
      "value": "100-140",
      "method": "spiking network model constrained by experimental data",
      "metric": "ING gamma frequency range",
      "n_analyzed": null,
      "ci_or_error": null,
      "text_access": "fulltext",
      "n_definition": "network simulations",
      "scope_region": "medial entorhinal cortex",
      "study_system": "mouse mEC computational model",
      "taxonomic_level": "PV fast-spiking interneurons",
      "scope_population": "fast-spiking interneurons",
      "value_source_sentence": "Simulations revealed that weak excitatory input to interneurons supports fast ING-dominated rhythms (∼100–140 Hz).",
      "experimental_conditions": "weak excitatory input to interneurons"
    },
    {
      "n": 0,
      "doi": "10.1523/ENEURO.0452-25.2026",
      "value": "60-100",
      "method": "spiking network model constrained by experimental data",
      "metric": "PING gamma frequency range",
      "n_analyzed": null,
      "ci_or_error": null,
      "text_access": "fulltext",
      "n_definition": "network simulations",
      "scope_region": "medial entorhinal cortex",
      "study_system": "mouse mEC computational model",
      "taxonomic_level": "PV fast-spiking interneurons and pyramidal cells",
      "scope_population": "E-I network",
      "value_source_sentence": "Simulations revealed that...strengthening excitatory drive induces a transition to slower PING-dominated oscillations (60–100 Hz).",
      "experimental_conditions": "strengthened excitatory drive to interneurons"
    },
    {
      "n": 3000,
      "doi": "10.1371/journal.pcbi.1012259",
      "value": "40",
      "method": "morphology-constrained cortical network model",
      "metric": "gamma frequency in E-I network",
      "n_analyzed": null,
      "ci_or_error": null,
      "text_access": "fulltext",
      "n_definition": "neurons in network model",
      "scope_region": "motor cortex cross-sectional layer",
      "study_system": "mouse motor cortex model (WT)",
      "taxonomic_level": "PV fast-spiking and pyramidal neurons",
      "scope_population": "pyramidal and fast-spiking interneurons",
      "value_source_sentence": "Our findings reveal a dynamic interplay between pyramidal and fast-spiking interneurons leading to the emergence of gamma activity (∼40 Hz).",
      "experimental_conditions": "wild-type morphological parameters"
    },
    {
      "n": 0,
      "doi": "10.1523/jneurosci.3041-11.2011",
      "value": "30-80",
      "method": "biophysically detailed compartmental model with asynchronous GABA release",
      "metric": "gamma oscillation frequency range",
      "n_analyzed": null,
      "ci_or_error": null,
      "text_access": "abstract_only",
      "n_definition": "cortical circuit model neurons",
      "scope_region": "cortex (generic)",
      "study_system": "biophysically detailed cortical circuit model",
      "taxonomic_level": "PV fast-spiking interneurons",
      "scope_population": "PV-pyramidal network",
      "value_source_sentence": "Parvalbumin (PV)-expressing, fast-spiking interneurons interacting with pyramidal neurons generate cortical gamma oscillations (30–80 Hz) that synchronize cortical activity during cognitive processing.",
      "experimental_conditions": "sensory stimulus-induced gamma"
    }
  ],
  "comparison_id": "gamma-frequency-across-models",
  "comparison_name": "Gamma Oscillation Frequency Ranges Across Computational PV Models",
  "comparison_type": "cross-study conflict",
  "what_it_reveals": "Different computational models predict substantially different gamma frequency ranges depending on the balance of ING vs PING mechanisms, brain region, and model complexity. This highlights that 'gamma' is not a single phenomenon but spans a wide frequency range (30-140 Hz) with distinct mechanistic regimes.",
  "homogeneity_check": {
    "caveats": [
      "Different brain regions: mEC, motor cortex, generic cortex",
      "Different model complexity: from simplified spiking to biophysically detailed compartmental",
      "ING vs PING vs combined mechanisms produce different frequency bands in the same model",
      "3000-neuron model vs unspecified network sizes"
    ],
    "n_definition_uniform": "false",
    "scope_region_uniform": "false",
    "taxonomic_level_uniform": "true",
    "scope_population_uniform": "true"
  },
  "suggested_plot_type": "grouped bar"
}

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