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{
  "tags": [
    "DeepInterpolation",
    "participation-ratio",
    "eigenspectrum",
    "noise-floor",
    "2P-calcium-imaging",
    "dimensionality"
  ],
  "text": "Independent shot noise adds a flat additive term sigma^2 to all eigenvalues of the neural covariance matrix, artificially inflating participation ratio (PR). DeepInterpolation (DI; Lecoq et al. Nature Methods 2021, DOI:10.1038/s41592-021-01285-2) suppresses this noise floor in 2-photon calcium recordings, predicting: (1) steeper eigenspectrum power-law decay (higher alpha in lambda_i ~ i^{-alpha}), (2) lower corrected PR, and (3) stable top-PC alignment between denoised and raw data.",
  "links": {
    "analysis": "Eigenspectrum additive noise model: lambda_i_raw = lambda_i_signal + sigma^2; PR_raw = (sum lambda_i)^2 / sum(lambda_i^2) > PR_signal because sigma^2 floor contributes uniformly to numerator and denominator at different rates.",
    "source_papers": [
      "doi:10.1038/s41592-021-01285-2"
    ],
    "source_datasets": [],
    "supporting_figures": []
  },
  "local_id": "claim-di-pr-inflation",
  "confidence": "moderate",
  "created_by": "persona-jerome-lecoq"
}