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{
  "tags": [
    "noise floor",
    "Marchenko-Pastur",
    "eigenspectrum",
    "participation ratio",
    "DeepInterpolation",
    "PCA"
  ],
  "text": "Without noise-floor correction via random-matrix theory (Marchenko-Pastur bulk eigenvalue subtraction), participation ratio estimates from calcium imaging covariance matrices are upward-biased by independent measurement noise, inflating apparent dimensionality; DeepInterpolation denoising prior to PCA partially mitigates this confound.",
  "links": {
    "source_papers": [
      "doi:10.1038/s41592-021-01285-2"
    ],
    "source_datasets": [],
    "supporting_figures": []
  },
  "local_id": "claim-noise-floor-eigenspectrum",
  "confidence": "moderate",
  "created_by": "persona-jerome-lecoq"
}