"eigenconnectivity" meaning in All languages combined

{
  "etymology_templates": [
    {
      "args": {
        "1": "en",
        "2": "eigen",
        "3": "connectivity"
      },
      "expansion": "eigen- + connectivity",
      "name": "prefix"
    }
  ],
  "etymology_text": "From eigen- + connectivity.",
  "forms": [
    {
      "form": "eigenconnectivities",
      "tags": [
        "plural"
      ]
    }
  ],
  "head_templates": [
    {
      "args": {},
      "expansion": "eigenconnectivity (plural eigenconnectivities)",
      "name": "en-noun"
    }
  ],
  "lang": "English",
  "lang_code": "en",
  "pos": "noun",
  "senses": [
    {
      "categories": [
        {
          "kind": "other",
          "name": "English entries with incorrect language header",
          "parents": [
            "Entries with incorrect language header",
            "Entry maintenance"
          ],
          "source": "w"
        },
        {
          "kind": "other",
          "name": "English terms prefixed with eigen-",
          "parents": [],
          "source": "w"
        },
        {
          "kind": "other",
          "name": "Pages with 1 entry",
          "parents": [],
          "source": "w"
        },
        {
          "kind": "other",
          "name": "Pages with entries",
          "parents": [],
          "source": "w"
        }
      ],
      "examples": [
        {
          "ref": "2021, Paola Valsasina, Milagros Hidalgo de la Cruz, Massimo Filippi, Maria A. Rocca, “Characterizing Rapid Fluctuations of Resting State Functional Connectivity in Demyelinating, Neurodegenerative, and Psychiatric Conditions: From Static to Time-Varying Analysis”, in Roberto Esposito, Filippo Cieri, Nicoletta Cera, Dante Mantini, Alessandra Griffa, editors, Dynamic Functioning of Resting State Networks in Physiological and Pathological Conditions:",
          "text": "Each eigenconnectivity pattern is characterized by a “contribution” (which can be thought as the equivalent of dwell times for k-means clustering analysis), which varies over time across subjects.",
          "type": "quote"
        }
      ],
      "glosses": [
        "The pattern of eigenvectors that emerges from a cluster analysis of a covariance matrix of neurophysiological events."
      ],
      "id": "en-eigenconnectivity-en-noun-gY5aA6hc",
      "links": [
        [
          "eigenvector",
          "eigenvector"
        ],
        [
          "cluster analysis",
          "cluster analysis"
        ],
        [
          "covariance",
          "covariance"
        ],
        [
          "matrix",
          "matrix"
        ],
        [
          "neurophysiological",
          "neurophysiological"
        ],
        [
          "event",
          "event"
        ]
      ]
    }
  ],
  "word": "eigenconnectivity"
}

{
  "etymology_templates": [
    {
      "args": {
        "1": "en",
        "2": "eigen",
        "3": "connectivity"
      },
      "expansion": "eigen- + connectivity",
      "name": "prefix"
    }
  ],
  "etymology_text": "From eigen- + connectivity.",
  "forms": [
    {
      "form": "eigenconnectivities",
      "tags": [
        "plural"
      ]
    }
  ],
  "head_templates": [
    {
      "args": {},
      "expansion": "eigenconnectivity (plural eigenconnectivities)",
      "name": "en-noun"
    }
  ],
  "lang": "English",
  "lang_code": "en",
  "pos": "noun",
  "senses": [
    {
      "categories": [
        "English countable nouns",
        "English entries with incorrect language header",
        "English lemmas",
        "English nouns",
        "English terms prefixed with eigen-",
        "English terms with quotations",
        "Pages with 1 entry",
        "Pages with entries"
      ],
      "examples": [
        {
          "ref": "2021, Paola Valsasina, Milagros Hidalgo de la Cruz, Massimo Filippi, Maria A. Rocca, “Characterizing Rapid Fluctuations of Resting State Functional Connectivity in Demyelinating, Neurodegenerative, and Psychiatric Conditions: From Static to Time-Varying Analysis”, in Roberto Esposito, Filippo Cieri, Nicoletta Cera, Dante Mantini, Alessandra Griffa, editors, Dynamic Functioning of Resting State Networks in Physiological and Pathological Conditions:",
          "text": "Each eigenconnectivity pattern is characterized by a “contribution” (which can be thought as the equivalent of dwell times for k-means clustering analysis), which varies over time across subjects.",
          "type": "quote"
        }
      ],
      "glosses": [
        "The pattern of eigenvectors that emerges from a cluster analysis of a covariance matrix of neurophysiological events."
      ],
      "links": [
        [
          "eigenvector",
          "eigenvector"
        ],
        [
          "cluster analysis",
          "cluster analysis"
        ],
        [
          "covariance",
          "covariance"
        ],
        [
          "matrix",
          "matrix"
        ],
        [
          "neurophysiological",
          "neurophysiological"
        ],
        [
          "event",
          "event"
        ]
      ]
    }
  ],
  "word": "eigenconnectivity"
}