{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2011:KIAVAS3YJL3XIA3XKV7NRJK2UW","short_pith_number":"pith:KIAVAS3Y","schema_version":"1.0","canonical_sha256":"5201504b784af7740377557ed8a55aa5a1cfece9a98d0f0c426ee2bf2d5c62bd","source":{"kind":"arxiv","id":"1108.3187","version":1},"attestation_state":"computed","paper":{"title":"The generalized shrinkage estimator for the analysis of functional connectivity of brain signals","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Hernando Ombao, Mark Fiecas","submitted_at":"2011-08-16T09:25:28Z","abstract_excerpt":"We develop a new statistical method for estimating functional connectivity between neurophysiological signals represented by a multivariate time series. We use partial coherence as the measure of functional connectivity. Partial coherence identifies the frequency bands that drive the direct linear association between any pair of channels. To estimate partial coherence, one would first need an estimate of the spectral density matrix of the multivariate time series. Parametric estimators of the spectral density matrix provide good frequency resolution but could be sensitive when the parametric m"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1108.3187","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.AP","submitted_at":"2011-08-16T09:25:28Z","cross_cats_sorted":[],"title_canon_sha256":"90d73f06be9453d98327b8a3aae89f3534a8947e2541ba1241f0d8a7acd8e8e2","abstract_canon_sha256":"abdd3c019a63c8199196f94b25e98c3eb868e10b6f3c304f6a54cfe8be858a2a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T04:15:27.810898Z","signature_b64":"86mNXK1aQksYKdSvhz0oPBsReaKsgtODFRLNGqS06Ws94f5/XtH5heUVUGjGC1gMJjQC6kDxGpJku5pISAcpAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5201504b784af7740377557ed8a55aa5a1cfece9a98d0f0c426ee2bf2d5c62bd","last_reissued_at":"2026-05-18T04:15:27.810271Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T04:15:27.810271Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"The generalized shrinkage estimator for the analysis of functional connectivity of brain signals","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.AP","authors_text":"Hernando Ombao, Mark Fiecas","submitted_at":"2011-08-16T09:25:28Z","abstract_excerpt":"We develop a new statistical method for estimating functional connectivity between neurophysiological signals represented by a multivariate time series. We use partial coherence as the measure of functional connectivity. Partial coherence identifies the frequency bands that drive the direct linear association between any pair of channels. To estimate partial coherence, one would first need an estimate of the spectral density matrix of the multivariate time series. Parametric estimators of the spectral density matrix provide good frequency resolution but could be sensitive when the parametric m"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1108.3187","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1108.3187","created_at":"2026-05-18T04:15:27.810381+00:00"},{"alias_kind":"arxiv_version","alias_value":"1108.3187v1","created_at":"2026-05-18T04:15:27.810381+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1108.3187","created_at":"2026-05-18T04:15:27.810381+00:00"},{"alias_kind":"pith_short_12","alias_value":"KIAVAS3YJL3X","created_at":"2026-05-18T12:26:32.869790+00:00"},{"alias_kind":"pith_short_16","alias_value":"KIAVAS3YJL3XIA3X","created_at":"2026-05-18T12:26:32.869790+00:00"},{"alias_kind":"pith_short_8","alias_value":"KIAVAS3Y","created_at":"2026-05-18T12:26:32.869790+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/KIAVAS3YJL3XIA3XKV7NRJK2UW","json":"https://pith.science/pith/KIAVAS3YJL3XIA3XKV7NRJK2UW.json","graph_json":"https://pith.science/api/pith-number/KIAVAS3YJL3XIA3XKV7NRJK2UW/graph.json","events_json":"https://pith.science/api/pith-number/KIAVAS3YJL3XIA3XKV7NRJK2UW/events.json","paper":"https://pith.science/paper/KIAVAS3Y"},"agent_actions":{"view_html":"https://pith.science/pith/KIAVAS3YJL3XIA3XKV7NRJK2UW","download_json":"https://pith.science/pith/KIAVAS3YJL3XIA3XKV7NRJK2UW.json","view_paper":"https://pith.science/paper/KIAVAS3Y","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1108.3187&json=true","fetch_graph":"https://pith.science/api/pith-number/KIAVAS3YJL3XIA3XKV7NRJK2UW/graph.json","fetch_events":"https://pith.science/api/pith-number/KIAVAS3YJL3XIA3XKV7NRJK2UW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KIAVAS3YJL3XIA3XKV7NRJK2UW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KIAVAS3YJL3XIA3XKV7NRJK2UW/action/storage_attestation","attest_author":"https://pith.science/pith/KIAVAS3YJL3XIA3XKV7NRJK2UW/action/author_attestation","sign_citation":"https://pith.science/pith/KIAVAS3YJL3XIA3XKV7NRJK2UW/action/citation_signature","submit_replication":"https://pith.science/pith/KIAVAS3YJL3XIA3XKV7NRJK2UW/action/replication_record"}},"created_at":"2026-05-18T04:15:27.810381+00:00","updated_at":"2026-05-18T04:15:27.810381+00:00"}