{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2013:LGUNT6WECLWK7KIL7EOWKORC2Q","short_pith_number":"pith:LGUNT6WE","canonical_record":{"source":{"id":"1310.3863","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-10-14T21:37:55Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"d5c72cabe144b7b5471f1420fe7a1c620fff36d789cd69e8ba3beed4924817d1","abstract_canon_sha256":"886acf6d2e42aa084a43d16ec43daff85f033d5c9cddee7745447f6e83f09d35"},"schema_version":"1.0"},"canonical_sha256":"59a8d9fac412ecafa90bf91d653a22d43acc14b05b0cd1331bcbff347f854b50","source":{"kind":"arxiv","id":"1310.3863","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1310.3863","created_at":"2026-05-18T02:54:21Z"},{"alias_kind":"arxiv_version","alias_value":"1310.3863v2","created_at":"2026-05-18T02:54:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1310.3863","created_at":"2026-05-18T02:54:21Z"},{"alias_kind":"pith_short_12","alias_value":"LGUNT6WECLWK","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_16","alias_value":"LGUNT6WECLWK7KIL","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_8","alias_value":"LGUNT6WE","created_at":"2026-05-18T12:27:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2013:LGUNT6WECLWK7KIL7EOWKORC2Q","target":"record","payload":{"canonical_record":{"source":{"id":"1310.3863","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-10-14T21:37:55Z","cross_cats_sorted":["stat.AP"],"title_canon_sha256":"d5c72cabe144b7b5471f1420fe7a1c620fff36d789cd69e8ba3beed4924817d1","abstract_canon_sha256":"886acf6d2e42aa084a43d16ec43daff85f033d5c9cddee7745447f6e83f09d35"},"schema_version":"1.0"},"canonical_sha256":"59a8d9fac412ecafa90bf91d653a22d43acc14b05b0cd1331bcbff347f854b50","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:54:21.219769Z","signature_b64":"/opTqrtWZkcA8eIUo6BGbQ1CC7KsY96Mjo4VAajKmTQI6M97qXpkSYr/gdTV6a7VFq7DRv8qVg1Vls9QUg6IBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"59a8d9fac412ecafa90bf91d653a22d43acc14b05b0cd1331bcbff347f854b50","last_reissued_at":"2026-05-18T02:54:21.219333Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:54:21.219333Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1310.3863","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:54:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Wf6l52jkf88qqgxast8LOVT72UyRtsGP2tPRRK7m9nYXz5Trd0iL/o16HlTEvM4ASfqegGN6nMqP8XzxJXyFCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T00:36:00.722842Z"},"content_sha256":"8f0b72c108d70b7241f0542883a837b0c4172b3753920dfe11a2794f0adf16c7","schema_version":"1.0","event_id":"sha256:8f0b72c108d70b7241f0542883a837b0c4172b3753920dfe11a2794f0adf16c7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2013:LGUNT6WECLWK7KIL7EOWKORC2Q","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Estimating Time-varying Brain Connectivity Networks from Functional MRI Time Series","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.AP"],"primary_cat":"stat.ML","authors_text":"Christoforos Anagnostopoulos, David Sharp, Giovanni Montana, Peter Hellyer, Ricardo Pio Monti, Robert Leech","submitted_at":"2013-10-14T21:37:55Z","abstract_excerpt":"Understanding the functional architecture of the brain in terms of networks is becoming increasingly common. In most fMRI applications functional networks are assumed to be stationary, resulting in a single network estimated for the entire time course. However recent results suggest that the connectivity between brain regions is highly non-stationary even at rest. As a result, there is a need for new brain imaging methodologies that comprehensively account for the dynamic (i.e., non-stationary) nature of the fMRI data. In this work we propose the Smooth Incremental Graphical Lasso Estimation ("},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1310.3863","kind":"arxiv","version":2},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:54:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l2cR5F+/UFL/Dl5n8fo5hEI/2d4JkYnLy+yJvLrosu/qbbegwvz+3ab1CajBXjfh/PgA4YCeFIQGTHhQ3QBMAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T00:36:00.723538Z"},"content_sha256":"079fc3082241c57eda3b69affc9cc66ff57d8b791d0ff8e3ca164c8d6c1f625c","schema_version":"1.0","event_id":"sha256:079fc3082241c57eda3b69affc9cc66ff57d8b791d0ff8e3ca164c8d6c1f625c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LGUNT6WECLWK7KIL7EOWKORC2Q/bundle.json","state_url":"https://pith.science/pith/LGUNT6WECLWK7KIL7EOWKORC2Q/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LGUNT6WECLWK7KIL7EOWKORC2Q/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-05-26T00:36:00Z","links":{"resolver":"https://pith.science/pith/LGUNT6WECLWK7KIL7EOWKORC2Q","bundle":"https://pith.science/pith/LGUNT6WECLWK7KIL7EOWKORC2Q/bundle.json","state":"https://pith.science/pith/LGUNT6WECLWK7KIL7EOWKORC2Q/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LGUNT6WECLWK7KIL7EOWKORC2Q/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2013:LGUNT6WECLWK7KIL7EOWKORC2Q","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"886acf6d2e42aa084a43d16ec43daff85f033d5c9cddee7745447f6e83f09d35","cross_cats_sorted":["stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-10-14T21:37:55Z","title_canon_sha256":"d5c72cabe144b7b5471f1420fe7a1c620fff36d789cd69e8ba3beed4924817d1"},"schema_version":"1.0","source":{"id":"1310.3863","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1310.3863","created_at":"2026-05-18T02:54:21Z"},{"alias_kind":"arxiv_version","alias_value":"1310.3863v2","created_at":"2026-05-18T02:54:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1310.3863","created_at":"2026-05-18T02:54:21Z"},{"alias_kind":"pith_short_12","alias_value":"LGUNT6WECLWK","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_16","alias_value":"LGUNT6WECLWK7KIL","created_at":"2026-05-18T12:27:51Z"},{"alias_kind":"pith_short_8","alias_value":"LGUNT6WE","created_at":"2026-05-18T12:27:51Z"}],"graph_snapshots":[{"event_id":"sha256:079fc3082241c57eda3b69affc9cc66ff57d8b791d0ff8e3ca164c8d6c1f625c","target":"graph","created_at":"2026-05-18T02:54:21Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"Understanding the functional architecture of the brain in terms of networks is becoming increasingly common. In most fMRI applications functional networks are assumed to be stationary, resulting in a single network estimated for the entire time course. However recent results suggest that the connectivity between brain regions is highly non-stationary even at rest. As a result, there is a need for new brain imaging methodologies that comprehensively account for the dynamic (i.e., non-stationary) nature of the fMRI data. In this work we propose the Smooth Incremental Graphical Lasso Estimation (","authors_text":"Christoforos Anagnostopoulos, David Sharp, Giovanni Montana, Peter Hellyer, Ricardo Pio Monti, Robert Leech","cross_cats":["stat.AP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-10-14T21:37:55Z","title":"Estimating Time-varying Brain Connectivity Networks from Functional MRI Time Series"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1310.3863","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:8f0b72c108d70b7241f0542883a837b0c4172b3753920dfe11a2794f0adf16c7","target":"record","created_at":"2026-05-18T02:54:21Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"886acf6d2e42aa084a43d16ec43daff85f033d5c9cddee7745447f6e83f09d35","cross_cats_sorted":["stat.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2013-10-14T21:37:55Z","title_canon_sha256":"d5c72cabe144b7b5471f1420fe7a1c620fff36d789cd69e8ba3beed4924817d1"},"schema_version":"1.0","source":{"id":"1310.3863","kind":"arxiv","version":2}},"canonical_sha256":"59a8d9fac412ecafa90bf91d653a22d43acc14b05b0cd1331bcbff347f854b50","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"59a8d9fac412ecafa90bf91d653a22d43acc14b05b0cd1331bcbff347f854b50","first_computed_at":"2026-05-18T02:54:21.219333Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:54:21.219333Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/opTqrtWZkcA8eIUo6BGbQ1CC7KsY96Mjo4VAajKmTQI6M97qXpkSYr/gdTV6a7VFq7DRv8qVg1Vls9QUg6IBA==","signature_status":"signed_v1","signed_at":"2026-05-18T02:54:21.219769Z","signed_message":"canonical_sha256_bytes"},"source_id":"1310.3863","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8f0b72c108d70b7241f0542883a837b0c4172b3753920dfe11a2794f0adf16c7","sha256:079fc3082241c57eda3b69affc9cc66ff57d8b791d0ff8e3ca164c8d6c1f625c"],"state_sha256":"2803d167c349f44cc13c6786825d2ffbd7cee636dda907935ec8c5cf18b434f5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oVQKCH8YeJbUAXxTqRPLlLdDqiWQQB13UAGc00xjEhzAyVz0qvw6UJWAhNLU/Cm1ux6n4HOP4ULZSOW0H2IqCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T00:36:00.727119Z","bundle_sha256":"1fa32c9777a0c8f29f353449d598d199ae9f3aadd24fd7fa958b24767d9aa39c"}}