{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2014:7UEEJP5WE55WDSKERU7O4SVJSD","short_pith_number":"pith:7UEEJP5W","canonical_record":{"source":{"id":"1405.0573","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-05-03T11:58:27Z","cross_cats_sorted":["q-bio.NC"],"title_canon_sha256":"2d70728bd93c7e400c9b3da7a861048f55044762dc970460e0a34fe46c8eb46e","abstract_canon_sha256":"b1a89bd13ee4327e77a9b48a5e914b5ad3d9a7d6724a2779391b622de7649b93"},"schema_version":"1.0"},"canonical_sha256":"fd0844bfb6277b61c9448d3eee4aa990ff2fa01347aaba3da46fa68eee0807b5","source":{"kind":"arxiv","id":"1405.0573","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1405.0573","created_at":"2026-05-18T02:52:41Z"},{"alias_kind":"arxiv_version","alias_value":"1405.0573v1","created_at":"2026-05-18T02:52:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1405.0573","created_at":"2026-05-18T02:52:41Z"},{"alias_kind":"pith_short_12","alias_value":"7UEEJP5WE55W","created_at":"2026-05-18T12:28:19Z"},{"alias_kind":"pith_short_16","alias_value":"7UEEJP5WE55WDSKE","created_at":"2026-05-18T12:28:19Z"},{"alias_kind":"pith_short_8","alias_value":"7UEEJP5W","created_at":"2026-05-18T12:28:19Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2014:7UEEJP5WE55WDSKERU7O4SVJSD","target":"record","payload":{"canonical_record":{"source":{"id":"1405.0573","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-05-03T11:58:27Z","cross_cats_sorted":["q-bio.NC"],"title_canon_sha256":"2d70728bd93c7e400c9b3da7a861048f55044762dc970460e0a34fe46c8eb46e","abstract_canon_sha256":"b1a89bd13ee4327e77a9b48a5e914b5ad3d9a7d6724a2779391b622de7649b93"},"schema_version":"1.0"},"canonical_sha256":"fd0844bfb6277b61c9448d3eee4aa990ff2fa01347aaba3da46fa68eee0807b5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T02:52:41.170741Z","signature_b64":"zOK3wljV26hqKSreQrO3Do0ySSu3bwHb64rMchA9HjogU8EDXKBMhvycIMhq/UMTumGiipbfhMpxHTQYCdf1Aw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fd0844bfb6277b61c9448d3eee4aa990ff2fa01347aaba3da46fa68eee0807b5","last_reissued_at":"2026-05-18T02:52:41.170312Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T02:52:41.170312Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1405.0573","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:52:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AoFzBv0yHo7MYhvEv3B1Awf4/+SEPLr+U/b+BQ/GphHhzo9ebLhmN9h7s2p2dSZ0ncwlGwjPJyDzaE2RgQujCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T15:08:45.190751Z"},"content_sha256":"28efcfb3bbf03c2cb5534399a81a39e31789c280b2643c0f23d5112e32959421","schema_version":"1.0","event_id":"sha256:28efcfb3bbf03c2cb5534399a81a39e31789c280b2643c0f23d5112e32959421"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2014:7UEEJP5WE55WDSKERU7O4SVJSD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Spatial Neural Networks and their Functional Samples: Similarities and Differences","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-bio.NC"],"primary_cat":"cs.NE","authors_text":"Liang Zhao, Lucas Antiqueira","submitted_at":"2014-05-03T11:58:27Z","abstract_excerpt":"Models of neural networks have proven their utility in the development of learning algorithms in computer science and in the theoretical study of brain dynamics in computational neuroscience. We propose in this paper a spatial neural network model to analyze the important class of functional networks, which are commonly employed in computational studies of clinical brain imaging time series. We developed a simulation framework inspired by multichannel brain surface recordings (more specifically, EEG -- electroencephalogram) in order to link the mesoscopic network dynamics (represented by sampl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1405.0573","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T02:52:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"R8Oc28BBn4CRxXkixYNKuf4gmgw6FDDJ16Y1EBNOTOCcKEFCwLST+uyevkNiGrm2f3oMgdoF19L0JPcpwoK3Dw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-08T15:08:45.191356Z"},"content_sha256":"2e551935f64ee07c6974be9a1e187fed22a198721e7466567636676d52c4c600","schema_version":"1.0","event_id":"sha256:2e551935f64ee07c6974be9a1e187fed22a198721e7466567636676d52c4c600"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7UEEJP5WE55WDSKERU7O4SVJSD/bundle.json","state_url":"https://pith.science/pith/7UEEJP5WE55WDSKERU7O4SVJSD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7UEEJP5WE55WDSKERU7O4SVJSD/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":"2026-06-08T15:08:45Z","links":{"resolver":"https://pith.science/pith/7UEEJP5WE55WDSKERU7O4SVJSD","bundle":"https://pith.science/pith/7UEEJP5WE55WDSKERU7O4SVJSD/bundle.json","state":"https://pith.science/pith/7UEEJP5WE55WDSKERU7O4SVJSD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7UEEJP5WE55WDSKERU7O4SVJSD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2014:7UEEJP5WE55WDSKERU7O4SVJSD","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":"b1a89bd13ee4327e77a9b48a5e914b5ad3d9a7d6724a2779391b622de7649b93","cross_cats_sorted":["q-bio.NC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-05-03T11:58:27Z","title_canon_sha256":"2d70728bd93c7e400c9b3da7a861048f55044762dc970460e0a34fe46c8eb46e"},"schema_version":"1.0","source":{"id":"1405.0573","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1405.0573","created_at":"2026-05-18T02:52:41Z"},{"alias_kind":"arxiv_version","alias_value":"1405.0573v1","created_at":"2026-05-18T02:52:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1405.0573","created_at":"2026-05-18T02:52:41Z"},{"alias_kind":"pith_short_12","alias_value":"7UEEJP5WE55W","created_at":"2026-05-18T12:28:19Z"},{"alias_kind":"pith_short_16","alias_value":"7UEEJP5WE55WDSKE","created_at":"2026-05-18T12:28:19Z"},{"alias_kind":"pith_short_8","alias_value":"7UEEJP5W","created_at":"2026-05-18T12:28:19Z"}],"graph_snapshots":[{"event_id":"sha256:2e551935f64ee07c6974be9a1e187fed22a198721e7466567636676d52c4c600","target":"graph","created_at":"2026-05-18T02:52:41Z","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":"Models of neural networks have proven their utility in the development of learning algorithms in computer science and in the theoretical study of brain dynamics in computational neuroscience. We propose in this paper a spatial neural network model to analyze the important class of functional networks, which are commonly employed in computational studies of clinical brain imaging time series. We developed a simulation framework inspired by multichannel brain surface recordings (more specifically, EEG -- electroencephalogram) in order to link the mesoscopic network dynamics (represented by sampl","authors_text":"Liang Zhao, Lucas Antiqueira","cross_cats":["q-bio.NC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-05-03T11:58:27Z","title":"Spatial Neural Networks and their Functional Samples: Similarities and Differences"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1405.0573","kind":"arxiv","version":1},"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":"sha256:28efcfb3bbf03c2cb5534399a81a39e31789c280b2643c0f23d5112e32959421","target":"record","created_at":"2026-05-18T02:52:41Z","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":"b1a89bd13ee4327e77a9b48a5e914b5ad3d9a7d6724a2779391b622de7649b93","cross_cats_sorted":["q-bio.NC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2014-05-03T11:58:27Z","title_canon_sha256":"2d70728bd93c7e400c9b3da7a861048f55044762dc970460e0a34fe46c8eb46e"},"schema_version":"1.0","source":{"id":"1405.0573","kind":"arxiv","version":1}},"canonical_sha256":"fd0844bfb6277b61c9448d3eee4aa990ff2fa01347aaba3da46fa68eee0807b5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fd0844bfb6277b61c9448d3eee4aa990ff2fa01347aaba3da46fa68eee0807b5","first_computed_at":"2026-05-18T02:52:41.170312Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T02:52:41.170312Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zOK3wljV26hqKSreQrO3Do0ySSu3bwHb64rMchA9HjogU8EDXKBMhvycIMhq/UMTumGiipbfhMpxHTQYCdf1Aw==","signature_status":"signed_v1","signed_at":"2026-05-18T02:52:41.170741Z","signed_message":"canonical_sha256_bytes"},"source_id":"1405.0573","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:28efcfb3bbf03c2cb5534399a81a39e31789c280b2643c0f23d5112e32959421","sha256:2e551935f64ee07c6974be9a1e187fed22a198721e7466567636676d52c4c600"],"state_sha256":"b30d0747e8206feaf7a0b5058a6f26763d97bdba4927a64918f994fe5b17715e"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9g0Kkv9iBDG2jGLtp9pB6QVMKLmBuDiMMnokQblWl2SfmKhq18LLfpZD0gaRYLoL1TFBV2xs4SUEWvtDKU+6Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-08T15:08:45.194952Z","bundle_sha256":"cf14b3bab9afea52c3f1330a1648632c1bdc41752d4ac781ab29abaff4c26654"}}