{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:HNQTBXQIKDKTUWJMQYWMAILXRG","short_pith_number":"pith:HNQTBXQI","canonical_record":{"source":{"id":"1708.01888","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2017-08-06T13:19:57Z","cross_cats_sorted":["q-bio.QM"],"title_canon_sha256":"fcce5c8bd953b63b3f6ac60f2cb5af899826dbdf6c402921a77a18d600c69aba","abstract_canon_sha256":"8c60161c68ce61c34c3e187fa5d3593ce48edbd641573d9f422db1599996ea63"},"schema_version":"1.0"},"canonical_sha256":"3b6130de0850d53a592c862cc0217789a99d2c1f35901e5167e3e5c91f61fc21","source":{"kind":"arxiv","id":"1708.01888","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.01888","created_at":"2026-05-18T00:27:57Z"},{"alias_kind":"arxiv_version","alias_value":"1708.01888v2","created_at":"2026-05-18T00:27:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.01888","created_at":"2026-05-18T00:27:57Z"},{"alias_kind":"pith_short_12","alias_value":"HNQTBXQIKDKT","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"HNQTBXQIKDKTUWJM","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"HNQTBXQI","created_at":"2026-05-18T12:31:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:HNQTBXQIKDKTUWJMQYWMAILXRG","target":"record","payload":{"canonical_record":{"source":{"id":"1708.01888","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2017-08-06T13:19:57Z","cross_cats_sorted":["q-bio.QM"],"title_canon_sha256":"fcce5c8bd953b63b3f6ac60f2cb5af899826dbdf6c402921a77a18d600c69aba","abstract_canon_sha256":"8c60161c68ce61c34c3e187fa5d3593ce48edbd641573d9f422db1599996ea63"},"schema_version":"1.0"},"canonical_sha256":"3b6130de0850d53a592c862cc0217789a99d2c1f35901e5167e3e5c91f61fc21","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:27:57.145661Z","signature_b64":"0FXA5QbAyDJccs6xMjtB40a+bKBua0kDBDt9g/2tCUvAMMc2824hpfbSv/fQ0xEB1pTooYYIeo8IMAfVjHyoDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3b6130de0850d53a592c862cc0217789a99d2c1f35901e5167e3e5c91f61fc21","last_reissued_at":"2026-05-18T00:27:57.144976Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:27:57.144976Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1708.01888","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":"2026-05-18T00:27:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"h7FLq3JA0i5G4+FqwWAabYDyLnvuSrv6oIaCXIGEWawD6Z7V9QnBhfjdDK871vYxoj4vRtU5zjDTsghBQsR+Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T03:58:30.351010Z"},"content_sha256":"17cde1ce175ba3eebf609f547929af7c5784ce176aabad8c0ab9395dfc5f40ba","schema_version":"1.0","event_id":"sha256:17cde1ce175ba3eebf609f547929af7c5784ce176aabad8c0ab9395dfc5f40ba"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:HNQTBXQIKDKTUWJMQYWMAILXRG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Connectivity Inference from Neural Recording Data: Challenges, Mathematical Bases and Research Directions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["q-bio.QM"],"primary_cat":"q-bio.NC","authors_text":"Ildefons Magrans de Abril, Junichiro Yoshimoto, Kenji Doya","submitted_at":"2017-08-06T13:19:57Z","abstract_excerpt":"This article presents a review of computational methods for connectivity inference from neural activity data derived from multi-electrode recordings or fluorescence imaging. We first identify biophysical and technical challenges in connectivity inference along the data processing pipeline. We then review connectivity inference methods based on two major mathematical foundations, namely, descriptive model-free approaches and generative model-based approaches. We investigate representative studies in both categories and clarify which challenges have been addressed by which method. We further ide"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.01888","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":"2026-05-18T00:27:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Oud5ZqFM1hEj/DW7YfeoLjTaDjff9sN6oaKJhtsklYGLwL8h2DBKMmurheVKuhtA8zqUiQbrwLlglwOxqnGsBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-03T03:58:30.351361Z"},"content_sha256":"141d960e3b06524ae2ac56461b3fd57446a690970f6ac44e90eafecbd2a694bc","schema_version":"1.0","event_id":"sha256:141d960e3b06524ae2ac56461b3fd57446a690970f6ac44e90eafecbd2a694bc"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HNQTBXQIKDKTUWJMQYWMAILXRG/bundle.json","state_url":"https://pith.science/pith/HNQTBXQIKDKTUWJMQYWMAILXRG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HNQTBXQIKDKTUWJMQYWMAILXRG/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":"2026-06-03T03:58:30Z","links":{"resolver":"https://pith.science/pith/HNQTBXQIKDKTUWJMQYWMAILXRG","bundle":"https://pith.science/pith/HNQTBXQIKDKTUWJMQYWMAILXRG/bundle.json","state":"https://pith.science/pith/HNQTBXQIKDKTUWJMQYWMAILXRG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HNQTBXQIKDKTUWJMQYWMAILXRG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:HNQTBXQIKDKTUWJMQYWMAILXRG","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":"8c60161c68ce61c34c3e187fa5d3593ce48edbd641573d9f422db1599996ea63","cross_cats_sorted":["q-bio.QM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2017-08-06T13:19:57Z","title_canon_sha256":"fcce5c8bd953b63b3f6ac60f2cb5af899826dbdf6c402921a77a18d600c69aba"},"schema_version":"1.0","source":{"id":"1708.01888","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1708.01888","created_at":"2026-05-18T00:27:57Z"},{"alias_kind":"arxiv_version","alias_value":"1708.01888v2","created_at":"2026-05-18T00:27:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1708.01888","created_at":"2026-05-18T00:27:57Z"},{"alias_kind":"pith_short_12","alias_value":"HNQTBXQIKDKT","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_16","alias_value":"HNQTBXQIKDKTUWJM","created_at":"2026-05-18T12:31:18Z"},{"alias_kind":"pith_short_8","alias_value":"HNQTBXQI","created_at":"2026-05-18T12:31:18Z"}],"graph_snapshots":[{"event_id":"sha256:141d960e3b06524ae2ac56461b3fd57446a690970f6ac44e90eafecbd2a694bc","target":"graph","created_at":"2026-05-18T00:27:57Z","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":"This article presents a review of computational methods for connectivity inference from neural activity data derived from multi-electrode recordings or fluorescence imaging. We first identify biophysical and technical challenges in connectivity inference along the data processing pipeline. We then review connectivity inference methods based on two major mathematical foundations, namely, descriptive model-free approaches and generative model-based approaches. We investigate representative studies in both categories and clarify which challenges have been addressed by which method. We further ide","authors_text":"Ildefons Magrans de Abril, Junichiro Yoshimoto, Kenji Doya","cross_cats":["q-bio.QM"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2017-08-06T13:19:57Z","title":"Connectivity Inference from Neural Recording Data: Challenges, Mathematical Bases and Research Directions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1708.01888","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":"sha256:17cde1ce175ba3eebf609f547929af7c5784ce176aabad8c0ab9395dfc5f40ba","target":"record","created_at":"2026-05-18T00:27:57Z","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":"8c60161c68ce61c34c3e187fa5d3593ce48edbd641573d9f422db1599996ea63","cross_cats_sorted":["q-bio.QM"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2017-08-06T13:19:57Z","title_canon_sha256":"fcce5c8bd953b63b3f6ac60f2cb5af899826dbdf6c402921a77a18d600c69aba"},"schema_version":"1.0","source":{"id":"1708.01888","kind":"arxiv","version":2}},"canonical_sha256":"3b6130de0850d53a592c862cc0217789a99d2c1f35901e5167e3e5c91f61fc21","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3b6130de0850d53a592c862cc0217789a99d2c1f35901e5167e3e5c91f61fc21","first_computed_at":"2026-05-18T00:27:57.144976Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:27:57.144976Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0FXA5QbAyDJccs6xMjtB40a+bKBua0kDBDt9g/2tCUvAMMc2824hpfbSv/fQ0xEB1pTooYYIeo8IMAfVjHyoDQ==","signature_status":"signed_v1","signed_at":"2026-05-18T00:27:57.145661Z","signed_message":"canonical_sha256_bytes"},"source_id":"1708.01888","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:17cde1ce175ba3eebf609f547929af7c5784ce176aabad8c0ab9395dfc5f40ba","sha256:141d960e3b06524ae2ac56461b3fd57446a690970f6ac44e90eafecbd2a694bc"],"state_sha256":"2bf6be307c446d89b4938cd4725490ea0ce91f7ff11737bd0f0a10587878fffe"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wmxWJSWc4/RN1SO92IY8BGR7/oHLWObYWDpzGrlWrwJww4IKz91yUm9lugyXOjE35zudipN9nf6G55xwReS3Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-03T03:58:30.353593Z","bundle_sha256":"be6fb82def01eb627bda27d4eb3f888ed885ad8a94a02a1f4aece79e27208bc9"}}