{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:KZNNNYQF3ZGXBJBVEI75V6ENGD","short_pith_number":"pith:KZNNNYQF","canonical_record":{"source":{"id":"1802.02210","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-19T05:12:59Z","cross_cats_sorted":[],"title_canon_sha256":"a8e156da42d5b63d2bb18a91e03a618b3cd2d5ddb554b68507c329dfddf532d0","abstract_canon_sha256":"a179d5201755960795d8a7d349807cead90086d776de9668e7d2dd777de44128"},"schema_version":"1.0"},"canonical_sha256":"565ad6e205de4d70a435223fdaf88d30e0966a62bf644b6a5f0ad76dba7ad3fb","source":{"kind":"arxiv","id":"1802.02210","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.02210","created_at":"2026-05-18T00:24:08Z"},{"alias_kind":"arxiv_version","alias_value":"1802.02210v1","created_at":"2026-05-18T00:24:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.02210","created_at":"2026-05-18T00:24:08Z"},{"alias_kind":"pith_short_12","alias_value":"KZNNNYQF3ZGX","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_16","alias_value":"KZNNNYQF3ZGXBJBV","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_8","alias_value":"KZNNNYQF","created_at":"2026-05-18T12:32:33Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:KZNNNYQF3ZGXBJBVEI75V6ENGD","target":"record","payload":{"canonical_record":{"source":{"id":"1802.02210","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-19T05:12:59Z","cross_cats_sorted":[],"title_canon_sha256":"a8e156da42d5b63d2bb18a91e03a618b3cd2d5ddb554b68507c329dfddf532d0","abstract_canon_sha256":"a179d5201755960795d8a7d349807cead90086d776de9668e7d2dd777de44128"},"schema_version":"1.0"},"canonical_sha256":"565ad6e205de4d70a435223fdaf88d30e0966a62bf644b6a5f0ad76dba7ad3fb","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:24:08.923535Z","signature_b64":"NEJPnaAGaXOBoe8w/y1x2Pu6HSEL9QXy6ShHIYRX38awjL2lznN/gMy2mYhZfmVjVMGjHZD54z1r2uGLu0iQCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"565ad6e205de4d70a435223fdaf88d30e0966a62bf644b6a5f0ad76dba7ad3fb","last_reissued_at":"2026-05-18T00:24:08.922921Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:24:08.922921Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1802.02210","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":"2026-05-18T00:24:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"94clQ1XtY7JN31yxun/XBx0SnEByY1l9Sqvn738So+wTlM9A0OQ9HZhXo+tZRgzX0qCecRcMoMP3IFYuZ+QzCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T11:59:52.764594Z"},"content_sha256":"11c56ba7f493dcc0e3fd084eed4419b7f727b4b97969a985e63e9711ac486f17","schema_version":"1.0","event_id":"sha256:11c56ba7f493dcc0e3fd084eed4419b7f727b4b97969a985e63e9711ac486f17"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:KZNNNYQF3ZGXBJBVEI75V6ENGD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Describing Semantic Representations of Brain Activity Evoked by Visual Stimuli","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Eri Matsuo, Hideki Asoh, Ichiro Kobayashi, Satoshi Nishida, Shinji Nishimoto","submitted_at":"2018-01-19T05:12:59Z","abstract_excerpt":"Quantitative modeling of human brain activity based on language representations has been actively studied in systems neuroscience. However, previous studies examined word-level representation, and little is known about whether we could recover structured sentences from brain activity. This study attempts to generate natural language descriptions of semantic contents from human brain activity evoked by visual stimuli. To effectively use a small amount of available brain activity data, our proposed method employs a pre-trained image-captioning network model using a deep learning framework. To ap"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.02210","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":"2026-05-18T00:24:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"T2PYwaWhtaX2lQWtYKt45FeHQ185bcLq5NJvF3oL90BJ8Lx7q8aO7sFSw4tYygJXpKRagY9A3EGTasWEpMCDAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-29T11:59:52.764934Z"},"content_sha256":"b5221cfe7d32038b58fe4e4b038d624caa9fcb70f11e933da9c131d0d06abceb","schema_version":"1.0","event_id":"sha256:b5221cfe7d32038b58fe4e4b038d624caa9fcb70f11e933da9c131d0d06abceb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/KZNNNYQF3ZGXBJBVEI75V6ENGD/bundle.json","state_url":"https://pith.science/pith/KZNNNYQF3ZGXBJBVEI75V6ENGD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/KZNNNYQF3ZGXBJBVEI75V6ENGD/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":"2026-06-29T11:59:52Z","links":{"resolver":"https://pith.science/pith/KZNNNYQF3ZGXBJBVEI75V6ENGD","bundle":"https://pith.science/pith/KZNNNYQF3ZGXBJBVEI75V6ENGD/bundle.json","state":"https://pith.science/pith/KZNNNYQF3ZGXBJBVEI75V6ENGD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/KZNNNYQF3ZGXBJBVEI75V6ENGD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:KZNNNYQF3ZGXBJBVEI75V6ENGD","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":"a179d5201755960795d8a7d349807cead90086d776de9668e7d2dd777de44128","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-19T05:12:59Z","title_canon_sha256":"a8e156da42d5b63d2bb18a91e03a618b3cd2d5ddb554b68507c329dfddf532d0"},"schema_version":"1.0","source":{"id":"1802.02210","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1802.02210","created_at":"2026-05-18T00:24:08Z"},{"alias_kind":"arxiv_version","alias_value":"1802.02210v1","created_at":"2026-05-18T00:24:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1802.02210","created_at":"2026-05-18T00:24:08Z"},{"alias_kind":"pith_short_12","alias_value":"KZNNNYQF3ZGX","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_16","alias_value":"KZNNNYQF3ZGXBJBV","created_at":"2026-05-18T12:32:33Z"},{"alias_kind":"pith_short_8","alias_value":"KZNNNYQF","created_at":"2026-05-18T12:32:33Z"}],"graph_snapshots":[{"event_id":"sha256:b5221cfe7d32038b58fe4e4b038d624caa9fcb70f11e933da9c131d0d06abceb","target":"graph","created_at":"2026-05-18T00:24:08Z","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":"Quantitative modeling of human brain activity based on language representations has been actively studied in systems neuroscience. However, previous studies examined word-level representation, and little is known about whether we could recover structured sentences from brain activity. This study attempts to generate natural language descriptions of semantic contents from human brain activity evoked by visual stimuli. To effectively use a small amount of available brain activity data, our proposed method employs a pre-trained image-captioning network model using a deep learning framework. To ap","authors_text":"Eri Matsuo, Hideki Asoh, Ichiro Kobayashi, Satoshi Nishida, Shinji Nishimoto","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-19T05:12:59Z","title":"Describing Semantic Representations of Brain Activity Evoked by Visual Stimuli"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1802.02210","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":"sha256:11c56ba7f493dcc0e3fd084eed4419b7f727b4b97969a985e63e9711ac486f17","target":"record","created_at":"2026-05-18T00:24:08Z","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":"a179d5201755960795d8a7d349807cead90086d776de9668e7d2dd777de44128","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2018-01-19T05:12:59Z","title_canon_sha256":"a8e156da42d5b63d2bb18a91e03a618b3cd2d5ddb554b68507c329dfddf532d0"},"schema_version":"1.0","source":{"id":"1802.02210","kind":"arxiv","version":1}},"canonical_sha256":"565ad6e205de4d70a435223fdaf88d30e0966a62bf644b6a5f0ad76dba7ad3fb","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"565ad6e205de4d70a435223fdaf88d30e0966a62bf644b6a5f0ad76dba7ad3fb","first_computed_at":"2026-05-18T00:24:08.922921Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:24:08.922921Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NEJPnaAGaXOBoe8w/y1x2Pu6HSEL9QXy6ShHIYRX38awjL2lznN/gMy2mYhZfmVjVMGjHZD54z1r2uGLu0iQCA==","signature_status":"signed_v1","signed_at":"2026-05-18T00:24:08.923535Z","signed_message":"canonical_sha256_bytes"},"source_id":"1802.02210","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:11c56ba7f493dcc0e3fd084eed4419b7f727b4b97969a985e63e9711ac486f17","sha256:b5221cfe7d32038b58fe4e4b038d624caa9fcb70f11e933da9c131d0d06abceb"],"state_sha256":"1c3f3ff2996f6f83fd54abd3c3d1102cc8cf3468126e9ea6b2d4f57e22429310"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mlA+T7ZX0kSTAPGBa+9E7ElTdUw7c9i/jPD4aRo1REBzEvESyFMYXg9adPVkAlu2TDFcqrSWQieJhraQjc2hBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-29T11:59:52.766824Z","bundle_sha256":"2101c9011bad7e4edb7ac2cba450195b6a5d28a111c87f637808bd9f97f68180"}}