{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:72CJN7LPSLYG7H5JEZHEDYQ4RP","short_pith_number":"pith:72CJN7LP","canonical_record":{"source":{"id":"1612.08392","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-12-26T14:37:57Z","cross_cats_sorted":["cs.LG","q-bio.NC"],"title_canon_sha256":"4cc836445dc0546eff3d0fa20bdaa1ebee354d9569a2345757da785285bf88d2","abstract_canon_sha256":"cc387676d07a449647481f641ae5548ecbf09ee256837a82f99c679f97ace2f2"},"schema_version":"1.0"},"canonical_sha256":"fe8496fd6f92f06f9fa9264e41e21c8bf5f8ba1090d994b3ecdd3a2a1081906c","source":{"kind":"arxiv","id":"1612.08392","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1612.08392","created_at":"2026-05-18T00:53:53Z"},{"alias_kind":"arxiv_version","alias_value":"1612.08392v1","created_at":"2026-05-18T00:53:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.08392","created_at":"2026-05-18T00:53:53Z"},{"alias_kind":"pith_short_12","alias_value":"72CJN7LPSLYG","created_at":"2026-05-18T12:30:04Z"},{"alias_kind":"pith_short_16","alias_value":"72CJN7LPSLYG7H5J","created_at":"2026-05-18T12:30:04Z"},{"alias_kind":"pith_short_8","alias_value":"72CJN7LP","created_at":"2026-05-18T12:30:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:72CJN7LPSLYG7H5JEZHEDYQ4RP","target":"record","payload":{"canonical_record":{"source":{"id":"1612.08392","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-12-26T14:37:57Z","cross_cats_sorted":["cs.LG","q-bio.NC"],"title_canon_sha256":"4cc836445dc0546eff3d0fa20bdaa1ebee354d9569a2345757da785285bf88d2","abstract_canon_sha256":"cc387676d07a449647481f641ae5548ecbf09ee256837a82f99c679f97ace2f2"},"schema_version":"1.0"},"canonical_sha256":"fe8496fd6f92f06f9fa9264e41e21c8bf5f8ba1090d994b3ecdd3a2a1081906c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:53:53.165888Z","signature_b64":"l0KO90R1zPQbBaloBOFY4EZRleSwiO+NsicdUz6sQtduCDmQSonrpnMx1VV8jQZ9/ljgKx2pxBmEMVDCuN1JBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fe8496fd6f92f06f9fa9264e41e21c8bf5f8ba1090d994b3ecdd3a2a1081906c","last_reissued_at":"2026-05-18T00:53:53.165302Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:53:53.165302Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1612.08392","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":"2026-05-18T00:53:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kZooQ2KN3YVUjsRtzW06o3pZvE6m4Qa1WpOWCeeHq17DeDLz5x+WadnEjt1OVM7+HjG2L0DTZMVqY/SzSWxbDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-12T09:22:40.507601Z"},"content_sha256":"a4cb6dad61717f9c6990de713ed7bada7aec176498c4984cc4f858d58524898a","schema_version":"1.0","event_id":"sha256:a4cb6dad61717f9c6990de713ed7bada7aec176498c4984cc4f858d58524898a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:72CJN7LPSLYG7H5JEZHEDYQ4RP","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Multi-Region Neural Representation: A novel model for decoding visual stimuli in human brains","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","q-bio.NC"],"primary_cat":"stat.ML","authors_text":"Daoqiang Zhang, Muhammad Yousefnezhad","submitted_at":"2016-12-26T14:37:57Z","abstract_excerpt":"Multivariate Pattern (MVP) classification holds enormous potential for decoding visual stimuli in the human brain by employing task-based fMRI data sets. There is a wide range of challenges in the MVP techniques, i.e. decreasing noise and sparsity, defining effective regions of interest (ROIs), visualizing results, and the cost of brain studies. In overcoming these challenges, this paper proposes a novel model of neural representation, which can automatically detect the active regions for each visual stimulus and then utilize these anatomical regions for visualizing and analyzing the functiona"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.08392","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":"2026-05-18T00:53:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"KdpG4ICah0kpYbl73em5xY2QvpezLKrqgwjS18M7lhqZq1fLlpdtibS3u0C/9gJzIhtCibl9SPCOL2Aux3HADA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-12T09:22:40.507960Z"},"content_sha256":"b5bbc17055b03a6f72a9c619c49e05efdb784e2d92ab89b3ca7701de809ecc85","schema_version":"1.0","event_id":"sha256:b5bbc17055b03a6f72a9c619c49e05efdb784e2d92ab89b3ca7701de809ecc85"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/72CJN7LPSLYG7H5JEZHEDYQ4RP/bundle.json","state_url":"https://pith.science/pith/72CJN7LPSLYG7H5JEZHEDYQ4RP/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/72CJN7LPSLYG7H5JEZHEDYQ4RP/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":"2026-06-12T09:22:40Z","links":{"resolver":"https://pith.science/pith/72CJN7LPSLYG7H5JEZHEDYQ4RP","bundle":"https://pith.science/pith/72CJN7LPSLYG7H5JEZHEDYQ4RP/bundle.json","state":"https://pith.science/pith/72CJN7LPSLYG7H5JEZHEDYQ4RP/state.json","well_known_bundle":"https://pith.science/.well-known/pith/72CJN7LPSLYG7H5JEZHEDYQ4RP/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:72CJN7LPSLYG7H5JEZHEDYQ4RP","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":"cc387676d07a449647481f641ae5548ecbf09ee256837a82f99c679f97ace2f2","cross_cats_sorted":["cs.LG","q-bio.NC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-12-26T14:37:57Z","title_canon_sha256":"4cc836445dc0546eff3d0fa20bdaa1ebee354d9569a2345757da785285bf88d2"},"schema_version":"1.0","source":{"id":"1612.08392","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1612.08392","created_at":"2026-05-18T00:53:53Z"},{"alias_kind":"arxiv_version","alias_value":"1612.08392v1","created_at":"2026-05-18T00:53:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.08392","created_at":"2026-05-18T00:53:53Z"},{"alias_kind":"pith_short_12","alias_value":"72CJN7LPSLYG","created_at":"2026-05-18T12:30:04Z"},{"alias_kind":"pith_short_16","alias_value":"72CJN7LPSLYG7H5J","created_at":"2026-05-18T12:30:04Z"},{"alias_kind":"pith_short_8","alias_value":"72CJN7LP","created_at":"2026-05-18T12:30:04Z"}],"graph_snapshots":[{"event_id":"sha256:b5bbc17055b03a6f72a9c619c49e05efdb784e2d92ab89b3ca7701de809ecc85","target":"graph","created_at":"2026-05-18T00:53:53Z","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":"Multivariate Pattern (MVP) classification holds enormous potential for decoding visual stimuli in the human brain by employing task-based fMRI data sets. There is a wide range of challenges in the MVP techniques, i.e. decreasing noise and sparsity, defining effective regions of interest (ROIs), visualizing results, and the cost of brain studies. In overcoming these challenges, this paper proposes a novel model of neural representation, which can automatically detect the active regions for each visual stimulus and then utilize these anatomical regions for visualizing and analyzing the functiona","authors_text":"Daoqiang Zhang, Muhammad Yousefnezhad","cross_cats":["cs.LG","q-bio.NC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-12-26T14:37:57Z","title":"Multi-Region Neural Representation: A novel model for decoding visual stimuli in human brains"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.08392","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:a4cb6dad61717f9c6990de713ed7bada7aec176498c4984cc4f858d58524898a","target":"record","created_at":"2026-05-18T00:53:53Z","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":"cc387676d07a449647481f641ae5548ecbf09ee256837a82f99c679f97ace2f2","cross_cats_sorted":["cs.LG","q-bio.NC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ML","submitted_at":"2016-12-26T14:37:57Z","title_canon_sha256":"4cc836445dc0546eff3d0fa20bdaa1ebee354d9569a2345757da785285bf88d2"},"schema_version":"1.0","source":{"id":"1612.08392","kind":"arxiv","version":1}},"canonical_sha256":"fe8496fd6f92f06f9fa9264e41e21c8bf5f8ba1090d994b3ecdd3a2a1081906c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fe8496fd6f92f06f9fa9264e41e21c8bf5f8ba1090d994b3ecdd3a2a1081906c","first_computed_at":"2026-05-18T00:53:53.165302Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:53:53.165302Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"l0KO90R1zPQbBaloBOFY4EZRleSwiO+NsicdUz6sQtduCDmQSonrpnMx1VV8jQZ9/ljgKx2pxBmEMVDCuN1JBw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:53:53.165888Z","signed_message":"canonical_sha256_bytes"},"source_id":"1612.08392","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a4cb6dad61717f9c6990de713ed7bada7aec176498c4984cc4f858d58524898a","sha256:b5bbc17055b03a6f72a9c619c49e05efdb784e2d92ab89b3ca7701de809ecc85"],"state_sha256":"bc4809c15928ec1bdda220c6a05ff51c58c348009df5b76b1bae6a2bd5f2d091"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0yxLVyVBAicaxKZVhp/u/lQiPFy+/QBCn8PIir2r4OuXOWkDS64EVYbct5Lr5xpSBAbiG6vonjoGJLC5t48eBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-12T09:22:40.509916Z","bundle_sha256":"60bdebb38ef6463f42b1f0bd655730c19858e4ad63b50331daafa1dd3d0bfc90"}}