{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2017:RJVFDOQJHE6GHASRM3U47BI2U3","short_pith_number":"pith:RJVFDOQJ","canonical_record":{"source":{"id":"1706.05796","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2017-06-19T06:11:17Z","cross_cats_sorted":["math.AP"],"title_canon_sha256":"9a1ab7a0901782cfc71e808c56d6afe8fa118022e3745224699619bcb28886f5","abstract_canon_sha256":"0aa55dee18891eda151d7b6af55ee9067094701e5c9681b2ae2dec2c7c7a7ac6"},"schema_version":"1.0"},"canonical_sha256":"8a6a51ba09393c63825166e9cf851aa6f9054b3178662cf678843fd93053a3c8","source":{"kind":"arxiv","id":"1706.05796","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.05796","created_at":"2026-05-18T00:42:08Z"},{"alias_kind":"arxiv_version","alias_value":"1706.05796v1","created_at":"2026-05-18T00:42:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.05796","created_at":"2026-05-18T00:42:08Z"},{"alias_kind":"pith_short_12","alias_value":"RJVFDOQJHE6G","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_16","alias_value":"RJVFDOQJHE6GHASR","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_8","alias_value":"RJVFDOQJ","created_at":"2026-05-18T12:31:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2017:RJVFDOQJHE6GHASRM3U47BI2U3","target":"record","payload":{"canonical_record":{"source":{"id":"1706.05796","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2017-06-19T06:11:17Z","cross_cats_sorted":["math.AP"],"title_canon_sha256":"9a1ab7a0901782cfc71e808c56d6afe8fa118022e3745224699619bcb28886f5","abstract_canon_sha256":"0aa55dee18891eda151d7b6af55ee9067094701e5c9681b2ae2dec2c7c7a7ac6"},"schema_version":"1.0"},"canonical_sha256":"8a6a51ba09393c63825166e9cf851aa6f9054b3178662cf678843fd93053a3c8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:42:08.868820Z","signature_b64":"442TPAifQb1TxJ5rItB8G5hhoqg7r8R6FN3snMSAPvM0/B5mAiV1k2bFJOaLbD+SHe2B7jXK+iXTOV6uA0JBBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8a6a51ba09393c63825166e9cf851aa6f9054b3178662cf678843fd93053a3c8","last_reissued_at":"2026-05-18T00:42:08.868374Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:42:08.868374Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1706.05796","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":"2026-05-18T00:42:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hCNA6vs4f89YvXs+QXLueSx9RoI8N0YQC/OZ05ugCtg78gz1ofGlBXYUxQAgbp6vxcOQHcutLM/beYB+nuoMCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T11:21:11.917079Z"},"content_sha256":"89a6a1fd75b3347ec6fe3a74c7dc86a7ea4a576d2587edc900760e220d51198e","schema_version":"1.0","event_id":"sha256:89a6a1fd75b3347ec6fe3a74c7dc86a7ea4a576d2587edc900760e220d51198e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2017:RJVFDOQJHE6GHASRM3U47BI2U3","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Distributed synaptic weights in a LIF neural network and learning rules","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.AP"],"primary_cat":"q-bio.NC","authors_text":"Beno\\^it Perthame (MAMBA, Delphine Salort (LCQB), Gilles Wainrib (DI-ENS), LJLL)","submitted_at":"2017-06-19T06:11:17Z","abstract_excerpt":"Leaky integrate-and-fire (LIF) models are mean-field limits, with a large number of neurons, used to describe neural networks. We consider inhomogeneous networks structured by a connec-tivity parameter (strengths of the synaptic weights) with the effect of processing the input current with different intensities. We first study the properties of the network activity depending on the distribution of synaptic weights and in particular its discrimination capacity. Then, we consider simple learning rules and determine the synaptic weight distribution it generates. We outline the role of noise as a "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.05796","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":"2026-05-18T00:42:08Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1yUPnevd73xclHyHcAxTlVgIi8Trv0dTSV1bCjpKT/iNrWPXhm42wA1CSMgJMu1jP5KiIDTyXnHRCH6ce6VvAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-02T11:21:11.917453Z"},"content_sha256":"1c4d0f3b9777c04378cc04796bbcf7729d9591a800a89c129fe237dbb1516b2a","schema_version":"1.0","event_id":"sha256:1c4d0f3b9777c04378cc04796bbcf7729d9591a800a89c129fe237dbb1516b2a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RJVFDOQJHE6GHASRM3U47BI2U3/bundle.json","state_url":"https://pith.science/pith/RJVFDOQJHE6GHASRM3U47BI2U3/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RJVFDOQJHE6GHASRM3U47BI2U3/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":"2026-06-02T11:21:11Z","links":{"resolver":"https://pith.science/pith/RJVFDOQJHE6GHASRM3U47BI2U3","bundle":"https://pith.science/pith/RJVFDOQJHE6GHASRM3U47BI2U3/bundle.json","state":"https://pith.science/pith/RJVFDOQJHE6GHASRM3U47BI2U3/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RJVFDOQJHE6GHASRM3U47BI2U3/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2017:RJVFDOQJHE6GHASRM3U47BI2U3","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":"0aa55dee18891eda151d7b6af55ee9067094701e5c9681b2ae2dec2c7c7a7ac6","cross_cats_sorted":["math.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2017-06-19T06:11:17Z","title_canon_sha256":"9a1ab7a0901782cfc71e808c56d6afe8fa118022e3745224699619bcb28886f5"},"schema_version":"1.0","source":{"id":"1706.05796","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1706.05796","created_at":"2026-05-18T00:42:08Z"},{"alias_kind":"arxiv_version","alias_value":"1706.05796v1","created_at":"2026-05-18T00:42:08Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.05796","created_at":"2026-05-18T00:42:08Z"},{"alias_kind":"pith_short_12","alias_value":"RJVFDOQJHE6G","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_16","alias_value":"RJVFDOQJHE6GHASR","created_at":"2026-05-18T12:31:39Z"},{"alias_kind":"pith_short_8","alias_value":"RJVFDOQJ","created_at":"2026-05-18T12:31:39Z"}],"graph_snapshots":[{"event_id":"sha256:1c4d0f3b9777c04378cc04796bbcf7729d9591a800a89c129fe237dbb1516b2a","target":"graph","created_at":"2026-05-18T00:42:08Z","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":"Leaky integrate-and-fire (LIF) models are mean-field limits, with a large number of neurons, used to describe neural networks. We consider inhomogeneous networks structured by a connec-tivity parameter (strengths of the synaptic weights) with the effect of processing the input current with different intensities. We first study the properties of the network activity depending on the distribution of synaptic weights and in particular its discrimination capacity. Then, we consider simple learning rules and determine the synaptic weight distribution it generates. We outline the role of noise as a ","authors_text":"Beno\\^it Perthame (MAMBA, Delphine Salort (LCQB), Gilles Wainrib (DI-ENS), LJLL)","cross_cats":["math.AP"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2017-06-19T06:11:17Z","title":"Distributed synaptic weights in a LIF neural network and learning rules"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.05796","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":"sha256:89a6a1fd75b3347ec6fe3a74c7dc86a7ea4a576d2587edc900760e220d51198e","target":"record","created_at":"2026-05-18T00:42:08Z","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":"0aa55dee18891eda151d7b6af55ee9067094701e5c9681b2ae2dec2c7c7a7ac6","cross_cats_sorted":["math.AP"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2017-06-19T06:11:17Z","title_canon_sha256":"9a1ab7a0901782cfc71e808c56d6afe8fa118022e3745224699619bcb28886f5"},"schema_version":"1.0","source":{"id":"1706.05796","kind":"arxiv","version":1}},"canonical_sha256":"8a6a51ba09393c63825166e9cf851aa6f9054b3178662cf678843fd93053a3c8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8a6a51ba09393c63825166e9cf851aa6f9054b3178662cf678843fd93053a3c8","first_computed_at":"2026-05-18T00:42:08.868374Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:42:08.868374Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"442TPAifQb1TxJ5rItB8G5hhoqg7r8R6FN3snMSAPvM0/B5mAiV1k2bFJOaLbD+SHe2B7jXK+iXTOV6uA0JBBg==","signature_status":"signed_v1","signed_at":"2026-05-18T00:42:08.868820Z","signed_message":"canonical_sha256_bytes"},"source_id":"1706.05796","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:89a6a1fd75b3347ec6fe3a74c7dc86a7ea4a576d2587edc900760e220d51198e","sha256:1c4d0f3b9777c04378cc04796bbcf7729d9591a800a89c129fe237dbb1516b2a"],"state_sha256":"e9624564752d8902393cf8ef7fe8e6d5f0a0715d60799d8e0344e11ef4735984"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"E96ACaQFoeJ89fsYEoz/n140Co1g16RBh2F5Ps34Pcl+ohFbVaDE6WXQpSU0Pru8u3pYhf+L7xeSwZVHnZPpAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-02T11:21:11.919392Z","bundle_sha256":"468e9d15751e23b179a6f8f0af01130acc59952b61f6506fbc71a5d97fec6040"}}