{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:FSJKALCWK2YEPAGG3LSPEUN7JS","short_pith_number":"pith:FSJKALCW","schema_version":"1.0","canonical_sha256":"2c92a02c5656b04780c6dae4f251bf4cb572488225d22202a708fe30da99a215","source":{"kind":"arxiv","id":"1904.10399","version":1},"attestation_state":"computed","paper":{"title":"Spike-Based Winner-Take-All Computation: Fundamental Limits and Order-Optimal Circuits","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"q-bio.NC","authors_text":"Chia-Jung Chang, Lili Su, Nancy Lynch","submitted_at":"2019-04-21T02:45:09Z","abstract_excerpt":"Winner-Take-All (WTA) refers to the neural operation that selects a (typically small) group of neurons from a large neuron pool. It is conjectured to underlie many of the brain's fundamental computational abilities. However, not much is known about the robustness of a spike-based WTA network to the inherent randomness of the input spike trains. In this work, we consider a spike-based $k$--WTA model wherein $n$ randomly generated input spike trains compete with each other based on their underlying statistics, and $k$ winners are supposed to be selected. We slot the time evenly with each time sl"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1904.10399","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2019-04-21T02:45:09Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"75e22c93fd8eedad67b50a75dc7ddd3508e3597ce285394c07b118587453ed5f","abstract_canon_sha256":"0311419613bc0c54d5df6b40fe56d1db8b3fd6d4f739b1105d36ff1b3264e185"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:47:54.259899Z","signature_b64":"bdSB21KqVDmYXS6YcorfaharQE3XFA4d/GkmSc78fOYyMjACMnd4bNBTPCrB8GIbBp/tayRbWeu4Qs3d4cQ2CQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2c92a02c5656b04780c6dae4f251bf4cb572488225d22202a708fe30da99a215","last_reissued_at":"2026-05-17T23:47:54.259370Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:47:54.259370Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Spike-Based Winner-Take-All Computation: Fundamental Limits and Order-Optimal Circuits","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"q-bio.NC","authors_text":"Chia-Jung Chang, Lili Su, Nancy Lynch","submitted_at":"2019-04-21T02:45:09Z","abstract_excerpt":"Winner-Take-All (WTA) refers to the neural operation that selects a (typically small) group of neurons from a large neuron pool. It is conjectured to underlie many of the brain's fundamental computational abilities. However, not much is known about the robustness of a spike-based WTA network to the inherent randomness of the input spike trains. In this work, we consider a spike-based $k$--WTA model wherein $n$ randomly generated input spike trains compete with each other based on their underlying statistics, and $k$ winners are supposed to be selected. We slot the time evenly with each time sl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1904.10399","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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1904.10399","created_at":"2026-05-17T23:47:54.259449+00:00"},{"alias_kind":"arxiv_version","alias_value":"1904.10399v1","created_at":"2026-05-17T23:47:54.259449+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1904.10399","created_at":"2026-05-17T23:47:54.259449+00:00"},{"alias_kind":"pith_short_12","alias_value":"FSJKALCWK2YE","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_16","alias_value":"FSJKALCWK2YEPAGG","created_at":"2026-05-18T12:33:15.570797+00:00"},{"alias_kind":"pith_short_8","alias_value":"FSJKALCW","created_at":"2026-05-18T12:33:15.570797+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/FSJKALCWK2YEPAGG3LSPEUN7JS","json":"https://pith.science/pith/FSJKALCWK2YEPAGG3LSPEUN7JS.json","graph_json":"https://pith.science/api/pith-number/FSJKALCWK2YEPAGG3LSPEUN7JS/graph.json","events_json":"https://pith.science/api/pith-number/FSJKALCWK2YEPAGG3LSPEUN7JS/events.json","paper":"https://pith.science/paper/FSJKALCW"},"agent_actions":{"view_html":"https://pith.science/pith/FSJKALCWK2YEPAGG3LSPEUN7JS","download_json":"https://pith.science/pith/FSJKALCWK2YEPAGG3LSPEUN7JS.json","view_paper":"https://pith.science/paper/FSJKALCW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1904.10399&json=true","fetch_graph":"https://pith.science/api/pith-number/FSJKALCWK2YEPAGG3LSPEUN7JS/graph.json","fetch_events":"https://pith.science/api/pith-number/FSJKALCWK2YEPAGG3LSPEUN7JS/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FSJKALCWK2YEPAGG3LSPEUN7JS/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FSJKALCWK2YEPAGG3LSPEUN7JS/action/storage_attestation","attest_author":"https://pith.science/pith/FSJKALCWK2YEPAGG3LSPEUN7JS/action/author_attestation","sign_citation":"https://pith.science/pith/FSJKALCWK2YEPAGG3LSPEUN7JS/action/citation_signature","submit_replication":"https://pith.science/pith/FSJKALCWK2YEPAGG3LSPEUN7JS/action/replication_record"}},"created_at":"2026-05-17T23:47:54.259449+00:00","updated_at":"2026-05-17T23:47:54.259449+00:00"}