{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:7AIWZMAK55J7JB7I6DFXMHIYBV","short_pith_number":"pith:7AIWZMAK","schema_version":"1.0","canonical_sha256":"f8116cb00aef53f487e8f0cb761d180d48af592ce7d31a6336bf9f125c9818d8","source":{"kind":"arxiv","id":"1508.07484","version":1},"attestation_state":"computed","paper":{"title":"Numerical Solution of the Neural Field Equation in the Two-dimensional Case","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.NA","authors_text":"Evelyn Buckwar, Pedro M. Lima","submitted_at":"2015-08-29T17:41:14Z","abstract_excerpt":"We are concerned with the numerical solution of a class integro-differential equations, known as Neural Field Equations, which describe the large-scale dynamics of spatially structured networks of neurons. These equations have many applications in Neuroscience and Robotics. We describe a numerical method for the approximation of solutions in the two-dimensional case, including a space-dependent delay in the integrand function. Compared with known algorithms for this type of equation we propose a scheme with higher accuracy in the time discretisation. Since computational efficiency is a key iss"},"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":"1508.07484","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"math.NA","submitted_at":"2015-08-29T17:41:14Z","cross_cats_sorted":[],"title_canon_sha256":"f9e4b9e6231f97251ff828305432de65521d1c434ce4f1d6d1e6520050875873","abstract_canon_sha256":"5da4a4533a035c013fd6e6fa849a4d94a9ddc5e464cefdde96550569c98054eb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:34:32.171345Z","signature_b64":"j3xCaSWNjQpEkELO+As6EERSrMa9OT/s2AgxLOgM6g7vl+Qx6834YVkeB51KSYiX1SD8S/TN9WBHkG14meXcAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f8116cb00aef53f487e8f0cb761d180d48af592ce7d31a6336bf9f125c9818d8","last_reissued_at":"2026-05-18T01:34:32.170684Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:34:32.170684Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Numerical Solution of the Neural Field Equation in the Two-dimensional Case","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.NA","authors_text":"Evelyn Buckwar, Pedro M. Lima","submitted_at":"2015-08-29T17:41:14Z","abstract_excerpt":"We are concerned with the numerical solution of a class integro-differential equations, known as Neural Field Equations, which describe the large-scale dynamics of spatially structured networks of neurons. These equations have many applications in Neuroscience and Robotics. We describe a numerical method for the approximation of solutions in the two-dimensional case, including a space-dependent delay in the integrand function. Compared with known algorithms for this type of equation we propose a scheme with higher accuracy in the time discretisation. Since computational efficiency is a key iss"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1508.07484","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":"1508.07484","created_at":"2026-05-18T01:34:32.170815+00:00"},{"alias_kind":"arxiv_version","alias_value":"1508.07484v1","created_at":"2026-05-18T01:34:32.170815+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1508.07484","created_at":"2026-05-18T01:34:32.170815+00:00"},{"alias_kind":"pith_short_12","alias_value":"7AIWZMAK55J7","created_at":"2026-05-18T12:29:07.941421+00:00"},{"alias_kind":"pith_short_16","alias_value":"7AIWZMAK55J7JB7I","created_at":"2026-05-18T12:29:07.941421+00:00"},{"alias_kind":"pith_short_8","alias_value":"7AIWZMAK","created_at":"2026-05-18T12:29:07.941421+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/7AIWZMAK55J7JB7I6DFXMHIYBV","json":"https://pith.science/pith/7AIWZMAK55J7JB7I6DFXMHIYBV.json","graph_json":"https://pith.science/api/pith-number/7AIWZMAK55J7JB7I6DFXMHIYBV/graph.json","events_json":"https://pith.science/api/pith-number/7AIWZMAK55J7JB7I6DFXMHIYBV/events.json","paper":"https://pith.science/paper/7AIWZMAK"},"agent_actions":{"view_html":"https://pith.science/pith/7AIWZMAK55J7JB7I6DFXMHIYBV","download_json":"https://pith.science/pith/7AIWZMAK55J7JB7I6DFXMHIYBV.json","view_paper":"https://pith.science/paper/7AIWZMAK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1508.07484&json=true","fetch_graph":"https://pith.science/api/pith-number/7AIWZMAK55J7JB7I6DFXMHIYBV/graph.json","fetch_events":"https://pith.science/api/pith-number/7AIWZMAK55J7JB7I6DFXMHIYBV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7AIWZMAK55J7JB7I6DFXMHIYBV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7AIWZMAK55J7JB7I6DFXMHIYBV/action/storage_attestation","attest_author":"https://pith.science/pith/7AIWZMAK55J7JB7I6DFXMHIYBV/action/author_attestation","sign_citation":"https://pith.science/pith/7AIWZMAK55J7JB7I6DFXMHIYBV/action/citation_signature","submit_replication":"https://pith.science/pith/7AIWZMAK55J7JB7I6DFXMHIYBV/action/replication_record"}},"created_at":"2026-05-18T01:34:32.170815+00:00","updated_at":"2026-05-18T01:34:32.170815+00:00"}