{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:7RHQJPHA2JQ6JLHK433TOK5LZW","short_pith_number":"pith:7RHQJPHA","schema_version":"1.0","canonical_sha256":"fc4f04bce0d261e4aceae6f7372babcda2bbd14b92d22350349863e5f4910d1c","source":{"kind":"arxiv","id":"1612.00644","version":1},"attestation_state":"computed","paper":{"title":"Bayesian Population Receptive Field Modelling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.NC","authors_text":"Chris Ian Baker, Dietrich Samuel Schwarzkopf, Edward Harry Silson, Peter Zeidman, Will Penny","submitted_at":"2016-12-02T11:48:17Z","abstract_excerpt":"We introduce a probabilistic (Bayesian) framework and associated software toolbox for mapping population receptive fields (pRFs) based on fMRI data. This generic approach is intended to work with stimuli of any dimension and is demonstrated and validated in the context of 2D retinotopic mapping. The framework enables the experimenter to specify generative (encoding) models of fMRI timeseries, in which experimental manipulations enter a pRF model of neural activity, which in turns drives a nonlinear model of neurovascular coupling and Blood Oxygenation Level Dependent (BOLD) response. The neuro"},"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":"1612.00644","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"q-bio.NC","submitted_at":"2016-12-02T11:48:17Z","cross_cats_sorted":[],"title_canon_sha256":"726f503a74a5754dd872cb0586f6f03ebe665ac9a41b14799c0f01b0a6ce306d","abstract_canon_sha256":"974c5131bb9b797d194e33b4ecd6f09d8c9e29703c5da4b58ea6a4f00418e96c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:15:42.947449Z","signature_b64":"D6NPkUcvqOY47SOKs8OmekwNktwqHlS8Yd+DapXrwruuSFGa570RsP3RtNH7H13MAJUUD+lQv52vXV+8paqXDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fc4f04bce0d261e4aceae6f7372babcda2bbd14b92d22350349863e5f4910d1c","last_reissued_at":"2026-05-18T00:15:42.946903Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:15:42.946903Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Bayesian Population Receptive Field Modelling","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"q-bio.NC","authors_text":"Chris Ian Baker, Dietrich Samuel Schwarzkopf, Edward Harry Silson, Peter Zeidman, Will Penny","submitted_at":"2016-12-02T11:48:17Z","abstract_excerpt":"We introduce a probabilistic (Bayesian) framework and associated software toolbox for mapping population receptive fields (pRFs) based on fMRI data. This generic approach is intended to work with stimuli of any dimension and is demonstrated and validated in the context of 2D retinotopic mapping. The framework enables the experimenter to specify generative (encoding) models of fMRI timeseries, in which experimental manipulations enter a pRF model of neural activity, which in turns drives a nonlinear model of neurovascular coupling and Blood Oxygenation Level Dependent (BOLD) response. The neuro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1612.00644","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":"1612.00644","created_at":"2026-05-18T00:15:42.946980+00:00"},{"alias_kind":"arxiv_version","alias_value":"1612.00644v1","created_at":"2026-05-18T00:15:42.946980+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1612.00644","created_at":"2026-05-18T00:15:42.946980+00:00"},{"alias_kind":"pith_short_12","alias_value":"7RHQJPHA2JQ6","created_at":"2026-05-18T12:30:04.600751+00:00"},{"alias_kind":"pith_short_16","alias_value":"7RHQJPHA2JQ6JLHK","created_at":"2026-05-18T12:30:04.600751+00:00"},{"alias_kind":"pith_short_8","alias_value":"7RHQJPHA","created_at":"2026-05-18T12:30:04.600751+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/7RHQJPHA2JQ6JLHK433TOK5LZW","json":"https://pith.science/pith/7RHQJPHA2JQ6JLHK433TOK5LZW.json","graph_json":"https://pith.science/api/pith-number/7RHQJPHA2JQ6JLHK433TOK5LZW/graph.json","events_json":"https://pith.science/api/pith-number/7RHQJPHA2JQ6JLHK433TOK5LZW/events.json","paper":"https://pith.science/paper/7RHQJPHA"},"agent_actions":{"view_html":"https://pith.science/pith/7RHQJPHA2JQ6JLHK433TOK5LZW","download_json":"https://pith.science/pith/7RHQJPHA2JQ6JLHK433TOK5LZW.json","view_paper":"https://pith.science/paper/7RHQJPHA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1612.00644&json=true","fetch_graph":"https://pith.science/api/pith-number/7RHQJPHA2JQ6JLHK433TOK5LZW/graph.json","fetch_events":"https://pith.science/api/pith-number/7RHQJPHA2JQ6JLHK433TOK5LZW/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/7RHQJPHA2JQ6JLHK433TOK5LZW/action/timestamp_anchor","attest_storage":"https://pith.science/pith/7RHQJPHA2JQ6JLHK433TOK5LZW/action/storage_attestation","attest_author":"https://pith.science/pith/7RHQJPHA2JQ6JLHK433TOK5LZW/action/author_attestation","sign_citation":"https://pith.science/pith/7RHQJPHA2JQ6JLHK433TOK5LZW/action/citation_signature","submit_replication":"https://pith.science/pith/7RHQJPHA2JQ6JLHK433TOK5LZW/action/replication_record"}},"created_at":"2026-05-18T00:15:42.946980+00:00","updated_at":"2026-05-18T00:15:42.946980+00:00"}