{"as_of":"2026-07-25T05:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:6759d08d2aa6e2d64a0aad2b8e4764c59618bc966abb5190075253bc6f710bf6","coverage":[{"denominator":112,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-08T04:48:04.799361Z","state":"measured"},{"denominator":100,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":100,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-07-24T06:31:00.690269+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2604.23903/citation-record","integrity":"/paper/2604.23903/integrity","json":"/paper/2604.23903/citation-record.json","paper":"/paper/2604.23903"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A uni- ﬁed, scalable framework for neural population decoding","venue":null,"work_id":"ea99d4de-c440-4c3c-b4d8-aaa479aa498e","year":2023},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:d7e97abb0a20d7c2e94fd63efeb5938419995563e57ebc101024fe2fca4fda22","observation_id":"24482367-7331-4743-893b-71af04c75c8a","resolution":{"observed_at":"2026-05-26T20:38:00.883773Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Multi- session, multi-task neural decoding from distinct cell-types and brain regions","venue":null,"work_id":"25d09d5a-ac71-41e8-88d1-f118612e23b1","year":2024},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:a8b2f4589aea82a45fac7b951bc1e183a0066a92f360540a481dff5235ef48b4","observation_id":"fe14dbe7-2914-4fe1-80f8-1a847cc0e434","resolution":{"observed_at":"2026-05-26T20:38:01.303289Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Do deep nets really need to be deep? Advances in Neural Information Processing Systems, 27","venue":null,"work_id":"30dd1851-8d7a-46ba-96ae-5ff3ea13af48","year":2014},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:db74d6eaa74f4c9ea368b3de616a7d942cd9682a031872128cc63b6c508c9b7c","observation_id":"cf2f2709-5600-4ad1-a489-baf25af570c9","resolution":{"observed_at":"2026-05-26T20:38:01.290439Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Prediction of neural activ- ity in connectome-constrained recurrent networks.Nature Neuro- science, 28(12):2561–2574, December 2025","venue":null,"work_id":"f36d0492-cb06-4bc3-a64a-ab59d5a2291d","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:be39404f61c6b32b7e9a67968ceb5cc26d025e5ec7799b23b46d9fc950a896d9","observation_id":"4032b1e1-0c6f-4baa-b153-bde49b413ccb","resolution":{"observed_at":"2026-05-26T20:38:01.300322Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"On the oppor- tunities and risks of foundation models.arXiv [cs.LG], August 2021","venue":null,"work_id":"656d4cc0-f948-4c4e-915e-02e99a269040","year":2021},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:e868ab6b4dbff649603c8a623031a24114cf4afd372eb94781e4b732e4a32fc1","observation_id":"0dd7a8fc-bad2-4979-8847-97a3ec2c9947","resolution":{"observed_at":"2026-05-26T20:38:01.293896Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"The tradeoﬀs of large scale learn- ing","venue":null,"work_id":"e0cde545-4a94-4364-a1ce-bbe3ab33fb30","year":2007},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:0fc55f535ae3767845bfb41b30f9fdaa65a51f68bc4f8a9f7ec8b468f24d452a","observation_id":"731b93a6-261b-463a-b64f-89373c6a2dc3","resolution":{"observed_at":"2026-05-26T20:38:01.312983Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dynamic models of large-scale brain activity","venue":null,"work_id":"f0626ae6-4da5-402f-bbf2-8eb794ed94fe","year":2017},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:9906b1cff6814d8733ed689f1c31f68d10099a5e9b179139047ddb2b8927c402","observation_id":"96b2c460-0bb4-40a4-9e20-06df7e4dd690","resolution":{"observed_at":"2026-05-26T20:38:01.222858Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A quantitative model of conserved macroscopic dynamics predicts future motor commands","venue":null,"work_id":"2490f1a2-d898-4d35-afeb-1d748c3bc4ec","year":2019},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:87ffe1c01d086dfc8cd846b8eeb859955795988505f55262dfdecab28813b577","observation_id":"cfe579d3-58cf-4bcd-b60f-d0e4ec3b316c","resolution":{"observed_at":"2026-05-26T20:38:01.225604Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"RT-1: Robotics transformer for real-world control at scale.arXiv [cs.RO], December 2022","venue":null,"work_id":"4516af7c-8d1e-480a-8a28-067ff2655178","year":2022},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:895f677b048f04ccd671ab533dc6d669dd9df8bd5cb0d7dcf6b2c5b11796714f","observation_id":"8e4fcdad-a59b-46c1-95bc-d5be1baca130","resolution":{"observed_at":"2026-05-26T20:38:01.255394Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Statistics of neu- ronal identiﬁcation with open- and closed-loop measures of intrinsic excitability.Frontiers in Neural Circuits, 6:19, April 2012","venue":null,"work_id":"666b870c-214a-4baa-8af7-8cfb21614f39","year":2012},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:dc61f2858bc3851d3a6243d43186a50beec2f9067e62d01bfe479c9abba97aea","observation_id":"66015b14-516f-4b9d-bfb9-5e362b066481","resolution":{"observed_at":"2026-05-26T20:38:01.283052Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Discovering governing equations from data by sparse identiﬁcation of nonlinear dynamical systems.Proceedings of the National Academy of Sciences, 113(15):3932–3937","venue":null,"work_id":"28a48f86-2d0b-48dc-a05c-38abf09241dd","year":2016},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:0fe0d5cee1e000342e4272922af5b937790440f638a33ce778a14fc03a1dbe9d","observation_id":"ec0db3d3-fb96-4b5f-8730-fc283fd7ef2e","resolution":{"observed_at":"2026-05-26T20:38:00.905823Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Analyzing populations of neural networks via dynam- ical model embedding.arXiv [cs.LG], February 2023","venue":null,"work_id":"40cd5db6-7b0f-49e1-abc9-466b25bff68a","year":2023},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:bb0677e7dbe24f039300426ce1056e564c12f4266d1f84b75447a67c888be61e","observation_id":"4dbeae77-1791-465c-bbb0-9695265839af","resolution":{"observed_at":"2026-05-26T20:38:00.971661Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Action suppres- sion reveals opponent parallel control via striatal circuits.Nature, 607(7919):521–526, July 2022","venue":null,"work_id":"7766c107-910c-4ac8-9670-a9e5413cb425","year":2022},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:3e0e2f6494f60327fbd294d9362549714cbe68a687a7270319d1f07960569ae0","observation_id":"c1f21345-0549-466d-a74c-7f3b9bbdf529","resolution":{"observed_at":"2026-05-26T20:38:01.347130Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Multilevel visuomotor con- trol of locomotion in Drosophila.Current Opinion in Neurobiology, 82: 102774, October 2023","venue":null,"work_id":"430b907c-39c7-4524-9b9f-98f8ca6cb79c","year":2023},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:968023bb4f0a0b0526bb4996f38da3a996aeb3c14978bb5f6df428665a6e97cb","observation_id":"81038d58-66b0-4966-b52a-167864d49045","resolution":{"observed_at":"2026-05-26T20:38:01.219652Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"ParaRNN: Unlocking parallel training of nonlinear RNNs for large language models","venue":null,"work_id":"52432223-50dc-4995-80e2-02138f32cc52","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:803d3388b29cf50ae672ecc4c25980d76044c0cf109b7262d66239dc3feb6100","observation_id":"d00cefc4-2792-4296-91b9-a0b482a78a06","resolution":{"observed_at":"2026-05-26T20:38:01.239396Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Brain-like functional specialization emerges spontaneously in deep neural networks.Science Advances, 8(11):eabl8913, March 2022","venue":null,"work_id":"f29d0aa8-afbd-4172-bdd8-e9db18f225ee","year":2022},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:8de298e831f66f3bfeafefb4aedd2f2e5ca9da7aa36f086e29bffd352bfb2304","observation_id":"5ea1f4dc-85a0-42c3-85b3-90c540046887","resolution":{"observed_at":"2026-05-26T20:38:01.276621Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Range, not inde- pendence, drives modularity in biologically inspired representations","venue":null,"work_id":"d4a46aeb-4a8d-47a7-a63b-a4f6c1119ba5","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:1167ecb1193ab31bcbb177938f8514461fced185d857c07a4becb0caec18fe33","observation_id":"5dcab50e-b1b8-4b0d-875d-8d2ee224df36","resolution":{"observed_at":"2026-05-26T20:38:01.323001Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"eXponential FAmily dynamical systems (XFADS): Large-scale nonlinear gaussian state-space modeling","venue":null,"work_id":"fbc57b90-de7d-4f70-a602-6effcb909f98","year":2024},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:cbc4bc2a3f586cd9b9e39b30207fd17a989e2902d218cf90a4d76e3fa3fb86c7","observation_id":"1c9e1365-f24d-4f07-95ba-f88a36e7519f","resolution":{"observed_at":"2026-05-26T20:38:01.343785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Computation through cortical dynamics.Neuron, 98(5):873–875, June 2018","venue":null,"work_id":"f0ab8057-2ab5-436b-a07b-ec3f567ce7be","year":2018},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:da0719a0254291d4fde3d2f47ca3f293e0f0abd0594ca9dd9ccbe41f7f4071b7","observation_id":"853a7e12-cd0f-4dfa-b971-016188d42762","resolution":{"observed_at":"2026-05-26T20:38:00.988973Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"the bitter lesson","venue":null,"work_id":"72a4b206-01e8-4e51-b2bc-0a7369515b41","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:9a8280d5f3ea298cfb88f365d34025339afce791ea9388753bb0c0866b340e5d","observation_id":"5c889c42-9887-4b80-94d3-f8c3a226bdc6","resolution":{"observed_at":"2026-05-26T20:38:01.198521Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ecker, Philipp Berens, R","venue":null,"work_id":"63ad4949-8cba-437a-a404-bb4970d05791","year":2014},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:ae964e42e4b449aec4146d531c9c51db68962f8fce5d935befe8776d8b5c0dab","observation_id":"1a7a96f0-3ba8-4a7f-aa3e-e24fa8833fb1","resolution":{"observed_at":"2026-05-26T20:38:01.329749Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A prac- tical survey on faster and lighter transformers.ACM computing sur- veys, 55(14s):1–40, December 2023","venue":null,"work_id":"3535f195-d729-43c5-b4a7-e344e633394e","year":2023},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:e3f4bc07754a42ba90233c60e9709ef9a0533686810cb20034efa866b8cb67a7","observation_id":"bb3e4c1f-bdf2-4285-a6d6-62cdfb136fc1","resolution":{"observed_at":"2026-05-26T20:38:01.187065Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dynamic representations and gen- erative models of brain function.Brain research bulletin, 54(3):275– 285","venue":null,"work_id":"ccf1133c-fbc3-4bde-89dd-16a5b5bce175","year":2001},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:a8e465d1581032f0faf61a705edc25d09cfffea3cba65111b93836706cd9c536","observation_id":"770b102d-0f0c-4acb-a4e7-c1f28e0798dd","resolution":{"observed_at":"2026-05-26T20:38:01.183972Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Walk- ing strides direct rapid and ﬂexible recruitment of visual circuits for course control in drosophila.Neuron, 110(13):2124–2138, July 2022","venue":null,"work_id":"cd9e74db-934d-4b96-85d1-42f7327458d8","year":2022},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:69be9ec9398c19124bddea0356b4f5b8985fdbf7de9ccc43e4361176828b769a","observation_id":"9c46cef4-d5b8-43c9-8ee4-a6ab57daf6fd","resolution":{"observed_at":"2026-05-26T20:38:00.978557Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Long-term stability of cortical population dynamics underlying consistent behavior.Nature neuroscience, Jan- uary 2020","venue":null,"work_id":"6421c03d-d54f-48df-9953-e92a7498d1a9","year":2020},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:5f2071e530496dc88d46f7d8eea8fd6a54b95781200ceddbe802264a71d86db5","observation_id":"8c79b2ce-18a1-4c99-8416-e249b85496d5","resolution":{"observed_at":"2026-05-26T20:38:00.982785Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Nonlinear convergence analysis for the parareal algorithm","venue":null,"work_id":"84a2725b-be27-45f6-8161-e06bae54366e","year":2008},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:f93e0288102383d5254bcfacc50436f7d214ef17db1ff7e0aedc667803629cf7","observation_id":"f3aa17bb-fb99-4339-8cc7-6c9ac980d14d","resolution":{"observed_at":"2026-05-26T20:38:01.207923Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Inferring system and optimal control parameters of closed-loop systems from partial observations.arXiv [math.OC], pages 8006–8013, February 2025","venue":null,"work_id":"f6942003-f61b-4e1e-b470-f57675096cec","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:27d577c77ae1d4355f4b25f108d0e8dfd420fb74a22b3cb96f391bd799527726","observation_id":"0d857319-15c0-4a2c-bb2c-9432072614d1","resolution":{"observed_at":"2026-05-26T20:38:00.995213Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Moving beyond generalization to accurate interpretation of ﬂexible models.Nature machine intelli- gence, 2(11):674–683, October 2020","venue":null,"work_id":"1eb2d514-37b1-40ef-9d3b-a0b12e5927d2","year":2020},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:847addd0396eaeb8f2b4c02df6b921d7f0a522bb53e6bca023ccdb507ea107c1","observation_id":"d9c8eadd-f8a2-4800-bdac-690b5a6c9ceb","resolution":{"observed_at":"2026-05-26T20:38:01.027059Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A high- performance neural prosthesis enabled by control algorithm design","venue":null,"work_id":"aac24944-fe99-4ee2-9730-5779668acb43","year":2012},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:c55e6ddbc6688dbed49f98803d25aaed5dd82c354210393477cd32cff9398464","observation_id":"26044d88-df4d-4055-bce8-1a7ed6b99512","resolution":{"observed_at":"2026-05-26T20:38:01.058762Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Predictability enables parallelization of nonlinear state space models","venue":null,"work_id":"5a59624a-ad7d-40d7-9df1-b6c3aff45b19","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:56ded28790cd7f7945d363a75d7152970c5ab5bad0666970f3ab25b7a8d8e8f3","observation_id":"6af6e0e2-f2c8-4ede-a5bd-8565bc9f1ad1","resolution":{"observed_at":"2026-05-26T20:38:01.001428Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"T owards scalable and stable parallelization of nonlinear RNNs","venue":null,"work_id":"4e619589-2029-4503-9002-b6d18940ef51","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:8a9eb689507ebede5b8b967382ea463ddc26d8bc90bedf477540f2cc9b0d83fb","observation_id":"cccf2207-60ae-429b-99d4-f5594b439c1c","resolution":{"observed_at":"2026-05-26T20:38:00.960594Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Reliable neuro- modulation from circuits with variable underlying structure.Proceed- ings of the National Academy of Sciences, 106(28):11742–11746, July 2009","venue":null,"work_id":"53efe8d6-a408-4e7a-a194-5500eecce9e9","year":2009},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:a4f76e61037757626b4fd0c4c599135228d56c82784075d9236d0a264d38c85b","observation_id":"348d9f13-64b6-457f-806d-e45781aea30c","resolution":{"observed_at":"2026-05-26T20:38:01.248742Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Mamba: Linear-time sequence modeling with selective state spaces.arXiv [cs.LG], December 2023","venue":null,"work_id":"7030cd52-51d2-4590-9c9b-deb5b808fe3b","year":2023},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:10d3745bca7f18dacbdc48977b55e32ea781bf582835610c45d367f9be884275","observation_id":"ed204810-8b99-4497-929e-64687ad349ca","resolution":{"observed_at":"2026-05-26T20:38:01.042606Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Multiple mechanisms switch an electrically coupled, synaptically inhibited neuron between competing rhythmic oscillators.Neuron, 77(5):845– 858, March 2013","venue":null,"work_id":"b3326ae4-2a1e-4b92-836b-5df5c193b597","year":2013},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:b5ed26a358ce9d8aadc950cfcac73105c8ec374783b3df6fce365c829edeae70","observation_id":"4349be9a-fd28-4fa9-8bd3-e3cb6d76a7fa","resolution":{"observed_at":"2026-05-26T20:38:01.048408Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Time, con- trol, and the nervous system.Annual Review of Neuroscience, 48(1): 465–489, July 2025","venue":null,"work_id":"081af3e9-d8a2-492f-a37c-27fdc214849a","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:de5dde60aa7963e3c557ac67803f2c7b3f9fb426398b13947ce7a62dd7af77ed","observation_id":"ca3a02b4-bd39-4caf-968b-02fc9fcf5e17","resolution":{"observed_at":"2026-05-26T20:38:01.235678Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"The time is ripe to reverse engineer an entire nervous system: simulating behavior from neural interactions.arXiv [q-bio.NC], August 2023","venue":null,"work_id":"38dc2cad-c3f4-4a7c-80f3-0dfd7b131c80","year":2023},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:a4aa7f20fb6894526e82de050ce69d9dd68f6448e3bffb17a4d406e91e3e34c0","observation_id":"556e1365-dbcf-44da-acd5-e44614f76afc","resolution":{"observed_at":"2026-05-26T20:38:00.935673Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Haykin and J","venue":null,"work_id":"bf78daa3-482b-4665-a6d8-51565b72dddb","year":1998},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:c9e71caac8e10e2ac583bce932cc3bcbfe720e2cac0383a114a69b02aa91ad0e","observation_id":"d92168f2-bd37-4b41-a48b-1a7697521401","resolution":{"observed_at":"2026-05-26T20:38:00.941116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Neural mechanisms of speed- accuracy tradeoﬀ.Neuron, 76(3):616–628, November 2012","venue":null,"work_id":"6997c47f-0ab0-4847-8c18-e3b5a429a870","year":2012},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:98cb17dc7176602a239d3dff126d0f61b058725eb4d45dabae957b5bf497e268","observation_id":"2e1e8825-e43b-415f-b99d-8e33be69a511","resolution":{"observed_at":"2026-05-26T20:38:01.340460Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Distilling the knowl- edge in a neural network.arXiv [stat.ML], March 2015","venue":null,"work_id":"7784e3b1-09c4-48aa-b586-ce54572c7c44","year":2015},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:165c7d216a80f378e5eaf0fd7cf63091b1b0c7f5c1afcad55935e4de8412b065","observation_id":"e21e91f3-f803-44e9-9823-c1f22f709df8","resolution":{"observed_at":"2026-05-26T20:38:01.080139Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Hochberg, Mijail D","venue":null,"work_id":"5ba227cf-2774-4b33-9fa1-11892dc923a9","year":2006},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:58d802fd7649f13586b484269f144f6c9b60aff7614d69a89a252efd6780f084","observation_id":"f3e9b4dd-7a29-414d-9bf4-52ad2e049e9c","resolution":{"observed_at":"2026-05-26T20:38:01.090838Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Myopic control of neural dy- namics.PLOS Computational Biology, March 2019","venue":null,"work_id":"b3408a26-1697-4576-91fc-a3fb249a4bfa","year":2019},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:8296b406a60045e482313eecccd5201f47d0acb8873c067782f4da187c7b3b57","observation_id":"8301aa7f-c4c7-429c-8d0e-883d8a725808","resolution":{"observed_at":"2026-05-26T20:38:01.163811Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dynamical movement primitives: learning attractor models for motor behaviors.Neural computation, 25(2):328–373, February 2013","venue":null,"work_id":"f49e8768-29cc-4391-9468-87f528840d06","year":2013},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:31f0941435d14aded25d1a475fd436323b70fc8043e6f13ecbc2e029dc0d75dd","observation_id":"2918030a-be0b-458c-89dc-b7056967f773","resolution":{"observed_at":"2026-05-26T20:38:00.931406Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Re- producibility of in vivo electrophysiological measurements in mice","venue":null,"work_id":"578d94e1-1a38-4f7d-ae24-63cf4162469d","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:60dc584470d87a2c6dcf97c9cd8c9cb976c9b3c7f338f8562a633fa67757618f","observation_id":"63c2fab1-cea1-4337-8125-cc5e1523220f","resolution":{"observed_at":"2026-05-26T20:38:00.967900Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dis- entangling the roles of distinct cell classes with cell-type dynamical systems","venue":null,"work_id":"ba793b61-63c1-4c89-91dc-4ae963a978a1","year":2024},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:a7b6c44420f9d13da3d8369f6256a21d3945cf6407397a57e409be09daefa8ca","observation_id":"b476625f-5bb1-463a-bcd4-5650e5556372","resolution":{"observed_at":"2026-05-26T20:38:01.286383Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A generic non-invasive neuromotor interface for human-computer interaction.Nature, pages 1–10, July 2025","venue":null,"work_id":"4bade55e-9a8a-4e69-8621-de1f7b09b30b","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:997f85504a376db7b1656eb38257536de2e55fd1e239b7a50ceb80cf9310515b","observation_id":"c2f51c1d-7f3e-44e9-83ac-cc023b037df5","resolution":{"observed_at":"2026-05-26T20:38:01.006126Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Kao, Paul Nuyujukian, Stephen I","venue":null,"work_id":"217be38c-6092-49b6-bb15-865114f5ade0","year":2015},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:35931221cb01965c86d55186d5a4d5023b435485081c25b538070c75f1d813f3","observation_id":"ecc2a1ce-a00c-4b00-bd8e-bba206a07127","resolution":{"observed_at":"2026-05-26T20:38:01.015759Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"The explanatory force of dynamical and mathematical models in neuroscience: A mechanistic perspective.Philosophy of Science, 78(4):601–627","venue":null,"work_id":"d01285bc-f412-44f7-a595-17cc71061e5b","year":2011},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:01f9745b85bb3fae1af3d87df0aea2a13b256ba825898136e1465a416d873287","observation_id":"1552dfa3-9f86-4b27-9f6d-78bf88c1b55a","resolution":{"observed_at":"2026-05-26T20:38:01.259058Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Few-shot al- gorithms for COnsistent neural decoding (FALCON) benchmark","venue":null,"work_id":"d49694b4-e4b8-45f4-af89-64e2f44e6efd","year":2024},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:58576be47048b657632bbb8bccfd3239948990e19c1969e2ade45b9603f5c165","observation_id":"64cb7f67-eae1-4d8d-9c3d-247b417f60d4","resolution":{"observed_at":"2026-05-26T20:38:01.262493Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Spontaneous evolution of modularity and network motifs.Proceedings of the National Academy of Sciences, 102(39):13773–13778, September 2005","venue":null,"work_id":"26020c70-4463-407c-be5c-1c282a80132c","year":2005},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:cca600cd3990c7ecaeaebf47850ccdee18832b8a9073c0d4b25097003f0ab5f9","observation_id":"4e29a145-bba7-4c7e-8fc9-72573c246c2d","resolution":{"observed_at":"2026-05-26T20:38:01.319541Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Dynamic causal modelling for EEG and MEG.Cognitive neurodynam- ics, 2(2):121–136, June 2008","venue":null,"work_id":"3e2973b4-5eae-43a8-89a0-deb555748105","year":2008},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:b23a678b9c002acd17f7d94bbb4a646dfd8a525ed6461096ca884540421170a6","observation_id":"859580fe-f924-4284-9bc0-1ce7dce1df1b","resolution":{"observed_at":"2026-05-26T20:38:01.100420Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Cluster- ing units in neural networks: upstream vs downstream information","venue":null,"work_id":"05535464-a7a6-47fe-a39c-17c48a9d14bc","year":2022},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:d98cf119058794fae753b7fb8f61e12c89470644a825adc2ffa5e05bec39aebd","observation_id":"335f8fb3-a287-4757-a07e-b9e4830a6aac","resolution":{"observed_at":"2026-05-26T20:38:01.297156Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Connectome-constrained networks predict neural activity across the ﬂy visual system.Nature, 634:1132–1140","venue":null,"work_id":"4c621a1c-d7b8-4c34-ae03-1622c2580e24","year":2024},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:5c3972e54a26530930658e8f3b8b98d2eb0012e6a7ed9a1a4dc629aed2b8e36b","observation_id":"b5e0502c-9fec-448b-b971-b2aa909450e5","resolution":{"observed_at":"2026-05-26T20:38:01.337036Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"4fc199a3-53fd-4c91-bc01-ca4deac06c8f","year":2017},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:ce300455d98944fb45c51b63c8be92cd85a9c782e283c0f6b3e8488e567d3bdd","observation_id":"3f141c5a-1bff-4fd5-847e-e2e7f0b36888","resolution":{"observed_at":"2026-05-26T20:38:01.242636Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Multitasking recurrent networks utilize compositional strategies for control of movement.bioRxiv, page 2025.09.10.675375, September 2025","venue":null,"work_id":"671bdc00-af44-41bd-805c-762b48f231fa","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:662a90422e7074a15b1e20a7e7c3f5ba9a925a12e78f8782c7f366fe2c86ba22","observation_id":"1c38d94d-dff4-441e-8505-d66aa83ae6a9","resolution":{"observed_at":"2026-05-26T20:38:01.265948Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Oﬄine reinforcement learning: T utorial, review, and perspectives on open problems.arXiv [cs.LG], May 2020","venue":null,"work_id":"83ca0421-e59d-4fbf-862a-4b25966be46a","year":2020},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:57ae1b87211aa06452c20f9dd851a2ee558c509c2adcf1a149f544abf9c6037c","observation_id":"956c477b-30b1-476b-80b5-53947413a3fe","resolution":{"observed_at":"2026-05-26T20:38:01.333524Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Hierarchical recurrent state space models reveal discrete and continuous dynamics of neural activity in C","venue":null,"work_id":"c908645a-df2e-4a5d-ad84-0d4c905e63e8","year":2019},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:0f4e74b935c5ab14ba4fd3872c16cd0037087acf2058a61ec2d0ff69f9c524c4","observation_id":"bc778f4b-a8c0-43c4-b173-35c6b412cbc6","resolution":{"observed_at":"2026-05-26T20:38:01.069563Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"What brain signals are suitable for feedback control of deep brain stimulation in parkinson’s disease? Annals of the New Y ork Academy of Sciences, 1265(1):9–24, August 2012","venue":null,"work_id":"4f511b82-6f75-4e51-b562-d9e2888383aa","year":2012},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:58ee70fc705d652c36708732b7299bf6189bffa72001f35d4711ee1c9ed62acc","observation_id":"7affd7c8-e2fd-4d4d-b60b-c628dd022146","resolution":{"observed_at":"2026-05-26T20:38:01.105099Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"ZAPBench: A benchmark for whole-brain activity prediction in ze- braﬁsh","venue":null,"work_id":"95e1ee3d-8d83-45c5-b56c-a1b613ca353f","year":2024},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:c54a295454506a469a919c992bd5f535269c46eb0f221891ecddd65390743efc","observation_id":"b14deff2-27e8-46e5-a91b-08cc7fa37547","resolution":{"observed_at":"2026-05-26T20:38:01.211016Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Shenoy, and William T","venue":null,"work_id":"6a70d636-3ff1-4e40-91bb-8c21d9d94f5c","year":2013},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:9f39e26cf6538f871d13371c8029fd7dda01a1f9db4ef18ded37d0723aeaab26","observation_id":"ea4f7ed8-fb21-4d5d-b81f-4d239b92ada8","resolution":{"observed_at":"2026-05-26T20:38:01.157410Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Joint modelling of brain and behaviour dynamics with artiﬁcial intelligence.Nature reviews","venue":null,"work_id":"33f579ee-b97d-4c74-ba58-ae69a32148ce","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:83c7e6b33a3436d073e36c666f3e74d68716b0be50b2c9a6abf0e521edefd542","observation_id":"3e956124-54c2-4fbf-9d30-091d2535511d","resolution":{"observed_at":"2026-05-26T20:38:01.153745Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep neuroethol- ogy of a virtual rodent.arXiv [q-bio.NC], November 2019","venue":null,"work_id":"8e87b25e-d659-4731-9381-f5b26afa1059","year":2019},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:4e2d1ba6320f547a6d2ef62db47ff465978c8e41e70570624f3d07193f5a1291","observation_id":"f3a644e3-7a0e-4161-88a7-3f84ae9d3939","resolution":{"observed_at":"2026-05-26T20:38:01.216939Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Connectome-constrained latent variable model of whole-brain neural activity","venue":null,"work_id":"027a241a-eef8-4aff-9a10-11880c77f60f","year":2022},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:32d0b298e3e911bfd66a6b9f250eba6dd8599cfa6a056cdb6fd5f91714d78c4f","observation_id":"d8b6f75c-57e7-4b6e-8490-6b0553d10617","resolution":{"observed_at":"2026-05-26T20:38:01.245654Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"59c9784f-7d50-47a6-8ab2-c472372b68b8","year":2020},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:c18e23fe27b31e4b19599ccb4519eb25053440a767a638bc2568ba492dfcf3d8","observation_id":"4bae136c-23e0-48af-82d2-8576fd4b36e3","resolution":{"observed_at":"2026-05-26T20:38:01.167389Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A rubric for human-like agents and NeuroAI.Philo- sophical Transactions of the Royal Society of London","venue":null,"work_id":"d3d8c39b-ff24-4625-baa7-b37d5d5281a0","year":2023},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:f39f23dfee9f946000454de9724eebd75d33b95ef6518197684732e2ab086e06","observation_id":"8f36df40-d106-4a74-9f19-ffaf19538bfa","resolution":{"observed_at":"2026-05-26T20:38:01.201527Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Neurodynamical comput- ing at the information boundaries of intelligent systems.Cognitive computation, 16(5):1–13","venue":null,"work_id":"3463091b-5cdb-4157-84d5-68d83d97c453","year":2024},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:832a848a371a0be98cc75cb5a0ac81b40692cb7d9fad949198af3e3eedee9cd5","observation_id":"0f3d2194-6c73-4b32-8c53-f3f78e954083","resolution":{"observed_at":"2026-05-26T20:38:01.141578Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"The neural compu- tation of aﬀective internal states in the hypothalamus: A dynamical systems perspective.Neuron, 113(23):3887–3907, December 2025","venue":null,"work_id":"039672bf-8b05-4fde-9cfa-983e7173c9e3","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:559ec5ac7a89d38af8386c7d94d5856e8fe6eac8a6ecfe428cd0ad3e0e26c419","observation_id":"fa4fac6a-a8e6-41c4-8e24-bc4ed7741e80","resolution":{"observed_at":"2026-05-26T20:38:01.306485Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Continual learning via local module composition","venue":null,"work_id":"dea8148b-6f60-4114-a9b0-981a1f198ba1","year":2021},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:cfea9b534d1021798673c16e8d81d533aeaa02ccf89ae0003f7fc46d14e1e3d5","observation_id":"ac4ee6de-b62f-4226-80a3-cd0491f7e1aa","resolution":{"observed_at":"2026-05-26T20:38:01.136106Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Individual variabil- ity of neural computations underlying ﬂexible decisions.Nature, 639 (8054):421–429","venue":null,"work_id":"60e8c768-d1e5-4301-bcf9-c7adae04d396","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:b7b3752f4e33a62128222b7ad6e108330d31aca453c8dba43cb73b69416dcb2a","observation_id":"0f5a6a6b-9dd9-4160-8125-2ada19eee22c","resolution":{"observed_at":"2026-05-26T20:38:01.160774Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Infer- ring single-trial neural population dynamics using sequential auto- encoders.Nat","venue":null,"work_id":"6a1bb9b8-5880-4ef0-970c-ffeef1a78387","year":2018},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:d345f34b24933d6ddf45c355576f430d19fde4f8150761d513f6fd438239dd5f","observation_id":"002dcdb7-4585-429d-a041-10e004d4670e","resolution":{"observed_at":"2026-05-26T20:38:01.125063Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ferreira, et al","venue":null,"work_id":"99f05349-3418-40f9-bf63-3d6f4477793a","year":2010},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:27ca05b52009b96c2bac0a46daa4fb77f65268688fd0d562342372f22b82b3ea","observation_id":"23e453c2-76bf-4dcf-89a0-ce52f9c67b3e","resolution":{"observed_at":"2026-05-26T20:38:01.131048Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Neural latents benchmark ’21: Evaluating latent variable models of neural population activ- ity","venue":null,"work_id":"1bcc4b85-c1c5-4012-b674-b5aec9f0c1dc","year":2021},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:b43f8f60245601f94ef041d0600f00abf88d390df8c58ab6028d1b3d68b60dce","observation_id":"aca1d029-6bb4-4f9d-88c1-957beb782959","resolution":{"observed_at":"2026-05-26T20:38:01.145116Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A neural manifold view of the brain.Nature neuroscience, pages 1–16, July 2025","venue":null,"work_id":"c4a18d83-5a9c-4ed8-9ea9-478ddad21eeb","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:8d023254f9cca3a36577a77e40c8b909993ff968466a225c49995b818b27ea1c","observation_id":"82dcd820-ffdd-4789-9ed0-fc8b1b6ff1d4","resolution":{"observed_at":"2026-05-26T20:38:01.114556Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Connectome simulations identify a central pattern generator circuit for ﬂy walking","venue":null,"work_id":"24e90170-8d82-4f00-99f7-d2675cb9d6dc","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:c67a135f4f21d4b4f774f3e4249d338a7b006f947e2b48b8085dd263cb62cb91","observation_id":"39335d3a-2388-4cef-a75d-f647e36c02ef","resolution":{"observed_at":"2026-05-26T20:38:01.148060Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A generalist agent","venue":null,"work_id":"eb49b08d-02f2-4f50-a4e9-c9cae3be4471","year":2022},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:08442cdd5495d98a70e148d01cea0ff1e262147dd316b404738b5c6cf48cd91f","observation_id":"3cf6c567-ff0d-4be8-8a57-6b2d7a9bafb9","resolution":{"observed_at":"2026-05-26T20:38:01.052730Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Rezende, Shakir Mohamed, and Daan Wierstra","venue":null,"work_id":"5c4fe148-8ffd-4d5a-8173-f8605f039b5d","year":2014},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:dad9442e258dfd9cd18cc2485a3dfd237565bad3915681a0aa4fabec60c084b1","observation_id":"dc261cc1-7d51-44b2-bac0-79047d3208a4","resolution":{"observed_at":"2026-05-26T20:38:00.925893Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Syntactic compo- sition in neural systems","venue":null,"work_id":"99c62b08-3639-46bb-8750-13c2b6d9d7fd","year":2026},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:0783c186ab15f60db49a0bec4455ffdb967a91a7b65171dbb1795d8c67193424","observation_id":"4e8b4030-3827-4452-be68-846482784efb","resolution":{"observed_at":"2026-05-26T20:38:01.021258Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A reduction of imitation learning and structured prediction to no-regret online learning","venue":null,"work_id":"551982e6-42cb-49da-b097-ae86b6f21551","year":2011},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:bd5e59ad29ebd09b8a184c988c72dd442556b885825d541f30f2f70818ee71d1","observation_id":"8a8c3036-53b2-48ee-8c23-bf8eb1eeac92","resolution":{"observed_at":"2026-05-26T20:38:00.888909Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"New Y ork, Wiley","venue":null,"work_id":"8d3f9516-400a-40b0-af0a-6aaa5be521b6","year":1952},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:f833110aae0e9f053804bf830e6fd127bd6b9dd0e9d8afbd25fb7d692b38de26","observation_id":"5a518e54-8c0d-41a1-adb3-dfbf3d3f851d","resolution":{"observed_at":"2026-05-26T20:38:01.316083Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning nonlinear dynami- cal systems using the expectation-maximization algorithm","venue":null,"work_id":"0dfd8193-3f9c-4042-ab54-975edc19119a","year":2001},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:0d88f675888caf500d6f314106e0f30612dc246a06280cd734522cffb2904a3f","observation_id":"09bf8513-09b3-4cdf-82ef-8603bb671b0d","resolution":{"observed_at":"2026-05-26T20:38:01.193223Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Princeton University Press, December 2025","venue":null,"work_id":"ea3c37c0-9d52-4a82-a720-06f1e2cef85d","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:a6be94a91d6e7ad2d81b612d17aaca99f9b30e622b0082cfeb3175461d24e217","observation_id":"e0dd2469-23fc-4a49-a8ff-9b8b3447db16","resolution":{"observed_at":"2026-05-26T20:38:01.031895Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Gen- eralizable, real-time neural decoding with hybrid state-space models","venue":null,"work_id":"637287cb-be07-435f-866d-99ec0bfca780","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:16c0a7b9e6551e2b0f65b1d86d53a80325bc38451ce04d4374b8fd858073b76f","observation_id":"732ba80d-5dfa-4b9d-81ae-056dea397079","resolution":{"observed_at":"2026-05-26T20:38:00.955000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Preserved neu- ral dynamics across animals performing similar behaviour.Nature, 623(7988):765–771, November 2023","venue":null,"work_id":"1f726c8b-8c53-4950-9a70-c1cd67f3763d","year":2023},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:0b395554baaf86de282375024c327aa9e6321e9f0d7c2baa467ac37a2f749ddc","observation_id":"4e071b88-223a-49e5-b89d-4f55d10952bb","resolution":{"observed_at":"2026-05-26T20:38:00.947238Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Cambridge University Press","venue":null,"work_id":"2cef9bc6-2119-4a9c-b20d-fc67b09594df","year":2013},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:a7158cf73e3852b84358e2abf003181c907d2ffe104e99d4a0a0b884b11e52d6","observation_id":"e6d62840-41e0-4d6e-a2b9-f73fa7433792","resolution":{"observed_at":"2026-05-26T20:38:01.119307Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"T emporal parallelization of bayesian smoothers.IEEE Transactions on Automatic Control, 66(1): 299–306","venue":null,"work_id":"5f85e011-6caa-47a7-8507-b2e9932fe025","year":2020},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:1774d94c454d2255aa4aea175b5ffc155832b70d03436dfaf32202f1d2223c65","observation_id":"248129a9-a1f9-42f7-8d76-512c1716b7d0","resolution":{"observed_at":"2026-05-26T20:38:01.011594Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Reverse-engineering recurrent neu- ral network solutions to a hierarchical inference task for mice","venue":null,"work_id":"692eecf0-88a8-4ad0-b1f5-6172685532b3","year":2020},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:dfdfcf4d9849dfb04584437839bdfaffafbea3c57ad8d670508d78e0d56f6e29","observation_id":"52473c63-3924-404f-b0e0-f650a4f65a81","resolution":{"observed_at":"2026-05-26T20:38:01.279497Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Discovering mod- ular solutions that generalize compositionally","venue":null,"work_id":"595df8e6-dc99-4f0c-8768-c1b31c3ed8df","year":2024},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:2c27cee5138080d58826e2ee6bc2a1e9eb1115bf8cab0686e49e956aa1b4b1a9","observation_id":"6c7d9bc2-9442-4686-9304-f93a613162d3","resolution":{"observed_at":"2026-05-26T20:38:01.190159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2411.12091","last_updated":"2025-05-19T17:01:57Z","snapshot_observed_at":"2026-07-06T19:52:15.853216Z","submitted_at":"2024-11-18T22:04:05Z","title":"Homogenized $\\textit{C. elegans}$ Neural Activity and Connectivity Data","version":4},"cited_work":{"arxiv_id":"2411.12091","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2411.12091","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"HomogenizedC","venue":null,"work_id":"e419e9ee-da83-4cc3-a170-38fe02a230bd","year":2024},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"cited_paper":"/paper/2411.12091","citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:c3725a15d248884d64f6abdbd41e044276b2a1af5efaf25c2ec458c4ed124507","observation_id":"e0780b2c-a673-4705-b7a3-88f2bdbcb6fa","resolution":{"observed_at":"2026-05-11T21:36:17.169693Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Reverse engineer- ing recurrent neural networks with jacobian switching linear dynam- ical systems.Advances in Neural Information Processing Systems, 34, December 2021","venue":null,"work_id":"cac132c0-cc1b-4a1f-9c82-4a6e98636da2","year":2021},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:382053134c88de09dc954375363f1610cf52a03dac27ddf7a7312d802e0ce23b","observation_id":"f9e55635-3f12-4b5d-9932-6c4624ae8282","resolution":{"observed_at":"2026-05-26T20:38:00.894931Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Simpli- ﬁed state space layers for sequence modeling","venue":null,"work_id":"808ecdda-7062-4dc7-822b-03838b4d529f","year":2022},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:3dcf97ab7a95aa14e655bc3c2baf5b188d9d51c5c5c4876338802620070eb475","observation_id":"f19274b3-f6d8-433f-942f-be2699476b3b","resolution":{"observed_at":"2026-05-26T20:38:01.063430Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"MABe22: A multi-species multi-task benchmark for learned representations of behavior","venue":null,"work_id":"2ae12dee-2695-40aa-bf52-0f2adce8dd13","year":2023},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:7758c578c4b2b7e5f27bfed596b495eb18a953364e477853e7045e504907aae8","observation_id":"fe95785a-6497-4972-a1be-7eab1b822fc1","resolution":{"observed_at":"2026-05-26T20:38:00.901108Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Speed always wins: A survey on eﬃcient architectures for large language models.arXiv [cs.CL], August 2025","venue":null,"work_id":"4817b6a5-7a4e-41f4-8d1f-c985d0a78fd8","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:d473601e181485dff38ffe66c756e30e5785e9d8df70cdf52e70b5b3b6490e41","observation_id":"e765e7e9-78d7-473e-8a0c-7e2ce7811c80","resolution":{"observed_at":"2026-05-26T20:38:00.912122Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Neural circuits as computational dynamical systems","venue":null,"work_id":"5cb18430-03dc-43ce-adee-4ab21df2da8f","year":2014},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:9db11e1e00bc18a074f173ce18a85b5903a61ad014f832a6320a504bcaeab7c5","observation_id":"074da632-240d-42cf-9852-7985b6e275fb","resolution":{"observed_at":"2026-05-26T20:38:01.111011Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"fc40bd06-29a6-4dc9-84f2-e3178214ed92","year":2019},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:bd2857643ef0dbdd72b9b6e9f6969a9bf21dbf8b37be1aaee236da12ff40b9c4","observation_id":"f6a8b6f6-a2bb-4dd6-a6b9-88adc373d567","resolution":{"observed_at":"2026-05-26T20:38:00.917024Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Data sharing for computational neuroscience.Neuroinformatics, 6(1):47–55, February 2008","venue":null,"work_id":"151eea50-b137-4486-87af-2dc03f428ed7","year":2008},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:097e54425d471b718b4029c37f905d5141241f6a32c4bea31e3c69304bff2323","observation_id":"c8455eb5-830c-49d9-ac8b-3511beb0d5d9","resolution":{"observed_at":"2026-05-26T20:38:01.204632Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Standardized and reproducible measurement of decision-making in mice.eLife, 10(biorxiv;2020.01.17.909838v4): e63711, May 2021","venue":null,"work_id":"e33c8897-a36a-4889-976e-7b6ea3f0cee0","year":2020},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:7dd53cc0fd2bd96cb0347ac7225c8dbb1cd1d67182a70c6f4ea07ddb75bdd1e6","observation_id":"c6256683-805e-4b1f-9e33-7d2b3daf30c8","resolution":{"observed_at":"2026-05-26T20:38:00.921279Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Extract- ing computational mechanisms from neural data using low-rank RNNs","venue":null,"work_id":"1615f201-775b-4da3-a296-53353a960196","year":2022},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:98bd4199c7c10abced489fbcab59dd0cf0f39cb58f5265ca635110f7bae3b2ab","observation_id":"7492845f-639d-42e0-8238-5d6455ddfc24","resolution":{"observed_at":"2026-05-26T20:38:01.326660Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"The dynamical hypothesis in cognitive science.The behavioral and brain sciences, 21:615–628, October 1998","venue":null,"work_id":"e734c416-b10f-4e67-a203-6ea458b98070","year":1998},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:90f42b8ea62c1ad0020a5d248dd1ea17d704fcdb06631645cb2c4edfe032f33a","observation_id":"79c6f2aa-19ea-4e2b-89ba-0437accc3571","resolution":{"observed_at":"2026-05-26T20:38:01.213949Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Whole-body physics simulation of fruit ﬂy locomotion.Nature, 643:1312–1320, April 2025","venue":null,"work_id":"29102270-5f6e-42dd-b6f2-8c4148b9488f","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:547c4c5537cf7b235006c10f5d4e690e2b0165d1fc7a8603170289db903e8a5a","observation_id":"3c76a89c-e31b-448b-b141-a1df5f0da33f","resolution":{"observed_at":"2026-05-26T20:38:01.309707Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Real-time machine learning strategies for a new kind of neuroscience experi- ments","venue":null,"work_id":"a7fad40a-b0da-493e-b0d7-14f727e024cc","year":2024},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:b2cb443872f9d13412054e53ea2d7d395d85fe6c90d1c31b2e5113cbd7a2f833","observation_id":"22ec3258-27db-4d54-90f8-7ef1e326eb02","resolution":{"observed_at":"2026-05-26T20:38:01.272851Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Meta-dynamical state space models for in- tegrative neural data analysis","venue":null,"work_id":"fbcc3a99-e5f5-413d-8e15-57c6b351444b","year":2025},"citing_paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience","version":1},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-05-08T04:48:04.799361Z"},"links":{"citing_paper":"/paper/2604.23903"},"observation_digest":"sha256:e1bb36efc2713616599a763dc90a9506528f56c28f7c3cdd6f84a27c8c33bac7","observation_id":"c543ce9d-74d8-4ec5-bbe6-bfff65bcbb66","resolution":{"observed_at":"2026-05-26T20:38:01.251676Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-07-24T06:31:00.690269+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2604.23903","last_updated":"2026-04-26T22:26:28Z","latest_version":1,"primary_category":"q-bio.NC","snapshot_observed_at":"2026-07-06T23:10:02.659384Z","submitted_at":"2026-04-26T22:26:28Z","title":"Integrative neurocybernetic modeling in the era of large-scale neuroscience"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":1,"verified_fuzzy":98},"total_outbound_references":112},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-07-24T06:31:00.690269+00:00","source":"crossref"},{"observed_at":"2026-07-24T06:30:55.483554+00:00","source":"retraction_watch"}],"thesis":"As of 25 July 2026, this Paper Citation Record lists 100 of 112 outbound references and 0 inbound Pith citation observations for arXiv:2604.23903."}