{"id":"doi:10.1016/j.neuron.2022.12.007","kind":"article","title":"The centrality of population-level factors to network computation is demonstrated by a versatile approach for training spiking networks","authors":["Brian DePasquale","David C. Sussillo","Larry F. Abbott","Mark M. Churchland"],"author_count":4,"year":2023,"published":"2023-01-10","venue":"Neuron","cited_by":55,"doi":"10.1016/j.neuron.2022.12.007","arxiv_id":null,"nct_id":null,"source_url":"https://doi.org/10.1016/j.neuron.2022.12.007","archive_url":"https://space-kitty.com/papers/doi:10.1016/j.neuron.2022.12.007","updated":null,"pmid":"36630961","pmcid":null,"openalex_id":"W4315477380","pdf_url":null,"abstract":null,"abstract_license":null,"license":null,"is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Neural dynamics and brain function"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0).","topics":[{"slug":"interpretability","name":"Mechanistic Interpretability","domain_slug":"ai"}],"cited_in_dossiers":[]}