{"doi":"10.7554/elife.102309.2","title":"Dimorphic neural network architecture prioritizes sexual-related behaviors in male Caenorhabditis elegans","abstract":"<jats:p>\n                    Neural network architecture determines its functional output. However, the detailed mechanisms are not well characterized. In this study, we focused on the neural network architectures of male and hermaphrodite\n                    <jats:italic>Caenorhabditis elegans</jats:italic>\n                    and the association with sexually dimorphic behaviors. We applied graph theory and computational neuroscience methods to systematically discern the features of these two neural networks. Our findings revealed that a small percentage of sexual-specific neurons exerted dominance throughout the entire male neural network, suggesting males prioritized sexual-related behavior outputs. Based on the structural and dynamical characteristics of two complete neural networks, sub-networks containing sex-specific neurons and their immediate neighbors, or sub-networks exclusively comprising sex-shared neurons, we predicted dimorphic behavioral outcomes for males and hermaphrodites. To verify the prediction, we performed behavioral and calcium imaging experiments and dissected a circuit that is specific for the increased spontaneous local search in males for mate-searching. Our research sheds light on the neural circuits that underlie sexually dimorphic behaviors in\n                    <jats:italic>C. elegans</jats:italic>\n                    and provides significant insights into the interconnected relationship between network architecture and functional outcomes at the whole-brain level.\n                  </jats:p>","journal":"eLife","year":2026,"id":625725,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1618403,"name":"Hanzhang Liu","orcid":null,"position":1,"is_corresponding":false},{"id":816193,"name":"Wenjing Yang","orcid":"0000-0002-9929-5480","position":2,"is_corresponding":false},{"id":622969,"name":"Jingxuan Yang","orcid":"0000-0003-3265-161X","position":3,"is_corresponding":false},{"id":1618404,"name":"Xuehong Sun","orcid":null,"position":4,"is_corresponding":false},{"id":1618405,"name":"Qiuhan Liu","orcid":null,"position":5,"is_corresponding":false},{"id":1071882,"name":"Ying Zhu","orcid":"0000-0002-3430-3929","position":6,"is_corresponding":false},{"id":313923,"name":"Yinghao Sun","orcid":"0000-0002-7603-0965","position":7,"is_corresponding":false},{"id":1618406,"name":"Chunxiuzi Liu","orcid":null,"position":8,"is_corresponding":false},{"id":1618407,"name":"Guiyuan Shi","orcid":null,"position":9,"is_corresponding":false},{"id":1196978,"name":"Qiang Liu","orcid":"0000-0002-9232-1420","position":10,"is_corresponding":false},{"id":370808,"name":"Ke Zhang","orcid":"0000-0002-7130-3215","position":11,"is_corresponding":false},{"id":1618408,"name":"Zengru Di","orcid":null,"position":12,"is_corresponding":false},{"id":355716,"name":"Wenxing Yang","orcid":"0000-0003-0965-787X","position":13,"is_corresponding":false},{"id":355714,"name":"He Liu","orcid":"0000-0001-9418-9171","position":14,"is_corresponding":false},{"id":418632,"name":"Xuebin Wang","orcid":"0000-0002-7894-1922","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Dimorphic neural network architecture prioritizes sexual-related behaviors in male Caenorhabditis elegans","abstract":"<jats:p>\n                    Neural network architecture determines its functional output. However, the detailed mechanisms are not well characterized. In this study, we focused on the neural network architectures of male and hermaphrodite\n                    <jats:italic>Caenorhabditis elegans</jats:italic>\n                    and the association with sexually dimorphic behaviors. We applied graph theory and computational neuroscience methods to systematically discern the features of these two neural networks. Our findings revealed that a small percentage of sexual-specific neurons exerted dominance throughout the entire male neural network, suggesting males prioritized sexual-related behavior outputs. Based on the structural and dynamical characteristics of two complete neural networks, sub-networks containing sex-specific neurons and their immediate neighbors, or sub-networks exclusively comprising sex-shared neurons, we predicted dimorphic behavioral outcomes for males and hermaphrodites. To verify the prediction, we performed behavioral and calcium imaging experiments and dissected a circuit that is specific for the increased spontaneous local search in males for mate-searching. Our research sheds light on the neural circuits that underlie sexually dimorphic behaviors in\n                    <jats:italic>C. elegans</jats:italic>\n                    and provides significant insights into the interconnected relationship between network architecture and functional outcomes at the whole-brain level.\n                  </jats:p>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19767382","pmcid":null,"openalex_id":"https://openalex.org/W7154961485","authors":[],"funders":[{"funder_name":"National Natural Science Foundation of China","grant_id":"32371079","title":null},{"funder_name":"National Natural Science Foundation of China","grant_id":"32000720","title":null},{"funder_name":"National Natural Science Foundation of China","grant_id":"32271178","title":null}],"total_grants":3,"fwci":0.0,"citation_percentile":0.43882175,"influential_citations":0,"citation_trend":[],"oa_status":"gold","license":"cc-by","oa_locations":[{"url":"https://doi.org/10.7554/elife.102309.2","host_type":"journal"},{"url":"https://doi.org/10.7554/elife.102309.2","host_type":"publisher"},{"url":"https://cdn.elifesciences.org/articles/102309/elife-102309-v1.pdf","host_type":"publisher"},{"url":"https://cdn.elifesciences.org/articles/102309/elife-102309-v1.xml","host_type":"publisher"},{"url":"https://elifesciences.org/articles/102309","host_type":"publisher"}],"fields_of_study":["Genetics, Aging, and Longevity in Model Organisms","Neurobiology and Insect Physiology Research","Evolution and Genetic Dynamics"],"mesh_terms":[],"keywords":["Sexual dimorphism","Biological neural network","Caenorhabditis elegans","Artificial neural network","Nerve net","Dominance (genetics)","Connectome","Nervous system network models"],"sdg_mappings":[{"sdg_number":0,"sdg_label":"Gender equality"}],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-04T07:39:22.235412Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}