{"doi":"10.17615/wp32-bk50","title":"Disrupted functional connectome in antisocial personality disorder","abstract":"Studies on antisocial personality disorder (ASPD) subjects focus on brain functional alterations in relation to antisocial behaviors. Neuroimaging research has identified a number of focal brain regions with abnormal structures or functions in ASPD. However, little is known about the connections among brain regions in terms of inter-regional whole-brain networks in ASPD patients, as well as possible alterations of brain functional topological organization. In this study, we employ resting-state functional magnetic resonance imaging (R-fMRI) to examine functional connectome of 32 ASPD patients and 35 normal controls by using a variety of network properties, including small-worldness, modularity, and connectivity. The small-world analysis reveals that ASPD patients have increased path length and decreased network efficiency, which implies a reduced ability of global integration of whole-brain functions. Modularity analysis suggests ASPD patients have decreased overall modularity, merged network modules, and reduced intra- and inter-module connectivities related to frontal regions. Also, network-based statistics show that an internal sub-network, composed of 16 nodes and 16 edges, is significantly affected in ASPD patients, where brain regions are mostly located in the fronto-parietal control network. These results suggest that ASPD is associated with both reduced brain integration and segregation in topological organization of functional brain networks, particularly in the fronto-parietal control network. These disruptions may contribute to disturbances in behavior and cognition in patients with ASPD. Our findings may provide insights into a deeper understanding of functional brain networks of ASPD.","journal":"UNC Libraries","year":2020,"id":141873,"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":0.9503,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":385161,"name":"Feng Shi","orcid":"0000-0003-1522-9943","position":1,"is_corresponding":false},{"id":434201,"name":"Huasheng Liu","orcid":"0000-0002-2635-999X","position":2,"is_corresponding":false},{"id":297699,"name":"Hui Shen","orcid":"0000-0003-3408-8154","position":3,"is_corresponding":false},{"id":275492,"name":"Wei Wang","orcid":"0000-0001-6853-7785","position":4,"is_corresponding":false},{"id":434202,"name":"Dewen Hu","orcid":"0000-0001-7357-0053","position":5,"is_corresponding":false},{"id":548906,"name":"Celina Shen","orcid":null,"position":6,"is_corresponding":false},{"id":607880,"name":"Tao Wang","orcid":"0000-0002-4765-9377","position":7,"is_corresponding":false},{"id":548292,"name":"Weixiong Jiang","orcid":"0000-0002-3898-4223","position":8,"is_corresponding":false},{"id":270449,"name":"Dinggang Shen","orcid":"0000-0002-7934-5698","position":9,"is_corresponding":false},{"id":607879,"name":"Jian Liao","orcid":"0000-0001-6290-3326","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-18T23:17:27.861239Z","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":[]}