{"doi":"10.1016/j.nbd.2025.106866","title":"Functional dynamic network connectivity differentiates biological patterns in the Alzheimer's disease continuum","abstract":"Alzheimer's disease (AD) can be conceptualized as a network-based syndrome. Network alterations are linked to the molecular hallmarks of AD, involving amyloid-beta and tau accumulation, and consecutively neurodegeneration. By combining molecular and resting-state functional magnetic resonance imaging, we assessed whether different biological patterns of AD identified through a data-driven approach matched specific abnormalities in brain dynamic connectivity. We identified three main patient clusters. The first group displayed mild pathological alterations. The second cluster exhibited typical behavioral impairment alongside AD pathology. The third cluster demonstrated similar behavioral impairment but with a divergent tau (low) and neurodegeneration (high) profile. Univariate and multivariate analyses revealed two connectivity patterns encompassing the default mode network and the occipito-temporal cortex, linked respectively with typical and atypical patterns. These results support the key association between macro-scale and molecular alterations. Dynamic connectivity markers can assist in identifying patients with AD-like clinical profiles but with different underlying pathologies. Within the clinical continuum of Alzheimer's disease (AD), we identified two main groups: one characterized by typical AD neuropathological changes, and the other by atypical pathophysiological mechanisms. Univariate and multivariate analyses revealed two dynamic functional connectivity patterns, involving the default mode network and the occipito-temporal cortex, respectively. • The study assessed the dynamic functional connectivity profile linked with different ATN patterns. • We identified an atypical ATN cluster showing specific dynamic functional connectivity patterns. • Dynamic connectivity showed an accuracy of 87 % in discriminating between biological AD clusters.","journal":"Neurobiology of Disease","year":2025,"id":519198,"datarank":0.29188652235829704,"base_score":1.9459101490553132,"endowment":1.9459101490553132,"self_citation_contribution":0.29188652235829704,"citation_network_contribution":0.0,"self_endowment_contribution":0.29188652235829704,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":6,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9496,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1248862,"name":"Lorenza Brusini","orcid":"0000-0001-5357-5180","position":1,"is_corresponding":false},{"id":640385,"name":"Alessandra Griffa","orcid":"0000-0003-1923-1653","position":2,"is_corresponding":false},{"id":1166441,"name":"Federica Cruciani","orcid":"0000-0001-7258-1463","position":3,"is_corresponding":false},{"id":986615,"name":"Gilles Allali","orcid":"0000-0002-4455-6719","position":4,"is_corresponding":false},{"id":302522,"name":"Giovanni B. Frisoni","orcid":"0000-0002-6419-1753","position":5,"is_corresponding":false},{"id":15949,"name":"Maurizio Corbetta","orcid":"0000-0001-8295-3304","position":6,"is_corresponding":false},{"id":984678,"name":"Gloria Menegaz","orcid":"0000-0002-6889-3461","position":7,"is_corresponding":false},{"id":1166442,"name":"Ilaria Boscolo Galazzo","orcid":"0000-0002-4153-3749","position":8,"is_corresponding":false},{"id":554521,"name":"Lorenzo Pini","orcid":"0000-0002-9305-3376","position":0,"is_corresponding":true}],"reference_count":58,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:49:18.751199Z","pmid":"40081429","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":[]}