{"doi":"10.1016/j.neuroimage.2020.116865","title":"Leveraging shared connectivity to aggregate heterogeneous datasets into a common response space","abstract":"Connectivity hyperalignment can be used to estimate a single shared response space across disjoint datasets. We develop a connectivity-based shared response model that factorizes aggregated fMRI datasets into a single reduced-dimension shared connectivity space and subject-specific topographic transformations. These transformations resolve idiosyncratic functional topographies and can be used to project response time series into shared space. We evaluate this algorithm on a large collection of heterogeneous, naturalistic fMRI datasets acquired while subjects listened to spoken stories. Projecting subject data into shared space dramatically improves between-subject story time-segment classification and increases the dimensionality of shared information across subjects. This improvement generalizes to subjects and stories excluded when estimating the shared space. We demonstrate that estimating a simple semantic encoding model in shared space improves between-subject forward encoding and inverted encoding model performance. The shared space estimated across all datasets is distinct from the shared space derived from any particular constituent dataset; the algorithm leverages shared connectivity to yield a consensus shared space conjoining diverse story stimuli.","journal":"NeuroImage","year":2020,"id":92068,"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":43,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9399,"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":462372,"name":"Yun-Fei Liu","orcid":null,"position":1,"is_corresponding":false},{"id":460911,"name":"Hanna Hillman","orcid":"0000-0001-8367-1640","position":2,"is_corresponding":false},{"id":269716,"name":"Kenneth A. Norman","orcid":"0000-0002-5887-9682","position":3,"is_corresponding":false},{"id":231578,"name":"Uri Hasson","orcid":"0000-0002-3599-7168","position":4,"is_corresponding":false},{"id":231579,"name":"Samuel A. Nastase","orcid":"0000-0001-7013-5275","position":0,"is_corresponding":true}],"reference_count":107,"raw_metadata":null,"created_at":"2026-07-18T22:29:54.256205Z","pmid":"32325212","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":[]}