{"id":"https://openalex.org/W2793741460","doi":"https://doi.org/10.1117/12.2293318","title":"High resolution robust and smooth precision matrices to capture functional connectivity","display_name":"High resolution robust and smooth precision matrices to capture functional connectivity","publication_year":2018,"publication_date":"2018-03-02","ids":{"openalex":"https://openalex.org/W2793741460","doi":"https://doi.org/10.1117/12.2293318","mag":"2793741460"},"language":"en","primary_location":{"id":"doi:10.1117/12.2293318","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2293318","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2018: Image Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5008142843","display_name":"Nicolas Honnorat","orcid":"https://orcid.org/0000-0003-2210-9341"},"institutions":[{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Nicolas Honnorat","raw_affiliation_strings":["Univ. of Pennsylvania (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Pennsylvania (United States)","institution_ids":["https://openalex.org/I36788626"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034999945","display_name":"Christos Davatzikos","orcid":"https://orcid.org/0000-0002-1025-8561"},"institutions":[{"id":"https://openalex.org/I36788626","display_name":"California University of Pennsylvania","ror":"https://ror.org/01spssf70","country_code":"US","type":"education","lineage":["https://openalex.org/I36788626"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christos Davatzikos","raw_affiliation_strings":["Univ. of Pennsylvania (United States)"],"affiliations":[{"raw_affiliation_string":"Univ. of Pennsylvania (United States)","institution_ids":["https://openalex.org/I36788626"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5008142843"],"corresponding_institution_ids":["https://openalex.org/I36788626"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.02057683,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"80","issue":null,"first_page":"82","last_page":"82"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11304","display_name":"Advanced Neuroimaging Techniques and Applications","score":0.9965000152587891,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10378","display_name":"Advanced MRI Techniques and Applications","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/human-connectome-project","display_name":"Human Connectome Project","score":0.7336723804473877},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.6883008480072021},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6510303616523743},{"id":"https://openalex.org/keywords/connectome","display_name":"Connectome","score":0.6404494047164917},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5451632142066956},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.5366380214691162},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5178821086883545},{"id":"https://openalex.org/keywords/resting-state-fmri","display_name":"Resting state fMRI","score":0.5029482245445251},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.4997138977050781},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49232518672943115},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41501346230506897},{"id":"https://openalex.org/keywords/functional-connectivity","display_name":"Functional connectivity","score":0.3786807656288147},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.251770555973053},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2202983796596527},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09248530864715576},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.07914280891418457}],"concepts":[{"id":"https://openalex.org/C97820695","wikidata":"https://www.wikidata.org/wiki/Q387749","display_name":"Human Connectome Project","level":3,"score":0.7336723804473877},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.6883008480072021},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6510303616523743},{"id":"https://openalex.org/C45715564","wikidata":"https://www.wikidata.org/wiki/Q1292103","display_name":"Connectome","level":3,"score":0.6404494047164917},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5451632142066956},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.5366380214691162},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5178821086883545},{"id":"https://openalex.org/C66324658","wikidata":"https://www.wikidata.org/wiki/Q7316120","display_name":"Resting state fMRI","level":2,"score":0.5029482245445251},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.4997138977050781},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49232518672943115},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41501346230506897},{"id":"https://openalex.org/C3018011982","wikidata":"https://www.wikidata.org/wiki/Q7316120","display_name":"Functional connectivity","level":2,"score":0.3786807656288147},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.251770555973053},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2202983796596527},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09248530864715576},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.07914280891418457},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/12.2293318","is_oa":false,"landing_page_url":"https://doi.org/10.1117/12.2293318","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Medical Imaging 2018: Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.6299999952316284}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1999598817","https://openalex.org/W2024729467","https://openalex.org/W2119963163","https://openalex.org/W2499800833","https://openalex.org/W2559162002","https://openalex.org/W2951407072","https://openalex.org/W3087273884","https://openalex.org/W3113720674","https://openalex.org/W4233688842","https://openalex.org/W6635744865"],"related_works":["https://openalex.org/W1520477417","https://openalex.org/W3150454329","https://openalex.org/W4250679599","https://openalex.org/W4236064658","https://openalex.org/W3016599742","https://openalex.org/W3136590534","https://openalex.org/W3082461017","https://openalex.org/W2047006349","https://openalex.org/W3210626554","https://openalex.org/W4281670718"],"abstract_inverted_index":{"Resting-state":[0],"functional":[1,18,28],"MRI":[2],"(fMRI)":[3],"provides":[4],"a":[5,13,144,217],"crucial":[6],"insight":[7],"into":[8],"brain":[9,21,42,54,103],"organization,":[10],"by":[11,37,168],"offering":[12],"mean":[14],"to":[15,52,112,173],"measure":[16],"the":[17,26,33,39,67,73,77,80,84,87,129,132,155,174,186,207,211,214,221,224,229],"connectivity":[19],"between":[20,41],"regions.":[22],"A":[23],"popular":[24],"measure,":[25],"effective":[27],"connectivity,":[29],"is":[30],"derived":[31,118],"from":[32,119],"precision":[34,81,94,116,158,196,225],"matrix":[35,226],"obtained":[36,160],"inverting":[38],"correlations":[40],"regions":[43],"fMRI":[44,64,74,121,163,208],"signals.":[45],"This":[46],"approach":[47],"has":[48],"been":[49],"widely":[50],"adopted":[51],"build":[53],"connectomes":[55],"for":[56,91,128,161,233],"large":[57],"populations.":[58],"For":[59],"small":[60],"populations":[61],"and":[62,83,147,237],"single":[63,120],"scans,":[65],"however,":[66],"significant":[68],"amount":[69],"of":[70,79,86,131,157,185,223],"noise":[71],"in":[72,141,231,238],"scans":[75,165,184],"reduces":[76],"quality":[78,156],"matrices,":[82],"non-invertibility":[85],"correlation":[88,133,145,192],"matrices":[89,117,159],"calls":[90],"more":[92],"sophisticated":[93],"estimators.":[95],"These":[96],"issues":[97],"are":[98,201],"especially":[99],"dramatic":[100],"at":[101],"full":[102,114],"resolution.":[104],"In":[105],"this":[106],"work,":[107],"we":[108,124,136],"investigate":[109,137],"several":[110],"approaches":[111,127],"improve":[113,228],"resolution":[115],"scans.":[122],"First,":[123],"compare":[125],"three":[126],"computation":[130],"matrix.":[134],"Then,":[135],"two":[138,148,199],"regularized":[139],"inversions,":[140],"combination":[142,239],"with":[143,203,240],"shrinkage":[146,193],"spatial":[149],"smoothing":[150],"strategies.":[151],"During":[152],"these":[153],"experiments,":[154,179],"random":[162],"half":[164],"was":[166],"measured":[167],"their":[169,171],"generalization:":[170],"fit":[172],"unseen":[175],"time":[176,235],"points.":[177],"Our":[178],"using":[180],"ten":[181],"high":[182],"resolutions":[183],"Human":[187],"Connectome":[188],"Project,":[189],"indicate":[190],"that":[191],"strongly":[194],"improves":[195],"generalization.":[197,205],"The":[198],"regularizations":[200],"associated":[202],"similar":[204],"Smoothing":[206],"signal":[209],"before":[210],"inversion":[212],"deteriorates":[213],"generalization":[215],"whereas":[216],"penalty":[218],"directly":[219],"improving":[220],"smoothness":[222],"can":[227],"generalization,":[230],"particular":[232],"short":[234],"series":[236],"shrinkage.":[241]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}