{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T23:11:08Z","timestamp":1778195468912,"version":"3.51.4"},"reference-count":80,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2023,4,1]],"date-time":"2023-04-01T00:00:00Z","timestamp":1680307200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/2.zoppoz.workers.dev:443\/https\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003196","name":"Italian Ministry of Health","doi-asserted-by":"publisher","award":["RF-2016-02361069"],"award-info":[{"award-number":["RF-2016-02361069"]}],"id":[{"id":"10.13039\/501100003196","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Nonlinear markers of coupling strength are often utilized to typify cardiorespiratory and cerebrovascular regulations. The computation of these indices requires techniques describing nonlinear interactions between respiration (R) and heart period (HP) and between mean arterial pressure (MAP) and mean cerebral blood velocity (MCBv). We compared two model-free methods for the assessment of dynamic HP\u2013R and MCBv\u2013MAP interactions, namely the cross-sample entropy (CSampEn) and k-nearest-neighbor cross-unpredictability (KNNCUP). Comparison was carried out first over simulations generated by linear and nonlinear unidirectional causal, bidirectional linear causal, and lag-zero linear noncausal models, and then over experimental data acquired from 19 subjects at supine rest during spontaneous breathing and controlled respiration at 10, 15, and 20 breaths\u00b7minute\u22121 as well as from 13 subjects at supine rest and during 60\u00b0 head-up tilt. Linear markers were computed for comparison. We found that: (i) over simulations, CSampEn and KNNCUP exhibit different abilities in evaluating coupling strength; (ii) KNNCUP is more reliable than CSampEn when interactions occur according to a causal structure, while performances are similar in noncausal models; (iii) in healthy subjects, KNNCUP is more powerful in characterizing cardiorespiratory and cerebrovascular variability interactions than CSampEn and linear markers. We recommend KNNCUP for quantifying cardiorespiratory and cerebrovascular coupling.<\/jats:p>","DOI":"10.3390\/e25040599","type":"journal-article","created":{"date-parts":[[2023,4,3]],"date-time":"2023-04-03T02:32:27Z","timestamp":1680489147000},"page":"599","update-policy":"https:\/\/2.zoppoz.workers.dev:443\/https\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["On the Different Abilities of Cross-Sample Entropy and K-Nearest-Neighbor Cross-Unpredictability in Assessing Dynamic Cardiorespiratory and Cerebrovascular Interactions"],"prefix":"10.3390","volume":"25","author":[{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-6720-9824","authenticated-orcid":false,"given":"Alberto","family":"Porta","sequence":"first","affiliation":[{"name":"Department of Biomedical Sciences for Health, University of Milan, 20133 Milan, Italy"},{"name":"Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato, 20097 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-5346-2677","authenticated-orcid":false,"given":"Vlasta","family":"Bari","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences for Health, University of Milan, 20133 Milan, Italy"},{"name":"Department of Cardiothoracic, Vascular Anesthesia and Intensive Care, IRCCS Policlinico San Donato, 20097 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-9221-6153","authenticated-orcid":false,"given":"Francesca","family":"Gelpi","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences for Health, University of Milan, 20133 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0003-3396-6883","authenticated-orcid":false,"given":"Beatrice","family":"Cairo","sequence":"additional","affiliation":[{"name":"Department of Biomedical Sciences for Health, University of Milan, 20133 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-5360-3137","authenticated-orcid":false,"given":"Beatrice","family":"De Maria","sequence":"additional","affiliation":[{"name":"IRCCS Istituti Clinici Scientifici Maugeri, 20138 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Davide","family":"Tonon","sequence":"additional","affiliation":[{"name":"Department of Neurology, IRCCS Sacro Cuore Don Calabria Hospital, 37024 Verona, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0001-9560-4437","authenticated-orcid":false,"given":"Gianluca","family":"Rossato","sequence":"additional","affiliation":[{"name":"Department of Neurology, IRCCS Sacro Cuore Don Calabria Hospital, 37024 Verona, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/2.zoppoz.workers.dev:443\/https\/orcid.org\/0000-0002-3271-5348","authenticated-orcid":false,"given":"Luca","family":"Faes","sequence":"additional","affiliation":[{"name":"Department of Engineering, University of Palermo, 90128 Palermo, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,4,1]]},"reference":[{"key":"ref_1","first-page":"H6","article-title":"Cardiorespiratory interactions in humans and animals: Rhythms for life","volume":"315","author":"Elstad","year":"2018","journal-title":"Am. 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