{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T16:06:03Z","timestamp":1772553963363,"version":"3.50.1"},"reference-count":53,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2019,9,14]],"date-time":"2019-09-14T00:00:00Z","timestamp":1568419200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Brain and heart continuously interact through anatomical and biochemical connections. Although several brain regions are known to be involved in the autonomic control, the functional brain\u2013heart interplay (BHI) during emotional processing is not fully characterized yet. To this aim, we investigate BHI during emotional elicitation in healthy subjects. The functional linear and nonlinear couplings are quantified using the maximum information coefficient calculated between time-varying electroencephalography (EEG) power spectra within the canonical bands (    \u03b4 , \u03b8 , \u03b1 , \u03b2     and    \u03b3   ), and time-varying low-frequency and high-frequency powers from heartbeat dynamics. Experimental data were gathered from 30 healthy volunteers whose emotions were elicited through pleasant and unpleasant high-arousing videos. Results demonstrate that functional BHI increases during videos with respect to a resting state through EEG oscillations not including the    \u03b3    band (&gt;30 Hz). Functional linear coupling seems associated with a high-arousing positive elicitation, with preferred EEG oscillations in the    \u03b8    band (    [ 4 , 8 )     Hz) especially over the left-temporal and parietal cortices. Differential functional nonlinear coupling between emotional valence seems to mainly occur through EEG oscillations in the     \u03b4 , \u03b8 , \u03b1     bands and sympathovagal dynamics, as well as through     \u03b4 , \u03b1 , \u03b2     oscillations and parasympathetic activity mainly over the right hemisphere. Functional BHI through    \u03b4    and    \u03b1    oscillations over the prefrontal region seems primarily nonlinear. This study provides novel insights on synchronous heartbeat and cortical dynamics during emotional video elicitation, also suggesting that a nonlinear analysis is needed to fully characterize functional BHI.<\/jats:p>","DOI":"10.3390\/e21090892","type":"journal-article","created":{"date-parts":[[2019,9,16]],"date-time":"2019-09-16T03:17:57Z","timestamp":1568603877000},"page":"892","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":27,"title":["Functional Linear and Nonlinear Brain\u2013Heart Interplay during Emotional Video Elicitation: A Maximum Information Coefficient Study"],"prefix":"10.3390","volume":"21","author":[{"given":"Vincenzo","family":"Catrambone","sequence":"first","affiliation":[{"name":"Department of Information Engineering and Bioengineering and Robotics Research Center \u201cE.Piaggio\u201d, University of Pisa, Largo Lucio Lazzarino, 56126 Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4822-5562","authenticated-orcid":false,"given":"Alberto","family":"Greco","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Bioengineering and Robotics Research Center \u201cE.Piaggio\u201d, University of Pisa, Largo Lucio Lazzarino, 56126 Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2588-4917","authenticated-orcid":false,"given":"Enzo Pasquale","family":"Scilingo","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Bioengineering and Robotics Research Center \u201cE.Piaggio\u201d, University of Pisa, Largo Lucio Lazzarino, 56126 Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6574-1879","authenticated-orcid":false,"given":"Gaetano","family":"Valenza","sequence":"additional","affiliation":[{"name":"Department of Information Engineering and Bioengineering and Robotics Research Center \u201cE.Piaggio\u201d, University of Pisa, Largo Lucio Lazzarino, 56126 Pisa, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"209","DOI":"10.1080\/02699930802204677","article-title":"Measures of emotion: A review","volume":"23","author":"Mauss","year":"2009","journal-title":"Cogn. Emot."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"101","DOI":"10.1111\/j.1749-6632.2001.tb03475.x","article-title":"Emotion and the human brain","volume":"935","author":"Damasio","year":"2001","journal-title":"Ann. N. Y. Acad. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/j.biopsycho.2010.03.010","article-title":"Autonomic nervous system activity in emotion: A review","volume":"84","author":"Kreibig","year":"2010","journal-title":"Biol. Psychol."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1037\/0033-295X.101.2.211","article-title":"The varieties of emotional experience: a meditation on James-Lange theory","volume":"101","author":"Lang","year":"1994","journal-title":"Psychol. Rev."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"106","DOI":"10.2307\/1415404","article-title":"The James-Lange theory of emotions: A critical examination and an alternative theory","volume":"39","author":"Cannon","year":"1927","journal-title":"Am. J. Psychol."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Benarroch, E.E. (2012). Central autonomic control. Primer on the Autonomic Nervous System, Elsevier.","DOI":"10.1016\/B978-0-12-386525-0.00002-0"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"10503","DOI":"10.1523\/JNEUROSCI.1103-13.2013","article-title":"The autonomic brain: An activation likelihood estimation meta-analysis for central processing of autonomic function","volume":"33","author":"Beissner","year":"2013","journal-title":"J. Neurosci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1016\/j.neuroimage.2019.04.075","article-title":"The central autonomic network at rest: uncovering functional MRI correlates of time-varying autonomic outflow","volume":"197","author":"Valenza","year":"2019","journal-title":"Neuroimage"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"R25","DOI":"10.1152\/ajpregu.00151.2018","article-title":"Lateralization of Directional Brain-Heart Information Transfer during Visual Emotional Elicitation","volume":"317","author":"Greco","year":"2019","journal-title":"Am. J. Physiol.-Regul. Integr. Comp. Physiol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.ijcard.2012.03.165","article-title":"Stressed brain, diseased heart: A review on the pathophysiologic mechanisms of neurocardiology","volume":"166","author":"Pereira","year":"2013","journal-title":"Int. J. Cardiol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1007\/s00429-010-0251-3","article-title":"The role of anterior insular cortex in social emotions","volume":"214","author":"Lamm","year":"2010","journal-title":"Brain Struct. Funct."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1038\/nn1176","article-title":"Neural systems supporting interoceptive awareness","volume":"7","author":"Critchley","year":"2004","journal-title":"Nat. Neurosci."},{"key":"ref_13","first-page":"I3","article-title":"The anatomy and physiology of cortical mechanisms of cardiac control","volume":"24","author":"Oppenheimer","year":"1993","journal-title":"Stroke"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2781","DOI":"10.1523\/JNEUROSCI.4372-06.2007","article-title":"The prefrontal cortex as a key target of the maladaptive response to stress","volume":"27","author":"Cerqueira","year":"2007","journal-title":"J. Neurosci."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"67","DOI":"10.3389\/fphys.2011.00067","article-title":"Anger, emotion, and arrhythmias: From brain to heart","volume":"2","author":"Taggart","year":"2011","journal-title":"Front. Physiol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1357","DOI":"10.1152\/ajplegacy.1975.229.5.1357","article-title":"Hypothalamic modulation of baroreceptor afferent unit activity","volume":"229","author":"Adair","year":"1975","journal-title":"Am. J. Physiol.-Leg. Content"},{"key":"ref_17","unstructured":"Foreman, R., and Chandler, M. (1994). Vagal afferent modulation of cardiac pain. Vagal Control of the Heart: Experimental Basis and Clinical Implications, Futura Publishing."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1111\/j.1528-1167.1990.tb06301.x","article-title":"Cardiac and respiratory correlations with unit discharge in epileptic human temporal lobe","volume":"31","author":"Frysinger","year":"1990","journal-title":"Epilepsia"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"573734","DOI":"10.1155\/2013\/573734","article-title":"A review on the computational methods for emotional state estimation from the human EEG","volume":"2013","author":"Kim","year":"2013","journal-title":"Comput. Math. Methods Med."},{"key":"ref_20","first-page":"1","article-title":"Emotion recognition using electroencephalography (EEG): A review","volume":"7","author":"Singh","year":"2013","journal-title":"Int. J. Inf. Technol. Knowl. Manag."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1109\/T-AFFC.2010.1","article-title":"Affect detection: An interdisciplinary review of models, methods, and their applications","volume":"1","author":"Calvo","year":"2010","journal-title":"IEEE Trans. Affect. Comput."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Coan, J.A., and Allen, J.J. (2007). Handbook of Emotion Elicitation and Assessment, Oxford University Press.","DOI":"10.1093\/oso\/9780195169157.001.0001"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1031","DOI":"10.1007\/s11517-006-0119-0","article-title":"Heart rate variability: A review","volume":"44","author":"Acharya","year":"2006","journal-title":"Med Biol. Eng. Comput."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/S0278-2626(03)00011-3","article-title":"Central and autonomic nervous system integration in emotion","volume":"52","author":"Hagemann","year":"2003","journal-title":"Brain Cogn."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1016\/j.neubiorev.2008.08.004","article-title":"Claude Bernard and the heart\u2013brain connection: Further elaboration of a model of neurovisceral integration","volume":"33","author":"Thayer","year":"2009","journal-title":"Neurosci. Biobehav. Rev."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"13315","DOI":"10.1038\/srep13315","article-title":"Complexity of cardiac signals for predicting changes in alpha-waves after stress in patients undergoing cardiac catheterization","volume":"5","author":"Chiu","year":"2015","journal-title":"Sci. Rep."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"105005","DOI":"10.1088\/1367-2630\/16\/10\/105005","article-title":"Information dynamics of brain\u2013heart physiological networks during sleep","volume":"16","author":"Faes","year":"2014","journal-title":"New J. Phys."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1479","DOI":"10.1007\/s10439-019-02251-y","article-title":"Time-Resolved Directional Brain\u2013Heart Interplay Measurement Through Synthetic Data Generation Models","volume":"47","author":"Catrambone","year":"2019","journal-title":"Ann. Biomed. Eng."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"20150178","DOI":"10.1098\/rsta.2015.0178","article-title":"Central-and autonomic nervous system coupling in schizophrenia","volume":"374","author":"Schulz","year":"2016","journal-title":"Philos. Trans. R. Soc. A: Math. Phys. Eng. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.ijpsycho.2015.02.009","article-title":"Resting state Rolandic mu rhythms are related to activity of sympathetic component of autonomic nervous system in healthy humans","volume":"103","author":"Triggiani","year":"2016","journal-title":"Int. J. Psychophysiol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"821061","DOI":"10.1155\/2015\/821061","article-title":"Cognitive behavior evaluation based on physiological parameters among young healthy subjects with yoga as intervention","volume":"2015","author":"Nagendra","year":"2015","journal-title":"Comput. Math. Methods Med."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"683","DOI":"10.1088\/0967-3334\/36\/4\/683","article-title":"Linear and non-linear brain\u2013heart and brain\u2013brain interactions during sleep","volume":"36","author":"Faes","year":"2015","journal-title":"Physiol. Meas."},{"key":"ref_33","first-page":"20120517","article-title":"Assessing causality in brain dynamics and cardiovascular control","volume":"371","author":"Porta","year":"2013","journal-title":"Philos. Trans. Ser. A Math. Phys. Eng. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1152\/japplphysiol.00842.2017","article-title":"Measures of sympathetic and parasympathetic autonomic outflow from heartbeat dynamics","volume":"125","author":"Valenza","year":"2018","journal-title":"J. Appl. Physiol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"20150176","DOI":"10.1098\/rsta.2015.0176","article-title":"Combining electroencephalographic activity and instantaneous heart rate for assessing brain\u2013heart dynamics during visual emotional elicitation in healthy subjects","volume":"374","author":"Valenza","year":"2016","journal-title":"Phil. Trans. R. Soc. A"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1959","DOI":"10.1016\/j.neubiorev.2011.05.001","article-title":"Human brain EEG indices of emotions: delineating responses to affective vocalizations by measuring frontal theta event-related synchronization","volume":"35","author":"Bekkedal","year":"2011","journal-title":"Neurosci. Biobehav. Rev."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1016\/S0304-3940(01)01703-7","article-title":"Affective picture processing: Event-related synchronization within individually defined human theta band is modulated by valence dimension","volume":"303","author":"Aftanas","year":"2001","journal-title":"Neurosci. Lett."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"206","DOI":"10.1111\/j.1467-9450.2012.00941.x","article-title":"The relationship of positive and negative expressiveness to the processing of emotion information","volume":"53","author":"Knyazev","year":"2012","journal-title":"Scand. J. Psychol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1518","DOI":"10.1126\/science.1205438","article-title":"Detecting novel associations in large data sets","volume":"334","author":"Reshef","year":"2011","journal-title":"Science"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1257","DOI":"10.1007\/s11042-013-1450-8","article-title":"Hybrid video emotional tagging using users\u2019 EEG and video content","volume":"72","author":"Wang","year":"2014","journal-title":"Multimed. Tools Appl."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1080\/02699939308409183","article-title":"Inducing and assessing differentiated emotion-feeling states in the laboratory","volume":"7","author":"Philippot","year":"1993","journal-title":"Cogn. Emot."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1080\/02699939508408966","article-title":"Emotion elicitation using films","volume":"9","author":"Gross","year":"1995","journal-title":"Cogn. Emot."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1109\/T-AFFC.2011.37","article-title":"Multimodal emotion recognition in response to videos","volume":"3","author":"Soleymani","year":"2012","journal-title":"IEEE Trans. Affect. Comput."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Schreuder, E., van Erp, J., Toet, A., and Kallen, V.L. (2016). Emotional responses to multisensory environmental stimuli: A conceptual framework and literature review. SAGE Open, 6.","DOI":"10.1177\/2158244016630591"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1038\/d41586-019-00857-9","article-title":"Scientists rise up against statistical significance","volume":"567","author":"Amrhein","year":"2019","journal-title":"Nature"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/00031305.2019.1583913","article-title":"Moving to a World Beyond p < 0.05","volume":"73","author":"Wasserstein","year":"2019","journal-title":"Am. Stat."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.neuropsychologia.2014.03.014","article-title":"A review of brain oscillations in perception of faces and emotional pictures","volume":"58","year":"2014","journal-title":"Neuropsychologia"},{"key":"ref_48","first-page":"258","article-title":"Emotions and the Right Hemisphere: Can New Data Clarify Old Models?","volume":"25","author":"Gainotti","year":"2019","journal-title":"Neurosci."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1111\/psyp.12027","article-title":"The utility of low frequency heart rate variability as an index of sympathetic cardiac tone: A review with emphasis on a reanalysis of previous studies","volume":"50","author":"Langewitz","year":"2013","journal-title":"Psychophysiology"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"2828","DOI":"10.1109\/TBME.2012.2211356","article-title":"A real-time automated point-process method for the detection and correction of erroneous and ectopic heartbeats","volume":"59","author":"Citi","year":"2012","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"ref_51","first-page":"1447","article-title":"Overlearning in marginal distribution-based ICA: analysis and solutions","volume":"4","year":"2003","journal-title":"J. Mach. Learn. Res."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"97","DOI":"10.3389\/fnins.2018.00097","article-title":"The Harvard Automated Processing Pipeline for Electroencephalography (HAPPE): Standardized processing software for developmental and high-artifact data","volume":"12","author":"Wilkinson","year":"2018","journal-title":"Front. Neurosci."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"663","DOI":"10.1109\/TBME.2011.2171959","article-title":"Characterization of dynamic interactions between cardiovascular signals by time-frequency coherence","volume":"59","author":"Orini","year":"2012","journal-title":"IEEE Trans. Biomed. Eng."}],"container-title":["Entropy"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1099-4300\/21\/9\/892\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:20:13Z","timestamp":1760188813000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1099-4300\/21\/9\/892"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,14]]},"references-count":53,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2019,9]]}},"alternative-id":["e21090892"],"URL":"https:\/\/doi.org\/10.3390\/e21090892","relation":{},"ISSN":["1099-4300"],"issn-type":[{"value":"1099-4300","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,9,14]]}}}