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dc.contributor.author | Alba, Guzmán | es_ES |
dc.contributor.author | Vila, Jaime | es_ES |
dc.contributor.author | Rey, Beatriz | es_ES |
dc.contributor.author | Montoya, Pedro | es_ES |
dc.contributor.author | Muñoz, Miguel Ángel | es_ES |
dc.date.accessioned | 2020-12-11T04:34:23Z | |
dc.date.available | 2020-12-11T04:34:23Z | |
dc.date.issued | 2019-02-25 | es_ES |
dc.identifier.issn | 1662-5161 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/156864 | |
dc.description.abstract | [EN] The neurovisceral integration model proposes a neuronal network that is related to heart rate activity and cognitive performance. The aim of this study was to determine whether heart rate variability (HRV) and variability in electroencephalographic (EEG) functional connectivity in the resting state are related to cognitive flexibility. Thirty-eight right-handed students completed the CAMBIOS test, and their heart and EEG activity was recorded during 6 min in the resting state with their eyes open. We calculated correlations, partial correlations and multiple linear regressions among HRV indices, functional brain connectivity variability and CAMBIOS scores. Furthermore, the sample was divided into groups according to CAMBIOS performance, and one-way ANOVA was applied to evaluate group differences. Our results show direct and inverse correlations among cognitive flexibility, connectivity (positive and negative task networks) and heartbeat variability. Partial correlations and multiple linear regressions suggest that the relation between HRV and CAMBIOS performance is mediated by neuronal oscillations. ANOVA confirms that HRV and variability in functional brain connectivity is related to cognitive performance. In conclusion, the levels of brain signal variability might predict cognitive flexibility in a cognitive task, while HRV might predict cognitive flexibility only when it is mediated by neuronal oscillations. | es_ES |
dc.description.sponsorship | This work was supported by the Spanish Ministry of Economy and Competitiveness (PSI2014-57231-R). Research was funded by Grant Nos. PSI2014-57231-R and PSI2017-88388-C4-3-R from Spanish Ministry of Science. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The authors have declared that no competing interests exist. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Frontiers Media SA | es_ES |
dc.relation.ispartof | Frontiers in Human Neuroscience | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | HRV | es_ES |
dc.subject | EEG | es_ES |
dc.subject | Resting-state | es_ES |
dc.subject | Sample entropy | es_ES |
dc.subject | Variability of functional connectivity | es_ES |
dc.subject | Cognitive flexibility | es_ES |
dc.subject.classification | EXPRESION GRAFICA EN LA INGENIERIA | es_ES |
dc.title | The Relationship Between Heart Rate Variability and Electroencephalography Functional Connectivity Variability Is Associated With Cognitive Flexibility | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3389/fnhum.2019.00064 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//PSI2014-57231-R/ES/MODULACION AFECTIVA DE LA ACTIVIDAD CEREBRAL PARA ALIVIAR EL DOLOR: ESTUDIO DE LA CONECTIVIDAD FUNCIONAL MEDIANTE EEG/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/PSI2017-88388-C4-3-R/ES/CORRELATOS NEUROFISIOLOGICOS DEL ENTRENAMIENTO EN LA PERCEPCION NOCICEPTIVA MEDIANTE LA ILUSION DE UN MIEMBRO VIRTUAL./ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Ingeniería Gráfica - Departament d'Enginyeria Gràfica | es_ES |
dc.description.bibliographicCitation | Alba, G.; Vila, J.; Rey, B.; Montoya, P.; Muñoz, MÁ. (2019). The Relationship Between Heart Rate Variability and Electroencephalography Functional Connectivity Variability Is Associated With Cognitive Flexibility. Frontiers in Human Neuroscience. 13(64):1-12. https://doi.org/10.3389/fnhum.2019.00064 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3389/fnhum.2019.00064 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 12 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 13 | es_ES |
dc.description.issue | 64 | es_ES |
dc.identifier.pmid | 30858800 | es_ES |
dc.identifier.pmcid | PMC6397840 | es_ES |
dc.relation.pasarela | S\391201 | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
dc.description.references | Alba, G., Pereda, E., Mañas, S., Méndez, L. D., Duque, M. R., González, A., & González, J. J. (2016). The variability of EEG functional connectivity of young ADHD subjects in different resting states. Clinical Neurophysiology, 127(2), 1321-1330. doi:10.1016/j.clinph.2015.09.134 | es_ES |
dc.description.references | Albinet, C. T., Abou-Dest, A., André, N., & Audiffren, M. (2016). Executive functions improvement following a 5-month aquaerobics program in older adults: Role of cardiac vagal control in inhibition performance. Biological Psychology, 115, 69-77. doi:10.1016/j.biopsycho.2016.01.010 | es_ES |
dc.description.references | Albinet, C. T., Boucard, G., Bouquet, C. A., & Audiffren, M. (2010). Increased heart rate variability and executive performance after aerobic training in the elderly. European Journal of Applied Physiology, 109(4), 617-624. doi:10.1007/s00421-010-1393-y | es_ES |
dc.description.references | Allen, E. A., Damaraju, E., Plis, S. M., Erhardt, E. B., Eichele, T., & Calhoun, V. D. (2012). Tracking Whole-Brain Connectivity Dynamics in the Resting State. Cerebral Cortex, 24(3), 663-676. doi:10.1093/cercor/bhs352 | es_ES |
dc.description.references | Barttfeld, P., Petroni, A., Báez, S., Urquina, H., Sigman, M., Cetkovich, M., … Ibañez, A. (2014). Functional Connectivity and Temporal Variability of Brain Connections in Adults with Attention Deficit/Hyperactivity Disorder and Bipolar Disorder. Neuropsychobiology, 69(2), 65-75. doi:10.1159/000356964 | es_ES |
dc.description.references | CAÑAS, J., QUESADA, J., ANTOLÍ, A., & FAJARDO, I. (2003). Cognitive flexibility and adaptability to environmental changes in dynamic complex problem-solving tasks. Ergonomics, 46(5), 482-501. doi:10.1080/0014013031000061640 | es_ES |
dc.description.references | Carrillo-de-la-Peña, M. T., & García-Larrea, L. (2007). Right frontal event related EEG coherence (ERCoh) differentiates good from bad performers of the Wisconsin Card Sorting Test (WCST). Neurophysiologie Clinique/Clinical Neurophysiology, 37(2), 63-75. doi:10.1016/j.neucli.2007.02.002 | es_ES |
dc.description.references | Catarino, A., Churches, O., Baron-Cohen, S., Andrade, A., & Ring, H. (2011). Atypical EEG complexity in autism spectrum conditions: A multiscale entropy analysis. Clinical Neurophysiology, 122(12), 2375-2383. doi:10.1016/j.clinph.2011.05.004 | es_ES |
dc.description.references | Chang, C., Liu, Z., Chen, M. C., Liu, X., & Duyn, J. H. (2013). EEG correlates of time-varying BOLD functional connectivity. NeuroImage, 72, 227-236. doi:10.1016/j.neuroimage.2013.01.049 | es_ES |
dc.description.references | Chang, C., Metzger, C. D., Glover, G. H., Duyn, J. H., Heinze, H.-J., & Walter, M. (2013). Association between heart rate variability and fluctuations in resting-state functional connectivity. NeuroImage, 68, 93-104. doi:10.1016/j.neuroimage.2012.11.038 | es_ES |
dc.description.references | Chen, Y., Wang, W., Zhao, X., Sha, M., Liu, Y., Zhang, X., … Ming, D. (2017). Age-Related Decline in the Variation of Dynamic Functional Connectivity: A Resting State Analysis. Frontiers in Aging Neuroscience, 9. doi:10.3389/fnagi.2017.00203 | es_ES |
dc.description.references | Contreras, M. J., Colom, R., Hernández, J. M., & Santacreu, J. (2003). Is Static Spatial Performance Distinguishable From Dynamic Spatial Performance? A Latent-Variable Analysis. The Journal of General Psychology, 130(3), 277-288. doi:10.1080/00221300309601159 | es_ES |
dc.description.references | Cooper, P. S., Wong, A. S. W., Fulham, W. R., Thienel, R., Mansfield, E., Michie, P. T., & Karayanidis, F. (2015). Theta frontoparietal connectivity associated with proactive and reactive cognitive control processes. NeuroImage, 108, 354-363. doi:10.1016/j.neuroimage.2014.12.028 | es_ES |
dc.description.references | De Carvalho, J. L. A., da Rocha, A. F., de Oliveira Nascimento, F. A., Neto, J. S., & Junqueira, L. F. (s. f.). Development of a Matlab software for analysis of heart rate variability. 6th International Conference on Signal Processing, 2002. doi:10.1109/icosp.2002.1180076 | es_ES |
dc.description.references | De Pasquale, F., Della Penna, S., Snyder, A. Z., Lewis, C., Mantini, D., Marzetti, L., … Corbetta, M. (2010). Temporal dynamics of spontaneous MEG activity in brain networks. Proceedings of the National Academy of Sciences, 107(13), 6040-6045. doi:10.1073/pnas.0913863107 | es_ES |
dc.description.references | Delorme, A., & Makeig, S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of Neuroscience Methods, 134(1), 9-21. doi:10.1016/j.jneumeth.2003.10.009 | es_ES |
dc.description.references | Dennis, J. P., & Vander Wal, J. S. (2009). The Cognitive Flexibility Inventory: Instrument Development and Estimates of Reliability and Validity. Cognitive Therapy and Research, 34(3), 241-253. doi:10.1007/s10608-009-9276-4 | es_ES |
dc.description.references | Duschek, S., Muckenthaler, M., Werner, N., & Reyes del Paso, G. A. (2009). Relationships between features of autonomic cardiovascular control and cognitive performance. Biological Psychology, 81(2), 110-117. doi:10.1016/j.biopsycho.2009.03.003 | es_ES |
dc.description.references | Fornito, A., Harrison, B. J., Zalesky, A., & Simons, J. S. (2012). Competitive and cooperative dynamics of large-scale brain functional networks supporting recollection. Proceedings of the National Academy of Sciences, 109(31), 12788-12793. doi:10.1073/pnas.1204185109 | es_ES |
dc.description.references | Fox, M. D., Corbetta, M., Snyder, A. Z., Vincent, J. L., & Raichle, M. E. (2006). Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems. Proceedings of the National Academy of Sciences, 103(26), 10046-10051. doi:10.1073/pnas.0604187103 | es_ES |
dc.description.references | Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005). From The Cover: The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences, 102(27), 9673-9678. doi:10.1073/pnas.0504136102 | es_ES |
dc.description.references | Garrett, D. D., Kovacevic, N., McIntosh, A. R., & Grady, C. L. (2011). The Importance of Being Variable. Journal of Neuroscience, 31(12), 4496-4503. doi:10.1523/jneurosci.5641-10.2011 | es_ES |
dc.description.references | Geurts, H. M., Corbett, B., & Solomon, M. (2009). The paradox of cognitive flexibility in autism. Trends in Cognitive Sciences, 13(2), 74-82. doi:10.1016/j.tics.2008.11.006 | es_ES |
dc.description.references | González-Hernández, J. A., Pita-Alcorta, C., Cedeño, I., Bosch-Bayard, J., Galán-Garcia, L., Scherbaum, W. A., & Figueredo-Rodriguez, P. (2002). Wisconsin card sorting test synchronizes the prefrontal, temporal and posterior association cortex in different frequency ranges and extensions. Human Brain Mapping, 17(1), 37-47. doi:10.1002/hbm.10051 | es_ES |
dc.description.references | Hansen, A. L., Johnsen, B. H., Sollers, J. J., Stenvik, K., & Thayer, J. F. (2004). Heart rate variability and its relation to prefrontal cognitive function: the effects of training and detraining. European Journal of Applied Physiology, 93(3), 263-272. doi:10.1007/s00421-004-1208-0 | es_ES |
dc.description.references | Hansen, A. L., Johnsen, B. H., & Thayer, J. F. (2003). Vagal influence on working memory and attention. International Journal of Psychophysiology, 48(3), 263-274. doi:10.1016/s0167-8760(03)00073-4 | es_ES |
dc.description.references | Hansen, A. L., Johnsen, B. H., & Thayer, J. F. (2009). Relationship between heart rate variability and cognitive function during threat of shock. Anxiety, Stress & Coping, 22(1), 77-89. doi:10.1080/10615800802272251 | es_ES |
dc.description.references | Hovland, A., Pallesen, S., Hammar, Å., Hansen, A. L., Thayer, J. F., Tarvainen, M. P., & Nordhus, I. H. (2012). The relationships among heart rate variability, executive functions, and clinical variables in patients with panic disorder. International Journal of Psychophysiology, 86(3), 269-275. doi:10.1016/j.ijpsycho.2012.10.004 | es_ES |
dc.description.references | Ionescu, T. (2012). Exploring the nature of cognitive flexibility. New Ideas in Psychology, 30(2), 190-200. doi:10.1016/j.newideapsych.2011.11.001 | es_ES |
dc.description.references | Jennings, J. R., Allen, B., Gianaros, P. J., Thayer, J. F., & Manuck, S. B. (2014). Focusing neurovisceral integration: Cognition, heart rate variability, and cerebral blood flow. Psychophysiology, 52(2), 214-224. doi:10.1111/psyp.12319 | es_ES |
dc.description.references | Jennings, J. R., Sheu, L. K., Kuan, D. C.-H., Manuck, S. B., & Gianaros, P. J. (2015). Resting state connectivity of the medial prefrontal cortex covaries with individual differences in high-frequency heart rate variability. Psychophysiology, 53(4), 444-454. doi:10.1111/psyp.12586 | es_ES |
dc.description.references | Jia, H., Hu, X., & Deshpande, G. (2014). Behavioral Relevance of the Dynamics of the Functional Brain Connectome. Brain Connectivity, 4(9), 741-759. doi:10.1089/brain.2014.0300 | es_ES |
dc.description.references | Kitzbichler, M. G., Smith, M. L., Christensen, S. R., & Bullmore, E. (2009). Broadband Criticality of Human Brain Network Synchronization. PLoS Computational Biology, 5(3), e1000314. doi:10.1371/journal.pcbi.1000314 | es_ES |
dc.description.references | Kucyi, A., & Davis, K. D. (2014). Dynamic functional connectivity of the default mode network tracks daydreaming. NeuroImage, 100, 471-480. doi:10.1016/j.neuroimage.2014.06.044 | es_ES |
dc.description.references | Lantz, G., Grave de Peralta, R., Spinelli, L., Seeck, M., & Michel, C. . (2003). Epileptic source localization with high density EEG: how many electrodes are needed? Clinical Neurophysiology, 114(1), 63-69. doi:10.1016/s1388-2457(02)00337-1 | es_ES |
dc.description.references | Laufs, H., Krakow, K., Sterzer, P., Eger, E., Beyerle, A., Salek-Haddadi, A., & Kleinschmidt, A. (2003). Electroencephalographic signatures of attentional and cognitive default modes in spontaneous brain activity fluctuations at rest. Proceedings of the National Academy of Sciences, 100(19), 11053-11058. doi:10.1073/pnas.1831638100 | es_ES |
dc.description.references | Liu, J., Liao, X., Xia, M., & He, Y. (2017). Chronnectome fingerprinting: Identifying individuals and predicting higher cognitive functions using dynamic brain connectivity patterns. Human Brain Mapping, 39(2), 902-915. doi:10.1002/hbm.23890 | es_ES |
dc.description.references | Mackey, A. P., Miller Singley, A. T., & Bunge, S. A. (2013). Intensive Reasoning Training Alters Patterns of Brain Connectivity at Rest. Journal of Neuroscience, 33(11), 4796-4803. doi:10.1523/jneurosci.4141-12.2013 | es_ES |
dc.description.references | Malik, M., Bigger, J. T., Camm, A. J., Kleiger, R. E., Malliani, A., Moss, A. J., & Schwartz, P. J. (1996). Heart rate variability: Standards of measurement, physiological interpretation, and clinical use. European Heart Journal, 17(3), 354-381. doi:10.1093/oxfordjournals.eurheartj.a014868 | es_ES |
dc.description.references | Mantini, D., Perrucci, M. G., Del Gratta, C., Romani, G. L., & Corbetta, M. (2007). Electrophysiological signatures of resting state networks in the human brain. Proceedings of the National Academy of Sciences, 104(32), 13170-13175. doi:10.1073/pnas.0700668104 | es_ES |
dc.description.references | Martínez, K., Solana, A. B., Burgaleta, M., Hernández-Tamames, J. A., Álvarez-Linera, J., Román, F. J., … Colom, R. (2012). Changes in resting-state functionally connected parietofrontal networks after videogame practice. Human Brain Mapping, 34(12), 3143-3157. doi:10.1002/hbm.22129 | es_ES |
dc.description.references | McDonough, I. M., & Nashiro, K. (2014). Network complexity as a measure of information processing across resting-state networks: evidence from the Human Connectome Project. Frontiers in Human Neuroscience, 8. doi:10.3389/fnhum.2014.00409 | es_ES |
dc.description.references | McIntosh, A. R., Kovacevic, N., & Itier, R. J. (2008). Increased Brain Signal Variability Accompanies Lower Behavioral Variability in Development. PLoS Computational Biology, 4(7), e1000106. doi:10.1371/journal.pcbi.1000106 | es_ES |
dc.description.references | Mennes, M., Kelly, C., Zuo, X.-N., Di Martino, A., Biswal, B. B., Castellanos, F. X., & Milham, M. P. (2010). Inter-individual differences in resting-state functional connectivity predict task-induced BOLD activity. NeuroImage, 50(4), 1690-1701. doi:10.1016/j.neuroimage.2010.01.002 | es_ES |
dc.description.references | Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The Unity and Diversity of Executive Functions and Their Contributions to Complex «Frontal Lobe» Tasks: A Latent Variable Analysis. Cognitive Psychology, 41(1), 49-100. doi:10.1006/cogp.1999.0734 | es_ES |
dc.description.references | Mizuno, T., Takahashi, T., Cho, R. Y., Kikuchi, M., Murata, T., Takahashi, K., & Wada, Y. (2010). Assessment of EEG dynamical complexity in Alzheimer’s disease using multiscale entropy. Clinical Neurophysiology, 121(9), 1438-1446. doi:10.1016/j.clinph.2010.03.025 | es_ES |
dc.description.references | Monti, R. P., Hellyer, P., Sharp, D., Leech, R., Anagnostopoulos, C., & Montana, G. (2014). Estimating time-varying brain connectivity networks from functional MRI time series. NeuroImage, 103, 427-443. doi:10.1016/j.neuroimage.2014.07.033 | es_ES |
dc.description.references | Palva, J. M., Zhigalov, A., Hirvonen, J., Korhonen, O., Linkenkaer-Hansen, K., & Palva, S. (2013). Neuronal long-range temporal correlations and avalanche dynamics are correlated with behavioral scaling laws. Proceedings of the National Academy of Sciences, 110(9), 3585-3590. doi:10.1073/pnas.1216855110 | es_ES |
dc.description.references | Perakakis, P., Joffily, M., Taylor, M., Guerra, P., & Vila, J. (2010). KARDIA: A Matlab software for the analysis of cardiac interbeat intervals. Computer Methods and Programs in Biomedicine, 98(1), 83-89. doi:10.1016/j.cmpb.2009.10.002 | es_ES |
dc.description.references | Pumprla, J., Howorka, K., Groves, D., Chester, M., & Nolan, J. (2002). Functional assessment of heart rate variability: physiological basis and practical applications. International Journal of Cardiology, 84(1), 1-14. doi:10.1016/s0167-5273(02)00057-8 | es_ES |
dc.description.references | Raichle, M. E., & Snyder, A. Z. (2007). A default mode of brain function: A brief history of an evolving idea. NeuroImage, 37(4), 1083-1090. doi:10.1016/j.neuroimage.2007.02.041 | es_ES |
dc.description.references | Ramon, C., & Holmes, M. D. (2012). Noninvasive Localization of Epileptic Sites from Stable Phase Synchronization Patterns on Different Days Derived from Short Duration Interictal Scalp dEEG. Brain Topography, 26(1), 1-8. doi:10.1007/s10548-012-0236-z | es_ES |
dc.description.references | Richman, J. S., & Moorman, J. R. (2000). Physiological time-series analysis using approximate entropy and sample entropy. American Journal of Physiology-Heart and Circulatory Physiology, 278(6), H2039-H2049. doi:10.1152/ajpheart.2000.278.6.h2039 | es_ES |
dc.description.references | Sadaghiani, S., & Kleinschmidt, A. (2016). Brain Networks and α-Oscillations: Structural and Functional Foundations of Cognitive Control. Trends in Cognitive Sciences, 20(11), 805-817. doi:10.1016/j.tics.2016.09.004 | es_ES |
dc.description.references | Sadaghiani, S., Poline, J.-B., Kleinschmidt, A., & D’Esposito, M. (2015). Ongoing dynamics in large-scale functional connectivity predict perception. Proceedings of the National Academy of Sciences, 112(27), 8463-8468. doi:10.1073/pnas.1420687112 | es_ES |
dc.description.references | Sakaki, M., Yoo, H. J., Nga, L., Lee, T.-H., Thayer, J. F., & Mather, M. (2016). Heart rate variability is associated with amygdala functional connectivity with MPFC across younger and older adults. NeuroImage, 139, 44-52. doi:10.1016/j.neuroimage.2016.05.076 | es_ES |
dc.description.references | Saus, E.-R., Johnsen, B. H., Eid, J., Riisem, P. K., Andersen, R., & Thayer, J. F. (2006). The Effect of Brief Situational Awareness Training in a Police Shooting Simulator: An Experimental Study. Military Psychology, 18(sup1), S3-S21. doi:10.1207/s15327876mp1803s_2 | es_ES |
dc.description.references | Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., … Greicius, M. D. (2007). Dissociable Intrinsic Connectivity Networks for Salience Processing and Executive Control. Journal of Neuroscience, 27(9), 2349-2356. doi:10.1523/jneurosci.5587-06.2007 | es_ES |
dc.description.references | Smith, R., Thayer, J. F., Khalsa, S. S., & Lane, R. D. (2017). The hierarchical basis of neurovisceral integration. Neuroscience & Biobehavioral Reviews, 75, 274-296. doi:10.1016/j.neubiorev.2017.02.003 | es_ES |
dc.description.references | Stenfors, C. U. D., Hanson, L. M., Theorell, T., & Osika, W. S. (2016). Executive Cognitive Functioning and Cardiovascular Autonomic Regulation in a Population-Based Sample of Working Adults. Frontiers in Psychology, 7. doi:10.3389/fpsyg.2016.01536 | es_ES |
dc.description.references | Tagliazucchi, E., Balenzuela, P., Fraiman, D., & Chialvo, D. R. (2012). Criticality in Large-Scale Brain fMRI Dynamics Unveiled by a Novel Point Process Analysis. Frontiers in Physiology, 3. doi:10.3389/fphys.2012.00015 | es_ES |
dc.description.references | Takeuchi, H., Taki, Y., Hashizume, H., Sassa, Y., Nagase, T., Nouchi, R., & Kawashima, R. (2011). Effects of Training of Processing Speed on Neural Systems. Journal of Neuroscience, 31(34), 12139-12148. doi:10.1523/jneurosci.2948-11.2011 | es_ES |
dc.description.references | Thayer, J. F., Hansen, A. L., & Johnsen, B. H. (2010). The Non-invasive Assessment of Autonomic Influences on the Heart Using Impedance Cardiography and Heart Rate Variability. Handbook of Behavioral Medicine, 723-740. doi:10.1007/978-0-387-09488-5_47 | es_ES |
dc.description.references | Thayer, J. F., Hansen, A. L., Sollers III, J. J., & Johnsen, B. H. (2005). Heart rate variability as an index of prefrontal neural function in military settings. Biomonitoring for Physiological and Cognitive Performance during Military Operations. doi:10.1117/12.604420 | es_ES |
dc.description.references | Thayer, J. F., & Lane, R. D. (2009). Claude Bernard and the heart–brain connection: Further elaboration of a model of neurovisceral integration. Neuroscience & Biobehavioral Reviews, 33(2), 81-88. doi:10.1016/j.neubiorev.2008.08.004 | es_ES |
dc.description.references | Thompson, T. W., Waskom, M. L., & Gabrieli, J. D. E. (2016). Intensive Working Memory Training Produces Functional Changes in Large-scale Frontoparietal Networks. Journal of Cognitive Neuroscience, 28(4), 575-588. doi:10.1162/jocn_a_00916 | es_ES |
dc.description.references | Vakorin, V. A., Lippe, S., & McIntosh, A. R. (2011). Variability of Brain Signals Processed Locally Transforms into Higher Connectivity with Brain Development. Journal of Neuroscience, 31(17), 6405-6413. doi:10.1523/jneurosci.3153-10.2011 | es_ES |
dc.description.references | Vatansever, D., Menon, D. K., Manktelow, A. E., Sahakian, B. J., & Stamatakis, E. A. (2015). Default mode network connectivity during task execution. NeuroImage, 122, 96-104. doi:10.1016/j.neuroimage.2015.07.053 | es_ES |
dc.description.references | Yang, A. C., Huang, C.-C., Yeh, H.-L., Liu, M.-E., Hong, C.-J., Tu, P.-C., … Tsai, S.-J. (2013). Complexity of spontaneous BOLD activity in default mode network is correlated with cognitive function in normal male elderly: a multiscale entropy analysis. Neurobiology of Aging, 34(2), 428-438. doi:10.1016/j.neurobiolaging.2012.05.004 | es_ES |
dc.description.references | Zahn, D., Adams, J., Krohn, J., Wenzel, M., Mann, C. G., Gomille, L. K., … Kubiak, T. (2016). Heart rate variability and self-control—A meta-analysis. Biological Psychology, 115, 9-26. doi:10.1016/j.biopsycho.2015.12.007 | es_ES |