Zaccaro, Piarulli et al., Neural Correlates of Non-ordinary States of Consciousness in Pranayama Practitioners, The Role of Slow Nasal Breathing.pdf.pdf
[en] The modulatory effect of nasal respiration on integrative brain functions and hence consciousness has recently been unambiguously demonstrated. This effect is sustained by the olfactory epithelium mechanical sensitivity complemented by the existence of massive projections between the olfactory bulb and the prefrontal cortex. However, studies on slow nasal breathing (SNB) in the context of contemplative practices have sustained the fundamental role of respiratory vagal stimulation, with little attention to the contribution of the olfactory epithelium mechanical stimulation. This study aims at disentangling the effects of olfactory epithelium stimulation (proper of nasal breathing) from those related to respiratory vagal stimulation (common to slow nasal and mouth breathing). We investigated the psychophysiological (cardio-respiratory and electroencephalographic parameters) and phenomenological (perceived state of consciousness) aftereffects of SNB (epithelium mechanical - 2.5 breaths/min) in 12 experienced meditators. We compared the nasal breathing aftereffects with those observed after a session of mouth breathing at the same respiratory rate and with those related to a resting state condition. SNB induced (1) slowing of electroencephalography (EEG) activities (delta-theta bands) in prefrontal regions, (2) a widespread increase of theta and high-beta connectivity complemented by an increase of phase-amplitude coupling between the two bands in prefrontal and posterior regions belonging to the Default Mode Network, (3) an increase of high-beta networks small-worldness. (4) a higher perception of being in a non-ordinary state of consciousness. The emerging scenario strongly suggests that the effects of SNB, beyond the relative contribution of vagal stimulation, are mainly ascribable to olfactory epithelium stimulation. In conclusion, slow Pranayama breathing modulates brain activity and hence subjective experience up to the point of inducing a non-ordinary state of consciousness.
Disciplines :
Neurosciences & behavior
Author, co-author :
Zaccaro, Andrea ✱; Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, Pisa, Italy ; Department of Neuroscience, Imaging and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy
Piarulli, Andrea ✱; Université de Liège - ULiège > GIGA > GIGA Consciousness - Coma Science Group ; Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, Pisa, Italy
Menicucci, Danilo; Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, Pisa, Italy
Gemignani, Angelo; Department of Surgical, Medical and Molecular Pathology and Critical Care Medicine, University of Pisa, Pisa, Italy ; Clinical Psychology Branch, Azienda Ospedaliero Universitaria Pisana, Pisa, Italy
✱ These authors have contributed equally to this work.
Language :
English
Title :
Neural Correlates of Non-ordinary States of Consciousness in Pranayama Practitioners: The Role of Slow Nasal Breathing.
Achard S. Bullmore E. (2007). Efficiency and cost of economical brain functional networks. PLoS Comput. Biol. 3:e17. 10.1371/journal.pcbi.0030017 17274684
Akselrod S. Gordon D. Ubel F. A. Shannon D. C. Berger A. C. Cohen R. J. (1981). Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to beatcardiovascular control. Science 213 220–222. 10.1126/science.6166045 6166045
Bassett D. S. (2006). Adaptive reconfiguration of fractal small-world human brain functional networks. Proc. Natl. Acad. Sci. U.S.A. 103 19518–19523.
Benjamini Y. Hochberg Y. (1995). Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. Roy. Stat. Soc. B Met. 57 289–300. 10.1111/j.2517-6161.1995.tb02031.x
Brown R. P. Gerbarg P. L. Muench F. (2013). Breathing practices for treatment of psychiatric and stress-related medical conditions. Psychiat. Clin. N. Am. 36 121–140. 10.1016/j.psc.2013.01.001 23538082
Bruns A. Eckhorn R. (2004). Task-related coupling from high- to low-frequency signals among visual cortical areas in human subdural recordings. Int. J. Psychophysiol. 51 97–116. 10.1016/j.ijpsycho.2003.07.001 14693360
Buckner R. L. Andrews-Hanna J. R. Schacter D. L. (2008). The brain’s default network: anatomy, function, and relevance to disease. Ann. N. Y. Acad. Sci. 1124 1–38. 10.1196/annals.1440.011 18400922
Bullmore E. Sporns O. (2009). Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 10 186–198. 10.1038/nrn2575 19190637
Buzsáki G. Logothetis N. Singer W. (2013). Scaling brain size, keeping timing: evolutionary preservation of brain rhythms. Neuron 80 751–764. 10.1016/j.neuron.2013.10.002 24183025
Canolty R. T. Knight R. T. (2010). The functional role of cross-frequency coupling. Trends Cogn. Sci. 14 506–515. 10.1016/j.tics.2010.09.001 20932795
Carmichael S. T. Clugnet M.-C. Price J. L. (1994). Central olfactory connections in the macaque monkey. J. Comp. Neurol. 346 403–434. 10.1002/cne.903460306 7527806
Chae J. H. Nahas Z. Lomarev M. Denslow S. Lorberbaum J. P. Bohning D. E. et al. (2003). A review of functional neuroimaging studies of vagus nerve stimulation (VNS). J. Psychiatr. Res. 37 443–455. 10.1016/s0022-3956(03)00074-8
Chennu S. Annen J. Wannez S. Thibaut A. Chatelle C. Cassol H. et al. (2017). Brain networks predict metabolism, diagnosis, and prognosis at the bedside in disorders of consciousness. Brain 140 2120–2132. 10.1093/brain/awx163 28666351
Chennu S. Finoia P. Kamau E. Allanson J. Williams G. B. Monti M. M. et al. (2014). Spectral signatures of reorganised brain networks in disorders of consciousness. PLoS Comput. Biol. 10:e1003887. 10.1371/journal.pcbi.1003887 25329398
Cinelli A. R. Ferreyra-Moyano H. Barragan E. (1987). Reciprocal functional connections of the olfactory bulbs and other olfactory related areas with the prefrontal cortex. Brain Res. Bull. 19 651–661. 10.1016/0361-9230(87)90051-7
Citi L. Brown E. N. Barbieri R. (2012). A real-time automated point-process method for the detection and correction of erroneous and ectopic heartbeats. IEEE Trans. Biomed. Eng. 59 2828–2837. 10.1109/TBME.2012.2211356 22875239
Conti L. (1999). Repertorio Delle Scale Di Valutazione In Psichiatria. Florence: SpocietàEditriceEuroea.
Courtiol E. Wilson D. A. (2015). The olfactory thalamus: unanswered questions about the role of the mediodorsal thalamic nucleus in olfaction. Front. Neural Circuits 9:49. 10.3389/fncir.2015.00049 26441548
Deahene S. Naccache L. (2001). Towards a cognitive neuroscience of consciousness: basic evidence and a workspace framework. Cognition 79 1–37. 10.1016/s0010-0277(00)00123-2
Delorme A. Makeig S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods 15 9–21. 10.1016/j.jneumeth.2003.10.009 15102499
Dietrich A. (2003). Functional neuroanatomy of altered states of consciousness: the transient hypofrontality hypothesis. Conscious Cogn. 12 231–256. 10.1016/s1053-8100(02)00046-6
Evans K. C. Dougherty D. D. Schmid A. M. Scannell E. McCallister A. Benson H. et al. (2009). Modulation of spontaneous breathing via limbic/paralimbic-bulbar circuitry: an event-related fMRI study. Neuroimage 47 961–971. 10.1016/j.neuroimage.2009.05.025 19450692
Fontanini A. Bower J. M. (2006). Slow-waves in the olfactory system: an olfactory perspective on cortical rhythms. Trends Neurosci. 29 429–437. 10.1016/j.tins.2006.06.013 16842864
Gallotto S. Sack A. T. Schumann T. de Graaf T. A. (2017). Oscillatory correlates of visual consciousness. Front. Psychol. 8:1147. 10.3389/fpsyg.2017.01147 28736543
Gard T. Taquet M. Dixit R. Hölzel B. K. de Montjoye Y.-A. Brach N. et al. (2014). Fluid intelligence and brain functional organization in aging yoga and meditation practitioners. Front. Aging Neurosci. 6:76. 10.3389/fnagi.2014.00076 24795629
Gerritsen R. J. S. Band G. P. H. (2018). Breath of life: the respiratory vagal stimulation model of contemplative activity. Front. Hum.Neurosci. 12:397. 10.3389/fnhum.2018.00397 30356789
Ghashghaei H. T. Hilgetag C. C. Barbas H. (2007). Sequence of information processing for emotions based on the anatomic dialogue between prefrontal cortex and amygdala. Neuroimage 34 905–923. 10.1016/j.neuroimage.2006.09.046 17126037
Golland Y. Bentin S. Gelbard H. Benjamini Y. Heller R. Nir Y. et al. (2007). Extrinsic and intrinsic systems in the posterior cortex of the human brain revealed during natural sensory stimulation. Cereb. Cortex 17 766–777. 10.1093/cercor/bhk030 16699080
Gross J. Schmitz F. Schnitzler I. Kessler K. Shapiro K. Hommel B. et al. (2004). Modulation of long-range neural synchrony reflects temporal limitations of visual attention in humans. Proc. Natl. Acad. Sci. U.S.A. 101 13050–13055. 10.1073/pnas.0404944101 15328408
He Y. Dagher A. Chen Z. Charil A. Zijdenbos A. Worsley K. et al. (2009). Impaired small-world efficiency in structural cortical networks in multiple sclerosis associated with white matter lesion load. Brain 132 3366–3379. 10.1093/brain/awp089 19439423
Heck D. H. McAfee S. S. Liu Y. Babajani-Feremi A. Rezaie R. Freeman W. J. et al. (2017). Breathing as a fundamental rhythm of brain function. Front. Neural Circuit 10:115. 10.3389/fncir.2016.00115 28127277
Herrero J. L. Khuvis S. Yeagle E. Cerf M. Mehta A. D. (2018). Breathing above the brain stem: volitional control and attentional modulation in humans. J. Neurophysiol. 119 145–159. 10.1152/jn.00551.2017 28954895
Holm S. (1979). A simple sequentially rejective multiple test procedure. Scand. J. Stat. 6 65–70. 10.2307/4615733
Holroyd J. (2003). The science of meditation and the state of hypnosis. Am. J. Clin. Hypn. 46 109–128. 10.1080/00029157.2003.10403582 14609297
Hughes S. W. Crunelli V. (2005). Thalamic mechanisms of EEG alpha rhythms and their pathological implications. Neuroscientist 11 357–372. 10.1177/1073858405277450 16061522
Hyafil A. Giraud A. L. Fontolan L. Gutkin B. (2015). Neural cross-frequency coupling: connecting architectures, mechanisms, and functions. Trends Neurosci. 38 725–740. 10.1016/j.tins.2015.09.001 26549886
Junghofer M. Elbert T. Tucker D. M. Rockstroh B. (2000). Statistical control of artifacts in dense array EEG/MEG studies. Psychophysiology 37 523–532. 10.1111/1469-8986.3740523
Kitney R. I. (1980). “An analysis of the thermoregulatory influences on heart-rate variability,” in The Study of Heart-Rate Variability, eds Kitney R. I. Rompelman O. (New York, NY: Oxford University Press), 81–106.
Knyazev G. G. Slobodskoj-Plusnin J. Y. Bocharov A. V. Pylkova L. V. (2011). The default mode network and EEG alpha oscillations: an independent component analysis. Brain Res. 1402 67–79. 10.1016/j.brainres.2011.05.052 21683942
Lachin J. M. Matts J. P. Wei L. J. (1988). Randomization in clinical trials: conclusions and recommendations. Control. Clin. Trials 9 365–374. 10.1016/0197-2456(88)90049-9
Lee D. J. Kulubya E. Goldin P. Goodarzi A. Girgis F. (2018). Review of the neural oscillations underlying meditation. Front. Neurosci. 12:178. 10.3389/fnins.2018.00178 29662434
Liu Y. Liang M. Zhou Y. He Y. Hao Y. Song M. et al. (2008). Disrupted small-world networks in schizophrenia. Brain 131 945–961. 10.1093/brain/awn018 18299296
Lomas T. Ivtzan I. Fu C. H. (2015). A systematic review of the neurophysiology of mindfulness on EEG oscillations. Neurosci. Biobehav. Rev. 57 401–410. 10.1016/j.neubiorev.2015.09.018 26441373
Lou H. C. Changeux J. P. Rosenstand A. (2017). Towards a cognitive neuroscience of self-awareness. Neurosci. Biobehav. Rev. 83 765–773. 10.1016/j.neubiorev.2016.04.004 27079562
Ludbrook J. Dudley H. (1998). Why permutation tests are superior to t and F tests in biomedical research. Am. Stat. 52 127–132. 10.1080/00031305.1998.10480551
Luppi A. I. Craig M. M. Pappas I. Finoia P. Williams G. B. Allanson J. et al. (2019). Consciousness-specific dynamic interactions of brain integration and functional diversity. Nat. Commun. 10:4616. 10.1038/s41467-019-12658-9 31601811
Marteau T. M. Bekker H. (1992). The development of a six-item short-form of the state scale of the Spielberger State-Trait Anxiety Inventory (STAI). Brit. J. Clin. Psychol. 31 301–306. 10.1111/j.2044-8260.1992.tb00997.x 1393159
Nakatani C. Raffone A. van Leeuween C. (2014). Efficiency of conscious access improves with coupling of slow and fast neural oscillations. J. Cogn. Neurosci. 26 1168–1179. 10.1162/jocn_a_00540
Narayanan J. T. Watts R. Haddad N. Labar D. R. Li M. Filippi C. G. (2002). Cerebral activation during vagus nerve stimulation: a functional MR study. Epilepsia 43 1509–1514. 10.1046/j.1528-1157.2002.16102.x 12460253
Nash J. D. Newberg A. Awasthi B. (2013). Toward a unifying taxonomy and definition for meditation. Front. Psychol. 4:806. 10.3389/fpsyg.2013.00806 24312060
Nash J. D. Newberg A. Awasthi B. (2019). Corrigendum: toward a unifying taxonomy and definition for meditation. Front. Psychol. 10:2206. 10.3389/fpsyg.2019.02206 31636579
Newman M. E. (2004). Analysis of weighted networks. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 70:056131. 10.1103/PhysRevE.70.056131 15600716
Nichols T. E. Holmes A. P. (2001). Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum. Brain Mapp. 15 1–25. 10.1002/hbm.1058 11747097
Northoff G. Huang Z. (2017). How do the brain’s time and space mediate consciousness and its different dimensions? Temporo-spatial theory of consciousness (TTC). Neurosci. Biobehav. Rev. 80 630–645. 10.1016/j.neubiorev.2017.07.013 28760626
Ongur D. Price J. L. (2000). The organization of networks within the orbital and medial prefrontal cortex of rats, monkeys and humans. Cereb. Cortex 10 206–219. 10.1093/cercor/10.3.206 10731217
Onslow A. C. Bogacz R. Jones M. W. (2011). Quantifying phase-amplitude coupling in neuronal network oscillations. Prog. Biophys. Mol. Biol. 105 49–57. 10.1016/j.pbiomolbio.2010.09.007 20869387
Pan J. Tompkins W. J. (1985). A real-time QRS detection algorithm. IEEE Trans. Biomed. Eng. 32 230–236. 10.1109/TBME.1985.325532 3997178
Pekala R. J. (1991). “The phenomenology of consciousness inventory,” in Quantifying Consciousness: An Empirical Approach (Emotions, Personality, and Psychotherapy) (Boston, MA: Springer), 127–143.
Pekala R. J. Baglio F. Cabinio M. Lipari S. Baglio G. Mendozzi L. et al. (2017). Hypnotism as a function of trance state effects, expectancy, and suggestibility: an italian replication. Int. J. Clin. Exp. Hypn. 65 210–240. 10.1080/00207144.2017.1276365 28230463
Perl O. Ravia A. Rubinson M. Eisen A. Soroka T. Mor N. et al. (2019). Human non-olfactory cognition phase-locked with inhalation. Nat. Hum. Behav. 3 501–512. 10.1038/s41562-019-0556-z 31089297
Piarulli A. Zaccaro A. Laurino M. Menicucci D. De Vito A. Bruschini L. et al. (2018). Ultra-slow mechanical stimulation of olfactory epithelium modulates consciousness by slowing cerebral rhythms in humans. Sci. Rep. 8:6581. 10.1038/s41598-018-24924-9 29700421
Pomeranz B. Macaulay R. J. Caudill M. A. Kutz I. Adam D. Gordon D. et al. (1985). Assessment of autonomic function in humans by heart-rates spectral-analysis.Am. J. Physiol. 248 H151–H153. 10.1152/ajpheart.1985.248.1.H151 3970172
Potter H. Nauta W. J. H. (1979). A note on the problem of olfactory associations of the orbitofrontal cortex in the monkey. Neuroscience 4 361–367. 10.1016/0306-4522(79)90099-x
Reyes Del Paso G. A. Langewitz W. Mulder L. J. M. Van Roon A. Duschek S. (2013). 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. Psychophysiology 50 477–487. 10.1111/psyp.12027 23445494
Rubinov M. Sporns O. (2010). Complex network measures of brain connectivity: uses and interpretations. Neuroimage 52 1059–1069. 10.1016/j.neuroimage.2009.10.003 19819337
Sirota A. Montgomery S. Fujisawa S. Isomura Y. Zugaro M. Buzsáki G. (2008). Entrainment of neocortical neurons and gamma oscillations by the hippocampal theta rhythm. Neuron 60 683–697. 10.1016/j.neuron.2008.09.014 19038224
Smith J. C. Abdala A. P. Rybak I. A. Paton J. F. (2009). Structural and functional architecture of respiratory networks in the mammalian brainstem. Philos. T. Roy. Soc. B 364 2577–2587. 10.1098/rstb.2009.0081 19651658
Takahashi H. Shiramatsu T. I. Hitsuyu R. Ibayashi K. Kawai K. (2020). Vagus nerve stimulation (VNS)-induced layer-specific modulation of evoked responses in the sensory cortex of rats. Sci. Rep. 10:8932. 10.1038/s41598-020-65745-z 32488047
Tarvainen M. P. Niskanen J.-P. Lipponen J. A. Ranta-Aho P. O. Karjalainen P. A. (2014). Kubios HRV–heart rate variability analysis software. Comput. Methods Programs Biomed. 113 210–220. 10.1016/j.cmpb.2013.07.024.37
Taylor J. A. Carr D. L. Myers C. W. Eckberg D. L. (1998). Mechanisms underlying very-low-frequency RR-interval oscillations in humans. Circulation 98 547–555. 10.1161/01.cir.98.6.547
Timmermann C. Roseman L. Schartner M. Milliere R. Williams L. T. J. Erritzoe D. et al. (2019). Neural correlates of the DMT experience assessed with multivariate EEG. Sci. Rep. 9:16324. 10.1038/s41598-019-51974-4 31745107
Tononi G. (2004). An information integration theory of consciousness. BMC Neurosci. 5:42. 10.1186/1471-2202-5-42 15522121
Tort A. B. L. Brankačk J. Draguhn A. (2018). Respiration-entrained brain rhythms are global but often overlooked. Trends. Neurosci. 41 186–197. 10.1016/j.tins.2018.01.007 29429805
Tripathi K. K. (2011). Very low frequency oscillations in the power spectra of heart rate variability during dry supine immersion and exposure to non-hypoxic hypobaria. Physiol. Meas. 32 717–729. 10.1088/0967-3334/32/6/008
Uhlhaas P. J. Singer W. (2010). Abnormal neural oscillations and synchrony in schizophrenia. Nat. Rev. Neurosci. 11 100–113. 10.1038/nrn2774 20087360
Uhlhaas P. J. Pipa G. Lima B. Melloni L. Neuenschwander S. Nikolić D. et al. (2009). Neural synchrony in cortical networks: history, concept and current status. Front. Integr. Neurosci. 3:17. 10.3389/neuro.07.017.2009 19668703
Vaitl D. Birbaumer N. Gruzelier J. Jamieson G. A. Kotchoubey B. Kübler A. et al. (2005). Psychobiology of altered states of consciousness. Psychol. Bull. 131 98–127. 10.1037/0033-2909.131.1.98 15631555
Varela F. Lachaux J. P. Rodriguez E. Martinerie J. (2001). The brainweb: phase synchronization and large-scale integration. Nat. Rev. Neurosci. 4 229–239. 10.1038/35067550 11283746
Varga S. Heck D. H. (2017). Rhythms of the body, rhythms of the brain: respiration, neural oscillations, and embodied cognition. Conscious. Cogn. 56 77–90. 10.1016/j.concog.2017.09.008 29073509
Vinck M. Oostenveld R. van Wingerden M. Battaglia F. Pennartz C. M. (2011). An improved index of phase-synchronization for electrophysiological data in the presence of volume-conduction, noise and sample-size bias. Neuroimage 55 1548–1565. 10.1016/j.neuroimage.2011.01.055 21276857
World Medical Association (2013). World Medical Association Declaration of Helsinki: ethical principles for medical research involving human subjects. JAMA 310 2191–2194. 10.1001/jama.2013.281053 24141714
Xia M. Wang J. He Y. (2013). BrainNet Viewer: a network visualization tool for human brain connectomics. PLoS One 8:e68910. 10.1371/journal.pone.0068910 23861951
Ye M. Yang T. Qing P. Lei X. Qiu J. Liu G. (2015). Changes of functional brain networks in major depressive disorder: a graph theoretical analysis of resting-state fMRI. PLoS One 10:e0133775. 10.1371/journal.pone.0133775 26327292
Zaccaro A. Piarulli A. Laurino M. Garbella E. Menicucci D. Neri B. et al. (2018). How breath-control can change your life: a systematic review on psycho-physiological correlates of slow breathing. Front. Hum. Neurosci. 12:353. 10.3389/fnhum.2018.00353 30245619
Zelano C. Jiang H. Zhou G. Arora N. Schuele S. Rosenow J. et al. (2016). Nasal respiration entrains human limbic oscillations and modulates cognitive function. J. Neurosci. 36 12448–12467. 10.1523/JNEUROSCI.2586-16.2016 27927961