Prefrontal hemodynamic after-effects caused by rebreathing may predict affective states – A multimodal functional near-infrared spectroscopy study
Brain activity has been shown to be influenced by respiratory behavior. Here, we evaluated whether respiration-induced hypo- or hypercapnia may support differentiation between physiological versus pathological respiratory behavior. In particular, we investigated whether systemic physiological measures could predict the brain’s time-frequency hemodynamics after three respiratory challenges (i.e., breath-holding, rebreathing, and hyperventilation) compared to resting-state. Prefrontal hemodynamics were assessed in healthy subjects (N = 27) using functional near-infrared spectroscopy (fNIRS). Systemic physiological measures were assessed in form of heart rate, partial end-tidal carbon dioxide, respiration rate, and saturation of peripheral oxygen. Time-frequency dynamics were quantified using the wavelet transform coherence (i.e., defined here as cortical-systemic coherence). We found that the three respiratory challenges modulated cortical-systemic coherence differently: (1) After rebreathing, cortical-systemic coherence could be predicted from the amplitude of the heart rate (strong negative correlation). (2) After breath-holding, the same observation was made (moderate negative correlation). (3) After hyperventilation, no significant effect was observed. (4) These effects were found only in the frequency range of very low-frequency oscillations. The presented findings highlight a distinct role of rebreathing in predicting cortical-systemic coupling based on heart rate changes, which may represents a measure of affective states in the brain. The applied multimodal assessment of hemodynamic and systemic physiological measures during respiratory challenges may therefore have potential applications in the differentiation between physiological and pathological respiratory behavior.
KeywordsRespiratory challenge Time-frequency dynamics Cortical-systemic coherence Functional near-infrared spectroscopy Heart rate Partial pressure of carbon dioxide
Compliance with ethical standards
This work was funded by the academic career program Filling the Gap (Grant number FTG-1415-007), University of Zurich.
Conflict of Interest
Author LH declares that she has no conflict of interest. Author FS declares that he has no conflict of interest. Author ES declares that he has no conflict of interest.
All procedures performed in studies involving human participants were in accordance with the ethical standards of the ethics committee of the Canton Zurich and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.
Informed consent was obtained from all individual participants included in the study.
- Birn, R. M., Murphy, K., Handwerker, D. A., & Bandettini, P. A. (2009). fMRI in the presence of task-correlated breathing variations. Brain Body Med, 47, 1092–1104.Google Scholar
- Funane, T., Atsumori, H., Katura, T., Obata, A. N., Sato, H., Tanikawa, Y., Okada, E., & Kiguchi, M. (2014). Quantitative evaluation of deep and shallow tissue layers’ contribution to fNIRS signal using multi-distance optodes and independent component analysis. Neuroimage, 85, 150–165.Google Scholar
- Gagnon, L., Yücel, M. A., Dehaes, M., Cooper, R. J., Perdue, K. L., Selb, J., Huppert, T. J., Hoge, R. D., & Boas, D. A. (2012). Quantification of the cortical contribution to the NIRS signal over the motor cortex using concurrent NIRS-fMRI measurements. NeuroImage, 59, 3933–3940.CrossRefPubMedGoogle Scholar
- Golestani, A. M., Chang, C., Kwinta, J. B., Khatamian, Y. B., & Jean Chen, J. (2015). Mapping the end-tidal CO2 response function in the resting-state BOLD fMRI signal: spatial specificity, test–retest reliability and effect of fMRI sampling rate. NeuroImage, 104, 266–277.CrossRefPubMedGoogle Scholar
- Holper L, Scholkmann F, Seifritz E (2015). Time-frequency dynamics of the sum of intra- and extracerebral hemodynamic functional connectivity during resting-state and respiratory challenges assessed by multimodal functional near-infrared spectroscopy. NeuroImage, 120, 481–492.Google Scholar
- Keller, C. J., Bickel, S., Honey, C. J., Groppe, D. M., Entz, L., Craddock, R. C., Lado, F. A., Kelly, C., Milham, M., & Mehta, A. D. (2013). Neurophysiological investigation of spontaneous correlated and anticorrelated fluctuations of the BOLD signal. The Journal of Neuroscience, 33, 6333–6342.CrossRefPubMedPubMedCentralGoogle Scholar
- Kim, D.-K., Rhee, J.-H., & Kang, S. W. (2013b). Reorganization of the brain and heart rhythm during autogenic meditation. Frontiers in Integrative Neuroscience, 7, 109.Google Scholar
- Kiviniemi V, Remes J, Starck T, Nikkinen J, Haapea M, Silven O, Tervonen O (2009): Mapping Transient Hyperventilation Induced Alterations with Estimates of the Multi-Scale Dynamics of BOLD Signal. Front Neuroinformatics 3.Google Scholar
- Kox, M., van Eijk, L. T., Zwaag, J., van den Wildenberg, J., Sweep, F. C. G. J., van der Hoeven, J. G., & Pickkers, P. (2014). Voluntary activation of the sympathetic nervous system and attenuation of the innate immune response in humans. Proceedings of the National Academy of Sciences, 111, 7379–7384.CrossRefGoogle Scholar
- Nardi, A. E., Valença, A. M., Lopes, F. L., Nascimento, I., Mezzasalma, M. A., & Zin, W. A. (2004). Clinical features of panic patients sensitive to hyperventilation or breath-holding methods for inducing panic attacks. Brazilian Journal of Medical and Biological Research, 37, 251–257.CrossRefPubMedGoogle Scholar
- Nardi, A. E., Valença, A. M., Mezzasalma, M. A., Levy, S. P., Lopes, F. L., Nascimento, I., Freire, R. C., Veras, A. B., & Zin, W. A. (2006). Comparison between hyperventilation and breath-holding in panic disorder: patients responsive and non-responsive to both tests. Psychiatry Research, 142, 201–208.CrossRefPubMedGoogle Scholar
- Roth WT, Wilhelm FH, Trabert W (1998): Voluntary Breath Holding in Panic and Generalized Anxiety Disorders. Psychosomatic Medicine, 60, 671–679.Google Scholar
- Scholkmann, F., Wolf, M., & Wolf, U. (2013b). The effect of inner speech on arterial CO2, cerebral hemodynamics and oxygenation - A functional NIRS study. advances in experimental medicine and biology. Advances in Experimental Medicine and Biology, 789, 81–87.Google Scholar
- Scholkmann, F., Kleiser, S., Metz, A. J., Zimmermann, R., Mata Pavia, J., Wolf, U., & Wolf, M. (2014a). A review on continuous wave functional near-infrared spectroscopy and imaging instrumentation and methodology. NeuroImage, 85, 6–27. Google Scholar
- Soladoye A, Owoyele B, Olatunji L, Adelusi S (2003): Cardiovascular responses to breath-holding with or without face immersion in young adults. Bioscience Research Communications, 15, 59–63.Google Scholar
- Tachtsidis, I., Leung, T., Tisdall, M., Devendra, P., Smith, M., Delpy, D., & Elwell, C. (2008b). Investigation of frontal cortex, motor cortex and systemic haemodynamic changes during anagram solving. Advances in Experimental Medicine and Biology, 614, 21–28.Google Scholar
- Tachtsidis, I., Leung, T., Chopra, A., Koh, P., Reid, C., & Elwell, C. (2009b). False positives In functional nearinfrared topography. Advances in Experimental Medicine and Biology, 645, 307–314.Google Scholar
- Takahashi, T., Takikawa, Y., Kawagoe, R., Shibuya, S., Iwano, T., & Kitazawa, S. (2011). Influence of skin blood flow on near-infrared spectroscopy signals measured on the forehead during a verbal fluency task. NeuroImage, 57, 991–1002.Google Scholar
- Thomas, S. A., Friedmann, E., Wimbush, F., & Schron, E. (1997). Psychological factors and survival in the cardiac arrhythmia suppression trial (CAST): a reexamination. American Journal of Critical Care, 6, 116–126.Google Scholar
- Tong, Y., Hocke, L. M., Fan, X., Janes, A., & Frederick, B. (2015). Can apparent resting state connectivity arise from systemic fluctuations? Frontiers in Human Neuroscience, 9.Google Scholar
- Trajkovic I, Scholkmann F, Wolf M (2011): Estimating and validating the interbeat intervals of the heart using near-infrared spectroscopy on the human forehead. Journal of Biomedical Optics, 16, 087002. Google Scholar
- Woods, S., Charney, D., Loke, J., Goodman, W., Redmond, D., & Heninger, G. (1986). Carbon dioxide sensitivity in panic anxiety: ventilatory and anxiogenic response to carbon dioxide in healthy subjects and patients with panic anxiety before and after alprazolam treatment. Archives of General Psychiatry, 43, 900–909.CrossRefPubMedGoogle Scholar
- Xu Y, Graber H, Barbour R (2014): nirsLAB: A Computing Environment for fNIRS Neuroimaging Data Analysis. Biomedical Optics 2014, OSA Technical Digest (online) (Optical Society of America, 2014), paper BM3A.1Google Scholar
- Zhao, H., Tanikawa, Y., Gao, F., Onodera, Y., Sassaroli, A., Tanaka, K., & Yamada, Y. (2002). Maps of optical differential pathlength factor of human adult forehead, somatosensory motor and occipital regions at multi-wavelengths in NIR. Physics in Medicine and Biology, 47, 2075–2093.CrossRefPubMedGoogle Scholar