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Respiration pattern variability and related default mode network connectivity are altered in remitted depression

Published online by Cambridge University Press:  16 January 2018

Vera Eva Zamoscik*
Affiliation:
Department of Clinical Psychology, Central Institute of Mental Health, Mannheim, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
Stephanie Nicole Lyn Schmidt
Affiliation:
Department of Clinical Psychology, Central Institute of Mental Health, Mannheim, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
Martin Fungisai Gerchen
Affiliation:
Department of Clinical Psychology, Central Institute of Mental Health, Mannheim, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany Bernstein Center for Computational Neuroscience Heidelberg/Mannheim, Mannheim, Germany
Christos Samsouris
Affiliation:
Department of Clinical Psychology, Central Institute of Mental Health, Mannheim, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany University of Amsterdam, Amsterdam, The Netherlands
Christina Timm
Affiliation:
Research Group Longitudinal and Intervention Research, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
Christine Kuehner
Affiliation:
Research Group Longitudinal and Intervention Research, Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Mannheim, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
Peter Kirsch
Affiliation:
Department of Clinical Psychology, Central Institute of Mental Health, Mannheim, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany Bernstein Center for Computational Neuroscience Heidelberg/Mannheim, Mannheim, Germany
*
Author for correspondence: Vera Eva Zamoscik, E-mail: [email protected]

Abstract

Background

Studies with healthy participants and patients with respiratory diseases suggest a relation between respiration and mood. The aim of the present analyses was to investigate whether emotionally challenged remitted depressed participants show higher respiration pattern variability (RPV) and whether this is related to mood, clinical outcome and increased default mode network connectivity.

Methods

To challenge participants, sad mood was induced with keywords of personal negative life events in individuals with remitted depression [recurrent major depressive disorder (rMDD), n = 30] and matched healthy controls (HCs, n = 30) during functional magnetic resonance imaging. Respiration was measured by means of a built-in respiration belt. Additionally, questionnaires, a daily life assessment of mood and a 3 years follow-up were applied. For replication, we analysed RPV in an independent sample of 53 rMDD who underwent the same fMRI paradigm.

Results

During sad mood, rMDD compared with HC showed greater RPV, with higher variability in pause duration and respiration frequency and lower expiration to inspiration ratio. Higher RPV was related to lower daily life mood and predicted higher depression scores as well as relapses during a 3-year follow-up period. Furthermore, in rMDD compared with HC higher main respiration frequency exhibited a more positive association with connectivity of the posterior cingulate cortex and the right parahippocampal gyrus.

Conclusions

The results suggest a relation between RPV, mood and depression on the behavioural and neural level. Based on our findings, we propose interventions focusing on respiration to be a promising additional tool in the treatment of depression.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2018 

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References

Ali, S, Stone, MA, Peters, JL, Davies, MJ and Khunti, K (2006) The prevalence of co-morbid depression in adults with type 2 diabetes: a systematic review and meta-analysis. Diabetic Medicine 23, 11651173.Google Scholar
Asnaashari, AM, Talaei, A and Haghigh, B (2012) Evaluation of psychological status in patients with asthma and COPD. Iranian Journal of Allergy, Asthma, and Immunology 11, 6571.Google Scholar
Beck, AT, Steer, RA and Brown, GK (1996) Manual for the Beck Depression Inventory-II. San Antonio: The Psychological Corporation.Google Scholar
Berman, MG, Peltier, S, Nee, DE, Kross, E, Deldin, PJ and Jonides, J (2011) Depression, rumination and the default network. Social Cognitive and Affective Neuroscience 6, 548555.Google Scholar
Birn, RM (2012) The role of physiological noise in resting-state functional connectivity. NeuroImage 62, 864870.Google Scholar
Birn, RM, Diamond, JB, Smith, MA and Bandettini, PA (2006) Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI. NeuroImage 31, 15361548.Google Scholar
Brannan, S, Liotti, M, Egan, G, Shade, R, Madden, L, Robillard, R et al. (2001) Neuroimaging of cerebral activations and deactivations associated with hypercapnia and hunger for air. Proceedings of the National Academy of Sciences USA 98, 20292034.Google Scholar
Brown, S, Martinez, MJ and Parsons, LM (2004) Passive music listening spontaneously engages limbic and paralimbic systems. Neuroreport 15, 20332037.Google Scholar
Catterall, JR, Douglas, NJ, Calverley, PM, Brash, HM, Brezinova, V, Shapiro, CM et al. (1982) Irregular breathing and hypoxaemia during sleep in chronic stable asthma. Lancet 1, 301304.Google Scholar
Chang, C, Cunningham, JP and Glover, GH (2009) Influence of heart rate on the BOLD signal: the cardiac response function. NeuroImage 44, 857869.Google Scholar
Chang, C, Metzger, CD, Glover, GH, Duyn, JH, Heinze, HJ and Walter, M (2013) Association between heart rate variability and fluctuations in resting-state functional connectivity. NeuroImage 68, 93104.Google Scholar
Evans, KC, Banzett, RB, Adams, L, Mckay, L, Frackowiak, RS and Corfield, DR (2002) BOLD fMRI identifies limbic, paralimbic, and cerebellar activation during air hunger. Journal of Neurophysiology 88, 15001511.Google Scholar
Fan, VS and Meek, PM (2014) Anxiety, depression, and cognitive impairment in patients with chronic respiratory disease. Clinics in Chest Medicine 35, 399409.Google Scholar
Faul, F, Erdfelder, E, Lang, AG and Buchner, A (2007) G*Power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods 39, 175191.Google Scholar
Figueroa, CA, Ruhe, HG, Koeter, MW, Spinhoven, P, Van Der Does, W, Bockting, CL et al. (2015) Cognitive reactivity versus dysfunctional cognitions and the prediction of relapse in recurrent major depressive disorder. Journal of Clinical Psychiatry 76, e1306e1312.Google Scholar
Greicius, M (2008) Resting-state functional connectivity in neuropsychiatric disorders. Current Opinion in Neurology 21, 424430.Google Scholar
Hamilton, JL and Alloy, LB (2016) Atypical reactivity of heart rate variability to stress and depression across development: systematic review of the literature and directions for future research. Clinical Psychology Review 50, 6779.Google Scholar
Huffziger, S, Ebner-Priemer, U, Zamoscik, V, Reinhard, I, Kirsch, P and Kuehner, C (2013) Effects of mood and rumination on cortisol levels in daily life: an ambulatory assessment study in remitted depressed patients and healthy controls. Psychoneuroendocrinology 38, 22582267.Google Scholar
Jaccard, J and Turrisi, R (2003) Interaction Effects in Multiple Regression. Thousand oaks, USA: Sage.Google Scholar
Kaiser, RH, Andrews-Hanna, JR, Wager, TD and Pizzagalli, DA (2015) Large-scale network dysfunction in major depressive disorder: a meta-analysis of resting-state functional connectivity. JAMA Psychiatry 72, 603611.Google Scholar
Karnath, HO, Baier, B and Nagele, T (2005) Awareness of the functioning of one's own limbs mediated by the insular cortex? Journal of Neuroscience 25, 71347138.Google Scholar
Kemp, AH, Quintana, DS, Gray, MA, Felmingham, KL, Brown, K and Gatt, JM (2010) Impact of depression and antidepressant treatment on heart rate variability: a review and meta-analysis. Biological Psychiatry 67, 10671074.Google Scholar
Klintworth, A, Ajtay, Z, Paljunite, A, Szabados, S and Hejjel, L (2012) Heart rate asymmetry follows the inspiration/expiration ratio in healthy volunteers. Physiological Measurement 33, 17171731.Google Scholar
Kovacs, M, Yaroslavsky, I, Rottenberg, J, George, CJ, Kiss, E, Halas, K et al. (2016) Maladaptive mood repair, atypical respiratory sinus arrhythmia, and risk of a recurrent major depressive episode among adolescents with prior major depression. Psychological Medicine 46, 21092119.Google Scholar
Kunik, ME, Roundy, K, Veazey, C, Souchek, J, Richardson, P, Wray, NP et al. (2005) Surprisingly high prevalence of anxiety and depression in chronic breathing disorders. Chest 127, 12051211.Google Scholar
Marrelec, G, Messe, A, Giron, A and Rudrauf, D (2016) Functional connectivity's degenerate view of brain computation. PLoS Computational Biology 12, e1005031.Google Scholar
Masaoka, Y, Sugiyama, H, Katayama, A, Kashiwagi, M and Homma, I (2012) Remembering the past with slow breathing associated with activity in the parahippocampus and amygdala. Neuroscience Letters 521, 98103.Google Scholar
Montgomery, SA and Asberg, M (1979) A new depression scale designed to be sensitive to change. British Journal of Psychiatry 134, 382389.Google Scholar
Morosini, PL, Magliano, L, Brambilla, L, Ugolini, S and Pioli, R (2000) Development, reliability and acceptability of a new version of the DSM-IV Social and Occupational Functioning Assessment Scale (SOFAS) to assess routine social functioning. Acta Psychiatrica Scandinavica 101, 323329.Google Scholar
O'donnell, DE, Guenette, JA, Maltais, F and Webb, KA (2012) Decline of resting inspiratory capacity in COPD: the impact on breathing pattern, dyspnea, and ventilatory capacity during exercise. Chest 141, 753762.Google Scholar
Patel, AX, Kundu, P, Rubinov, M, Jones, PS, Vertes, PE, Ersche, KD, Suckling, J and Bullmore, ET (2014) A wavelet method for modeling and despiking motion artifacts from resting-state fmri time series. Neuroimage 95, 287304.Google Scholar
Peiffer, C, Costes, N, Herve, P and Garcia-Larrea, L (2008) Relief of dyspnea involves a characteristic brain activation and a specific quality of sensation. American Journal of Respiratory and Critical Care Medicine 177, 440449.Google Scholar
Rainville, P, Bechara, A, Naqvi, N and Damasio, AR (2006) Basic emotions are associated with distinct patterns of cardiorespiratory activity. International Journal of Psychophysiology 61, 518.Google Scholar
Renner, F, Siep, N, Arntz, A, Van De Ven, V, Peeters, FP, Quaedflieg, CW et al. (2017) Negative mood-induction modulates default mode network resting-state functional connectivity in chronic depression. Journal of Affective Disorders 208, 590596.Google Scholar
Spijkerman, T, De Jonge, P, Van Den Brink, RH, Jansen, JH, May, JF, Crijns, HJ et al. (2005) Depression following myocardial infarction: first-ever versus ongoing and recurrent episodes. General Hospital Psychiatry 27, 411417.Google Scholar
Stoeckel, MC, Esser, RW, Gamer, M, Buchel, C and Von Leupoldt, A (2016) Brain responses during the anticipation of dyspnea. Neural Plasticity 2016, 6434987.Google Scholar
Strauss-Blasche, G, Moser, M, Voica, M, Mcleod, DR, Klammer, N and Marktl, W (2000) Relative timing of inspiration and expiration affects respiratory sinus arrhythmia. Clinical and Experimental Pharmacology and Physiology 27, 601606.Google Scholar
Strik, C, Klose, U, Erb, M, Strik, H and Grodd, W (2002) Intracranial oscillations of cerebrospinal fluid and blood flows: analysis with magnetic resonance imaging. Journal of Magnetic Resonance Imaging 15, 251258.Google Scholar
Trull, TJ and Ebner-Priemer, UW (2013) Ambulatory assessment. Annual Review of Clinical Psychology 9, 4.14.27.Google Scholar
Tsakiris, M, Hesse, MD, Boy, C, Haggard, P and Fink, GR (2007) Neural signatures of body ownership: a sensory network for bodily self-consciousness. Cerebral Cortex 17, 22352244.Google Scholar
Van Buuren, M, Gladwin, TE, Zandbelt, BB, Van Den Heuvel, M, Ramsey, NF, Kahn, RS et al. (2009) Cardiorespiratory effects on default-mode network activity as measured with fMRI. Human Brain Mapping 30, 30313042.Google Scholar
Vlemincx, E, Van Diest, I and Van Den Bergh, O (2015) Emotion, sighing, and respiratory variability. Psychophysiology 52, 657666.Google Scholar
Vlemincx, E, Vigo, D, Vansteenwegen, D, Van Den Bergh, O and Van Diest, I (2013) Do not worry, be mindful: effects of induced worry and mindfulness on respiratory variability in a nonanxious population. International Journal of Psychophysiology 87, 147151.Google Scholar
Watson, D, Clark, LA and Tellegen, A (1988) Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of Personality and Social Psychology 54, 10631070.Google Scholar
Wilhelm, P and Schoebi, D (2007) Assessing mood in daily life: structural validity, sensitivity to change, and reliability of a short-scale to measure three basic dimensions of mood. Psychological Assessment 23, 258267.Google Scholar
Wittchen, HU, Wunderlich, U, Gruschwitz, S and Zaudig, M (1997) SCID: Structured Clinical Interview for DSM-IV Axis I Disorders. Goettingen: Hogrefe.Google Scholar
Woodward, ND and Cascio, CJ (2015) Resting-state functional connectivity in psychiatric disorders. JAMA Psychiatry 72, 743744.Google Scholar
Yackle, K, Schwarz, LA, Kam, K, Sorokin, JM, Huguenard, JR, Feldman, JL et al. (2017) Breathing control center neurons that promote arousal in mice. Science 355, 14111415.Google Scholar
Yamada, S, Miyazaki, M, Yamashita, Y, Ouyang, C, Yui, M, Nakahashi, M et al. (2013) Influence of respiration on cerebrospinal fluid movement using magnetic resonance spin labeling. Fluids Barriers CNS 10, 36.Google Scholar
Yildiz, S, Thyagaraj, S, Jin, N, Zhong, X, Heidari Pahlavian, S, Martin, BA et al. (2017) Quantifying the influence of respiration and cardiac pulsations on cerebrospinal fluid dynamics using real-time phase-contrast MRI. Journal of Magnetic Resonance Imaging 46, 431439.Google Scholar
Zamoscik, V, Huffziger, S, Ebner-Priemer, U, Kuehner, C and Kirsch, P (2014) Increased involvement of the parahippocampal gyri in a sad mood predicts future depressive symptoms. Social Cognitive and Affective Neuroscience 9, 20342040.Google Scholar
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