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ORIGINAL ARTICLES |
From the Department of Psychiatry Robert Wood Johnson Medical School (P.M.L., R.E., Y.L.), Piscataway, New Jersey; UMDNJNew Jersey Medical School, Department of Neurosciences, Newark, New Jersey (E.V., B.V.); UMDNJSchool of Public Health, Division of Biometrics (S-E.L., W.J.S.); Medical College of Virginia at Virginia Commonwealth University (D.L.E.), Richmond, Virginia; Department of Physics, University of Turku (T.A.K.), Turku, Finland; Department of Clinical Physiology, Kuopio University Hospital (K.U.O.T.), Kuopio, Finland; and Department of Psychiatry University of North Carolina, School of Medicine, Chapel Hill, North Carolina (R.M.H.).
Address reprint requests to: Paul Lehrer, Ph.D., Department of Psychiatry, Robert Wood Johnson Medical School, 671 Hoes Lane, Piscataway, NJ 08854, USA. Email: lehrer{at}umdnj.edu
| ABSTRACT |
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METHODS: We compared 10 sessions of biofeedback training with an uninstructed control. Cognitive and physiological effects were measured in four of the sessions.
RESULTS: We found acute increases in low-frequency and total spectrum heart rate variability, and in vagal baroreflex gain, correlated with slow breathing during biofeedback periods. Increased baseline baroreflex gain also occurred across sessions in the biofeedback group, independent of respiratory changes, and peak expiratory flow increased in this group, independently of cardiovascular changes. Biofeedback was accompanied by fewer adverse relaxation side effects than the control condition.
CONCLUSIONS: Heart rate variability biofeedback had strong long-term influences on resting baroreflex gain and pulmonary function. It should be examined as a method for treating cardiovascular and pulmonary diseases. Also, this study demonstrates neuroplasticity of the baroreflex.
Key Words: biofeedback, heart rate variability, baroreflex, pulmonary function, neuroplasticity.
Abbreviations: BP = blood pressure;; HF = high frequency;; HR = heart rate;; HRV = heart rate variability;; LF = low frequency;; RSA = respiratory sinus arrhythmia.
| INTRODUCTION |
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Arterial baroreflex responses, triggered by stretch receptors in the walls of the aortic arch and carotid artery, modulate vagus nerve traffic to the sinoatrial node, and mediate beat-by-beat HR responses to changing arterial pressures (4). Risk for cardiac events (including sudden death) in patients with heart disease is inversely related to the robustness of their baroreflex responses. La Rovere et al. (5) showed that in patients recovering from myocardial infarction, those with subnormal vagal baroreflex gains have a high risk of fatal cardiac events, especially if the patient also has low HRV. The linkage between vagal baroreflex impairment and mortality may partially reflect patients autonomic responses to cardiac rhythm changes. Ventricular tachycardia, a rapid rhythm that commonly precedes sudden death (6), precipitously lowers arterial pressure, and increases muscle-sympathetic (7) and reduces vagal-cardiac (8) nerve activity. During ventricular tachycardia, arterial perfusion pressures recover more rapidly in patients with stronger than weaker vagal and sympathetic baroreflexes (9). In an exercise/ischemia dog model of sudden cardiac death, ventricular fibrillation occurs when baroreflexes are weak, but does not occur when they are strong (10).
Vagal mechanisms also figure importantly in asthma, because the parasympathetic nervous system plays a major role in modulating airway smooth muscle tone (11). Just as increased baroreflex responsiveness may promote successful responses to abrupt rhythm disturbances in cardiac patients, increased vagal activity can cause bronchoconstriction in asthma, and asthma exacerbations can be associated with cholinergic hyperreactivity (12). The therapeutic effects of HRV biofeedback may be through influencing the bodys modulatory processes (eg, the well-known modulation of BP changes by baroreflex activity), through which vagal as well as sympathetic reflexes may be controlled.
The levels of baroreflex gain and vagal bronchoconstriction both vary over time, influenced by various neurobehavioral factors. The earliest quantitative analysis of human baroreflex function (13) documented elevated baroreflex gain during sleep. Fritsch et al. (14) reported that changes of arterial pressure lasting only seconds reset the relation between arterial pressure and vagal and sympathetic neural outflows. Systematic changes in pulmonary function also occur during behavioral laboratory tasks (12) and relaxation (15).
When people try to maximize their respiratory sinus arrhythmia (the vagally mediated HR speeding and slowing that occurs in synchrony with breathing), they spontaneously slow their breathing rates to
0.1 Hz, about one breath every 10 seconds (16). There are previous reports that slow or deep breathing may acutely increase baroreflex gain in healthy people (17) and can even counteract the bronchoconstrictive effects of inhaled methacholine (18). A controlled trial of slow breathing in the context of yoga documented acute reductions of airway resistance among people with asthma (19). Thus, vagal cardiac and pulmonary mechanisms are linked, and there are reasons to expect that improvements in one vagal limb might spill over into the other.
| BIOFEEDBACK AND RESONANT FREQUENCY IN HRV |
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0.1 Hz (6 cycles/min). At this frequency, we previously found that HR and BP oscillate 180° out of phase (20), while HR and respiration oscillate in phase with each other (0° phase relationship, with inhalation coinciding with HR accelerations and exhalation with decelerations). Thus, when people breathe at their resonant frequency, respiratory effects on HRV stimulate baroreflex effects (ie, as the individual inhales, HR rises, BP falls, and the consequent baroreflex response produces a further increase in HR, with corresponding effects during exhalation). The consequent resonance effects produce very large increases in both HRV and baroreflex gain, which can be obtained only when subjects try to increase HRV at this particular frequency (20). | METHOD |
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Instrumentation and Software
Physiological data were recorded on a J&J Engineering (Poulsbo, WA) I-330 DSP physiograph unit. EKG data were collected from sensors on the right arm and left leg (Lead II), digitized at the rate of 512 samples/s. Beat-to-beat BP was recorded from a Finapres unit (Ohmeda model 223), and digitized at a rate of 256 samples/s. The sensor was placed on the participants left middle finger, and the hand was elevated on a table to approximately the level of the heart. End-tidal CO2 was taken from a Datex 223 capnometer. The intake tube was inserted into a mouthpiece, and subjects wore nose clips and breathed through the mouth during the 5-minute testing periods. A pneumotachometer was used to record respiratory patterns from which measurements of respiratory rate and tidal volume were derived. During biofeedback sessions, strain gauges around the chest and abdomen were also used to display respiratory activity for training purposes. Spirometry was done before and after each testing session following procedures recommended by the American Thoracic Society (21) using a Koko pneumotach-based spirometer (PDS Instrumentation, Louisville, CO), calibrated daily with a 3-liter syringe.
HR and BP data were edited, and analyzed using the WinCPRS program (Absolute Aliens Oy, Turku, Finland), a program for general analysis of physiological data, including analysis of HR and BP variability and baroreflex gain. Spectral baroreflex gain in the LF range correlates closely with baroreflex gain assessed directly by using phenylephrine injection to alter BP and trigger baroreflex responses BP (22). In cats, baroreceptor denervation abolishes the coherence between systolic pressure and R-R interval oscillations in this frequency range (23). We estimated baroreflex gain over coherent LF (0.040.15 Hz) segments from the squared coherence between pairs of measurements. In this procedure, the squared cross-spectral densities of systolic pressure and R-R intervals are divided by the product of the individual power densities. The transfer function was calculated as the cross-spectral densities divided by the power spectral densities of the systolic pressure. The modulus of the transfer function was used to estimate baroreflex gain (10, 24).
Participants also completed two self-report inventories about their experiences during the testing sessions: 1) the Relaxation Inventory (25), a factor-analytically derived scale that yields a full scale score and three dimensions of the relaxation experience, experience of physical tension, cognitive tension, and subjective assessment of relaxation; and 2) the Side Effects of Relaxation Scale (26), which assesses common adverse experiences of people undergoing various kinds of relaxation training.
Procedure for HRV Biofeedback
The details of the procedure for HRV biofeedback have been described elsewhere (27). The trainee was first taught to breathe at his/her resonant frequency, ie, the frequency at which maximum amplitudes of HRV could be generated voluntarily for each individual. The resonant frequency was determined in the first session by measuring HR oscillation amplitudes while the individual breathed for intervals of 2 minutes at each of the following frequencies: 4.5, 5, 5.5, 6, and 6.5 breaths/min. We provide a "pacing stimulus" for this purpose: a light display that moved up and down on the computer screen at the target respiratory rate. The trainee was instructed to breathe at the rate of that stimulus. The resonant frequency was determined as the respiratory frequency yielding the highest frequency power peak on a moving Fourier analysis of HR data displayed by the I-330 physiograph. Subjects were instructed to practice breathing at the resonant frequency for 20-minute periods twice daily for the next week. Throughout training, the individual was cautioned to breathe shallowly and naturally, in order to avoid hyperventilation, as can be provoked by this technique (16). Participants also were trained to breathe abdominally and to exhale through pursed lips.
At the next session, the participant was given HRV biofeedback in two forms: 1) A beat-to-beat cardiotachometer display superimposed on respiratory activity taken from the strain gauges. The participant was instructed to breathe approximately in phase with HR changes, with the goal of maximally increasing amplitude of RSA; 2) A moving frequency analysis of HR within the band of 0.0050.4 Hz, updated approximately every second, reflecting the frequency of HR oscillations within the past 30 seconds. The participant was instructed to increase the spectral power peak that occurred at approximately resonant frequency. In the third session, a stand-alone analog HRV biofeedback device was provided for home practice (Cardiosignalizer KC-3, Biosvyaz Corp., St. Petersburg, Russia), which provided a light-bar display whose height was proportional to amplitude of RSA. The upper and lower limits of the display could be adjusted in order to help shape the participants response. Participants home practice now was assisted by the machine.
| RESULTS |
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We found a significant pattern of differences in baroreflex gain and HRV between the biofeedback and the control groups across sessions, although mean R-R intervals and systolic pressures were similar (Figs. 35![]()
; Table 2). During each session, baroreflex gain was significantly (p < .0001) higher during the two 5-minute biofeedback periods (Table 3
) than during the two rest periods. Total R-R interval spectral power also was significantly (p < .0001) greater during biofeedback than during rest conditions, as was LF spectral power for both BP and R-R interval. Baroreflex gain and R-R interval spectral power did not change in the control group. Because subjects tended to breathe in the LF range, HF variability in RR-interval decreased during biofeedback tasks. The increase in baroreflex gain indicates that the increase in LF R-R variability was greater than that in LF systolic BP variability.
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Respiration rate slowed during biofeedback training periods to approximately six breaths/min (median = 0.1 Hz, mean = 0.092 Hz), and tidal volume increased. However, there were no significant between session differences in either measure at baseline (Task A). In order to determine whether changes in baroreflex gain were explained by changed respiratory patterns, we included tidal volume and respiration rate as factors in the mixed models analysis of baroreflex gain. The immediate effects of biofeedback (ie, the comparison between rest periods [Tasks A and D] and biofeedback periods [Tasks B and C]) were erased by this procedure, but the long-term baseline effects (Task A in Session 1 vs. Task A in Session 10) were not influenced by respiratory patterns (Table 3
). End-tidal CO2 was not affected by the experimental procedures.
Although pulmonary function was normal in all participants, significant (p < .0001) increases in peak expiratory flow occurred between the first and last treatment sessions in the biofeedback group (respectively, 95.3 ± 18.5 and 109.6 ± 16.2%), but no changes in the control group and no correlation between baroreflex and pulmonary effects in either group.
We found no significant between-group differences in the Relaxation Inventory, but, across sessions, subjects in the biofeedback condition reported significantly fewer negative side effects of relaxation training than subjects in the waiting list condition in Sessions 4, 7, and 10, but not in Session 1 (Table 4), indicating that regular training and/or practice of biofeedback tended to block some of the negative side effects of relaxation that might occur when people are instructed to relax without special training in how to do it.
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| DISCUSSION |
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The acute baroreflex effects are consistent with our hypothesis that stimulation of HRV at its resonant frequency by respiratory activity involves amplification of the vagal baroreflex response, and that this "exercises" the baroreflex. Evidence for resonance in HRV includes the large and highly significant (p < .0001) increase in total as well as LF HRV (Tables 24![]()
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) during biofeedback, all at a single frequency. This frequency was close to 0.1 Hz, which appears to be the modal resonant frequency across individuals (20). The acute effects of biofeedback on baroreflex gain were related to respiratory frequency and tidal volume, and were probably produced by the latter. After we adjusted for changes in respiration rate by entering respiration rate as an independent variable in the mixed models analysis, we found that baroreflex gain during biofeedback periods no longer differed significantly from that during rest periods.
However, the cumulative changes in baroreflex gain, both within and, more importantly, across sessions, were not simple effects of slow breathing. The effects of biofeedback on baroreflex gain, both within and between sessions, remained significant, after factoring out the effects of respiration rate. Thus, although breathing at participants resonant frequencies produced immediate baroreflex augmentation, over time (both within individual sessions and over weeks of practice) the baroreflex became intrinsically more responsive, an effect that no longer depended on breathing rate and volume. Thus, the intrinsic resting baroreflex increased.
We suggest that chronic biofeedback-induced increases in baroreflex gain, which, to our knowledge, has not previously been reported, reflects neuroplasticity. There are many opportunities within the baroreflex arc for such plastic changes to occur. It is known that the neurochemical phenotype of autonomic neurons changes continuously in response to changes of neural traffic, feedback by innervated targets, and changing neurotransmitter and hormone levels (32). Also, it is known that baroreflex gain is modulated by higher centers. Electrical hypothalamic stimulation inhibits baroreflex responses (33). It seems likely that biofeedback alters central modulation of baroreflex gain.
At the same time, biofeedback appears to modulate traffic over vagal pathways involved in maintenance of airway tone. However, the lack of correlation between baroreflex and pulmonary effects suggests that the mechanisms for the two effects may be different. Similarly, none of the physiological changes were closely associated with self-reported experiences of relaxation, suggesting also that the cardiorespiratory effects cannot be explained by relaxation. The fewer relaxation side effects reported in the biofeedback condition suggest that the training procedures are less stressful than asking people to relax on demand, without special instruction.
Our peak flow results are consistent with data from preliminary studies showing that HRV biofeedback may be helpful in treating asthma (3, 16). Similarly, the baroreflex effects suggest that it may be helpful for various cardiovascular disorders linked to impaired baroreflex control, including orthostatic hypotension and perhaps other forms of BP dysregulation, and perhaps other cardiovascular diseases.
The principal limitation of our experiment is its duration. Future research should probe the possibility that the trend we identified continues.
| ACKNOWLEDGMENTS |
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Received for publication June 12, 2002.
| REFERENCES |
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