Application of computer averaging techniques to the study of learned volitive heartbeat control

Eh,ctroencwhah~graph )' and clinical Neuroptg,siologv, 1987, 6 6 : 9 3 96

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Else'tier Scientific Publishers Ireland, Ltd. EE(I 03202

Short communication

Application of computer averaging techniques to the study of learned volitive heartbeat control A.M. Yellin Laboratorv of Neuroscience.,

Department of P.~v('htatrv, Unwer.sitv ~f Minnesota. Minneapolis, MN 55455 (U.S. 4.) (Accepted for publication: 20 August. 1986)

Summary. Research on the acqmsition of conscious cardiovascular control (Yellin 1984, 1986) utilized computer averaging of electrocardiographic (ECG) cycles to demonstrate and document precise, reliable and sustainable time-locking of heartbeat to external stimuli on demand. E C G cycles were treated as evoked responses, and successive epochs were summated, beginning with Zeitgeber-stimulus (ZS) onset, and with the duration of each epoch equaling the ZS's interstimulus interval. Cardiac synchrony was exhibited by event-modulated (time-locked) cardiac responses (EMCRs) and in average ECGs. Key words: voluntaw control of heartbeat: heart rate synchronization EC(;- averaging; event-modulated cardiac responses (EMCRs): CNS control/modulation of ANS functions.

Computer averaging techniques have been used extensively' in the analysis of transient bioelectrical events, especially in ERP (event-related brain potentials) research (John et ah 1978; Van der Tweel et al. 1980). The main purpose of such techniques is to extract for analysis relevant information (responses to stimuli) embedded in (background) "noise,' i.e., to overcome problems inherent in situations in which the signal-to-noise ratio is too low to permit resolution of stimulus-dependent activity' (Srebro and Wright 1982). In ERP research, the signal-to-noise ratio is enhanced by presenting repetitive stimuli and recording and summating electrophysiological responses from the brain. Averaging these responses reduces background "noise' (EEG) in proportion to the square root of the number of responses that are included in the averaging, provided that the background EEG is unrelated to the stimuli. If the repeated stimuli have elicited time-locked responses, an average "signal' (ERP) is produced. The variability associated with the various "components' of the average ERP will be substantially smaller than the variability associated with the average of the random background EEG epochs preceding the stimuli or occurring after the cessation of the time-locked response. If the repeated stimuli have not elicited time-locked responses, no average ERP results; and, with a sufficient number of runs, the average of the random responses approaches a straight line which has the same variability

('orre~pondence to: Dr. A.M. Yellin, Laboratory of Ncurosciences, Department of Psychiatry', Box 95, Mayo Building, University of Minnesota, Minneapolis, MN 55455, U.S.A.

standard deviation) for each point along that line. Averaging techniques as well as more sophisticated methods which rely on some form of averaging (Regan 1982: Srebro and Wright 1982) are essential for ERP research, especially for responses recorded from surface electrodes, since the very' low signal-to noise ratio does not permit effective and reliable direct study ing and measurement of individual responses (Srebro and Wright 1982). In a study undertaken to investigate the potential for the establishment of precise volitive cardiac control, including the development of ability to synchronize heartbeat (HB) to Zeitgebe>stimuli (ZSs) on demand (Cohn and Yellin 1984: Yellin 1984, 1986). I ,,','as interested in employing a data-reducing technique {both for off-line analysis, as well as for on-line monitoring) that would readily' display the absence or presence of ECG (electrocardiograph) synchrony, as well as the degree of precision and sustainability over time of attained synchrony. The choice was ECG averaging.

ECG

averaging

Averaging is not essential in electrocardiographic research, due to the fact that, unlike ERPs, ECGs do not occur against a background of complex bioelectrical activity, and signal-to noise ratio is relatively high. Recently, ECG averaging has been utilized in some cardiological research, in order to en hance the resolution of low-level potentials in the cardiac cycle that may be of some diagnostic significance (Berbari 1983:

0013-4649/87fl$03.50 i', 1987 Elsevier Scientific Publishers Ireland, Ltd.

A.M. YELl.IN

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Fig. 1. Top left: computer average (thick line) of 10 successive 1 sec sweeps of ECG unsynchronized to ZS rate of 60 beats/rain. Bottom left: computer average of 10 successive 1 sec sweeps (10 successive E M C R s or time-locked ECGs) of HB synchronized to ZS rate of 60 b e a t s / m i n , resulting in average ECG. Top right: computer average, over a 1 min period, of ECGs unsynchronized to ZS rate of 60 b e a t s / m i n . Bottom right: computer average, over a 6 min period, of E M C R s synchronized to ZS rate of 60 beats/rain. The greater 'amplitude' variability ( + 1 S.D., shaded area) of the QRS complex is due to the fact that the latency variability of the individual E M C R s results in greater differences for sharper (shorter duration) than for less sharp (longer duration) peaks, such as P, T. ZS (metronome beat) onset at 0.

Berbari et al. 1983; Baruthio et al. 1984; Berbari and DeCarlo 1984). Such averaging is attained by selecting a finite-width window which is generally referenced to the QRS complex of the cardiac cycle, or by generating a template and fitting individual E C G cycles to it, since the averaged ECGs are spontaneous, not synchronized to ZSs. In order to demonstrate event-modulated (synchronized) cardiac responses (EMCR), each cardiac (ECG) cycle was treated as an evoked response: successive epochs were summated, beginning with ZS onset and with each epoch's duration equaling the ZS interstimulus interval. In the absence of HB synchrony to the repetitive ZSs, no average E C G is produced (Fig. 1, top); and averaging a sufficient number of epochs would result in a straight line, since the ECGs are floating C free-running') relative to the fixed-presentation rate

of the ZSs (i.e., no E M C R s are elicited). If HB synchrony is attained and maintained (i.e., E M C R s are elicited), an average E C G is produced (Fig. 1, bottom), since HBs arc time-locked to the ZSs. The shape of the average ECG will reflect distortions caused by time-jitter (latency variability between the individual time-locked ECGs). Some ERP averaging programs have applied adaptive filtering, in order to eliminate the distortions caused by time-jitter and to eliminate variability due to it, leaving only variability associated with amplitude (Woody 1967; A u n o n 1978). However, for the purposes described above, the elimination of time-jitter is not desirable, since this is important information appertaining to the precision of s?~n chronization. Adaptive filtering should be applied tas an additional step) only if information is also desired about ampli tude variability of various ECG components.

ECG A V E R A G I N G

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Advantages of ECG averaging

and calculating (e.g., via means and standard deviations) EMCR variability or time-jitter, i.e., synchronization precision. (3) Used on-line, it can provide the researcher with useful feedback about the progress of the training. (4) It provides for inspection of ECGs (both averages and individual cycles) for changes in various components that might be associated with the progress of training, as well as changes that might occur as a result of experimental (e.g,, pharmacological) manipulations.

ECG averaging can provide the following advantages in research on precise volitive control of HB: (1) It provides a useful visual display for examination and reporting of the presence or absence of EMCRs (HB synchronization; Figs. 1 and 2), as well as the sustainability of the volunta~' entrainment (Yetlin 1984, 1986). (2) It provides a means for both displaying (Figs. 1 and 2)

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Fig. 2. Computer averages of 2 successive EMCRs demonstrating ranges of time-jitter (precision of synchronization). Top: 2 averages, derived from 2 successive EMCRs from a 30 min session of HB synchronization to ZS rate of 104 beats/rain. ZS (inetronome beat) onset at 0 and 577 msec. Note the virtual absence of time-litter. Bottom left and Eight: 2 averages, each comprised of 2 successive EMCRs frorn a 6 min session of HB synchronization to ZS rate of 84 beats/rain. Note (left) hov, time-litter (40 mscc) causes reduction in the amplitude of sharp peaks (R-waves) and results in large "amplitude' variability. ZS (metronome beat) onset at 0.

96 A disadvantage of the averaging technique is that it does not provide for a precise quantification of the degree of time-jitter other than through computation of standard deviation. A more precise quantification of jitter can be accomplished by the addition of a routine for generating post-ZS histograms of R-wave events. The histogram-generating routine can also be used by itself for gauging the acquisition of heart rate synchronization. However, it will not provide information about electrophysiological events in the cardiac cycles, and, thus, will not enable investigation of psycho-physiological changes. Computer programs for input and averaging of physiological data have been developed in many laboratories, as well as commercially, and they are easily obtainable and applicable to ECG research. The recent demonstration that precise, reliable and sustainable volitive cardiovascular control is achievable (Cohn and Yellin 1984; Yellin 1984, 1986), should lend impetus to the use of ECG averaging in psychophysiological studies of HB control.

R6sum6

Application du movennage par ordinateur 2a I'&ude du contrg)le ¢,olontaire appris des hattements cardiaques

L'dtude de l'acquisition du contrgle cardiovasculaire conscient (Yellin 1984, 1986) a 6t6 effectu6 par moyennage instrumental des cycles de I'ECG, ceci pour d4montrer et analyser la ddpendance chronologique pr6cise, fiable et durable des battements cardiaques, de stimulus externes, sur consigne. Les cycles ECG ont 6t6 trait~s comme des r6ponses 4voqu6es, les dpoques successives ont 6t6 somm6es 5_ partir d'un stimulus Zeitgeber (ZS), la dur4e de chaque 4poque ~tant dgale ~ l'intervalle interstimulus du ZS. Le synchronisme cardiaque 6tait mis en dvidence sous forme de r6ponses cardiaques moduldes par l'4vdnement et dans I'ECG moyennd.

References

Aunon, J.I. Computer techniques for the processing of evoked potentials. Comput. Progr. Biomed., 1978, 8: 243-255.

A.M. YELl.IN Baruthio, J., Chambron, J,, Germain, P., Mossard, J.M., Voegtlin, R. and Sacrez, A. Late potentials after ventricu[ar tachycardia, after myocardial infarction and in healthy subjects. In: Computers in Cardiology, IEEE Computer Society, Los Angeles, CA, 1984:497 500. Berbari, E.J. High resolution electrocardiology. In: Proc. 5th Ann. Conf. IEEE/Eng. Med. Biol. IEEE Computer Society, Los Angeles, CA, 1983: 240-245. Berbari, E.J. and DeCarlo, L. Optimizing the signal averaging method for ventricular late potentials. In: Computers in Cardiology. IEEE Computer Society, Los Angeles, ('A, 1984: 45-49. Berbari, E.J., Brachman, J., Harrison. L.A., Scherlag, B.J. and Lazzara, R. Noninvasively determining the severity and mechanism of ventricular arrhythmias following myocardial infarction. In: Computers in Cardiology. IEEE Computer Society, Los Angeles, CA, 1983:135 138. Cohn, J.N. and Yellin, A.M. Learned precise cardiovascular control through graded central sympathetic stimulation. J. Hypertens., 1984, 2 (Suppl. 3): 77 79. John. E.R., Ruchkin, D.S. and Vidal, J.J. Measurement of event-related potentials. In: E. Callaway, P. Tueting and S.H. Koslow (Eds.), Event-Related Brain Potentials in Man. Academic Press, New York, 1978: 93-138. Regan, D. Comparison of transient and steady-state methods. Ann. N.Y. Acad. Sci., 1982, 388:45 71. Srebro, R. and Wright, W. Pseudorandom sequences in the study of evoked potentials. Ann. N.Y. Acad. Sci., 1982, 388:98 112. Van der Tweel, L.H., Estdvez, O. and Strackee, J. Measurement of evoked potentials. In: C. Barber (Ed.t. Evoked Potentials. University Park Press, Baltimore, MD, 1980: 19-41. Woody, C.D. Characterization of an adaptive filter for the analysis of variable latency neuroelectrical signals. Med. biol. Engng, 1967, 5: 539--553. Yellin, A.M. Learned prompt precise volitive control of heartbeat. Psychophysiology. 1984, 21: 565-566. Yellin, A.M. Acquired precise volitive cardiac control. Ann. N.Y. Aead. Sci., 1986, 463: 362-365.