[Show abstract][Hide abstract] ABSTRACT: The present study examines a measure of cardiac autonomic function, the heart rate variability (HRV), in a group of depressed elderly. Cardiac autonomic abnormalities have been implicated as a potential mediator of cardiovascular events and sudden death in depression. Because aging is associated with decreased cardiac vagal activity, it is possible that autonomic abnormalities are even more pronounced in the older depressed patients.
Cross-sectional comparison between those with or without depression. The groups were compared using the Wilcoxon matched-pair sign-rank test. Setting: Advanced Center for Interventions and Services Research for Late-Life Mood Disorders at University of Pittsburgh Medical Center.
Fifty-three patients with major depression (mean age: 73.3; SD: 7.4; range: 60-93) and an equal number of age and gender-matched subjects as a comparison group.
Time domain and frequency domain measures of HRV.
The groups did not differ in any of the time domain or frequency domain measures of HRV. As expected, subjects without depression displayed decreasing cardiac vagal function with aging (Spearman correlation coefficient r(s) = -0.33, p = 0.02). However, there was no significant change in vagal function with age in the depressed (r = 0.12, p= 0.38). Post-hoc analysis using Fisher's z(r) transformation revealed that the relationship between age and cardiac vagal function was significantly different between the groups (z = 2.32, p = 0.02).
Our findings suggest that age has differential influence on vagal function in individuals with and without depression, a difference with implications for cardiovascular disease risk in depression. Prospective studies of cardiac vagal activity in depressed patients with or without preexisting cardiac disease in different age groups are needed to replicate and extend these findings.
The American journal of geriatric psychiatry: official journal of the American Association for Geriatric Psychiatry 12/2008; 16(11):861-6. DOI:10.1097/JGP.0b013e318180053d · 4.24 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The objective of this study was to evaluate cross-sectional relationships among symptoms of psychological stress, sleep, and physiological arousal during non-rapid eye movement (NREM) sleep in a sample of 30 patients with chronic, primary insomnia (mean age, 30.2 years, 60% female). Study measures included indexes of subjective stress, visually scored sleep, and physiological arousal during NREM sleep: quantitative electroencephalogram (QEEG) and quantitative electrocardiogram (QEKG) measures. Psychological stress was more strongly related to indexes of physiological arousal during NREM sleep than to visually scored measures of sleep. Higher levels of perceived stress were associated with decreased EEG delta power (rho = -0.50, p < .01) and increased EEG beta power (rho = 0.38, p < .05). Increased frequency of stress-related avoidance behaviors was associated with decreased EKG high-frequency power (rho = -0.46, p < .05). Although QEEG measures were significantly correlated with sleep maintenance (QEEG delta power rho = 0.45, p < .01; QEEG beta power rho = -0.54, p < .01) and time spent in delta sleep (QEEG delta power rho = 0.65, p < .001; QEEG beta power rho = -0.65, p < .001), QEKG measures were unrelated to visually scored measures of sleep. Perceived stress and stress-related avoidance behaviors were associated with multiple indexes of physiological arousal during NREM sleep in patients with chronic, primary insomnia.
Behavioral Sleep Medicine 08/2007; 5(3):178-93. DOI:10.1080/15402000701263221 · 2.34 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Although stress can elicit profound and lasting effects on sleep, the pathways whereby stress affects sleep are not well understood. In this study, we used autoregressive spectral analysis of the electrocardiogram (EKG) interbeat interval sequence to characterize stress-related changes in heart rate variability during sleep in 59 healthy men and women.
Participants (N = 59) were randomly assigned to a control or stress condition, in which a standard speech task paradigm was used to elicit acute stress in the immediate presleep period. EKG was collected throughout the night. The high frequency component (0.15-0.4 Hz Eq) was used to index parasympathetic modulation, and the ratio of low to high frequency power (0.04-0.15 Hz Eq/0.15-0.4 Hz Eq) of heart rate variability was used to index sympathovagal balance.
Acute psychophysiological stress was associated with decreased levels of parasympathetic modulation during nonrapid eye movement (NREM) and rapid eye movement sleep and increased levels of sympathovagal balance during NREM sleep. Parasympathetic modulation increased across successive NREM cycles in the control group; these increases were blunted in the stress group and remained essentially unchanged across successive NREM periods. Higher levels of sympathovagal balance during NREM sleep were associated with poorer sleep maintenance and lower delta activity.
Changes in heart rate variability associated with acute stress may represent one pathway to disturbed sleep. Stress-related changes in heart rate variability during sleep may also be important in association with chronic stressors, which are associated with significant morbidity and increased risk for mortality.
Psychosomatic Medicine 01/2004; 66(1):56-62. DOI:10.1097/01.PSY.0000106884.58744.09 · 3.47 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Chemotherapy-induced nausea has been associated with a time-related decrease in cardiac parasympathetic activity. We tested the hypothesis that a time-related decrease in cardiac parasympathetic activity would also be associated with nausea and other motion sickness symptoms during illusory self-motion (vection). Fifty-nine participants (aged 18-34 years: 25 male) were exposed to a rotating optokinetic drum to induce vection. Symptoms of motion sickness and an estimate of cardiac parasympathetic activity (respiratory sinus arrhythmia; RSA) were obtained at baseline and throughout a drum-rotation period. As expected, motion sickness symptoms increased and RSA decreased over time during drum rotation. Moreover, greater decreases in RSA over time correlated with greater motion sickness severity. These results suggest that a time-related decrease in cardiac parasympathetic activity may be an important correlate of nausea and motion sickness across different evocative contexts.
[Show abstract][Hide abstract] ABSTRACT: Several, though not all, polysomnographic studies that use conventional visual scoring techniques show delta sleep deficits in schizophrenia. Delta sleep (in particular, > or = 1- to 2-Hz frequency range), mediated by thalamocortical circuits, is postulated to be abnormal in schizophrenia. We investigated whether deficits in delta sleep occur in schizophrenia and whether these are primarily related to the illness or are epiphenomena of previous medication use or illness chronicity.
We compared 30 unmedicated schizophrenic patients and 30 age- and sex-matched controls for sleep data evaluated by visual scoring as well as automated period amplitude analyses and power spectral analyses.
Schizophrenic patients had reduced visually scored delta sleep. Period amplitude analyses showed significant reductions in delta wave counts but not rapid eye movement counts; power spectral analyses showed reductions in delta as well as theta power. Delta spectral power was also reduced in the subset of 19 neuroleptic-naive, first-episode schizophrenic patients compared with matched controls. Delta deficits were more pronounced in the greater than 1- to 2-Hz frequency range.
Delta sleep deficits that occur in schizophrenia may be related to the primary pathophysiological characteristics of the illness and may not be secondary to previous neuroleptic use. Automated sleep quantification by means of period amplitude and power spectral analyses can complement the use of conventional visual scoring for understanding electrophysiological abnormalities in psychiatric disorders.
Archives of General Psychiatry 06/1998; 55(5):443-8. · 14.48 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: We describe the methods for power spectral analysis (PSA) of sleep electroencephalogram (EEG) data at a large clinical and research sleep laboratory. The multiple-bedroom, multiple-polygraph design of the sleep laboratory poses unique challenges for the quantitative analysis of the data. This paper focuses on the steps taken to ensure that our PSA results are not biased by the particular bedroom or polygraph from which the data were acquired.
After describing the data acquisition system hardware, we present our signal amplitude calibration procedure and our methods for performing PSA. We validate the amplitude calibration procedure in several experiments using PSA to establish tolerances for data acquisition from multiple bedrooms and polygraphs.
Since it is not possible to acquire identical digitized versions of an EEG signal using different sets of equipment, the best that can be achieved is data acquisition that is polygraph-independent within a known tolerance. We are able to demonstrate a tolerance in signal amplitude of +/- 0.25% when digitizing data from different bedrooms. When different data acquisition hardware is used, the power tolerance is approximately +/- 3% for frequencies from 1 to 35 Hz. The power tolerance is between +/- 3 and +/- 7% for frequencies below 1 Hz and frequencies between 35 and 50 Hz. Additional data demonstrate that variability due to the hardware system is small relative to the inherent variability of the sleep EEG.
The PSA results obtained in one location can be replicated elsewhere (subject to known tolerances) only if the data acquisition system and PSA method are adequately specified.
International Journal of Medical Informatics 11/1997; 46(3):175-84. DOI:10.1016/S1386-5056(97)00064-6 · 2.00 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Owing to the use of scalp electrodes in human sleep recordings, cortical EEG signals are inevitably intermingled with the electrical activity of the muscle tissue on the skull. Muscle artifacts are characterized by surges in high frequency activity and are readily identified because of their outlying high values relative to the local background activity. To detect bursts of myogenic activity a simple algorithm is introduced that compares high frequency activity (26.25-32.0 Hz) in each 4-s epoch with the activity level in a local 3-min window. A 4-s value was considered artifactual if it exceeded the local background activity by a certain factor. Sensitivity and specificity of the artifact detection algorithm were empirically adjusted by applying different factors as artifact thresholds. In an analysis of sleep EEG signals recorded from 25 healthy young adults 2.3% (SEM: 0.16) of all 4-s epochs during sleep were identified as artifacts when a threshold factor of four was applied. Contamination of the EEG by muscle activity was more frequent towards the end of non-REM sleep episodes when EEG slow wave activity declined. Within and across REM sleep episodes muscle artifacts were evenly distributed. When the EEG signal was cleared of muscle artifacts, the all-night EEG power spectrum showed significant reductions in power density for all frequencies from 0.25-32.0 Hz. Between 15 and 32 Hz, muscle artifacts made up a substantial part (20-70%) of all-night EEG power density. It is concluded that elimination of short-lasting muscle artifacts reduces the confound between cortical and myogenic activity and is important in interpreting quantitative EEG data. Quantitative approaches in defining and detecting transient events in the EEG signal may help to determine which EEG phenomena constitute clinically significant arousals.
Journal of Sleep Research 10/1996; 5(3):155-64. DOI:10.1046/j.1365-2869.1996.00009.x · 3.35 Impact Factor