Heart Rate Variability in Patients With Major Depression

Nahshoni, Eitan; Aravot, Dan; Aizenberg, Dov; Sigler, Mayanit; Zalsman, Gil; Strasberg, Boris; Imbar, Shula; Adler, Edgar; Weizman, Abraham

doi:10.1176/appi.psy.45.2.129

Cited by 114 publications

(87 citation statements)

References 35 publications

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“…Interestingly, a low PD2i of the heartbeats has also been found in major depression in human subjects (Nahshoni, Aravot, et al, 2004b). These same authors showed in an animal model that the neuronal spike-intervals thought to give rise to depressive behavior also show a reduction in PD2i compared to controls (Dremencov, Nahshoni et al, 2004;Friedman, Deri et al, 2007).…”

Section: Wwwintechopencommentioning

confidence: 77%

The Electrocardiogram – Waves and Intervals

Skinner¹,

Weiss²,

Lundy³

2012

Advances in Electrocardiograms - Methods and Analysis

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To understand the Electrocardiogram, one must understand both the origin of the waves (PQRST) and intervals between them (PQRST to PQRST or R-R). The waves are intrinsically generated within the heart, with some regulation by the cardiac nerves, but the intervals are extrinsically controlled primarily by the brain, through projections to both the auricular pacemakers and the ventricular tissues. That is, the intervals are regulated by the brain, as mediated through the autonomic effectors. To understand the R-R interval variations, one must understand the neural mechanism(s) that underlie changes in the T to P segments, which are lengthened and shortened in time to create the R-R variation. The Society for Neuroscience does not pay substantive attention to Cardiology, and the various societies of Cardiology do not pay much attention to Neuroscience. This two-way neglect has forced the formation of a new society devoted to both fields of inquiry. The Society for Heart-Brain Medicine was formed in 2007, and the plenary talks that established the field on its own foundation included two by the current authors (Skinner, 2007a;2007b). A paradigm is a way of thinking, and a new one is a way of "thinking outside the box." Two new paradigms were presented by us at the first SHBM Meeting and each was based on pivotal new discoveries. First, we showed that only nonlinear algorithms are appropriate for analysis of physiological data, because the data themselves are nonlinear---a nonlinear algorithm is thus a more sensitive measure of the heartbeat dynamics (e.g., of R-R variability) than all previous stochastic measures, such as the, mean, standard deviation, power spectrum, and so on. Secondly, small proteins and peptides are known to regulate physiology in parallel with the nervous system---that is, the "state" (behavioral / neural) determines the outputs of these two types of physiological effectors. Hibernation, for example, in which the cold eventually shuts off the nervous system, continues to be regulated by neuroendocrine molecules, some of which were indicated in a similar state (REM sleep) to have salutary effects on the ischemic heart (suppression of arrhythmogenesis in the electrocardiogram). This analogy between the similar states enabled conventional proteomics to be used in the other state (e.g., in hibernation) and thus formed the basis for a new way to discover drugs, "state-dependent proteomics." With the method a new (antiinfarction) drug candidate was actually discovered (Skinner, 2007a). The realization that the heartbeat intervals in the electrocardiogram are primarily regulated by the brain provides us with an entirely new way to look at the electrocardiogram -the intervals are not intrinsically regulated by currents and pacemakers within the heart, as are the waves, but rather are under extrinsic control by the brain, mediated of course through the autonomic www.intechopen.com Advances in Electrocardiograms -Methods and Analysis

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Section: Wwwintechopencommentioning

confidence: 77%

The Electrocardiogram – Waves and Intervals

Skinner¹,

Weiss²,

Lundy³

2012

Advances in Electrocardiograms - Methods and Analysis

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“…[17] Nahshoni, et al [1] have done a remarkable study in which comparison has been made between normal healthy controls, major depression patients and mentally healthy heart transplant recipients. Their results supported the hypothesis that cardiac autonomic imbalance (reduced vagal modulation) to the extent of cardiac neuropathy is present in depression.…”

Section: Discussionmentioning

confidence: 99%

“…[1] This has been hypothesized to be because of alterations in the autonomic nervous system among depressed persons. Such alterations are believed to reduce heart rate variability (HRV), a well-known prognostic risk factor for cardiovascular disease and mortality.…”

Section: Introductionmentioning

confidence: 99%

Cardiac autonomic dysfunction assessed by heart rate variability in major depression

Dubey¹,

Sawane²

2017

Int J Med Sci Public Health

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“…For example, Schiffrin and Nelson [31] reported a significant relationship between perceived psychological stress level and both cognitive and affective well-being, and Suh et al [42] reported a significant negative correlation between psychological stress level anticipated by the occurrence of significant life events and cognitive well-being. Furthermore, a significant relationship between HRV and psychometrics such as perceived stress level and depression has been reported [1,22,28,45]. Trimmel [45] also reported a significant positive correlation between HRV and the frequency of the appearance of positive moods in a day; the relationship, however, between daily transactions of affective states and HRV has not yet been examined.…”

Section: Physiological Stress Psychological Stress and Affective Stmentioning

confidence: 99%

Measuring Affective Well-Being by the Combination of the Day Reconstruction Method and a Wearable Device: Case Study of an Aging and Depopulating Community in Japan

Ishio

Abe

2017

Augment Hum Res

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Affective well-being indicates the changes in the predominance of positive or negative affects of people in response to their daily experiences. For measuring affective well-being, people are usually asked to indicate their affective states in several episodes that they experienced in a day. However, such conventional methods have been problematic in terms of their burdensomeness on participants and the validity of the rating. To overcome these problems, we attempted to introduce a new approach for measuring affective states, based on the combination of the day reconstruction method and the measurement of physiological stress levels by a wristband-type wearable device. As the indicator of physiological stress levels, we used heart rate variability calculated from the data recorded by the device. We examined the interpretability of the physiological stress level as a substitute for affective states by applying this combinational approach to an aging and depopulating village in Japan, because the well-being of the residents in such areas is a matter of public concern. As a result, we could depict the sources of affective well-being and the physiological stressors in the village. We also found a reasonable, but weak, correlation between the scores of affective states and the indicator of physiological stress levels. We discussed the challenges that should be overcome for utilizing the physiological stress level as a substitute for affective state.

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Heart Rate Variability in Patients With Major Depression

Cited by 114 publications

References 35 publications

The Electrocardiogram – Waves and Intervals

The Electrocardiogram – Waves and Intervals

Cardiac autonomic dysfunction assessed by heart rate variability in major depression

Measuring Affective Well-Being by the Combination of the Day Reconstruction Method and a Wearable Device: Case Study of an Aging and Depopulating Community in Japan

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