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Background: Neurophysiological models link dissociation (e.g. feeling detached during or after a traumatic event) to hypoarousal. It is currently assumed that the initial passive reaction to a threat may coincide with a blunted autonomic response, which constitutes the dissociative subtype of post-traumatic stress disorder (PTSD). Objective: Within this systematic review we summarize research which evaluates autonomic nervous system activation (e.g. heart rate, blood pressure) and dissociation in PTSD patients to discern the validity of current neurophysiological models of trauma-related hypoarousal. Method: Of 553 screened articles, 28 studies (N = 1300 subjects) investigating the physiological response to stress provocation or trauma-related interventions were included in the final analysis. Results: No clear trend exists across all measured physiological markers in trauma-related dissociation. Extracted results are inconsistent, in part due to high heterogeneity in experimental methodology. Conclusion: The current review is unable to provide robust evidence that peri- and post-traumatic dissociation are associated with hypoarousal, questioning the validity of distinct psychophysiological profiles in PTSD. There is no consensus on physiological biomarkers of trauma-related dissociation. Peri- and post-traumatic dissociation are physiologically distinct from stress reactions in chronic states. Standardized methodologies may increase the reproducibility and specificity of psychophysiological biomarkers of dissociation.

Background: New technologies may profoundly change our way of understanding psychiatric disorders including posttraumatic stress disorder (PTSD). Imaging and biomarkers, along with technological and medical informatics developments, might provide an answer regarding at-risk patient's identification. Recent advances in the concept of 'digital phenotype', which refers to the capture of characteristics of a psychiatric disorder by computerized measurement tools, is one paradigmatic example. Objective: The impact of the new technologies on health professionals practice in PTSD care remains to be determined. The recent evolutions could disrupt the clinical practices and practitioners in their beliefs, ethics and representations, going as far as questioning their professional culture. In the present paper, we conducted an extensive search to highlight the articles which reflect the potential of these new technologies. Method: We conducted an overview by querying PubMed database with the terms [PTSD] [Posttraumatic stress disorder] AND [Computer] OR [Computerized] OR [Mobile] OR [Automatic] OR [Automated] OR [Machine learning] OR [Sensor] OR [Heart rate variability] OR [HRV] OR [actigraphy] OR [actimetry] OR [digital] OR [motion] OR [temperature] OR [virtual reality]. Results: We summarized the synthesized literature in two categories: prediction and assessment (including diagnostic, screening and monitoring). Two independent reviewers screened, extracted data and quality appraised the sources. Results were synthesized narratively. Conclusions: This overview shows that many studies are underway allowing researchers to start building a PTSD digital phenotype using passive data obtained by biometric sensors. Active data obtained from Ecological Momentary Assessment (EMA) could allow clinicians to assess PTSD patients. The place of connected objects, Artificial Intelligence and remote monitoring of patients with psychiatric pathology remains to be defined. These tools must be explained and adapted to the different profiles of physicians and patients. The involvement of patients, caregivers and health professionals is essential to the design and evaluation of these new tools.

Background: Childhood maltreatment (CM) can disrupt the development of behavioural and physiological systems, increasing the risk of physical and psychological adverse outcomes across the lifespan. CM may cause interpersonal dysfunctions that impair social communication and lead to dysfunctional activation of the autonomic nervous system. The present exploratory study analyzed the long-term impact of CM from an integrated perspective through the simultaneous assessment of psychological symptoms, social and behavioural communication, and physiological regulation. Methods: Participants were 55 healthy university students (9 males and 46 females; mean age ± SD = 25.26 ± 2.83 years), who filled out a battery of questionnaires to assess the presence of CM (Childhood Trauma Questionnaire) and psychopathological symptoms (Symptom Check-List-90 Item Revised). Participants were then subjected to a videotaped interview for the assessment of non-verbal behaviour (Ethological Coding System for Interviews) and measurement of tonic heart rate variability (HRV), a measure of physiological adaptability to the environment. We performed Pearson's correlation analysis to evaluate the associations between non-verbal behaviour, HRV, and CM variables. Multiple regression analysis was used to evaluate the independent associations between CM variables on HRV and nonverbal behaviour. Results: We found an association between more severe CM, increased symptoms-related distress (ps < .001), less submissive behaviour (ps < .018), and decreased tonic HRV (ps < .028). As a result of multiple regression analysis, participants with a history of emotional abuse (R² = .18, p = .002) and neglect (R² = .10, p = .03) were more likely to display decreased submissive behaviour during the dyadic interview. Moreover, early experience of emotional (R² = .21, p = .005) and sexual abuse (R² = .14, p = .04) was associated with decreased tonic HRV. Conclusion: Our preliminary findings show the utility of analyzing the long-term effects of adverse early experiences at different levels of 'adaptive functioning' (the capabilities needed to respond effectively to environmental demands). Substantial traumatic experiences during childhood, such as emotional abuse, emotional neglect, and sexual abuse were associated with lower heart rate variability levels in a sample of young adults. Young adults with a history of emotional abuse and neglect were more likely to display decreased submissive behaviour (ethological behaviour) during the dyadic interview. Severe childhood maltreatment was associated with increased symptoms-related distress, less submissive behaviour (ethological behaviour), and decreased tonic heart rate variability in young adults.

Background: Difficulties in emotion regulation are a core symptom of borderline personality disorder (BPD) and often interfere with cognitive functions, such as working memory (WM). Traumatic childhood experiences, including severe maltreatment, can contribute to emotion dysregulation, possibly mediated by changes in high-frequency heart rate variability (HF-HRV). However, it is not yet entirely understood if HF-HRV alterations underlie impaired WM during emotional distraction in BPD and if this is related to traumatic childhood experiences and to comorbid post-traumatic stress disorder (PTSD). Objective: Our aim was to investigate performance (reaction times, RTs) and HF-HRV during an emotional working memory task (EWMT) in relation to childhood maltreatment severity and comorbid PTSD in BPD. Method: Eighty-one women (n = 28 healthy controls (HC) and n = 53 BPD patients of which n = 18 had comorbid PTSD) performed an adapted Sternberg item recognition WM task with neutral and negative social cues (interpersonal scenes from the International Affective Picture System (IAPS), and neutral, fearful, and angry faces) as distractors. Dependent variables were RTs of correct trials and HF-HRV. Childhood maltreatment was assessed with the Childhood Trauma Questionnaire. Results: Compared to healthy participants, patients with BPD showed prolonged RTs across all distractor conditions with social cues, regardless of their emotional valence. Patients with BPD, especially those with PTSD, demonstrated reduced HF-HRV both at rest and during EWMT. Severity of childhood maltreatment predicted longer RTs and lower HF-HRV during the EWMT. Conclusions: Findings suggest that adverse childhood experiences accelerate difficulties in shifting attention away from social information and that these are more pronounced in individuals with BPD. Reduced HF-HRV (low parasympathetic-tonus) may be an important psychophysiological mechanism underlying impaired WM in the presence of distracting social cues in patients with BPD, especially in those with comorbid PTSD. This study provides evidence that childhood maltreatment experiences are associated with hypersensitivity to social information and reduced high-frequency heart rate variability during a working memory task in borderline personality disorder.

Voluntary recall of trauma is a key element in exposure-based psychotherapies and can trigger spontaneous dissociative responses such as flashbacks, depersonalisation, and derealisation. In order to examine the associations between cardiovascular and psychological responses to voluntary recollection of trauma, individuals with PTSD recalled a traumatic memory. Heart rate and heart rate variability were recorded continuously and the episodes when different forms of dissociation were experienced during the recall were identified. A significant increase in parasympathetic activity was found during trauma recall, with greater parasympathetic dominance being indicative of greater state depersonalisation/derealisation. Whereas overall decreases in heart rate during trauma recall were associated with increased fear and perceived threat, flashbacks were accompanied by short-term increases in heart rate. These findings demonstrate different types of cardiovascular responses associated with different psychological experiences during trauma recall. Future research directions were discussed.

Background： Renal function is associated with mortality and functional disabilities in stroke patients, and impaired autonomic function is common in stroke, but little is known regarding its effects on stroke patients with renal dysfunction. This study sought to evaluate the association between autonomic function and stroke in patients with renal dysfunction. Methods： This study comprised 232 patients with acute ischemic stroke consecutively enrolled from February 2013 to November 2014 at Guangdong Provincial Hospital of Chinese Medicine in China. All patients recruited underwent laboratory evaluation and 24 h Holter electrocardiography （ECG）. Autonomic function was measured based on the heart rate variability （HRV） using 24 h Holter ECG. Renal damage was assessed through the estimated glomerular filtration rate （eGFR）, and stroke severity was rated according to the National Institutes of Health Stroke Scale （NIHSS）. The Barthel index and modifed Rankin score were also determined following admission. All the clinical covariates that could potentially affect autonomic outcome variables were adjusted with linear regression. Results： In the patients with a mild or moderate decreased eGFR, the values for the standard deviation of the averaged normal-to-normal RR interval （SDANN） index （P = 0.022L very low frequency （VLF） （P = 0.043）, low frequency （LF） （P= 0.023）, and ratio of low-to-high frequency power （LF/HF） （P = 0.001 ） were significantly lower than those in the patients with a normal eGFR. A lnultinomial linear regression indicated that eGFR （t - 2.47, P - 0.014）, gender （t - -3.60, P 〈0.001）, and a history of hypertension （t = -2.65, P = 0.008） were the risk factors of LF/HF; the NIHSS score （SDANN index： t = -3.83, P 〈 0.001 ; VLF： t = -3.07, P = 0.002： LF： t = -2.79, P = 0.006） and a history of diabetes （SDANN index： t = -3.58, P 〈 0.001; VLF： t = -2.54, P = 0.012; LF： t = -2.87, P = 0.004） were independent factors Ibr the SDANN index, VLF, and LF; the Oxfordshire Community Stroke Project （t = -2.38, P = 0.018） was related to the SDANN index. Conclusions： Autonomic dysfunction is aggravated with the progression ofeGFR stage in patients with acute ischemic stroke; the eGFR is an independent factor of LF/HF in the adjusted models. Stroke severity and a history of diabetes are more significantly associated with HRV in patients with acute ischemic stroke at different stages of renal dysfnnction.

The aim of this paper is to describe and analyse the behaviour of heart rate variability (HRV) during constant-load, high-intensity exercise using a time frequency analysis (Wavelet Transform). Eleven elite cyclists took part in the study (age: 18.6±3.0 years; VO2max: 4.88±0.61 litres·min−1). Initially, all subjects performed an incremental cycloergometer test to determine load power in a constant load-test (379.55±36.02 W; 89.0%). HRV declined dramatically from the start of testing (p <0.05). The behaviour of power spectral density within the LF band mirrored that of total energy, recording a significant decrease from the outset LF peaks fell rapidly thereafter, remaining stable until the end of the test. HF-VHF fell sharply in the first 20 to 30 seconds. The relative weighting (%) of HF-VHF was inverted with the onset of fatigue, [1.6% at the start, 7.1 (p <0.05) at the end of the first phase, and 43.1% (p <0.05) at the end of the test]. HF-VHFpeak displayed three phases: a moderate initial increase, followed by a slight fall, thereafter increasing to the end of the test. The LF/HF-VHF ratio increased at the start, later falling progressively until the end of the first phase and remaining around minimal values until the end of the test.

Poststroke depression （PSD） is one of the common complications of cerebrovascular diseases. Drug therapy and cognitive behavioral therapy are two commonly used methods in current clinical treatments of PSD. However, either method has its own drawbacks： The tbrmer has problems such as the slow onset of action and various side effects, and patients olden have a poor response to the latter Recently, scientists have started using the heart rate variability （HRV） biofeedback approach to treating patients with depression and found significant clinical efficacy. HRV biofeedback requires patients to synchronize heart rate （HR） oscillations, and breathe by slow abdominal breathing （about 6 times/min; i.e., at the resonance frequency of 0. 1Hz）, and thus maximizes HRV. The objective of this study is to examine the impacts of HRV biofeedback on patients＇ emotional improvement and to explore the potential of this approach as an effective, side-effect-free supplement for comprehensive recovery.

Mental states such as stress and anxiety can cause heart disease.On the other hand,meditation can improve cardiac performance.In this study,the heart rate variability,directed transfer function and corrected conditional entropy were used to investigate the effects of mental tasks on cardiac performance,and the functional coupling between the cerebral cortex and the heart.When subjects tried to decrease their heart rate by volition,the sympathetic nervous system was inhibited and the heart rate decreased.When subjects tried to increase their heart rate by volition,the parasympathetic nervous system was inhibited and the sympathetic nervous system was stimulated,and the heart rate increased.When autonomic nervous system activity was regulated by mental tasks,the information flow from the post-central areas to the pre-central areas of the cerebral cortex increased,and there was greater coupling between the brain and the heart.Use of directed transfer function and corrected conditional entropy techniques enabled analysis of electroencephalographic recordings,and of the information flow causing functional coupling between the brain and the heart.

Slow trends in the RR interval (RRI) series should be removed in the preprocessing step to get a reliable result of heart rate variability (HRV) analysis. Re-sampling is required to convert the unevenly sampled RRI series into evenly sampled time series when using the widely accepted smoothness priors approach (SPA). Noise is introduced in this process and the information quality is thus compromised. Empirical mode decomposition (EMD) and its variants, were introduced to directly process the unevenly sampled RRI series. Besides, a RR interval model was proposed to fascinate the introduction of standard metrics for the evaluation of the detrending performance. Based on standard metrics including signal-to-noise-ratio in dB (ISNR), mean square error (EMS), and percent root square difference (DPRS), the effectiveness of detrending methods in RR interval analysis were determined. Results demonstrate that complementary ensemble EMD (CEEMD, a variant of EMD) based method has a higher ISNR, a lower EMS and a lower DPRS as well as a better RRI series detrending performance compared with the SPA method, which would in turn lead to a more accurate HRV analysis.