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Hypnosis can act on the autonomic nervous system which can be presented by heart rate variability (HRV). So HRV implies many information related to hypnosis. Because HRV signal is time-variant and non-stationary, the traditional methods, such as Fourier transform and AR spectral estimation, are unable to analyze it. Hence, wavelet time-frequency analysis is applied here to not only offer superior time and frequency resolution, but also detect sudden amplitude and frequency jumps. The electrocardiograms of subjects were recorded under hypnosis, from which the corresponding HRV signals are obtained. The instant parameters including HRV, very low frequency (VLF), low frequency (LF), high frequency (HF), and the ratio of LF to HF (LF/HF) components of each HRV signal are then computed. Furthermore, mean, coefficient of variation, skewness, and kurtosis of independent frequency components in four hypnotic states (resting state, inducing state, imagining state and awaking state) were also obtained from the instant parameters to describe variation during hypnosis. The experiment results show that the parameters of HRV can reflect some physiological features of hypnosis, e.g., the LF/HF was more concentrative and steady in imagining state.

Hypnosis is an adjuvant treatment of major depression (MD). Heart rate variability (HRV) can assess the autonomic nervous system, which is associated with MD, and HRV is decreased in MD patients. There is a lack of research on HRV changes before, during, and after the use of hypnosis in MD patients. A total of 21 MD patients participated in this study, and 5-minute electrocardiograms were recorded before, during, and after hypnosis. Compared with the prehypnotic condition, HRV parameters significantly (p

An image-guided surgical navigation system requires the improvement of the patient-to-image registration time to enhance the convenience of the registration procedure. A critical step in achieving this aim is performing a fully automatic patient-to-image registration. This study reports on a design of custom fiducial markers and the performance of a real-time automatic patient-to-image registration method using these markers on the basis of an optical tracking system for rigid anatomy. The custom fiducial markers are designed to be automatically localized in both patient and image spaces. An automatic localization method is performed by registering a point cloud sampled from the three dimensional (3D) pedestal model surface of a fiducial marker to each pedestal of fiducial markers searched in image space. A head phantom is constructed to estimate the performance of the real-time automatic registration method under four fiducial configurations. The head phantom experimental results demonstrate that the real-time automatic registration method is more convenient, rapid, and accurate than the manual method. The time required for each registration is approximately 0.1 s. The automatic localization method precisely localizes the fiducial markers in image space. The averaged target registration error for the four configurations is approximately 0.7 mm. The automatic registration performance is independent of the positions relative to the tracking system and the movement of the patient during the operation.

Patients with depression have lower heart rate variability (HRV) compared with controls. However, studies have indicated HRV difference between male and female controls. The gender effect might be interactive with the depression effect on the HRV, resulting in a low accuracy of recognising the patients with depression from the controls. Our study explores the effect of gender-related depression on HRV. Four ANS tests including resting, deep breathing, Valsalva, and orthostatic test are employed as stimuli. HRV were collected from 182 subjects comprising 91 depressive patients (33 females/58 males) and 91 controls (33 females/58 males) in the four tests. Time and frequency domains and nonlinear parameters are employed to quantify HRV. Two-way ANOVA is applied to evaluate the effect of gender-related depression. Most HRV parameters of the patients significantly differ from those of the controls, but some parameters indicate different depression effect between the males and females in the deep breathing and Valsalva test. Some HRV parameters illustrate significant difference between the male and female controls. Therefore, the effect of depression on HRV of each gender should be investigated.

Background Doctors mainly use scale tests and subjective judgment in the clinical diagnosis of depression. Researches have demonstrated that depression is associated with the dysfunction of the autonomic nervous system (ANS), where its modulation can be evaluated by heart rate variability (HRV). Depression patients have lower HRV than healthy subjects. Therefore, HRV may be used to distinguish depression patients from healthy people. Methods HRV signals were collected from 76 female subjects composed of 38 depression patients and 38 healthy people. Time domain, frequency domain, and non-linear features were extracted from the HRV signals of these subjects, who were subjected to the Ewing test as an ANS stimulus. Then, these multiple features were input into Bayesian networks, served as a classifier, to distinguish depression patients from healthy people. Hence, accuracy, sensitivity, and specificity were calculated to evaluate the performance of the classifier. Results Recognition results indicate 86.4% accuracy, 89.5% sensitivity, and 84.2% specificity. The individuals subjected to the Ewing test showed better recognition results than those at individual test states (resting state, deep breathing state, Valsalva state, and standing state) of the Ewing test. The root mean square of successive differences (RMSSD) of the HRV exhibits a significant relevance with recognition. Conclusion Bayesian networks can be applied to the recognition of depression patients from healthy people and the recognition results demonstrate the significant association between depression and HRV. The Ewing test is a good ANS stimulus for acquiring the difference of HRV between depression patients and healthy people to recognize depression. The RMSSD of the HRV is important in recognition and may be a significant index in distinguishing depression patients from healthy people.

Alcohol addiction is a major social and health concern. Here, we determined the expression profile of microRNAs (miRNAs) in the nucleus accumbens (NAc) of rats treated with alcohol. The results suggest that multiple miRNAs were aberrantly expressed in rat NAc after alcohol injection. Among them, miR-382 was down-regulated in alcohol-treated rats. In both cultured neuronal cells in vitro and in the NAc in vivo, we identified that the dopamine receptor D1 (Drd1) is a direct target gene of miR-382. Via this target gene, miR-382 strongly modulated the expression of DeltaFosB. Moreover, overexpression of miR-382 significantly attenuated alcohol-induced up-regulation of DRD1 and DeltaFosB, decreased voluntary intake of and preference for alcohol and inhibited the DRD1-induced action potential responses. The results indicated that miRNAs are involved in and may represent novel therapeutic targets for alcoholism.

Major depression disorder (MDD) patients express dysfunction autonomic nervous system (ANS) and reduced heart rate variability (HRV). However, previous researches mainly focused on examining resting state without considering a series of stimulation tests of ANS between MDD patients and healthy people. For this purpose, 40 healthy people and 40 MDD patients participated and finished 10min clinical autonomic test-Ewing test. Parameters of HRV such as time domain, frequency domain, and nonlinear dynamical parameters were calculated. Most of HRV parameters during Ewing test of MDD patients are lower than healthy people, and inversely, the ratio of low frequency to high frequency is higher when standing up. In addition, heart rate of healthy people in deep breathing and Valsalva test states are higher than that in resting state, nonlinear dynamical parameter (RCMSE1) of healthy people in standing up state is higher than that in Valsalva test state. The experimental results suggest that parasympathetic nervous system of MDD patients is influenced by mental state and become dysfunction under long-term depression, it cannot exert normal physiological functions when it is activated. Sympathetic activity increases on MDD patients, and this enhancement is more obvious which expresses higher complexity of HRV time series.