Physiological paradigm for assessing reward prediction and extinction using cortical direct current potential responses in rats.

Anticipating positive outcomes is a core cognitive function in the process of reward prediction. However, no neurophysiological method objectively assesses reward prediction in basic medical research. In the present study, we established a physiological paradigm using cortical direct current (DC) potential responses in rats to assess reward prediction. This paradigm consisted of five daily 1-h sessions with two tones, wherein the rewarded tone was followed by electrical stimulation of the medial forebrain bundle (MFB) scheduled at 1000 ms later, whereas the unrewarded tone was not. On day 1, both tones induced a negative DC shift immediately after auditory responses, persisting up to MFB stimulation. This negative shift progressively increased and peaked on day 4. Starting from day 3, the negative shift from 600 to 1000 ms was significantly larger following the rewarded tone than that following the unrewarded tone. This negative DC shift was particularly prominent in the frontal cortex, suggesting its crucial role in discriminative reward prediction. During the extinction sessions, the shift diminished significantly on extinction day 1. These findings suggest that cortical DC potential is related to reward prediction and could be a valuable tool for evaluating animal models of depression, providing a testing system for anhedonia.

Heart Rate Variability Measurement Can Be a Point-of-Care Sensing Tool for Screening Postpartum Depression: Differentiation from Adjustment Disorder.

Postpartum depression (PPD) is a serious mental health issue among women after childbirth, and screening systems that incorporate questionnaires have been utilized to screen for PPD. These questionnaires are sensitive but less specific, and the additional use of objective measures could be helpful. The present study aimed to verify the usefulness of a measure of autonomic function, heart rate variability (HRV), which has been reported to be dysregulated in people with depression. Among 935 women who had experienced childbirth and completed the Edinburgh Postnatal Depression Scale (EPDS), HRV was measured in EPDS-positive women (n = 45) 1 to 4 weeks after childbirth using a wearable device. The measurement was based on a three-behavioral-state paradigm with a 5 min duration, consisting of rest (Rest), task load (Task), and rest-after-task (After) states, and the low-frequency power (LF), the high-frequency power (HF), and their ratio (LF/HF) were calculated. Among the women included in this study, 12 were diagnosed with PPD and 33 were diagnosed with adjustment disorder (AJD). Women with PPD showed a lack of adequate HRV regulation in response to the task load, accompanying a high LF/HF score in the Rest state. On the other hand, women with AJD exhibited high HF and reduced LF/HF during the After state. A linear discriminant analysis using HRV indices and heart rate (HR) revealed that both the differentiation of PPD and AJD patients from the controls and that of PPD patients from AJD patients were possible. The sensitivity and specificity for PPD vs. AJD were 75.0% and 90.9%, respectively. Using this paradigm, an HRV measurement revealed the characteristic autonomic profiles of PPD and AJD, suggesting that it may serve as a point-of-care sensing tool in PPD screening systems.

"KAIZEN" method realizing implementation of deep-learning models for COVID-19 CT diagnosis in real world hospitals.

Numerous COVID-19 diagnostic imaging Artificial Intelligence (AI) studies exist. However, none of their models were of potential clinical use, primarily owing to methodological defects and the lack of implementation considerations for inference. In this study, all development processes of the deep-learning models are performed based on strict criteria of the "KAIZEN checklist", which is proposed based on previous AI development guidelines to overcome the deficiencies mentioned above. We develop and evaluate two binary-classification deep-learning models to triage COVID-19: a slice model examining a Computed Tomography (CT) slice to find COVID-19 lesions; a series model examining a series of CT images to find an infected patient. We collected 2,400,200 CT slices from twelve emergency centers in Japan. Area Under Curve (AUC) and accuracy were calculated for classification performance. The inference time of the system that includes these two models were measured. For validation data, the slice and series models recognized COVID-19 with AUCs and accuracies of 0.989 and 0.982, 95.9% and 93.0% respectively. For test data, the models' AUCs and accuracies were 0.958 and 0.953, 90.0% and 91.4% respectively. The average inference time per case was 2.83 s. Our deep-learning system realizes accuracy and inference speed high enough for practical use. The systems have already been implemented in four hospitals and eight are under progression. We released an application software and implementation code for free in a highly usable state to allow its use in Japan and globally.

Pulse rate variability estimation method based on imaging-photoplethysmography and application to telepsychiatry.

The worldwide adoption of telehealth services may benefit people who otherwise would not be able to access mental health support. In this paper, we present a novel algorithm to obtain reliable pulse and respiration signals from non-contact facial image sequence analysis. The proposed algorithm involved a skin pixel extraction method in the image processing part and signal reconstruction using the spectral information of RGB signal in the signal processing part. The algorithm was tested on 15 healthy subjects in a laboratory setting. The results show that the proposed algorithm can accurately monitor respiration rate (RR), pulse rate (PR), and pulse rate variability (PRV) in rest conditions.Clinical Relevance- The main achievement of this study is enabling non-contact PR and RR signal extraction from facial image sequences, which has potential for future use and support for psychiatrists in telepsychiatry.

Major Depressive Disorder and Chronic Fatigue Syndrome Show Characteristic Heart Rate Variability Profiles Reflecting Autonomic Dysregulations: Differentiation by Linear Discriminant Analysis.

Major depressive disorder (MDD) and chronic fatigue syndrome (CFS) have overlapping symptoms, and differentiation is important to administer the proper treatment. The present study aimed to assess the usefulness of heart rate variability (HRV) indices. Frequency-domain HRV indices, including high-frequency (HF) and low-frequency (LF) components, their sum (LF+HF), and their ratio (LF/HF), were measured in a three-behavioral-state paradigm composed of initial rest (Rest), task load (Task), and post-task rest (After) periods to examine autonomic regulation. It was found that HF was low at Rest in both disorders, but was lower in MDD than in CFS. LF and LF+HF at Rest were low only in MDD. Attenuated responses of LF, HF, LF+HF, and LF/HF to task load and an excessive increase in HF at After were found in both disorders. The results indicate that an overall HRV reduction at Rest may support a diagnosis of MDD. HF reduction was found in CFS, but with a lesser severity. Response disturbances of HRV to Task were observed in both disorders, and would suggest the presence of CFS when the baseline HRV has not been reduced. Linear discriminant analysis using HRV indices was able to differentiate MDD from CFS, with a sensitivity and specificity of 91.8% and 100%, respectively. HRV indices in MDD and CFS show both common and different profiles, and can be useful for the differential diagnosis.

Screening for Major Depressive Disorder Using a Wearable Ultra-Short-Term HRV Monitor and Signal Quality Indices.

To encourage potential major depressive disorder (MDD) patients to attend diagnostic sessions, we developed a novel MDD screening system based on sleep-induced autonomic nervous responses. The proposed method only requires a wristwatch device to be worn for 24 h. We evaluated heart rate variability (HRV) via wrist photoplethysmography (PPG). However, previous studies have indicated that HRV measurements obtained using wearable devices are susceptible to motion artifacts. We propose a novel method to improve screening accuracy by removing unreliable HRV data (identified on the basis of signal quality indices (SQIs) obtained by PPG sensors). The proposed algorithm enables real-time calculation of signal quality indices in the frequency domain (SQI-FD). A clinical study conducted at Maynds Tower Mental Clinic enrolled 40 MDD patients (mean age, 37.5 ± 8.8 years) diagnosed on the basis of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, and 29 healthy volunteers (mean age, 31.9 ± 13.0 years). Acceleration data were used to identify sleep states, and a linear classification model was trained and tested using HRV and pulse rate data. Ten-fold cross-validation showed a sensitivity of 87.3% (80.3% without SQI-FD data) and specificity of 84.0% (73.3% without SQI-FD data). Thus, SQI-FD drastically improved sensitivity and specificity.

Asymptomatic Autonomic Dysregulation after Recovery from Mild COVID-19 Infection Revealed by Analysis of Heart Rate Variability Responses to Task Load.

(1) Background: The coronavirus disease 2019 (COVID-19) infection is often followed by various complications, which can cause disturbances in daily life after recovery from the infectious state, although etiological mechanisms are not fully elucidated. Previous studies have indicated that autonomic dysregulation is an underlying factor, and it is of interest to clarify whether autonomic dysregulation is also present in the asymptomatic subjects after COVID-19 infection (post-COVID-19) for early detection of post-COVID-19 complications. (2) Methods: In the present study, autonomic activity was assessed using heart rate variability (HRV) analysis in the workers who recovered from mild COVID-19 infection (n = 39). They took a leave of absence for an average of 11.9 days and returned to the original work without complications. HRV was measured after an average of 9.3 days from return. High-frequency (HF) and low-frequency (LF) HRV parameters and heart rate (HR) were recorded during a three-behavioral-state paradigm of approximately 5 min length composed of initial rest, task load, and post-task rest periods and were compared with the data of the workers without the history of COVID-19 infection (normal, n = 38). (3) Results: The HRV and HR scores at the initial rest in the post-COVID-19 subjects showed no difference from those in the control. It is found that the post-COVID-19 subjects exhibited an attenuation of LF/HF increment during the task load and an excessive increase of HF together with a decrease of LF, LF/HF and HR during the post-task rest period in comparison with the initial rest scores. (4) Conclusions: These abnormalities are evaluated as asymptomatic autonomic dysregulation in response to task load, are frequently present after COVID-19 infection, and could be related to the generation of complications.

The development and clinical application of a novel schizophrenia screening system using yoga-induced autonomic nervous system responses.

Background: In severe cases, schizophrenia can result in suicide and social isolation. Diagnosis delay can lead to worsening symptoms, and often results in prolonged therapy. An estimated 50%-80% of patients with schizophrenia are unaware of their condition. Biomarkers for schizophrenia are important for receiving a diagnosis from a psychiatrist at an early stage. Although previous studies have investigated near-infrared spectroscopy as a biomarker for schizophrenia, the required equipment is expensive and not designed for home use. Hence, we developed a novel home-use schizophrenia screening system that uses a wearable device to measure autonomic nervous system responses induced by yoga, which is frequently adopted in rehabilitation for schizophrenia. Materials and methods: The schizophrenia screening system automatically distinguishes patients with schizophrenia from healthy subjects via yoga-induced transient autonomic responses measured with a wearable wireless electrocardiograph (ECG) using linear discriminant analysis (LDA; Z score ≥ 0 → suspected schizophrenia, Z-score < 0 → healthy). The explanatory variables of LDA are averages of four indicators: components of heart rate variability (HRV): the very low-frequency (VLF), the low-frequency (LF), HR, and standard deviation of the NN intervals (SDNN). In the current study, HRV is defined as frequency domain HRV, which is determined by integrating RRI power spectrum densities from 0.0033 to 0.04 Hz (VLF) and 0.04-0.15 Hz (LF), and as time domain HRV, SDNN of which is calculated as the mean of the standard deviations of the RR intervals. These variables were measured before (5 min), during (15 min), and after (5 min) yoga in a 15-min mindfulness-based yoga program for schizophrenia (MYS). The General Health Questionnaire-28 (GHQ28) score was used to assess the severity of mental disorders for patients with schizophrenia and healthy volunteers. Twelve patients with schizophrenia (eight female and four male, 23-60 years old) and 16 healthy volunteers (seven female and nine male, 22-54 years old) were recruited. Results: The schizophrenia screening system achieved sensitivity of 91% and specificity of 81%. Z-scores of LDA were significantly correlated with GHQ28 scores (r = 0.45, p = 0.01). Conclusion: Our proposed system appears to be promising for future automated preliminary schizophrenia screening at home.

Suppression of Glucocorticoid Response in Stressed Mice Using 50 Hz Electric Field According to Immobilization Degree and Posture.

Various studies on immobilized BALB/c mice to evaluate changes in hormone levels associated with stress responses have advanced the characterization of multiple aspects of the biological actions of extremely low-frequency (ELF) electric fields (EFs). In this study, we aimed to investigate the effect of mouse posture on its stress responses and evaluate the importance of adjusting the stress degree in the model. Mice were immobilized inside centrifuge tubes and exposed to an ELF EF generated between parallel plate electrodes. Blood was collected under anesthesia immediately after EF exposure, and plasma glucocorticoids were assayed. The inhibitory effects of EFs on glucocorticoid elevation by immobilization were reproduced regardless whether mice were in the abdominal or lateral recumbent position, for the EF vector delivered to mice through the sagittal or frontal plane. The effect of ELF EF was reproduced in moderately and mildly stressed mice but not in severely immobilized mice. Hence, adjusting the stress degree is critical to the reproducibility of the results for this model. We characterized the effects of ELF EF on homeostasis, including the stress response, and provided valuable information for the scientific evaluation of the biological risks and medical applications of ELF EF.

Near-Infrared Time-Resolved Spectroscopy Shows Anterior Prefrontal Blood Volume Reduction in Schizophrenia but Not in Major Depressive Disorder.

Previous studies using various brain imaging methods have reported prefrontal blood flow disturbances in psychiatric disorders, including schizophrenia and major depressive disorder. In both disorders, alterations of the resting blood flow, in addition to that of the activation in response to task load, have been shown, but the results are not consistent. The present study aimed to examine the anterior prefrontal hemoglobin concentration at the resting state in schizophrenia and depression using near-infrared time-resolved spectroscopy (NIR-TRS), which estimates the optical absorption coefficients and calculates the absolute concentrations of oxygenated (oxy-Hb), deoxygenated (deoxy-Hb), and total (total-Hb; sum of oxy-Hb and deoxy-Hb) hemoglobin. Their ratios to systemic blood hemoglobin concentration (blood-Hb) were also assessed. In agreement with our previous data, total-Hb and total-Hb/blood-Hb in schizophrenia were significantly lower. The present study further revealed that both oxy-Hb/blood-Hb and deoxy-Hb/blood-Hb in schizophrenia were reduced. In depression, total-Hb, total-Hb/blood-Hb, oxy-Hb, and oxy-Hb/blood-Hb were higher than in schizophrenia and were not different from the control. The oxygen saturation (oxy-Hb/total-Hb), in addition to the optical pathlengths, did not show group differences. Lowered oxy-Hb/blood-Hb and deoxy-Hb/blood-Hb together with unchanged oxygen saturation may indicate that the prefrontal blood volume is reduced in schizophrenia. The present findings suggest that NIR-TRS is useful in analyzing the hemodynamic aspects of prefrontal dysfunction in schizophrenia and differentiating schizophrenia from depression.

Stress-Reducing Effect of a 50 Hz Electric Field in Mice after Repeated Immobilizations, Electric Field Shields, and Polarization of the Electrodes.

In BALB/c mice, immobilization-increased plasma glucocorticoid (GC) levels are suppressed by extremely low frequency (ELF) electric fields (EF). The aim of this study was to advance our understanding of the biological effects of ELF-EF, using its suppressive effect on the GC response. Mice were exposed to a 50 Hz EF of 10 kV/m via a parallel plate electrode and immobilized as needed. We examined the suppressive effect of ELF-EF on GC level change after repeated immobilizations, electrode polarization, and EF shielding of different portions of the mouse body parts. Additionally, bodyweight changes owing to stress and EF were examined. Immobilization-induced reduction in the plasma GC levels was reproduced in mice with stress and EF exposure, regardless of the stress episode numbers and electrode polarization. Furthermore, when the head of mice was shielded from the EF, the suppressive effect was possibly relatively lower than that when the abdomen was shielded. The bodyweight of the mice decreased for 3 days after immobilization before recovering; ELF-EF did not affect the bodyweight. Thus, to elicit the biological effects of the EF, not only the size of the area where the EF is distributed but also the area where the field is distributed should be important. The results also confirmed the stableness of the present experimental system, at least in terms of the stress-reducing effect. In addition, the restriction in this study caused weight loss, but ELF-EF was not considered to affect it. The results improve the understanding of the biological effect and medical applications of ELF-EF.

Non-contact Measurement of Pulse Rate Variability Using a Webcam and Application to Mental Illness Screening System.

The COVID-19 pandemic is a global health crisis. Mental health is critical in such uncertain situations, particularly when people are required to significantly restrict their movements and change their lifestyles. Under these conditions, many countries have turned to telemedicine to strengthen and expand mental health services. Our research group previously developed a mental illness screening system based on heart rate variability (HRV) analysis, enabling an objective and easy mental health self-check. This screening system cannot be used for telemedicine because it uses electrocardiography (ECG) and contact photoplethysmography (PPG), that are not widely available outside of a clinical setting. The purpose of this study is to enable the extension of the aforementioned system to telemedicine by the application of non-contact PPG using an RGB webcam, also called imaging- photoplethysmography (iPPG). The iPPG measurement errors occur due to changes in the relative position between the camera and the target, and due to changes in light. Conventionally, in image processing, the pixel value of the entire face region is used. We propose skin pixel extraction to eliminate blinks, eye movements, and changes in light and shadow. In signal processing, the green channel signal is conventionally used as a pulse wave owing to the absorption characteristics of blood flow. Taking advantage of the fact that the red and blue channels contain noise, we propose a signal reconstruction method for removing noise and strengthening the signal in the pulse rate variability (PRV) frequency band by weighting the three signals of the RGB camera. We conducted an experiment with 13 healthy subjects, and showed that the PRV index and pulse rate (PR) errors estimated by the proposed method were smaller than those of the conventional method. The correlation coefficients between estimated values by the proposed method and reference values of LF, HF, and PR were 0.86, 0.69, and 0.96, respectively.

Return-to-Work Screening by Linear Discriminant Analysis of Heart Rate Variability Indices in Depressed Subjects.

Using a linear discriminant analysis of heart rate variability (HRV) indices, the present study sought to verify the usefulness of autonomic measurement in major depressive disorder (MDD) patients by assessing the feasibility of their return to work after sick leave. When reinstatement was scheduled, patients' HRV was measured using a wearable electrocardiogram device. The outcome of the reinstatement was evaluated at one month after returning to work. HRV indices including high- and low-frequency components were calculated in three conditions within a session: initial rest, mental task, and rest after task. A linear discriminant function was made using the HRV indices of 30 MDD patients from our previous study to effectively discriminate the successful reinstatement from the unsuccessful reinstatement; this was then tested on 52 patients who participated in the present study. The discriminant function showed that the sensitivity and specificity in discriminating successful from unsuccessful returns were 95.8% and 35.7%, respectively. Sensitivity is high, indicating that normal HRV is required for a successful return, and that the discriminant analysis of HRV indices is useful for return-to-work screening in MDD patients. On the other hand, specificity is low, suggesting that other factors may also affect the outcome of reinstatement.

Chronic antidepressant treatment rescues abnormally reduced REM sleep theta power in socially defeated rats.

The effects of chronic antidepressant (AD) treatment on sleep disturbances in rodent chronic stress models have not been thoroughly investigated. Here, we show that chronic social defeat stress (SDS) in rats induces prolonged social avoidance, alterations in sleep architecture (increased total rapid eye movement [REM] sleep duration, bout, and shortened REM latency), and contextual but not cued fear memory deficits, even 1 month after the last SDS. These abnormalities were associated with changes in electroencephalography (EEG) spectral powers, including reduced REM sleep theta power during the light phase. Chronic treatment with two different classes of antidepressants (ADs), imipramine and fluoxetine, significantly ameliorated these behavioral, sleep, and EEG abnormalities. Interestingly, REM theta power was normalized by chronic (1 month) but not 1 week AD administration and solely correlated with the ratio (an objective indicator) of social interaction 1 month after the last SDS. These data suggest that reductions in REM sleep theta power, an EEG parameter that has never been directly investigated in humans, is a core sleep symptom in socially defeated rats, and, potentially, also in patients with stress-related psychiatric disorders, including major depressive and posttraumatic stress disorders.

Usefulness of heart rate variability indices in assessing the risk of an unsuccessful return to work after sick leave in depressed patients.

AIM: The present study aimed to examine whether heart rate variability (HRV) indices in depressed patients measured at return to work after sick leave are related to the outcome of reinstatement. METHODS: This study included 30 workers who took a leave of absence due to major depressive disorder. HRV was measured twice, once when participants left work and another when they returned to work. One month after returning to work, 19 participants continued their original work (successful return group), while 11 failed to perform their original work (unsuccessful return group). HRV indices including high- and low-frequency components (HF and LF) were calculated in three conditions within a session lasting for about 5 minutes, initial rest (Rest), mental task (Task), and rest after task (After), and were compared between the two participant groups. Psychological states were evaluated using Self-rating Depression Scale and State-Trait Anxiety Inventory. RESULTS: No significant differences were observed in the HRV indices on leaving work between groups. On returning to work, the "unsuccessful return group" exhibited lower HF Rest score, higher HF Task/Rest ratio, and higher LF/HF Rest score than the "successful return group." Psychological scores improved in both groups. CONCLUSION: These results indicate that autonomic dysregulations revealed by HRV measurement at return to work after a leave of absence in MDD patients were related to the outcome of reinstatement and can serve as useful information for the assessment of the risk of unsuccessful return.

Changes in Heart Rate Variability after Yoga are Dependent on Heart Rate Variability at Baseline and during Yoga: A Study Showing Autonomic Normalization Effect in Yoga-Naïve and Experienced Subjects.

BACKGROUND: Yoga therapy is widely applied to the maintenance of health and to treatment of various illnesses. Previous researches indicate the involvement of autonomic control in its effects, although the general agreement has not been reached regarding the acute modulation of autonomic function. AIM: The present study aimed at revealing the acute effect of yoga on the autonomic activity using heart rate variability (HRV) measurement. METHODS: Twenty-seven healthy controls participated in the present study. Fifteen of them (39.5 ± 8.5 years old) were naïve and 12 (45.1 ± 7.0 years old) were experienced in yoga. Yoga skills included breath awareness, two types of asana, and two types of pranayama. HRV was measured at the baseline, during yoga, and at the resting state after yoga. RESULTS: In both yoga-naïve and experienced participants, the changes in low-frequency (LF) component of HRV and its ratio to high-frequency (HF) component (LF/HF) after yoga were found to be correlated negatively with the baseline data. The changes in LF after yoga were also correlated with LF during yoga. The changes in HF as well as the raw HRV data after yoga were not related to the baseline HRV or the HRV during yoga. CONCLUSION: The results indicate that yoga leads to an increase in LF when LF is low and leads to a decrease in LF when it is high at the baseline. This normalization of LF is dependent on the autonomic modulation during yoga and may underlie the clinical effectiveness of yoga therapy both in yoga-naïve and experienced subjects.

Decreased anxiety after catheter ablation for paroxysmal atrial fibrillation is associated with augmented parasympathetic reactivity to stress.

BACKGROUND: Psychological improvement after catheter ablation for atrial fibrillation (AF) has been reported, but its mechanism is unclear. OBJECTIVE: This study aimed to clarify the relationship between cardiac autonomic modification and psychological changes after catheter ablation for paroxysmal AF (PAF). METHODS: Thirty-five consecutive patients (60.5 ± 11.9 years; male, n = 24) with PAF treated by catheter ablation were enrolled. Autonomic activity and reactivity to stress and psychological status were measured before (baseline) and at 1 and 3 months after ablation. We assessed autonomic activity and reactivity to stress by measuring heart rate variability (HRV) at rest (Rest), and during (Task) and after (After) the execution of a task and assessed relationships between HRV parameters and psychological changes using the State-Trait Anxiety Inventory (STAI) and Self-Rating Depression Scale (SDS). RESULTS: The STAI state and trait scores significantly decreased at 3 months compared with baseline, whereas SDS scores essentially remained unchanged. The high-frequency (HF) response index (Task/Rest) and HF recovery index (After/Rest) were significantly higher than baseline at 3 months (0.40 [0.29-0.90] vs 1.30 [0.64-2.18], P = .007 for HF response index; 1.13 [0.92-2.19] vs 1.87 [1.19-2.97], P = .049 for HF recovery index). Reductions in STAI scores positively correlated with increments in the HF recovery index in the entire cohort as well as in 5 patients with recurrent AF. CONCLUSIONS: Some augmentation of parasympathetic reactivity to stress correlated with reduced anxiety, implying that cardiac autonomic modification plays roles in psychological improvement after catheter ablation for AF.

Development and Clinical Application of a Novel Autonomic Transient Response-Based Screening System for Major Depressive Disorder Using a Fingertip Photoplethysmographic Sensor.

Over 350 million people across the world suffer from major depressive disorder (MDD). More than 10% of MDD patients have suicide intent, while it has been reported that more than 40% patients did not consult their doctors for MDD. In order to increase consultation rate of potential MDD patients, we developed a novel MDD screening system which can be used at home without help of health-care professionals. Using a fingertip photoplethysmograph (PPG) sensor as a substitute of electrocardiograph (ECG), the system discriminates MDD patients from healthy subjects using autonomic nerve transient responses induced by a mental task (random number generation) via logistic regression analysis. The nine logistic regression variables are averages of heart rate (HR), high frequency (HF) component of heart rate variability (HRV), and the low frequency (LF)/HF ratio of HRV before, during, and after the mental task. We conducted a clinical test of the proposed system. Participants were 6 MDD patients (4 females and 2 males, aged 23-60 years) from Shizuoka Saiseikai General Hospital psychiatry outpatient unit and 14 healthy volunteers from University of Electro-Communications (6 females and 8 males, aged 21-63 years). The average PPG- and ECG (as a reference)-derived HR, HF and LF/HF were significantly correlated with each other (HR; r = 1.00, p < 0.0001, HF; r = 0.98, p < 0.0001, LF/HF; r = 0.98, p < 0.0001). Leave-one-out cross validation (LOOCV) revealed 83% sensitivity and 93% specificity. The proposed system appears promising for future MDD self-screening at home and are expected to encourage psychiatric visits for potential MDD patients.

Increase of frontal cerebral blood volume during transcranial magnetic stimulation in depression is related to treatment effectiveness: A pilot study with near-infrared spectroscopy.

AIM: Alterations of cerebral blood flow have been reported in studies of depression treated by transcranial magnetic stimulation (TMS). However, the relation between these changes in activity during stimulation and the effectiveness of TMS is not known. The aim of this study was to determine whether changes in frontal cerebral blood volume measured as frontal hemoglobin concentration (fHbC) during TMS are correlated with clinical outcomes of treatment. METHODS: Fifteen drug-resistant patients with depression underwent a standard treatment regimen of TMS to the left dorsolateral prefrontal cortex. We recorded fHbC during stimulation at the start and end of the TMS treatment series using near-infrared spectroscopy. Symptom severity was determined using the Montgomery-Åsberg Depression Rating Scale. RESULTS: At the start of the TMS series, fHbC increased during stimulation in a majority of patients with no relation to symptom severity. However, at the end of the series, fHbC increase during stimulation was negatively correlated with the Montgomery-Åsberg Depression Rating Scale score and positively with the score reduction. Patients showing a decreasing response of fHbC during TMS at the end of the series experienced less clinical improvement. CONCLUSION: These results suggest that the maintenance of frontal activation during stimulation in the course of TMS series is related to the effectiveness in the treatment of depression. Measurement of fHbC during stimulation is informative in the clinical use of TMS.

The development of a novel high-precision major depressive disorder screening system using transient autonomic responses induced by dual mental tasks.

12.6% of major depressive disorder (MDD) patients have suicide intent, while it has been reported that 43% of patients did not consult their doctors for MDD, automated MDD screening is eagerly anticipated. Recently, in order to achieve automated screening of MDD, biomarkers such as multiplex DNA methylation profiles or physiological method using near infra-red spectroscopy (NIRS) have been studied, however, they require inspection using 96-well DNA ELIZA kit after blood sampling or significant cost. Using a single-lead electrocardiography (ECG), we developed a high-precision MDD screening system using transient autonomic responses induced by dual mental tasks. We developed a novel high precision MDD screening system which is composed of a single-lead ECG monitor, analogue to digital (AD) converter and a personal computer with measurement and analysis program written by LabView programming language. The system discriminates MDD patients from normal subjects using heat rate variability (HRV)-derived transient autonomic responses induced by dual mental tasks, i.e. verbal fluency task and random number generation task, via linear discriminant analysis (LDA) adopting HRV-related predictor variables (hear rate (HR), high frequency (HF), low frequency (LF)/HF). The proposed system was tested for 12 MDD patients (32 ± 15 years) under antidepressant treatment from Shizuoka Saiseikai General Hospital outpatient unit and 30 normal volunteers (37 ± 17 years) from Tokyo Metropolitan University. The proposed system achieved 100% sensitivity and 100% specificity in classifying 42 examinees into 12 MDD patients and 30 normal subjects. The proposed system appears promising for future HRV-based high-precision and low-cost screening of MDDs using only single-lead ECG.