Investigating Emotion EEG Patterns for Depression Detection with Attentive Simple Graph Convolutional Network.

Depression severely limits daily functioning, diminishes quality of life and possibly leads to self-harm and suicide. Noninvasive electroencephalography (EEG) has been shown effective as biomarkers for objective depression diagnose and treatment response prediction, and dry EEG electrodes further extend its availability for clinical use. Even though many efforts have been made to identify depression biomarkers, searching reliable EEG biomarkers for depression detection remains challenging. This work presents a systematic investigation of capabilities of emotion EEG patterns for depression detection using a dry EEG electrode system. We design an emotion elicitation paradigm with happy, neutral and sad emotions and collect EEG signals during film watching from 33 depressed patients and 40 healthy controls. The mean activation levels at frontal and temporal sites in the alpha, beta and gamma bands of the depressed group are different to those of the healthy group, indicating the impacts of depressive symptoms on the emotion experiences. To leverage the topology information among EEG channels for emotion recognition and depression detection, an Attentive Simple Graph Convolutional network is built. The deep depression-health classifier achieves a sensitivity of 81.93% and a specificity of 91.69% on the happy emotions, suggesting the promising use of the emotion neural patterns for distinguishing the depressed patients from the healthy controls.

Deep Depression Detection with Resting-State and Cognitive-Task EEG.

Depression is a common mental disorder that negatively affects physical health and personal, social and occupational functioning. Currently, accurate and objective diagnosis of depression remains challenging, and electroencephalography (EEG) provides promising clinical practice or home use due to considerable performance and low cost. This work investigates the capabilities of deep neural networks with EEG-based neural patterns from both resting states and cognitive tasks for depression detection. We collect EEG signals from 33 depressed patients and 40 healthy controls using wearable dry electrodes and build Attentive Simple Graph Convolutional network and Transformer neural network for objective depression detection. Four experiment stages, including two resting states and two cognitive tasks, are designed to characterize the alteration of relevant neural patterns in the depressed patients, in terms of decreased energy and impaired performance in sustained attention and response inhibition. The Transformer model achieves an AUC of 0.94 on the Continuous Performance Test-Identical Pairs version (sensitivity: 0.87, specificity: 0.91) and the Stroop Color Word Test (sensitivity: 0.93, specificity: 0.88), and an AUC of 0.89 on the two resting states (sensitivity: 0.85 and 0.87, specificity: 0.88 and 0.90, respectively), indicating the potential of EEG-based neural patterns in identifying depression. These findings provide new insights into the research of depression mechanisms and EEG-based depression biomarkers.

Frameless Robot-Assisted Asleep Centromedian Thalamic Nucleus Deep Brain Stimulation Surgery in Patients with Drug-Resistant Epilepsy: Technical Description and Short-Term Clinical Results.

INTRODUCTION: This purpose of this work is to give a detailed description of a surgical technique for frameless robot-assisted asleep deep brain stimulation (DBS) of the centromedian thalamic nucleus (CMT) in drug-resistant epilepsy (DRE). METHODS: Ten consecutively enrolled patients who underwent CMT-DBS were included in the study. The FreeSurfer "Thalamic Kernel Segmentation" module and experience target coordinates were used for locating the CMT, and quantitative susceptibility mapping (QSM) images were used to check the target. The patient's head was secured with a head clip, and electrode implantation was performed with the assistance of the neurosurgical robot Sinovation®. After opening the dura, the burr hole was continuously flushed with physiological saline to stop air from entering the skull. All procedures were performed under general anesthesia without intraoperative microelectrode recording (MER). RESULTS: The mean age of the patients at surgery and onset of seizures was 22 years (range 11-41 years) and 11 years (range 1-21 years), respectively. The median duration of seizures before CMT-DBS surgery was 10 years (2-26 years). CMT was successfully segmented, and its position was verified by experience target coordinates and QSM images in all ten patients. The mean surgical time for bilateral CMT-DBS in this cohort was 165 ± 18 min. The mean pneumocephalus volume was 2 cm3. The median absolute errors in the x-, y-, and z-axes were 0.7 mm, 0.5 mm, and 0.9 mm, respectively. The median Euclidean distance (ED) and radial error (RE) was 1.3 ± 0.5 mm and 1.0 ± 0.3 mm, respectively. No significant difference was found between right- and left-sided electrodes regarding the RE nor the ED. After a mean 12-month follow-up, the average reduction in seizures was 61%, and six patients experienced a ≥ 50% reduction in seizures, including one patient who had no seizures after the operation. All patients tolerated the anesthesia operation, and no permanent or serious complications were reported. CONCLUSIONS: Frameless robot-assisted asleep surgery is a precise and safe approach for placing CMT electrodes in patients with DRE, shortening the surgery time. The segmentation of the thalamic nuclei enables the precise location of the CMT, and the flow of physiological saline to seal the burr holes is a good way to reduce the influx of air. CMT-DBS is an effective method to reduce seizures.

The accuracy of a novel self-tapping bone fiducial marker for frameless robot-assisted stereo-electro-encephalography implantation and registration techniques.

BACKGROUND: We aimed to evaluate the accuracy and safety of a novel self-tapping bone fiducial as a registration technique for stereoelectroencephalography (SEEG) implantation. METHODS: Each patient was installed with five bone fiducial markers. All procedures were performed using the same Sinovation robot system. The accuracy was determined by calculating the target point error (TPE) and the entry point error (EPE) of electrodes. RESULTS: Fourteen patients underwent SEEG implantation surgery; and the average installation time of the markers per patient was 86.1 s. In the operating theatre, the average registration time was 206.6 s, and the average registration error was 0.18 mm. The average TPE of 174 electrodes was 1.98 mm and the average EPE was 0.88 mm. CONCLUSION: Our study provided a bone fiducial marker installation and registration technique that was convenient and fast, highly accurate in registration, and highly tolerated by patients.

Neural Correlates of Facial Emotion Recognition in Non-help-seeking University Students With Ultra-High Risk for Psychosis.

Background: Since the introduction of the neurodevelopmental perspective of schizophrenia research on individuals at ultra-high risk for psychosis (UHR) has gained increasing interest, aiming at early detection and intervention. Results from fMRI studies investigating behavioral and brain functional changes in UHR during facial emotion recognition, an essential component of social cognition, showed heterogenous results, probably due clinical diversity across these investigations. This fMRI study investigated emotion recognition in a sub-group of the UHR spectrum, namely non-help-seeking, drug-naïve UHR with high cognitive functioning to reveal the neurofunctional underpinnings of their social functioning in comparison to healthy controls. Methods: Two large cohorts of students from an elite University (n 1 = 4,040, n 2 = 4,364) were screened firstly with the Prodromal Questionnaires and by surpassing predefined cut-offs then interviewed with the semi-structured Interview for Psychosis-Risk Syndromes to verify their UHR status. Twenty-one identified non-help-seeking UHR and 23 non-UHR control subjects were scanned with functional magnetic resonance imaging while classifying emotions (i.e., neutral, happy, disgust and fear) in a facial emotion recognition task. Results: Behaviorally, no group differences were found concerning accuracy, reaction times, sensitivity or specificity, except that non-help-seeking UHR showed higher specificity when recognizing neutral facial expressions. In comparison to healthy non-UHR controls, non-help-seeking UHR showed generally higher activation in the superior temporal and left Heschl's gyrus as well as in the somatosensory, insular and midcingulate cortex than the control subjects during the entire recognition task regardless of the emotion categories. In an exploratory analysis, in the non-help-seeking UHR group, functional activity in the left superior temporal gyrus was significantly correlated with deficits in the ability to experience emotions at uncorrected statistical thresholds. Conclusions: Compared to healthy controls, non-help-seeking UHR show no behavioral deficits during facial emotion recognition, but functional hyperactivities in brain regions associated with this cognitive process. Our study may inspire future early intervention and provide loci for treatment using neural stimulation.

Association between Parents' Relationship, Emotion-Regulation Strategies, and Psychotic-like Experiences in Adolescents.

This study aimed to examine the association between the psychotic-like experiences (PLEs) and emotion-regulation (ER) strategies of adolescents and their parents' relationship, and we hypothesized that the parents' relationship moderates the link between ER strategies and PLEs. We recruited a total of 2708 first-year college students (1659 males and 1049 females) aged 15-20 years (mean = 17.9). Participants completed assessments of PLEs, their use of ER strategies, and reported their parents' relationship as harmonious, conflicting, or divorced. Regression analyses indicated that the lower the use of the emotion-reappraisal strategy, the greater the use of the emotion-suppression strategy and that parental conflict or divorce predicted the number of PLEs endorsed and the level of distress from the PLEs. The parents' relationship moderated the association between ER strategies and distress from PLEs. Among those who reported parental conflict or divorce, their lower use of the reappraisal strategy predicted their experiencing higher levels of distress from their PLEs. This study suggested the direct and interactive influence of the parents' relationship and ER strategies on the presence of PLEs and PLE-related distress levels among adolescents, which may represent potential intervention targets.

Robot-Assisted Percutaneous Balloon Compression for Trigeminal Neuralgia: Technique Description and Short-Term Clinical Results.

Objective: Percutaneous balloon compression (PBC) is a minimally invasive treatment for trigeminal neuralgia (TG) with a favorable cost-effectiveness ratio, but this technique has a steep learning curve. This study presents our initial clinical experience of robot-assisted PBC using a neurosurgical robot on six consecutive patients with TG. Methods: We fixed the patient's head with a skull clamp and connected it with the linkage arms of a Sinovation® neurosurgical robot, which was then registered using four bone fiducials by the robotic pointer. The puncture needle was positioned at the entry point on the skin using a robotic arm and advanced to the target point after the skin had been incised with a pointed surgical blade. This procedure was repeated for a second trajectory. A balloon was then advanced and inflated using 0.3 ml of a contrast agent. Upon injection of 0.6 ml contrast agent, the ganglion was kept compressed for 120 s. After removal of the balloon and puncture needle, compression of the face was performed to achieve hemostasis. Results: All patients achieved immediate pain relief following PBC. No permanent or severe complications were registered, and there was no pain recurrence in any of the patients during the follow-up period. Conclusions: Despite requiring a longer time for preoperative preparation, robot-assisted PBC provided a high degree of accuracy and safety, and it can also shorten the learning curve for surgeons unfamiliar with PBC. Robot-assisted surgical approaches should be further developed and adopted for PBC.

The Relationship Between Big Five Personality Traits and Psychotic Experience in a Large Non-clinical Youth Sample: The Mediating Role of Emotion Regulation.

Objective: Despite a long history of interest in personality traits and psychosis, the association between personality traits and psychotic experiences in the general population is not yet well understood. One possible factor that could influence the degree of distress from psychotic experiences is emotion regulation. The purpose of this study was to explore whether the association between personality and psychotic symptoms is already apparent in non-clinical youth as well as the mediating role of emotion regulation strategies between personality traits and psychotic experiences. Methods: Three thousand one hundred and forty seven college students were surveyed via self-report questionnaires measuring the Five-Factor model of personality, emotion regulation strategies, and psychotic experiences. Results: Neuroticism was found to be significantly positively correlated with psychotic experiences, while Extraversion, Openness, Agreeableness, and Conscientiousness were found to be significantly negatively correlated. Both the suppression and reappraisal strategies mediated the relationship between personality traits and psychotic experiences. Conclusion: Our findings suggest that youth with certain personality traits are more likely to have psychotic experiences. The reappraisal emotion regulation strategy could serve as a protective factor against the distress of psychotic experiences.

Comorbid Mental Disorders and 6-Month Symptomatic and Functioning Outcomes in Chinese University Students at Clinical High Risk for Psychosis.

BACKGROUND: High rates of non-psychotic psychopathological symptoms have been observed in clinical population at clinical high risk (CHR) for psychosis. These comorbid disorders affected the baseline functional level of CHR patients. However, little is known about the comorbid mental disorder in CHR individuals in non-clinical adolescent population. This study aimed to investigate the comorbid mental disorder in non-clinical CHR adolescents and the impact on attenuated psychosis symptoms (APS) as well as clinical outcome. METHODS: The sample consisted of 32 CHR students, who were screened from 2,800 university students. CHR status was evaluated with the Structured Interview of Prodromal Syndromes, comorbid mental disorder diagnoses with the International Neuropsychiatric Interview. RESULTS: In the CHR sample, 46.9% was found at least one non-psychotic comorbid mental disorder. The CHR participants presenting comorbid mental disorder had significantly more severity of APS than those without comorbid mental disorders, and the remission rate at 6-month follow-up is significantly higher in the individuals without comorbid mental disorders at baseline. CONCLUSION: In the non-clinical sample of individuals at CHR, non-psychotic comorbid mental disorders are common and anxiety disorder is most frequent. Copresence of anxiety and/or depression is related to higher level of attenuated psychotic symptoms and unfavorable clinical outcome at 6-month follow-up. Assessment and intervention in anxiety and depression for non-clinical CHR adolescents are suggested.