Alexithymia Is Associated With Deficits in Visual Search for Emotional Faces in Clinical Depression

Background: The concept of alexithymia is characterized by difficulties identifying and describing one’s emotions. Alexithymic individuals are impaired in the recognition of others’ emotional facial expressions. Alexithymia is quite common in patients suffering from major depressive disorder. The face-in-the-crowd task is a visual search paradigm that assesses processing of multiple facial emotions. In the present eye-tracking study, the relationship between alexithymia and visual processing of facial emotions was examined in clinical depression. Materials and Methods: Gaze behavior and manual response times of 20 alexithymic and 19 non-alexithymic depressed patients were compared in a face-in-the-crowd task. Alexithymia was empirically measured via the 20-item Toronto Alexithymia-Scale. Angry, happy, and neutral facial expressions of different individuals were shown as target and distractor stimuli. Our analyses of gaze behavior focused on latency to the target face, number of distractor faces fixated before fixating the target, number of target fixations, and number of distractor faces fixated after fixating the target. Results: Alexithymic patients exhibited in general slower decision latencies compared to non-alexithymic patients in the face-in-the-crowd task. Patient groups did not differ in latency to target, number of target fixations, and number of distractors fixated prior to target fixation. However, after having looked at the target, alexithymic patients fixated more distractors than non-alexithymic patients, regardless of expression condition. Discussion: According to our results, alexithymia goes along with impairments in visual processing of multiple facial emotions in clinical depression. Alexithymia appears to be associated with delayed manual reaction times and prolonged scanning after the first target fixation in depression, but it might have no impact on the early search phase. The observed deficits could indicate difficulties in target identification and/or decision-making when processing multiple emotional facial expressions. Impairments of alexithymic depressed patients in processing emotions in crowds of faces seem not limited to a specific affective valence. In group situations, alexithymic depressed patients might be slowed in processing interindividual differences in emotional expressions compared with non-alexithymic depressed patients. This could represent a disadvantage in understanding non-verbal communication in groups

Evoked potentials and behavioral performance during different states of brain arousal

Additional file 4. Paired sample t-tests for comparisons of EPs and behavioral performance between EEG-vigilance (sub-)stages

The Big Five Personality Traits and Brain Arousal in the Resting State

Based on Eysenck’s biopsychological trait theory, brain arousal has long been considered to explain individual differences in human personality. Yet, results from empirical studies remained inconclusive. However, most published results have been derived from small samples and, despite inherent limitations, EEG alpha power has usually served as an exclusive indicator for brain arousal. To overcome these problems, we here selected N = 468 individuals of the LIFE-Adult cohort and investigated the associations between the Big Five personality traits and brain arousal by using the validated EEG- and EOG-based analysis tool VIGALL. Our analyses revealed that participants who reported higher levels of extraversion and openness to experience, respectively, exhibited lower levels of brain arousal in the resting state. Bayesian and frequentist analysis results were especially convincing for openness to experience. Among the lower-order personality traits, we obtained the strongest evidence for neuroticism facet ‘impulsivity’ and reduced brain arousal. In line with this, both impulsivity and openness have previously been conceptualized as aspects of extraversion. We regard our findings as well in line with the postulations of Eysenck and consistent with the recently proposed ‘arousal regulation model’. Our results also agree with meta-analytically derived effect sizes in the field of individual differences research, highlighting the need for large (collaborative) studies.Peer Reviewe

Genetic association of objective sleep phenotypes with a functional polymorphism in the neuropeptide S receptor gene

Background: The neuropeptide S receptor (NPSR1) and its ligand neuropeptide S (NPS) have received increased attention in the last few years, as both establish a previously unknown system of neuromodulation. Animal research studies have suggested that NPS may be involved in arousal/wakefulness and may also have a crucial role in sleep regulation. The single nucleotide polymorphism (SNP) rs324981 in NPSR1 has begun to shed light on a function of the NPS-system in human sleep regulation. Due to an amino acid exchange, the T-allele leads to an increased sensitivity of the NPSR1. In the only genomewide association study to date on circadian sleep parameters in humans, an association was found between rs324981 and regular bedtime. However, the sleep parameters in this study were only measured by self-rating. Therefore, our study aimed to replicate these findings using an objective measure of sleep. Methods: The study included n = 393 white subjects (62–79 years) who participated in an actigraphic assessment for determining sleep duration, rest duration, sleep onset, rest onset and sleep onset latency. Genotyping of the SNP rs324981 was performed using the TaqMan OpenArray System. Results: The genotype at rs324981 was not significantly associated with rest onset (bedtime) or sleep onset (p = .146 and p = .199, respectively). However, the SNP showed a significant effect on sleep- and rest duration (p = .007 and p = .003, respectively). Subjects that were homozygous for the minor T-allele had a significantly decreased sleep- and rest duration compared to A-allele carriers. Conclusion: The results of this study indicate that the sleep pattern in humans is influenced by the NPS-system. However, the previously reported association between bedtime and rs324981 could not be confirmed. The current finding of decreased sleep duration in T/T allele carriers is in accordance with studies in rodents reporting similar results after NPS application.:Background; Methods; Results; Conclusion

Depression Diagnosis using Deep Convolutional Neural Networks

Depression is a prevalent psychiatric disorder that impacts the quality of life of 300 million people around the world. The complex nature of depression manifestations in patients and the lack of technological advances in the diagnosis process has left a lot of room for improvement in this particular domain. At present, the diagnosis is mainly made by physicians during a conversation comprising the exploration of the symptoms and the diagnostic criteria for depression. Recently, the electroencephalography (EEG) has regained interest as a promising approach to provide bio-markers which are of clinical value in the diagnostic process and for response prediction to therapy. In the present landscape, even the addition of EEG data has resulted in a semi-automated process, where the expert still has to heavily modify the raw data. This adds an inherent bias to the process based on the expert and incurs costs as well as time to the process of diagnosis. In this paper, we present a fast, effective and automated method that is able to quickly determine if the patient has depression while still maintaining a high accuracy of diagnosis. Our approach is built on using raw EEG-data, performing frequency domain preprocessing in order to split the data into its different frequency domains and to create EEG ’images’. These images are then treated by a convolutional neural network, which is a novel approach in this area. Experimental results have shown to provide outstanding results and to work without the need for feature engineering or any human interaction, which is a core strength of the model we are proposing

Singular nonlinear (n-1,1) conjugate boundary value problems

Solutions are obtained for the boundary value problem, y (n) + f(x,y) = 0, y (i)(0) = y(1) = 0, 0 i n – 2, where f(x,y) is singular at y = 0. An application is made of a fixed point theorem for operators that are decreasing with respect to a cone

Fatigue in Cancer and Neuroinflammatory and Autoimmune Disease: CNS Arousal Matters

The term fatigue is not only used to describe a sleepy state with a lack of drive, as observed in patients with chronic physical illnesses, but also a state with an inhibition of drive and central nervous system (CNS) hyperarousal, as frequently observed in patients with major depression. An electroencephalogram (EEG)-based algorithm has been developed to objectively assess CNS arousal and to disentangle these pathophysiologically heterogeneous forms of fatigue. The aim of this study was to test the hypothesis that fatigued patients with CNS hyperarousal score higher on depressive symptoms than those without this neurophysiological pattern. Methods: Subjects with fatigue (Multidimensional Fatigue Inventory sum-score > 40) in the context of cancer, neuroinflammatory, or autoimmune diseases were drawn from the 60+ cohort of the Leipzig Research Center for Civilization Diseases. CNS arousal was assessed by automatic EEG-vigilance stage classification using the Vigilance Algorithm Leipzig (VIGALL 2.1) based on 20 min EEG recordings at rest with eyes closed. Depression was assessed by the Inventory of Depressive Symptomatology (IDS-SR). Results: Sixty participants (33 female; median age: 67.5 years) were included in the analysis. As hypothesized, fatigued patients with CNS hyperarousal had higher IDS-SR scores than those without hyperarousal (F1,58 = 18.34; p < 0.0001, η2 = 0.240). Conclusion: hyperaroused fatigue in patients with chronic physical illness may be a sign of comorbid depression.Peer Reviewe

Alexithymia Is Associated With Deficits in Visual Search for Emotional Faces in Clinical Depression

Background: The concept of alexithymia is characterized by difficulties identifying and describing one’s emotions. Alexithymic individuals are impaired in the recognition of others’ emotional facial expressions. Alexithymia is quite common in patients suffering from major depressive disorder. The face-in-the-crowd task is a visual search paradigm that assesses processing of multiple facial emotions. In the present eye-tracking study, the relationship between alexithymia and visual processing of facial emotions was examined in clinical depression. Materials and Methods: Gaze behavior and manual response times of 20 alexithymic and 19 non-alexithymic depressed patients were compared in a face-in-the-crowd task. Alexithymia was empirically measured via the 20-item Toronto Alexithymia-Scale. Angry, happy, and neutral facial expressions of different individuals were shown as target and distractor stimuli. Our analyses of gaze behavior focused on latency to the target face, number of distractor faces fixated before fixating the target, number of target fixations, and number of distractor faces fixated after fixating the target. Results: Alexithymic patients exhibited in general slower decision latencies compared to non-alexithymic patients in the face-in-the-crowd task. Patient groups did not differ in latency to target, number of target fixations, and number of distractors fixated prior to target fixation. However, after having looked at the target, alexithymic patients fixated more distractors than non-alexithymic patients, regardless of expression condition. Discussion: According to our results, alexithymia goes along with impairments in visual processing of multiple facial emotions in clinical depression. Alexithymia appears to be associated with delayed manual reaction times and prolonged scanning after the first target fixation in depression, but it might have no impact on the early search phase. The observed deficits could indicate difficulties in target identification and/or decision-making when processing multiple emotional facial expressions. Impairments of alexithymic depressed patients in processing emotions in crowds of faces seem not limited to a specific affective valence. In group situations, alexithymic depressed patients might be slowed in processing interindividual differences in emotional expressions compared with non-alexithymic depressed patients. This could represent a disadvantage in understanding non-verbal communication in groups

Alexithymia Is Associated With Deficits in Visual Search for Emotional Faces in Clinical Depression

Background: The concept of alexithymia is characterized by difficulties identifying and describing one’s emotions. Alexithymic individuals are impaired in the recognition of others’ emotional facial expressions. Alexithymia is quite common in patients suffering from major depressive disorder. The face-in-the-crowd task is a visual search paradigm that assesses processing of multiple facial emotions. In the present eye-tracking study, the relationship between alexithymia and visual processing of facial emotions was examined in clinical depression. Materials and Methods: Gaze behavior and manual response times of 20 alexithymic and 19 non-alexithymic depressed patients were compared in a face-in-the-crowd task. Alexithymia was empirically measured via the 20-item Toronto Alexithymia-Scale. Angry, happy, and neutral facial expressions of different individuals were shown as target and distractor stimuli. Our analyses of gaze behavior focused on latency to the target face, number of distractor faces fixated before fixating the target, number of target fixations, and number of distractor faces fixated after fixating the target. Results: Alexithymic patients exhibited in general slower decision latencies compared to non-alexithymic patients in the face-in-the-crowd task. Patient groups did not differ in latency to target, number of target fixations, and number of distractors fixated prior to target fixation. However, after having looked at the target, alexithymic patients fixated more distractors than non-alexithymic patients, regardless of expression condition. Discussion: According to our results, alexithymia goes along with impairments in visual processing of multiple facial emotions in clinical depression. Alexithymia appears to be associated with delayed manual reaction times and prolonged scanning after the first target fixation in depression, but it might have no impact on the early search phase. The observed deficits could indicate difficulties in target identification and/or decision-making when processing multiple emotional facial expressions. Impairments of alexithymic depressed patients in processing emotions in crowds of faces seem not limited to a specific affective valence. In group situations, alexithymic depressed patients might be slowed in processing interindividual differences in emotional expressions compared with non-alexithymic depressed patients. This could represent a disadvantage in understanding non-verbal communication in groups

Fatigue and brain arousal in patients with major depressive disorder

Fatigue is considered a key symptom of major depressive disorder (MDD), yet the term lacks specificity. It can denote a state of increased sleepiness and lack of drive (i.e., downregulated arousal) as well as a state of high inner tension and inhibition of drive with long sleep onset latencies (i.e., upregulated arousal), the latter typically found in depression. It has been proposed to differentiate fatigue along the dimension of brain arousal. We investigated whether such stratification within a group of MDD patients would reveal a subgroup with distinct clinical features. Using an automatic classification of EEG vigilance stages, an arousal stability score was calculated for 15-min resting EEGs of 102 MDD patients with fatigue. 23.5% of the patients showed signs of hypoarousal with EEG patterns indicating drowsiness or sleep; this hypoaroused subgroup was compared with remaining patients (non-hypoaroused subgroup) concerning self-rated measures of depressive symptoms, sleepiness, and sleep. The hypoaroused subgroup scored higher on the Beck Depression Inventory items 'loss of energy' (Z = - 2.13, p = 0.033; (2) = 0.044, 90% CI 0.003-0.128) and 'concentration difficulty' (Z = - 2.40, p = 0.017; (2) = 0.056, 90% CI 0.009-0.139), and reported higher trait and state sleepiness (p &amp;lt; 0.05) as compared to the non-hypoaroused group. The non-hypoaroused subgroup, in contrast, reported more frequently the presence of suicidal ideation (Chi(2) = 3.81, p = 0.051; (2) = 0.037, 90% CI 0.0008-0.126). In this study, we found some evidence that stratifying fatigued MDD patients by arousal may lead to subgroups that are pathophysiologically and clinically more homogeneous. Brain arousal may be a worth while target in clinical research for better understanding the mechanisms underlying suicidal tendencies and to improve treatment response