Autonomic nervous system responses in the intermediate band to cranial cutaneous stimulation.

Cardiovascular rhythms representing functional states of the autonomic nervous system (ANS) are insufficiently reflected by the current physiological model based on low and high frequency bands (LF, HF, resp.). An intermediate (IM) frequency band generated by a brainstem pacemaker was included in systemic physiological ANS analyses of forehead skin perfusion (SP), ECG, and respiration. Data of 38 healthy participants at T0 and T1 (+1 week) before, during, and following osteopathic cranial vault hold (CVH) stimulation were analyzed including momentary frequencies of highest amplitude, amplitudes in low (0.05-0.12 Hz), IM (0.12-0.18 Hz), and high (0.18-0.4 Hz) frequency bands, and established heart rate variability (HRV) metrics. During CVH, LF interval durations increased, whereas IM/HF band durations decreased significantly. Amplitudes increased significantly in all frequency bands. A cluster analysis found one response pattern dominated by IM activity (47% of participants) with highly stable 0.08 Hz oscillation to CVH, and one dominated by LF activity (0.10 Hz) at T0, increasing to IM activity at T1. Showing frequency ratios at ≈3:1, respiration was not responsible for oscillations in PPG during CVH. HRV revealed no significant responses. Rhythmic patterns in SP and respiration matched previous findings on a reticular "0.15 Hz rhythm". Involvement of baroreflex pathways is discussed as alternative explanation.

Auditory neural correlates and neuroergonomics of driving assistance in a simulated virtual environment.

Objective.Driver assistance systems play an increasingly important role in modern vehicles. In the current level of technology, the driver must continuously supervise the driving and intervene whenever necessary when using driving assistance systems. The driver's attentiveness plays an important role in this human-machine interaction. Our aim was to design a simplistic technical framework for studying neural correlates of driving situations in a functional magnetic resonance imaging (fMRI) setting. In this work we assessed the feasibility of our proposed platform.Methods.We proposed a virtual environment (VE) simulation of driver assistance as a framework to investigate brain states related to partially automated driving. We focused on the processing of auditory signals during different driving scenarios as they have been shown to be advantageous as warning stimuli in driving situations. This provided the necessary groundwork to study brain auditory attentional networks under varying environmental demands in an fMRI setting. To this end, we conducted a study with 20 healthy participants to assess the feasibility of the VE simulation.Results.We demonstrated that the proposed VE can elicit driving related brain activation patterns. Relevant driving events evoked, in particular, responses in the bilateral auditory, sensory-motor, visual and insular cortices, which are related to perceptual and behavioral processes during driving assistance. Conceivably, attentional mechanisms increased somatosensory integration and reduced interoception, which are relevant for requesting interactions during partially automated driving.Significance.In modern vehicles, driver assistance technologies are playing an increasingly prevalent role. It is important to study the interaction between these systems and drivers' attentional responses to aid in future optimizations of the assistance systems. The proposed VE provides a foundational first step in this endeavor. Such simulated VEs provide a safe setting for experimentation with driving behaviors in a semi-naturalistic environment.

The associations of Positive and Negative Valence Systems, Cognitive Systems and Social Processes on disease severity in anxiety and depressive disorders.

Background: Anxiety and depressive disorders share common features of mood dysfunctions. This has stimulated interest in transdiagnostic dimensional research as proposed by the Research Domain Criteria (RDoC) approach by the National Institute of Mental Health (NIMH) aiming to improve the understanding of underlying disease mechanisms. The purpose of this study was to investigate the processing of RDoC domains in relation to disease severity in order to identify latent disorder-specific as well as transdiagnostic indicators of disease severity in patients with anxiety and depressive disorders. Methods: Within the German research network for mental disorders, 895 participants (n = 476 female, n = 602 anxiety disorder, n = 257 depressive disorder) were recruited for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) and included in this cross-sectional study. We performed incremental regression models to investigate the association of four RDoC domains on disease severity in patients with affective disorders: Positive (PVS) and Negative Valance System (NVS), Cognitive Systems (CS) and Social Processes (SP). Results: The results confirmed a transdiagnostic relationship for all four domains, as we found significant main effects on disease severity within domain-specific models (PVS: ß = -0.35; NVS: ß = 0.39; CS: ß = -0.12; SP: ß = -0.32). We also found three significant interaction effects with main diagnosis showing a disease-specific association. Limitations: The cross-sectional study design prevents causal conclusions. Further limitations include possible outliers and heteroskedasticity in all regression models which we appropriately controlled for. Conclusion: Our key results show that symptom burden in anxiety and depressive disorders is associated with latent RDoC indicators in transdiagnostic and disease-specific ways.

Validation of subjective manual palpation using objective physiological recordings of the cranial rhythmic impulse during osteopathic manipulative intervention.

Intermediate (IM) band physiology in skin blood flow exhibits parallels with the primary respiratory mechanism (PRM) or cranial rhythmic impulse (CRI), controversial concepts of osteopathy in the cranial field (OCF). Owing to inconsistent manual palpation results, validity of evidence of PRM/CRI activity has been questionable. We therefore tried to validate manual palpation combining instrumented tracking and algorithmic objectivation of frequencies, amplitudes, and phases. Using a standard OCF intervention, cranial vault hold (CVH), two OCF experts palpated and digitally marked CRI frequencies in 25 healthy adults. Autonomic nervous system (ANS) activity in low frequency (LF) and IM band in photoplethysmographic (PPG) forehead skin recordings was probed with momentary frequency of highest amplitude (MFHA) and wavelet amplitude spectra (WAS) in examiners and participants. Palpation errors and frequency expectation bias during CVH were analyzed for phases of MFHA and CRI. Palpated CRI frequencies (0.05-0.08 Hz) correlated highly with mean MFHA frequencies with 1:1 ratio in 77% of participants (LF-responders; 0.072 Hz) and with 2:1 ratio in 23% of participants (IM-responders; 0.147 Hz). WAS analysis in both groups revealed integer number (harmonic) waves in (very) low and IM bands in > 98% of palpated intervals. Phase analyses in participants and examiners suggested synchronization between MFHA and CRI in a subset of LF-responders. IM band physiology in forehead PPG may offer a sensible physiological correlate of palpated CRI activity. Possible coordination or synchronization effects with additional physiological signals and between examiners and participants should be investigated in future studies.

Functional connectivity signatures of NMDAR dysfunction in schizophrenia-integrating findings from imaging genetics and pharmaco-fMRI.

Both, pharmacological and genome-wide association studies suggest N-methyl-D-aspartate receptor (NMDAR) dysfunction and excitatory/inhibitory (E/I)-imbalance as a major pathophysiological mechanism of schizophrenia. The identification of shared fMRI brain signatures of genetically and pharmacologically induced NMDAR dysfunction may help to define biomarkers for patient stratification. NMDAR-related genetic and pharmacological effects on functional connectivity were investigated by integrating three different datasets: (A) resting state fMRI data from 146 patients with schizophrenia genotyped for the disease-associated genetic variant rs7191183 of GRIN2A (encoding the NMDAR 2 A subunit) as well as 142 healthy controls. (B) Pharmacological effects of the NMDAR antagonist ketamine and the GABA-A receptor agonist midazolam were obtained from a double-blind, crossover pharmaco-fMRI study in 28 healthy participants. (C) Regional gene expression profiles were estimated using a postmortem whole-brain microarray dataset from six healthy donors. A strong resemblance was observed between the effect of the genetic variant in schizophrenia and the ketamine versus midazolam contrast of connectivity suggestive for an associated E/I-imbalance. This similarity became more pronounced for regions with high density of NMDARs, glutamatergic neurons, and parvalbumin-positive interneurons. From a functional perspective, increased connectivity emerged between striato-pallido-thalamic regions and cortical regions of the auditory-sensory-motor network, while decreased connectivity was observed between auditory (superior temporal gyrus) and visual processing regions (lateral occipital cortex, fusiform gyrus, cuneus). Importantly, these imaging phenotypes were associated with the genetic variant, the differential effect of ketamine versus midazolam and schizophrenia (as compared to healthy controls). Moreover, the genetic variant was associated with language-related negative symptomatology which correlated with disturbed connectivity between the left posterior superior temporal gyrus and the superior lateral occipital cortex. Shared genetic and pharmacological functional connectivity profiles were suggestive of E/I-imbalance and associated with schizophrenia. The identified brain signatures may help to stratify patients with a common molecular disease pathway providing a basis for personalized psychiatry.

Mapping Research Domain Criteria using a transdiagnostic mini-RDoC assessment in mental disorders: a confirmatory factor analysis.

This study aimed to build on the relationship of well-established self-report and behavioral assessments to the latent constructs positive (PVS) and negative valence systems (NVS), cognitive systems (CS), and social processes (SP) of the Research Domain Criteria (RDoC) framework in a large transnosological population which cuts across DSM/ICD-10 disorder criteria categories. One thousand four hundred and thirty one participants (42.1% suffering from anxiety/fear-related, 18.2% from depressive, 7.9% from schizophrenia spectrum, 7.5% from bipolar, 3.4% from autism spectrum, 2.2% from other disorders, 18.4% healthy controls, and 0.2% with no diagnosis specified) recruited in studies within the German research network for mental disorders for the Phenotypic, Diagnostic and Clinical Domain Assessment Network Germany (PD-CAN) were examined with a Mini-RDoC-Assessment including behavioral and self-report measures. The respective data was analyzed with confirmatory factor analysis (CFA) to delineate the underlying latent RDoC-structure. A revised four-factor model reflecting the core domains positive and negative valence systems as well as cognitive systems and social processes showed a good fit across this sample and showed significantly better fit compared to a one factor solution. The connections between the domains PVS, NVS and SP could be substantiated, indicating a universal latent structure spanning across known nosological entities. This study is the first to give an impression on the latent structure and intercorrelations between four core Research Domain Criteria in a transnosological sample. We emphasize the possibility of using already existing and well validated self-report and behavioral measurements to capture aspects of the latent structure informed by the RDoC matrix.

Real-time fMRI neurofeedback compared to cognitive behavioral therapy in a pilot study for the treatment of mild and moderate depression.

Real-time functional magnetic resonance imaging (rt-fMRI) neurofeedback was found to reduce depressive symptoms. However, no direct comparison of drug-free patients with an active psychotherapy control group is available. The present study compared rt-fMRI neurofeedback with cognitive behavioral therapy, as the standard treatment in patients declining anti-depressants. Twenty adult, drug-free patients with mild or moderate depression were non-randomly assigned either to a course of eight half-hour sessions of neurofeedback targeting the left medial prefrontal cortex (N = 12) or to a 16-session course of cognitive behavioral therapy (N = 8). Montgomery-Asberg Depression Rating Scale was introduced at baseline, mid-treatment, and end-treatment points. In each group, 8 patients each remained in the study to a mid-treatment evaluation and 6 patients each to the study end-point. ANOVA revealed a depression reduction with a significant effect of Time (F(3,6) = 19.0, p < 0.001, η2 = 0.76). A trend to greater improvement in the cognitive behavioral therapy group compared to neurofeedback emerged (Group × Time; p = 0.078). Percent signal change in the region of interest between up- and down-regulation conditions was significantly correlated with session number (Pearson's r = 0.85, p < 0.001) indicating a learning effect. As limitations, small sample size could lead to insufficient power and non-random allocation to selection bias. Both neurofeedback and cognitive behavioral therapy improved mild and moderate depression. Neurofeedback was not superior to cognitive behavioral therapy. Noteworthy, the neurofeedback training course was associated with continuous improvement in the self-regulation skill, without plateau. This study delivers data to plan clinical trials comparing neurofeedback with cognitive behavioral interventions.

Anxiety and Depression in Adults With Congenital Heart Disease.

Introduction: Anxiety and depression can worsen outcome in patients with heart disease. We elucidate the prevalence of anxiety and depression in a cohort of adults with congenital heart disease (ACHD). Materials and Methods: Prospective screening for anxiety or depression was performed in 204 consecutive patients of the outpatient clinic of our tertiary care center using the Hospital Anxiety and Depression Scale (HADS) questionnaire and the distress thermometer (DT) as a potential ultra-short screening test. Functional data were assessed at liberty of the responsible physician. HADS scores ≥ 8 were considered doubtful and scores ≥ 11 as confirmed cases of anxiety or depression, respectively. HADS results were compared with a historical group of 100 patients with non-Hodgkin Lymphoma (NHL) as well as German reference values from the literature. Results: Patients from the ACHD cohort were 28 ± 10 years old (mean ± SD, 54% male), 34% had a simple, 51% a moderate, including 52 patients with transposition of the great arteries after arterial switch operation, and 15% a heart defect of severe complexity. Prevalence of depression in ACHD was comparable to the German normal population (5.9% ACHD vs. 5.4% control). In contrast, prevalence of anxiety was higher than expected from reference values (12.7% ACHD vs. 5.6% control). There was a positive association between psychological distress and NYHA class [anxiety: OR 2.67 (95% CI, 1.50-4.76) p = 0.001; depression: OR 2.93 (95% CI, 1.60-5.35) p = 0.0005], but not with age, gender, or heart defect severity. Percentages of patients with ACHD with anxiety were significantly higher than in a cohort of patients with indolent non-Hodgkin lymphoma (NHL) but comparable to those with aggressive NHL (HADS-A ≥ 11: ACHD 12.7%, indolent NHL 2.2%, aggressive NHL 13.2%; p = 0.037 ACHD vs. indolent NHL; p = 0.929 ACHD vs. aggressive NHL). The distress thermometer screening test had only a fair discriminatory ability (AUC 0.708; p = 0.002) and is therefore of limited usability. Conclusion: Adults with congenital heart disease exhibit an increased risk for anxiety disorders independently of the severity of the underlying heart defect. Anxiety prevalence was comparable to a historical cohort of patients with aggressive NHL underlining the importance of a routine screening for psychosocial distress in adults with congenital heart disease.

Shared network-level functional alterations across substance use disorders: A multi-level kernel density meta-analysis of resting-state functional connectivity studies.

An increasing number of neuroimaging studies indicate functional alterations in cortico-striatal loops in individuals with substance use disorders (SUD). Dysregulations in these circuits may contribute to drug-seeking and drug-consuming behaviour by impeding inhibitory control, habit formation, and reward processing. Despite evidence of network-level changes in SUD, a shared pattern of functional alterations within and between spatially distributed brain networks has not been systematically investigated. The present meta-analytic investigation aims at identifying common alterations in resting-state functional connectivity patterns across different SUD, including stimulant, heroin, alcohol, cannabis, and nicotine use. To this aim, seed-based whole-brain connectivity maps for different functional networks were extracted and subjected to multi-level kernel density analysis to identify dysfunctional networks in individuals with SUD compared with healthy controls. In addition, an exploratory analysis examined substance-specific effects as well as the influence of drug use status on the main findings. Our findings indicate a hypoconnectivity pattern for the limbic, salience, and frontoparietal networks in individuals with SUD as compared with healthy controls. The default mode network additionally exhibited a complex pattern of hypo- and hyperconnectivity across the studies. The observed disrupted connectivity between networks in SUD may associate with deficient inhibitory control mechanisms that are thought to contribute to excessive craving and automatic drug-related behaviour as well as failure in substance use cessation. The identified network-based alterations in SUD represent potential treatment targets for neuromodulation, for example, network-based real-time functional magnetic resonance imaging (fMRI) neurofeedback. Such interventions can evaluate the behavioural relevance of the identified neural circuits.

The Interplay between Vitamin D, Exposure of Anticholinergic Antipsychotics and Cognition in Schizophrenia.

Vitamin D deficiency is a frequent finding in schizophrenia and may contribute to neurocognitive dysfunction, a core element of the disease. However, there is limited knowledge about the neuropsychological profile of vitamin D deficiency-related cognitive deficits and their underlying molecular mechanisms. As an inductor of cytochrome P450 3A4, a lack of vitamin D might aggravate cognitive deficits by increased exposure to anticholinergic antipsychotics. This cross-sectional study aims to assess the relationship between 25-OH-vitamin D-serum concentrations, anticholinergic drug exposure and neurocognitive functioning (Brief Assessment of Cognition in Schizophrenia, BACS, and Trail Making Test, TMT) in 141 patients with schizophrenia. The anticholinergic drug exposure was estimated by adjusting the concentration of each drug for its individual muscarinic receptor affinity. Using regression analysis, we observed a positive relationship between vitamin D levels and processing speed (TMT-A and BACS Symbol Coding) as well as executive functioning (TMT-B and BACS Tower of London). Moreover, a negative impact of vitamin D on anticholinergic drug exposure emerged, but the latter did not significantly affect cognition. When other cognitive items were included as regressors, the impact of vitamin D remained only significant for the TMT-A. Among the different cognitive impairments in schizophrenia, vitamin D deficiency may most directly affect processing speed, which in turn may aggravate deficits in executive functioning. This finding is not explained by a cytochrome P450-mediated increased exposure to anticholinergic antipsychotics.

EEG Spectral Changes Linked to Psychiatric Medications: Computational Pipeline for Data Mining and Analysis.

The presented computational pipeline is designed to analyze drug-induced changes in EEG data from the Temple University EEG Corpus. The data is cleaned from artifacts, pre-processed, the averaged absolute and relative frequency powers are calculated and compared to a control group. Thus, different research hypotheses can be tested with the intention to reuse accessible data collections.

The negative impact of vitamin D on antipsychotic drug exposure may counteract its potential benefits in schizophrenia.

AIMS: Patients with schizophrenia frequently show insufficient vitamin D levels, which are associated with somatic comorbidity and may contribute to psychopathology. For many reasons, vitamin D supplementation may be indicated for this patient cohort. However, there is growing evidence for a vitamin D-mediated increase of drug metabolism by induction of cytochrome P450 (CYP) 3A4. Hence, this study aimed to assess vitamin D's impact on both antipsychotic drug concentrations and psychopathology in a non-interventional manner. METHODS: Totals of 107 serum concentrations of different antipsychotic drugs (amisulpride, aripiprazole, clozapine, olanzapine, quetiapine and risperidone), 80 serum concentrations of vitamin D and psychopathological assessments were obtained from 80 patients with schizophrenia. The impact of Vitamin D on antipsychotic drug concentrations and symptomatology was assessed using a generalized linear model, path and correlation analyses. RESULTS: We observed a negative relationship between vitamin D and dose-adjusted antipsychotic drug concentrations, which was particularly pronounced for drugs which are predominantly metabolized via CYP3A4 (i.e., aripiprazole and quetiapine). A path analysis suggested a relieving effect of vitamin D on symptomatology which was, however, counteracted by its negative impact on antipsychotic drug levels. Finally, patients with vitamin D levels above the median exhibited a significantly higher proportion of therapeutically insufficient dose-normalized drug concentrations of aripiprazole and quetiapine. CONCLUSION: Despite vitamin D's potential benefits on physical and mental health, clinicians should be aware of its negative impact on blood concentrations of antipsychotics metabolized by CYP3A4 in patients with schizophrenia. Therefore, when considering its supplementation, therapeutic drug monitoring should be applied to guide dose adjustment.

Deep Learning-based detection of psychiatric attributes from German mental health records.

BACKGROUND: Health care records provide large amounts of data with real-world and longitudinal aspects, which is advantageous for predictive analyses and improvements in personalized medicine. Text-based records are a main source of information in mental health. Therefore, application of text mining to the electronic health records - especially mental state examination - is a key approach for detection of psychiatric disease phenotypes that relate to treatment outcomes. METHODS: We focused on the mental state examination (MSE) in the patients' discharge summaries as the key part of the psychiatric records. We prepared a sample of 150 text documents that we manually annotated for psychiatric attributes and symptoms. These documents were further divided into training and test sets. We designed and implemented a system to detect the psychiatric attributes automatically and linked the pathologically assessed attributes to AMDP terminology. This workflow uses a pre-trained neural network model, which is fine-tuned on the training set, and validated on the independent test set. Furthermore, a traditional NLP and rule-based component linked the recognized mentions to AMDP terminology. In a further step, we applied the system on a larger clinical dataset of 510 patients to extract their symptoms. RESULTS: The system identified the psychiatric attributes as well as their assessment (normal and pathological) and linked these entities to the AMDP terminology with an F1-score of 86% and 91% on an independent test set, respectively. CONCLUSION: The development of the current text mining system and the results highlight the feasibility of text mining methods applied to MSE in electronic mental health care reports. Our findings pave the way for the secondary use of routine data in the field of mental health, facilitating further clinical data analyses.

Transdiagnostic alterations in neural emotion regulation circuits - neural substrates of cognitive reappraisal in patients with depression and post-traumatic stress disorder.

BACKGROUND: Impaired cognitive reappraisal, associated with the social functioning and well-being of patients affected by mood or anxiety disorders, is characterized by distinct neural activation patterns across clinical populations. To date, studies dedicated to identifying common and distinct neural activation profiles need to be clarified. The aim of the present study was to investigate transdiagnostic differences and commonalities in brain activation patterns during reappraisal-mediated downregulation of emotions. METHODS: Cognitive reappraisal of negative images was contrasted with maintaining emotions during a control viewing condition. Brain activation in 35 patients with major depressive disorder (MDD), 20 patients with post-traumatic stress disorder (PTSD), and 34 healthy controls (HC) during cognitive reappraisal was compared. Moreover, the neural circuitry of emotion regulation in these clinical populations was examined using seed-to-voxel and voxel-to-voxel functional connectivity analyses. RESULTS: Whole-brain fMRI analyses showed less right-lateralized activation of the inferior, middle, and superior frontal gyrus during cognitive reappraisal compared to viewing of negative images in MDD and PTSD patients compared to HCs. Right IFG activation was negatively correlated with the severity of anxiety and depressive symptomatology. In addition, increased seed-to-voxel connectivity of the right IFG as well as increased voxel-to-voxel connectivity was observed in PTSD patients compared to HCs and MDD patients. CONCLUSIONS: FMRI results therefore suggested a common deficit of depression and anxiety symptomatology reflected by reduced activation in right IFG during cognitive reappraisal as well as diagnosis specific effects in patients with PTSD based on seed-to-voxel and voxel-to-voxel connectivity showing an overactive and hyperconnected salience network. Findings highlight the role of transdiagnostic research to identify disorder specific brain patterns as well as patterns common across disorders.

fMRI Neurofeedback-Enhanced Cognitive Reappraisal Training in Depression: A Double-Blind Comparison of Left and Right vlPFC Regulation.

Affective disorders are associated with maladaptive emotion regulation strategies. In particular, the left more than the right ventrolateral prefrontal cortex (vlPFC) may insufficiently regulate emotion processing, e.g., in the amygdala. A double-blind cross-over study investigated NF-supported cognitive reappraisal training in major depression (n = 42) and age- and gender-matched controls (n = 39). In a randomized order, participants trained to upregulate either the left or the right vlPFC during cognitive reappraisal of negative images on two separate days. We wanted to confirm regional specific NF effects with improved learning for left compared to right vlPFC (ClinicalTrials.gov NCT03183947). Brain responses and connectivity were studied with respect to training progress, gender, and clinical outcomes in a 4-week follow-up. Increase of vlPFC activity was stronger after NF training from the left- than the right-hemispheric ROI. This regional-specific NF effect during cognitive reappraisal was present across patients with depression and controls and supports a central role of the left vlPFC for cognitive reappraisal. Further, the activity in the left target region was associated with increased use of cognitive reappraisal strategies (r = 0.48). In the 4-week follow-up, 75% of patients with depression reported a successful application of learned strategies in everyday life and 55% a clinically meaningful symptom improvement suggesting clinical usability.

Data-Driven Approach to the Analysis of Real-Time FMRI Neurofeedback Data: Disorder-Specific Brain Synchrony in PTSD.

Brain-computer interfaces (BCIs) can be used in real-time fMRI neurofeedback (rtfMRI NF) investigations to provide feedback on brain activity to enable voluntary regulation of the blood-oxygen-level dependent (BOLD) signal from localized brain regions. However, the temporal pattern of successful self-regulation is dynamic and complex. In particular, the general linear model (GLM) assumes fixed temporal model functions and misses other dynamics. We propose a novel data-driven analyses approach for rtfMRI NF using intersubject covariance (ISC) analysis. The potential of ISC was examined in a reanalysis of data from 21 healthy individuals and nine patients with post-traumatic stress-disorder (PTSD) performing up-regulation of the anterior cingulate cortex (ACC). ISC in the PTSD group differed from healthy controls in a network including the right inferior frontal gyrus (IFG). In both cohorts, ISC decreased throughout the experiment indicating the development of individual regulation strategies. ISC analyses are a promising approach to reveal novel information on the mechanisms involved in voluntary self-regulation of brain signals and thus extend the results from GLM-based methods. ISC enables a novel set of research questions that can guide future neurofeedback and neuroimaging investigations.

Tracking of Mental Workload with a Mobile EEG Sensor.

The aim of the present investigation was to assess if a mobile electroencephalography (EEG) setup can be used to track mental workload, which is an important aspect of learning performance and motivation and may thus represent a valuable source of information in the evaluation of cognitive training approaches. Twenty five healthy subjects performed a three-level N-back test using a fully mobile setup including tablet-based presentation of the task and EEG data collection with a self-mounted mobile EEG device at two assessment time points. A two-fold analysis approach was chosen including a standard analysis of variance and an artificial neural network to distinguish the levels of cognitive load. Our findings indicate that the setup is feasible for detecting changes in cognitive load, as reflected by alterations across lobes in different frequency bands. In particular, we observed a decrease of occipital alpha and an increase in frontal, parietal and occipital theta with increasing cognitive load. The most distinct levels of cognitive load could be discriminated by the integrated machine learning models with an accuracy of 86%.

Judgmental perception of co-speech gestures in MDD.

Cognitive bias in depression may increase sensitivity to judgmental appraisal of communicative cues. Nonverbal communication encompassing co-speech gestures is crucial for social functioning and is perceived differentially by men and women, however, little is known about the effect of depression on the perception of appraisal. We investigate if a cognitive bias influences the perception of appraisal and judgement of nonverbal communication in major depressive disorder (MDD). During watching videos of speakers retelling a story and gesticulating, 22 patients with MDD and 22 matched healthy controls pressed a button when they perceived the speaker as appraising in a positive or negative way. The speakers were presented in four different conditions (with and without speech and with natural speaker or as stick-figures) to evaluate context effects. Inter-subject covariance (ISC) of the button-press time series measured consistency across the groups of the response pattern depending on the factors diagnosis and gender. Significant effects emerged for the factors diagnosis (p = .002), gender (p = .007), and their interaction (p < .001). The female healthy controls perceived the gestures more consistently appraising than male controls, the female patients, and male patients whereas the latter three groups did not differ. Further, the ISC measure for consistency correlated negatively with depression severity. The natural speaker video without audio speech yielded the highest responses consistency. Indeed co-speech gestures may drive these ISC effects because number of gestures but not facial shrugs correlated with ISC amplitude. During co-speech gestures, a cognitive bias led to disturbed perception of appraisal in MDD for females. Social communication is critical for functional outcomes in mental disorders; thus perception of gestural communication is important in rehabilitation.

Clinical Application of Real-Time fMRI-Based Neurofeedback for Depression.

Real-time functional magnetic resonance imaging-based neurofeedback (rt-fMRI NF) is a recent technique used to train self-regulation of circumscribed brain areas or networks. For clinical applications in depression, NF training targets brain areas with disturbed activation patterns, such as heightened reactivity of amygdala in response to negative stimuli, in order to normalize the neurophysiology and their behavioral correlates. Recent studies have targeted emotion processing areas such as the amygdala, the salience network, and top-down control areas such as the lateral prefrontal cortex. Different methods of rt-fMRI-based NF in depression, their potential for clinical improvement, and most recent advancements of this technology are discussed considering their role for future clinical applications. Initial findings of randomized controlled trials show promising results. However, for lasting treatment effects, clinical efficiency and optimal target regions, tasks, control conditions, and duration of training need to be established.