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.

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.

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.

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.

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.

Supramodal neural networks support top-down processing of social signals.

The perception of facial and vocal stimuli is driven by sensory input and cognitive top-down influences. Important top-down influences are attentional focus and supramodal social memory representations. The present study investigated the neural networks underlying these top-down processes and their role in social stimulus classification. In a neuroimaging study with 45 healthy participants, we employed a social adaptation of the Implicit Association Test. Attentional focus was modified via the classification task, which compared two domains of social perception (emotion and gender), using the exactly same stimulus set. Supramodal memory representations were addressed via congruency of the target categories for the classification of auditory and visual social stimuli (voices and faces). Functional magnetic resonance imaging identified attention-specific and supramodal networks. Emotion classification networks included bilateral anterior insula, pre-supplementary motor area, and right inferior frontal gyrus. They were pure attention-driven and independent from stimulus modality or congruency of the target concepts. No neural contribution of supramodal memory representations could be revealed for emotion classification. In contrast, gender classification relied on supramodal memory representations in rostral anterior cingulate and ventromedial prefrontal cortices. In summary, different domains of social perception involve different top-down processes which take place in clearly distinguishable neural networks.

Putamen volume predicts real-time fMRI neurofeedback learning success across paradigms and neurofeedback target regions.

Real-time fMRI guided neurofeedback training has gained increasing interest as a noninvasive brain regulation technique with the potential to modulate functional brain alterations in therapeutic contexts. Individual variations in learning success and treatment response have been observed, yet the neural substrates underlying the learning of self-regulation remain unclear. Against this background, we explored potential brain structural predictors for learning success with pooled data from three real-time fMRI data sets. Our analysis revealed that gray matter volume of the right putamen could predict neurofeedback learning success across the three data sets (n = 66 in total). Importantly, the original studies employed different neurofeedback paradigms during which different brain regions were trained pointing to a general association with learning success independent of specific aspects of the experimental design. Given the role of the putamen in associative learning this finding may reflect an important role of instrumental learning processes and brain structural variations in associated brain regions for successful acquisition of fMRI neurofeedback-guided self-regulation.

Common neurofunctional dysregulations characterize obsessive-compulsive, substance use, and gaming disorders-An activation likelihood meta-analysis of functional imaging studies.

Compulsivity and loss of behavioral control represent core symptoms in obsessive-compulsive disorder (OCD), substance use disorder (SUD), and internet gaming disorder (IGD). Despite elaborated animal models suggesting that compulsivity is mediated by cortico-striatal circuits and a growing number of neuroimaging case-control studies, common neurofunctional alterations in these disorders have not been systematically examined. The present activation likelihood estimation (ALE) meta-analysis capitalized on previous functional magnetic resonance imaging (fMRI) studies to determine shared neurofunctional alterations among the three disorders. Task-based fMRI studies of individuals with SUD, OCD, or IGD were obtained. ALE was performed within each disorder. Next, contrast and conjunction meta-analyses were performed to determine differential and common alterations. Task-paradigm classes were group according to Research Domain Criteria (RDoC) domains to determine contributions of underlying behavioral domains. One hundred forty-four articles were included representing data from n = 6897 individuals (SUD = 2418, controls = 2332; IGD = 361, controls = 360; OCD = 715, controls = 711) from case-control studies. Conjunction meta-analyses revealed shared alterations in the anterior insular cortex between OCD and SUDs. SUD exhibited additionally pronounced dorsal-striatal alterations compared with both, OCD and IGD. IGD shared frontal, particularly cingulate alterations with all SUDs, while IGD demonstrated pronounced temporal alterations compared with both, SUD and OCD. No robust overlap between IGD and OCD was observed. Across the disorders, neurofunctional alterations were mainly contributed by cognitive systems and positive valence RDoC domains. The present findings indicate that neurofunctional dysregulations in prefrontal regions engaged in regulatory-control represent shared neurofunctional alterations across substance and behavioral addictions, while shared neurofunctional dysregulations in the anterior insula may mediate compulsivity in substance addiction and OCD.

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.

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%.

Discovering dynamic task-modulated functional networks with specific spectral modes using MEG.

Efficient neuronal communication between brain regions through oscillatory synchronization at certain frequencies is necessary for cognition. Such synchronized networks are transient and dynamic, established on the timescale of milliseconds in order to support ongoing cognitive operations. However, few studies characterizing dynamic electrophysiological brain networks have simultaneously accounted for temporal non-stationarity, spectral structure, and spatial properties. Here, we propose an analysis framework for characterizing the large-scale phase-coupling network dynamics during task performance using magnetoencephalography (MEG). We exploit the high spatiotemporal resolution of MEG to measure time-frequency dynamics of connectivity between parcellated brain regions, yielding data in tensor format. We then use a tensor component analysis (TCA)-based procedure to identify the spatio-temporal-spectral modes of covariation among separate regions in the human brain. We validate our pipeline using MEG data recorded during a hand movement task, extracting a transient motor network with beta-dominant spectral mode, which is significantly modulated by the movement task. Next, we apply the proposed pipeline to explore brain networks that support cognitive operations during a working memory task. The derived results demonstrate the temporal formation and dissolution of multiple phase-coupled networks with specific spectral modes, which are associated with face recognition, vision, and movement. The proposed pipeline can characterize the spectro-temporal dynamics of functional connectivity in the brain on the subsecond timescale, commensurate with that of cognitive performance.

Common and separable neural alterations in substance use disorders: A coordinate-based meta-analyses of functional neuroimaging studies in humans.

Delineating common and separable neural alterations in substance use disorders (SUD) is imperative to understand the neurobiological basis of the addictive process and to inform substance-specific treatment strategies. Given numerous functional MRI (fMRI) studies in different SUDs, a meta-analysis could provide an opportunity to determine robust shared and substance-specific alterations. The present study employed a coordinate-based meta-analysis covering fMRI studies in individuals with addictive cocaine, cannabis, alcohol, and nicotine use. The primary meta-analysis demonstrated common alterations in primary dorsal striatal, and frontal circuits engaged in reward/salience processing, habit formation, and executive control across different substances and task-paradigms. Subsequent sub-analyses revealed substance-specific alterations in frontal and limbic regions, with marked frontal and insula-thalamic alterations in alcohol and nicotine use disorders respectively. Examining task-specific alterations across substances revealed pronounced frontal alterations during cognitive processes yet stronger striatal alterations during reward-related processes. Finally, an exploratory meta-analysis revealed that neurofunctional alterations in striatal and frontal reward processing regions can already be determined with a high probability in studies with subjects with comparably short durations of use. Together the findings emphasize the role of dysregulations in frontostriatal circuits and dissociable contributions of these systems in the domains of reward-related and cognitive processes which may contribute to substance-specific behavioral alterations.

Exploring Frequency-Dependent Brain Networks from Ongoing EEG Using Spatial ICA During Music Listening.

Recently, exploring brain activity based on functional networks during naturalistic stimuli especially music and video represents an attractive challenge because of the low signal-to-noise ratio in collected brain data. Although most efforts focusing on exploring the listening brain have been made through functional magnetic resonance imaging (fMRI), sensor-level electro- or magnetoencephalography (EEG/MEG) technique, little is known about how neural rhythms are involved in the brain network activity under naturalistic stimuli. This study exploited cortical oscillations through analysis of ongoing EEG and musical feature during freely listening to music. We used a data-driven method that combined music information retrieval with spatial Fourier Independent Components Analysis (spatial Fourier-ICA) to probe the interplay between the spatial profiles and the spectral patterns of the brain network emerging from music listening. Correlation analysis was performed between time courses of brain networks extracted from EEG data and musical feature time series extracted from music stimuli to derive the musical feature related oscillatory patterns in the listening brain. We found brain networks of musical feature processing were frequency-dependent. Musical feature time series, especially fluctuation centroid and key feature, were associated with an increased beta activation in the bilateral superior temporal gyrus. An increased alpha oscillation in the bilateral occipital cortex emerged during music listening, which was consistent with alpha functional suppression hypothesis in task-irrelevant regions. We also observed an increased delta-beta oscillatory activity in the prefrontal cortex associated with musical feature processing. In addition to these findings, the proposed method seems valuable for characterizing the large-scale frequency-dependent brain activity engaged in musical feature processing.

Functional connectivity of supplementary motor area during finger-tapping in major depression.

Psychomotor disturbance has been consistently regarded as an essential feature of depressive disorders. Studying objectively measurable motor behaviors like finger-tapping may help advance the diagnostic methods. Twenty-five patients with major depressive disorder (MDD) and 15 healthy participants underwent functional magnetic resonance imaging (fMRI) measurements while tapping their index fingers. The finger-tapping (FT) task was performed by the right hand (the tapping frequency varied between 1, 2 and 4 Hz) or both hands either in synchrony or alternation (the tapping frequency varied between 1 and 2 Hz). A mixed-model ANOVA was used for between- and within-group comparisons of the task accuracy and fMRI percent signal change in the supplementary motor area (SMA) during 26-second sequences of finger-tapping. Furthermore, using seed-based correlation analyses we compared the connectivity of the SMA between the two samples. At the behavioral level, no significant group differences in FT performance between the patient and control groups was observed. The mean fMRI percent signal change of the SMA was significantly elevated at higher levels of speed in both groups. In the MDD group, an increased connectivity of the left SMA with the bilateral cortical and cerebellar motor- and vision-related regions was found. Most importantly, a decreased connectivity between the SMA and the basal ganglia was found at frequencies of 4 Hz. Our findings support the contention that, in depression, brain connectivity measures during motor performance may reveal deviant neural processes that are potentially relevant to measurable (bio)markers for individual diagnosis and treatment.

Neurofeedback of core language network nodes modulates connectivity with the default-mode network: A double-blind fMRI neurofeedback study on auditory verbal hallucinations.

BACKGROUND: The experience of auditory verbal hallucinations in schizophrenia is associated with changes in brain network function. In particular, studies indicate altered functional coupling between nodes of the language and default mode networks. Neurofeedback based on real-time functional magnetic resonance imaging (rtfMRI) can be used to modulate such aberrant network connectivity. METHODS: We investigated resting-state connectivity changes after neurofeedback (NF) in 21 patients with schizophrenia and 35 healthy individuals. All participants underwent two days of neurofeedback training of important nodes of the left-hemispheric language network including the inferior frontal gyrus (IFG) and posterior superior temporal gyrus (pSTG). In a double-blind randomized cross-over design, participants learned to down- and up-regulate their brain activation in the designated target regions based on NF. Prior to and after each training day, a resting state measurement took place. RESULTS: Coupling between nodes of the language and the default mode network (DMN) selectively increased after down-as compared to up-regulation NF. Network analyses revealed more pronounced increases in functional connectivity between nodes of the language network and the DMN in patients compared to healthy individuals. In particular, down-regulation NF led to increased coupling between nodes of the language network and bilateral inferior parietal lobe (IPL) as well as posterior cingulate cortex (PCC)/precuneus in patients. Up-regulation strengthened connectivity with the medial prefrontal cortex (mPFC). Improved well-being four weeks after the training predicted increased functional coupling between the left IFG and left IPL. CONCLUSION: Modulatory effects emerged as increased internetwork communication, indicating that down-regulation NF selectively enhances coupling between language and DM network nodes in patients with AVH. RtfMRI NF may thus be used to modulate brain network function that is relevant to the phenomenology of AVH. Specific effects of self-regulation on symptom improvement have to be explored in therapeutic interventions.

Fronto-parietal and temporal brain dysfunction in depression: A fMRI investigation of auditory mismatch processing.

Mismatch responses reflect neural mechanisms of early cognitive processing in the auditory domain. Disturbances of these mechanisms on multiple levels of neural processing may contribute to clinical symptoms in major depression (MD). A functional magnetic resonance imaging (fMRI) study was conducted to identify neurobiological foundations of altered mismatch processing in MD. Twenty-five patients with major depression and 25 matched healthy individuals completed an auditory mismatch paradigm optimized for fMRI. Brain activity during mismatch processing was compared between groups. Moreover, seed-based connectivity analyses investigated depression-specific brain networks. In patients, mismatch processing was associated with reduced activation in the right auditory cortex as well as in a fronto-parietal attention network. Moreover, functional coupling between the right auditory cortex and frontal areas was reduced in patients. Seed-to voxel analysis on the whole-brain level revealed reduced connectivity between the auditory cortex and the thalamus as well as posterior cingulate. The present study indicates deficits in sensory processing on the level of the auditory cortex in depression. Hyposensitivity in a fronto-parietal network presumably reflects altered attention mechanisms in depression. The observed impairments may contribute to psychopathology by reducing the ability of the affected individuals to orient attention toward important environmental cues.

Amygdala response and functional connectivity during cognitive emotion regulation of aversive image sequences.

Emotion regulation (ER) is crucial in terms of mental health and social functioning. Attention deployment (AD) and cognitive reappraisal (CR) are both efficient cognitive ER strategies, which are based on partially dissociated neural effects. Our understanding of the neural underpinnings of ER is based on laboratory paradigms that study changes of the brain activation related to isolated emotional stimuli. To track the neural response to ER in the changing and dynamic environment of daily life, we extended the common existing paradigms by applying a sequence of emotionally provocative stimuli involving three aversive images. Eighteen participants completed an ER paradigm, in which they had to either shift their attention away from the emotionally negative images by counting backwards (AD strategy) or reinterpret the meaning of stimuli (CR strategy) to attain a down-regulation of affective responses. An increased recruitment of left-sided lateral and medial PFC was shown upon regulation of negative emotions with CR as compared to AD. Remarkably, the amygdala activation showed an increasing pattern of activation during CR. The inverse relationship between PFC and amygdala was compromised during elongated blocks of reappraisal, reflecting a reduction in engagement of the top-down prefrontal regulatory circuitry upon repeated exposure to negative stimuli. These results highlight that temporal dynamic of amygdala response and its functional connectivity differentiates AD and CR strategies in regulating emotions. Findings of the current study underscore the importance of adopting temporally variant approaches for investigating the neural effects of ER. Identifying neural systems that subserve down-regulation of negative emotions is of importance in developing treatment strategies for various forms of psychopathology.

Variation of temporal order reveals deficits in categorisation of facial expressions in patients afflicted with depression.

INTRODUCTION: It is well established that depressive disorders are associated with abnormalities in the processing of affective information. However, type of stimuli, perceptual complexity and cognitive demand are important factors in evaluating these findings. In particular, processing mechanisms of perceptual boundaries in ecologically valid face stimuli are largely unknown in depression. METHODS: In the current study, intensity-ordered frame sequences provided a dynamic visualisation of happy or sad facial expressions fading from or to neutral expressions. Patients (n = 20) with major depression (MD) disorder and controls (n = 20) indicated their perceptual boundaries between neutral and emotional face depending on direction and emotion. The averaged time of the perceptual boundary entered a group × condition ANOVA and regression analysis. RESULTS: MD group did not systematically shift perceptual boundaries in the dynamic emotional faces but yielded altered statistics in information processing. The Gaussian distribution of boundary judgements was disturbed in depression, increasing goodness-of-fit errors in disappearing emotions. Goodness-of-fit correlated with depression symptom score (Beck Depression Inventory-II (BDI-II)) in the MD group during the disappearing sad (r(18) = 46, p = 0.04) and happy (r(18) = 51, p = 0.02) conditions. CONCLUSION: We evaluated detection of appearing and disappearing emotions in dynamic faces. A deviant distribution of categorisation responses emerged in the MD group, which was not emotion-specific. Such a perceptional uncertainty can impede individuals' functioning in interpersonal interaction.

Cortico-limbic connectivity in MAOA-L carriers is vulnerable to acute tryptophan depletion.

INTRODUCTION: A gene-environment interaction between expression genotypes of the monoamine oxidase A (MAOA) and adverse childhood experience increases the risk of antisocial behavior. However, the neural underpinnings of this interaction remain uninvestigated. A cortico-limbic circuit involving the prefrontal cortex (PFC) and the amygdala is central to the suppression of aggressive impulses and is modulated by serotonin (5-HT). MAOA genotypes may modulate the vulnerability of this circuit and increase the risk for emotion regulation deficits after specific life events. Acute tryptophan depletion (ATD) challenges 5-HT regulation and may identify vulnerable neuronal circuits, contributing to the gene-environment interaction. METHODS: Functional magnetic resonance imaging measured the resting-state state activity in 64 healthy males in a double-blind, placebo-controlled study. Cortical maps of amygdala correlation identified the impact of ATD and its interaction with low- (MAOA-L) and high-expression variants (MAOA-H) of MAOA on cortico-limbic connectivity. RESULTS: Across all Regions of Interest (ROIs) exhibiting an ATD effect on cortico-limbic connectivity, MAOA-L carriers were more susceptible to ATD than MAOA-H carriers. In particular, the MAOA-L group exhibited a larger reduction of amygdala connectivity with the right prefrontal cortex and a larger increase of amygdala connectivity with the insula and dorsal PCC. CONCLUSION: MAOA-L carriers were more susceptable to a central 5-HT challenge in cortico-limbic networks. Such vulnerability of the cortical serotonergic system may contribute to the emergence of antisocial behavior after systemic challenges, observed as gene-environment interaction. Hum Brain Mapp 38:1622-1635, 2017. © 2016 Wiley Periodicals, Inc.

Temporal processing deficit leads to impaired multisensory binding in schizophrenia.

INTRODUCTION: Schizophrenia has been characterised by neurodevelopmental dysconnectivity resulting in cognitive and perceptual dysmetria. Hence patients with schizophrenia may be impaired to detect the temporal relationship between stimuli in different sensory modalities. However, only a few studies described deficit in perception of temporally asynchronous multisensory stimuli in schizophrenia. METHODS: We examined the perceptual bias and the processing time of synchronous and delayed sounds in the streaming-bouncing illusion in 16 patients with schizophrenia and a matched control group of 18 participants. RESULTS: Equal for patients and controls, the synchronous sound biased the percept of two moving squares towards bouncing as opposed to the more frequent streaming percept in the condition without sound. In healthy controls, a delay of the sound presentation significantly reduced the bias and led to prolonged processing time whereas patients with schizophrenia did not differentiate between this condition and the condition with synchronous sound. CONCLUSION: Schizophrenia leads to a prolonged window of simultaneity for audiovisual stimuli. Therefore, temporal processing deficit in schizophrenia can lead to hyperintegration of temporally unmatched multisensory stimuli.