Default mode network alterations during implicit emotional faces processing in first-episode, treatment-naive major depression patients

Transcranial focused ultrasound targeting the default mode network for the treatment of depression

Introduction

Up to 50% of individuals fail to respond to current depression treatments. Repetitive negative thought and default mode network hyperconnectivity are central in depression and can potentially be targeted using novel neuromodulation techniques. This community-based study assessed whether a treatment using non-invasive transcranial focused ultrasound targeting the default mode network can decrease depression symptoms and repetitive negative thought, and improve quality of life.

Methods

Study recruitment began in August 2023 and ended in February 2024. Twenty individuals aged 18 - 50 were enrolled from among 247 screened. Exclusion criteria included history of psychosis/mania, acute suicidality, MRI contraindications, pregnancy, and medical and neurological factors that may complicate diagnosis or brain function. Participants completed up to three weeks of transcranial ultrasound (11 sessions) targeting the anterior medial prefrontal cortex; ten minutes per session. Depression severity (Beck Depression Inventory - II and the Hamilton Depression Rating Scale), repetitive negative thought (Perseverative Thinking Questionnaire), and quality of life (World Health Organization Quality of Life Scale) were outcomes.

Results

This sample was young (mean 30.4 years ± 10.0), predominantly female (75%), with moderate to severe depression and high comorbidity. Fifty percent of participants endorsed current psychiatric medication use. Ten percent of subjects dropped out of the study due to time constraints. Significant decreases in depression were observed over the course of treatment on self-report, 10.9 (p < 0.001, CI = -13.55, -7.92) and interview depression ratings, 4.2 (p < 0.001, CI = -5.85, -2.62), as well as significant decreases in repetitive negative thought, 8.4 (p <0.001, CI = -10.55, -6.03). Improvements in physical and psychological well-being were also observed over the course of treatment, 7.2 (p < 0.001, CI = 3.64, 10.63) and 11.2 (p < 0.001, CI = 7.79, 14.49), respectively, as well as improvements in environment satisfaction, 5.0 (p =0.001, CI = 2.24, 7.56).

Discussion

Non-invasive transcranial focused ultrasound holds promise as a treatment for depression holds promise as a treatment for depression, however, future work including control arms is required to ascertain its causal role in depression.

Clinical trial registration

https://clinicaltrials.gov/study/NCT06320028intr=Ultrasound&cond=depression&locStr=Arizona&country=United%20States&state=Arizona&rank=1, identifier NCT06320028.

Large-scale functional network connectivity alterations in adolescents with major depression and non-suicidal self-injury

Non-suicidal self-injury (NSSI) is prevalent among adolescent populations worldwide, yet its neuropathological mechanisms remain unclear. This study aimed to investigate brain functional differences in NSSI patients by utilizing large-scale functional networks and examining their correlation with clinical outcomes. Cross-sectional clinical and functional magnetic resonance imaging (fMRI) data were collected from 42 patients and 47 healthy controls. Independent component analysis (ICA) was utilized to investigate changes in both intra-network and inter-network functional connectivity. We then investigated the potential association between functional network connectivity and clinical self-injurious behavior. The results revealed significant abnormalities in intra-network functional connectivity within the left middle cingulum gyrus, right angular gyrus, and middle frontal gyrus in patients with NSSI. Additionally, we found altered inter-network connectivity patterns, particularly between higher-order cognitive networks and primary sensory networks, suggesting potential disruptions in multisensory integration and emotional regulation in these patients. This study revealed significant alterations in large-scale functional network connectivity in adolescents with depression and NSSI, particularly in networks related to emotion regulation and cognitive control. These findings provide novel perspectives on the neurobiological mechanisms of NSSI and suggest possible avenues for early intervention and treatment.

Automatic Positive and Negative Emotion Regulation in Adolescents with Major Depressive Disorder

INTRODUCTION

Adolescents with major depressive disorder (MDD) exhibit hypoactivity to positive stimuli and hyperactivity to negative stimuli in terms of neural responses. Automatic emotion regulation (AER) activates triple networks (i.e., the central control network, default mode network, and salience network). Based on previous studies, we hypothesized that adolescents with MDD exhibit dissociable spatiotemporal deficits during positive and negative AER.

METHODS

We first collected EEG data from 32 adolescents with MDD and 35 healthy adolescents while they performed an implicit emotional Go/NoGo task. Then, we characterized the spatiotemporal dynamics of cortical activity during AER.

RESULTS

In Go trials, MDD adolescents exhibited reduced N2 amplitudes, enhanced theta power for positive pictures, and stronger bottom-up information flow from the left orbitofrontal cortex (OFC) to the right superior frontal gyrus compared to top-down information flow than the controls. In contrast, in NoGo trials, MDD adolescents exhibited elevated P3 amplitudes, enhanced theta power, and stronger top-down information flows from the right middle frontal gyrus to the right OFC and the left insula than the controls.

CONCLUSION

Overall, adolescents with MDD exhibited impaired automatic attention to positive emotions and impaired automatic response inhibition. These findings have potential implications for the clinical treatment of adolescents with MDD.

Functional dysconnectivity of cerebellum and attention networks in emotional dysregulation shared between attention deficit hyperactivity disorder and major depressive disorder: a multimodal imaging study

BACKGROUND

Emotional dysregulation (ED) is a common characteristic of both attention deficit hyperactivity disorder (ADHD) and major depressive disorder (MDD), especially in adolescents. However, whether ADHD and MDD may share the specific ED-related neural networks remains unknown.

METHODS

In total, 43 adolescents with clinical ED (22 adolescents with ADHD and 21 with MDD) were recruited; in addition, 29 sex- and age-matched healthy controls (HCs) were included. Resting-state functional connectivity (RSFC) analysis, voxel-based morphometry, and diffusion tensor imaging analysis were performed for each patient. In addition, we determined the significant regions of interest in patients with ED due to ADHD and MDD as compared with HCs and tested their correlations with clinical rating scale scores.

RESULTS

Compared with HCs, patients with ED had greater RSFC in the cerebellum and supramarginal gyrus (SMG), especially between vermis VI and the SMG in the attention networks, and lower RSFC between the right supplementary motor area and right lateral parietal area. Lower gray matter (GM) volume in the SMG was also found. RSFC was significantly correlated with clinical rating scale scores for all patients with ED due to ADHD or MDD. GM change was correlated with ED and MDD rating scale scores.

DISCUSSION

The cerebellum and attention networks might play major roles in ED pathophysiology in adolescents with ADHD and MDD. Increased connectivity of the vermis to the SMG serves as a possible underlying neural network.

Transcutaneous Electrical Cranial-Auricular Acupoint Stimulation Modulating the Brain Functional Connectivity of Mild-to-Moderate Major Depressive Disorder: An fMRI Study Based on Independent Component Analysis

Evidence has shown the roles of taVNS and TECS in improving depression but few studies have explored their synergistic effects on MDD. Therefore, the treatment responsivity and neurological effects of TECAS were investigated and compared to escitalopram, a commonly used medication for depression. Fifty patients with mild-to-moderate MDD (29 in the TECAS group and 21 in another) and 49 demographically matched healthy controls were recruited. After an eight-week treatment, the outcomes of TECAS and escitalopram were evaluated by the effective rate and reduction rate based on the Montgomery-Asberg Depression Rating Scale, Hamilton Depression Rating Scale, and Hamilton Anxiety Rating Scale. Altered brain networks were analyzed between pre- and post-treatment using independent component analysis. There was no significant difference in clinical scales between TECAS and escitalopram but these were significantly decreased after each treatment. Both treatments modulated connectivity of the default mode network (DMN), dorsal attention network (DAN), right frontoparietal network (RFPN), and primary visual network (PVN), and the decreased PVN-RFPN connectivity might be the common brain mechanism. However, there was increased DMN-RFPN and DMN-DAN connectivity after TECAS, while it decreased in escitalopram. In conclusion, TECAS could relieve symptoms of depression similarly to escitalopram but induces different changes in brain networks.

Cognitive and Affective Empathy as Indirect Paths Between Heterogeneous Depression Symptoms on Default Mode and Salience Network Connectivity in Adolescents

Depression amongst adolescents is a prevalent disorder consisting of heterogeneous emotional and functional symptoms-often involving impairments in social domains such as empathy. Cognitive and affective components of empathy as well as their associated neural networks (default mode network for cognitive empathy and salience network for affective empathy) are affected by depression. Depression commonly onsets during adolescence, a critical period for brain development underlying empathy. However, the available research in this area conceptualizes depression as a homogenous construct, and thereby miss to represent the full spectrum of symptoms. The present study aims to extend previous literature by testing whether cognitive and affective empathy indirectly account for associations between brain network connectivity and heterogeneous depression symptoms in adolescents. Heterogeneous functional and emotional symptoms of depression were measured using the child depression inventory. Our results indicate that cognitive empathy mediates the association between default mode network functional connectivity and emotional symptoms of depression. More specifically, that adolescents with a stronger positive association between the default mode network and cognitive empathy show lower emotional depression symptoms. This finding highlights the importance of cognitive empathy in the relationship between brain function and depression symptoms, which may be an important consideration for existing models of depression in adolescents.

Anticipatory cues in emotional processing shift the activation of a combined salience sensorimotor functional network in drug-naïve depressed patients

BACKGROUND

Major depressive disorder is characterized by a large-scale brain network dysfunction, contributing to impairments in cognitive and affective functioning. Core regions of default mode, limbic and salience networks are also impaired in emotional processing and anticipation. This study aimed to explore default mode, salience, and limbic networks modulation during the processing of emotional stimuli with and without anticipatory cues in depression, and further investigate how these networks were functionally coupled with the rest of the brain.

METHODS

Twenty-one drug-naïve depressed patients and 15 matched controls were included in the study. All participants completed a psychological assessment and the affective pictures paradigm during an fMRI acquisition. Group independent component analysis and psychophysiological interactions analyses were performed.

RESULTS

A significant interaction between Cue, Valence and Group was found for the salience/sensorimotor network. When processing uncued emotional stimuli, patients showed increased activation of this network for negative vs. neutral pictures, whereas when anticipatory cues were displayed previously to the picture presentation, they invert this pattern of activation (hyperactivating the salience/sensorimotor network for positive vs. neutral pictures). Patients showed increased functional connectivity between the salience/sensorimotor network and the left amygdala as well as the right inferior parietal lobule compared to controls when processing uncued negative pictures.

LIMITATIONS

The sample size was modest, and the salience/sensorimotor network included regions not typically identified as part of salience network. Thus, this study should be replicated to further interpret the results.

CONCLUSIONS

Anticipatory cues shift the pattern of activation of the salience/sensorimotor network in drug-naïve depressed patients.

Early-life stress exposure and large-scale covariance brain networks in extremely preterm-born infants

The stressful extrauterine environment following premature birth likely has far-reaching and persistent adverse consequences. The effects of early "third-trimester" ex utero stress on large-scale brain networks' covariance patterns may provide a potential avenue to understand how early-life stress following premature birth increases risk or resilience. We evaluated the impact of early-life stress exposure (e.g., quantification of invasive procedures) on maturational covariance networks (MCNs) between 30 and 40 weeks of gestational age in 180 extremely preterm-born infants (<28 weeks of gestation; 43.3% female). We constructed MCNs using covariance of gray matter volumes between key nodes of three large-scale brain networks: the default mode network (DMN), executive control network (ECN), and salience network (SN). Maturational coupling was quantified by summating the number of within- and between-network connections. Infants exposed to high stress showed significantly higher SN but lower DMN maturational coupling, accompanied by DMN-SN decoupling. Within the SN, the insula, amygdala, and subthalamic nucleus all showed higher maturational covariance at the nodal level. In contrast, within the DMN, the hippocampus, parahippocampal gyrus, and fusiform showed lower coupling following stress. The decoupling between DMN-SN was observed between the insula/anterior cingulate cortex and posterior parahippocampal gyrus. Early-life stress showed longitudinal network-specific maturational covariance patterns, leading to a reprioritization of developmental trajectories of the SN at the cost of the DMN. These alterations may enhance the ability to cope with adverse stimuli in the short term but simultaneously render preterm-born individuals at a higher risk for stress-related psychopathology later in life.

Extending the "resting state hypothesis of depression" - dynamics and topography of abnormal rest-task modulation

Major depressive disorder (MDD) is characterized by changes in both rest and task states as manifested in temporal dynamics (EEG) and spatial patterns (fMRI). Are rest and task changes related to each other? Extending the "Resting state hypothesis of depression" (RSHD) (Northoff et al., 2011), we, using multimodal imaging, take a tripartite approach: (i) we conduct a review of EEG studies in MDD combining both rest and task states; (ii) we present our own EEG data in MDD on brain dynamics, i.e., intrinsic neural timescales as measured by the autocorrelation window (ACW); and (iii) we review fMRI studies in MDD to probe whether different regions exhibit different rest-task modulation. Review of EEG data shows reduced rest-task change in MDD in different measures of temporal dynamics like peak frequency (and others). Notably, our own EEG data show decreased rest-task change as measured by ACW in frontal electrodes of MDD. The fMRI data reveal that different regions exhibit different rest-task relationships (normal rest-abnormal task, abnormal rest-normal task, abnormal rest-abnormal task) in MDD. Together, we demonstrate altered spatiotemporal dynamics of rest-task modulation in MDD; this further supports and extends the key role of the spontaneous activity in MDD as proposed by the RSHD.

Interleukin 6 predicts increased neural response during face processing in a sample of individuals with schizophrenia and healthy participants: A functional magnetic resonance imaging study

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IL-6 has been associated with poorer facial emotion recognition.

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fMRI was performed during a faces task and IL-6 measured from blood samples.

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IL-6 predicted increased neural response during facial emotion recognition.

Background

Deficits in facial emotion recognition are a core feature of schizophrenia and predictive of functional outcome. Higher plasma levels of the cytokine interleukin 6 (IL-6) have recently been associated with poorer facial emotion recognition in individuals with schizophrenia and healthy participants, but the neural mechanisms affected remain poorly understood.

Methods

Forty-nine individuals with schizophrenia or schizoaffective disorder and 158 healthy participants were imaged using functional magnetic resonance imaging during a dynamic facial emotion recognition task. Plasma IL-6 was measured from blood samples taken outside the scanner. Multiple regression was used in statistical parametric mapping software to test whether higher plasma IL-6 predicted increased neural response during task performance.

Results

Higher plasma IL-6 predicted increased bilateral medial prefrontal response during neutral face processing compared to angry face processing in the total sample (N = 207, t_max = 5.67) and increased left insula response during angry face processing compared to neutral face processing (N = 207, t_max = 4.40) (p < 0.05, family-wise error corrected across the whole brain at the cluster level).

Conclusions

These findings suggest that higher peripheral IL-6 levels predict altered neural response within brain regions involved in social cognition and emotion during facial emotion recognition. This is consistent with recent neuroimaging research on IL-6 and suggesting a possible neural mechanism by which this cytokine might affect facial emotion recognition accuracy.

Abnormal neural activities in adults and youths with major depressive disorder during emotional processing: a meta-analysis

BACKGROUND

Abnormal neural activities during emotional processing have been found in both adults and youths with major depressive disorder. However, findings were inconsistent in each group and cannot be compared to each other.

METHODS

We first identified neuroimaging experiments that revealed abnormal neural activities during emotional processing in patients with major depressive disorder published from January 1997 to January 2019. Then we conducted voxel-wise meta-analyses on adult and youth patients separately and compared the two age groups using direct meta-comparison.

RESULTS

Fifty-four studies comprising 1141 patients and 1242 healthy controls were identified. Both adult and youth patients showed abnormal neural activities in anterior cingulate cortex, insula, superior and middle temporal gyrus, and occipital cortex compared to healthy controls. However, hyperactivities in the superior and middle frontal gyrus, amygdala, and hippocampus were only observed in adult patients, while hyperactivity in the striatum was only found in youth patients compared to controls. In addition, compared with youths, adult patients exhibited significantly greater abnormal activities in insula, middle frontal gyrus, and hippocampus, and significantly lower abnormal activities in middle temporal gyrus, middle occipital gyrus, lingual gyrus, and striatum.

CONCLUSIONS

The common alterations confirmed the negative processing bias in major depressive disorder. Both adult and youth patients were suggested to have disturbed emotional perception, appraisal, and reactivity. However, adult patients might be more subject to the impaired appraisal and reactivity processes, while youth patients were more subject to the impaired perception process. These findings help us understand the progressive pathophysiology of major depressive disorder.

Task MRI-Based Functional Brain Network of Major Depression

This chapter will focus on task magnetic resonance imaging (MRI) to understand the biological mechanisms and pathophysiology of brain in major depressive disorder (MDD), which would have minor alterations in the brain function. Therefore, the functional study, such as task MRI functional connectivity, would play a crucial role to explore the brain function in MDD. Different kinds of tasks would determine the alterations in functional connectivity in task MRI studies of MDD. The emotion-related tasks are linked with alterations in anterior cingulate cortex, insula, and default mode network. The emotional memory task is linked with amygdala-hippocampus alterations. The reward-related task would be related to the reward circuit alterations, such as fronto-straital. The cognitive-related tasks would be associated with frontal-related functional connectivity alterations, such as the dorsolateral prefrontal cortex, anterior cingulate cortex, and other frontal regions. The visuo-sensory characteristics of tasks might be associated with the parieto-occipital alterations. The frontolimbic regions might be major components of task MRI-based functional connectivity in MDD. However, different scenarios and tasks would influence the representations of results.

Efficacy and brain mechanism of transcutaneous auricular vagus nerve stimulation for adolescents with mild to moderate depression: Study protocol for a randomized controlled trial

BACKGROUND

Depression is a common mental illness in childhood and adolescence, with an incidence of 4%-5%; it can lead to impairments in learning and social functioning. Transcutaneous auricular vagus nerve stimulation (taVNS) is a commonly used method of auricular acupuncture point stimulation, which is regarded as an effective treatment for adults with depression. The aim of this study was to investigate the efficacy and mechanism of taVNS for adolescents with mild to moderate depression.

METHODS

This randomized controlled clinical trial will include 120 patients aged 12-16 years, all of whom are diagnosed with mild to moderate depression. Patients will be randomly assigned to a taVNS group and a drug control group (sertraline hydrochloride) at a ratio of 1:1. Patients will be evaluated using the 17-item Hamilton Depression Scale, Hamilton Anxiety Rating Scale, Self-Rating Depression Scale, Self-Rating Anxiety Scale, and Pittsburgh Sleep Quality Index scores at baseline, as well as at the 2nd, 4th, 6th, 8th, and 12th weeks. To investigate the underlying neural mechanisms of taVNS treatment from the perspective of the default mode network, multimodal magnetic resonance imaging (MRI; i.e., structural MRI [sMRI], resting state MRI [rsMRI], and pseudocontinuous arterial spin-labeled [pcASL] MRI) will be used to compare cerebral images among groups. MRI data will also be collected from 40 healthy volunteers to assess whether the participants exhibit normal development of structural and functional components.

DISCUSSION

Depression is the most common mental disorder in adolescence. Drug treatment can improve depression symptoms; however, the side effects of drug treatments are often severe. This study proposes a simple physiotherapy that aims to treat adolescents with mild to moderate depression. The mechanism of taVNS in the treatment of depression will also be investigated. The results of this study will provide evidence to guide the application of taVNS in adolescents with depression.

ADHD with Comorbid Bipolar Disorders: A Systematic Review of Neurobiological, Clinical and Pharmacological Aspects Across the Lifespan

BACKGROUND

Attention deficit hyperactivity (ADHD) disorder is a neurodevelopmental disorder characterized by inattention, hyperactivity, disruptive behaviour, and impulsivity. Despite considered typical of children for a long time, the persistence of ADHD symptoms in adulthood gained increasing interest during the last decades. Indeed, its diagnosis, albeit controversial, is rarely carried out even because ADHD is often comorbid with several other psychiatric diosrders, in particular with bipolar disorders (BDs), a condition that complicates the clinical picture, assessment and treatment.

AIMS

The aim of this paper was to systematically review the scientific literature on the neurobiological, clinical features and current pharmacological management of ADHD comorbid with BDs across the entire lifespan, with a major focus on the adulthood.

DISCUSSION

The pharmacology of ADHD-BD in adults is still empirical and influenced by the individual experience of the clinicians. Stimulants are endowed of a prompt efficacy and safety, whilst non-stimulants are useful when a substance abuse history is detected, although they require some weeks in order to be fully effective. In any case, an in-depth diagnostic and clinical evaluation of the single individual is mandatory.

CONCLUSION

The comorbidity of ADHD with BD is still a controversial matter, as it is the notion of adult ADHD as a distinct nosological category. Indeed, some findings highlighted the presence of common neurobiological mechanisms and overlapping clinical features, although disagreement does exist. In any case, while expecting to disentangle this crucial question, a correct management of this comorbidity is essential, which requires the co-administration of mood stabilizers. Further controlled clinical studies in large samples of adult ADHD-BD patients appear extremely urgent in order to better define possible therapeutic guidelines, as well as alternative approaches for this potentially invalidating condition.

Direct replication of task-dependent neural activation patterns during sadness introspection in two independent adolescent samples

Functional neuroimaging results need to replicate to inform sound models of human social cognition and its neural correlates. Introspection, the capacity to reflect on one's thoughts and feelings, is one process required for normative social cognition and emotional functioning. Engaging in introspection draws on a network of brain regions including medial prefrontal cortex (mPFC), posterior cingulate cortex (PCC), middle temporal gyri (MTG), and temporoparietal junction (TPJ). Maturation of these regions during adolescence mirrors the behavioral advances seen in adolescent social cognition, but the neural correlates of introspection in adolescence need to replicate to confirm their generalizability and role as a possible mechanism. The current study investigated whether reflecting upon one's own feelings of sadness would activate and replicate similar brain regions in two independent samples of adolescents. Participants included 156 adolescents (50% female) from the California Families Project and 119 adolescent girls from the Pittsburgh Girls Study of Emotion. All participants completed the Emotion Regulation Questionnaire (ERQ) and underwent a functional magnetic resonance imaging scan while completing the same facial emotion‐processing task at age 16–17 years. Both samples showed similar whole‐brain activation patterns when engaged in sadness introspection and when judging a nonemotional facial feature. Whole‐brain activation was unrelated to ERQ scores in both samples. Neural responsivity to task manipulations replicated in regions recruited for socio‐emotional (mPFC, PCC, MTG, TPJ) and attention (dorsolateral PFC, precentral gyri, superior occipital gyrus, superior parietal lobule) processing. These findings demonstrate robust replication of neural engagement during sadness introspection in two independent adolescent samples.

Temporal dynamics of spontaneous default-mode network activity mediate the association between reappraisal and depression

Cognitive reappraisal is associated with major depressive disorder (MDD), while spontaneous activity patterns of the default mode network (DMN) is implicated in reappraisal and MDD. However, neural mechanisms subserving the close association of spontaneous reappraisal and depression are unclear. Spontaneous reappraisal, depression and resting-state functional magnetic resonance imaging (rsfMRI) were measured from 105 healthy subjects. We assessed the temporal complexity (Hurst exponent), Regional Homogeneity (ReHo) and fractional Amplitude of Low Frequency Fluctuation (fALFF) profiles of DMN, a network involved in both reappraisal and depression. Mediation effects of these standard measures on the relationship between reappraisal and depression, and the contributions of each DMN subregion, were assessed. Results indicated that Hurst exponent (H) of DMN, whether extracted by independent component analysis (ICA) or region of interest (ROI), was significantly associated with reappraisal scores. An individual with a higher reappraisal score has a lower Hurst value of DMN. Mediation analyses suggest that H of DMN partially mediates the association between reappraisal and the degree of depression, and this mediation effect arises from the contribution of medial prefrontal cortex. Neither ReHo nor fALFF showed a similar correlation or mediation effect. These findings suggest that temporal dynamics of DMN play an important role in emotion regulation and its association with depression. H of DMN may serve as a neural marker mediating the association between reappraisal and depression.

The Influence of Self-Relevance and Cultural Values on Moral Orientation

Moral orientation refers to moral values that have a consistent guiding orientation toward an individual's moral cognition and behavior. Gilligan (1982) proposed that individuals have two moral orientations, namely “justice” and “care.” In the current study, we investigated the influence of self-relevance and cultural values on justice and care by using Single Attribute Implicit Association Test (SA-IAT). In Experiments 1 and 2, we adopted cultural icon prime paradigm to examine the effects of different self-referential stimuli (self, friend, and stranger) on implicit moral justice and care orientation under two cultural value conditions: traditionality, modernity, and neutral cultural values. Participants exhibited more difference toward different self-referential stimuli in the traditionality condition than in the modernity condition; the priming of traditional culture aggravated the differential order, whereas the priming of modernity weakened the differential order regarding implicitly just moral orientation. In the implicit care orientation, participants in the modern culture group exhibited the least difference to different self-referential stimuli compared with the other two groups, and the traditional group and the control group did not differ significantly. These findings indicate that psychological modernity weakens the degree of self-related effect in implicit justice and care orientation, whereas traditional culture aggravates the differential order in justice orientation. The current studies provide empirical support for theories relating moral orientation, also informing the literature on the role of self-relevance information and cultural values in moral decision making.

Risk factors associated with cognitions for late-onset depression based on anterior and posterior default mode sub-networks

BACKGROUND

Abnormal functional connectivity (FC) in the default mode network (DMN) plays an important role in late-onset depression (LOD) patients. In this study, the risk predictors of LOD based on anterior and posterior DMN are explored.

METHODS

A total of 27 LOD patients and 40 healthy controls (HC) underwent resting-state functional magnetic resonance imaging and cognitive assessments. Firstly, FCs within DMN sub-networks were determined by placing seeds in the ventral medial prefrontal cortex (vmPFC) and posterior cingulate cortex (PCC). Secondly, multivariable logistic regression was used to identify risk factors for LOD patients. Finally, correlation analysis was performed to investigate the relationship between risk factors and the cognitive value.

RESULTS

Multivariable logistic regression showed that the FCs between the vmPFC and right middle temporal gyrus (MTG) (vmPFC-MTG_R), FCs between the vmPFC and left precuneus (PCu), and FCs between the PCC and left PCu (PCC-PCu_L) were the risk factors for LOD. Furthermore, FCs of the vmPFC-MTG_R and PCC-PCu_L correlated with processing speed (R = 0.35, P = 0.002; R = 0.32, P = 0.009), and FCs of the vmPFC-MTG_R correlated with semantic memory (R = 0.41, P = 0.001).

LIMITATIONS

The study was a cross-sectional study. The results may be potentially biased because of a small sample.

CONCLUSIONS

In this study, we confirmed that LOD patients mainly present cognitive deficits in processing speed and semantic memory. Moreover, our findings further suggested that FCs within DMN sub-networks associated with cognitions were risk factors, which may be used for the prediction of LOD.

Neural correlates of the natural observation of an emotionally loaded video

Studies based on a paradigm of free or natural viewing have revealed characteristics that allow us to know how the brain processes stimuli within a natural environment. This method has been little used to study brain function. With a connectivity approach, we examine the processing of emotions using an exploratory method to analyze functional magnetic resonance imaging (fMRI) data. This research describes our approach to modeling stress paradigms suitable for neuroimaging environments. We showed a short film (4.54 minutes) with high negative emotional valence and high arousal content to 24 healthy male subjects (36.42 years old; SD = 12.14) during fMRI. Independent component analysis (ICA) was used to identify networks based on spatial statistical independence. Through this analysis we identified the sensorimotor system and its influence on the dorsal attention and default-mode networks, which in turn have reciprocal activity and modulate networks described as emotional.

A Bayesian Approach for Estimating Dynamic Functional Network Connectivity in fMRI Data

Dynamic functional connectivity, i.e., the study of how interactions among brain regions change dynamically over the course of an fMRI experiment, has recently received wide interest in the neuroimaging literature. Current approaches for studying dynamic connectivity often rely on ad-hoc approaches for inference, with the fMRI time courses segmented by a sequence of sliding windows. We propose a principled Bayesian approach to dynamic functional connectivity, which is based on the estimation of time varying networks. Our method utilizes a hidden Markov model for classification of latent cognitive states, achieving estimation of the networks in an integrated framework that borrows strength over the entire time course of the experiment. Furthermore, we assume that the graph structures, which define the connectivity states at each time point, are related within a super-graph, to encourage the selection of the same edges among related graphs. We apply our method to simulated task-based fMRI data, where we show how our approach allows the decoupling of the task-related activations and the functional connectivity states. We also analyze data from an fMRI sensorimotor task experiment on an individual healthy subject and obtain results that support the role of particular anatomical regions in modulating interaction between executive control and attention networks.

The correlation between mood states and functional connectivity within the default mode network can differentiate Internet gaming disorder from healthy controls

The default-mode network (DMN) has been suggested to support a baseline state of brain activity. However, whether connectivity within the DMN is associated with mood states remains incompletely understood. The current study examined the correlation between mood state and the functional connectivity (FC) among DMN regions, and examined if the FC can differentiate Internet gaming disorder (IGD) from healthy controls (HC). Resting state data were collected within 108 college students (IGD,41; HC,67). Negative correlations were observed between measures of: (1) Depression and FCs among ventral DMN regions; (2) Anger and FCs among dorsal DMN regions; and, (3) Anger and Depression and FCs of both the ventral and dorsal DMN. The results suggest that negative mood states of Depression and Anger might reflect poorer, or might impair, FCs among DMN regions. In addition, the FC among DMNs could be useful indexes in differencing IGD from HC. Future studies should examine the extent to which the findings may extend to clinical populations and whether increased connectivity of DMN regions may represent a mechanism for reducing negative mood states.

Default mode functional connectivity is associated with social functioning in schizophrenia

Individuals with schizophrenia display notable deficits in social functioning. Research indicates that neural connectivity within the default mode network (DMN) is related to social cognition and social functioning in healthy and clinical populations. However, the association between DMN connectivity, social cognition, and social functioning has not been studied in schizophrenia. For the present study, the authors used resting-state neuroimaging data to evaluate connectivity between the main DMN hubs (i.e., the medial prefrontal cortex [mPFC] and the posterior cingulate cortex-anterior precuneus [PPC]) in individuals with schizophrenia (n = 28) and controls (n = 32). The authors also examined whether DMN connectivity was associated with social functioning via social attainment (measured by the Specific Levels of Functioning Scale) and social competence (measured by the Social Skills Performance Assessment), and if social cognition mediates the association between DMN connectivity and these measures of social functioning. Results revealed that DMN connectivity did not differ between individuals with schizophrenia and controls. However, connectivity between the mPFC and PCC hubs was significantly associated with social competence and social attainment in individuals with schizophrenia but not in controls as reflected by a significant group-by-connectivity interaction. Social cognition did not mediate the association between DMN connectivity and social functioning in individuals with schizophrenia. The findings suggest that fronto-parietal DMN connectivity in particular may be differentially associated with social functioning in schizophrenia and controls. As a result, DMN connectivity may be used as a neuroimaging marker to monitor treatment response or as a potential target for interventions that aim to enhance social functioning in schizophrenia. (PsycINFO Database Record

Altered dynamics of brain connectivity in major depressive disorder at-rest and during task performance

Major depressive disorder (MDD) has been associated with alterations in several functional brain networks. Previous studies investigating brain networks in MDD during the performance of a task have yielded inconsistent results with the function of the brain at rest. In this study, we used functional magnetic resonance imaging at rest and during a goal-directed task to investigate dynamics of functional connectivity in 19 unmedicated patients with MDD and 19 healthy controls across both experimental paradigms. Patients had spatial differences in the default mode network (DMN), in the executive network (EN), and in the dorsal attention network (DAN) compared to controls at rest and during task performance. In patients the amplitude of the low frequency (LFO) oscillations was reduced in the motor and in the DAN networks during both paradigms. There was a diagnosis by paradigm interaction on the LFOs amplitude of the salience network, with increased amplitude change between task and rest in patients relative to controls. Our findings suggest that the function of several networks could be intrinsically affected in MDD and this could be viable phenotype for the investigation on the neurobiological mechanisms of this disorder and its treatment.

Abnormalities in the structural covariance of emotion regulation networks in major depressive disorder

Major depressive disorder (MDD) is a common psychiatric disorder that is characterized by cognitive deficits and affective symptoms. To date, an increasing number of neuroimaging studies have focused on emotion regulation and have consistently shown that emotion dysregulation is one of the central features and underlying mechanisms of MDD. Although gray matter morphological abnormalities in regions within emotion regulation networks have been identified in MDD, the interactions and relationships between these gray matter structures remain largely unknown. Thus, in this study, we adopted a structural covariance method based on gray matter volume to investigate the brain morphological abnormalities within the emotion regulation networks in a large cohort of 65 MDD patients and 65 age- and gender-matched healthy controls. A permutation test with p < 0.05 was used to identify the significant changes in covariance connectivity strengths between MDD patients and healthy controls. The structural covariance analysis revealed an increased correlation strength of gray matter volume between the left angular gyrus and the left amygdala and between the right angular gyrus and the right amygdala, as well as a decreased correlation strength of the gray matter volume between the right angular gyrus and the posterior cingulate cortex in MDD. Our findings support the notion that emotion dysregulation is an underlying mechanism of MDD by revealing disrupted structural covariance patterns in the emotion regulation network.

Default Mode Network alterations in alexithymia: an EEG power spectra and connectivity study

Recent neuroimaging studies have shown that alexithymia is characterized by functional alterations in different brain areas [e.g., posterior cingulate cortex (PCC)], during emotional/social tasks. However, only few data are available about alexithymic cortical networking features during resting state (RS). We have investigated the modifications of electroencephalographic (EEG) power spectra and EEG functional connectivity in the default mode network (DMN) in subjects with alexithymia. Eighteen subjects with alexithymia and eighteen subjects without alexithymia matched for age and gender were enrolled. EEG was recorded during 5 min of RS. EEG analyses were conducted by means of the exact Low Resolution Electric Tomography software (eLORETA). Compared to controls, alexithymic subjects showed a decrease of alpha power in the right PCC. In the connectivity analysis, compared to controls, alexithymic subjects showed a decrease of alpha connectivity between: (i) right anterior cingulate cortex and right PCC, (ii) right frontal lobe and right PCC, and (iii) right parietal lobe and right temporal lobe. Finally, mediation models showed that the association between alexithymia and EEG connectivity values was directed and was not mediated by psychopathology severity. Taken together, our results could reflect the neurophysiological substrate of some core features of alexithymia, such as the impairment in emotional awareness.

Neural Modulation in Aversive Emotion Processing: An Independent Component Analysis Study

Emotional processing has an important role in social interaction. We report the findings about the Independent Component Analysis carried out on a fMRI set obtained with a paradigm of face emotional processing. The results showed that an independent component, mainly cerebellar-medial-frontal, had a positive modulation associated with fear processing. Also, another independent component, mainly parahippocampal-prefrontal, showed a negative modulation that could be associated with implicit reappraisal of emotional stimuli. Independent Component Analysis could serve as a method to understand complex cognitive processes and their underlying neural dynamics.

Electroencephalographic findings in patients with major depressive disorder during cognitive or emotional tasks: a systematic review

Objective:

Major depressive disorder (MDD) is a prevalent psychiatric condition characterized by multiple symptoms that cause great distress. Uncovering the brain areas involved in MDD is essential for improving therapeutic strategies and predicting response to interventions. This systematic review discusses recent findings regarding cortical alterations in depressed patients during emotional or cognitive tasks, as measured by electroencephalography (EEG).

Methods:

A search of the MEDLINE/PubMed and Cochrane databases was carried out using the keywords EEG and depression, confined to article title.

Results:

The studies identified reveal the frontal cortex as an important brain structure involved in the complex neural processes associated with MDD. Findings point to disorganization of right-hemisphere activity and deficient cognitive processing in MDD. Depressed individuals tend to ruminate on negative information and respond with a pattern of relatively higher right frontal activity to emotional stimuli associated with withdrawal and isolation.

Conclusion:

Patients with MDD may have altered dynamic patterns of activity in several neuroanatomical structures, especially in prefrontal and limbic areas involved in affective regulation. Identification of these alterations might help predict the response of patients to different interventions more effectively and thus maximize the effects both of pharmacotherapeutic and of psychotherapeutic strategies.

Dysfunction of the cingulo-opercular network in first-episode medication-naive patients with major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a common psychiatric disorder that may be associated with abnormal cognitive control and emotion regulation. Previous studies have found that network disconnection within the cingulo-opercular network (CON) plays an important role in psychiatric disorders and that the CON may be relevant to the psychopathology of MDD. We thus used the resting-state functional connectivity method in patients with MDD and healthy controls to examine CON neural circuit abnormalities in MDD.

METHODS

Using resting-state functional magnetic resonance imaging (fMRI), we investigated the resting state functional connectivity of the CON using the dorsal anterior cingulate cortex (dACC) as the seed region of interest. The resulting functional connectivity (FC) correlation maps were employed to investigate between-group differences. Additionally, we examined the association between depression symptom severity and functional connectivity results. The participants were patients with MDD (n=19) and healthy controls (n=19).

RESULTS

Patients with MDD showed abnormalities in the connectivity of the CON. We found abnormal connectivity in MDD patients between the dACC and the bilateral middle frontal gyrus (MFG) and left angular gyrus (LAG) and precentral gyrus. Moreover, regression analysis showed that depression symptom severity (measured with the Hamilton Depression Rating Scale (HDRS), Hamilton Anxiety Rating Scale (HARS) and Automatic Thoughts Questionnaire scores (ATQ)) was significantly correlated with the FC values of the CON.

LIMITATIONS

First, our study consisted of a relatively small sample size that may have limited statistical power. Second, the current study design cannot conclusively specify the role of the CON in the neuropathology of depression.

CONCLUSIONS

Our findings suggest that MDD is associated with disrupted FC of the CON, which plays an important role in the pathophysiological mechanisms of MDD.

Accuracy of automated classification of major depressive disorder as a function of symptom severity

Background

Growing evidence documents the potential of machine learning for developing brain based diagnostic methods for major depressive disorder (MDD). As symptom severity may influence brain activity, we investigated whether the severity of MDD affected the accuracies of machine learned MDD-vs-Control diagnostic classifiers.

Methods

Forty-five medication-free patients with DSM-IV defined MDD and 19 healthy controls participated in the study. Based on depression severity as determined by the Hamilton Rating Scale for Depression (HRSD), MDD patients were sorted into three groups: mild to moderate depression (HRSD 14–19), severe depression (HRSD 20–23), and very severe depression (HRSD ≥ 24). We collected functional magnetic resonance imaging (fMRI) data during both resting-state and an emotional-face matching task. Patients in each of the three severity groups were compared against controls in separate analyses, using either the resting-state or task-based fMRI data. We use each of these six datasets with linear support vector machine (SVM) binary classifiers for identifying individuals as patients or controls.

Results

The resting-state fMRI data showed statistically significant classification accuracy only for the very severe depression group (accuracy 66%, p = 0.012 corrected), while mild to moderate (accuracy 58%, p = 1.0 corrected) and severe depression (accuracy 52%, p = 1.0 corrected) were only at chance. With task-based fMRI data, the automated classifier performed at chance in all three severity groups.

Conclusions

Binary linear SVM classifiers achieved significant classification of very severe depression with resting-state fMRI, but the contribution of brain measurements may have limited potential in differentiating patients with less severe depression from healthy controls.

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SVM binary classifiers achieved significant classification of very severe depression with resting state fMRI data.

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Prefrontal, anterior cingulate and insula were the most discriminative brain regions.

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No significant classification could be achieved for less severe MDD with resting state data.

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With emotional task data, SVM classifier performed at chance for all MDD severity groups.

The Significance of the Default Mode Network (DMN) in Neurological and Neuropsychiatric Disorders: A Review

The relationship of cortical structure and specific neuronal circuitry to global brain function, particularly its perturbations related to the development and progression of neuropathology, is an area of great interest in neurobehavioral science. Disruption of these neural networks can be associated with a wide range of neurological and neuropsychiatric disorders. Herein we review activity of the Default Mode Network (DMN) in neurological and neuropsychiatric disorders, including Alzheimer's disease, Parkinson's disease, Epilepsy (Temporal Lobe Epilepsy - TLE), attention deficit hyperactivity disorder (ADHD), and mood disorders. We discuss the implications of DMN disruptions and their relationship to the neurocognitive model of each disease entity, the utility of DMN assessment in clinical evaluation, and the changes of the DMN following treatment.

The Structural Connectivity Pattern of the Default Mode Network and Its Association with Memory and Anxiety

The default mode network (DMN) is one of the most widely studied resting state functional networks. The structural basis for the DMN is of particular interest and has been studied by several researchers using diffusion tensor imaging (DTI). Most of these previous studies focused on a few regions or white matter tracts of the DMN so that the global structural connectivity pattern and network properties of the DMN remain unclear. Moreover, evidences indicate that the DMN is involved in both memory and emotion, but how the DMN regulates memory and anxiety from the perspective of the whole DMN structural network remains unknown. We used multimodal neuroimaging methods to investigate the structural connectivity pattern of the DMN and the association of its network properties with memory and anxiety in 205 young healthy subjects with age ranging from 18 to 29 years old. The Group ICA method was used to extract the DMN component from functional magnetic resonance imaging (fMRI) data and a probabilistic fiber tractography technique based on DTI data was applied to construct the global structural connectivity pattern of the DMN. Then we used the graph theory method to analyze the DMN structural network and found that memory quotient (MQ) score was significantly positively correlated with the global and local efficiency of the DMN whereas anxiety was found to be negatively correlated with the efficiency. The strong structural connectivity between multiple brain regions within DMN may reflect that the DMN has certain structural basis. Meanwhile, the results we found that the network efficiency of the DMN were related to memory and anxiety measures, indicated that the DMN may play a role in the memory and anxiety.