Depression: perspectives from affective neuroscience

Individual large-scale functional network mapping for major depressive disorder with electroconvulsive therapy

Personalized functional connectivity mapping has been demonstrated to be promising in identifying underlying neurophysiological basis for brain disorders and treatment effects. Electroconvulsive therapy (ECT) has been proved to be an effective treatment for major depressive disorder (MDD) while its active mechanisms remain unclear. Here, 46 MDD patients before and after ECT as well as 46 demographically matched healthy controls (HC) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. A spatially regularized form of non-negative matrix factorization (NMF) was used to accurately identify functional networks (FNs) in individuals to map individual-level static and dynamic functional network connectivity (FNC) to reveal the underlying neurophysiological basis of therepetical effects of ECT for MDD. Moreover, these static and dynamic FNCs were used as features to predict the clinical treatment outcomes for MDD patients. We found that ECT could modulate both static and dynamic large-scale FNCs at individual level in MDD patients, and dynamic FNCs were closely associated with depression and anxiety symptoms. Importantly, we found that individual FNCs, particularly the individual dynamic FNCs could better predict the treatment outcomes of ECT suggesting that dynamic functional connectivity analysis may be better to link brain functional characteristics with clinical symptoms and treatment outcomes. Taken together, our findings provide new evidence for the active mechanisms and biomarkers for ECT to improve diagnostic accuracy and to guide individual treatment selection for MDD patients.

β-arrestin2 is indispensable for the antidepressant effects of fluoxetine via inhibiting astrocytic pyroptosis in chronic mild stress mouse model for depression

β-arrestin2 is a versatile protein for signaling transduction in brain physiology and pathology. Herein, we investigated the involvement of β-arrestin2 in pharmacological effects of fluoxetine for depression. A chronic mild stress (CMS) model was established using wild-type (WT) and β-arrestin2-/- mice. Behavioral results demonstrated that CMS mice showed increased immobility time in the tail suspension test and forced swimming test, elevated concentrations of pro-inflammatory factors in peripheral blood, increased expression of pyroptosis-related proteins, and increased co-labeling of glial fibrillary acidic protein and Caspase1 p10 in the hippocampus compared to the CON group. Treatment with fluoxetine (FLX) ameliorated these conditions. However, compared with the β-arrestin2-/- CMS group, these results of the β-arrestin2-/- CMS + FLX group showed no significant changes. These results suggested that the above effects of FLX could be eliminated by knocking out β-arrestin2. Mass spectrometry implying that FLX promoted the binding of β-arrestin2 to the NLRP2 inflammasome of depressed mice. Subsequently, the results of the cellular experiments suggested that the 5HT2B receptor antagonist may attenuate L-kynurenine + ATP-induced cell pyroptosis by attenuating NLRP2 binding to β-arrestin2. We further found that the lack of β-arrestin2 eliminated the anti-pyroptosis effect of fluoxetine. In conclusion, β-arrestin2 is an essential protein for fluoxetine to alleviate pyroptosis in the hippocampal astrocytes of CMS mice. Mechanistically, we found that the 5-HT2BR-β-arrestin2-NLRP2 axis is vital for maintaining the antidepressant effects of fluoxetine.

Intrinsic disruption of white matter microarchitecture in major depressive disorder: A voxel-based meta analysis of diffusion tensor imaging

BACKGROUND

Major depressive disorder (MDD) is a prevalent and disabling mood disorder, thought to be linked with brain white matter (WM) alterations. Prior diffusion tensor imaging (DTI) studies have reported inconsistent changes in fractional anisotropy (FA) across different brain regions in MDD patients. However, none of these studies utilized raw t-map data for WM meta-analysis in MDD. Our study aims to address this gap by conducting a whole-brain-based meta-analysis of FA in MDD using Seed-based d mapping via permutation of subject images (SDM-PSI), combining reported peak coordinates and raw statistical parametric maps.

OBJECTIVES

Following PRISMA guidelines, we performed a systematic search and meta-analysis to compare FA in MDD patients with healthy controls (HC). Our goal was to identify WM abnormalities in MDD, using SDM, which could shed light on the disorder's pathogenesis.

RESULTS

The meta-analysis included 39 studies with 3696 participants (2094 with MDD, 1602HC). It revealed that MDD patients, in comparison to HC, have lower FA in the corpus callosum (CC) and anterior thalamic projections (ATP). Subgroup analyses indicated that the CC is a more stable pathogenic factor in MDD. Meta-regression analyses showed no linear correlation between the mean age, percentage of female patients, duration of depression, and FA abnormalities. This suggests that WM impairments in interhemispheric connections and anterior thalamocortical circuits are significant in the pathogenesis of MDD.

From movement to motivation: a proposed framework to understand the antidepressant effect of exercise

Depression is the leading cause of disability worldwide, exerting a profound negative impact on quality of life in those who experience it. Depression is associated with disruptions to several closely related neural and cognitive processes, including dopamine transmission, fronto-striatal brain activity and connectivity, reward processing and motivation. Physical activity, especially aerobic exercise, reduces depressive symptoms, but the mechanisms driving its antidepressant effects are poorly understood. Here we propose a novel hypothesis for understanding the antidepressant effects of exercise, centred on motivation, across different levels of explanation. There is robust evidence that aerobic exercise decreases systemic inflammation. Inflammation is known to reduce dopamine transmission, which in turn is strongly implicated in effort-based decision making for reward. Drawing on a broad range of research in humans and animals, we propose that by reducing inflammation and boosting dopamine transmission, with consequent effects on effort-based decision making for reward, exercise initially specifically improves 'interest-activity' symptoms of depression-namely anhedonia, fatigue and subjective cognitive impairment - by increasing propensity to exert effort. Extending this framework to the topic of cognitive control, we explain how cognitive impairment in depression may also be conceptualised through an effort-based decision-making framework, which may help to explain the impact of exercise on cognitive impairment. Understanding the mechanisms underlying the antidepressant effects of exercise could inform the development of novel intervention strategies, in particular personalised interventions and boost social prescribing.

Fatty Acid Amide Hydrolase and Cannabinoid Receptor Type 1 Genes Regulation is Modulated by Social Isolation in Rats

Social isolation is a state of lack of social connections, involving the modulation of different molecular signalling cascades and associated with high risk of mental health issues. To investigate if and how gene expression is modulated by social experience at the central level, we analyzed the effects of 5 weeks of social isolation in rats focusing on endocannabinoid system genes transcription in key brain regions involved in emotional control. We observed selective reduction in mRNA levels for fatty acid amide hydrolase (Faah) and cannabinoid receptor type 1 (Cnr1) genes in the amygdala complex and of Cnr1 in the prefrontal cortex of socially isolated rats when compared to controls, and these changes appear to be partially driven by trimethylation of Lysine 27 and acetylation of Lysine 9 at Histone 3. The alterations of Cnr1 transcriptional regulation result also directly correlated with those of oxytocin receptor gene. We here suggest that to counteract the effects of SI, it is of relevance to restore the endocannabinoid system homeostasis via the use of environmental triggers able to revert those epigenetic mechanisms accounting for the alterations observed.

Self-Reported Mood and Lifestyle-Related Physical Activity of Young Adults With Major Depressive Disorder

We investigated whether mood and lifestyle-related indicators of physical health are differentially expressed according to self-reported levels of depressive symptoms among young adults with a current episode of major depression. In a cross-sectional study, we recruited 94 young adults (females = 67, 71.3%; males = 27, 28.7%; aged 18-35 years) with a current episode of major depression. We assessed their mood with the Profile of Mood States (POMS), and Beck Anxiety Inventory-(BAI), sleep with the Pittsburgh Sleep Quality Index (PSQI), physical activity with the Simple Physical Activity Questionnaire (SIMPAQ), and their cardiorespiratory fitness. Participants' depression levels were classified as follows using established cut-points: (a) Mild Depressive Symptoms (MIDS, BDI-II 14-19 points, n = 17), (b) Moderate Depressive Symptoms (MODS, BDI-II 20-28 points, n = 37) or (c) Severe Depressive Symptoms (SEDS, BDI-II 29-63 points, n = 40). As expected, we found that young adults with SEDS, when compared to those with MODS and MIDS, showed higher depressive mood on the POMS, and they exhibited greater anxiety symptoms, lower reported 'vigor' on physical activity measures, worse sleep quality as expressed by their global score sleep; daytime dysfunction; and sleep disturbance, and they showed lower cardiorespiratory fitness. Those with moderate depressive symptoms only differed from those with mild symptoms with respect to hostility, fatigue and mood disturbance. Although there was a gradient whereby worse mental and physical health indicators were more closely related to the SEDS depression categorization, while healthier indicators were associated with the MIDS category, some parameters were not different between the MDD severity groups, particularly when comparing MIDS and MODS. Clinicians treating patients with MDD should consider these factors when designing lifestyle-based interventions.

Affective neuroscience: applications for sexual medicine research and clinical practice

INTRODUCTION

Affective neuroscience is the study of the brain substrates of emotional, embodied experiences. Affective neuroscience theory (ANT) is based on experimental evidence that all mammals are hardwired with 7 primary subcortical emotional operating systems, or "core emotions," that have overlapping but distinct circuits buried in the deep, ancient parts of the brain. Imbalances in the 7 core emotions can affect multiple aspects of the individual's psychosocial well-being (eg, depression, anxiety, substance abuse). Here, we propose that core emotions can also influence sexual function and, specifically, that imbalances in core emotions are the bridge connecting psychiatric symptoms (eg, anhedonia) to sexual dysfunction (eg, anorgasmia).

OBJECTIVES

In this targeted review and commentary, we outline potential connections between ANT and sexual medicine research and clinical practice. We summarize ANT by defining the 3-level BrainMind and core emotions; examining how they relate to personality, behavior, and mental health; and determining the implications for sexual health research and clinical practice.

METHODS

A targeted literature review was conducted. Case studies were adapted from client files and clinician interviews and then anonymized.

RESULTS

We propose a novel organizational schema for implementing affective balance therapies for sexual dysfunction, which integrate psychoeducational, somatic, and cognitive therapeutic approaches under the ANT framework. We provide 3 patient case studies (anorgasmia, hypersexuality, spinal cord injury) outlining the implementation of this approach and patient outcomes.

CONCLUSION

ANT has practical translational applications in sexual health research and clinical practice. By integrating our understanding of the role of core emotions in human sexuality, clinicians can better tailor treatments to address sexual dysfunction.

Decreased intrinsic neural timescale in treatment-naïve adolescent depression

BACKGROUND

Major depressive disorder (MDD) is mainly characterized by its core dysfunction in higher-order brain cortices involved in emotional and cognitive processes, whose neurobiological basis remains unclear. In this study, we applied a relatively new developed resting-state functional magnetic resonance imaging (rs-fMRI) method of intrinsic neural timescale (INT), which reflects how long neural information is stored in a local brain area and reflects an ability of information integration, to investigate the local intrinsic neural dynamics using univariate and multivariate analyses in adolescent depression.

METHOD

Based on the rs-fMRI data of sixty-six treatment-naïve adolescents with MDD and fifty-two well-matched healthy controls (HCs), we calculated an INT by assessing the magnitude of autocorrelation of the resting-state brain activity, and then compared the difference of INT between the two groups. Correlation between abnormal INT and clinical features was performed. We also utilized multivariate pattern analysis to determine whether INT could differentiate MDD patients from HCs at the individual level.

RESULT

Compared with HCs, patients with MDD showed shorter INT widely distributed in cortical and partial subcortical regions. Interestingly, the decreased INT in the left hippocampus was related to disease severity of MDD. Furthermore, INT can distinguish MDD patients from HCs with the most discriminative regions located in the dorsolateral prefrontal cortex, angular, middle occipital gyrus, and cerebellar posterior lobe.

CONCLUSION

Our research aids in advancing understanding the brain abnormalities of treatment-naïve adolescents with MDD from the perspective of the local neural dynamics, highlighting the significant role of INT in understanding neurophysiological mechanisms. This study shows that the altered intrinsic timescales of local neural signals widely distributed in higher-order brain cortices regions may be the neurodynamic basis of cognitive and emotional disturbances in MDD patients, and provides preliminary support for the suggestion that these could be used to aid the identification of MDD patients in clinical practice.

Theta oscillatory dynamics serving cognitive control index psychosocial distress in youth

Background

Psychosocial distress among youth is a major public health issue characterized by disruptions in cognitive control processing. Using the National Institute of Mental Health's Research Domain Criteria (RDoC) framework, we quantified multidimensional neural oscillatory markers of psychosocial distress serving cognitive control in youth.

Methods

The sample consisted of 39 peri-adolescent participants who completed the NIH Toolbox Emotion Battery (NIHTB-EB) and the Eriksen flanker task during magnetoencephalography (MEG). A psychosocial distress index was computed with exploratory factor analysis using assessments from the NIHTB-EB. MEG data were analyzed in the time-frequency domain and peak voxels from oscillatory maps depicting the neural cognitive interference effect were extracted for voxel time series analyses to identify spontaneous and oscillatory aberrations in dynamics serving cognitive control as a function of psychosocial distress. Further, we quantified the relationship between psychosocial distress and dynamic functional connectivity between regions supporting cognitive control.

Results

The continuous psychosocial distress index was strongly associated with validated measures of pediatric psychopathology. Theta-band neural cognitive interference was identified in the left dorsolateral prefrontal cortex (dlPFC) and middle cingulate cortex (MCC). Time series analyses of these regions indicated that greater psychosocial distress was associated with elevated spontaneous activity in both the dlPFC and MCC and blunted theta oscillations in the MCC. Finally, we found that stronger phase coherence between the dlPFC and MCC was associated with greater psychosocial distress.

Conclusions

Greater psychosocial distress was marked by alterations in spontaneous and oscillatory theta activity serving cognitive control, along with hyperconnectivity between the dlPFC and MCC.

Altered resting-state brain oscillation and the associated cognitive impairments in late-life depression with different depressive severity: An EEG power spectrum and functional connectivity study

OBJECTIVE

Cognitive impairments are prevalent in late-life depression (LLD). However, it remains unclear whether there are concurrent brain oscillation alterations in resting condition across varying level of depression severity. This cross-sectional study aims to investigate the characteristics of altered resting-state oscillations, including power spectrum and functional connectivity, and their association with the cognitive impairments in LLD with different depression severity.

METHODS

A total of 65 patients with LLD and 40 elder participants without depression were recruited. Global cognition and subtle cognitive domains were evaluated. A five-minute resting-state electroencephalography (EEG) was conducted under eyes-closed conditions. Measurements included the ln-transformed absolute power for power spectrum analysis and the weighted phase lag index (wPLI) for functional connectivity analysis.

RESULTS

Attentional and executive dysfunction were exhibited in Moderate-Severe LLD group. Enhanced posterior upper gamma power was observed in both LLD groups. Additionally, enhanced parietal and fronto-parietal/occipital theta connectivity were observed in Moderate-Severe LLD group, which were associated with the attentional impairment.

LIMITATIONS

Limitations include a small sample size, concomitant medication use, and a relatively higher proportion of females.

CONCLUSIONS

Current study observed aberrant brain activity patterns in LLD across different levels of depression severity, which were linked to cognitive impairments. The altered posterior brain oscillations may be trait marker of LLD. Moreover, cognitive impairments and associated connectivity alterations were exhibited in moderate-severe group, which may be a state-like marker of moderate-to severe LLD. The study deepens understanding of cognitive impairments with the associated oscillation changes, carrying implications for neuromodulation targets in LLD.

Behavioral and neuroanatomical correlates of facial emotion processing in post-stroke depression

BACKGROUND

Emotion processing deficits are known to accompany depressive symptoms and are often seen in stroke patients. Little is known about the influence of post-stroke depressive (PSD) symptoms and specific brain lesions on altered emotion processing abilities and how these phenomena develop over time. This potential relationship may impact post-stroke rehabilitation of neurological and psychosocial function. To address this scientific gap, we investigated the relationship between PSD symptoms and emotion processing abilities in a longitudinal study design from the first days post-stroke into the early chronic phase.

METHODS

Twenty-six ischemic stroke patients performed an emotion processing task on videos with emotional faces ('happy,' 'sad,' 'anger,' 'fear,' and 'neutral') at different intensity levels (20%, 40%, 60%, 80%, 100%). Recognition accuracies and response times were measured, as well as scores of depressive symptoms (Montgomery-Åsberg Depression Rating Scale). Twenty-eight healthy participants matched in age and sex were included as a control group. Whole-brain support-vector regression lesion-symptom mapping (SVR-LSM) analyses were performed to investigate whether specific lesion locations were associated with the recognition accuracy of specific emotion categories.

RESULTS

Stroke patients performed worse in overall recognition accuracy compared to controls, specifically in the recognition of happy, sad, and fearful faces. Notably, more depressed stroke patients showed an increased processing towards specific negative emotions, as they responded significantly faster to angry faces and recognized sad faces of low intensities significantly more accurately. These effects obtained for the first days after stroke partly persisted to follow-up assessment several months later. SVR-LSM analyses revealed that inferior and middle frontal regions (IFG/MFG) and insula and putamen were associated with emotion-recognition deficits in stroke. Specifically, recognizing happy facial expressions was influenced by lesions affecting the anterior insula, putamen, IFG, MFG, orbitofrontal cortex, and rolandic operculum. Lesions in the posterior insula, rolandic operculum, and MFG were also related to reduced recognition accuracy of fearful facial expressions, whereas recognition deficits of sad faces were associated with frontal pole, IFG, and MFG damage.

CONCLUSION

PSD symptoms facilitate processing negative emotional stimuli, specifically angry and sad facial expressions. The recognition accuracy of different emotional categories was linked to brain lesions in emotion-related processing circuits, including insula, basal ganglia, IFG, and MFG. In summary, our study provides support for psychosocial and neural factors underlying emotional processing after stroke, contributing to the pathophysiology of PSD.

Vulnerability of the Hippocampus to Insults: Links to Blood-Brain Barrier Dysfunction

The hippocampus is a critical brain substrate for learning and memory; events that harm the hippocampus can seriously impair mental and behavioral functioning. Hippocampal pathophysiologies have been identified as potential causes and effects of a remarkably diverse array of medical diseases, psychological disorders, and environmental sources of damage. It may be that the hippocampus is more vulnerable than other brain areas to insults that are related to these conditions. One purpose of this review is to assess the vulnerability of the hippocampus to the most prevalent types of insults in multiple biomedical domains (i.e., neuroactive pathogens, neurotoxins, neurological conditions, trauma, aging, neurodegenerative disease, acquired brain injury, mental health conditions, endocrine disorders, developmental disabilities, nutrition) and to evaluate whether these insults affect the hippocampus first and more prominently compared to other brain loci. A second purpose is to consider the role of hippocampal blood-brain barrier (BBB) breakdown in either causing or worsening the harmful effects of each insult. Recent research suggests that the hippocampal BBB is more fragile compared to other brain areas and may also be more prone to the disruption of the transport mechanisms that act to maintain the internal milieu. Moreover, a compromised BBB could be a factor that is common to many different types of insults. Our analysis indicates that the hippocampus is more vulnerable to insults compared to other parts of the brain, and that developing interventions that protect the hippocampal BBB may help to prevent or ameliorate the harmful effects of many insults on memory and cognition.

The effect of chronic academic stress on intentional forgetting

This study investigated whether chronic academic stress could affect the directed forgetting (DF) process. Both the stress group (undergoing preparation for a major academic examination) and the control group performed a DF task. A forgetting cue was presented after a to-be-forgotten (TBF) word, whereas no cue appeared after a to-be-remembered (TBR) item in the study phase. An old/new recognition test was used in the test phase. The results showed that (1) the stress group showed a higher level of self-reported stress, state anxiety, negative affect, and decreased cortisol awakening response (CAR) compared with the control group, suggesting a higher level of stress for the stress group. (2) Both groups showed superior recognition performance of TBR than TBF items, suggesting a DF effect. (3) The stress group showed inferior recognition performance of TBF items and an enhanced DF effect compared with the control group. These results demonstrated that the intentional memory control process might be enhanced under chronic academic stress.

Cortical glutamate, Glx, and total N-acetylaspartate: potential biomarkers of repetitive transcranial magnetic stimulation treatment response and outcomes in major depression

Repetitive transcranial magnetic stimulation (rTMS) is an effective treatment for individuals with major depressive disorder (MDD) who have not improved with standard therapies. However, only 30-45% of patients respond to rTMS. Predicting response to rTMS will benefit both patients and providers in terms of prescribing and targeting treatment for maximum efficacy and directing resources, as individuals with lower likelihood of response could be redirected to more suitable treatment alternatives. In this exploratory study, our goal was to use proton magnetic resonance spectroscopy to examine how glutamate (Glu), Glx, and total N-acetylaspartate (tNAA) predict post-rTMS changes in overall MDD severity and symptoms, and treatment response. Metabolites were measured in a right dorsal anterior cingulate cortex voxel prior to a standard course of 10 Hz rTMS to the left DLPFC in 25 individuals with MDD. MDD severity and symptoms were evaluated via the Inventory of Depression Symptomatology Self-Report (IDS-SR). rTMS response was defined as ≥50% change in full-scale IDS-SR scores post treatment. Percent change in IDS-SR symptom domains were evaluated using principal component analysis and established subscales. Generalized linear and logistic regression models were used to evaluate the relationship between baseline Glu, Glx, and tNAA and outcomes while controlling for age and sex. Participants with baseline Glu and Glx levels in the lower range had greater percent change in full scale IDS-SR scores post-treatment (p < 0.001), as did tNAA (p = 0.007). Low glutamatergic metabolite levels also predicted greater percent change in mood/cognition symptoms (p ≤ 0.001). Low-range Glu, Glx, and tNAA were associated with greater improvement on the immuno-metabolic subscale (p ≤ 0.003). Baseline Glu predicted rTMS responder status (p = 0.025) and had an area under the receiving operating characteristic curve of 0.81 (p = 0.009), demonstrating excellent discriminative ability. Baseline Glu, Glx, and tNAA significantly predicted MDD improvement after rTMS; preliminary evidence also demonstrates metabolite association with symptom subdomain improvement post-rTMS. This work provides feasibility for a personalized medicine approach to rTMS treatment selection, with individuals with Glu levels in the lower range potentially being the best candidates.

Novel mechanism-based treatments for pediatric anxiety and depressive disorders

Pediatric anxiety and depressive disorders are common, can be highly impairing, and can persist despite the best available treatments. Here, we review research into novel treatments for childhood anxiety and depressive disorders designed to target underlying cognitive, emotional, and neural circuit mechanisms. We highlight three novel treatments lying along a continuum relating to clinical impact of the disorder and the intensity of clinical management required. We review cognitive training, which involves the lowest risk and may be applicable for problems with mild to moderate impact; psychotherapy, which includes a higher level of clinical involvement and may be sufficient for problems with moderate impact; and brain stimulation, which has the highest potential risks and is therefore most appropriate for problems with high impact. For each treatment, we review the specific underlying cognitive, emotional, and brain circuit mechanisms that are being targeted, whether treatments modify those underlying mechanisms, and efficacy in reducing symptoms. We conclude by highlighting future directions, including the importance of work that leverages developmental windows of high brain plasticity to time interventions to the specific epochs in childhood that have the largest and most enduring life-long impact.

Baby blues, premenstrual syndrome and postpartum affective disorders: intersection of risk factors and reciprocal influences

BACKGROUND

The aetiology and consequences of 'baby blues' (lower mood following childbirth) are yet to be sufficiently investigated with respect to an individual's clinical history.

AIMS

The primary aim of the study was to assess the symptoms of baby blues and the relevant risk factors, their associations with clinical history and premenstrual syndrome (PMS), and their possible contribution to the early recognition of postpartum depression (PPD).

METHOD

Beginning shortly after childbirth, 369 mothers were followed up for 12 weeks. Information related to their clinical history, PMS, depression, stress and mother-child attachment was collected. At 12 weeks, mothers were classified as non-depressed, or with either PPD or adjustment disorder.

RESULTS

A correlation was found between the severity of baby blues and PMS (r = 0.397, P < 0.001), with both conditions increasing the possibility of adjustment disorder and PPD (baby blues: OR = 6.72, 95% CI 3.69-12.25; PMS: OR = 3.29, 95% CI 2.01-5.39). Baby blues and PMS independently predicted whether a mother would develop adjustment disorder or PPD after childbirth (χ2(64) = 198.16, P < 0.001). Among the non-depressed participants, baby blues were found to be associated with primiparity (P = 0.012), family psychiatric history (P = 0.001), PMS (P < 0.001) and childhood trauma (P = 0.017).

CONCLUSIONS

Baby blues are linked to a number of risk factors and a history of PMS, with both conditions adding to the risk of PPD. The neuroendocrine effects on mood need be understood in the context of individual risk factors. The assessment of both baby blues and PMS symptoms within the first postpartum days may contribute to an early identification of PPD.

Human-centred artificial intelligence for mobile health sensing: challenges and opportunities

Advances in wearable sensing and mobile computing have enabled the collection of health and well-being data outside of traditional laboratory and hospital settings, paving the way for a new era of mobile health. Meanwhile, artificial intelligence (AI) has made significant strides in various domains, demonstrating its potential to revolutionize healthcare. Devices can now diagnose diseases, predict heart irregularities and unlock the full potential of human cognition. However, the application of machine learning (ML) to mobile health sensing poses unique challenges due to noisy sensor measurements, high-dimensional data, sparse and irregular time series, heterogeneity in data, privacy concerns and resource constraints. Despite the recognition of the value of mobile sensing, leveraging these datasets has lagged behind other areas of ML. Furthermore, obtaining quality annotations and ground truth for such data is often expensive or impractical. While recent large-scale longitudinal studies have shown promise in leveraging wearable sensor data for health monitoring and prediction, they also introduce new challenges for data modelling. This paper explores the challenges and opportunities of human-centred AI for mobile health, focusing on key sensing modalities such as audio, location and activity tracking. We discuss the limitations of current approaches and propose potential solutions.

Emotional processing and positive affect after acute exercise in healthy older adults

The well-elucidated improvement of mood immediately after exercise in older adults presumably involves adaptations in emotion-processing brain networks. However, little is known about effects of acute exercise on appetitive and aversive emotion-related network recruitment in older adults. The purpose of this study was to determine the effect of acute exercise, compared to a seated rest control condition, on pleasant and unpleasant emotion-related regional activation in healthy older adults. Functional MRI data were acquired from 32 active older adults during blocked presentations of pleasant, neutral and unpleasant images from the International Affective Pictures System. fMRI data were collected after participants completed 30 min of moderate to vigorous intensity cycling or seated rest, performed in a counterbalanced order across separate days in a within-subject design. The findings suggest three ways that emotional processing in the brain may be different immediately after exercise (relative to immediately after rest): First, reduced demands on emotional regulation during pleasant emotional processing as indicated by lower precuneus activation for pleasant stimuli; second, reduced processing of negative emotional stimuli in visual association areas as indicated by lower activation for unpleasant stimuli in the bilateral fusiform and ITG; third, an increased recruitment in activation associated with regulating/inhibiting unpleasant emotional processing in the bilateral medial superior frontal gyrus (dorsomedial prefrontal cortex), angular gyri, supramarginal gyri, left cerebellar crus I/II and a portion of right dorsolateral prefrontal cortex. Overall, these findings support that acute exercise in active older adults alters activation in key emotional processing and regulating brain regions.

Neuroanatomy of post-stroke depression: the association between symptom clusters and lesion location

Post-stroke depression affects about 30% of stroke patients and often hampers functional recovery. The diagnosis of depression encompasses heterogeneous symptoms at emotional, motivational, cognitive, behavioural or somatic levels. Evidence indicates that depression is caused by disruption of bio-aminergic fibre tracts between prefrontal and limbic or striatal brain regions comprising different functional networks. Voxel-based lesion-symptom mapping studies reported discrepant findings regarding the association between infarct locations and depression. Inconsistencies may be due to the usage of sum scores, thereby mixing different symptoms of depression. In this cross-sectional study, we used multivariate support vector regression for lesion-symptom mapping to identify regions significantly involved in distinct depressive symptom domains and global depression. MRI lesion data were included from 200 patients with acute first-ever ischaemic stroke (mean 0.9 ± 1.5 days of post-stroke). The Montgomery-Åsberg Depression Rating interview assessed depression severity in five symptom domains encompassing motivational, emotional and cognitive symptoms deficits, anxiety and somatic symptoms and was examined 8.4 days of post-stroke (±4.3). We found that global depression severity, irrespective of individual symptom domains, was primarily linked to right hemispheric lesions in the dorsolateral prefrontal cortex and inferior frontal gyrus. In contrast, when considering distinct symptom domains individually, the analyses yielded much more sensitive results in regions where the correlations with the global depression score yielded no effects. Accordingly, motivational deficits were associated with lesions in orbitofrontal cortex, dorsolateral prefrontal cortex, pre- and post-central gyri and basal ganglia, including putamen and pallidum. Lesions affecting the dorsal thalamus, anterior insula and somatosensory cortex were significantly associated with emotional symptoms such as sadness. Damage to the dorsolateral prefrontal cortex was associated with concentration deficits, cognitive symptoms of guilt and self-reproach. Furthermore, somatic symptoms, including loss of appetite and sleep disturbances, were linked to the insula, parietal operculum and amygdala lesions. Likewise, anxiety was associated with lesions impacting the central operculum, insula and inferior frontal gyrus. Interestingly, symptoms of anxiety were exclusively left hemispheric, whereas the lesion-symptom associations of the other domains were lateralized to the right hemisphere. In conclusion, this large-scale study shows that in acute stroke patients, differential post-stroke depression symptom domains are associated with specific structural correlates. Our findings extend existing concepts on the neural underpinnings of depressive symptoms, indicating that differential lesion patterns lead to distinct depressive symptoms in the first weeks of post-stroke. These findings may facilitate the development of personalized treatments to improve post-stroke rehabilitation.

Research on a New Intelligent and Rapid Screening Method for Depression Risk in Young People Based on Eye Tracking Technology

Depression is a prevalent mental disorder, with young people being particularly vulnerable to it. Therefore, we propose a new intelligent and rapid screening method for depression risk in young people based on eye tracking technology. We hypothesized that the "emotional perception of eye movement" could characterize defects in emotional perception, recognition, processing, and regulation in young people at high risk for depression. Based on this hypothesis, we designed the "eye movement emotional perception evaluation paradigm" and extracted digital biomarkers that could objectively and accurately evaluate "facial feature perception" and "facial emotional perception" characteristics of young people at high risk of depression. Using stepwise regression analysis, we identified seven digital biomarkers that could characterize emotional perception, recognition, processing, and regulation deficiencies in young people at high risk for depression. The combined effectiveness of an early warning can reach 0.974. Our proposed technique for rapid screening has significant advantages, including high speed, high early warning efficiency, low cost, and high intelligence. This new method provides a new approach to help effectively screen high-risk individuals for depression.

Hippocampus links perceived social support with self-esteem

Self-esteem is an important psychological resource with adaptive values, and numerous investigations have revealed that self-esteem is influenced by perceived social support. However, the potential neural basis linking perceived social support with self-esteem remains unclear. Therefore, we used voxel-based morphometry to explore whether the hippocampus and amygdala function as the neuroanatomical basis linking perceived social support with self-esteem in a cohort of 243 young healthy adults (128 women; mean age 22.64 years, standard deviation 1.01 years). The Social Provisions Scale and Rosenberg Self Esteem Scale were used for the survey. Magnetic resonance imaging was used to measure the gray matter volume of the hippocampus and amygdala. Correlation analysis revealed that those who perceived more social support had higher self-esteem. Notably, mediation analysis showed that hippocampal gray matter volume linked perceived social support with self-esteem. Our study suggests that the hippocampus plays a primary, but not exclusive, role in linking perceived social support with self-esteem, which provides a novel explanation for how perceived social support affects self-esteem from the perspective of cognitive neuroscience.

A resting state EEG study on depressed persons with suicidal ideation

Background

Major Depressive Disorder (MDD) is a psychiatric illness that is often associated with potentially life-threatening physiological changes and increased risk for suicidal behavior. Electroencephalography (EEG) research suggests an association between depression and specific frequency imbalances in the frontal brain region. Further, while recently developed technology has been proposed to simplify EEG data acquisition, more research is still needed to support its use in patients with MDD.

Methods

Using the 14-channel EMOTIV EPOC cap, we recorded resting state EEG from 15 MDD patients with and MDD persons with suicidal ideation (SI) vs. 12 healthy controls (HC) to investigate putative power spectral density (PSD) between-group differences at the F3 and F4 electrode sites. Specifically, we explored 1) between-group alpha power asymmetries (AA), 2) between-group differences in delta, theta, alpha and beta power, 3) between PSD data and the scores in the Beck's Depression Inventory-II (BDI-II), Beck's Anxiety Inventory (BAI), Reasons for Living Inventory (RFL), and Self-Disgust Questionnaire (SDS).

Results

When compared to HC, patients had higher scores on the BAI (p = 0.0018), BDI-II (p = 0.0001) or SDS (p = 0.0142) scale and lower scores in the RFL (p = 0.0006) scale. The PSD analysis revealed no between-group difference or correlation with questionnaire scores for any of the measures considered.

Conclusions

The present study could not confirm previous research suggesting frequency-specific anomalies in depressed persons with SI but might suggest that frontal EEG imbalances reflect greater anxiety and negative self-referencing. Future studies should confirm these findings in a larger population sample.

Agomelatine: A Potential Multitarget Compound for Neurodevelopmental Disorders

Agomelatine (AGM) is one of the latest atypical antidepressants, prescribed exclusively for the treatment of depression in adults. AGM belongs to the pharmaceutical class of melatonin agonist and selective serotonin antagonist ("MASS"), as it acts both as a selective agonist of melatonin receptors MT1 and MT2, and as a selective antagonist of 5-HT2C/5-HT2B receptors. AGM is involved in the resynchronization of interrupted circadian rhythms, with beneficial effects on sleep patterns, while antagonism on serotonin receptors increases the availability of norepinephrine and dopamine in the prefrontal cortex, with an antidepressant and nootropic effect. The use of AGM in the pediatric population is limited by the scarcity of data. In addition, few studies and case reports have been published on the use of AGM in patients with attention deficit and hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Considering this evidence, the purpose of this review is to report the potential role of AGM in neurological developmental disorders. AGM would increase the expression of the cytoskeleton-associated protein (ARC) in the prefrontal cortex, with optimization of learning, long-term memory consolidation, and improved survival of neurons. Another important feature of AGM is the ability to modulate glutamatergic neurotransmission in regions associated with mood and cognition. With its synergistic activity a melatoninergic agonist and an antagonist of 5-HT2C, AGM acts as an antidepressant, psychostimulant, and promoter of neuronal plasticity, regulating cognitive symptoms, resynchronizing circadian rhythms in patients with autism, ADHD, anxiety, and depression. Given its good tolerability and good compliance, it could potentially be administered to adolescents and children.

Functional Connectivity Mapping for rTMS Target Selection in Depression

OBJECTIVE

Repetitive transcranial magnetic stimulation (rTMS) protocols increasingly use subgenual anterior cingulate cortex (sgACC) functional connectivity to individualize treatment targets. However, the efficacy of this approach is unclear, with conflicting findings and varying effect sizes across studies. Here, the authors investigated the effect of the stimulation site's functional connectivity with the sgACC (sgACC-StimFC) on treatment outcome to rTMS in 295 patients with major depression.

METHODS

The reliability and accuracy of estimating sgACC functional connectivity were validated with data from individuals who underwent extensive functional MRI testing. Electric field modeling was used to analyze associations between sgACC-StimFC and clinical improvement using standardized assessments and to evaluate sources of heterogeneity.

RESULTS

An imputation-based method provided reliable and accurate sgACC functional connectivity estimates. Treatment responses weakly but robustly correlated with sgACC-StimFC (r=-0.16), but only when the stimulated cortex was identified using electric field modeling. Surprisingly, this association was driven by patients with strong global signal fluctuations stemming from a specific periodic respiratory pattern (r=-0.49).

CONCLUSIONS

Functional connectivity between the sgACC and the stimulated cortex was correlated with individual differences in treatment outcomes, but the association was weaker than those observed in previous studies and was accentuated in a subgroup of patients with distinct, respiration-related signal patterns in their scans. These findings indicate that in a large representative sample of patients with major depressive disorder, individual differences in sgACC-StimFC explained only ∼3% of the variance in outcomes, which may limit the utility of existing sgACC-based targeting protocols. However, these data also provide strong evidence for a true-albeit small-effect and highlight opportunities for incorporating additional functional connectivity measures to generate models of rTMS response with enhanced predictive power.

The Possible Role of Apathy on Conflict Monitoring: Preliminary Findings of a Behavioral Study on Severe Acquired Brain Injury Patients Using Flanker Tasks

The diagnosis of apathy, one of the most common behavioral changes after acquired brain injury (ABI), is important for improving clinical understanding and treatment of persons with ABI. The main aim of this study was to determine the possible role of apathy in conflict monitoring, by using choice reaction time tasks. Methods: We examined behavioral responses of conflict monitoring during three different flanker tasks in 10 severe ABI patients with or without diagnosis of apathy (3 M, mean age = 56.60; 3 M, mean age ± SD = 58.60, respectively), and 15 healthy controls (9 M, mean age = 54.46) Reaction times (RTs), accuracy, and global index of performance (GIP) were analyzed for each task. Results: Only apathetic ABI patients showed a significant difference from healthy subjects (p-value ≤ 0.001), while the performance of patients without apathy was not significantly different from that of healthy controls (p-value = 0.351). Healthy participants had higher accuracy in comparison to both ABI patients with (p < 0.001) and without (p-value = 0.038) apathy, whilst slower RTs were shown by ABI patients without apathy in comparison to both healthy subjects (p-value = 0.045) and apathetic ABI patients (p-value = 0.022). Only patients with apathy exhibited a significantly higher number of missing trials (p-value = 0.001). Conclusions: Our results may suggest a potential link between apathy following severe ABI and conflict monitoring processes, even though further investigations with larger sample size are needed.

Negative Bias or Positive Deficiency, or Both? The Relationship Between Individual Authenticity and Depression Among Preschool Teachers: The Sequential Mediation Effects of Mindfulness and Self-Alienation

Objective

Depression has become a topic of widespread concern around the world, and teachers' depression has also had an important impact on the healthy development of education. However, there are differences in the cognitive theory of depression and positive psychology about the mechanism of depression. This study attempts to verify the related viewpoints of the two viewpoints through empirical research.

Methods

Three hundred and twenty eight preschool teachers were measured with authenticity scale, five facet mindfulness questionnaire, center for epidemiologic studies depression scale, and general alienation scale.

Results

Individual authenticity negatively predicted depression. Mindfulness can mediate the relationship between individual authenticity and depression. Self-alienation mediates the relationship between individual authenticity and depression. In addition, mindfulness and self-alienation played a sequential mediating role between individual authenticity and depression.

Conclusion

Mindfulness and self-alienation play a sequential mediating role between individual authenticity and depression. This study not only confirms the relevant theoretical viewpoints of positive psychology on depression, but also believes that individual depression is not only affected by one's own negative bias but also by one's own positive factors. At the same time, the individual's own positive factors will affect the negative factors. This perspective will provide new literature references to existing relevant theories about depression. In addition, this study will also provide literature reference for early childhood education practice.

Cognitive rehabilitation for improving cognitive functions and reducing the severity of depressive symptoms in adult patients with Major Depressive Disorder: a systematic review and meta-analysis of randomized controlled clinical trials

INTRODUCTION

Nearly 40% of patients with Major Depressive Disorder (MDD) have been found to experience cognitive impairment in at least one domain. Cognitive impairment associated with MDD is disproportionately represented in patients that have not fully returned to psychosocial functioning. As awareness regarding cognitive dysfunction in MDD patients grows, so does the interest in developing newer treatments that specifically address these deficits.

METHOD

In the present study, we conduct a systematic review of controlled randomized clinical trials that used cognitive training and remediation interventions for improving cognitive functions and reducing symptom severity in adult patients with MDD. We selected studies published before March 2022 using search databases including PubMed, ScienceDirect, Scopus, and Google scholar. For conducting the meta-analysis, standard differences in means with the random effect model and with a 95% confidence interval of change in outcome measures from baseline to post-intervention between the cognitive rehabilitation and the control groups were calculated.

RESULTS

The database search resulted in identifying 756 studies of interest, which ultimately 15 studies with 410 participants in the cognitive rehabilitation group and 339 participants in the control group were included. The meta-analysis of the data extracted from these studies, shows a moderate and significant effect on the executive function (d = 0.59 (95% CI, 0.25 to 0.93) p-value = 0.001, I² = 15.2%), verbal learning (d = 0.45 (95% CI, 0.12 to 0.78) p-value = 0.007, I² = 0.00%), and working memory (d = 0.41 (95% CI, 0.18 to 0.64) p-value < 0.001, I² = 33%) of MDD patients. Although, there were no significant difference between intervention and control group in attention (d = 0.32 (95% CI, -0.01 to 0.66) p-value = 0.058, I² = 0.00%) or depressive symptoms.

CONCLUSION

This systematic review and meta-analysis indicate that cognitive rehabilitation is an effective intervention for the executive function, verbal learning, and working memory of MDD patients. Due to the importance of these neuropsychological deficits in day-to-day life and the core symptoms of MDD, cognitive rehabilitation should be considered an important part of treating MDD. Further research in this area and concentrated on these particular deficits is warranted.

Neurofeedback Treatment Affects Affective Symptoms, But Not Perceived Cognitive Impairment in Cancer Patients: Results of an Explorative Randomized Controlled Trial

BACKGROUND

EEG biofeedback (NF) is an established therapy to enable individuals to influence their own cognitive-emotional state by addressing changes in brainwaves. Psycho-oncological approaches of NF in cancer patients are rare and effects are hardly studied.

OBJECTIVE

The aim of this explorative, randomized controlled trial was to test the effectiveness of an alpha and theta NF training protocol, compared to mindfulness based therapy as an established psycho-oncological treatment.

METHODS

Of initially 62 screened patients, 56 were included (inclusion criteria were cancer independent of tumor stage, age >18 years, German speaking; exclusion criteria suicidal ideation, brain tumor). Randomization and stratification (tumor stage) was conducted by a computer system. Participants got 10 sessions over 5 weeks, in (a) an NF intervention (n = 21; 13 female, 8 male; MAge = 52.95(10 519); range = 31 to 73 years)) or (b) a mindfulness group therapy as control condition (CG; n = 21; ie, 15 female, 6 male; MAge = 50.33(8708); range = 32 to 67 years)). Outcome parameters included self-reported cognitive impairment (PCI) as primary outcome, and secondary outcomes of emotional distress (DT, PHQ-8, GAD-7), fatigue (MFI-20), rumination (RSQ), quality of life (QoL, EORTC-30 QoL), self-efficacy (GSE), and changes in EEG alpha, and theta-beta band performance in the NF condition.

RESULTS

No changes in cognitive impairment were found (P = .079), neither in NF nor CG. High affective distress was evident, with 70.7% showing elevated distress and 34.1% showing severe depressive symptoms. Affective symptoms of distress (P ≤ .01), depression (P ≤ .05) and generalized anxiety (P ≤ .05) decreased significantly over time. No differences between NF and CG were found. There was a significant increase of the alpha band (P ≤ .05; N = 15) over the NF sessions. Self-efficacy predicted QoL increase in NF with P ≤ .001 and an explained variance of 48.2%.

CONCLUSION

This is the first study to investigate NF technique with regard to basic mechanisms of effectiveness in a sample of cancer patients, compared to an established psycho-oncological intervention in this field. Though there were no changes in cognitive impairment, present data show that NF improves affective symptoms comparably to mindfulness-based therapy and even more pronounced in QoL and self-efficacy.Trial registration: ID: DRKS00015773.

Functional contextual implementation of an evolutionary, entropy-based, and embodied free energy framework: Utilizing Lagrangian mechanics and evolutionary game theory's truth vs. fitness test of the veridicality of phenomenological experience

The Bayesian approach of cognitive science largely takes the position that evolution drives perception to produce precepts that are veridical. However, some efforts utilizing evolutionary game theory simulations have shown that perception is more likely based on a fitness function, which promotes survival rather than promoting perceptual truth about the environment. Although these findings do not correspond well with the standard Bayesian approach to cognition, they may correspond with a behavioral functional contextual approach that is ontologically neutral (a-ontological). This approach, formalized through a post-Skinnerian account of behaviorism called relational frame theory (RFT), can, in fact, be shown to correspond well with an evolutionary fitness function, whereby contextual functions form that corresponds to a fitness function interface of the world. This fitness interface approach therefore may help provide a mathematical description for a functional contextual interface of phenomenological experience. Furthermore, this more broadly fits with a neurological active inference approach based on the free-energy principle (FEP) and more broadly with Lagrangian mechanics. These assumptions of how fitness beats truth (FBT) and FEP correspond to RFT are then discussed within a broader multidimensional and evolutionary framework called the extended evolutionary meta-model (EEMM) that has emerged out of the functional contextual behavioral science literature to incorporate principles of cognition, neurobiology, behaviorism, and evolution and are discussed in the context of a novel RFT framework called "Neurobiological and Natural Selection Relational Frame Theory" (N-frame). This framework mathematically connects RFT to FBT, FEP, and EEMM within a single framework that expands into dynamic graph networking. This is then discussed for its implications of empirical work at the non-ergodic process-based idiographic level as applied to individual and societal level dynamic modeling and clinical work. This discussion is framed within the context of individuals that are described as evolutionary adaptive and conscious (observer-self) agents that minimize entropy and can promote a prosocial society through group-level values and psychological flexibility.

FMRI study of implicit emotional face processing in patients with MDD with melancholic subtype

Introduction

The accurate perception of facial expressions plays a vital role in daily life, allowing us to select appropriate responses in social situations. Understanding the neuronal basis of altered emotional face processing in patients with major depressive disorder (MDD) may lead to the appropriate choice of individual interventions to help patients maintain social functioning during depressive episodes. Inconsistencies in neuroimaging studies of emotional face processing are caused by heterogeneity in neurovegetative symptoms of depressive subtypes. The aim of this study was to investigate brain activation differences during implicit perception of faces with negative and positive emotions between healthy participants and patients with melancholic subtype of MDD. The neurobiological correlates of sex differences of MDD patients were also examined.

Methods

Thirty patients diagnosed with MDD and 21 healthy volunteers were studied using fMRI while performing an emotional face perception task.

Results

Comparing general face activation irrespective of emotional content, the intensity of BOLD signal was significantly decreased in the left thalamus, right supramarginal gyrus, right and left superior frontal gyrus, right middle frontal gyrus, and left fusiform gyrus in patients with melancholic depression compared to healthy participants. We observed only limited mood-congruence in response to faces of differing emotional valence. Brain activation in the middle temporal gyrus was significantly increased in response to fearful faces in comparison to happy faces in MDD patients. Elevated activation was observed in the right cingulate for happy and fearful faces, in precuneus for happy faces, and left posterior cingulate cortex for all faces in depressed women compared to men. The Inventory for Depressive Symptomatology (IDS) score was inversely correlated with activation in the left subgenual gyrus/left rectal gyrus for sad, neutral, and fearful faces in women in the MDD group. Patients with melancholic features performed similarly to controls during implicit emotional processing but showed reduced activation.

Discussion and conclusion

This finding suggests that melancholic patients compensate for reduced brain activation when interpreting emotional content in order to perform similarly to controls. Overall, frontal hypoactivation in response to implicit emotional stimuli appeared to be the most robust feature of melancholic depression.

An automated platform for Assessing Working Memory and prefrontal circuit function

Working memory is a process for actively maintaining and updating task-relevant information, despite interference from competing inputs, and is supported in part by sustained activity in prefrontal cortical pyramidal neurons and coordinated interactions with inhibitory interneurons, which may serve to regulate interference. Chronic stress has potent effects on working memory performance, possibly by interfering with these interactions or by disrupting long-range inputs from key upstream brain regions. Still, the mechanisms by which chronic stress disrupts working memory are not well understood, due in part to a need for scalable, easy-to-implement behavioral assays that are compatible with two-photon calcium imaging and other tools for recording from large populations of neurons. Here, we describe the development and validation of a platform that was designed specifically for automated, high-throughput assessments of working memory and simultaneous two-photon imaging in chronic stress studies. This platform is relatively inexpensive and easy to build; fully automated and scalable such that one investigator can test relatively large cohorts of animals concurrently; fully compatible with two-photon imaging, yet also designed to mitigate head-fixation stress; and can be easily adapted for other behavioral paradigms. Our validation data confirm that mice could be trained to perform a delayed response working memory task with relatively high-fidelity over the course of ∼15 days. Two-photon imaging data validate the feasibility of recording from large populations of cells during working memory tasks performance and characterizing their functional properties. Activity patterns in >70% of medial prefrontal cortical neurons were modulated by at least one task feature, and a majority of cells were engaged by multiple task features. We conclude with a brief literature review of the circuit mechanisms supporting working memory and their disruption in chronic stress states-highlighting directions for future research enabled by this platform.

Fluctuations in core depressive symptoms in colorectal cancer patients. A prospective, population-based PROFILES-registry study

PURPOSE

Research investigating depressive symptoms among cancer patients rarely distinguish between core symptoms of depression (motivational and consummatory anhedonia, and negative affect). This distinction is important as these symptoms may show different trajectories during the course of the illness and require different treatment approaches. The aim of the present study is to investigate fluctuations in core depressive symptoms in patients with colorectal cancer (CRC). It is hypothesized that these core depressive symptoms fluctuate differently during the course of the illness and depend on the phase of the illness (diagnostic, treatment, recovery and palliative phase).

METHOD

This study is based on data from the PROCORE study. PROCORE is a prospective, population-based study aimed to examine the longitudinal impact of CRC and its treatment on patient-reported outcomes. Eligible patients completed self-report questionnaires (i.e. Multifactorial Fatigue Index, Hospital Anxiety and Depression scale, EORTC-C30) after diagnosis, after surgery and at one and two years after diagnosis.

RESULTS

In total, 539 patients participated of whom 68 have died until March 1ste 2021. Core depressive symptoms fluctuated differently during the course of the illness with higher levels of motivational anhedonia during treatment and palliative phase (P<.001), consummatory anhedonia at the palliative phase (p < .001) and negative affect at the diagnostic and palliative phase (P<.001).

CONCLUSION

It is important to distinguish between different core depressive symptoms as they fluctuate differently during the course of an illness like CRC. The various depressive symptoms may require a different treatment approach at specific moments during the illness process.

Mining voices from self-expressed messages on social-media: Diagnostics of mental distress during COVID-19

The COVID-19 pandemic has had a severe impact on mankind, causing physical suffering and deaths across the globe. Even those who have not contracted the virus have experienced its far-reaching impacts, particularly on their mental health. The increased incidences of psychological problems, anxiety associated with the infection, social restrictions, economic downturn, etc., are likely to aggravate with the virus spread and leave a longer impact on humankind. These reasons in aggregation have raised concerns on mental health and created a need to identify novel precursors of depression and suicidal tendencies during COVID-19. Identifying factors affecting mental health and causing suicidal ideation is of paramount importance for timely intervention and suicide prevention. This study, thus, bridges this gap by utilizing computational intelligence and Natural Language Processing (NLP) to unveil the factors underlying mental health issues. We observed that the pandemic and subsequent lockdown anxiety emerged as significant factors leading to poor mental health outcomes after the onset of COVID-19. Consistent with previous works, we found that psychological disorders have remained pre-eminent. Interestingly, financial burden was found to cause suicidal ideation before the pandemic, while it led to higher odds of depressive (non-suicidal) thoughts for individuals who lost their jobs. This study offers significant implications for health policy makers, governments, psychiatric practitioners, and psychologists.

Altered functional connectivity in emotional subregions of the anterior cingulate cortex in young and middle-aged patients with major depressive disorder: A resting-state fMRI study

BACKGROUND

It has been demonstrated that the anterior cingulate cortex (ACC) has three subregions, involved in behavior, cognition, and emotion. However, the intrinsic connectivity of the ACC subregions in patients with major depressive disorder (MDD) is still unclear. In this study, functional magnetic resonance imaging (fMRI) data was used to detect the functional connectivity (FC) of ACC subregions and the correlation with the disease severity in young and middle-aged patients with MDD.

METHODS

A total of 36 young and middle-aged patients with first-episode MDD and 36 healthy controls (HCs) were enrolled in this study. FC was applied to investigate altered connectivity of the ACC subregion in MDD patients compared to HCs. Correlation analysis was then used to assess possible relationship between the neuroimaging findings and clinical symptoms in the patient group.

RESULTS

Compared to HCs, young and middle-aged patients had significantly decreased FC between the emotional subregion of the ACC and the hippocampus, thalamus, insula, angular gyrus, and posterior cingulate cortex. The FC between the ACC emotional subregion and the insula, the AG, the RPHG was negatively correlated with depression index. The FC between the ACC emotional subregion and the putamen was positively correlated with depression index.

CONCLUSION

The present findings indicate that abnormal ACC subregions-seeded FC may be implicated in the MDD-related abnormalities of emotion regulation and information processing. And there is a correlation between the above FC changes and the clinical symptoms of young and middle-aged MDD patients. This study may provide preliminary evidence for the ACC-related neural mechanism in young and middle-aged MDD patients and enhance the understanding of the pathophysiology of MDD.

From descriptive connectome to mechanistic connectome: Generative modeling in functional magnetic resonance imaging analysis

As a newly emerging field, connectomics has greatly advanced our understanding of the wiring diagram and organizational features of the human brain. Generative modeling-based connectome analysis, in particular, plays a vital role in deciphering the neural mechanisms of cognitive functions in health and dysfunction in diseases. Here we review the foundation and development of major generative modeling approaches for functional magnetic resonance imaging (fMRI) and survey their applications to cognitive or clinical neuroscience problems. We argue that conventional structural and functional connectivity (FC) analysis alone is not sufficient to reveal the complex circuit interactions underlying observed neuroimaging data and should be supplemented with generative modeling-based effective connectivity and simulation, a fruitful practice that we term "mechanistic connectome." The transformation from descriptive connectome to mechanistic connectome will open up promising avenues to gain mechanistic insights into the delicate operating principles of the human brain and their potential impairments in diseases, which facilitates the development of effective personalized treatments to curb neurological and psychiatric disorders.

No travel worsens depression: reciprocal relationship between travel and depression among older adults

BACKGROUND

The aim of this study was to examine the bidirectional relationship between depression and travel.

METHOD

We analyzed 8524 participants' data obtained from the 2008 to 2016 waves of the Korean Longitudinal Study of Ageing, a prospective cohort study. Depression was diagnosed using the Center for Epidemiological Studies Depression Scale: 10-Items (CES-D10), with scores of 4 or higher indicating depression. We used a generalized estimating equation and a cross-lagged panel model for statistical analysis.

RESULTS

Participants who had not traveled for one year had a 71% higher risk of suffering from depression in the following year than did those who had traveled [relative risk (RR) = 1.71, P < 0.001], and participants with depression had more than double the increased risk of not traveling than did those not currently suffering from depression (RR = 2.08, P < 0.001). The cross-lagged panel model confirmed the vicious cycle involving the amount of travel and score on the CES-D10; individuals who traveled more frequently were more likely to have lower scores on the CES-D10 (coefficient = - 0.04 to - 0.03, Ps < 0.01), and individuals with higher scores were less likely to travel (coefficient = - 0.06 to - 0.03, Ps < 0.01).

CONCLUSIONS

The risk of depression increases for people who do not travel, and a reciprocal relationship exists between travel and depression.

Encore: Behavioural animal models of stress, depression and mood disorders

Animal studies over the past two decades have led to extensive advances in our understanding of pathogenesis of depressive and mood disorders. Among these, rodent behavioural models proved to be of highest informative value. Here, we present a comprehensive overview of the most popular behavioural models with respect to physiological, circuit, and molecular biological correlates. Behavioural stress paradigms and behavioural tests are assessed in terms of outcomes, strengths, weaknesses, and translational value, especially in the domain of pharmacological studies.

Altered intrinsic default mode network functional connectivity in patients with remitted geriatric depression and amnestic mild cognitive impairment

OBJECTIVES

Patients with geriatric depression exhibit a spectrum of symptoms ranging from mild to severe cognitive impairment which could potentially lead to the development of Alzheimer's disease (AD). The aim of the study is to assess the alterations of the default mode network (DMN) in remitted geriatric depression (RGD) patients and whether it could serve as an underlying neuropathological mechanism associated with the risk of progression of AD.

DESIGN

Cross-sectional study.

PARTICIPANTS

A total of 154 participants, comprising 66 RGD subjects (which included 27 patients with comorbid amnestic mild cognitive impairment [aMCI] and 39 without aMCI [RGD]), 45 aMCI subjects without a history of depression (aMCI), and 43 matched healthy comparisons (HC), were recruited.

MEASUREMENTS

All participants completed neuropsychological tests and underwent resting-state functional magnetic resonance imaging (fMRI). Posterior cingulate cortex (PCC)-seeded DMN functional connectivity (FC) along with cognitive function were compared among the four groups, and correlation analyses were conducted.

RESULTS

In contrast to HC, RGD, aMCI, and RGD-aMCI subjects showed significant impairment across all domains of cognitive functions except for attention. Furthermore, compared with HC, there was a similar and significant decrease in PCC-seed FC in the bilateral medial superior frontal gyrus (M-SFG) in the RGD, aMCI, and RGD-aMCI groups.

CONCLUSIONS

The aberrations in rsFC of the DMN were associated with cognitive deficits in RGD patients and might potentially reflect an underlying neuropathological mechanism for the increased risk of developing AD. Therefore, altered connectivity in the DMN could serve as a potential neural marker for the conversion of geriatric depression to AD.

Alterations in white matter microarchitecture in adolescents and young adults with major depressive disorder: A voxel-based meta-analysis of diffusion tensor imaging

Adolescents and young adults are at a critical stage of life development, and depression can have serious consequences. In recent decades, an increasing number of diffusion tensor imaging (DTI) studies of major depressive disorder (MDD) have reported inconsistent alterations in white matter (WM) microarchitecture. To rule out the confounding effects of age, we conducted a meta-analysis of fractional anisotropy (FA) in adolescents and young adults with MDD to identify abnormalities in WM involved in the pathogenesis of MDD using anisotropic effect-size signed differential mapping (AES-SDM). The pooled meta-analysis revealed significantly lower FA mainly in the corpus callosum (CC) extending to the left anterior thalamic projections (ATP) and left cortico-spinal projection (CSP) in depressed adolescents and young adults than that in healthy controls. A reduction in FA was also identified in the right frontal orbito-polar tract (FOPT) extending to the right inferior fronto-occipital fasciculus (IFOF). In the meta-regression analysis, the mean age of patients, percentage of female patients and duration of depression were not linearly associated with abnormalities in FA. These results constitute robust evidence that abnormalities in WM microarchitecture in the interhemispheric connections and frontal-subcortical neuronal circuits may contribute to the pathogenesis of MDD during adolescence and young adulthood.

Mood-congruent negative thinking styles and cognitive vulnerability in depressed COVID-19 survivors: A comparison with major depressive disorder

BACKGROUND

COVID-19 is associated with depressive psychopathology in survivors. Negative thinking styles are a core feature of major depression, fostering the experience of negative emotions and affects and hampering recovery. This cognitive vulnerability has been observed in medical conditions associated with depression, but never explored in post-COVID depression.

METHODS

We studied 729 participants: 362 COVID-19 survivors, 73 inpatients with Major Depressive Disorder (MDD), and 294 healthy participants (HC). Severity of depression was self-rated on the Zung Self-Rating Depression Scale (ZSDS). Neuropsychological bias toward negative emotional stimuli and the negative outlook on the self were tested in a self-description task, yielding latencies and frequencies of attribution of morally tuned elements. Dimensions of negative thinking and depressive cognitive style in evaluation of hypothetical events were measured on the Cognition Questionnaire (CQ).

RESULTS

22.4% COVID survivors self-rated depression above the clinical threshold. Frequencies and latencies of attribution of morally negative elements, and CQ scores, correlated between themselves and predicted ZSDS scores, with post-COVID depressed patients showing intermediate scores between the more severe MDD patients, and non-depressed post-COVID participants and HC.

LIMITATIONS

Recruitment was in a single center, thus raising the possibility of population stratification.

CONCLUSIONS

The breadth of self-reproach and depressive cognitive style in evaluating events showed the same association with severity of depression in MDD and in post-COVID depressed patients, distributing along a gradient of severity, thus suggesting that individual features of negative thinking styles are shared in these conditions, and should be addressed as treatment targets in depressed COVID-19 survivors.

Self-Reported Depression Is Associated With Aberration in Emotional Reactivity and Emotional Concept Coding

Cognitive impairment, alterations in mood, emotion dysregulation are just a few of the consequences of depression. Despite depression being reported as the most common mental disorder worldwide, examining depression or risks of depression is still challenging. Emotional reactivity has been observed to predict the risk of depression, but the results have been mixed for negative emotional reactivity (NER). To better understand the emotional response conflict, we asked our participants to describe their feeling in meaningful sentences alongside reporting their reactions to the emotionally evocative words. We presented a word on the screen and asked participants to perform two tasks, rate their feeling after reading the word using the self-assessment manikin (SAM) scale, and describe their feeling using the property generation task. The emotional content was analyzed using a novel machine-learning algorithm approach. We performed these two tasks in blocks and randomized their order across participants. Beck Depression Inventory (BDI) was used to categorize participants into self-reported non-depressed (ND) and depressed (D) groups. Compared to the ND, the D group reported reduced positive emotional reactivity when presented with extremely pleasant words regardless of their arousal levels. However, no significant difference was observed between the D and ND groups for negative emotional reactivity. In contrast, we observed increased sadness and inclination toward low negative context from descriptive content by the D compared to the ND group. The positive content analyses showed mixed results. The contrasting results between the emotional reactivity and emotional content analyses demand further examination between cohorts of self-reported depressive symptoms, no-symptoms, and MDD patients to better examine the risks of depression and help design early interventions.

A Novel Stress State Assessment Method for College Students Based on EEG

Stress is an unavoidable problem for today's college students. Stress can arouse strong personal emotional and behavioral responses. Compared with other groups of the same age, college students have a special way of life and living environment. They have complex interpersonal relationships and relatively weak social support systems. At the same time, they also face fierce competition in both academic and employment. However, they lack the skills to deal with the crisis and are reluctant to ask others for help, which leads to a simultaneous increase in mental stress. The pressure on college students mainly comes from study, family, social, employment, society, and economy. When students face multiple pressures from family, school, society, etc., some students are prone to some psychological problems due to their own personality or external environment and other reasons. Therefore, regular assessment of students' stress status is an important means to prevent college students' psychological problems. Considering that in real life, the number of students whose pressure is within the tolerable range is the majority, while the number of students who are under too much pressure is a minority. Therefore, the actual dataset to be identified belongs to a kind of imbalanced data. In this study, an improved extreme learning machine (IELM) is used to improve the performance of the recognition model as much as possible. IELM takes the idea of label weighting as the starting point, introduces the AdaBoost algorithm, and combines its weight distribution with the label weighted extreme learning machine (ELM). During the weight update process, the advantage of the imbalanced nature of multi-label datasets is taken. IELM was used to classify EEG data to determine the stress level of college students. The experimental results demonstrate that the algorithm used in this study has excellent classification performance and can accurately assess students' stress levels. The accurate assessment of stress has provided a solid foundation for the development of students' mental health and has significant practical implications.

Mu opioid receptors on hippocampal GABAergic interneurons are critical for the antidepressant effects of tianeptine

Tianeptine is an atypical antidepressant used in Europe to treat patients who respond poorly to selective serotonin reuptake inhibitors (SSRIs). The recent discovery that tianeptine is a mu opioid receptor (MOR) agonist has provided a potential avenue for expanding our understanding of antidepressant treatment beyond the monoamine hypothesis. Thus, our studies aim to understand the neural circuits underlying tianeptine's antidepressant effects. We show that tianeptine induces rapid antidepressant-like effects in mice after as little as one week of treatment. Critically, we also demonstrate that tianeptine's mechanism of action is distinct from fluoxetine in two important aspects: (1) tianeptine requires MORs for its chronic antidepressant-like effect, while fluoxetine does not, and (2) unlike fluoxetine, tianeptine does not promote hippocampal neurogenesis. Using cell-type specific MOR knockouts we further show that MOR expression on GABAergic cells-specifically somatostatin-positive neurons-is necessary for the acute and chronic antidepressant-like responses to tianeptine. Using central infusion of tianeptine, we also implicate the ventral hippocampus as a potential site of antidepressant action. Moreover, we show a dissociation between the antidepressant-like phenotype and other opioid-like phenotypes resulting from acute tianeptine administration such as analgesia, conditioned place preference, and hyperlocomotion. Taken together, these results suggest a novel entry point for understanding what circuit dysregulations may occur in depression, as well as possible targets for the development of new classes of antidepressant drugs.

Mindfulness-Enhanced Computerized Cognitive Training for Depression: An Integrative Review and Proposed Model Targeting the Cognitive Control and Default-Mode Networks

Depression is often associated with co-occurring neurocognitive deficits in executive function (EF), processing speed (PS) and emotion regulation (ER), which impact treatment response. Cognitive training targeting these capacities results in improved cognitive function and mood, demonstrating the relationship between cognition and affect, and shedding light on novel targets for cognitive-focused interventions. Computerized cognitive training (CCT) is one such new intervention, with evidence suggesting it may be effective as an adjunct treatment for depression. Parallel research suggests that mindfulness training improves depression via enhanced ER and augmentation of self-referential processes. CCT and mindfulness training both act on anti-correlated neural networks involved in EF and ER that are often dysregulated in depression—the cognitive control network (CCN) and default-mode network (DMN). After practicing CCT or mindfulness, downregulation of DMN activity and upregulation of CCN activity have been observed, associated with improvements in depression and cognition. As CCT is posited to improve depression via enhanced cognitive function and mindfulness via enhanced ER ability, the combination of both forms of training into mindfulness-enhanced CCT (MCCT) may act to improve depression more rapidly. MCCT is a biologically plausible adjunct intervention and theoretical model with the potential to further elucidate and target the causal mechanisms implicated in depressive symptomatology. As the combination of CCT and mindfulness has not yet been fully explored, this is an intriguing new frontier. The aims of this integrative review article are four-fold: (1) to briefly review the current evidence supporting the efficacy of CCT and mindfulness in improving depression; (2) to discuss the interrelated neural networks involved in depression, CCT and mindfulness; (3) to present a theoretical model demonstrating how MCCT may act to target these neural mechanisms; (4) to propose and discuss future directions for MCCT research for depression.

Cross-Sectional Associations between Living and Built Environments and Depression Symptoms among Chinese Older Adults

In this study, we explored the cross-sectional associations between living and built environments and depression among older Chinese adults. Data from 5822 participants were obtained. Depression symptoms were evaluated through the use of the Patient Health Questionnaire (PHQ-9), with a score higher than 4 categorized as having depression symptoms. The living environment was assessed by asking about dust in the environment and barrier-free facilities. We considered the presence of amenities within a 10 min walking distance and the proportion of green space within an 800 m distance from participants’ dwellings to reflect the built environment. Data were analyzed by multilevel logistic regression. Participants living in a non-dusty environment with proximity to green space had a lower risk of depression (non-dusty environment: OR = 0.784, 95% CI = 0.642, 0.956; green space: OR = 0.834, 95% CI = 0.697, 0.998). However, having no access to barrier-free facilities and hospital proximity increased the depression risk (barrier-free facilities: OR = 1.253, 95% CI = 1.078, 1.457; hospital: OR = 1.318, 95% CI = 1.104, 1.574). Dusty environments, access to barrier-free facilities and proximity to hospitals and green spaces were associated with depression symptoms among older Chinese adults.

Higher Peripheral Inflammation Is Associated With Lower Orbitofrontal Gamma Power in Chronic Tinnitus

Chronic tinnitus, the continuous perception of a phantom sound, is a highly prevalent audiological symptom, for which the underlying pathology has not yet been fully understood. It is associated with neurophysiological alterations in the central nervous system and chronic stress, which can be related with a disinhibition of the inflammatory system. We here investigated the association between resting-state oscillatory activity assessed with Magnetoencephalography (MEG), and peripheral inflammation assessed by C-reactive protein (CRP) in a group of patients with chronic tinnitus (N = 21, nine males, mean age: 40.6 ± 14.6 years). Additionally, CRP was assessed in an age- and sex-matched healthy control group (N = 21, nine males, mean age: 40.9 ± 15.2 years). No MEG data was available for the control group. We found a significant negative correlation between CRP and gamma power in the orbitofrontal cortex in tinnitus patients (p < 0.001), pointing to a deactivation of the orbitofrontal cortex when CRP was high. No significant clusters were found for other frequency bands. Moreover, CRP levels were significantly higher in the tinnitus group than in the healthy controls (p = 0.045). Our results can be interpreted based on findings from previous studies having disclosed the orbitofrontal cortex as part of the tinnitus distress network. We suggest that higher CRP levels and the associated deactivation of the orbitofrontal cortex in chronic tinnitus patients is maintaining the tinnitus percept through disinhibition of the auditory cortex and attentional or emotional top-down processes. Although the direction of the association (i.e., causation) between CRP levels and orbitofrontal gamma power in chronic tinnitus is not yet known, inflammation reducing interventions are promising candidates when developing treatments for tinnitus patients. Overall, our study highlights the importance of considering immune-brain communication in tinnitus research.

An aberrant hippocampal subregional network, rather than structure, characterizes major depressive disorder

BACKGROUND

Behavioral and neuroimaging studies have implicated the hippocampus as a cardinal neural structure in major depressive disorder (MDD) pathogenesis. The hippocampal subregion-specific structural and functional abnormalities in MDD remain unknown.

METHODS

Multimodal magnetic resonance imaging (MRI) was acquired in 140 patients with MDD and 44 age- and sex-matched healthy controls (HCs). We quantified hippocampal subregional volumes and fractional anisotropy (FA) following a structural and diffusion MRI data analysis processing stream. Hippocampal subregional networks were established using seed-based functional connectivity (FC) analysis. Univariate analysis was used to investigate the differences between the two groups. Significant subfield metrics were correlated with depression severity.

RESULTS

Compared with HCs, we did not find significant differences in subregional volumes or FA metrics in the MDD group. The MDD group exhibited a significantly weaker connectivity of the right hippocampal subregional networks with the temporal cortex (extending to the insula) and basal ganglia but showed increased connectivity of the right subiculum to the bilateral lingual gyrus. The FC between the right cornu ammonis 1 and right fusiform, between the right hippocampal amygdala transition area and the bilateral basal ganglia, were negatively correlated with depression severity (r = -0.224, p = 0.010; r = -0.196, p = 0.025, respectively) in the MDD group.

LIMITATIONS

This study did not consider the longitudinal changes in the structure and functional connectivity of the hippocampal subregion.

CONCLUSION

These findings advance our understanding of the neurobiological basis of depression by identifying the hippocampal subregional structural and functional abnormalities.