Alteration of spontaneous neuronal activity in young adults with non-clinical depressive symptoms

Resting-state functional connectivity disruption between the left and right pallidum as a biomarker for subthreshold depression

Although the identification of late adolescents with subthreshold depression (StD) may provide a basis for developing effective interventions that could lead to a reduction in the prevalence of StD and prevent the development of major depressive disorder, knowledge about the neural basis of StD remains limited. The purpose of this study was to develop a generalizable classifier for StD and to shed light on the underlying neural mechanisms of StD in late adolescents. Resting-state functional magnetic resonance imaging data of 91 individuals (30 StD subjects, 61 healthy controls) were included to build an StD classifier, and eight functional connections were selected by using the combination of two machine learning algorithms. We applied this biomarker to an independent cohort (n = 43) and confirmed that it showed generalization performance (area under the curve = 0.84/0.75 for the training/test datasets). Moreover, the most important functional connection was between the left and right pallidum, which may be related to clinically important dysfunctions in subjects with StD such as anhedonia and hyposensitivity to rewards. Investigation of whether modulation of the identified functional connections can be an effective treatment for StD may be an important topic of future research.

"When You're Smiling": How Posed Facial Expressions Affect Visual Recognition of Emotions

Facial imitation occurs automatically during the perception of an emotional facial expression, and preventing it may interfere with the accuracy of emotion recognition. In the present fMRI study, we evaluated the effect of posing a facial expression on the recognition of ambiguous facial expressions. Since facial activity is affected by various factors, such as empathic aptitudes, the Interpersonal Reactivity Index (IRI) questionnaire was administered and scores were correlated with brain activity. Twenty-six healthy female subjects took part in the experiment. The volunteers were asked to pose a facial expression (happy, disgusted, neutral), then to watch an ambiguous emotional face, finally to indicate whether the emotion perceived was happiness or disgust. As stimuli, blends of happy and disgusted faces were used. Behavioral results showed that posing an emotional face increased the percentage of congruence with the perceived emotion. When participants posed a facial expression and perceived a non-congruent emotion, a neural network comprising bilateral anterior insula was activated. Brain activity was also correlated with empathic traits, particularly with empathic concern, fantasy and personal distress. Our findings support the idea that facial mimicry plays a crucial role in identifying emotions, and that empathic emotional abilities can modulate the brain circuits involved in this process.

Emotional Dysregulation in Mild Behavioral Impairment Is Associated with Reduced Cortical Thickness in the Right Supramarginal Gyrus

BACKGROUND

Mild behavioral impairment (MBI) has attracted attention as a possible precursor symptom of dementia, but its neural basis has not been fully investigated.

OBJECTIVE

We aimed to investigate the relationship between MBI and surface area, cortical thickness, and volume in the temporal and parietal lobes, which are strongly associated with dementia and emotional disorders.

METHODS

This retrospective study evaluated 123 participants: 90 with mild cognitive impairment (MCI), 13 with subjective cognitive decline (SCD), and 20 cognitively healthy (CH). Using analysis of covariance (ANCOVA) with sex, age, and MMSE score as covariates, cortical thickness, surface area, and volume in 10 regions were compared between groups with and without MBI. Groups with MBI emotional dysregulation were also compared with groups without MBI.

RESULTS

ANCOVA revealed significantly smaller cortical thickness in the MBI group's right parahippocampal (p = 0.01) and supramarginal gyri (p = 0.002). After multiple comparison correction, only the right supramarginal gyrus was significantly smaller (p = 0.02). When considering only MBI emotional dysregulation, the right parahippocampal and supramarginal gyrus' cortical thicknesses were significantly smaller in this MBI group (p = 0.03, 0.01). However, multiple comparison correction identified no significant differences (p = 0.14, 0.11).

CONCLUSION

Overall MBI and the emotional dysregulation domains were associated with reduced cortical thickness in the right parahippocampal and supramarginal gyri. Since neurodegeneration in the medial temporal and parietal lobe precedes early Alzheimer's disease (AD), MBI, particularly emotion dysregulation, may predict early AD below the diagnostic threshold.

Resting-state neural signal variability in women with depressive disorders

Aberrant activity and connectivity in default mode (DMN), frontoparietal (FPN), and salience (SN) network regions is well-documented in depression. Recent neuroimaging research suggests that altered variability in the blood oxygen level-dependent (BOLD) signal may disrupt normal network integration and be an important novel predictor of psychopathology. However, no studies have yet determined the relationship between resting-state BOLD signal variability and depressive disorders nor applied BOLD signal variability features to the classification of depression history using machine learning (ML). We collected resting-state fMRI data for 79 women with different depression histories: no history, past history, and current depressive disorder. We tested voxelwise differences in BOLD signal variability related to depression group and severity. We also investigated whether BOLD signal variability of DMN, FPN, and SN regions could predict depression history group using a supervised random forest ML model. Results indicated that individuals with any history of depression had significantly decreased BOLD signal variability in the left and right cerebellum and right parietal cortex (pFWE <0.05). Furthermore, greater depression severity was also associated with reduced BOLD signal variability in the cerebellum. A random forest model classified participant depression history with 74% accuracy, with the ventral anterior cingulate cortex of the DMN as the most important variable in the model. These findings provide novel support for resting-state BOLD signal variability as a marker of neural dysfunction in depression and implicate decreased neural signal variability in the pathophysiology of depression.

Resting-state neural activity and connectivity associated with subjective happiness

The majority of people throughout the world rate subjective happiness as the top of the important thing in life. A recent structural neuroimaging study exploring neurocognitive mechanisms underlying subjective happiness has suggested that the gray matter volume of the right precuneus is associated with Subjective Happiness Scale (SHS) scores. However, how the neural activity in this region, as well as the neural functional coupling between this and other regions, could be related to SHS scores remains unclear. To investigate these issues, we performed resting-state functional magnetic resonance imaging and analyzed the fractional amplitude of low-frequency fluctuation (fALFF) in participants, whose subjective happiness was evaluated using the SHS. Lower fALFF values in the right precuneus were associated with higher SHS scores. Furthermore, functional connectivity and spectral dynamic causal modeling analyses showed that both functional and effective connectivity of the right precuneus with the right amygdala were positively associated with SHS scores. These findings, together with other evidence on the information-processing functions of these brain regions, suggest the possibility that subjective happiness is associated with a reduction in self-referential mental processes, which are well integrated with emotional processing.

Cortical thickness in major depressive disorder: A systematic review and meta-analysis

Neuroimaging studies assessing neurobiological differences between patients with major depressive disorder (MDD) and healthy controls (HC) are often hindered by small sample sizes and heterogeneity of the patient sample. We performed a comprehensive literature search for studies assessing cortical thickness between patient and control groups, including studies investigating treatment effects on cortical thickness. We identified 34 studies meeting criteria for the systematic review and used Seed-based d Mapping to meta-analyze 24 of those that met additional criteria. Analysis of the full sample of subjects (MDD = 1073; HC = 936) revealed significant thinning in the MDD group in the bilateral orbitofrontal gyrus (BA 11), left pars opercularis (BA 45) and left calcarine fissure/lingual gyrus (BA 17), as well as an area of significant thickening in the left supramarginal gyrus (BA 40). These results support other imaging modalities that report disruptions in various frontal and temporal areas in MDD and identify additional areas in all major cerebral lobes likely to be significant when parsing for biomarkers of treatment or relapse.

Connectome-Based Biomarkers Predict Subclinical Depression and Identify Abnormal Brain Connections With the Lateral Habenula and Thalamus

Subclinical depression (SD) has been considered as the precursor to major depressive disorder. Accurate prediction of SD and identification of its etiological origin are urgent. Bursts within the lateral habenula (LHb) drive depression in rats, but whether dysfunctional LHb is associated with SD in human is unknown. Here we develop connectome-based biomarkers which predict SD and identify dysfunctional brain regions and connections. T1 weighted images and resting-state functional MRI (fMRI) data were collected from 34 subjects with SD and 40 healthy controls (HCs). After the brain is parcellated into 48 brain regions (246 subregions) using the human Brainnetome Atlas, the functional network of each participant is constructed by calculating the correlation coefficient for the time series of fMRI signals of each pair of subregions. Initial candidates of abnormal connections are identified by the two-sample t-test and input into Support Vector Machine models as features. A total of 24 anatomical-region-based models, 231 sliding-window-based models, and 100 random-selection-based models are built. The performance of these models is estimated through leave-one-out cross-validation and evaluated by measures of accuracy, sensitivity, confusion matrix, receiver operating characteristic curve, and the area under the curve (AUC). After confirming the region with the highest accuracy, subregions within the thalamus and connections associated with subregions of LHb are compared. It is found that five prediction models using connections of the thalamus, posterior superior temporal sulcus, cingulate gyrus, superior parietal lobule, and superior frontal gyrus achieve an accuracy >0.9 and an AUC >0.93. Among 90 abnormal connections associated with the thalamus, the subregion of the right posterior parietal thalamus where LHb is located has the most connections (n = 18), the left subregion only has 3 connections. In SD group, 10 subregions in the thalamus have significantly different node degrees with those in the HC group, while 8 subregions have lower degrees ( p < 0.01), including the one with LHb. These results implicate abnormal brain connections associated with the thalamus and LHb to be associated with SD. Integration of these connections by machine learning can provide connectome-based biomarkers to accurately diagnose SD.

Altered resting-state connectivity within default mode network associated with late chronotype

Current evidence suggests late chronotype individuals have an increased risk of developing depression. However, the underlying neural mechanisms of this association are not fully understood. Forty-six healthy, right-handed individuals free of current or previous diagnosis of depression, family history of depression or sleep disorder underwent resting-state functional Magnetic Resonance Imaging (rsFMRI). Using an Independent Component Analysis (ICA) approach, the Default Mode Network (DMN) was identified based on a well validated template. Linear effects of chronotype on DMN connectivity were tested for significance using non-parametric permutation tests (applying 5000 permutations). Sleep quality, age, gender, measures of mood and anxiety, time of scan and cortical grey matter volume were included as covariates in the regression model. A significant positive correlation between chronotype and functional connectivity within nodes of the DMN was observed, including; bilateral PCC and precuneus, such that later chronotype (participants with lower rMEQ scores) was associated with decreased connectivity within these regions. The current results appear consistent with altered DMN connectivity in depressed patients and weighted evidence towards reduced DMN connectivity in other at-risk populations which may, in part, explain the increased vulnerability for depression in late chronotype individuals. The effect may be driven by self-critical thoughts associated with late chronotype although future studies are needed to directly investigate this.

Altered interhemispheric functional connectivity in remitted bipolar disorder: A Resting State fMRI Study

Abnormalities in structural and functional brain connectivity have been increasingly reported in patients with bipolar disorder (BD). However, alterations of remitted BD (RBD) in functional connectivity between the cerebral hemispheres are still not well understood. This study was designed to analyze the pattern of the interhemispheric functional connectivity of the whole brain in patients with remitted BD during resting state. Twenty patients with RBD and 38 healthy controls (HC) underwent the resting-state functional magnetic resonance imaging. The functional connectivity between any pair of symmetrical interhemispheric voxels (i.e., functional homotopy) was measured by voxel-mirrored homotopic connectivity (VMHC). The patients with RBD showed lower VMHC than HC in the middle frontal gyrus and precentral gyrus. No regions of increased VMHC were detected in the RBD patients. There were no significant correlations between the VMHC values in these regions and the clinical variables. These findings suggest substantial impairment of interhemispheric coordination in RBD and they may represent trait, rather than state, neurobiological feature of brain function in BD.

Decreased Subcortical and Increased Cortical Degree Centrality in a Nonclinical College Student Sample with Subclinical Depressive Symptoms: A Resting-State fMRI Study

Abnormal functional connectivity (FC) at rest has been identified in clinical depressive disorder. However, very few studies have been conducted to understand the underlying neural substrates of subclinical depression. The newly proposed centrality analysis approach has been increasingly used to explore the large-scale brain network of mental diseases. This study aimed to identify the degree centrality (DC) alteration of the brain network in subclinical depressive subjects. Thirty-seven candidates with subclinical depression and 34 well-matched healthy controls (HCs) were recruited from the same sample of college students. All subjects underwent a resting-state fMRI (rs-fMRI) scan to assess the DC of the whole brain. Compared with controls, subclinical depressive subjects displayed decreased DC in the right parahippocampal gyrus (PHG), left PHG/amygdala, and left caudate and elevated DC in the right posterior parietal lobule (PPL), left inferior frontal gyrus (IFG) and left middle frontal gyrus (MFG). In addition, by using receiver operating characteristic (ROC) analysis, we determined that the DC values in the regions with altered FC between the two groups can be used to differentiate subclinical depressive subjects from HCs. We suggest that decreased DC in subcortical and increased DC in cortical regions might be the neural substrates of subclinical depression.

Neural activity during object perception in schizophrenia patients is associated with illness duration and affective symptoms

BACKGROUND

Abnormalities in visual processes have been observed in schizophrenia patients and have been associated with alteration of the lateral occipital complex and visual cortex. However, the relationship of these abnormalities with clinical symptomatology is largely unknown.

METHODS

We investigated the brain activity associated with object perception in schizophrenia. Pictures of common objects were presented to 26 healthy participants (age=36.9; 11 females) and 20 schizophrenia patients (age=39.9; 8 females) in an fMRI study.

RESULTS

In the healthy sample the presentation of pictures yielded significant activation (pFWE (cluster)<0.001) of the bilateral fusiform gyrus, bilateral lingual gyrus, and bilateral middle occipital gyrus. In patients, the bilateral fusiform gyrus and bilateral lingual gyrus were significantly activated (pFWE (cluster)<0.001), but not so the middle occipital gyrus. However, significant bilateral activation of the middle occipital gyrus (pFWE (cluster)<0.05) was revealed when illness duration was controlled for. Depression was significantly associated with increased activation, and anxiety with decreased activation, of the right middle occipital gyrus and several other brain areas in the patient group. No association with positive or negative symptoms was revealed.

CONCLUSIONS

Illness duration accounts for the weak activation of the middle occipital gyrus in patients during picture presentation. Affective symptoms, but not positive or negative symptoms, influence the activation of the right middle occipital gyrus and other brain areas.