Aberrant brain dynamics in major depressive disorder during working memory task.

Working memory (WM) is a distributed and dynamic process, and WM deficits are recognized as one of the top-ranked endophenotype candidates for major depressive disorders (MDD). However, there is a lack of knowledge of brain temporal-spatial profile of WM deficits in MDD. We used the dynamical degree centrality (dDC) to investigate the whole-brain temporal-spatial profile in 40 MDD and 40 controls during an n-back task with 2 conditions (i.e., '0back' and '2back'). We explored the dDC temporal variability and clustered meta-stable states in 2 groups during different WM conditions. Pearson's correlation analysis was used to evaluate the relationship between the altered dynamics with clinical symptoms and WM performance. Compared with controls, under '2back vs. 0back' contrast, patients showed an elevated dDC variability in wide range of brain regions, including the middle frontal gyrus, orbital part of inferior frontal gyrus (IFGorb), hippocampus, and middle temporal gyrus. Furthermore, the increased dDC variability in the hippocampus and IFGorb correlated with worse WM performance. However, there were no significant group-related differences in the meta-stable states were observed. This study demonstrated the increased WM-related instability (i.e., the elevated dDC variability) was represented in MDD, and enhancing stability may help patients achieve better WM performance.

Multimetric structural covariance in first-episode major depressive disorder: a graph theoretical analysis.

BACKGROUND: Abnormalities of cortical morphology have been consistently reported in major depressive disorder (MDD), with widespread focal alterations in cortical thickness, surface area and gyrification. However, it is unclear whether these distributed focal changes disrupt the system-level architecture (topology) of brain morphology in MDD. If present, such a topological disruption might explain the mechanisms that underlie altered cortical morphology in MDD. METHODS: Seventy-six patients with first-episode MDD (33 male, 43 female) and 66 healthy controls (32 male, 34 female) underwent structural MRI scans. We calculated cortical indices, including cortical thickness, surface area and local gyrification index, using FreeSurfer. We constructed morphological covariance networks using the 3 cortical indices separately, and we analyzed the topological properties of these group-level morphological covariance networks using graph theoretical approaches. RESULTS: Topological differences between patients with first-episode MDD and healthy controls were restricted to the thickness-based network. We found a significant decrease in global efficiency but an increase in local efficiency of the left superior frontal gyrus and the right paracentral lobule in patients with first-episode MDD. When we simulated targeted lesions affecting the most highly connected nodes, the thickness-based networks in patients with first-episode MDD disintegrated more rapidly than those in healthy controls. LIMITATIONS: Our sample of patients with first-episode MDD has limited generalizability to patients with chronic and recurrent MDD. CONCLUSION: A systems-level disruption in cortical thickness (but not surface area or gyrification) occurs in patients with first-episode MDD.

The anatomical networks based on probabilistic structurally connectivity in bipolar disorder across mania, depression, and euthymic states.

BACKGROUNDS: There have pieces of evidence of the distinct aberrant functional network topology profile in bipolar disorder (BD) across mania, depression, and euthymic episodes. However, the underlying anatomical network topology pattern in BD across different episodes is unclear. METHODS: We calculated the whole-brain probabilistic structurally connectivity across 143 subjects (72 with BD [34 depression; 13 mania; 25 euthymic] and 53 healthy controls), and used graph theory to examine the trait- and state-related topology alterations of the structural connectome in BD. The correlation analysis was further conducted to explore the relationship between detected network measures and clinical symptoms. RESULTS: There no omnibus alteration of any global network metrics were observed across all diagnostic groups. In the regional network metrics level, bipolar depression showed increased clustering coefficient in the right lingual gyrus compared with all other groups, and the increased clustering coefficient in the right lingual gyrus positively correlated with depression, anxiety, and illness burden symptoms but negatively correlated with mania symptoms; manic and euthymic patients showed decreased clustering coefficient in the left inferior occipital gyrus compared with HCs. LIMITATIONS: The moderate sample size of all patient groups (especially for subjects with mania) might have contributed to the negative findings of the trait feature in this study. CONCLUSIONS: We demonstrated the altered regional connectivity pattern in the occipital lobe of the bipolar depression and mania episode, especially the lingual gyrus. The association of the clustering coefficient in the lingual gyrus with clinical symptoms helps monitor the state of BD.

Fabrication of Flexible and Transparent Metal Mesh Electrodes Using Surface Energy-Directed Assembly Process for Touch Screen Panels and Heaters.

Transparent conductive electrodes (TCEs) are indispensable components of various optoelectronic devices such as displays, touch screen panels, solar cells, and smart windows. To date, the fabrication processes for metal mesh-based TCEs are either costly or having limited resolution and throughput. Here, a two-step surface energy-directed assembly (SEDA) process to efficiently fabricate high resolution silver meshes is introduced. The two-step SEDA process turns from assembly on a functionalized substrate with hydrophilic mesh patterns into assembly on a functionalized substrate with stripe patterns. During the SEDA process, a three-phase contact line pins on the hydrophilic pattern regions while recedes on the hydrophobic non-pattern regions, ensuring that the assembly process can be achieved with excellent selectivity. The necessity of using the two-step SEDA process rather than a one-step SEDA process is demonstrated by both experimental results and theoretical analysis. Utilizing the two-step SEDA process, silver meshes with a line width down to 2 µm are assembled on both rigid and flexible substrates. The thickness of the silver meshes can be tuned by varying the withdraw speed and the assembly times. The assembled silver meshes exhibit excellent optoelectronic properties (sheet resistance of 1.79 Ω/□, optical transmittance of ≈92%, and a FoM value of 2465) as well as excellent mechanical stability. The applications of the assembled silver meshes in touch screen panels and thermal heaters are demonstrated, implying the potential of using the two-step SEDA process for the fabrication of TCEs for optoelectronic applications.

Hypoactive Visual Cortex, Prefrontal Cortex and Insula during Self-Face Recognition in Adults with First-Episode Major Depressive Disorder.

Self-face recognition is a vital aspect of self-referential processing, which is closely related to affective states. However, neuroimaging research on self-face recognition in adults with major depressive disorder is lacking. This study aims to investigate the alteration of brain activation during self-face recognition in adults with first-episode major depressive disorder (FEMDD) via functional magnetic resonance imaging (fMRI); FEMDD (n = 59) and healthy controls (HC, n = 36) who performed a self-face-recognition task during the fMRI scan. The differences in brain activation signal values between the two groups were analyzed, and Pearson correlation analysis was used to evaluate the relationship between the brain activation of significant group differences and the severity of depressive symptoms and negative self-evaluation; FEMDD showed significantly decreased brain activation in the bilateral occipital cortex, bilateral fusiform gyrus, right inferior frontal gyrus, and right insula during the task compared with HC. No significant correlation was detected between brain activation with significant group differences and the severity of depression and negative self-evaluation in FEMDD or HC. The results suggest the involvement of the malfunctioning visual cortex, prefrontal cortex, and insula in the pathophysiology of self-face recognition in FEMDD, which may provide a novel therapeutic target for adults with FEMDD.

Shared and distinct patterns of dynamical degree centrality in bipolar disorder across different mood states.

Background: Previous studies have probed the brain static activity pattern in bipolar disorder across different states. However, human intrinsic brain activity is time-varying and dynamic. There is a lack of knowledge about the brain dynamical pattern in bipolar disorder across different mood states. Methods: This study used the dynamical degree centrality (dDC) to investigate the resting-state whole-brain dynamical pattern voxel-wise in a total of 62 bipolar disorder [28 bipolar depression (BD), 13 bipolar mania (BM), 21 bipolar euthymia (BE)], and 30 healthy controls (HCs). One-way analysis of variance (ANOVA) was applied to explore the omnibus differences of the dDC pattern across all groups, and Pearson's correlation analysis was used to evaluate the relationship between the dDC variability in detected regions with clinical symptom severity. Results: One-way ANOVA analysis showed the omnibus differences in the left inferior parietal lobule/middle occipital gyrus (IPL/MOG) and right precuneus/posterior cingulate cortex (PCUN/PCC) across all groups. The post hoc analysis revealed that BD showed decreased dDC in the IPL/MOG compared with all other groups, and both BD and BM exhibited decreased dDC in the PCUN/PCC compared with BE and HCs. Furthermore, correlation analysis showed that the dDC variability of the IPL/MOG and PCUN/PCC negatively correlated with the depression symptom levels in all patients with bipolar disorder. Conclusion: This study demonstrated the distinct and shared brain dynamical pattern of the depressive, manic, and euthymia states. Our findings provide new insights into the pathophysiology of bipolar disorder across different mood states from the dynamical brain network pattern perspective.

Aberrant brain dynamics in major depressive disorder with suicidal ideation.

BACKGROUND: Suicidal ideation (SI) is a common symptom of major depressive disorder (MDD). Accumulating studies demonstrated that MDD with SI was associated with static alterations in brain activity and functional connectivity. However, given that brain is a highly dynamic system, the changes of brain dynamic patterns in MDD with SI remain unknown. METHODS: We included 60 MDD patients with SI (MDD-SI), 58 MDD patients without SI (MDD-NSI), and 58 healthy controls (HCs) who underwent resting-state functional magnetic resonance imaging. The sliding-window approach was used to calculate the dynamic fractional amplitude of low-frequency fluctuation (dfALFF) and dynamic degree centrality (dDC) to characterize the temporal dynamic regional activity and distant functional connectivity. We compared dfALFF and dDC across groups and further conducted correlations between abnormal dynamic metrics and the severity of suicidality. RESULTS: In terms of the dynamic regional activity, MDD-SI showed decreased dfALFF in the left lingual gyrus and right middle occipital gyrus compared with MDD-NSI; in terms of the dynamic distant connectivity, MDD-SI showed decreased dDC in the right middle frontal gyrus compared with MDD-NSI. The decreased dDC in the right middle frontal gyrus was correlated with increased severity of suicidality. LIMITATIONS: The relatively small sample size. CONCLUSIONS: We demonstrate the specific brain dynamic patterns of MDD-SI in regional activity and distant functional connectivity compared to MDD-NSI. Especially the decreased temporal variability of the distant connectivity in the middle frontal gyrus was associated with SI. These altered dynamic patterns may represent a potential neurobiological diathesis of SI in MDD.

Decreased integration of default-mode network during a working memory task in schizophrenia with severe attention deficits.

Background: Working memory (WM) and attention deficits are both important features of schizophrenia. WM is closely related to attention, for it acted as an important characteristic in activating and manipulating WM. However, the knowledge of neural mechanisms underlying the relationship between WM and attention deficits in schizophrenia is poorly investigated. Methods: Graph theory was used to examine the network topology at the whole-brain and large-scale network levels among 125 schizophrenia patients with different severity of attention deficits (65 mild attention deficits; 46 moderate attention deficits; and 14 severe attention deficits) and 53 healthy controls (HCs) during an N-back WM task. These analyses were repeated in the same participants during the resting state. Results: In the WM task, there were omnibus differences in small-worldness and normalized clustering coefficient at a whole-brain level and normalized characterized path length of the default-mode network (DMN) among all groups. Post hoc analysis further indicated that all patient groups showed increased small-worldness and normalized clustering coefficient of the whole brain compared with HCs, and schizophrenia with severe attention deficits showed increased normalized characterized path length of the DMN compared with schizophrenia with mild attention deficits and HCs. However, these observations were not persisted under the resting state. Further correlation analyses indicated that the increased normalized characterized path length of the DMN was correlated with more severe attentional deficits and poorer accuracy of the WM task. Conclusion: Our research demonstrated that, compared with the schizophrenia patients with less attention deficits, disrupted integration of the DMN may more particularly underlie the WM deficits in schizophrenia patients with severe attention deficits.

Dynamical regional activity in putamen distinguishes bipolar type I depression and unipolar depression.

OBJECTIVES: Intrinsic human brain activity is time-varying and dynamic. However, there is still a lack of knowledge about the dynamic regional activity differences between unipolar depression (UD) and bipolar type I depression (BD-I), and whether their differential pattern can help to distinguish these two patient groups who are prone to misdiagnosis in clinical practice. METHOD: In this study, we used the dynamical fractional amplitude of low-frequency fluctuations (dfALFF) to examine the resting-state dynamical regional activity in 40 BD-I, 42 UD, and 44 healthy controls (HCs). Analysis of covariance was applied to explore the shared and distinct dfALFF pattern among three groups, and machine-learning methods were conducted to classify BD-I from UD by using the detected distinct dfALFF pattern. RESULTS: Compared with HCs, both BD-I and UD exhibited decreased dfALFF temporal variability in the left inferior temporal gyrus. The BD-I showed significantly decreased dfALFF temporal variability in the left putamen compared to UD. By using the dfALFF variability pattern of the left putamen as features, we achieved the 75.61% accuracy and 0.756 area under curve in classifying BD-I from UD. LIMITATIONS: The small sample size of the current study may limit the generalizability of the findings. CONCLUSIONS: The current study demonstrated that the dfALFF temporal variability pattern in the putamen may show a promise as future diagnostic aids for BD-I and UD.

Aberrant integrity of the cortico-limbic-striatal circuit in major depressive disorder with suicidal ideation.

BACKGROUND: Suicidal ideation is a common symptom of major depressive disorder (MDD) that reflects a cognitive alteration in the background of intense emotional dysregulation. Amygdala is a critical emotion processing center that facilitates moving from emotional appraisal to action. However, whether MDD patients with suicidal ideation show dysconnectivity of the amygdala within a large-scale neurocognitive circuitry remains unknown. METHODS: Participants were 22 MDD patients without suicidal ideation (MDD-NSI), 59 MDD patients with suicidal ideation (MDD-SI), and 60 healthy controls (HCs). We compared the amygdala-based resting-state functional connectivity of four amygdala subregions across the three groups. We selected brain regions with significant between-group differences in amygdalar conectivity as the regions of interest (ROI) and performed ROI-to-ROI and graph-theoretical analyses to explore dysconnectivity patterns at various granularity levels. RESULTS: Brain regions showing omnibus differences across the three groups were distributed across a cortico-limbic-striatal circuitry. MDD-SI had unique dysconnectivity of the lateral amygdala with caudate, middle temporal gyrus, and postcentral gyrus compared with the other two groups. MDD-SI and MDD-NSI had shared dysconnectivity of the medial amygdala with medial superior frontal gyrus and middle temporal gyrus. Within the derived cortico-limbic-striatal circuitry, MDD-SI exhibited lower global connectivity, reduced sigma (small-worldness), but increased lambda (path-length) than HCs. Reduced sigma correlated with increased severity of suicidal ideation. We achieved high classification accuracy (84.09%, with AUC 0.82) in distinguishing MDD-SI from MDD-NSI. CONCLUSIONS: Aberrant integrity of the cortico-limbic-striatal circuit centered on the amygdala provides a promising neural substrate for suicidal ideation that requires further investigation in MDD.

Differential Dynamical Pattern of Regional Homogeneity in Bipolar and Unipolar Depression: A Preliminary Resting-State fMRI Study.

Background: Bipolar depression (BD) and unipolar depression (UD) are both characterized by depressive moods, which are difficult to distinguish in clinical practice. Human brain activity is time-varying and dynamic. Investigating dynamical pattern alterations of depressed brains can provide deep insights into the pathophysiological features of depression. This study aimed to explore similar and different abnormal dynamic patterns between BD and UD. Methods: Brain resting-state functional magnetic resonance imaging data were acquired from 36 patients with BD type I (BD-I), 38 patients with UD, and 42 healthy controls (HCs). Analysis of covariance was adopted to examine the differential pattern of the dynamical regional homogeneity (dReHo) temporal variability across 3 groups, with gender, age, and education level as covariates. Post-hoc analyses were employed to obtain the different dynamic characteristics between any 2 groups. We further applied the machine-learning methods to classify BD-I from UD by using the detected distinct dReHo pattern. Results: Compared with patients with UD, patients with BD-I demonstrated decreased dReHo variability in the right postcentral gyrus and right parahippocampal gyrus. By using the dReHo variability pattern of these two regions as features, we achieved the 91.89% accuracy and 0.92 area under curve in classifying BD-I from UD. Relative to HCs, patients with UD showed increased dReHo variability in the right postcentral gyrus, while there were no dReHo variability differences in patients with BD-I. Conclusions: The results of this study mainly report the differential dynamic pattern of the regional activity between BD-I and UD, particular in the mesolimbic system, and show its promising potential in assisting the diagnosis of these two depression groups.

The Role of Military Training in Improving Psychological Resilience and Reducing Depression Among College Freshmen.

Background: Military training plays an important protective role in enhancing mental health. However, the effects of military training on psychological resilience and depression among college freshmen in China remain unclear. The present study aimed to evaluate changes in psychological resilience and depression through military training among college freshmen, and to investigate associated psychosocial factors including childhood trauma that may influence its effects on psychological resilience. Methods: A prospective and self-comparison study design was employed. College freshmen who received 3 weeks of military training were recruited. Socio-demographic variables were collected and childhood trauma exposure was estimated by the Childhood Trauma Questionnaire (CTQ). The Connor-Davidson Resilience Scale (CD-RISC) and Patient Health Questionnaire (PHQ-9) were used to assess psychological resilience and depression before and after the military-style training. Results: The military training significantly increased the total and subscale scores of CD-RISC (p < 0.001), and decreased the PHQ-9 score (p < 0.001). The proportion of students with clinical depression reduced from 10.5% at baseline to 7.2% after the training (p < 0.001). Improvement of CD-RISC scores was positively affected by male gender and urban area, while negatively affected by older age, and higher baseline scores of PHQ-9 and CTQ. A significant correlation was found between changes in scores of CD-RISC and PHQ-9 through the training (r = -0.238, p < 0.001). Conclusions: Military training may have a positive effect on increasing psychological resilience and reducing depressive symptoms among college freshmen, especially in male students and those from an urban area, while older age, childhood trauma, higher depression levels, and resilience at baseline may weaken, or even mask its positive effect. Follow-up research should be considered for the long-term effects of military-style training.

Abnormal Thalamocortical Circuit in Adolescents With Early-Onset Schizophrenia.

OBJECTIVE: Thalamic circuit imbalance characterized by increased sensorimotor-thalamic connectivity and decreased prefrontal-thalamic connectivity has been consistently observed in adult-onset schizophrenia (AOS), although it is unclear whether this pattern is also a feature of early-onset schizophrenia (EOS). If this is the case, thalamic circuit imbalance can be considered as a core mechanistic defect in schizophrenia, unconfounded by the age of onset. METHOD: A total of 116 adolescents with EOS (63 drug-naive EOS) and 55 matched healthy controls (HC) were recruited and underwent resting-state functional magnetic resonance imaging scans. To define the specific location of the thalamic subregions in thalamocortical circuit, 16 atlas-based thalamic subdivisions were used in functional connectivity analysis. RESULTS: The EOS group showed increased sensorimotor-thalamic connectivity and decreased prefrontal-cerebello-thalamic connectivity, consistent with AOS. Sensorimotor-thalamic hyperconnectivity was more prominent than prefrontal-thalamic hypoconnectivity, which was circumscribed to the medial prefrontal cortex (mPFC), in EOS. Of note, the EOS group specifically exhibited strengthened thalamic connectivity with the salience network (SN). In addition, the EOS showed a more prominent disruption of the lateral thalamic nuclear connectivity. CONCLUSION: Thalamic dysconnectivity observed in the EOS extends the observations from adult patients. Sensorimotor-thalamic hyperconnectivity is critical for the expression of schizophrenia phenotype irrespective of the age of onset, raising the possibility of aberrant but accelerated functional network maturation in EOS. The specific thalamocortical dysconnectivity involving the SN and mPFC may underlie the distinctive features of multi-modal hallucinations and heightened emotional valence of psychosis seen in EOS.

Bipolar Mood State Reflected in Functional Connectivity of the Hate Circuit: A Resting-State Functional Magnetic Resonance Imaging Study.

BACKGROUND: Previous studies suggested bipolar disorder caused an aberrant alteration in the insular, putamen, and left superior frontal gyrus, which are the main components of the hate circuit. However, the relationship between the hate circuit and the pathophysiologic substrate underlying different phases of bipolar disorder remain unclear. In this study, we aimed to identify group differences of resting-state functional connectivity within the hate circuit in healthy controls (HCs) and bipolar patients in different mood states. METHODS: Resting-state functional magnetic resonance imaging of the brain were acquired from 54 HCs and 81 patients with bipolar disorder including 20 with bipolar mania (BM), 35 with bipolar depression (BD), and 26 with bipolar euthymia (BE). We selected bilateral insula (L.INS and R.INS), bilateral putamen (L.PUT and R.PUT), and left superior frontal gyrus (L.SFGd) as seed regions, and conducted the seed-based functional connectivity analysis to identify group differences of connectivity strength within the hate circuit. Spearman correlations were performed to evaluate the relationship between the hate circuit and manic/depressive symptoms. RESULTS: Significant group differences of connectivity strength within the hate circuit were found in links of the R.INS-L.SFGd, R.PUT-L.SFGd, and L.INS- R.PUT after false discovery rate was corrected. The BM group showed an opposite hate circuit pattern to BD, BE, and HCs. The BD group showed decreased hate circuit connectivity in the L.INS-R.PUT compared with the BE group. No significant difference was detected among BD, BE, and HCs. Furthermore, functional connectivity of the R.INS-L.SFGd and R.PUT-L.SFGd were positively correlated with manic symptoms, while the L.INS- R.PUT was negatively correlated with depressive symptoms. CONCLUSIONS: Our preliminary findings suggest that altered functional connectivity of the hate circuit in different mood phases may be related to state markers and underpin the neuropathological basis of bipolar disorder.

Connectomic signatures of working memory deficits in depression, mania, and euthymic states of bipolar disorder.

BACKGROUND: Working memory (WM) deficit is a feature persistently reported across mania, depression, and euthymic periods of bipolar disorder (BD). WM capacity relates to distributed brain regions that are systemically organized at the connectome level. It is not clear whether the same disruption of this network-level organization underlies the WM impairment seen in different phases of BD. METHODS: We used graph theory to examine the topology of the functional connectome in different granularity in 143 subjects (72 with BD [32 depression; 15 mania; 25 euthymic] and 71 healthy controls) during a n-back task. Linear regression analysis was used to test associations of altered graph properties, clinical symptoms, and WM accuracy in patients. RESULTS: Altered topological properties characterised by an increase in small-worldness of the whole-brain connectome, were specific for bipolar depressed, but not in manic and euthymic states. Depressed subjects showed a shift in the distribution of the number of connections per brain region (degree) within the connectome during WM task. Increased small-worldness related to worse WM accuracy in patients with more severe depression, anxiety and illness burden. LIMITATIONS: We used only 2-back load, limiting our ability to study the parametric effects of task demand. CONCLUSIONS: We demonstrate a putative state-dependent mechanistic link between connectome topology, hub re-distribution and impaired n-back performance in bipolar disorder. The aberrant task-dependent modulation of the connectome relates to worse WM performance especially when anxiety and depression are prominent in BD.

Psychological resilience negatively correlates with resting-state brain network flexibility in young healthy adults: a dynamic functional magnetic resonance imaging study.

BACKGROUND: Psychological resilience is an important personality trait whose decrease is associated with many common psychiatric disorders, but the neural mechanisms underlying it remain largely unclear. In this study, we aimed to explore the neural correlates of psychological resilience in healthy adults by investigating its relationship with functional brain network flexibility, a fundamental dynamic feature of brain network defined by switching frequency of its modular community structures. METHODS: Resting-state functional magnetic resonance imaging (fMRI) scans were acquired from 41 healthy adults, whose psychological resilience was quantified by the Connor-Davidson Resilience Scale (CD-RISC). Dynamic functional brain network was constructed for each subject, whose flexibility was calculated at all the global, subnetwork and region-of-interest (ROI) levels. After that, the associations between CD-RISC score and brain network flexibility were assessed at all levels by partial correlations controlling for age, sex, education and head motion. Correlation was also tested between the CD-RISC score and modularity of conventional static brain network for comparative purposes. RESULTS: The CD-RISC score was significant negatively correlated with the brain network flexibility at global level (r=-0.533, P=0.001), and with flexibility of the visual subnetwork at subnetwork level (r=-0.576, corrected P=0.002). Moreover, significant (corrected P<0.05) or trends for (corrected P<0.10) negative correlations were found between the CD-RISC score and flexibilities of a number of visual and default-mode areas at ROI level. Meanwhile, the modularity of static brain network did not reveal significant correlation with CD-RISC score (P>0.05). CONCLUSIONS: Our results suggest that excessive fluctuations of the functional brain community structures during rest may be indicative of a lower psychological resilience, and the visual and default-mode systems may play crucial roles in such relationship. These findings may provide important implications for improving our understanding of the psychological resilience.