Investigating executive control network and default mode network dysfunction in major depressive disorder

Resting-state functional connectivity abnormalities in subjective cognitive decline: A 7T MRI study

Resting-state functional connectivity (FC) MRI is sensitive to brain changes in Alzheimer's disease in preclinical stages, however studies in persons with subjective cognitive decline (SCD) have reported conflicting findings, and no study is available at 7T MRI. In this study, we investigated FC alterations in sixty-six participants recruited at the Geneva Memory Center (24 controls, 14 SCD, 28 cognitively impaired [CI]). Participants were classified as SCD if they reported cognitive complaints without objective cognitive deficits, and underwent 7T fMRI to assess FC in canonical brain networks and their association with cognitive/clinical features. SCD showed normal cognition, a trend for higher depressive symptoms, and normal AD biomarkers. Compared to the other two groups, SCD showed higher FC in frontal default mode network (DMN) and insular and superior temporal nodes of ventral attention network (VAN). Higher FC in the DMN and VAN was associated with worse cognition but not depression, suggesting that hyper-connectivity in these networks may be a signature of age-related cognitive decline in SCD at low risk of developing AD.

EEG coherences of the default mode network among patients comorbid with major depressive disorder and anxiety symptoms

BACKGROUND

Higher functional connectivity within the default mode network (DMN) has been found in functional magnetic resonance imaging (fMRI) studies of major depressive disorder (MDD). We used electroencephalogram (EEG) coherence as an index of functional connectivity to examine group differences in DMN between the MDD and healthy control (HC) groups during the resting state.

METHODS

MDD patients with comorbid anxiety symptoms (n = 154) and healthy controls (n = 165) completed the questionnaires of depression, anxiety, and rumination. A 19-channel EEG recording was measured under resting state for all participants. EEG coherences of the delta, theta, alpha, beta, and high beta in the anterior DMN (aDMN), posterior DMN (pDMN), aDMN-pDMN, DMN-parahippocampal gyrus (PHG), and DMN-temporal gyrus were compared between the two groups. The correlations between rumination, anxiety, and DMN coherence were examined in the MDD group.

RESULTS

(1) No difference was found in the delta, theta, alpha, and beta within the DMN brain regions between the two groups; the MDD group showed higher high beta coherence within DMN brain regions than the HC group. (2) Rumination was negatively correlated with theta coherence of aDMN, and positively correlated with beta coherence of aDMN and with alpha coherence of pDMN and DMN-PHG. (3) Anxiety was positively correlated with high beta coherence of aDMN, pDMN, and DMN-PHG.

CONCLUSIONS

MDD patients with comorbid anxiety symptoms exhibited hypercoherence within the DMN brain regions. Hypercoherences were related to symptoms of rumination, and anxiety may be a biomarker for MDD patients with comorbid anxiety symptoms.

Features of attention network impairment in patients with temporal lobe epilepsy: Evidence from eye-tracking and electroencephalogram

AIM

To explore multiple features of attention impairments in patients with temporal lobe epilepsy (TLE).

METHODS

A total of 93 patients diagnosed with TLE at Xiangya Hospital during May 2022 and December 2022 and 85 healthy controls were included in this study. Participants were asked to complete neuropsychological scales and attention network test (ANT) with recording of eye-tracking and electroencephalogram.

RESULTS

All means of evaluation showed impaired attention functions in TLE patients. ANT results showed impaired orienting (p < 0.001) and executive control (p = 0.041) networks. Longer mean first saccade time (p = 0.046) and more total saccadic counts (p = 0.035) were found in eye-tracking results, indicating abnormal alerting and orienting networks. Both alerting, orienting and executive control networks were abnormal, manifesting as decreased amplitudes (N1 & P3, p < 0.001) and extended latency (P3, p = 0.002). The energy of theta, alpha and beta were all sensitive to the changes of alerting and executive control network with time, but only beta power was sensitive to the changes of orienting network.

CONCLUSION

Our findings are helpful for early identification of patients with TLE combined with attention impairments, which have strong clinical guiding significance for long-term monitoring and intervention.

Exploring the correlation between childhood trauma experiences, inflammation, and brain activity in first-episode, drug-naive major depressive disorder

BACKGROUND

Childhood trauma experiences and inflammation are pivotal factors in the onset and perpetuation of major depressive disorder (MDD). However, research on brain mechanisms linking childhood trauma experiences and inflammation to depression remains insufficient and inconclusive.

METHODS

Resting-state fMRI scans were performed on fifty-six first-episode, drug-naive MDD patients and sixty healthy controls (HCs). A whole-brain functional network was constructed by thresholding 246 brain regions, and connectivity and network properties were calculated. Plasma interleukin-6 (IL-6) levels were assessed using enzyme-linked immunosorbent assays in MDD patients, and childhood trauma experiences were evaluated through the Childhood Trauma Questionnaire (CTQ).

RESULTS

Negative correlations were observed between CTQ total (r = -0.28, p = 0.047), emotional neglect (r = -0.286, p = 0.042) scores, as well as plasma IL-6 levels (r = -0.294, p = 0.036), with mean decreased functional connectivity (FC) in MDD patients. Additionally, physical abuse exhibited a positive correlation with the nodal clustering coefficient of the left thalamus in patients (r = 0.306, p = 0.029). Exploratory analysis indicated negative correlations between CTQ total and emotional neglect scores and mean decreased FC in MDD patients with lower plasma IL-6 levels (n = 28), while these correlations were nonsignificant in MDD patients with higher plasma IL-6 levels (n = 28).

CONCLUSIONS

This finding enhances our understanding of the correlation between childhood trauma experiences, inflammation, and brain activity in MDD, suggesting potential variations in their underlying pathophysiological mechanisms.

A novel biomarker selection method using multimodal neuroimaging data

Identifying biomarkers is essential to obtain the optimal therapeutic benefit while treating patients with late-life depression (LLD). We compare LLD patients with healthy controls (HC) using resting-state functional magnetic resonance and diffusion tensor imaging data to identify neuroimaging biomarkers that may be potentially associated with the underlying pathophysiology of LLD. We implement a Bayesian multimodal local false discovery rate approach for functional connectivity, borrowing strength from structural connectivity to identify disrupted functional connectivity of LLD compared to HC. In the Bayesian framework, we develop an algorithm to control the overall false discovery rate of our findings. We compare our findings with the literature and show that our approach can better detect some regions never discovered before for LLD patients. The Hub of our discovery related to various neurobehavioral disorders can be used to develop behavioral interventions to treat LLD patients who do not respond to antidepressants.

The Role of the Insula in Chronic Pain and Associated Structural Changes: An Integrative Review

Chronic pain affects a substantial portion of the global population, significantly impacting quality of life and well-being. This condition involves complex mechanisms, including dysfunction of the autonomic nervous system, which plays a crucial role in pain perception. The insula, a key brain region involved in pain processing, plays a critical role in pain perception and modulation. Lesions in the insula can result in pain asymbolia, where pain perception remains intact but emotional responses are inappropriate. The insula is anatomically and functionally divided into anterior and posterior regions, with the posterior insula processing nociceptive input based on intensity and location before relaying it to the anterior insula for emotional mediation. Understanding the insula's intricate role in pain processing is crucial, as it is involved in encoding prediction errors and mediating emotional dimensions of pain perception. The focus of this review was on synthesizing existing literature on the role of the insula in chronic pain and associated structural changes. The goal was to integrate findings from various sources to provide a comprehensive overview of the topic. The search strategy included a combination of Medical Subject Headings (MeSH) and relevant keywords related to insula and chronic pain. The following databases were surveyed: PubMed, Embase, Scopus, and Web of Science. We identified a total of 2515 articles, and after following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline based on eligibility criteria, 46 articles were used to synthesize this review. Our study highlights the pivotal role of the insula in chronic pain processing and associated structural changes, integrating findings from diverse studies and neuroimaging investigations. Beyond mere pain sensation, the insula contributes to emotional awareness, attention, and salience detection within the pain network. Various chronic pain conditions reveal alterations in insular activity and connectivity, accompanied by changes in gray matter volume and neurochemical profiles. Interventions targeting the insula show promise in alleviating chronic pain symptoms. However, further research is needed to understand underlying mechanisms, which can aid in developing more effective therapeutic interventions for pain.

Increased functional connectivity coupling with supplementary motor area in blepharospasm at rest

OBJECTIVE

To explore the abnormalities of brain function in blepharospasm (BSP) and to illustrate its neural mechanisms by assuming supplementary motor area (SMA) as the entry point.

METHODS

Twenty-five patients with BSP and 23 controls underwent resting-state functional MRI, seed-based functional connectivity (FC), correlation analysis, receiver operating characteristic curve (ROC) analysis, and support vector machine (SVM) were applied to process the data.

RESULTS

Patients showed that the left medial prefrontal cortex (MPFC), left lingual gyrus, right cerebellar crus I, and right lingual gyrus/cerebellar crus I had enhanced FC with the left SMA, whereas the right inferior temporal gyrus (ITG) had enhanced FC with the right SMA relative to controls. The FC between the left MPFC and left SMA was positively correlated with symptomatic severity. The ROC analysis verified that the abnormal FCs demonstrated in this study can separate patients and controls at high sensitivity and specificity. SVM analysis exhibited that combined FCs of the left SMA were optimal for distinguishing patients and control group at the accuracy of 89.58%, with sensitivity of 92.00% and specificity of 86.96%.

CONCLUSIONS

Several brain networks partake in the neurobiology of BSP. SMA plays a vital role in several brain networks and might be the key pathogenic factor in BSP.

SIGNIFICANCE

Providing novel evidence for the engagement of the MPFC in the motor symptoms of BSP, enhancing credibility of the thesis that SMA regulates the neurobiology of BSP, and providing ideas of screening susceptible population of BSP using neuroimaging.

The conscious processing of emotion in depression disorder: a meta-analysis of neuroimaging studies

Background

Depression is generally accompanied by a disturbed conscious processing of emotion, which manifests as a negative bias to facial/voice emotion information and a decreased accuracy in emotion recognition tasks. Several studies have proved that abnormal brain activation was responsible for the deficit function of conscious emotion recognition in depression. However, the altered brain activation related to the conscious processing of emotion in depression was incongruent among studies. Therefore, we conducted an activation likelihood estimation (ALE) analysis to better understand the underlying neurophysiological mechanism of conscious processing of emotion in depression.

Method

Electronic databases were searched using the search terms "depression," "emotion recognition," and "neuroimaging" from inceptions to April 10th, 2023. We retrieved trials which explored the neuro-responses of depressive patients to explicit emotion recognition tasks. Two investigators independently performed literature selection, data extraction, and risk of bias assessment. The spatial consistency of brain activation in conscious facial expressions recognition was calculated using ALE. The robustness of the results was examined by Jackknife sensitivity analysis.

Results

We retrieved 11,365 articles in total, 28 of which were included. In the overall analysis, we found increased activity in the middle temporal gyrus, superior temporal gyrus, parahippocampal gyrus, and cuneus, and decreased activity in the superior temporal gyrus, inferior parietal lobule, insula, and superior frontal gyrus. In response to positive stimuli, depressive patients showed hyperactivity in the medial frontal gyrus, middle temporal gyrus, and insula (uncorrected p < 0.001). When receiving negative stimuli, a higher activation was found in the precentral gyrus, middle frontal gyrus, precuneus, and superior temporal gyrus (uncorrected p < 0.001).

Conclusion

Among depressive patients, a broad spectrum of brain areas was involved in a deficit of conscious emotion processing. The activation of brain regions was different in response to positive or negative stimuli. Due to potential clinical heterogeneity, the findings should be treated with caution.

Systematic review registration

https://inplasy.com/inplasy-2022-11-0057/, identifier: 2022110057.

Development of a Bayesian multimodal model to detect biomarkers in neuroimaging studies

In this article, we developed a Bayesian multimodal model to detect biomarkers (or neuromarkers) using resting-state functional and structural data while comparing a late-life depression group with a healthy control group. Biomarker detection helps determine a target for treatment intervention to get the optimal therapeutic benefit for treatment-resistant patients. The borrowing strength of the structural connectivity has been quantified for functional activity while detecting the biomarker. In the biomarker searching process, thousands of hypotheses are generated and tested simultaneously using our novel method to control the false discovery rate for small samples. Several existing statistical approaches, frequently used in analyzing neuroimaging data have been investigated and compared via simulation with the proposed approach to show its excellent performance. Results are illustrated with a live data set generated in a late-life depression study. The role of detected biomarkers in terms of cognitive function has been explored.

Resting state connectivity predictors of symptom change during gaze-contingent music reward therapy of social anxiety disorder

BACKGROUND

Social anxiety disorder (SAD) is common, first-line treatments are often only partially effective, and reliable predictors of treatment response are lacking. Here, we assessed resting state functional connectivity (rsFC) at pre-treatment and during early treatment as a potential predictor of response to a novel attention bias modification procedure, gaze-contingent music reward therapy (GC-MRT).

METHODS

Thirty-two adults with SAD were treated with GC-MRT. rsFC was assessed with multi-voxel pattern analysis of fMRI at pre-treatment and after 2-3 weeks. For comparison, 20 healthy control (HC) participants without treatment were assessed twice for rsFC over the same time period. All SAD participants underwent clinical evaluation at pre-treatment, early-treatment (week 2-3), and post-treatment.

RESULTS

SAD and depressive symptoms improved significantly from pre-treatment to post-treatment. After 2-3 weeks of treatment, decreased connectivity between the executive control network (ECN) and salience network (SN), and increased connectivity within the ECN predicted improvement in SAD and depressive symptoms at week 8. Increased connectivity between the ECN and default mode network (DMN) predicted greater improvement in SAD but not depressive symptoms at week 8. Connectivity within the DMN decreased significantly after 2-3 weeks of treatment in the SAD group, while no changes were found in HC over the same time interval.

CONCLUSION

We identified early changes in rsFC during a course of GC-MRT for SAD that predicted symptom change. Connectivity changes within the ECN, ECN-DMN, and ECN-SN may be related to mechanisms underlying the clinical effects of GC-MRT and warrant further study in controlled trials.

Understanding the heterogeneity of dynamic functional connectivity patterns in first-episode drug naïve depression using normative models

BACKGROUND

The heterogeneity of the clinical symptoms and presumptive neural pathologies has stunted progress toward identifying reproducible biomarkers and limited therapeutic interventions' effectiveness for the first episode drug-naïve major depressive disorders (FEDN-MDD). This study combined the dynamic features of fMRI data and normative modeling to quantitative and individualized metrics for delineating the biological heterogeneity of FEDN-MDD.

METHOD

Two hundred seventy-four adults with FEDN-MDD and 832 healthy controls from International Big-Data Center for Depression Research were included. Subject-specific dynamic brain networks and network fluctuation characteristics were computed for each subject using the group information-guided independent component analysis. Then, we mapped the heterogeneity of the dynamic features (network fluctuation characteristics and dynamic functional connectivity within brain networks) in the patients group via normative modeling.

RESULTS

The FEDN-MDD whose network fluctuation characteristics deviate from the normative model also showed significant differences within the default mode network, executive control network, and limbic network compared with healthy controls. Furthermore, the network fluctuation characteristics are significantly increased in patients with FEDN-MDD. About 4.74 % of the patients showed a deviation of dynamic functional connectivity, and only 3.35 % of the controls deviated from the normative model in above 100 connectivities. More patients than healthy controls showed extreme dynamic variabilities in above 100 connectivities.

CONCLUSIONS

This work evaluates the efficacy of an individualized approach based on normative modeling for understanding the heterogeneity of abnormal dynamic functional connectivity patterns in FEDN-MDD, and could be used as complementary to classical case-control comparisons.

Functional brain alterations in migraine patients: an activation likelihood estimation study

BACKGROUND

Previous functional magnetic resonance imaging (fMRI) studies reported inconsistent results for comparison in brain activation between migraine patients and healthy controls (HC). Thus, activation likelihood estimation (ALE) method, a powerful voxel-based technique, was used to explore the concordant functional brain changes in migraine patients.

METHODS

Studies published before October 2022 were searched in the following databases (PubMed, Web of Science and Google Scholar).

RESULTS

Migraine without aura (MWoA) patients showed reduced amplitude of low-frequency fluctuations (ALFF) in right lingual gyrus, the left posterior cingulate and the right precuneus (PCUN), compared to HC. Migraine patients showed increased ALFF in the right claustrum, the left caudate, the left insula and the right parahippocampal gyrus, compared to HC. MWoA patients showed reduced regional homogeneity (ReHo) in the right culmen, compared to HC. In addition, migraine patients showed increased ReHo in the bilateral thalamus, compared to HC. MWoA patients showed reduced whole-brain functional connectivity (FC) in the left middle occipital gyrus and the right superior parietal lobule, compared to HC. In addition, migraine patients showed increased whole-brain FC in the left middle temporal gyrus (MTG), the right inferior frontal gyrus, the right superior temporal gyrus (STG) and the left inferior temporal gyrus, compared to HC.

CONCLUSIONS

ALE analysis identified consistent functional changes in widespread regions, especially in cingulate gyrus, basal ganglia region and frontal cortex in migraine. These regions involve in pain processing, cognitive dysfunction and emotional problems. These results may provide important clues for clarifying the pathophysiology of migraine.

Functional Activity in the Effect of Transcranial Magnetic Stimulation Therapy for Patients with Depression: A Meta-Analysis

Depression is a long-lasting mental disorder that affects more than 264 million people worldwide. Transcranial magnetic stimulation (TMS) can be a safe and effective choice for the treatment of depression. Functional neuroimaging provides unique insights into the neuropsychiatric effects of antidepressant TMS. In this meta-analysis, we aimed to assess the functional activity of brain regions caused by TMS for depression. A literature search was conducted from inception to 5 January 2022. Studies were then selected according to predetermined inclusion and exclusion criteria. Activation likelihood estimation was applied to analyze functional activation. Five articles were ultimately included after selection. The main analysis results indicated that TMS treatment for depression can alter the activity in the right precentral gyrus, right posterior cingulate, left inferior frontal gyrus and left middle frontal gyrus. In resting-state studies, increased activation was shown in the right precentral gyrus, right posterior cingulate, left inferior frontal gyrus and left superior frontal gyrus associated with TMS treatment. In task-related studies, clusters in the right middle frontal gyrus, left sub-gyrus, left middle frontal gyrus and left posterior cingulate were hyperactivated post-treatment. Our study offers an overview of brain activity changes in patients with depression after TMS treatment.

Functional connectivity directionality between large-scale resting-state networks across typical and non-typical trajectories in children and adolescence

Mental disorders often emerge during adolescence and have been associated with age-related differences in connection strengths of brain networks (static functional connectivity), manifesting in non-typical trajectories of brain development. However, little is known about the direction of information flow (directed functional connectivity) in this period of functional brain progression. We employed dynamic graphical models (DGM) to estimate directed functional connectivity from resting state functional magnetic resonance imaging data on 1143 participants, aged 6 to 17 years from the healthy brain network (HBN) sample. We tested for effects of age, sex, cognitive abilities and psychopathology on estimates of direction flow. Across participants, we show a pattern of reciprocal information flow between visual-medial and visual-lateral connections, in line with findings in adults. Investigating directed connectivity patterns between networks, we observed a positive association for age and direction flow from the cerebellar to the auditory network, and for the auditory to the sensorimotor network. Further, higher cognitive abilities were linked to lower information flow from the visual occipital to the default mode network. Additionally, examining the degree networks overall send and receive information to each other, we identified age-related effects implicating the right frontoparietal and sensorimotor network. However, we did not find any associations with psychopathology. Our results suggest that the directed functional connectivity of large-scale resting-state brain networks is sensitive to age and cognition during adolescence, warranting further studies that may explore directed relationships at rest and trajectories in more fine-grained network parcellations and in different populations.

Altered spatio-temporal state patterns for functional dynamics estimation in first-episode drug-naive major depression

Patients with major depressive disorder (MDD) display affective and cognitive impairments. Although MDD-associated abnormalities of brain function and structure have been explored in depth, the relationships between MDD and spatio-temporal large-scale functional networks have not been evaluated in large-sample datasets. We employed data from International Big-Data Center for Depression Research (IBCDR), and comparable 543 healthy controls (HC) and 314 first-episode drug-naive (FEDN) MDD patients were included. We used a multivariate pattern classification method to learn informative spatio-temporal functional states. Brain states of each participant were extracted for functional dynamic estimation using an independent component analysis. Then, a multi-kernel pattern classification method was developed to identify discriminative spatio-temporal states associated with FEDN MDD. Finally, statistical analysis was applied to intrinsic and clinical brain characteristics. Compared with HC, FEDN MDD patients exhibited altered spatio-temporal functional states of the default mode network (DMN), the salience network, a hub network (centered on the dorsolateral prefrontal cortex), and a relatively complex coupling network (visual, DMN, motor-somatosensory and subcortical networks). Multi-kernel classification models to distinguish patients from HC obtained areas under the receiver operating characteristic curves up to 0.80. Classification scores correlated with Hamilton Depression Rating Scale scores and age at MDD onset. FEDN MDD patients had multiple abnormal spatio-temporal functional states. Classification scores derived from these states were related to symptom severity. The assessment of spatio-temporal states may represent a powerful clinical and research tool to distinguish between neuropsychiatric patients and controls.

Altered neural networks and cognition in a hereditary colon cancer

Familial Adenomatous Polyposis (FAP) is an autosomal dominant disorder caused by mutation of the APC gene presenting with numerous colorectal adenomatous polyps and a near 100% risk of colon cancer. Preliminary research findings from our group indicate that FAP patients experience significant deficits across many cognitive domains. In the current study, fMRI brain metrics in a FAP population and matched controls were used to further the mechanistic understanding of reported cognitive deficits. This research identified and characterized any possible differences in resting brain networks and associations between neural network changes and cognition from 34 participants (18 FAP patients, 16 healthy controls). Functional connectivity analysis was performed using FSL with independent component analysis (ICA) to identify functional networks. Significant differences between cases and controls were observed in 8 well-established resting state networks. With the addition of an aggregate cognitive measure as a covariate, these differences were virtually non-existent, indicating a strong correlation between cognition and brain activity at the network level. The data indicate robust and pervasive effects on functional neural network activity among FAP patients and these effects are likely involved in cognitive deficits associated with this disease.

No associations in preregistered study of youth depression and functional connectivity of fronto-parietal and default mode networks

Adolescence is characterized by vulnerability to the onset of major depressive disorder (MDD). The goal of this preregistered study was to assess neural correlates of depression symptoms in young adolescents, both cross-sectionally and longitudinally. The default mode network (DMN) is believed to support internal attention towards self-referential thoughts, while the fronto-parietal network (FPN) is theorized to support cognitive control and regulation of attention. As MDD diagnosis has been associated with heightened connectivity within DMN regions and diminished connectivity within FPN regions relative to healthy controls, our study builds upon group-difference analyses by using dimensional measures of depression severity. Our preregistered hypotheses were that within-DMN functional connectivity would be positively associated with concurrent depression severity, while within-FPN functional connectivity would be negatively associated with concurrent depression severity. Preregistered analyses also examined between DMN-FPN connectivity as an alternative predictor variable, and assessed the longitudinal associations between all three functional connectivity measures and change in depression severity over three subsequent waves. Multiple regression models tested cross-sectional analyses and hierarchical linear models tested longitudinal analyses. One hundred and twenty-four youth completed a resting state functional MRI. Their depression severity was assessed at the time of the scan and at three follow-up sessions. None of the predictor variables were associated with concurrent depression severity, nor with the slope of depression symptom trajectories in longitudinal analyses. These negative results add to extant cross-sectional studies, and may inform future investigations of brain correlates of depression psychopathology in youth.

Disrupted rich-club network organization and individualized identification of patients with major depressive disorder

BACKGROUND

Altered structural and functional brain networks have been extensively studied in major depressive disorder (MDD) patients. However, whether the differential connectivity patterns in the rich-club organization, assessed from structural brain network analyses, and the associated connections of these regions are particularly susceptible to depression remain unclear.

METHODS

We acquired resting-state functional magnetic resonance imaging (R-fMRI) and diffusion tensor imaging (DTI) from 31 unmedicated MDD patients and 32 cognitively normal (CN) subjects and completed a series of neuropsychological tests. Rich-club organization, network properties, and coupling between structural and functional connectivity (SC-FC) were explored. Furthermore, whether these indices could potentially deliver effective clinical predictive value for MDD patients were examined.

RESULTS

The MDD patients showed disrupted structural rich-club organization and modularity, as well as a distinct correlation pattern between global efficiency and rich-club organization. Importantly, reduced SC-FC coupling, reflecting a decreased agreement in the integrity of the networks, was significantly associated with the strength of structural rich-club connections in the MDD patients. Furthermore, the disrupted structural rich-club organization, which was primarily located in the default mode network (DMN) and executive control network (ECN), emerged as a valuable indicator to distinguish between MDD and CN.

CONCLUSIONS

Findings of this study identified that the disrupted rich-club structural organization significantly influenced brain structural network modularity and integrity and could serve as a promising biological marker for the identification of MDD patients.

Default Mode Network Functional Connectivity Negatively Associated with Trait Openness to Experience

Evaluating associations between the five-factor personality domains and resting-state functional connectivity networks (e.g., default mode network, DMN) highlights distributed neurobiological systems linked to behaviorally relevant phenotypes. Establishing these associations can highlight a potential underlying role for these neural pathways in related clinical illness and treatment response. Here we examined associations between within- and between-network resting-state functional connectivity with functional magnetic resonance imaging (fMRI) and the five-factor personality domains: Openness to experience (Openness), Extraversion, Neuroticism, Agreeableness and Conscientiousness. We included data from 470 resting-state scan sessions and personality assessments in 295 healthy participants. Within- and between-network functional connectivity from 32 a priori defined regions was computed across seven resting-state networks. The association between functional connectivity and personality traits was assessed using generalized least squares. Within-network DMN functional connectivity was significantly negatively associated with trait Openness (regression coefficient= -0.0010; [95% CI] = [-0.0017, -0.0003]; pFWER = 0.033), seemingly driven by association with the Fantasy subfacet. Trait Extraversion was significantly negatively associated with functional connectivity between the visual and dorsal attention networks and positively associated with functional connectivity between the frontoparietal and language networks. Our findings provide evidence that resting-state DMN is associated with trait Openness and gives insight into personality neuroscience.

Altered Resting State Brain Networks and Cognition in Familial Adenomatous Polyposis

Familial Adenomatous Polyposis (FAP) is an autosomal dominant disorder caused by mutation of the APC gene presenting with numerous colorectal adenomatous polyps and a near 100% risk of colon cancer. Preliminary research findings from our group indicate that FAP patients experience significant deficits across many cognitive domains. In the current study, fMRI brain metrics in a FAP population and matched controls were used to further the mechanistic understanding of reported cognitive deficits. This research identified and characterized any possible differences in resting brain networks and associations between neural network changes and cognition from 34 participants (18 FAP patients, 16 healthy controls). Functional connectivity analysis was performed using FSL with independent component analysis (ICA) to identify functional networks. Significant differences between cases and controls were observed in 8 well-established resting state networks. With the addition of an aggregate cognitive measure as a covariate, these differences were virtually non-existent, indicating a strong correlation between cognition and brain activity at the network level. The data indicate robust and pervasive effects on functional neural network activity among FAP patients and these effects are likely involved in cognitive deficits associated with this disease.

Persistent Intrinsic Functional Network Connectivity Alterations in Middle-Aged and Older Women With Remitted Depression

BACKGROUND

In younger adults, residual alterations in functional neural networks persist during remitted depression. However, there are fewer data for midlife and older adults at risk of recurrence. Such residual network alterations may contribute to vulnerability to recurrence. This study examined intrinsic network functional connectivity in midlife and older women with remitted depression.

METHODS

A total of 69 women (24 with a history of depression, 45 with no psychiatric history) over 50 years of age completed 3T fMRI with resting-state acquisition. Participants with remitted depression met DSM-IV-TR criteria for an episode in the last 10 years but not the prior year. Whole-brain seed-to-voxel resting-state functional connectivity analyses examined the default mode network (DMN), executive control network (ECN), and salience network (SN), plus bilateral hippocampal seeds. All analyses were adjusted for age and used cluster-level correction for multiple comparisons with FDR < 0.05 and a height threshold of p < 0.001, uncorrected.

RESULTS

Women with a history of depression exhibited decreased functional connectivity between the SN (right insula seed) and ECN regions, specifically the left superior frontal gyrus. They also exhibited increased functional connectivity between the left hippocampus and the left postcentral gyrus. We did not observe any group differences in functional connectivity for DMN or ECN seeds.

CONCLUSIONS

Remitted depression in women is associated with connectivity differences between the SN and ECN and between the hippocampus and the postcentral gyrus, a region involved in interoception. Further work is needed to determine whether these findings are related to functional alterations or are predictive of recurrence.