Aberrant Functional Connectivity of Sensorimotor Network and Its Relationship With Executive Dysfunction in Bipolar Disorder Type I

Network-based alterations in task-induced functional connectivity in bipolar disorder: An functional near-infrared spectroscopy study

BACKGROUND

Functional near-infrared spectroscopy (fNIRS) is increasingly used to examine cognitive abilities and support the diagnosis of bipolar disorder (BD). Despite its growing application, research on functional connectivity in BD remains limited, and task-induced functional connectivity remains under-investigated. This study aims to differentiate patients with BD from healthy controls (HCs) based on fNIRS-derived functional connectivity.

METHODS

We analyzed fNIRS data from 50 patients with BD and 50 HCs during resting state and two cognitive tasks, including the verbal fluency test (VFT) and Stroop color-word test (Stroop). Functional connectivity was quantified using coherence and correlation evaluations, and four network characteristics, such as local efficiency, global efficiency, global clustering coefficient, and average closeness centrality, were extracted. A thresholding method was applied by filtering the top 10 % to 50 % to highlight significant network connections. Group differences were evaluated using t-tests with false discovery rate.

FINDINGS

Patients with BD showed significantly altered coherence values, especially between channels 4 and 10 (p < 0.001, t = -5.534, η2 = 0.562) and lower global clustering coefficients (p < 0.001, t = -5.666, η2 = 0.578) compared to HCs. The k-nearest neighbor (KNN) classifier using coherence-based network metrics during the VFT achieved the highest classification performance with an accuracy of 0.818, precision of 0.819, recall of 0.824, and an F1-score of 0.817.

CONCLUSION

Our findings suggest that task-induced functional connectivity, particularly coherence-based metrics derived during the VFT, reflects distinct functional connectivity patterns that differentiate patients with BD from HCs. These findings support the utility of network-based approaches under cognitive task conditions in characterizing functional connectivity alterations associated with BD.

Advancements in the study of large-scale network alterations in brain functional connectivity among individuals with bipolar disorder

BACKGROUND

Bipolar disorder (BD) is characterized by structural and functional impairments of varying severity. However, inconsistent findings from previous studies have led to an incomplete understanding of the precise associations both within and between functional networks in BD. Analysis from a large-scale network perspective may offer more comprehensive insights.

METHOD

Studies that used functional magnetic resonance imaging (fMRI) to explore the changes in functional connectivity (FC) within and between major brain networks in patients with BD were included by searching for keywords such as "bipolar disorder," "brain networks," and "functional connectivity" in PubMed and Web of Science.

RESULT

51 studies met the inclusion criteria. At rest, BD patients exhibited reduced intrinsic connectivity within the default mode network (DMN), salience network (SAN), and central executive network (CEN). Furthermore, alterations were observed in other networks, suggesting a complex pattern of connectivity changes associated with emotional states and cognitive functions.

CONCLUSION

BD disrupts the activity of brain networks during both resting state and task stimulation. Posterior cingulate cortex (PCC), anterior insula (AI), postcentral gyrus (PoCG), and precuneus (PreCu) play a crucial role in the identification and diagnosis of BD. They are significant in differentiating BD from other mental illnesses and assessing patients' cognitive deficits. However, this study has limitations in the insufficient exploration of other potentially related networks.

Biomarker identification in bipolar disorder

Bipolar disorder (BD) is a severe psychiatric condition whose pathophysiology is complex and multifactorial. Genetic, environmental and social risk factors play a role in its development as well as in its progressive course. Research is currently focusing on the identification of the biological basis underlying these processes in order to suggest novel biomarkers capable to predict BD etiopathogenesis and staging. Staging has been recognized as of great value for the treatment and management of many illnesses and might also be suitable for mental health issues, particularly in disorders like BD, which progress from an initial mild phase to a more severe and thus difficult-to-treat situation. Thus, it would be of great help the characterization of to suggest better treatment requirements and improve prognosis across the different stages of the illness. Here, we summarize current research on the biological hypotheses of BD and the biomarkers associated with its progression, reviewing clinical studies available in the literature.

Limbic-Sensorimotor Tug of War for the Hippocampus: Dynamic Functional Connectivity as a Transdiagnostic Vulnerability Marker in Offspring of Emotion Dysregulation Patients

BACKGROUND

Emotion dysregulation (ED) is a key transdiagnostic symptom in several psychiatric disorders such as borderline personality disorder (BPD), bipolar disorder (BD), and attention-deficit/hyperactivity disorder (ADHD). These disorders, here defined as ED disorders (EDD), share similarities in symptoms, comorbidity, and heritability, emphasizing the importance of a transdiagnostic approach to identify markers of vulnerability to EDD in high-risk populations, such as EDD patients' offspring (EDDoff). The hippocampus, central to ED, exhibits alterations across EDD.

METHODS

We employed a state-of-the-art approach (micro-co-activation patterns, μCAPs) to study the transdiagnostic dynamic functional connectivity (dFC) of hippocampal subregions from resting-state functional MRI of 201 participants (74 EDD patients, 57 EDDoff, 70 controls). μCAPs provide a data-driven differentiation within the seed region.

RESULTS

DFC between the sensorimotor network (SMN) and the hippocampal body was lower in EDD patients (pFDR=0.0002) and EDDoff (pFDR=0.01) compared to controls, with EDDoff displaying an intermediate pattern between EDD patients and controls. dFC between the limbic network (LN) and the hippocampal head was higher in EDD patients than in controls (pFDR=0.01) and in EDDoff (pFDR=0.01). A negative correlation was found between ED and SMN (pFDR=0.01), suggesting increasing ED with decreasing SMN dFC with the hippocampus.

CONCLUSIONS

Increased dFC between the hippocampal head and the LN, at the expense of the SMN, may represent a marker of disease in EDD patients. Lower dFC between the SMN and the hippocampal body may represent a marker of vulnerability to EDD in EDDoff, correlating with ED. Such a transdiagnostic construct represents a clinically relevant target for early interventions aimed at reducing vulnerability to EDD in high-risk populations.

Individualized prediction of multi-domain intelligence quotient in bipolar disorder patients using resting-state functional connectivity

BACKGROUND

Although accumulating studies have explored the neural underpinnings of intelligence quotient (IQ) in patients with bipolar disorder (BD), these studies utilized a classification/comparison scheme that emphasized differences between BD and healthy controls at a group level. The present study aimed to infer BD patients' IQ scores at the individual level using a prediction model.

METHODS

We applied a cross-validated Connectome-based Predictive Modeling (CPM) framework using resting-state fMRI functional connectivity (FCs) to predict BD patients' IQ scores, including verbal IQ (VIQ), performance IQ (PIQ), and full-scale IQ (FSIQ). For each IQ domain, we selected the FCs that contributed to the predictions and described their distribution across eight widely-recognized functional networks. Moreover, we further explored the overlapping patterns of the contributed FCs for different IQ domains.

RESULTS

The CPM achieved statistically significant prediction performance for three IQ domains in BD patients. Regarding the contributed FCs, we observed a widespread distribution of internetwork FCs across somatomotor, visual, dorsal attention, and ventral attention networks, demonstrating their correspondence with aberrant FCs correlated to cognition deficits in BD patients. A convergent pattern in terms of contributed FCs for different IQ domains was observed, as evidenced by the shared-FCs with a leftward hemispheric dominance.

CONCLUSIONS

The present study preliminarily explored the feasibility of inferring individual IQ scores in BD patients using the FCs-based CPM framework. It is a step toward the development of applicable techniques for quantitative and objective cognitive assessment in BD patients and contributes novel insights into understanding the complex neural mechanisms underlying different IQ domains.

Diagnostic value of structural, functional and effective connectivity in bipolar disorder

INTRODUCTION

The aim of this systematic review is to assess the functional magnetic resonance imaging (fMRI) studies of bipolar disorder (BD) patients that characterize differences in terms of structural, functional, and effective connectivity between the patients with BD, patients with other psychiatric disorders and healthy controls as possible biomarkers for diagnosing the disorder using neuroimaging.

METHODS

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), guidelines a systematic search for recent (since 2015) original studies on connectivity in bipolar disorder was conducted in PUBMED and SCOPUS.

RESULTS

A total of 60 studies were included in this systematic review: 20 of the structural connectivity, 33 of the functional connectivity, and only 7 of the studies focused on effective connectivity complied with the inclusion and exclusion criteria.

DISCUSSION

Despite the great heterogeneity in the findings, there are several trends that emerge. In structural connectivity studies, the main abnormalities in bipolar disorder patients were in the frontal gyrus, anterior, as well as posterior cingulate cortex and differences in emotion and reward-related networks. Cerebellum (vermis) to cerebrum functional connectivity was found to be the most common finding in BD. Moreover, prefrontal cortex and amygdala connectivity as part of the rich-club hubs were often reported to be disrupted. The most common findings based on effective connectivity were alterations in salience network, default mode network and executive control network. Although more studies with larger sample sizes are needed to ascertain altered brain connectivity as diagnostic biomarker, there is a perspective that the method could be used as a single marker of diagnosis in the future, and the process of adoption could be accelerated by using approaches such as semiunsupervised machine learning.

Functional connectivity density of postcentral gyrus predicts rumination and major depressive disorders in males

Major depressive disorder (MDD) is characterized by persistent sadness and loss of interest. Recent evidence suggested that abnormal functional connectivity (FC) may be linked to the development of MDD, and gender differences existed in FC patterns. In this study, we utilized resting-state functional magnetic resonance imaging (RS-fMRI) data from 41 healthy participants to identify FC patterns that correlate with levels of rumination in both genders. A 2-sample t-test showed no gender differences in rumination levels. A functional connectivity density (FCD) analysis was then conducted using DPABI. It was revealed that in males, the FCD of the postcentral gyrus (PCG) was negatively correlated with the levels of rumination and brooding (Pearson's r > 0.25), while not with reflection. No FCD in females was related to rumination or its subtypes. Further FC analysis revealed that the FC between the PCG and several regions, predominantly from the default mode network (DMN), were negatively correlated with rumination levels (Pearson's r > 0.25). This link was assumed to be a risk factor for rumination and MDD in males. In conclusion, our findings indicate that the PCG-DMN connectivity is a potential risk factor for MDD in males, while no FC risk factors were found in females.

Assessing the Modulatory Effects of tDCS and Acupuncture on Cerebral Blood Flow in Chronic Low Back Pain Using Arterial Spin Labeling Perfusion Imaging

BACKGROUND

Both transcranial direct current stimulation (tDCS) and acupuncture are promising methods for managing chronic low back pain (cLBP), however, their underlying mechanisms remain unclear.

METHODS

To explore the neural mechanisms of tDCS and acupuncture on cLBP, we examined how real and sham tDCS applied to the bilateral motor cortex (M1), combined with real or sham acupuncture, influenced cerebral blood flow (CBF) using pulsed continuous arterial spin labeling (pCASL) imaging. tDCS was administered over six sessions, combined with real or sham acupuncture, over one month.

RESULTS

Following real tDCS, we observed increased CBF in the bilateral occipital cortex, precuneus, left hippocampus, and parahippocampal gyrus/posterior cingulate cortex. After sham tDCS, CBF decreased in regions including the bilateral superior parietal lobule, precuneus, bilateral precentral and postcentral gyri, and left angular gyrus. Real acupuncture led to reduced CBF in the bilateral occipital cortex and hippocampus, and left posterior cingulate gyrus, and increased CBF in the right postcentral gyrus, superior parietal lobule, and frontal areas. Sham acupuncture was associated with decreased CBF in the bilateral hippocampus and anterior cingulate gyrus.

CONCLUSIONS

These results suggest both shared and distinct patterns of CBF changes between real and sham tDCS, as well as between real and sham acupuncture, reflecting mode-dependent effects on brain networks involved in pain processing and modulation. Our findings highlight the different neural circuits implicated in the therapeutic mechanisms of tDCS and acupuncture in the management of cLBP.

Hippocampal temporal dynamics and spatial heterogeneity unveil vulnerability markers in the offspring of bipolar patients

OBJECTIVES

Bipolar disorder (BD) is a highly heritable disorder characterized by emotion dysregulation and recurrent oscillations between mood states. Despite the proven efficacy of early interventions, vulnerability markers in high-risk individuals are still lacking. BD patients present structural alterations of the hippocampus, a pivotal hub of emotion regulation networks composed of multiple subregions with different projections. However, the hippocampal dynamic functional connectivity (dFC) in BD remains unclear. We aim to investigate whether the dFC of hippocampal subdivisions differentiates BD patients, offspring of BD patients (BDoff), and healthy controls (HC); and whether it correlates with symptoms differently between these groups.

METHODS

We studied for the first time the dFC of the hippocampus through a cutting-edge micro-co-activation patterns (μCAPs) analysis of resting-state functional MRI data of 97 subjects (26 BD, 18 BDoff, 53 HC). μCAPs allow a data-driven differentiation within the seed region.

RESULTS

dFC between the hippocampal body and a somatomotor-μCAP was lower both in BD patients (p-valueFDR:0.00015) and in BDoff (p-valueFDR:0.020) than in HC. Inversely, dFC between the hippocampal head and a limbic-μCAP was higher in BD patients than in HC (p-valueFDR: 0.005). Furthermore, the correlations between a frontoparietal-μCAP and both depression and emotion dysregulation symptoms were significantly higher in BD than HC (p-valueFDR <0.02).

CONCLUSION

Overall, we observed alterations of large-scale functional brain networks associated with decreased cognitive control flexibility and disrupted somatomotor, saliency, and emotion processing in BD. Interestingly, BDoff presented an intermediate phenotype between BD and HC, suggesting that dFC of hippocampal subregions might represent a marker of vulnerability to BD.

Cerebellocerebral connectivity predicts body mass index: a new open-source Python-based framework for connectome-based predictive modeling

BACKGROUND

The cerebellum is one of the major central nervous structures consistently altered in obesity. Its role in higher cognitive function, parts of which are affected by obesity, is mediated through projections to and from the cerebral cortex. We therefore investigated the relationship between body mass index (BMI) and cerebellocerebral connectivity.

METHODS

We utilized the Human Connectome Project's Young Adults dataset, including functional magnetic resonance imaging (fMRI) and behavioral data, to perform connectome-based predictive modeling (CPM) restricted to cerebellocerebral connectivity of resting-state fMRI and task-based fMRI. We developed a Python-based open-source framework to perform CPM, a data-driven technique with built-in cross-validation to establish brain-behavior relationships. Significance was assessed with permutation analysis.

RESULTS

We found that (i) cerebellocerebral connectivity predicted BMI, (ii) task-general cerebellocerebral connectivity predicted BMI more reliably than resting-state fMRI and individual task-based fMRI separately, (iii) predictive networks derived this way overlapped with established functional brain networks (namely, frontoparietal networks, the somatomotor network, the salience network, and the default mode network), and (iv) we found there was an inverse overlap between networks predictive of BMI and networks predictive of cognitive measures adversely affected by overweight/obesity.

CONCLUSIONS

Our results suggest obesity-specific alterations in cerebellocerebral connectivity, specifically with regard to task execution. With brain areas and brain networks relevant to task performance implicated, these alterations seem to reflect a neurobiological substrate for task performance adversely affected by obesity.

Dynamic brain entropy predicts risky decision-making across transdiagnostic dimensions of psychopathology

OBJECTIVES

Maladaptive risky decision-making is a common pathological behavior among patients with various psychiatric disorders. Brain entropy, which measures the complexity of brain time series signals, provides a novel approach to assessing brain health. Despite its potential, the dynamics of brain entropy have seldom been explored. This study aimed to construct a dynamic model of brain entropy and examine its predictive value for risky decision-making in patients with mental disorders, utilizing resting-state functional magnetic resonance imaging (rs-fMRI).

METHODS

This study analyzed the rs-fMRI data from a total of 198 subjects, including 48 patients with bipolar disorder (BD), 47 patients with schizophrenia (SZ), 40 patients with adult attention deficit hyperactivity disorder (ADHD), as well as 63 healthy controls (HC). Time series signals were extracted from 264 brain regions based on rs-fMRI. The traditional static entropy and dynamic entropy (coefficient of variation, CV; rate of change, Rate) were constructed, respectively. Support vector regression was employed to predict risky decision-making utilizing leave-one-out cross-validation within each group.

RESULTS

Our findings showed that CV achieved the best performances in HC and BD groups (r = -0.58, MAE = 6.43, R2 = 0.32; r = -0.78, MAE = 12.10, R2 = 0.61), while the Rate achieved the best in SZ and ADHD groups (r = -0.69, MAE = 10.20, R2 = 0.47; r = -0.78, MAE = 7.63, R2 = 0.60). For the dynamic entropy, the feature selection threshold rather than the time window length and overlapping ratio influenced predictive performance.

CONCLUSIONS

These results suggest that dynamic brain entropy could be a more effective predictor of risky decision-making than traditional static brain entropy. Our findings offer a novel perspective on exploring brain signal complexity and can serve as a reference for interventions targeting risky decision-making behaviors, particularly in individuals with psychiatric diagnoses.

Frequent absent mindedness and the neural mechanism trapped by mobile phone addiction

With the increased availability and sophistication of digital devices in the last decade, young people have become mainstream mobile phone users. Heavy mobile phone dependence causes affective problems (depression, anxiety) and loss of attention on current activities, leading to more cluttered thoughts. Problematic mobile phone use has been found to increase the occurrence of mind wandering, but the neural mechanism underlying this relationship remains unclear. The current study aims to investigate the neural mechanism between mobile phone use and mind wandering. University students from datasets (ongoing research project named Gene-Brain-Behavior project, GBB) completed psychological assessments of mobile phone addiction and mind wandering and underwent resting-state functional connectivity (FC) scanning. FC matrix was constructed to further conduct correlation and mediation analyses. Students with high mobile phone addiction scores were more likely to have high mind wandering scores. FC among the default mode, motor, frontoparietal, basal ganglia, limbic, medial frontal, visual association, and cerebellar networks formed the neural basis of mind wandering. FC between the frontoparietal and motor networks, between the default mode network and cerebellar network, and within the cerebellar network mediated the relationship between mobile phone addiction and mind wandering. The findings confirm that mobile phone addiction is a risk factor for increased mind wandering and reveal that FC in several brain networks underlies this relationship. They contribute to research on behavioral addiction, education, and mental health among young adults.

Abnormal Dynamic Reconfiguration of Multilayer Temporal Networks in Patients with Bipolar Disorder

BACKGROUND

Multilayer networks have been used to identify abnormal dynamic reconfiguration in bipolar disorder (BD). However, these studies ignore the differences in information interactions between adjacent layers when constructing multilayer networks, and the analysis of dynamic reconfiguration is not comprehensive enough; Methods: Resting-state functional magnetic resonance imaging data were collected from 46 BD patients and 54 normal controls. A multilayer temporal network was constructed for each subject, and inter-layer coupling of different nodes was considered using network similarity. The promiscuity, recruitment, and integration coefficients were calculated to quantify the different dynamic reconfigurations between the two groups; Results: The global inter-layer coupling, recruitment, and integration coefficients were significantly lower in BD patients. These results were further observed in the attention network and the limbic/paralimbic and subcortical network, reflecting reduced temporal stability, intra- and inter-subnetwork communication abilities in BD patients. The whole-brain promiscuity was increased in BD patients. The same results were observed in the somatosensory/motor and auditory network, reflecting more functional interactions; Conclusions: This study discovered abnormal dynamic interactions of BD from the perspective of dynamic reconfiguration, which can help to understand the pathological mechanisms of BD.

The causal relationship between human brain morphometry and knee osteoarthritis: a two-sample Mendelian randomization study

BACKGROUND

Knee Osteoarthritis (KOA) is a prevalent and debilitating condition affecting millions worldwide, yet its underlying etiology remains poorly understood. Recent advances in neuroimaging and genetic methodologies offer new avenues to explore the potential neuropsychological contributions to KOA. This study aims to investigate the causal relationships between brain-wide morphometric variations and KOA using a genetic epidemiology approach.

METHOD

Leveraging data from 36,778 UK Biobank participants for human brain morphometry and 487,411 UK Biobank participants for KOA, this research employed a two-sample Mendelian Randomization (TSMR) approach to explore the causal effects of 83 brain-wide volumes on KOA. The primary method of analysis was the Inverse Variance Weighted (IVW) and Wald Ratio (WR) method, complemented by MR Egger and IVW methods for heterogeneity and pleiotropy assessments. A significance threshold of p < 0.05 was set to determine causality. The analysis results were assessed for heterogeneity using the MR Egger and IVW methods. Brain-wide volumes with Q_pval < 0.05 were considered indicative of heterogeneity. The MR Egger method was employed to evaluate the pleiotropy of the analysis results, with brain-wide volumes having a p-value < 0.05 considered suggestive of pleiotropy.

RESULTS

Our findings revealed significant causal associations between KOA and eight brain-wide volumes: Left parahippocampal volume, Right posterior cingulate volume, Left transverse temporal volume, Left caudal anterior cingulate volume, Right paracentral volume, Left paracentral volume, Right lateral orbitofrontal volume, and Left superior temporal volume. These associations remained robust after tests for heterogeneity and pleiotropy, underscoring their potential role in the pathogenesis of KOA.

CONCLUSION

This study provides novel evidence of the causal relationships between specific brain morphometries and KOA, suggesting that neuroanatomical variations might contribute to the risk and development of KOA. These findings pave the way for further research into the neurobiological mechanisms underlying KOA and may eventually lead to the development of new intervention strategies targeting these neuropsychological pathways.

Structural and functional disruption of subcortical limbic structures related with executive function in pediatric bipolar disorder

BACKGROUND

Impaired cognition has been demonstrated in pediatric bipolar disorder (PBD). The subcortical limbic structures play a key role in PBD. However, alternations of anatomical and functional characteristics of subcortical limbic structures and their relationship with neurocognition of PBD remain unclear.

METHODS

Thirty-six PBD type I (PBD-I) (15.36 ± 0.32 years old), twenty PBD type II (PBD-II) (14.80 ± 0.32 years old) and nineteen age-gender matched healthy controls (HCs) (14.16 ± 0.36 years old) were enlisted. Primarily, the volumes of the subcortical limbic structures were obtained and differences in the volumes were evaluated. Then, these structures served as seeds of regions of interest to calculate the voxel-wised functional connectivity (FC). After that, correlation analysis was completed between volumes and FC of brain regions showing significant differences and neuropsychological tests.

RESULTS

Compared to HCs, both PBD-I and PBD-II patients showed a decrease in the Stroop color word test (SCWT) and digit span backward test scores. Compared with HCs, PBD-II patients exhibited a significantly increased volume of right septal nuclei, and PBD-I patients presented increased FC of right nucleus accumbens and bilateral pallidum, of right basal forebrain with right putamen and left pallidum. Both the significantly altered volumes and FC were negatively correlated with SCWT scores.

SIGNIFICANCE

The study revealed the role of subcortical limbic structural and functional abnormalities on cognitive impairments in PBD patients. These may have far-reaching significance for the etiology of PBD and provide neuroimaging clues for the differential diagnosis of PBD subtypes.

CONCLUSIONS

Distinctive features of neural structure and function in PBD subtypes may contribute to better comprehending the potential mechanisms of PBD.

Functional connectivity alterations in the thalamus among patients with bronchial asthma

Objective

Bronchial Asthma (BA) is a common chronic respiratory disease worldwide. Earlier research has demonstrated abnormal functional connectivity (FC) in multiple cognition-related cortices in asthma patients. The thalamus (Thal) serves as a relay center for transmitting sensory signals, yet the modifications in the thalamic FC among individuals with asthma remain uncertain. This research employed the resting-state functional connectivity (rsFC) approach to explore alterations in thalamic functional connectivity among individuals with BA.

Patients and methods

After excluding participants who did not meet the criteria, this study finally included 31 patients with BA, with a gender distribution of 16 males and 15 females. Subsequently, we recruited 31 healthy control participants (HC) matched for age, gender, and educational background. All participants underwent the Montreal Cognitive Assessment (MoCA) and the Hamilton Depression Rating Scale (HAMD) assessment. Following this, both groups underwent head magnetic resonance imaging scans, and resting-state functional magnetic resonance imaging (rs-fMRI) data was collected. Based on the AAL (Automated Anatomical Labeling) template, the bilateral thalamic regions were used as seed points (ROI) for subsequent rsFC research. Pearson correlation analysis was used to explore the relationship between thalamic functional connectivity and neuropsychological scales in both groups. After controlling for potential confounding factors such as age, gender, intelligence, and emotional level, a two-sample t-test was further used to explore differences in thalamic functional connectivity between the two groups of participants.

Result

Compared to the HC group, the BA group demonstrated heightened functional connectivity (FC) between the left thalamus and the left cerebellar posterior lobe (CPL), left postcentral gyrus (PCG), and right superior frontal gyrus (SFG). Concurrently, there was a decrease in FC with both the Lentiform Nucleus (LN) and the left corpus callosum (CC). Performing FC analysis with the right thalamus as the Region of Interest (ROI) revealed an increase in FC between the right thalamus and the right SFG as well as the left CPL. Conversely, a decrease in FC was observed between the right thalamus and the right LN as well as the left CC.

Conclusion

In our study, we have verified the presence of aberrant FC patterns in the thalamus of BA patients. When compared to HCs, BA patients exhibit aberrant alterations in FC between the thalamus and various brain areas connected to vision, hearing, emotional regulation, cognitive control, somatic sensations, and wakefulness. This provides further confirmation of the substantial role played by the thalamus in the advancement of BA.

Morphological and regional spontaneous functional aberrations in the brain associated with Crohn's disease: a systematic review and coordinate-based meta-analyses

Crohn's disease is an acknowledged "brain-gut" disorder with unclear physiopathology. This study aims to identify potential neuroimaging biomarkers of Crohn's disease. Gray matter volume, cortical thickness, amplitude of low-frequency fluctuations, and regional homogeneity were selected as indices of interest and subjected to analyses using both activation likelihood estimation and seed-based d mapping with permutation of subject images. In comparison to healthy controls, Crohn's disease patients in remission exhibited decreased gray matter volume in the medial frontal gyrus and concurrently increased regional homogeneity. Furthermore, gray matter volume reduction in the medial superior frontal gyrus and anterior cingulate/paracingulate gyri, decreased regional homogeneity in the median cingulate/paracingulate gyri, superior frontal gyrus, paracentral lobule, and insula were observed. The gray matter changes of medial frontal gyrus were confirmed through both methods: decreased gray matter volume of medial frontal gyrus and medial superior frontal gyrus were identified by activation likelihood estimation and seed-based d mapping with permutation of subject images, respectively. The meta-regression analyses showed a positive correlation between regional homogeneity alterations and patient age in the supplementary motor area and a negative correlation between gray matter volume changes and patients' anxiety scores in the medial superior frontal gyrus. These anomalies may be associated with clinical manifestations including abdominal pain, psychiatric disorders, and possibly reflective of compensatory mechanisms.

Inflammation and emotion regulation: a narrative review of evidence and mechanisms in emotion dysregulation disorders

Emotion dysregulation (ED) describes a difficulty with the modulation of which emotions are felt, as well as when and how these emotions are experienced or expressed. It is a focal overarching symptom in many severe and prevalent neuropsychiatric diseases, including bipolar disorders (BD), attention deficit/hyperactivity disorder (ADHD), and borderline personality disorder (BPD). In all these disorders, ED can manifest through symptoms of depression, anxiety, or affective lability. Considering the many symptomatic similarities between BD, ADHD, and BPD, a transdiagnostic approach is a promising lens of investigation. Mounting evidence supports the role of peripheral inflammatory markers and stress in the multifactorial aetiology and physiopathology of BD, ADHD, and BPD. Of note, neural circuits that regulate emotions appear particularly vulnerable to inflammatory insults and peripheral inflammation, which can impact the neuroimmune milieu of the central nervous system. Thus far, few studies have examined the link between ED and inflammation in BD, ADHD, and BPD. To our knowledge, no specific work has provided a critical comparison of the results from these disorders. To fill this gap in the literature, we review the known associations and mechanisms linking ED and inflammation in general, and clinically, in BD, ADHD, and BD. Our narrative review begins with an examination of the routes linking ED and inflammation, followed by a discussion of disorder-specific results accounting for methodological limitations and relevant confounding factors. Finally, we critically discuss both correspondences and discrepancies in the results and comment on potential vulnerability markers and promising therapeutic interventions.

Connectome-based modeling reveals a resting-state functional network that mediates the relationship between social rejection and rumination

Background

Rumination impedes problem solving and is one of the most important factors in the onset and maintenance of multiple psychiatric disorders. The current study aims to investigate the impact of social rejection on rumination and explore the underlying neural mechanisms involved in this process.

Methods

We utilized psychological questionnaire and resting-state brain imaging data from a sample of 560 individuals. The predictive model for rumination scores was constructed using resting-state functional connectivity data through connectome-based predictive modeling. Additionally, a mediation analysis was conducted to investigate the mediating role of the prediction network in the relationship between social rejection and rumination.

Results

A positive correlation between social rejection and rumination was found. We obtained the prediction model of rumination and found that the strongest contributions came from the intra- and internetwork connectivity within the default mode network (DMN), dorsal attention network (DAN), frontoparietal control network (FPCN), and sensorimotor networks (SMN). Analysis of node strength revealed the significance of the supramarginal gyrus (SMG) and angular gyrus (AG) as key nodes in the prediction model. In addition, mediation analysis showed that the strength of the prediction network mediated the relationship between social rejection and rumination.

Conclusion

The findings highlight the crucial role of functional connections among the DMN, DAN, FPCN, and SMN in linking social rejection and rumination, particular in brain regions implicated in social cognition and emotion, namely the SMG and AG regions. These results enhance our understanding of the consequences of social rejection and provide insights for novel intervention strategies targeting rumination.

Seasonal variations of functional connectivity of human brains

Seasonal variations have long been observed in various aspects of human life. While there is an abundance of research that has characterized seasonality effects in, for example, cognition, mood, and behavior, including studies of underlying biophysical mechanisms, direct measurements of seasonal variations of brain functional activities have not gained wide attention. We have quantified seasonal effects on functional connectivity as derived from MRI scans. A cohort of healthy human subjects was divided into four groups based on the seasons of their scanning dates as documented in the image database of the Human Connectome Project. Sinusoidal functions were used as regressors to determine whether there were significant seasonal variations in measures of brain activities. We began with the analysis of seasonal variations of the fractional amplitudes of low frequency fluctuations of regional functional signals, followed by the seasonal variations of functional connectivity in both global- and network-level. Furthermore, relevant environmental factors, including average temperature and daylength, were found to be significantly associated with brain functional activities, which may explain how the observed seasonal fluctuations arise. Finally, topological properties of the brain functional network also showed significant variations across seasons. All the observations accumulated revealed seasonality effects of human brain activities in a resting-state, which may have important practical implications for neuroimaging research.

Brain nuclei and neural circuits in neuropathic pain and brain modulation mechanisms of acupuncture: a review on animal-based experimental research

Neuropathic pain (NP) is known to be associated with abnormal changes in specific brain regions, but the complex neural network behind it is vast and complex and lacks a systematic summary. With the help of various animal models of NP, a literature search on NP brain regions and circuits revealed that the related brain nuclei included the periaqueductal gray (PAG), lateral habenula (LHb), medial prefrontal cortex (mPFC), and anterior cingulate cortex (ACC); the related brain circuits included the PAG-LHb and mPFC-ACC. Moreover, acupuncture and injurious information can affect different brain regions and influence brain functions via multiple aspects to play an analgesic role and improve synaptic plasticity by regulating the morphology and structure of brain synapses and the expression of synapse-related proteins; maintain the balance of excitatory and inhibitory neurons by regulating the secretion of glutamate, γ-aminobutyric acid, 5-hydroxytryptamine, and other neurotransmitters and receptors in the brain tissues; inhibit the overactivation of glial cells and reduce the release of pro-inflammatory mediators such as interleukins to reduce neuroinflammation in brain regions; maintain homeostasis of glucose metabolism and regulate the metabolic connections in the brain; and play a role in analgesia through the mediation of signaling pathways and signal transduction molecules. These factors help to deepen the understanding of NP brain circuits and the brain mechanisms of acupuncture analgesia.

Dynamic functional hippocampal markers of residual depressive symptoms in euthymic bipolar disorder

OBJECTIVES

Bipolar disorder (BD) is a severe, chronic, affective disorder characterized by recurrent switching between mood states, psychomotor and cognitive symptoms, which can linger in euthymic states as residual symptoms. Hippocampal alterations may play a key role in the neural processing of BD symptoms. However, its dynamic functional connectivity (dFC) remains unclear. Therefore, the present study explores hippocampal dFC in relation to BD symptoms.

METHODS

We assessed hippocampus-based dFC coactivation patterns (CAPs) on resting-state fMRI data of 25 euthymic BD patients and 25 age- and sex-matched healthy controls (HC).

RESULTS

Bilateral hippocampal dFC with somatomotor networks (SMN) was reduced in BD, compared to HC, while at the same time dFC between the left hippocampus and midcingulo-insular salience system (SN) was higher in BD. Correlational analysis between CAPs and clinical scores revealed that dFC between the bilateral hippocampus and the default-like network (DMN) correlated with depression scores in BD. Furthermore, pathological hyperconnectivity between the default mode network (DMN) and SMN and the frontoparietal network (FPN) was modulated by the same depression scores in BD.

CONCLUSIONS

Overall, we observed alterations of large-scale functional brain networks associated with decreased flexibility in cognitive control, salience detection, and emotion processing in BD. Additionally, the present study provides new insights on the neural architecture underlying a self-centered perspective on the environment in BD patients. dFC markers may improve detection, treatment, and follow-up of BD patients and of disabling residual depressive symptoms in particular.

Common and unique alterations of functional connectivity in major depressive disorder and bipolar disorder

OBJECTIVE

Major depressive disorder (MDD) and bipolar disorder (BD) are considered whole-brain disorders with some common clinical and neurobiological features. It is important to investigate neural mechanisms to distinguish between the two disorders. However, few studies have explored the functional dysconnectivity between the two disorders from the whole brain level.

METHODS

In this study, 117 patients with MDD, 65 patients with BD, and 116 healthy controls completed resting-state functional magnetic resonance imaging (R-fMRI) scans. Both edge-based network construction and large-scale network analyses were applied.

RESULTS

Results found that both the BD and MDD groups showed decreased FC in the whole brain network. The shared aberrant network across patients involves the visual network (VN), sensorimotor network (SMN), dorsal attention network (DAN), and ventral attention network (VAN), which is related to the processing of external stimuli. The default mode network (DMN) and the limbic network (LN) abnormalities were only found in patients with MDD. Furthermore, results showed the highest decrease in edges of patients with MDD in between-network FC in SMN-VN, whereas in VAN-VN of patients with BD.

CONCLUSIONS

Our findings indicated that both MDD and BD are extensive abnormal brain network diseases, mainly aberrant in those brain networks correlated to the processing of external stimuli, especially the attention network. Specific altered functional connectivity also was found in MDD and BD groups, respectively. These results may provide possible trait markers to distinguish the two disorders.

Aberrant structural and functional alterations in postpartum depression: a combined voxel-based morphometry and resting-state functional connectivity study

Objectives

Postpartum depression (PPD) is a severe postpartum psychiatric disorder with unclear pathogenesis. Previous neuroimaging studies have reported structural or functional alterations in areas associated with emotion regulation, cognitive disorder, and parenting behaviors of PPD. The primary goal of this investigation was to explore the presence of brain structural alterations and relevant functional changes in PPD patients.

Methods

A total of 28 patients and 30 matched healthy postnatal women (HPW) underwent both three-dimensional T1-weighted magnetic resonance imaging (MRI) and resting-state functional MRI. Structural analysis was performed by voxel-based morphometry (VBM), followed by resting-state functional analysis using a seed-based whole-brain functional connectivity (FC) approach with abnormal gray matter volume (GMV) regions as seed.

Results

Compared with HPW, the PPD patients showed increased GMV in the left dorsolateral prefrontal cortex (DLPFC.L), the right precentral gyrus (PrCG.R), and the orbitofrontal cortex (OFC). In the PPD group, the DLPFC.L showed increased FC with the right anterior cingulate and paracingulate gyri (ACG.R) and the right middle frontal gyrus (MFG.R); the FC between the PrCG.R and the right median cingulate and paracingulate gyri (DCG.R) exhibited enhanced; the OFC showed increased FC with MFG.R and the left inferior occipital gyrus (IOG.L). In PPD, GMV of DLPFC.L was positively correlated with EDPS scores (r = 0.409 p = 0.031), and FC of PrCG.R-DCG.R was positively correlated with EDPS scores (r = 0.483 p = 0.020).

Conclusion

Structural and functional damage of the DLPFC.L and OFC is associated with cognitive disorders and parenting behaviors in PPD, while structural abnormalities of the DLPFC.L and PrCG.R are involved in impaired executive function. The increased GMV of DLPFC.L may be a unique structural pathological mechanism of PPD related to the inability of PPD patients to withstand long-term parenting stress. These findings have important implications for understanding neural mechanisms in PPD.

A review of resting-state fMRI correlations with executive functions and social cognition in bipolar disorder

BACKGROUND

Deficits in executive functions (EF) and social cognition (SC) are often observed in bipolar disorder (BD), leading to a severe impairment in engaging a functional interaction with the others and the surrounding environment. Therefore, in recent years, resting-state functional magnetic resonance imaging (rs-fMRI) studies on BD tried to identify the neural underpinnings of these cognitive domains by exploring the association between the intrinsic functional connectivity (FC) and the scores in clinical scales evaluating these domains.

METHODS

A bibliographic search on PubMed and Scopus of studies evaluating the correlations between rs-fMRI findings and EF and/or SC in BD was conducted until March 2022. Ten studies met the inclusion criteria.

RESULTS

Overall, the results of the reviewed studies showed that BD patients had FC deficits compared to healthy controls (HC) in selective resting-state networks involved in EF and SC, which include the default mode network, especially the link between medial prefrontal cortex and posterior cingulate cortex, and the sensory-motor network. Finally, it also emerged the predominant role of alterations in prefrontal connections in explaining the cognitive deficits in BD patients.

LIMITATIONS

The heterogeneity of the reviewed studies, in terms of cognitive domains explored and neuroimaging acquisitions, limited the comparability of the findings.

CONCLUSIONS

rs-fMRI studies could help deepen the brain network alterations underlying EF and SC deficits in BD, pointing the attention on the neuronal underpinning of cognition, whose knowledge may lead to the development of new neurobiological-based approaches to improve the quality of life of these patients.

Structural and functional MRI correlates of inflammation in bipolar disorder: A systematic review

BACKGROUND

Bipolar disorder (BD) is a common affective disorder characterized by recurrent oscillations between mood states and associated with inflammatory diseases and chronic inflammation. However, data on MRI abnormalities in BD and their relationship with inflammation are heterogeneous and no review has recapitulated them.

METHODS

In this pre-registered (PROSPERO: CRD42022308461) systematic review we searched Web of Science Core Collection and PubMed for articles correlating functional or structural MRI measures with immune-related markers in BD.

RESULTS

We included 23 studies (6 on functional, 16 on structural MRI findings, 1 on both, including 1'233 BD patients). Overall, the quality of the studies included was fair, with a low risk of bias.

LIMITATIONS

Heterogeneity in the methods and results of the studies and small sample sizes limit the generalizability of the conclusions.

CONCLUSIONS

A qualitative synthesis suggests that the links between immune traits and functional or structural MRI alterations point toward brain areas involved in affective and somatomotor processing, with a trend toward a negative correlation between peripheral inflammatory markers and brain regions volume. We discuss how disentangling the complex relationship between the immune system and MRI alterations in BD may unveil mechanisms underlying symptoms pathophysiology, potentially with quickly translatable diagnostic, prognostic, and therapeutic implications.

Altered dynamic amplitude of low-frequency fluctuation between bipolar type I and type II in the depressive state

BACKGROUND

Bipolar disorder is a chronic and highly recurrent mental disorder that can be classified as bipolar type I (BD I) and bipolar type II (BD II). BD II is sometimes taken as a milder form of BD I or even doubted as an independent subtype. However, the fact that symptoms and severity differ in patients with BD I and BD II suggests different pathophysiologies and underlying neurobiological mechanisms. In this study, we aimed to explore the shared and unique functional abnormalities between subtypes.

METHODS

The dynamic amplitude of low-frequency fluctuation (dALFF) was performed to compare 31 patients with BD I, 32 with BD II, and 79 healthy controls (HCs). Global dALFF was calculated using sliding-window analysis. Group differences in dALFF among the 3 groups were compared using analysis of covariance (ANCOVA), with covariates of age, sex, years of education, and mean FD, and Bonferroni correction was applied for post hoc analysis. Pearson and Spearman's correlations were conducted between clusters with significant differences and clinical features in the BD I and BD II groups, after which false error rate (FDR) was used for correction.

RESULTS

We found a significant decrease in dALFF values in BD patients compared with HCs in the following brain regions: the bilateral-side inferior frontal gyrus (including the triangular, orbital, and opercular parts), inferior temporal gyrus, the medial part of the superior frontal gyrus, middle frontal gyrus, anterior cingulum, insula gyrus, lingual gyrus, calcarine gyrus, precuneus gyrus, cuneus gyrus, left-side precentral gyrus, postcentral gyrus, inferior parietal gyrus, superior temporal pole gyrus, middle temporal gyrus, middle occipital gyrus, superior occipital gyrus and right-side fusiform gyrus, parahippocampal gyrus, hippocampus, middle cingulum, orbital part of the medial frontal gyrus and superior frontal gyrus. Unique alterations in BD I were observed in the right-side supramarginal gyrus and postcentral gyrus. In addition, dALFF values in BD II were significantly higher than those in BD I in the right superior temporal gyrus and middle temporal gyrus. The variables of dALFF correlated with clinical characteristics differently according to the subtypes, but no correlations survived after FDR correction.

LIMITATIONS

Our study was cross-sectional. Most of our patients were on medication, and the sample was limited.

CONCLUSIONS

Our findings demonstrated neurobiological characteristics of BD subtypes, providing evidence for BD II as an independent existence, which could be the underlying explanation for the specific symptoms and/or severity and point to potential biomarkers for the differential diagnosis of bipolar subtypes.