Abnormal degree centrality in Alzheimer's disease patients with depression: A resting-state functional magnetic resonance imaging study

Degree centrality-based resting-state functional magnetic resonance imaging explores central mechanisms in lumbar disc herniation patients with chronic low back pain

Objective

To investigate the central mechanism of lumbar disc herniation in patients with chronic low back pain (LDHCP) using resting-state functional magnetic resonance imaging (rs-fMRI) utilizing the Degree Centrality (DC) method.

Methods

Twenty-five LDHCP and twenty-two healthy controls (HCs) were enrolled, and rs-fMRI data from their brains were collected. We compared whole-brain DC values between the LDHCP and HC groups, and examined correlations between DC values within the LDHCP group and the Visual Analogue Score (VAS), Oswestry Dysfunction Index (ODI), and disease duration. Diagnostic efficacy was evaluated using receiver operating characteristic (ROC) curve analysis.

Results

LDHCP patients exhibited increased DC values in the bilateral cerebellum and brainstem, whereas decreased DC values were noted in the left middle temporal gyrus and right post-central gyrus when compared with HCs. The DC values of the left middle temporal gyrus were positively correlated with VAS (r = 0.416, p = 0.039) and ODI (r = 0.405, p = 0.045), whereas there was no correlation with disease duration (p > 0.05). Other brain regions showed no significant correlations with VAS, ODI, or disease duration (p > 0.05). Furthermore, the results obtained from ROC curve analysis demonstrated that the Area Under the Curve (AUC) for the left middle temporal gyrus was 0.929.

Conclusion

The findings indicated local abnormalities in spontaneous neural activity and functional connectivity in the bilateral cerebellum, bilateral brainstem, left middle temporal gyrus, and right postcentral gyrus among LDHCP patients.

Altered brain network centrality in patients with orbital fracture: A resting‑state functional MRI study

The present study aimed to investigate potential functional network brain-activity abnormalities in individuals with orbital fracture (OF) using the voxel-wise degree centrality (DC) technique. The present study included 20 patients with OF (12 males and 8 females) and 20 healthy controls (HC; 12 males and 8 females), who were matched for gender, age and educational attainment. Functional magnetic resonance imaging (fMRI) in the resting state has been widely applied in several fields. Receiver operating characteristic (ROC) curves were calculated to distinguish between patients with OF and HCs. In addition, correlation analyses were performed between behavioral performance and average DC values in various locations. The DC technique was used to assess unprompted brain activity. Right cerebellum 9 region (Cerebelum_9_R) and left cerebellar peduncle 2 area (Cerebelum_Crus2_L) DC values of patients with OF were increased compared with those in HCs. Cerebelum_9_R and Cerebelum_Crus2_L had area under the ROC curve values of 0.983 and 1.000, respectively. Patients with OF appear to have several brain regions that exhibited aberrant brain network characteristics, which raises the possibility of neuropathic causes and offers novel therapeutic options.

Relapse risk revealed by degree centrality and cluster analysis in heroin addicts undergoing methadone maintenance treatment

BACKGROUND

Based on hubs of neural circuits associated with addiction and their degree centrality (DC), this study aimed to construct the addiction-related brain networks for patients diagnosed with heroin dependence undertaking stable methadone maintenance treatment (MMT) and further prospectively identify the ones at high risk for relapse with cluster analysis.

METHODS

Sixty-two male MMT patients and 30 matched healthy controls (HC) underwent brain resting-state functional MRI data acquisition. The patients received 26-month follow-up for the monthly illegal-drug-use information. Ten addiction-related hubs were chosen to construct a user-defined network for the patients. Then the networks were discriminated with K-means-clustering-algorithm into different groups and followed by comparative analysis to the groups and HC. Regression analysis was used to investigate the brain regions significantly contributed to relapse.

RESULTS

Sixty MMT patients were classified into two groups according to their brain-network patterns calculated by the best clustering-number-K. The two groups had no difference in the demographic, psychological indicators and clinical information except relapse rate and total heroin consumption. The group with high-relapse had a wider range of DC changes in the cortical-striatal-thalamic circuit relative to HC and a reduced DC in the mesocorticolimbic circuit relative to the low-relapse group. DC activity in NAc, vACC, hippocampus and amygdala were closely related with relapse.

CONCLUSION

MMT patients can be identified and classified into two subgroups with significantly different relapse rates by defining distinct brain-network patterns even if we are blind to their relapse outcomes in advance. This may provide a new strategy to optimize MMT.

Multimodality neuroimaging in vascular mild cognitive impairment: A narrative review of current evidence

The vascular mild cognitive impairment (VaMCI) is generally accepted as the premonition stage of vascular dementia (VaD). However, most studies are focused mainly on VaD as a diagnosis in patients, thus neglecting the VaMCI stage. VaMCI stage, though, is easily diagnosed by vascular injuries and represents a high-risk period for the future decline of patients’ cognitive functions. The existing studies in China and abroad have found that magnetic resonance imaging technology can provide imaging markers related to the occurrence and development of VaMCI, which is an important tool for detecting the changes in microstructure and function of VaMCI patients. Nevertheless, most of the existing studies evaluate the information of a single modal image. Due to the different imaging principles, the data provided by a single modal image are limited. In contrast, multi-modal magnetic resonance imaging research can provide multiple comprehensive data such as tissue anatomy and function. Here, a narrative review of published articles on multimodality neuroimaging in VaMCI diagnosis was conducted，and the utilization of certain neuroimaging bio-markers in clinical applications was narrated. These markers include evaluation of vascular dysfunction before tissue damages and quantification of the extent of network connectivity disruption. We further provide recommendations for early detection, progress, prompt treatment response of VaMCI, as well as optimization of the personalized treatment plan.

The Characteristics of Entorhinal Cortex Functional Connectivity in Alzheimer's Disease Patients with Depression

BACKGROUND

Depression is one of the most common neuropsychiatric symptoms of Alzheimer's disease (AD) which decreases the life quality of both patients and caregivers. There are currently no effective drugs. It is therefore important to explore the pathogenesis of depression in AD patients.

OBJECTIVE

The present study aimed to investigate the characteristics of the entorhinal cortex (EC) functional connectivity (FC) in the whole brain neural network of AD patients with depression (D-AD).

METHODS

Twenty-four D-AD patients, 14 AD patients without depression (nD-AD), and 20 healthy controls underwent resting-state functional magnetic resonance imaging. We set the EC as the seed and used FC analysis. One-way analysis of variance was used to examine FC differences among the three groups.

RESULTS

Using the left EC as the seed point, there were FC differences among the three groups in the left EC-inferior occipital gyrus. Using the right EC as the seed point, there were FC differences among the three groups in the right EC-middle frontal gyrus, -superior parietal gyrus, -superior medial frontal gyrus, and -precentral gyrus. Compared with the nD-AD group, the D-AD group had increased FC between the right EC and right postcentral gyrus.

CONCLUSION

Asymmetry of FC in the EC and increased FC between the EC and right postcentral gyrus may be important in the pathogenesis of depression in AD.

Connectomic disturbances in Duchenne muscular dystrophy with mild cognitive impairment

Duchenne muscular dystrophy (DMD) is frequently associated with mild cognitive deficits. However, the underlying disrupted brain connectome and the neural basis remain unclear. In our current study, 38 first-episode, treatment-naive patients with DMD and 22 matched healthy controls (HC) were enrolled and received resting-sate functional magnetic resonance imaging scans. Voxel-based degree centrality (DC), seed-based functional connectivity (FC), and clinical correlation were performed. Relative to HC, DMD patients had lower height, full Intellectual Quotients (IQ), and IQ-verbal comprehension. Significant increment of DC of DMD patients were found in the left dorsolateral prefrontal cortex (DLPFC.L) and right dorsomedial prefrontal cortex (DMPFC.R), while decreased DC were found in right cerebellum posterior lobe (CPL.R), right precentral/postcentral gyrus (Pre/Postcentral G.R). DMD patients had stronger FC in CPL.R-bilateral lingual gyrus, Pre/Postcentral G.R-Insular, and DMPFC.R-Precuneus.R, had attenuated FC in DLPFC.L-Insular. These abnormally functional couplings were closely associated with the extent of cognitive impairment, suggested an over-activation of default mode network and executive control network, and a suppression of primary sensorimotor cortex and cerebellum-visual circuit. The findings collectively suggest the distributed brain connectome disturbances maybe a neuroimaging biomarker in DMD patients with mild cognitive impairment.

Alterations of degree centrality and functional connectivity in classic trigeminal neuralgia

Objectives

Recent neuroimaging studies have indicated a wide range of structural and regional functional alterations in patients with classic trigeminal neuralgia (CTN). However, few studies have focused on the intrinsic functional characteristics of network organization in the whole brain. Therefore, the present study aimed to characterize the potential intrinsic dysconnectivity pattern of the whole brain functional networks at the voxel level using the degree centrality (DC) analysis in CTN patients.

Methods

Thirty-four patients with CTN and twenty-nine well-matched healthy controls (HCs) participated in this study. All subjects underwent resting-state functional magnetic resonance imaging (rs-MRI) examination and clinical and neuropsychologic assessments. DC is a graph theory-based measurement that represents the overall functional connectivity (FC) numbers between one voxel and other brain voxels. We first investigated brain regions exhibiting abnormal DC, and further identified their perturbation on FC with other brain regions using a seed-based FC analysis in patients with CTN. In addition, correlation analyses were performed to evaluate the relationship between the abnormal DC value and clinical variables in CTN patients.

Results

Compared with the HCs, the patients with CTN exhibited significantly greater DC values in the right pallidum and right putamen, and lower DC values in the right lingual gyrus, right calcarine sulcus, left paracentral lobule, and left midcingulate cortex. A further seed-based FC analysis revealed that the right lingual gyrus showed decreased FC within the visual network and with other core brain networks, including the sensorimotor network, default mode network, and salience network, relative to HCs. Additionally, the left midcingulate cortex exhibited decreased FC within the middle cingulate cortex and the visual network in CTN patients. Moreover, the DC value in the left midcingulate cortex was negatively correlated with the illness duration.

Conclusion

The present study shows that CTN patients exhibited specific functional connectivity network alterations in the basal ganglia, visual network, and salience network, which may reflect the aberrant neural network communication in pain processing and modulation. These findings may provide novel insight for understanding the mechanisms of pain chronicity in CTN patients.

Aberrant degree centrality of functional brain networks in subclinical depression and major depressive disorder

BACKGROUND

As one of the most common diseases, major depressive disorder (MDD) has a significant adverse impact on the li of patients. As a mild form of depression, subclinical depression (SD) serves as an indicator of progression to MDD. This study analyzed the degree centrality (DC) for MDD, SD, and healthy control (HC) groups and identified the brain regions with DC alterations.

METHODS

The experimental data were composed of resting-state functional magnetic resonance imaging (rs-fMRI) from 40 HCs, 40 MDD subjects, and 34 SD subjects. After conducting a one-way analysis of variance, two-sample t-tests were used for further analysis to explore the brain regions with changed DC. Receiver operating characteristic (ROC) curve analysis of single index and composite index features was performed to analyze the distinguishable ability of important brain regions.

RESULTS

For the comparison of MDD vs. HC, increased DC was found in the right superior temporal gyrus (STG) and right inferior parietal lobule (IPL) in the MDD group. For SD vs. HC, the SD group showed a higher DC in the right STG and the right middle temporal gyrus (MTG), and a smaller DC in the left IPL. For MDD vs. SD, increased DC in the right middle frontal gyrus (MFG), right IPL, and left IPL, and decreased DC in the right STG and right MTG was found in the MDD group. With an area under the ROC (AUC) of 0.779, the right STG could differentiate MDD patients from HCs and, with an AUC of 0.704, the right MTG could differentiate MDD patients from SD patients. The three composite indexes had good discriminative ability in each pairwise comparison, with AUCs of 0.803, 0.751, and 0.814 for MDD vs. HC, SD vs. HC, and MDD vs. SD, respectively.

CONCLUSION

Altered DC in the STG, MTG, IPL, and MFG were identified in depression groups. The DC values of these altered regions and their combinations presented good discriminative ability between HC, SD, and MDD. These findings could help to find effective biomarkers and reveal the potential mechanisms of depression.

Disrupted topological organization of functional brain networks in Alzheimer's disease patients with depressive symptoms

BACKGROUND

Depression is a common symptom of Alzheimer's disease (AD), but the underlying neural mechanism is unknown. The aim of this study was to explore the topological properties of AD patients with depressive symptoms (D-AD) using graph theoretical analysis.

METHODS

We obtained 3-Tesla rsfMRI data from 24 D-AD patients, 20 non-depressed AD patients (nD-AD), and 20 normal controls (NC). Resting state networks were identified using graph theory analysis. ANOVA with a two-sample t-test post hoc analysis in GRETNA was used to assess the topological measurements.

RESULTS

Our results demonstrate that the three groups show characteristic properties of a small-world network. NCs showed significantly larger global and local efficiency than D-AD and nD-AD patients. Compared with nD-AD patients, D-AD patients showed decreased nodal centrality in the pallidum, putamen, and right superior temporal gyrus. They also showed increased nodal centrality in the right superior parietal gyrus, the medial orbital portion of the right superior frontal gyrus, and the orbital portion of the right superior frontal gyrus. Compared with nD-AD patients, NC showed decreased nodal betweenness in the right superior temporal gyrus, and increased nodal betweenness in medial orbital part of the right superior frontal gyrus.

CONCLUSIONS

These results indicate that D-AD is associated with alterations of topological structure. Our study provides new insights into the brain mechanisms underlying D-AD.

Separation of memory span and learning rate: Evidence from behavior and spontaneous brain activity in older adults

It is unclear how the ability to initially acquire information in a first learning trial relates to learning rate in subsequent repeated trials. The separation of memory span and learning rate is an important psychological dilemma that remains unaddressed. Given the potential effects of aging on memory and learning, this study investigated the separation of memory span and learning rate from behavior and spontaneous brain activity in older adults. We enrolled a total of 758 participants, including 707 healthy older adults and 51 mild cognitive impairment (MCI) patients. Sixty-five participants out of 707 completed resting-state functional magnetic resonance imaging (fMRI) scanning. Behaviorally, memory span and learning rate were not correlated with each other in the paired-associative learning test (PALT) but were negatively correlated in the auditory verbal learning test (AVLT). This indicated that the relationship between memory span and learning rate for item memory might be differentially affected by aging. Interaction analysis confirmed that these two capacities were differentially affected by test type (associative memory vs. item memory). Additionally, at three progressive brain activity indexes (ALFF, ReHo, and DC), the right brain regions (right inferior temporal gyrus and right middle frontal gyrus) were more negatively correlated with memory span, whereas, the left precuneus was more positively correlated with learning rate. Regarding pathological aging, none of the correlations between memory span and learning rate were significant in either PALT or AVLT in MCI. This study provides novel evidence for the dissociation of memory span and learning rate at behavioral and brain activity levels, which may have useful applications in detecting cognitive deficits or conducting cognitive interventions.

Changes in Degree Centrality and Functional Connectivity after the First Cycle of Neoadjuvant Chemotherapy in Newly Diagnosed Breast Cancer: A Longitudinal Study

Purpose

To evaluate the longitudinal changes of brain degree centrality (DC) and functional connectivity (FC) in breast cancer patients after the first cycle of neoadjuvant chemotherapy (NAC).

Methods

Thirty-five breast cancer patients were included in the NAC group. Resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychological test were performed at baseline before NAC (time point 0, TP0) and after the first cycle of NAC (time point 1, TP1). The healthy controls (HC) included 30 healthy subjects and received the same rs-fMRI scan and neuropsychological test as the above-mentioned NAC group at one time point. DC and FC analyses were conducted to assess brain connectivity of all participants. Receiver operating characteristic (ROC) curve was used to assess the ability of DC and FC in distinguishing patients before and after chemotherapy.

Results

In the NAC group, the Self-Rating Anxiety Scale scores decreased significantly over time. At TP0 and TP1, the Digital Span Test forward score of the NAC group was significantly lower than that of the HC group. In the NAC group, DC in the right middle frontal gyrus and left precentral gyrus/middle frontal gyrus decreased significantly at TP1, and FC between the left precentral gyrus/middle frontal gyrus and bilateral precuneus was significantly reduced at TP1. Through ROC analysis, we found that the area under the curve (AUC) of DC, FC, and the combined model in distinguishing patients in TP0 or TP1 was 0.7886, 0.7665, and 0.8278, respectively.

Conclusions

Brain connectivity, involving executive and motor function related brain areas, changes in the short term after NAC treatment in breast cancer patients.

Resting-state functional connectivity alteration in elderly patients with knee osteoarthritis and declined cognition: An observational study

OBJECTIVE

This study is designed to investigate the brain function changed regions in elderly patients with knee osteoarthritis (KOA) and to explore the relationship between neuropsychological tests and resting-state functional magnetic resonance imaging (rs-fMRI) network to clarify the possible mechanism underlying cognitive changes in KOA patients.

MATERIALS AND METHODS

Fifty-two patients aged ≥ 65 with KOA and twenty-two healthy-matched controls were recruited in this study. All participants were given rs-fMRI check. We used graph theory analysis to characterize functional connectivity (FC) and topological organization of the brain structural network. The relationship between FC values, topological properties, and the neuropsychological test scores was analyzed.

RESULTS

Compared with the controls, fourteen edges with lower functional connectivity were noted in the KOA group. Local efficiency and small-worldness of KOA patients decreased compared to the healthy controls. No significant alterations of nodal topological properties were found between the two groups. There was a significant positive correlation between the AVLT-H (L) and the internetwork of default mode network (DMN) (left/right orbitofrontal Superior cortex) and limbic/cortical areas (left/right caudate, right amygdala). AVLT-H(L) was positively correlated with small-worldness and local efficiency.

CONCLUSION

The results indicated that for elderly KOA patients with declined cognition, topological properties, FC between DMN and subcortical limbic network related regions are significantly decreased compared to healthy controls. These alterations demonstrated a significant correlation with the neuropsychological test scores.

Global Network Analysis of Alzheimer’s Disease with Minimum Spanning Trees

Background: A minimum spanning tree (MST) is a unique efficient network comprising the necessary connections needed to connect all regions in a network while retaining the lowest possible cost of connection weight. Objective: This study aimed to utilize functional near-infrared spectroscopy (fNIRS) to analyze brain activity in different regions and then construct MST-based regions to characterize the brain topologies of participants with Alzheimer’s disease (AD), mild cognitive impairment (MCI), and normal controls (NC). Methods: A 46 channel fNIRS setup was used on all participants, with correlation being calculated for each channel pair. An MST was constructed from the resulting correlation matrix, from which graph theory measures were calculated. The average number of connections within a lobe in the left versus right hemisphere was calculated to identify which lobes displayed and abnormal amount of connectivity. Results: Compared to those in the MCI group, the AD group showed a less integrated network structure, with a higher characteristic path length, but lower leaf fraction, maximum degree, and degree divergence. The AD group also showed a higher number of connections in the frontal lobe within the left hemisphere and a lower number between hemispheric frontal lobes as compared to MCI. Conclusion: These results indicate a deviation in network structure and connectivity within patient groups that is consistent with the theory of dysconnectivity for AD. Additionally, the AD group showed strong correlations between the Hamilton depression rating scale and different graph metrics, suggesting a link between network organization and the recurrence of depression in AD.

Effects of animal-assisted therapy on patients with dementia: A systematic review and meta-analysis of randomized controlled trials

The purpose of this meta-analysis is to systematically examine the efficacy of animal-assisted therapy (AAT) for patients with dementia. PubMed, Embase, and Cochrane libraries were searched till November 2021 to collect studies in relation to AAT that had been adopted in patients with dementia. Eleven randomized controlled trials (RCTs) involving 825 participants were included. Compared with the control group, the AAT group showed a significant reduction in behavioral and psychological symptoms of dementia (BPSD), especially depression. However, no significant improvement was found in cognitive function, activities of daily living, agitation, or the quality of life. This meta-analysis shows that AAT can effectively reduce BPSD in patients with dementia.

Abnormal Voxel-Based Degree Centrality in Patients With Postpartum Depression: A Resting-State Functional Magnetic Resonance Imaging Study

Postpartum depression (PPD) is a major public health concern with significant consequences for mothers, their children, and their families. However, less is known about its underlying neuropathological mechanisms. The voxel-based degree centrality (DC) analysis approach provides a new perspective for exploring the intrinsic dysconnectivity pattern of whole-brain functional networks of PPD. Twenty-nine patients with PPD and thirty healthy postpartum women were enrolled and received resting-state functional magnetic resonance imaging (fMRI) scans in the fourth week after delivery. DC image, clinical symptom correlation, and seed-based functional connectivity (FC) analyses were performed to reveal the abnormalities of the whole-brain functional network in PPD. Compared with healthy controls (HCs), patients with PPD exhibited significantly increased DC in the right hippocampus (HIP.R) and left inferior frontal orbital gyrus (ORBinf.L). The receiver operating characteristic (ROC) curve analysis showed that the area under the curve (AUC) of the above two brain regions is all over 0.7. In the seed-based FC analyses, the PPD showed significantly decreased FC between the HIP.R and right middle frontal gyrus (MFG.R), between the HIP.R and left median cingulate and paracingulate gyri (DCG.L), and between the ORBinf.L and the left fusiform (FFG.L) compared with HCs. The PPD showed significantly increased FC between the ORBinf.L and the right superior frontal gyrus, medial (SFGmed.R) compared with HCs. Mean FC between the HIP.R and DCG.L positively correlated with EDPS scores in the PPD group. This study provided evidence of aberrant DC and FC within brain regions in patients with PPD, which was associated with the default mode network (DMN) and limbic system (LIN). Identification of these above-altered brain areas may help physicians to better understand neural circuitry dysfunction in PPD.

State and Trait Anxiety Share Common Network Topological Mechanisms of Human Brain

Anxiety is a future-oriented unpleasant and negative mental state induced by distant and potential threats. It could be subdivided into momentary state anxiety and stable trait anxiety, which play a complex and combined role in our mental and physical health. However, no studies have systematically investigated whether these two different dimensions of anxiety share a common or distinct topological mechanism of human brain network. In this study, we used macroscale human brain morphological similarity network and functional connectivity network as well as their spatial and temporal variations to explore the topological properties of state and trait anxiety. Our results showed that state and trait anxiety were both negatively correlated with the coefficient of variation of nodal efficiency in the left frontal eyes field of volume network; state and trait anxiety were both positively correlated with the median and mode of pagerank centrality distribution in the right insula for both static and dynamic functional networks. In summary, our study confirmed that state and trait anxiety shared common human brain network topological mechanisms in the insula and the frontal eyes field, which were involved in preliminary cognitive processing stage of anxiety. Our study also demonstrated that the common brain network topological mechanisms had high spatiotemporal robustness and would enhance our understanding of human brain temporal and spatial organization.

Classification of early-MCI patients from healthy controls using evolutionary optimization of graph measures of resting-state fMRI, for the Alzheimer's disease neuroimaging initiative

Identifying individuals with early mild cognitive impairment (EMCI) can be an effective strategy for early diagnosis and delay the progression of Alzheimer's disease (AD). Many approaches have been devised to discriminate those with EMCI from healthy control (HC) individuals. Selection of the most effective parameters has been one of the challenging aspects of these approaches. In this study we suggest an optimization method based on five evolutionary algorithms that can be used in optimization of neuroimaging data with a large number of parameters. Resting-state functional magnetic resonance imaging (rs-fMRI) measures, which measure functional connectivity, have been shown to be useful in prediction of cognitive decline. Analysis of functional connectivity data using graph measures is a common practice that results in a great number of parameters. Using graph measures we calculated 1155 parameters from the functional connectivity data of HC (n = 72) and EMCI (n = 68) extracted from the publicly available database of the Alzheimer's disease neuroimaging initiative database (ADNI). These parameters were fed into the evolutionary algorithms to select a subset of parameters for classification of the data into two categories of EMCI and HC using a two-layer artificial neural network. All algorithms achieved classification accuracy of 94.55%, which is extremely high considering single-modality input and low number of data participants. These results highlight potential application of rs-fMRI and efficiency of such optimization methods in classification of images into HC and EMCI. This is of particular importance considering that MRI images of EMCI individuals cannot be easily identified by experts.

Integrating Chronic Obstructive Pulmonary Disease Treatment With 8-Week Tai Chi Chuan Practice: An Exploration of Mind-Body Intervention and Neural Mechanism

Objective

This study aims to explore the effect of integrating routine treatment with Tai Chi Chuan (TCC) intervention on the clinical symptom of patients with Chronic Obstructive Pulmonary Disease (COPD) from clinical and neurological perspectives.

Methods

Twenty patients with COPD were recruited for regular treatment combined with 8-week TCC rehabilitative practice. Clinical symptoms were evaluated by Chronic Obstructive Pulmonary Symptom Assessment Scale (CAT) and Modified Dyspnea Scale (mMRC) at baseline and after treatment. Resting-state MRI scan was also performed with multiline T2-weighted echo-planar imaging (EPI) to acquire their functional images before and after the treatment. TCC rehabilitation involved a total of 8 weeks of practice with 90 min per session, three times a week.

Results

After an 8-week integration routine treatment with TCC practice, the patient’s clinical symptoms improved significantly. Imaging analysis showed that COPD patients exhibited decreased Degree of Centrality (DC) in the right inferior frontal gyrus (IFG), right middle frontal gyrus, bilateral cingulate cortex, bilateral precuneus, and right precentral gyrus. Moreover, correlation analysis found that the decreased DC in the right IFG was positively correlated with the CAT improvements.

Conclusion

The routine treatment involving TCC rehabilitation practice could improve the clinical symptoms of patients with COPD. The right IFG might be a key brain region to contribute to the neural mechanism underlying integrative intervention on the clinical symptoms in COPD. These findings provide neurological evidence for treating COPD rehabilitation practice with mind-body practice based on Chinese culture to some extent, which also advances the understanding of the efficacy of TCC as the adjuvant technology from a neuroscience perspective.

Clinical Trial Registration:

[http://www.chictr.org.cn/showproj.aspx?proj=45189], identifier [ChiCTR1900028335].

Detecting Biomarkers of Alzheimer's Disease Based on Multi-constrained Uncertainty-Aware Adaptive Sparse Multi-view Canonical Correlation Analysis

Image genetics mainly explores the pathogenesis of Alzheimer's disease (AD) by studying the relationship between genetic data (such as SNP, gene expression data, and DNA methylation) and imaging data (such as structural MRI (sMRI), fMRI, and PET). Most of the existing research on brain imaging genomics uses two-way or three-way bi-multivariate methods to explore the correlation analysis between genes and brain imaging. However, many of these methods are still affected by the gradient domination or cannot take into account the effect of feature redundancy on the results, so that the typical correlation coefficient and program running speed are not significantly improved. In order to solve the above problems, this paper proposes a multi-constrained uncertainty-aware adaptive sparse multi-view canonical correlation analysis method (MC-unAdaSMCCA) to explore associations among SNPs, gene expression data, and sMRI; that is, based on traditional unAdaSMCCA, orthogonal constraints are imposed on the weights of the three data features through linear programming, which can reduce the redundancy of feature weights to improve the correlation between the data and reduce the complexity of the algorithm to significantly speed up the running speed of the program. Three adaptive sparse multi-view canonical correlation analysis methods are used as benchmarks to evaluate the difference between real neuroimaging data and synthetic data. Compared with the other three methods, our proposed method has obtained better or comparable typical correlation coefficients and typical weights. Moreover, the following experimental results show that the MC-unAdaSMCCA method cannot only identify biomarkers related to AD and mild cognitive impairment (MCI), but also has a strong ability to resist noise and process high-dimensional data. Therefore, our proposed method provides a reliable approach to multi-modal imaging genetic researches.

Graphlet eigencentralities capture novel central roles of genes in pathways

MOTIVATION

Graphlet adjacency extends regular node adjacency in a network by considering a pair of nodes being adjacent if they participate in a given graphlet (small, connected, induced subgraph). Graphlet adjacencies captured by different graphlets were shown to contain complementary biological functions and cancer mechanisms. To further investigate the relationships between the topological features of genes participating in molecular networks, as captured by graphlet adjacencies, and their biological functions, we build more descriptive pathway-based approaches.

CONTRIBUTION

We introduce a new graphlet-based definition of eigencentrality of genes in a pathway, graphlet eigencentrality, to identify pathways and cancer mechanisms described by a given graphlet adjacency. We compute the centrality of genes in a pathway either from the local perspective of the pathway or from the global perspective of the entire network.

RESULTS

We show that in molecular networks of human and yeast, different local graphlet adjacencies describe different pathways (i.e., all the genes that are functionally important in a pathway are also considered topologically important by their local graphlet eigencentrality). Pathways described by the same graphlet adjacency are functionally similar, suggesting that each graphlet adjacency captures different pathway topology and function relationships. Additionally, we show that different graphlet eigencentralities describe different cancer driver genes that play central roles in pathways, or in the crosstalk between them (i.e. we can predict cancer driver genes participating in a pathway by their local or global graphlet eigencentrality). This result suggests that by considering different graphlet eigencentralities, we can capture different functional roles of genes in and between pathways.

Functional connectome of arousal and motor brainstem nuclei in living humans by 7 Tesla resting-state fMRI

Brainstem nuclei play a pivotal role in many functions, such as arousal and motor control. Nevertheless, the connectivity of arousal and motor brainstem nuclei is understudied in living humans due to the limited sensitivity and spatial resolution of conventional imaging, and to the lack of atlases of these deep tiny regions of the brain. For a holistic comprehension of sleep, arousal and associated motor processes, we investigated in 20 healthy subjects the resting-state functional connectivity of 18 arousal and motor brainstem nuclei in living humans. To do so, we used high spatial-resolution 7 Tesla resting-state fMRI, as well as a recently developed in-vivo probabilistic atlas of these nuclei in stereotactic space. Further, we verified the translatability of our brainstem connectome approach to conventional (e.g. 3 Tesla) fMRI. Arousal brainstem nuclei displayed high interconnectivity, as well as connectivity to the thalamus, hypothalamus, basal forebrain and frontal cortex, in line with animal studies and as expected for arousal regions. Motor brainstem nuclei showed expected connectivity to the cerebellum, basal ganglia and motor cortex, as well as high interconnectivity. Comparison of 3 Tesla to 7 Tesla connectivity results indicated good translatability of our brainstem connectome approach to conventional fMRI, especially for cortical and subcortical (non-brainstem) targets and to a lesser extent for brainstem targets. The functional connectome of 18 arousal and motor brainstem nuclei with the rest of the brain might provide a better understanding of arousal, sleep and accompanying motor function in living humans in health and disease.

The alterations of degree centrality in the frontal lobe of patients with panic disorder

Objective: The brain network in panic disorder (PD) is still an intriguing issue for research. In this study, we hoped to investigate the role of DC (degree centrality) for the pathophysiology of PD, especially for the fear network. Methods: We enrolled 60 patients with PD and 60 controls in the current study. The gender and age were matched for two groups. All participants received the resting-state functional magnetic resonance imaging to survey the baseline brain activity. Then the DC values of all participants were using REST toolbox. We also compared the DC values between PD and controls. The statistical threshold was set as FDR (false discovery rate) < 0.05. Results: The DC values were significantly lower in the right superior frontal gyrus of PD patients compared to controls (FDR < 0.05). In addition, a negative correlation between the DC values and panic severity was observed in the right superior frontal gyrus and left inferior frontal gyrus. However, there was no significant association between the DC values and illness duration. Conclusion: The DC seemed significantly altered in the frontal lobe of PD patients. The role of the frontal lobe might be more emphasized in the pathophysiology research for PD.

Effects of animal-assisted interventions for people with dementia: A systematic review and meta-analysis

Animal-assisted interventions (AAIs) are non-pharmacological, cost-effective interventions developed to improve outcomes in patients with dementia; however, the effects remain inconclusive. The purpose of this study was to analyze the efficacy of AAIs for people with dementia. A systematic review and meta-analysis was performed of English-language literature published from January 1, 2001, to July 3,2021, and indexed in the following databases: CINAHL, EMBASE, MEDLINE, PubMed, Web of Science, Cochrane, and PsycINFO. Intervention groups were people with dementia who received AAIs. Study quality was assessed using the Joanna Briggs Institute tool. Among 10 included studies, significant differences in depression levels were identified between the intervention and control groups (p < 0.001). No significant differences in cognitive function, neuropsychiatric syndrome, or independence in activities of daily living were observed between groups. Future research remains necessary to examine the effects of AAIs on depression during different stages of dementia. AAIs therapists may collaborate with healthcare workers to improve AAIs benefits.

Brain controllability distinctiveness between depression and cognitive impairment

Alzheimer's disease (AD) is a progressive form of dementia marked by cognitive and memory deficits, estimated to affect ∼5.7 million Americans and account for ∼$277 billion in medical costs in 2018. Depression is one of the most common neuropsychiatric disorders that accompanies AD, appearing in up to 50% of patients. AD and Depression commonly occur together with overlapped symptoms (depressed mood, anxiety, apathy, and cognitive deficits.) and pose diagnostic challenges early in the clinical presentation. Understanding their relationship is critical for advancing treatment strategies, but the interaction remains poorly studied and thus often leads to a rapid decline in functioning. Modern systems and control theory offer a wealth of novel methods and concepts to assess the important property of a complex control system, such as the brain. In particular, the brain controllability analysis captures the ability to guide the brain behavior from an initial state (healthy or diseased) to a desired state in finite time, with suitable choice of inputs such as external or internal stimuli. The controllability property of the brain's dynamic processes will advance our understanding of the emergence and progression of brain diseases and thus helpful in the early diagnosis and novel treatment approaches. This study aims to assess the brain controllability differences between mild cognitive impairment (MCI), as prodromal AD, and Depression. This study used diffusion tensor imaging (DTI) data from 60 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI): 15 cognitively normal subjects and 45 patients with MCI, including 15 early MCI (EMCI) patients without depression, 15 EMCI patients with mild depression (EMCID), and 15 late MCI (LMCI) patients without depression. The structural brain network was firstly constructed and the brain controllability was characterized for each participant. The controllability of default mode network (DMN) and its sub-regions were then compared across groups in a structural basis. Results indicated that the brain average controllability of DMN in EMCI, LMCI, and EMCID were significantly decreased compared to healthy subjects (P < 0.05). The EMCI and LMCI groups also showed significantly greater average controllability of DMN versus the EMCID group. Furthermore, compared to healthy subjects, the regional controllability of the left/right superior prefrontal cortex and the left/right cingulate gyrus in the EMCID group showed a significant decrease (P < 0.01). Among these regions, the left superior prefrontal region's controllability was significantly decreased (P < 0.05) in the EMCID group compared with EMCI and LMCI groups. Our results provide a new perspective in understanding depressive symptoms in MCI patients and provide potential biomarkers for diagnosing depression from MCI and AD.

Altered Functional Connectivity Strength at Rest in Medication-Free Obsessive-Compulsive Disorder

Background

Previous studies explored the whole-brain functional connectome using the degree approach in patients with obsessive-compulsive disorder (OCD). However, whether the altered degree values can be used to discriminate OCD from healthy controls (HCs) remains unclear.

Methods

A total of 40 medication-free patients with OCD and 38 HCs underwent a resting-state functional magnetic resonance imaging (rs-fMRI) scan. Data were analyzed with the degree approach and a support vector machine (SVM) classifier.

Results

Patients with OCD showed increased degree values in the left thalamus and left cerebellum Crus I and decreased degree values in the left dorsolateral prefrontal cortex, right precuneus, and left postcentral gyrus. SVM classification analysis indicated that the increased degree value in the left thalamus is a marker of OCD, with an acceptable accuracy of 88.46%, sensitivity of 87.50%, and specificity of 89.47%.

Conclusion

Altered degree values within and outside the cortical-striatal-thalamic-cortical (CSTC) circuit may cocontribute to the pathophysiology of OCD. Increased degree values of the left thalamus can be used as a future marker for OCD understanding-classification.

Brain Functional Connectivity Changes in Patients with Acute Eye Pain: A Resting-State Functional Magnetic Resonance Imaging (fMRI) Study

Background

By using functional magnetic resonance imaging (fMRI), we aimed to study the changes in potential brain function network activity in patients with acute eye pain. Also, by using the voxel-wise degree centrality (DC) method, we aimed to explore the relationship between spontaneous brain activity and the clinical features of patients with acute eye pain.

Material/Methods

A total of 15 patients with acute eye pain (5 women and 10 men; EP group) and 15 healthy controls (5 women and 10 men; HC group), were scanned by fMRI. The DC method was used to evaluate changes in spontaneous brain activity. Receiver operating characteristic (ROC) curves were analyzed, and Pearson correlation analysis was used to study the relationship between DC values and clinical manifestations in different regions of brain.

Results

The area of the left limbic lobe showed a reduction in DC value in patients in the EP group. DC values were elevated in the left cerebellum posterior lobe, left inferior parietal lobule, left inferior temporal gyrus, left precuneus, and right cerebellum posterior lobe in the EP group. The visual analog scale value of the eyes in the EP group was negatively correlated with the left limbic lobe signal value and positively correlated with the left inferior parietal lobule signal value. Further, the scores of the hospital anxiety and depression scale and DC value of the left limbic lobe were negatively correlated.

Conclusions

Compared with the HC group, patients with acute eye pain had abnormal patterns of intrinsic brain activity in different brain regions, which may help reveal the potential neural mechanisms involved in eye pain.

Abnormal degree centrality in lifelong premature ejaculation patients: an fMRI study

Lifelong premature ejaculation (PE) is one of the most prevalent male sexual dysfunctions. It is still not well known about the possible neural mechanisms of lifelong PE. This study tried to investigate the abnormal characteristics of brain functional networks of lifelong PE and to assess relationships of PE-related functional abnormalities with clinical symptoms. Functional magnetic resonance imaging (fMRI) data and clinical symptoms were collected from 45 lifelong PE patients and 37 healthy controls (HCs) since 2016, including disease and sexual life history, intravaginal ejaculatory latency time measured by stopwatch and other scales. The degree centrality (DC) approach were applied to distinguish altered brain functions between the two groups (p < 0.05, false discovery rate corrected). Correlation analysis was then performed to examine relationships between the imaging findings and clinical symptoms (p < 0.05, Bonferroni corrected). Results showed that compared with HCs, lifelong PE patients had increased DC value in the medial prefrontal cortex (mPFC), precuneus and primary somatosensory cortex (SI) as well as decreased DC value in the insula and orbitofrontal cortex. After controlling for anxiety and depression levels, the significant difference in the mPFC was not found. The DC value in the SI positively correlated with premature ejaculation diagnostic tool (PEDT) score in the patients. The present findings indicate that lifelong PE patients have altered DC in brain regions involved in sensation, motivation and inhibitory control processing. Our study may improve our understanding and provide a new sight into the further research of lifelong PE.

Abnormal degree centrality in end-stage renal disease (ESRD) patients with cognitive impairment: a resting-state functional MRI study

To investigate functional connectivity (FC) changes in end-stage renal disease (ESRD) patients with and without cognitive impairment (CI) by using resting-state functional magnetic resonance imaging (rs-fMRI). Twenty-three ESRD patients with CI, 22 ESRD patients with non-CI (NCI) and 23 matched healthy controls (HC) were included. Rs-fMRI scans were performed in all subjects. Full-range, long-range, and short-range FC defined voxel-wise based degree centrality (DC) and seed based FC were computed and contrasted among the groups. Compared with HC, the DC value of short functional connectivity (SFC), in ESRD patients have increased on the left supramarginal gyrus, while it reduced on the left insula and right postcentral gyrus in CI and decreased on the right precentral gyrus in NCI. Compared with NCI, the DC value of LFC in CI increased on the left fusiform gyrus, while the DC value of short functional connectivity (SFC) increased on the left middle orbital gyrus. In the seed-based FC analyses, the CI showed significantly decreased FC between the left insula and bilateral middle temporal gyrus, between the left fusiform gyrus and the right hippocampus, and between the left postcentral gyrus and the right parahippocampus compared to HC; the CI showed significantly increased FC between the left precuneus and the left fusiform gyrus, between the left postcentral gyrus and the right precuneus compared with NCI. Positive correlations were found between DC values on the right superior frontal gyrus and LDL and BDST, and between MoCA and the DC values on the left insula and the left postcentral gyrus. The altered degree centrality may serve as early biomarkers for CI in ESRD patients.

Impact of Transcranial Direct Current Stimulation on Cognitive Function, Brain Functional Segregation, and Integration in Patients with Mild Cognitive Impairment According to Amyloid-Beta Deposition and APOE ε4-Allele: A Pilot Study

Anodal transcranial direct current stimulation (anodal-tDCS) is known to improve cognition and normalize abnormal network configuration during resting-state functional magnetic resonance imaging (fMRI) in patients with mild cognitive impairment (MCI). We aimed to evaluate the impact of sequential anodal-tDCS on cognitive functions, functional segregation, and integration parameters in patients with MCI, according to high-risk factors for Alzheimer’s disease (AD): amyloid-beta (Aβ) deposition and APOE ε4-allele status. In 32 patients with MCI ([¹⁸ F] flutemetamol-: n = 10, [¹⁸ F] flutemetamol+: n = 22; APOE ε4-: n = 13, APOE ε4+: n = 19), we delivered anodal-tDCS (2 mA/day, five times/week, for 2 weeks) over the left dorsolateral prefrontal cortex and assessed the neuropsychological test battery and resting-state fMRI measurements before and after 2 weeks stimulation. We observed a non-significant impact of an anodal-tDCS on changes in neuropsychological battery scores between MCI patients with and without high-risk factors of AD, Aβ retention and APOE ε4-allele. However, there was a significant difference in brain functional segregation and integration parameters between MCI patients with and without AD high-risk factors. We also found a significant effect of tDCS-by-APOE ε4-allele interaction on changes in the functional segregation parameter of the temporal pole. In addition, baseline Aβ deposition significantly associated negatively with change in global functional integrity of hippocampal formation. Anodal-tDCS might help to enhance restorative and compensatory intrinsic functional changes in MCI patients, modulated by the presence of Aβ retention and the APOE ε4-allele.

Changes in Degree Centrality of Network Nodes in Different Frequency Bands in Parkinson's Disease With Depression and Without Depression

Background

Depression induces an early onset of Parkinson’s disease (PD), aggravates dyskinesia and cognitive impairment, and accelerates disease progression. However, it is very difficult to identify and diagnose PD with depression (PDD) in the early clinical stage. Few studies have suggested that the changes in neural networks are associated with PDD, while degree centrality (DC) has been documented to be effective in detecting brain network changes.

Objectives

The objectives of this study are to explore DC changes between patients with PDD and without depression (PDND) and to find the key brain hubs involved with depression in PD patients.

Methods

One hundred and four PD patients and 54 healthy controls (HCs) underwent brain resting-state functional magnetic resonance imaging. The Data Processing and Analysis of Brain Imaging and Resting-State Functional Magnetic Resonance Data Analysis Toolkit were used for processing and statistical analysis. The DC value of each frequency band was calculated. One-way analysis of variance and a two-sample t-test for post hoc comparison were used to compare the differences of the DC values in different frequency bands among PDD, PDND, and healthy control group. Gaussian random field was used for multiple comparison correction. Pearson correlation analysis was performed between each individual’s DC map and clinical indicators.

Results

The DC value of different brain regions changed in PDD and PDND in different frequency bands. The prefrontal lobe, limbic system, and basal ganglia were the main brain regions involved. PDD patients showed a wider range and more abnormal brain areas in the slow-4 frequency band (0.027–0.073 Hz) compared to the HCs. PDD showed a decreased DC value in the medial frontal gyrus, bilateral cuneus gyrus, right lingual gyrus, bilateral supplementary motor area (SMA), bilateral superior frontal gyrus, and left paracentral lobule, but an increased DC value in the bilateral brainstem, midbrain, bilateral parahippocampal gyrus, cerebellum, left superior temporal gyrus, bilateral insula, left fusiform gyrus, and left caudate nucleus in the traditional frequency band (0.01–0.08 Hz) compared to PDND patients. PDND patients displayed more abnormal functions in the basal ganglia in the slow-4 frequency band.

Conclusion

The DC changes in PDD and PDND are frequency dependent and frequency specific. The medial frontal gyrus, SMA, and limbic system may be the key hubs for depression in PD.

Reorganization of auditory-visual network interactions in long-term unilateral postlingual hearing loss

Long-term unilateral hearing loss could reorganize the functional network association between the bilateral auditory cortices, while alterations of other functional networks need to be further explored. We attempted to investigate the pattern of the reorganization of functional network associations between the auditory and visual cortex caused by long-term postlingual unilateral hearing loss (UHI) and its relationship with clinical characteristics. Therefore, 48 patients with hearing loss caused by unilateral acoustic tumors and 52 matched healthy controls were enrolled, and their high-resolution structural MRI and resting-state functional MRI data were also collected to depict the brain network. Degree centrality (DC) was employed to evaluate the functional network association of the auditory-visual network interaction. Group comparisons were performed to investigate the network reorganization, and its correlations with clinical data were calculated. Compared with the healthy control group, patients with UHI showed significantly increased DC between the auditory network (superior temporal gyrus and the medial geniculate body) and the visual network. Meanwhile, this difference was positively correlated with the extent of hearing impairment, and the correlation was more significant with the ipsilateral superior temporal gyrus in cases of acoustic neuroma. These results suggest that long-term unilateral hearing impairment may lead to enhancement of the visual-auditory network interactions and that the degree of reorganization is positively correlated with the pure tone average (PTA) and is more significant for the ipsilateral superior temporal gyrus, which provides clinical evidence regarding cross-modal plasticity in the UHI and its lateralization.

Brain network construction and analysis for patients with mild cognitive impairment and Alzheimer's disease based on a highly-available nodes approach

INTRODUCTION

Using brain network and graph theory methods to analyze the Alzheimer's disease (AD) and mild cognitive impairment (MCI) abnormal brain function is more and more popular. Plenty of potential methods have been proposed, but the representative signal of each brain region in these methods remains poor performance.

METHODS

We propose a highly-available nodes approach for constructing brain network of patients with MCI and AD. With resting-state functional magnetic resonance imaging (rs-fMRI) data of 84 AD subjects, 81 MCI subjects, and 82 normal control (NC) subjects from the Alzheimer's Disease Neuroimaging Initiative Database, we construct connected weighted brain networks based on the different sparsity and minimum spanning tree. Support Vector Machine of Radial Basis Function kernel was selected as classifier.

RESULTS

Accuracies of 74.09% and 77.58% in classification of MCI and AD from NC, respectively. We also performed a hub node analysis and found 18 significant brain regions were identified as hub nodes.

CONCLUSIONS

The findings of this study provide insights for helping understanding the progress of the AD. The proposed method highlights the effectively representative time series of brain regions of rs-fMRI data for construction and topology analysis brain network.

Dysfunctional beliefs and attitudes about sleep are associated with regional homogeneity of left inferior occidental gyrus in primary insomnia patients: a preliminary resting state functional magnetic resonance imaging study

BACKGROUND

The neural mechanisms of sleep beliefs and attitudes in primary insomnia (PI) patients at resting state remain unclear. The aim of this study was to investigate the features of regional homogeneity (ReHo) in PI using resting-state functional magnetic resonance imaging (rsfMRI).

METHODS

Thirty-two PI patients and 34 normal controls (NC) underwent rsfMRI using a 3 T scanner at Tongde Hospital of Zhejiang Province. Participants were assessed with the Dysfunctional Beliefs and Attitudes about Sleep scale (DBAS-16) and Pittsburgh Sleep Quality Index (PSQI). Statistical analyses were performed to determine the regions in which ReHo differed between the two groups. Correlation analyses were performed between the ReHo index of each of these regions and DBAS-16 in PI patients.

RESULTS

PI patients showed increased ReHo values in the right superior frontal gyrus, and decreased ReHo values in the left cerebellar gyrus, left inferior occipital gyrus (IOG) and left amygdala compared with those of NC. ReHo values in the left IOG were negatively correlated with total DBAS-16 scores, and scores for "consequences of insomnia" and"worry/helplessness about sleep"in PI patients.

CONCLUSIONS

These results suggest that ReHo alterations in the left IOG may play an important role in the dysfunctional beliefs and attitudes about sleep in PI.

Altered brain intrinsic functional hubs and connectivity associated with relapse risk in heroin dependents undergoing methadone maintenance treatment: A resting-state fMRI study

BACKGROUND

The neural substrates underlying the relapse behavior of heroin dependents (HD) who received long-term methadone maintenance treatment (MMT) have yet to be thoroughly expounded. This study investigated the relapse-related intrinsic functional hubs of HD and their functional integration feature at whole brain network level.

METHODS

57 male HD receiving MMT and 49 matched healthy controls (HC) were enrolled. All of the subjects received resting-state functional magnetic resonance imaging scan. And the 57 patients were assigned a 26-month follow-up for collecting illegal drug use information. Of them, 11 were non-relapsers and 46 relapsers. We analyzed the voxel-based degree centrality (DC) to reveal the differences in nodule centrality between HD and HC, conducted Pearson partial-correlation analysis to confirm the relationship between relapse frequency and DC value of the nodes with significant intergroup differences, and finally compared the functional connectivity (FC) of the relapse-related hubs between non-relapsers and relapsers.

RESULTS

We found the DC values of right insula and left nucleus accumbens (NAc) were negatively correlated with relapse frequency. Compared with the non-relapsers, the relapsers had a significant decreased FC between left NAc and inhibitory control circuitry, including left dorsolateral prefrontal cortex, left inferior frontal gyrus and motor regions.

CONCLUSIONS

These findings suggest that the neural substrates of relapse vulnerability in HD undergoing MMT are the intrinsic functional hubs of introceptive and reward systems and the latter modulates relapse behavior via interaction with inhibitory control circuit.

Crosstalk between Depression and Dementia with Resting-State fMRI Studies and Its Relationship with Cognitive Functioning

Alzheimer’s disease (AD) is the most common type of dementia, and depression is a risk factor for developing AD. Epidemiological studies provide a clinical correlation between late-life depression (LLD) and AD. Depression patients generally remit with no residual symptoms, but LLD patients demonstrate residual cognitive impairment. Due to the lack of effective treatments, understanding how risk factors affect the course of AD is essential to manage AD. Advances in neuroimaging, including resting-state functional MRI (fMRI), have been used to address neural systems that contribute to clinical symptoms and functional changes across various psychiatric disorders. Resting-state fMRI studies have contributed to understanding each of the two diseases, but the link between LLD and AD has not been fully elucidated. This review focuses on three crucial and well-established networks in AD and LLD and discusses the impacts on cognitive decline, clinical symptoms, and prognosis. Three networks are the (1) default mode network, (2) executive control network, and (3) salience network. The multiple properties emphasized here, relevant for the hypothesis of the linkage between LLD and AD, will be further developed by ongoing future studies.

Abnormal intrinsic functional hubs and connectivity in stable patients with COPD: a resting-state MRI study

Chronic obstructive pulmonary disease (COPD) affects a large population and is closely associated with cognitive impairment. However, the mechanisms of cognitive impairment in COPD patients have not been unraveled. This study investigated the change in patterns of intrinsic functional hubs using a degree centrality (DC) analysis. The connectivity between these abnormal hubs with the remaining brain was also investigated using functional connectivity (FC). Nineteen stable patients with COPD and 20 normal controls(NC) underwent functional magnetic resonance imaging (MRI) examinations and clinical and neuropsychologic assessments. We measured the voxel-wise DC across the whole brain gray matter and the seed-based FC between these abnormal hubs in the remaining brain matter; the group difference was calculated. A partial correlation analysis was performed to assess the relationship between the abnormal DC and clinical variables in COPD patients. Compared to NC, the patients with COPD exhibited significantly decreased DC in the right lingual gyrus (LG), bilateral supplementary motor area (SMA), and right paracentral lobule (PCL). A further seed-based FC analysis found that COPD patients demonstrated significantly decreased FC between these abnormal hubs in several brain areas, including the left cerebellum anterior lobe, left lingual gyrus, left fusiform gyrus, right insula, right inferior frontal gyrus, limbic lobe, cingulate gyrus, left putamen, lentiform nucleus, right precuneus, and right paracentral lobule. A partial correlation analysis showed that the decreased DC in the right PCL was positively correlated with the FEV1 and FEV1/FVC, and the decreased DC in the SMA was positively correlated with naming and pH in COPD patients. This study demonstrates that there are intrinsic functional hubs and connectivity alterations that may reflect the aberrant information communication in the brain of COPD patients. These findings may help provide new insight for understanding the mechanisms of COPD-related cognitive impairment from whole brain functional connections.

Abnormal Degree Centrality in White Matter Hyperintensities: A Resting-State Functional Magnetic Resonance Imaging Study

Background: White matter hyperintensities (WMHs) are a common occurrence with aging and are associated with cognitive impairment. However, the neurobiological mechanisms of WMHs remain poorly understood. Functional magnetic resonance imaging (fMRI) is a prominent tool that helps in non-invasive examinations and is increasingly used to diagnose neuropsychiatric diseases. Degree centrality (DC) is a common and reliable index in fMRI, which counts the number of direct connections for a given voxel in a network and reflects the functional connectivity within brain networks. We explored the underlying mechanism of cognitive impairment in WMHs from the perspective of DC. Methods: A total of 104 patients with WMHs and 37 matched healthy controls (HCs) were enrolled in the current study. All participants underwent individual and overall cognitive function tests and resting-state fMRI (rs-fMRI). WMHs were divided into three groups (39 mild WMHs, 37 moderate WMHs, and 28 severe WMHs) according to their Fazekas scores, and the abnormal DC values in the WMHs and HCs groups were analyzed. Results: There was a significant difference in the right inferior frontal orbital gyrus and left superior parietal gyrus between the WMHs and HCs groups. The functional connectivity between the right inferior frontal orbital gyrus and left inferior temporal gyrus, left superior parietal gyrus, and left parietal inferior gyrus was also different in the WMHs group. Conclusion: The change in DC value may be one of the underlying mechanisms of cognitive impairment in individuals with WMHs, which provides us with a new approach to delaying cognitive impairment in WMHs.

Aberrant voxel-based degree centrality in Parkinson's disease patients with mild cognitive impairment

The purpose was to explore the intrinsic dysconnectivity pattern of whole-brain functional networks in Parkinson's disease patients with mild cognitive impairment (PD-MCI) using a voxel-wise degree centrality (DC) analysis approach. The resting-state functional magnetic resonance imaging (rs-fMRI) scanning was performed in all subjects including PD-MCI, PD patients with no cognitive impairment (PD-NCI), and healthy controls (HCs). DC mapping was used to identify functional connectivity (FC) alterations among these groups. Correlation between abnormal DC and clinical features was performed. Secondary seed-based FC analyses and voxel-based morphometry (VBM) analyses were also conducted. Compared with HCs, PD-MCI and PD-NCI showed DC abnormalities mainly in the right temporal lobe, thalamus, left cuneus, middle frontal gyrus, and corpus callosum. Compared with PD-NCI, PD-MCI showed abnormal DC in the left fusiform gyrus (FFG) and left cerebellum lobule VI, left cuneus, right hippocampus, and bilateral precuneus. In PD-MCI patients, correlation analyses revealed that DC in the left FFG was positively correlated with the Montreal Cognitive Assessment (MoCA) scores, and DC in the left precuneus was negatively correlated with the MoCA scores. Secondary seed-based FC analysis further revealed FC changes mainly in the default mode network, right middle cingulum, right supramarginal gyrus, and right postcentral/precentral gyrus. However, no significant difference was found in the secondary VBM analysis. The findings suggest that dysfunction in extensive brain areas is involved in PD-MCI. Among these regions, the left precuneus, FFG, and cerebellum VI may be the key hubs in the pathogenesis of PD-MCI.

Alterations of Brain Networks in Alzheimer's Disease and Mild Cognitive Impairment: A Resting State fMRI Study Based on a Population-specific Brain Template

This study aimed to investigate the alterations in brain networks in patients with Alzheimer's disease (AD) and mild cognitive impairment (MCI) based on a population-specific brain template. Previous studies on AD brain networks using graph theory rarely adopted brain templates specific for certain ethnicities. In this study, patients were divided into 3 groups: AD (n = 24), MCI (n = 27), and healthy controls (HCs, n = 33), and all of the subjects are Chinese. Functional brain networks were constructed for each group based on a Chinese brain template using resting-state functional magnetic resonance imaging (rs-fMRI) data; several graph metrics were calculated. Graph metrics with significant differences after false discovery rate (FDR) correction were analyzed with respect to correlations with four neuropsychological test scores: Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Activities of Daily Living (ADL), and Clinical Dementia Rating (CDR), which assessed the subjects' cognitive functions and ability to engage in ADL. Graph metrics including assortativity coefficient, nodal degree centrality, nodal clustering coefficient, nodal efficiency, and nodal local efficiency of the frontal gyrus and cerebellum were significantly altered in AD and MCI compared with HC. Several graph metrics were significantly correlated with cognitive function and the ability to engage in daily activities. The findings suggest that altered graph metrics in the frontal gyrus may reflect brain plasticity, and that patients with MCI may have unique graph metric alterations in the cerebellum. Future graph analysis studies on functional brain networks in AD and MCI based on population-specific brain atlases for particular ethnicities may prove valuable.

Abnormal functional connectivity density in patients with dysthyroid optic neuropathy

[Objective] Functional connectivity density (FCD) mapping was used to investigate abnormalities and factors related to brain functional connectivity (F.C.) in cortical regions of patients with dysthyroid optic neuropathy (DON) and to analyze the pathogenesis of DON further. [Methods] Patients diagnosed with thyroid-associated ophthalmopathy (TAO) in the Eye Hospital were enrolled. All patients underwent comprehensive eye examinations and best-corrected visual acuity, visual field(V.F.) test. MRI data collection and analysis were completed in the 2nd Affiliated Hospital of Wenzhou Medical University. The patients were divided into two groups: the DON group, with an average visual field, mean deviation (M.D.) of both eyes < -5 dB, and the non-DON group (nDON group), with an average visual field M.D. of both eyes ≥ -2 dB. [Results] A total of 30 TAO patients (14 men, 16 women) with complete data who met the experimental requirements were enrolled. The average age was 48.79 (40~ 57) years. There were 16 patients in the DON group and 14 patients in the nDON group. No significant differences in age, gender, education level, and the maximum horizontal diameter of either medial rectus muscle were found between the two groups. The difference of brain FCD between the two groups showed significant abnormal connectivity in the right orbital gyri of the frontal lobe (Frontal_Inf_Orb_R) and the left precuneus in the DON group compared with the nDON group. As demonstrated by decreased FCD values in the right inferior frontal gyrus/orbital part, the relevant brain regions were the left middle temporal gyrus, left precuneus, left middle frontal gyrus, right postcentral gyrus, and brain gyri (excluding the supramarginal gyrus and angular gyrus) below the left parietal bone. The FCD associated with the left precuneus was increased, and the relevant brain areas were the left middle temporal gyrus, right cuneus, superior occipital gyrus, and right fusiform gyrus. A significant correlation was identified between the MD. of the binocular visual field and brain FCD. [Conclusion] The abnormal FCD in the cortex of DON patients suggests that a central nervous system mechanism may be related to the pathogenesis of the DON.

Alterations in Degree Centrality and Functional Connectivity in Parkinson's Disease Patients With Freezing of Gait: A Resting-State Functional Magnetic Resonance Imaging Study

Objective

Freezing of gait (FOG) is a common disabling motor symptom in Parkinson's disease (PD), but the potential pathogenic mechanisms are still unclear.

Methods

A total of 22 patients with PD with FOG (PD-FOG), 28 patients with PD without FOG (PD-nFOG), and 33 healthy controls (HCs) were recruited in this study. Degree centrality (DC)-a graph theory-based measurement of global connectivity at the voxel level by measuring the number of instantaneous functional connections between one region and the rest of the brain-can map brain hubs with high sensitivity, specificity, and reproducibility. DC was used to explore alterations in the centrality of PD-FOG correlated with brain node levels. PD-FOG cognitive network dysfunction was further revealed via a seed-based functional connectivity (FC) analysis. In addition, correlation analyses were carried out between clinical symptoms and acquired connectivity measurement.

Results

Compared to the PD-nFOG group, the PD-FOG group showed remarkably increased DC values in the right middle frontal gyrus (RMFG). There were no significant differences in other gray matter regions. Importantly, the clinical severity of FOG was related to the mean DC values in the RMFG. This brain region served as a seed in secondary seed-based FC analysis, and we further found FC changes in the right precuneus, right inferior frontal gyrus, right superior frontal gyrus (SFG), and cerebellum.

Conclusion

Increased RMFG activity and FC network alterations in the middle frontal cortex with the precuneus, inferior, and SFG, and the cerebellum may have great potential in brain dysfunction in PD with FOG.

Dynamic Neural Network Changes Revealed by Voxel-Based Functional Connectivity Strength in Left Basal Ganglia Ischemic Stroke

Objective

This study intends to track whole-brain functional connectivity strength (FCS) changes and the lateralization index (LI) in left basal ganglia (BG) ischemic stroke patients.

Methods

Twenty-five patients (N = 25; aged 52.73 ± 10.51 years) with five visits at <7, 14, 30, 90, and 180 days and 26 healthy controls (HCs; N = 26; 51.84 ± 8.06 years) were examined with resting-state functional magnetic resonance imaging (rs-fMRI) and motor function testing. FCS and LI were calculated through constructing the voxel-based brain functional network. One-way analysis of covariance (ANOVA) was first performed to obtain longitudinal FCS and LI changes in patients among the five visits (Bonferroni corrected, P < 0.05). Then, pairwise comparisons of FCS and LI were obtained during the five visits, and the two-sample t test was used to examine between-group differences in FCS [family-wise error (FWE) corrected, P < 0.05] and LI. Correlations between connectivity metrics (FCS and LI) and motor function were further assessed.

Results

Compared to HCs, decreased FCS in the patients localized in the calcarine and inferior occipital gyrus (IOG), while increased FCS gathered in the middle prefrontal cortex (MPFC), middle frontal gyrus, and insula (P < 0.05). The LI and FCS of patients first decreased and then increased, which showed significant differences compared with HCs (P < 0.05) and demonstrated a transition at the 30-day visit. Additionally, LI at the third visit was significantly different from those at the other visits (P < 0.05). No significant longitudinal correlations were observed between motor function and FCS or LI (P > 0.05).

Conclusion

Focal ischemic stroke in the left BG leads to extensive alterations in the FCS. Strong plasticity in the functional networks could be reorganized in different temporal dynamics to facilitate motor recovery after BG stroke, contribute to diagnosing the disease course, and estimate the intervention treatment.

Structural and Functional Thalamic Changes in Parkinson's Disease With Mild Cognitive Impairment

BACKGROUND

The thalamus is a key node of deep gray matter and previous studies have demonstrated that it is involved in the modulation of cognition.

PURPOSE

To investigate the volume changes of the thalamus and its subregions and altered thalamus functional connectivity patterns in Parkinson's disease (PD) patients with and without mild cognitive impairment (MCI).

STUDY TYPE

Prospective.

POPULATION

Thirty-three patients with MCI (PD-MCI), 36 PD patients having no cognitive impairment (PD-NCI), 21 healthy controls (HCs).

SEQUENCE

3.0T MRI scanner; 3D T₁ -weighted fast spoiled gradient recalled echo (3D T₁ -FSPGR); resting-state fMRI ASSESSMENT: Voxel-based morphometry (VBM) was performed to calculate the volume of the thalamus and its subregions. The left and right total thalamus were considered seeds and seed-based functional connectivity (FC) was analyzed. Additionally, correlations between volumes and cognitive performance and between FC values and cognitive performance were examined separately.

STATISTICAL TEST

Analysis of covariance (ANCOVA); two-sample t-tests; partial correlation analysis.

RESULTS

The volumes of the total thalamus (PD-MCI vs. PD-NCI vs. HCs: 18.39 ± 1.67 vs. 19.63 ± 1.79 vs. 19.47 ± 1.35) and its subregions were significantly reduced in PD-MCI as compared to PD-NCI (total thalamus: P = 0.002) and HCs (total thalamus: P = 0.012). Compared with PD-NCI, PD-MCI showed increased FC between the thalamus and bilateral middle cingulate cortex and left posterior cingulate cortex, and decreased FC between thalamus and the left superior occipital gyrus, left cuneus, left precuneus, and left middle occipital gyrus. Volumes of thalamus and the subregions, as well as the FC of thalamus with the identified regions, were significantly correlated (P < 0.05, FDR-corrected) with neuropsychological scores in PD patients.

DATA CONCLUSION

We noted volume loss and altered FC of thalamus in PD-MCI patients, and these changes were correlated with global cognitive performance.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICIENCY: Stage 2 J. Magn. Reson. Imaging 2020;52:1207-1215.

Animal-Assisted and Pet-Robot Interventions for Ameliorating Behavioral and Psychological Symptoms of Dementia: A Systematic Review and Meta-Analysis

Patients with dementia suffer from psychological symptoms such as depression, agitation, and aggression. One purpose of dementia intervention is to manage patients’ inappropriate behaviors and psychological symptoms while taking into consideration their quality of life (QOL). Animal-assisted intervention (AAI) and pet-robot intervention (PRI) are effective intervention strategies for older people with cognitive impairment and dementia. In addition, AAI and PRI have been shown to have positive effects on behavioral and psychological symptoms of dementia (BPSD). However, studies into the association between AAI/PRI and BPSD have elicited inconsistent results. Thus, we performed a meta-analysis to investigate this association. We analyzed nine randomized controlled trials on AAI and PRI for dementia patients published between January 2000 and August 2019 and evaluated the impact of AAI/PRI on agitation, depression, and QOL. We found that AAI and PRI significantly reduce depression in patients with dementia. Subsequent studies should investigate the impact of AAI and PRI on the physical ability and cognitive function of dementia patients and conduct a follow-up to investigate their effects on the rate of progression and reduction of symptoms of dementia. Our research will help with neuropsychological and environmental intervention to delay or improve the development and progression of BPSD.

Neuropsychiatric Aspects of Alzheimer Dementia: From Mechanism to Treatment

Developing disease-modifying treatments for Alzheimer dementia requires innovative approaches to identify novel biological targets during the course of the disease. Treatment development for the neuropsychiatric symptoms of Alzheimer may benefit from a mechanistic approach to treatment. There has been progress in identifying mild forms of behavioral impairment along the Alzheimer spectrum that may lead to additional insights into progression to dementia as well as the fundamental mechanisms of the symptoms. Developing therapies for complex neurobehavioral syndromes may require the translation of mechanistic insights into therapy, which may both improve the symptoms and delay progression to dementia in certain patients.

The Challenge of Antidepressant Therapeutics in Alzheimer's Disease

The link between depression and Alzheimer's disease (AD) is controversial, because it is not clear if depression is an independent risk factor for the disease or a prodromal symptom in the older population. Cerebral amyloid-β (Aβ) peptide deposition is associated with both cognitive symptoms and neuropsychiatric symptoms (NPS), which may be a biological mechanism of compensation. Despite the widespread use of antidepressant therapeutics (30-50% of patients with AD/dementia are on antidepressants), there is mixed evidence regarding the benefits from their use in AD depression. Monoaminergic antidepressant drugs have shown only modest or no clinical benefits. Therefore, it is important to understand the reason of this drug-resistance and the relationship between antidepressant drugs and the Aβ peptide. The goal of the present review is to highlight the etiology of depression in patients affected by AD in comparison to depressive disorders without AD, and to speculate on more appropriate and alternative therapeutics.

Brain MRI analysis using a deep learning based evolutionary approach

Convolutional neural network (CNN) models have recently demonstrated impressive performance in medical image analysis. However, there is no clear understanding of why they perform so well, or what they have learned. In this paper, a three-dimensional convolutional neural network (3D-CNN) is employed to classify brain MRI scans into two predefined groups. In addition, a genetic algorithm based brain masking (GABM) method is proposed as a visualization technique that provides new insights into the function of the 3D-CNN. The proposed GABM method consists of two main steps. In the first step, a set of brain MRI scans is used to train the 3D-CNN. In the second step, a genetic algorithm (GA) is applied to discover knowledgeable brain regions in the MRI scans. The knowledgeable regions are those areas of the brain which the 3D-CNN has mostly used to extract important and discriminative features from them. For applying GA on the brain MRI scans, a new chromosome encoding approach is proposed. The proposed framework has been evaluated using ADNI (including 140 subjects for Alzheimer's disease classification) and ABIDE (including 1000 subjects for Autism classification) brain MRI datasets. Experimental results show a 5-fold classification accuracy of 0.85 for the ADNI dataset and 0.70 for the ABIDE dataset. The proposed GABM method has extracted 6 to 65 knowledgeable brain regions in ADNI dataset (and 15 to 75 knowledgeable brain regions in ABIDE dataset). These regions are interpreted as the segments of the brain which are mostly used by the 3D-CNN to extract features for brain disease classification. Experimental results show that besides the model interpretability, the proposed GABM method has increased final performance of the classification model in some cases with respect to model parameters.

Depression Affects Intrinsic Brain Activity in Patients With Mild Cognitive Impairment

Numerous observational studies have shown that depressive symptoms are common in individuals with mild cognitive impairment (MCI) who have a higher rate of progress to dementia. However, it is still uncertain whether there are any differences between MCI patients with and without depression symptom in their brain function activities. Here we have identified the brain function activity differences in two groups of MCI patients (with depression or without depression) using the resting state MRI (rsfMRI) measurements. 76 right-handed MCI subjects have been recruited in this study, including 27 MCI patients with depression symptom (MCID), 49 MCI patients without depression symptom (MCIND). Analyses based on 7 rsfMRI measurements, including four static measurements (ALFF, fALFF, PerAF, and ReHo) and three dynamic measurements (dALFF, dfALFF, and dReHo) have been used to explore the temporal variability of intrinsic brain activity. No significant differences in ALFF and dALFF between the two group were found. In the MCID group, fALFF decreased in temporal gyrus, frontal gyrus, inferior occipital gyrus, middle frontal gyrus and cerebellum, but increased in cuneus, calcarine, lingual; while PerAF increased in left parahippocampus. The differences of ReHo in the two groups was only found in cerebellum. Compared to MCIND group, dfALFF in MCID decreased in cuneus, occipital gyrus and calcarine, while dReHo in MCID increased in bilateral temporal gyrus, frontal gyrus, superior parietal gyrus, inferior parietal gyrus and precuneus. Our results may provide a better understanding in the relationship between the depressive symptoms and memory deficits.