Resting-state Networks In Patients Research Articles

Alterations of resting-state network dynamics in Alzheimer's disease based on leading eigenvector dynamics analysis.

Alzheimer's disease (AD) is a neurodegenerative disease, and mild cognitive impairment (MCI) is considered a transitional stage between healthy aging and dementia. Early detection of MCI can help slow down the progression of AD. At present, there are few studies exploring the characteristics of abnormal dynamic brain activity in AD. This article uses a method called leading eigenvector dynamics analysis (LEiDA) to study resting-state functional magnetic resonance imaging (rs-fMRI) data of AD, MCI, and cognitively normal (CN) participants. By identifying repetitive states of phase coherence, intergroup differences in brain dynamic activity indicators are examined, and the neurobehavioral scales were used to assess the relationship between abnormal dynamic activities and cognitive function. The results showed that in the indicators of occurrence probability and lifetime, the globally synchronized state of the patient group decreased. The activity state of the limbic regions significantly detected the difference between AD and the other two groups. Compared to CN, AD and MCI have varying degrees of increase in default and visual region activity states. In addition, in the analysis related to the cognitive scales, it was found that individuals with poorer cognitive abilities were less active in the globally synchronized state and more active in limbic region activity state and visual region activity state. Taken together, these findings reveal abnormal dynamic activity of resting-state networks in patients with AD and MCI, provide new insights into the dynamic analysis of brain networks, and contribute to a deeper understanding of abnormal spatial dynamic patterns in AD patients.NEW & NOTEWORTHY Alzheimer's disease (AD) is a neurodegenerative disease, but few studies have explored the characteristics of abnormal dynamic brain activity in AD patients. Here, our report reveals the abnormal dynamic activity of the patients' resting-state network, providing new insights into the dynamic analysis of brain networks and helping to gain a deeper understanding of the abnormal spatial dynamic patterns in AD patients.

Magnetic resonance-guided focused ultrasound thalamotomy restored distinctive resting-state networks in patients with essential tremor.

Magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy ameliorates symptoms in patients with essential tremor (ET). How this treatment affects canonical brain networks has not been elucidated. The purpose of this study was to clarify changes of brain networks after MRgFUS thalamotomy in ET patients by analyzing resting-state networks (RSNs). Fifteen patients with ET were included in this study. Left MRgFUS thalamotomy was performed in all cases, and MR images, including resting-state functional MRI (rsfMRI), were taken before and after surgery. MR images of 15 age- and sex-matched healthy controls (HCs) were also used for analysis. Using rsfMRI data, canonical RSNs were extracted by performing dual regression analysis, and the functional connectivity (FC) within respective networks was compared among pre-MRgFUS patients, post-MRgFUS patients, and HCs. The severity of tremor was evaluated using the Clinical Rating Scale for Tremor (CRST) score pre- and postoperatively, and its correlation with RSNs was examined. Preoperatively, ET patients showed a significant decrease in FC in the sensorimotor network (SMN), primary visual network (VN), and visuospatial network (VSN) compared with HCs. The decrease in FC in the SMN correlated with the severity of tremor. After MRgFUS thalamotomy, ET patients still exhibited a significant decrease in FC in a small area of the SMN, but they exhibited an increase in the cerebellar network (CN). In comparison between pre- and post-MRgFUS patients, the FC in the SMN and the VSN significantly increased after treatment. Quantitative evaluation of the FCs in these three groups showed that the SMN and VSN increased postoperatively and demonstrated a trend toward those of HCs. The SMN and CN, which are considered to be associated with the cerebello-thalamo-cortical loop, exhibited increased connectivity after MRgFUS thalamotomy. In addition, the FC of the visual network, which declined in ET patients compared with HCs, tended to normalize postoperatively. This could be related to the hypothesis that visual feedback is involved in tremor severity in ET patients. Overall, the analysis of the RSNs by rsfMRI reflected the pathophysiology with the intervention of MRgFUS thalamotomy in ET patients and demonstrated a possibility of a biomarker for successful treatment.

Altered functional connectivity within and between resting-state networks in patients with vestibular migraine.

Previous functional magnetic resonance imaging studies have substantiated changes in multiple brain regions of functional activity in patients with vestibular migraine. However, few studies have assessed functional connectivity within and between specific brain networks in vestibular migraine. Our study subjects included 37 patients with vestibular migraine and 35 healthy controls, and the quality of magnetic resonance images of all subjects met the requirements. Independent component analysis was performed to identify resting-state networks, and we investigated changes in functional connectivity patterns within and between brain networks. We also used Pearson correlation analysis to assess the relationship between changes in functional connectivity and the clinical features of patients with vestibular migraine. A total of 14 independent components were identified. Compared to healthy controls, patients with vestibular migraine exhibited decreased intra-network functional connectivity in the executive control network and weakened functional connectivity between the anterior default mode network and the ventral attention network, between the anterior default mode network and the salience network, and between the right frontoparietal network and the auditory network. Moreover, the functional connectivity between the salience network and the dorsal attention network was increased. However, the functional connectivity of networks and clinical characteristics of vestibular migraine patients did not demonstrate any significant correlation. In conclusion, our study suggested that patients with vestibular migraine also have abnormal multisensory integration during the interictal period and that the attention network is involved. Changing within- and between-network functional connectivity may indicate that vestibular cortex areas are in a sensitive state.

Clusterwise Independent Component Analysis (C-ICA): Using fMRI resting state networks to cluster subjects and find neurofunctional subtypes

Background:FMRI resting state networks (RSNs) are used to characterize brain disorders. They also show extensive heterogeneity across patients. Identifying systematic differences between RSNs in patients, i.e. discovering neurofunctional subtypes, may further increase our understanding of disease heterogeneity. Currently, no methodology is available to estimate neurofunctional subtypes and their associated RSNs simultaneously. New method:We present an unsupervised learning method for fMRI data, called Clusterwise Independent Component Analysis (C-ICA). This enables the clustering of patients into neurofunctional subtypes based on differences in shared ICA-derived RSNs. The parameters are estimated simultaneously, which leads to an improved estimation of subtypes and their associated RSNs. Results:In five simulation studies, the C-ICA model is successfully validated using both artificially and realistically simulated data (N = 30–40). The successful performance of the C-ICA model is also illustrated on an empirical data set consisting of Alzheimer’s disease patients and elderly control subjects (N = 250). C-ICA is able to uncover a meaningful clustering that partially matches (balanced accuracy = .72) the diagnostic labels and identifies differences in RSNs between the Alzheimer and control cluster. Comparison with other methods:Both in the simulation study and the empirical application, C-ICA yields better results compared to competing clustering methods (i.e., a two step clustering procedure based on single subject ICA’s and a Group ICA plus dual regression variant thereof) that do not simultaneously estimate a clustering and associated RSNs. Indeed, the overall mean adjusted Rand Index, a measure for cluster recovery, equals 0.65 for C-ICA and ranges from 0.27 to 0.46 for competing methods. Conclusions:The successful performance of C-ICA indicates that it is a promising method to extract neurofunctional subtypes from multi-subject resting state-fMRI data. This method can be applied on fMRI scans of patient groups to study (neurofunctional) subtypes, which may eventually further increase understanding of disease heterogeneity.

Static and Dynamic Functional Connectivity Alterations in Alzheimer's Disease and Neuropsychiatric Diseases.

Background: To date, numerous studies have documented various alterations in resting brain activity in Alzheimer's disease (AD) and other neuropsychiatric diseases. In particular, disease-related alterations of functional connectivity (FC) in the resting state networks (RSN) have been documented. Altered FC in RSN is useful not only for interpreting the phenotype of diseases but also for diagnosing the diseases. More recently, several studies proposed the dynamics of resting-brain activity as a useful marker for detecting altered RSNs related to AD and other diseases. Objectives: In this article, we review recent studies exploring alterations of static and dynamic functional connectivity in AD and other neuropsychiatric diseases. We then discuss how to utilize and interpret dynamics of FC for studying resting brain activity in diseases. Results: In contrast to previous studies, which focused on FC calculated using an entire fMRI scan (static FC), newer studies focused on the temporal dynamics of FC within the scan (dynamic FC) to provide more sensitive measures to characterize RSNs. However, despite the increasing popularity of dynamic FC, several statistical investigations of dynamic FC cautioned that the results obtained in commonly used analyses for dynamic FC require careful interpretation. Conclusions: Although static and dynamic FC are likely to be a useful tool to detect altered RSN in patients affected by AD and other neuropsychiatric disorders, interpretation of altered dynamic FC in patients require special care. Impact statement We review recent studies of static and dynamic functional connectivity (dFC) in Alzheimer's disease and discuss interpretation of dFC.

Altered functional connectivity in common resting-state networks in patients with major depressive disorder: A resting-state functional connectivity study

The neural correlates of major depressive disorder (MDD) remain disputed. In the absence of reliable biological markers, the dysfunction and interaction of neural networks have been proposed as pathophysiological neural mechanisms in depression. Here, we examined the functional connectivity (FC) of brain networks. 51 healthy volunteers (mean age 33.57 ± 7.80) and 55 individuals diagnosed with MDD (mean age 33.89 ± 11.00) participated by performing a resting-state (rs) fMRI scan. Seed to voxel FC analyses were performed. Compared to healthy control (HC), MDD patients showed higher connectivity between the hippocampus and the anterior cingulate cortex (ACC) and lower connectivity between the insula and the ACC. The MDD group displayed lower connectivity between the inferior parietal lobule (IPL) and the superior frontal gyrus (SFG). The current data replicate previous findings regarding the cortico-limbic network (hippocampus – ACC connection) and the salience network (insula - ACC connection) and provide novel insight into altered rsFC in MDD, in particular involving the hippocampus - ACC and the insula - ACC connection. Furthermore, altered connectivity between the IPL and SFG indicates that the processing in higher cognitive processes such as attention and working memory is affected in MDD. These data further support dysfunctional neuronal networks as an interesting pathophysiological marker in depression.

Intra and inter: Alterations in functional brain resting-state networks in patients with functional constipation

BackgroundFunctional constipation (FCon), is a symptom-based functional gastrointestinal disorder without an organic etiology and altering brain structure and function. However, previous studies mainly focused on isolated brain regions involved in brain plasticity. Therefore, little is known about the altered large-scale interaction of brain networks in FCon.MethodsFor this study, we recruited 20 patients with FCon and 20 healthy controls. We used group independent component analysis to identify resting-state networks (RSNs) and documented intra- and inter-network alterations in the RSNs of the patients with FCon.ResultsWe found 14 independent RSNs. Differences in the intra-networks included decreased activities in the bilateral caudate of RSN 3 (strongly related to emotional and autonomic processes) and decreased activities in the left precuneus of RSN 10 (default mode network). Notably, the patients with FCon exhibited significantly decreased interactive connectivity between RSNs, mostly involving the connections to the visual perception network (RSN 7–9).ConclusionCompared with healthy controls, patients with FCon had extensive brain plastic changes within and across related RSNs. Furthermore, the macroscopic brain alterations in FCon were associated with interoceptive abilities, emotion processing, and sensorimotor control. These insights could therefore lead to the development of new treatment strategies for FCon.

Alterations in functional connectivity and interactions in resting-state networks in female patients with functional constipation.

Functional MRI with independent component analysis was applied to investigate alterations in FC within and functional network connectivity (FNC) between RSNs including default mode- (DMN), basal ganglia- (BGN), salience- (SN), and left and right control executive-networks (LCEN/RCEN) in 39 female patients with FCon and 36 female healthy controls (HC). Patient Assessment of Constipation Quality of Life Scale (PAC-QOL) and Patient Assessment of Constipation Symptom Scale (PAC-SYM) were used to assess the constipation symptoms. FCon patients had changed regional FC between different networks contributing to the abnormal FNC among RSNs compared with HC. Patients with greater stool syndromes had increased FNC of BGN-SN and DMN-LCEN, and patients with greater worries/concerns and PAC-QOL total score had reduced FNC of SN-RCEN. The greater strength changes in FC in prefrontal and parietal cortices were associated with higher negative emotion scores and greater rectal symptoms, respectively. The findings suggested that FCon patients had altered FC within and interactions between RSNs and the brain FC changes were associated with constipation symptoms and altered emotions.

Study of extravisual resting-state networks in pituitary adenoma patients with vision restoration

BackgroundPituitary adenoma (PA) may compress the optic apparatus, resulting in impaired vision. Some patients can experience improved vision rapidly after surgery. During the early period after surgery, however, the change in neurofunction in the extravisual cortex and higher cognitive cortex has yet to be explored.ObjectiveOur study focused on the changes in the extravisual resting-state networks in patients with PA after vision restoration.MethodsWe recruited 14 patients with PA who experienced visual improvement after surgery. The functional connectivity (FC) of 6 seeds [auditory cortex (A1), Broca’s area, posterior cingulate cortex (PCC) for the default mode network (DMN), right caudal anterior cingulate cortex for the salience network (SN) and left dorsolateral prefrontal cortex for the executive control network (ECN)] were evaluated. A paired t test was conducted to identify the differences between two groups of patients.ResultsCompared with their preoperative counterparts, patients with PA with improved vision exhibited decreased FC with the right A1 in the left insula lobule, right middle temporal gyrus and left postcentral gyrus and increased FC in the right paracentral lobule; decreased FC with the Broca in the left middle temporal gyrus and increased FC in the left insula lobule and right thalamus; decreased FC with the DMN in the right declive and right precuneus; increased FC in right Brodmann area 17, the left cuneus and the right posterior cingulate; decreased FC with the ECN in the right posterior cingulate, right angular and right precuneus; decreased FC with the SN in the right middle temporal gyrus, right hippocampus, and right precuneus; and increased FC in the right fusiform gyrus, the left lingual gyrus and right Brodmann area 19.ConclusionsVision restoration may cause a response of cross-modal plasticity and multisensory systems related to A1 and the Broca. The DMN and SN may be involved in top-down control of the subareas within the visual cortex. The precuneus may be involved in the DMN, ECN and SN simultaneously.

Altered Intra- and Inter-Network Functional Connectivity in Patients With Crohn's Disease: An Independent Component Analysis-Based Resting-State Functional Magnetic Resonance Imaging Study.

BackgroundMany studies have reported changes in the structure and function of several brain areas in patients with Crohn’s disease (CD). However, little is known about whether the possible functional connectivity of resting-state networks (RSNs) is altered in CD patients.PurposeAim to investigate the intra- and inter-network alterations between related RSNs in patients with CD and the potential relationships between altered neuroimaging and CD clinical indices.Materials and MethodsIn this study, 20 CD patients and 22 age- and sex-matched healthy controls were included. All participants underwent functional magnetic resonance imaging examination. We used independent component analysis (ICA) to explore the changes in RSNs and evaluated functional connectivity between different RSNs using functional network connectivity (FNC) analysis, and Pearson correlation analysis was performed between altered intra- and inter-network functional connectivity and CD clinical index.ResultsSix CD-related RSNs were identified via ICA, namely the high visual, prime visual, language, dorsal default mode, posterior insula, and precuneus networks. Compared to healthy controls, patients with CD showed significant changes in prime visual and language networks. Additionally, the functional connectivity (FC) values of the left calcarine within the prime visual network were negatively correlated with CD duration. The inter-alterations showed that a significantly increased FNC existed between the language and dorsal default mode networks.ConclusionThe results showed CD-related changes in brain functional networks. This evidence provides more insights into the pathophysiological mechanisms of brain plasticity in CD.

Disrupted Strength and Stability of Regional Brain Activity in Disorder of Consciousness Patients: A Resting-State Functional Magnetic Resonance Imaging Study

Although the resting-state networks of patients with disorders of consciousness (DOC) have been widely investigated, the underlying neural mechanisms remain unclear. Here we aimed to explore the static and dynamic alterations in the regional brain activity in patients with DOC and detect the diagnostic ability of each index. Nineteen patients in the vegetative state, 19 in the minimally conscious state (MCS), and 41 healthy controls were recruited for this study. The fractional amplitudes of the low-frequency fluctuation (fALFF) and dynamic fALFF (dfALFF) values were computed, and intergroup differences were detected by analysis of variance. Sub-frequency analysis (slow-4 band and slow-5 band) of fALFF was also performed. Machine learning classifiers were established based on these measures to explore the classification accuracies between patients and controls. The fALFF and dfALFF analyses showed significant intergroup differences in the medial prefrontal gyrus, precuneus, left angular gyrus, and right middle cingulate cortex (MCC), whereas only the dfALFF analysis revealed aberrations in the right inferior frontal gyrus (IFG), right angular gyrus, left supramarginal gyrus (SMG), and left middle occipital gyrus (MOG). Sub-frequency analysis suggested a potential frequency dependent alteration in the default mode network (DMN). The fALFF model exhibited a higher classification accuracy (ACC) (90.50%) than the dfALFF model (86.29%). The combination of fALFF and dfALFF did not improve classification performance. The strength and stability of regional brain activities were disrupted in patients with DOC. Our findings demonstrate that dynamic analysis may reveal more pathological regions and provide a better understanding of the pathophysiologic mechanisms of DOC.

Altered Posterior Midline Activity in Patients with Jerky and Tremulous Functional Movement Disorders.

Objective: To explore changes in resting-state networks in patients with jerky and tremulous functional movement disorders (JT-FMD). Methods: Resting-state functional magnetic resonance imaging data from seventeen patients with JT-FMD and seventeen age-, sex-, and education-matched healthy controls (HC) were investigated. Independent component analysis was used to examine the central executive network (CEN), salience network, and default mode network (DMN). Frequency distribution of network signal fluctuations and intra- and internetwork functional connectivity were investigated. Symptom severity was measured using the Clinical Global Impression-Severity scale. Beck Depression Inventory and Beck Anxiety Inventory scores were collected to measure depression and anxiety in FMD, respectively. Results: Compared with HC, patients with JT-FMD had significantly decreased power of lower range (0.01-0.10 Hz) frequency fluctuations in a precuneus and posterior cingulate cortex component of the DMN and in the dorsal attention network (DAN) component of the CEN (false discovery rate-corrected p < 0.05). No significant group differences were found for intra- and internetwork functional connectivity. In patients with JT-FMD, symptom severity was not significantly correlated with network measures. Depression scores were weakly correlated with intranetwork functional connectivity in the medial prefrontal cortex, while anxiety was not found to be related to network connectivity. Conclusions: Given the changes in the posterodorsal components of the DMN and DAN, we postulate that the JT-FMD-related functional alterations found in these regions could provide support for the concept that particularly attentional dysregulation is a fundamental disturbance in these patients. Impact statement In this study, we explored static brain network functional connectivity in patients with jerky and tremulous functional movement disorders (JT-FMD) and healthy controls. We studied network functioning by analyzing functional connectivity measures, and also time course frequency spectra, which is novel compared with previous studies. We discovered aberrations in the frequency distribution of a posterior component of the default mode network (precuneus/posterior cingulate) and the dorsal attention network in patients with JT-FMD relative to controls. Conclusively, our findings could provide support for impaired attentional control as a fundamental disturbance in JT-FMD and contribute to the growing conceptualization of this disorder.

Intraoperative Resting-State Functional Connectivity and Resting-State Networks in Patients with Intracerebral Lesions: Detectability and Variations Between Sessions

To evaluate the functional connectivity (FC) and resting-state networks (RSNs) in patients under anesthesia operated for resection of intracerebral lesions. We performed intraoperative resting-state functional magnetic resonance imaging (irs-fMRI) in 24 patients under anesthesia before and after lesion resection. Correlation matrices were established for each session (a total 48 of sessions). We analyzed the changes in overall FC and in FC of the healthy and operated hemispheres between the first and second sessions. We tested the correlation between changes in FC and clinical outcomes and the duration, rate, and total dosage of anesthesia. We also performed a group analysis to detect topographic changes in RSNs in patients under anesthesia. A single-subject analysis was performed to detect clinically relevant RSNs in each patient. FC decreased significantly in the second session, as did interhemispheric connectivity. The decrease in the pathological hemisphere was significant and significantly greater than the decrease in the intrahemispheric connectivity of the healthy hemisphere. The change in FC was not correlated with clinical outcome or with the duration, rate, or dosage of anesthesia. Group analysis showed topographic changes in RSNs, especially in high-level networks such as default mode and salience networks. Identification of clinically relevant networks was also possible. FC and RSNs could be identified under anesthesia and used for extended brain mapping. Further studies are needed to optimize the depth of hypnosis to stabilize FC between sessions.

Electroencephalogram Microstate Abnormalities in Early-Course Psychosis

BackgroundMicrostates are periods of characteristic electroencephalographic signal topography that are related to activity in brain networks. Previous work has identified abnormal microstate parameters in individuals with psychotic disorders. We combined microstate analysis with sample entropy analysis to study the dynamics of resting-state networks in patients with early-course psychosis. MethodsWe used microstate analysis to transform resting-state high-density electroencephalography data from 22 patients with early-course psychosis and 22 healthy control subjects into sequences of characteristic scalp topographies. Sample entropy was used to calculate the complexity of microstate sequences across a range of template lengths. ResultsPatients and control subjects produced similar sets of 4 microstates that agree with a widely reported canonical set (A, B, C, and D). Relative to control subjects, patients had decreased frequency of microstate A. In control subjects, sample entropy decreased as template length increased, suggesting that sequence of microstate transitions is self-similar across multiple transitions. In patients, sample entropy did not decrease, suggesting a lack of self-similarity in transition sequences. This finding was unrelated to data length or microstate topography. Entropy was elevated in unmedicated patients, and it decreased in patients who were administered medication. We identified patterns of transitions between microstates that were overrepresented in control data compared with representation in patient data. ConclusionsOur findings suggest that patients with early-course psychosis have abnormally chaotic transitions between brain networks. This chaos may reflect an underlying abnormality in allocating neural resources and effecting appropriate transitions between distinct activity states in psychosis.

Semantic Deficits in ALS Related to Right Lingual/Fusiform Gyrus Network Involvement: A Case-Control Study

Background: The clinicopathological continuity between amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) is well known. Although patients with ALS demonstrate similar language symptoms to patients with FTLD, including semantic dementia, word reading impairments in ALS have not been well studied. are kanji-written with irregular pronunciation that applies to exception words and are useful for detecting semantic deficits in Japan. We investigated Jukujikun reading impairments and related changes in resting-state networks in patients with ALS. Methods: We enrolled 140 participants, including 71 ALS patients and 69 healthy controls. We examined demographic and comprehensive neuropsychological factors, including Jukujikun. We also performed resting-state functional magnetic resonance imaging with voxel-based graph analysis on a subset of participants who agreed to participate in the imaging study to investigate the regions and related networks associated with Jukujikun impairments in ALS. Findings: Fifty-two percent of ALS patients (N=37) exhibited a significantly reduced score in Jukujikun reading compared with controls. We classified those patients as ALS with positive Jukujikun deficit (ALS-JD+) and the other patients as ALS with negative deficit (ALS-JD-). Resting-state network analysis showed significantly decreased degree centrality in the right fusiform/lingual gyrus and increased degree centrality in the left inferior/middle temporal gyrus in ALS-JD+ compared with ALS-JD- and controls. Seed-based analysis also revealed that the dysfunction in the right fusiform/lingual gyrus depended on decreased connectivity with regions associated with visual word perception, semantic processing, and speech. On the other hand, the observed increased degree centrality in the left inferior/middle temporal gyrus was derived from regions related to semantic processing. Interpretation Dysfunction of the hub in the right fusiform/lingual gyrus can affect semantic deficit in ALS. Considering neuropsychological symptoms as network impairments is vital for understanding various diseases. Funding MHLW and MEXT, Japan. Funding Statement: MHLW and MEXT, Japan. Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: The study conformed to the Ethical Guidelines for Medical and Health Research Involving Human Subjects endorsed by the Japanese government. The study protocol was approved by the Ethics Review Committee of the Nagoya University Graduate School of Medicine, and written informed consent was obtained from all participants.

Potential Intra- or Cross-Network Functional Reorganization of the Triple Unifying Networks in Patients with Frontal Glioma

Patients with frontal glioma might experience cognition alterations together with potential dysfunction of resting-state networks (RSNs). To understand the altered patterns of the intrinsic activity and underlying network interactions between the cognitive-related RSNs is of great importance. This study aimed to investigate the characteristics of the altered RSNs, including default mode network, executive control network, and salience network and further elucidate the possible functional reorganization of RSNs in patients with frontal glioma. Thirteen patients with frontal glioma and 10 healthy controls (HCs) were enrolled in this study. Independent component analysis was performed to identify the characteristics of the selected RSNs activity. Further, functional connectivity analysis was applied to investigate the relationship between the altered regions. Subsequently, partial correlation analysis was performed to examine associations between the neural activity of RSNs and neurocognitive characteristics. Compared with the HCs group, the patient group exhibited significant differences in functional connectivity among default mode network, executive control network, and salience network. In addition, the number of the significant functional connectivities between the paired seeds observed in the patients was greater than that in HCs and significantly increased functional connectivity was detected between left posterior cingulate cortex and right angular gyrus. Furthermore, altered neural activities in the RSNs of patients with frontal glioma were positively associated with certain aspects of cognitive function. Our results suggested underlying network functional reorganization of the triple unifying RSNs in patients with frontal glioma, providing novel insights for improving understanding of brain function.

Childhood trauma history is linked to abnormal brain connectivity in major depression

Patients with major depressive disorder (MDD) present with heterogeneous symptom profiles, while neurobiological mechanisms are still largely unknown. Brain network studies consistently report disruptions of resting-state networks (RSNs) in patients with MDD, including hypoconnectivity in the frontoparietal network (FPN), hyperconnectivity in the default mode network (DMN), and increased connection between the DMN and FPN. Using a large, multisite fMRI dataset (n = 189 patients with MDD, n = 39 controls), we investigated network connectivity differences within and between RSNs in patients with MDD and healthy controls. We found that MDD could be characterized by a network model with the following abnormalities relative to controls: (i) lower within-network connectivity in three task-positive RSNs [FPN, dorsal attention network (DAN), and cingulo-opercular network (CON)], (ii) higher within-network connectivity in two intrinsic networks [DMN and salience network (SAN)], and (iii) higher within-network connectivity in two sensory networks [sensorimotor network (SMN) and visual network (VIS)]. Furthermore, we found significant alterations in connectivity between a number of these networks. Among patients with MDD, a history of childhood trauma and current symptoms quantified by clinical assessments were associated with a multivariate pattern of seven different within- and between-network connectivities involving the DAN, FPN, CON, subcortical regions, ventral attention network (VAN), auditory network (AUD), VIS, and SMN. Overall, our study showed that traumatic childhood experiences and dimensional symptoms are linked to abnormal network architecture in MDD. Our results suggest that RSN connectivity may explain underlying neurobiological mechanisms of MDD symptoms and has the potential to serve as an effective diagnostic biomarker.

Anxiety and Depression Symptoms Disrupts Resting State Networks in Patients with Generalized Epilepsies (P3.286)

Anxiety and Depression Symptoms Disrupts Resting State Networks in Patients with Generalized Epilepsies (P3.286)

The Default Mode Network as a Biomarker of Persistent Complaints after Mild Traumatic Brain Injury: A Longitudinal Functional Magnetic Resonance Imaging Study.

The objective of this study was to examine longitudinal functional connectivity of resting-state networks in patients with and without complaints after uncomplicated mild traumatic brain injury (mTBI). Second, we aimed to determine the value of network connectivity in predicting persistent complaints, anxiety, depression and long-term outcome. Thirty mTBI patients with three or more post-traumatic complaints at 2 weeks post-injury, 19 without complaints, and 20 matched healthy controls were selected for this study. Resting-state functional MRI (fMRI) was performed in patients at 1 month and 3 months post-injury, and once in healthy controls. Independent component analysis (ICA) was used to investigate the default mode, executive and salience networks. Persistent post-traumatic complaints, anxiety, and depression were measured at 3 months post-injury, and outcome was determined at 1 year post-injury. Within the group with complaints, higher functional connectivity between the anterior and posterior components of the default mode network at 1 month post-injury was associated with a greater number of complaints at 3 months post-injury (ρ = 0.59, p = 0.001). Minor longitudinal changes in functional connectivity were found for patients with and without complaints after mTBI, which were limited to connectivity within the precuneus component of the default mode network. No significant results were found for the executive and salience networks. Current results suggest that the default mode network may serve as a biomarker of persistent complaints in patients with uncomplicated mTBI.

Disturbed Brain Activity in Resting-State Networks of Patients with First-Episode Schizophrenia with Auditory Verbal Hallucinations: A Cross-sectional Functional MR Imaging Study.

Purpose To investigate auditory verbal hallucination (AVH)-specific patterns of brain activity within the resting-state networks (RSNs) that have been proposed to underpin the neural mechanisms of schizophrenia (SZ). Materials and Methods This cross-sectional study was approved by the local ethics committee, and written informed consent was obtained from all participants prospectively recruited. Independent component analysis was used to investigate RSNs in 17 patients with first-episode untreated SZ with AVHs, 15 patients with SZ without AVHs, and 19 healthy control subjects who underwent resting-state functional magnetic resonance imaging. Dual regression was implemented to perform between-group analysis. Regional brain function was then explored within RSNs by using the amplitude of low-frequency fluctuation. Two-sample t tests were used to compare regional brain function between the two patient groups, and Pearson correlation analysis was used to characterize the relationship between imaging findings and severity of AVHs. Receiver operating characteristic analysis was used to evaluate the diagnostic performance of these brain function measures. Results Independent component analysis demonstrated symptom-specific abnormal disrupted coactivation within the auditory, default mode, executive, motor, and frontoparietal networks and was pronounced in the auditory cortex, supramarginal gyrus, insula, putamen, dorsolateral prefrontal cortex, angular gyrus, precuneus, and thalamus (P < .05 with false discovery rate correction). Amplitude of low-frequency fluctuation analysis demonstrated similar patterns within these RSNs (P < .05 with false discovery rate correction). Furthermore, a positive correlation between the degree of coactivation within the motor network and the severity of AVHs was observed in patients with SZ with AVHs (r = 0.67, P = .003). The area under the receiver operating characteristic curve was 0.76-0.90 for all RSNs. Conclusion These findings indicate that dysfunctional brain regions are involved in auditory processing, language production and monitoring, and sensory information filtering in patients with SZ with AVHs, which may be helpful in furthering the understanding of pathophysiological correlates of AVHs in SZ. Online supplemental material is available for this article.