Dynamic functional network connectivity in idiopathic generalized epilepsy with generalized tonic-clonic seizure

Altered dynamic functional network connectivity within default mode network of epileptic children with generalized tonic-clonic seizures

OBJECTIVE

Generalized tonic-clonic seizures (GTCS) is a group of epileptic disorders characterized by widespread generalized spike-and-waves discharges along with unresponsiveness and convulsions. Abnormal connectivity in the DMN is the common findings in children with generalized epilepsy. However, the neural mechanisms underlying the altered brain connectivity of DMN in children with GTCS remain unclear. The aim of the current study was to explore the temporal properties of functional connectivity states by dynamic functional connectivity (dFC) within the DMN of GTCS children.

METHODS

We collected resting-state functional MRI data from 22 GTCS children and 29 age-matched healthy controls. Sliding window approach and k-mean clustering analysis were applied to analyze the dFC and identify transient states of the DMN. Furthermore, the relationship between the dynamic properties and clinical features was assessed.

RESULTS

The dFC analyses identified two reoccurring states: a more frequent and weak connected state (State 1) and a less frequent and strong connected state (State 2). Relative to the normal control, GTCS children spent more time in State 1 showing weak connections and spent less time in State 2 showing strong connections. Dynamic functional network connectivity strength within the DMN showed both increase and decrease in patient group. In addition, the changes of dynamic metric were found to be correlated with epilepsy duration.

SIGNIFICANT

Our findings imply abnormal interactions and the state dynamics in DMN of the children with GTCS. These disruptions of temporal dynamic in DMN may provide significance for understanding the neural mechanism underlying the GTCS in children and suggest that dFC method can be considered as a valuable tool in children with epilepsy.

Impaired Functional Homotopy and Topological Properties Within the Default Mode Network of Children With Generalized Tonic-Clonic Seizures: A Resting-State fMRI Study

Introduction

The aim of the present study was to examine interhemispheric functional connectivity (FC) and topological organization within the default-mode network (DMN) in children with generalized tonic-clonic seizures (GTCS).

Methods

Resting-state functional MRI was collected in 24 children with GTCS and 34 age-matched typically developing children (TDC). Between-group differences in interhemispheric FC were examined by an automated voxel-mirrored homotopic connectivity (VMHC) method. The topological properties within the DMN were also analyzed using graph theoretical approaches. Consistent results were detected and the VMHC values were extracted as features in machine learning for subject classification.

Results

Children with GTCS showed a significant decrease in VMHC in the DMN, including the hippocampal formation (HF), lateral temporal cortex (LTC), and angular and middle frontal gyrus. Although the patients exhibited efficient small-world properties of the DMN similar to the TDC, significant changes in regional topological organization were found in the patients, involving the areas of the bilateral temporal parietal junction, bilateral LTC, left temporal pole, and HF. Within the DMN, disrupted interhemispheric FC was found between the bilateral HF and LTC, which was consistent with the VMHC results. The VMHC values in bilateral HF and LTC were significantly correlated with clinical information in patients. Support vector machine analysis using average VMHC information in the bilateral HF and LTC as features achieved a correct classification rate of 89.34% for the classification.

Conclusion

These results indicate that decreased homotopic coordination in the DMN can be used as an effective biomarker to reflect seizure effects and to distinguish children with GTCSs from TDC.

Abnormal Dynamic Functional Connectivity in Patients With End-Stage Renal Disease

Dynamic functional connectivity (FC) analysis can capture time-varying properties of connectivity; however, studies focusing on dynamic FC in patients with end-stage renal disease (ESRD) are very limited. This is the first study to explore the dynamic aspects of whole-brain FC and topological properties in ESRD patients. Resting-state functional magnetic resonance imaging data were acquired from 100 ESRD patients [50 hemodialysis (HD) patients and 50 non-dialysis patients] and 64 healthy controls (HCs). Independent component analysis, a sliding-window approach and graph-theory methods were used to study the dynamic FC properties. The intrinsic brain FC were clustered into four configuration states. Compared with HCs, both patient groups spent longer time in State 3, in which decreased FC between subnetworks of the default mode network (DMN) and between the dorsal DMN and language network was observed in these patients, and a further reduction in FC between the DMN subnetworks was found in HD patients compared to non-dialysis patients. The number of transitions and the variability of global and local efficiency progressively decreased from that in HCs to that of non-dialysis patients to that of HD patients. The completion time of Trail Making Test A and Trail Making Test B positively correlated with the mean dwell time of State 3 and negatively correlated with the number of transitions in ESRD patients. Our findings suggest impaired functional flexibility of network connections and state-specific FC disruptions in patients with ESRD, which may underlie their cognitive deficits. HD may have an adverse effect on time-varying FC.

Abnormal Functional Connectivity of Hippocampal Subdivisions in Obstructive Sleep Apnea: A Resting-State Functional Magnetic Resonance Imaging Study

The hippocampus is involved in various cognitive function, including memory. Hippocampal structural and functional abnormalities have been observed in patients with obstructive sleep apnoea (OSA), but the functional connectivity (FC) patterns among hippocampal subdivisions in OSA patients remain unclear. The purpose of this study was to investigate the changes in FC between hippocampal subdivisions and their relationship with neurocognitive function in male patients with OSA. Resting-state fMRI were obtained from 46 male patients with untreated severe OSA and 46 male good sleepers. The hippocampus was divided into anterior, middle, and posterior parts, and the differences in FC between hippocampal subdivisions and other brain regions were determined. Correlation analysis was used to explore the relationships between abnormal FC of hippocampal subdivisions and clinical characteristics in patients with OSA. Our results revealed increased FC in the OSA group between the left anterior hippocampus and left middle temporal gyrus; between the left middle hippocampus and the left inferior frontal gyrus, right anterior central gyrus, and left anterior central gyrus; between the left posterior hippocampus and right middle frontal gyrus; between the right middle hippocampus and left inferior frontal gyrus; and between the right posterior hippocampus and left middle frontal gyrus. These FC abnormalities predominantly manifested in the sensorimotor network, fronto-parietal network, and semantic/default mode network, which are closely related to the neurocognitive impairment observed in OSA patients. This study advances our understanding of the potential pathophysiological mechanism of neurocognitive dysfunction in OSA.

Altered Temporal Variations of Functional Connectivity Associated With Surgical Outcomes in Drug-Resistant Temporal Lobe Epilepsy

Background

Currently, more than one-third of patients with drug-resistant temporal lobe epilepsy (TLE) continue to develop seizures after resection surgery. Dynamic functional network connectivity (DFNC) analyses, capturing temporal properties of functional connectivity during MRI acquisition, may help us identify unfavorable surgical outcomes. The purpose of this work was to explore the association of DFNC variations of preoperative resting-state MRI and surgical outcomes in patients with drug-resistant TLE.

Methods

We evaluated 61 patients with TLE matched for age and gender with 51 healthy controls (HC). Patients with TLE were classified as seizure-free (n = 39) and not seizure-free (n = 16) based on the Engel surgical outcome scale. Six patients were unable to confirm the postoperative status and were not included in the subgroup analysis. The DFNC was calculated using group spatial independent component analysis and the sliding window approach.

Results

Dynamic functional network connectivity analyses suggested two distinct connectivity “States.” The dynamic connectivity state of patients with TLE was different from HC. TLE subgroup analyses showed not seizure-free (NSF) patients spent significantly more time in State II compared to seizure-free (SF) patients and HC. Further, the number of transitions from State II to State I was significantly lower in NSF patients. SF patients had compensatory enhancement of DFNC strengths between default and dorsal attention network, as well as within the default network. While reduced DFNC strengths of within-network and inter-network were both observed in NSF patients, patients with abnormally temporal properties and more extension DFNC strength alterations were less likely to receive seizure freedom.

Conclusions

Our study indicates that DFNC could offer a better understanding of dynamic neural impairment mechanisms of drug-resistant TLE functional network, epileptic brain network reorganization, and provide an additional preoperative evaluation support for surgical treatment of drug-resistant TLE.

Dynamic functional connectivity in modular organization of the hippocampal network marks memory phenotypes in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) is a network disorder with a high incidence of memory impairment. Memory processing ability highly depends on the dynamic coordination between distinct modules within the hippocampal network. Here, we investigate the relationship between memory phenotypes and modular alterations of dynamic functional connectivity (FC) in the hippocampal network in TLE patients. Then, 31 healthy controls and 66 TLE patients with hippocampal sclerosis were recruited. The patients were classified into memory-intact (MI, 35 cases) group and memory-deficit (MD, 31 cases) group, each based on individual's Wechsler Memory Scale-Revised score. The sliding-windows approach and graph theory analysis were used to analyze the hippocampal network based on resting state functional magnetic resonance imaging. Temporal properties and modular metrics were calculated. Two discrete and switchable states were revealed: a high modularized state (State I) and a low modularized state (State II), which corresponded to either anterior or posterior hippocampal network dominated pattern. TLE was prone to drive less State I but more State II, and the tendency was more obvious in TLE-MD. Additionally, TLE-MD showed more widespread alterations of modular properties compared with TLE-MI across two states. Furthermore, the dynamic modularity features had unique superiority in discriminating TLE-MD from TLE-MI. These findings demonstrated that state transitions and modular function of dissociable hippocampal networks were altered in TLE and more importantly, they could reflect different memory phenotypes. The trend revealed potential values of dynamic FC in elucidating the mechanism underlying memory impairments in TLE.

Aberrant dynamic structure-function relationship of rich-club organization in treatment-naïve newly diagnosed juvenile myoclonic epilepsy

Neuroimaging studies have shown that juvenile myoclonic epilepsy (JME) is characterized by impaired brain networks. However, few studies have investigated the potential disruptions in rich‐club organization—a core feature of the brain networks. Moreover, it is unclear how structure–function relationships dynamically change over time in JME. Here, we quantify the anatomical rich‐club organization and dynamic structural and functional connectivity (SC–FC) coupling in 47 treatment‐naïve newly diagnosed patients with JME and 40 matched healthy controls. Dynamic functional network efficiency and its association with SC–FC coupling were also calculated to examine the supporting of structure–function relationship to brain information transfer. The results showed that the anatomical rich‐club organization was disrupted in the patient group, along with decreased connectivity strength among rich‐club hub nodes. Furthermore, reduced SC–FC coupling in rich‐club organization of the patients was found in two functionally independent dynamic states, that is the functional segregation state (State 1) and the strong somatomotor‐cognitive control interaction state (State 5); and the latter was significantly associated with disease severity. In addition, the relationships between SC–FC coupling of hub nodes connections and functional network efficiency in State 1 were found to be absent in patients. The aberrant dynamic SC–FC coupling of rich‐club organization suggests a selective influence of densely interconnected network core in patients with JME at the early phase of the disease, offering new insights and potential biomarkers into the underlying neurodevelopmental basis of behavioral and cognitive impairments observed in JME.

The trait and state negative affect can be separately predicted by stable and variable resting-state functional connectivity

BACKGROUND

Many emotional experiences such as anxiety and depression are influenced by negative affect (NA). NA has both trait and state features, which play different roles in physiological and mental health. Attending to NA common to various emotional experiences and their trait-state features might help deepen the understanding of the shared foundation of related emotional disorders.

METHODS

The principal component of five measures was calculated to indicate individuals' NA level. Applying the connectivity-based correlation analysis, we first identified resting-state functional connectives (FCs) relating to NA in sample 1 (n = 367), which were validated through an independent sample (n = 232; sample 2). Next, based on the variability of FCs across large timescale, we further divided the NA-related FCs into high- and low-variability groups. Finally, FCs in different variability groups were separately applied to predict individuals' neuroticism level (which is assumed to be the core trait-related factor underlying NA), and the change of NA level (which represents the state-related fluctuation of NA).

RESULTS

The low-variability FCs were primarily within the default mode network (DMN) and between the DMN and dorsal attention network/sensory system and significantly predicted trait rather than state NA. The high-variability FCs were primarily between the DMN and ventral attention network, the fronto-parietal network and DMN/sensory system, and significantly predicted the change of NA level.

CONCLUSIONS

The trait and state NA can be separately predicted by stable and variable spontaneous FCs with different attentional processes and emotion regulatory mechanisms, which could deepen our understanding of NA.

Aberrant Volume-Wise and Voxel-Wise Concordance Among Dynamic Intrinsic Brain Activity Indices in Parkinson's Disease: A Resting-State fMRI Study

Researches using resting-state functional magnetic resonance imaging (rs-fMRI) have applied different regional measurements to study the intrinsic brain activity (IBA) of patients with Parkinson's disease (PD). Most previous studies have only examined the static characteristics of IBA in patients with PD, neglecting the dynamic features. We sought to explore the concordance between the dynamics of different rs-fMRI regional indices. This study included 31 healthy controls (HCs) and 57 PD patients to calculate the volume-wise (across voxels) and voxel-wise (across periods) concordance using a sliding time window approach. This allowed us to compare the concordance of dynamic alterations in frequently used metrics such as degree centrality (DC), global signal connectivity (GSC), voxel-mirrored heterotopic connectivity (VMHC), the amplitude of low-frequency fluctuations (ALFF), and regional homogeneity (ReHo). We analyzed the changes of concordance indices in the PD patients and investigated the relationship between aberrant concordance values and clinical/neuropsychological assessments in the PD patients. We found that, compared with the HCs, the PD patients had lower volume concordance in the whole brain and lower voxel-wise concordance in the posterior cerebellar lobe, cerebellar tonsils, superior temporal gyrus, and supplementary motor region. We also found negative correlations between these concordance alterations and patients' age. The exploratory results contribute to a better understanding of IBA alterations and pathophysiological mechanisms in PD.

Statelets: Capturing recurrent transient variations in dynamic functional network connectivity

Dynamic functional network connectivity (dFNC) analysis is a widely used approach for capturing brain activation patterns, connectivity states, and network organization. However, a typical sliding window plus clustering (SWC) approach for analyzing dFNC models the system through a fixed sequence of connectivity states. SWC assumes connectivity patterns span throughout the brain, but they are relatively spatially constrained and temporally short‐lived in practice. Thus, SWC is neither designed to capture transient dynamic changes nor heterogeneity across subjects/time. We propose a state‐space time series summarization framework called “statelets” to address these shortcomings. It models functional connectivity dynamics at fine‐grained timescales, adapting time series motifs to changes in connectivity strength, and constructs a concise yet informative representation of the original data that conveys easily comprehensible information about the phenotypes. We leverage the earth mover distance in a nonstandard way to handle scale differences and utilize kernel density estimation to build a probability density profile for local motifs. We apply the framework to study dFNC of patients with schizophrenia (SZ) and healthy control (HC). Results demonstrate SZ subjects exhibit reduced modularity in their brain network organization relative to HC. Statelets in the HC group show an increased recurrence across the dFNC time‐course compared to the SZ. Analyzing the consistency of the connections across time reveals significant differences within visual, sensorimotor, and default mode regions where HC subjects show higher consistency than SZ. The introduced approach also enables handling dynamic information in cross‐modal and multimodal applications to study healthy and disordered brains.

The temporal dedifferentiation of global brain signal fluctuations during human brain ageing

The variation of brain functions as healthy ageing has been discussed widely using resting-state brain imaging. Previous conclusions may be misinterpreted without considering the effects of global signal (GS) on local brain activities. Up to now, the variation of GS with ageing has not been estimated. To fill this gap, we defined the GS as the mean signal of all voxels in the gray matter and systematically investigated correlations between age and indices of GS fluctuations. What's more, these tests were replicated with data after hemodynamic response function (HRF) de-convolution and data without noise regression as well as head motion data to verify effects of non-neural information on age. The results indicated that GS fluctuations varied as ageing in three ways. First, GS fluctuations were reduced with age. Second, the GS power transferred from lower frequencies to higher frequencies with age. Third, the GS power was more evenly distributed across frequencies in ageing brain. These trends were partly influenced by HRF and physiological noise, indicating that the age effects of GS fluctuations are associated with a variety of physiological activities. These results may indicate the temporal dedifferentiation hypothesis of brain ageing from the global perspective.

Abnormal regional spontaneous brain activities in white matter in patients with autism spectrum disorder

Previous studies have demonstrated patients with autism spectrum disorder (ASD) are accompanied by alterations of spontaneous brain activity in gray matter. However, whether the alterations of spontaneous brain activity exist in white matter remains largely unclear. In this study, 88 ASD patients and 87 typical controls (TCs) were included and regional homogeneity (ReHo) was calculated to characterize spontaneous brain activity in white matter. Voxel-wise two-sample t-tests were performed to investigate ReHo alterations, and cluster-level analyses were conducted to examine structural-functional coupling changes. Compared with TCs, the ASD group showed significantly decreased ReHo in the left superior corona radiata and left posterior limb of internal capsule, and decreased ReHo in the left anterior corona radiata with a trend level of significance. In addition, significantly weaker structural-functional coupling was observed in the left superior corona radiata and left posterior limb of internal capsule in ASD patients. Taken together, these findings highlighted abnormalities of white matter's regional spontaneous brain activity in ASD, which may provide new insights into the pathophysiological mechanisms of this disorder.

Reconfiguration of Brain Network Dynamics in Autism Spectrum Disorder Based on Hidden Markov Model

Autism spectrum disorder (ASD) is a group of complex neurodevelopment disorders characterized by altered brain connectivity. However, the majority of neuroimaging studies for ASD focus on the static pattern of brain function and largely neglect brain activity dynamics, which might provide deeper insight into the underlying mechanism of brain functions for ASD. Therefore, we proposed a framework with Hidden Markov Model (HMM) analysis for resting-state functional MRI (fMRI) from a large multicenter dataset of 507 male subjects. Specifically, the 507 subjects included 209 subjects with ASD and 298 well-matched health controls across 14 sites from the Autism Brain Imaging Data Exchange (ABIDE). Based on the HMM, we can identify the recurring brain function networks over time across ASD and healthy controls (HCs). Then we assessed the dynamical configuration of the whole-brain networks and further analyzed the community structure of transitions across the brain states. Based on the 19 HMM states, we found that the global temporal statistics of the specific HMM states (including fractional occupancies and lifetimes) were significantly altered in ASD compared to HCs. These specific HMM states were characterized by the activation pattern of default mode network (DMN), sensory processing networks [including visual network, auditory network, and sensory and motor network (SMN)]. Meanwhile, we also find that the specific modules of transitions between states were closely related to ASD. Our findings indicate the temporal reconfiguration of the brain network in ASD and provide novel insights into the dynamics of the whole-brain networks for ASD.

Hyperintensities of middle frontal gyrus in patients with diabetic optic neuropathy: a dynamic amplitude of low-frequency fluctuation study

Diabetic optic neuropathy (DON) is a diverse complication of diabetes and its pathogenesis has not been fully elucidated. The purpose of this study was to explore dynamic cerebral activity changes in DON patients using dynamic amplitude of low-frequency fluctuation (dALFF). In total, 22 DON patients and 22 healthy controls were enrolled. The dALFF approach was used in all participants to investigate dynamic intrinsic brain activity differences between the two groups. Compared with HCs, DON patients exhibited significantly increased dALFF variability in the right middle frontal gyrus (P < 0.01). Conversely, DON patients exhibited obviously decreased dALFF variability in the right precuneus (P < 0.01). We also found that there were significant negative correlations between HADS scores and dALFF values of the right middle frontal gyrus in the DON patients (r = -0.6404, P <0.01 for anxiety and r = -0.6346, P <0.01 for depression; HADS, Hospital Anxiety and Depression Scale). Abnormal variability of dALFF was observed in specific areas of the cerebrum in DON patients, which may contribute to distinguishing patients with DON from HCs and a better understanding of DON, hyperintensities of right middle frontal gyrus may be potential diagnostic marker for DON.

Acupuncture Treatment Decreased Temporal Variability of Dynamic Functional Connectivity in Chronic Tinnitus

Acupuncture is recommended for the relief of chronic tinnitus in traditional Chinese medicine, but the underlying neural mechanism remains unclear. The human brain is a dynamic system, and it’s unclear about acupuncture’s effects on the dynamic functional connectivity (DFC) of chronic tinnitus. Therefore, this study based on resting-state functional magnetic resonance imaging (fMRI) investigates abnormal DFC in chronic tinnitus patients and the neural activity change evoked by acupuncture treatment for tinnitus. In this study, 17 chronic tinnitus patients and 22 age- and sex-matched normal subjects were recruited, and their tinnitus-related scales and hearing levels were collected. The fMRI data were measured before and after acupuncture, and then sliding-window and k-means clustering methods were used to calculate DFC and perform clustering analysis, respectively. We found that, compared with the normal subjects, chronic tinnitus patients had higher temporal variability of DFC between the supplementary motor area and medial part of the superior frontal gyrus, and it positively correlated with hearing loss. Clustering analysis showed higher transition probability (TP) between connection states in chronic tinnitus patients, and it was positively correlated with tinnitus severity. Furthermore, the findings showed that acupuncture treatment might improve tinnitus. DFC between the posterior cingulate gyrus and angular gyrus in chronic tinnitus patients after acupuncture showed significantly decreased, and it positively correlated with the improvement of tinnitus. Clustering analysis showed that acupuncture treatment might promote chronic tinnitus patients under lower DFC state, and it also positively correlated with the improvement of tinnitus. This study suggests that acupuncture as an alternative therapy method might decrease the tinnitus severity by decreasing the time variability of DFC in chronic tinnitus patients.

Intrinsic Brain Activity in Temporal Lobe Epilepsy With and Without Depression: Insights From EEG Microstates

Background: Depression is the most common psychiatric comorbidity of temporal lobe epilepsy (TLE). In the recent years, studies have focused on the common pathogenesis of TLE and depression. However, few of the studies focused on the dynamic characteristics of TLE with depression. We tested the hypotheses that there exist abnormalities in microstates in patients with TLE with depression.

Methods: Participants were classified into patients with TLE with depression (PDS) (n = 19) and patients with TLE without depression (nPDS) (n = 19) based upon the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V). Microstate analysis was applied based on 256-channel electroencephalography (EEG) to detect the dynamic changes in whole brain. The coverage (proportion of time spent in each state), frequency of occurrence, and duration (average time of each state) were calculated.

Results: Patients with PDS showed a shorter mean microstate duration with higher mean occurrence per second compared to patients with nPDS. There was no difference between the two groups in the coverage of microstate A–D.

Conclusion: This is the first study to present the temporal fluctuations of EEG topography in comorbid depression in TLE using EEG microstate analysis. The temporal characteristics of the four canonical EEG microstates were significantly altered in patients with TLE suffer from comorbid depression.

Dynamic Alterations of Functional Connectivity and Amplitude of Low-Frequency Fluctuations in Patients with Unilateral Sudden Sensorineural Hearing Loss

Unilateral sudden sensorineural hearing loss (SSNHL) adversely affects the quality of life, leading to increased risk of depression and cognitive decline. Our previous studies have mainly focused on the static brain function abnormalities in SSNHL patients. However, the dynamic features of brain activity in SSNHL patients are not elucidated. To explore the dynamic brain functional alterations in SSNHL patients, age- and sex- matched SSNHL patients (n=38) and healthy controls (HC, n=44) were enrolled. The dynamic functional connectivity (dFC) and dynamic amplitude of low-frequency fluctuation (dALFF) methods were used to compare the temporal features and dynamic neural activity between the two groups. In dFC analyses, the multiple functional connectivities (FCs) were clustered into 2 different states; a greater proportion of FCs in SSNHL patients showed sparse state compared with HC. In dALFF analyses, SSNHL individuals exhibited decreased dALFF variability in bilateral inferior occipital gyrus, middle occipital gyrus, calcarine, right lingual gyrus, and right fusiform gyrus. dALFF variability showed a negative correlation with activated partial thromboplatin time. The dynamic characteristics of SSNHL patients were different from static functional connectivity and static amplitude of low-frequency fluctuation, especially within the visual cortices. These findings suggest that SSNHL patients experience cross-modal plasticity and visual compensation, which may be closely related to the pathophysiology of SSNHL.

Dynamic Functional Connectivity Alterations and Their Associated Gene Expression Pattern in Autism Spectrum Disorders

Autism spectrum disorders (ASDs) are a group of heterogeneous neurodevelopmental disorders that are highly heritable and are associated with impaired dynamic functional connectivity (DFC). However, the molecular mechanisms behind DFC alterations remain largely unknown. Eighty-eight patients with ASDs and 87 demographically matched typical controls (TCs) from the Autism Brain Imaging Data Exchange II database were included in this study. A seed-based sliding window approach was then performed to investigate the DFC changes in each of the 29 seeds in 10 classic resting-state functional networks and the whole brain. Subsequently, the relationships between DFC alterations in patients with ASDs and their symptom severity were assessed. Finally, transcription-neuroimaging association analyses were conducted to explore the molecular mechanisms of DFC disruptions in patients with ASDs. Compared with TCs, patients with ASDs showed significantly increased DFC between the right dorsolateral prefrontal cortex (DLPFC) and left fusiform/lingual gyrus, between the DLPFC and the superior temporal gyrus, between the right frontal eye field (FEF) and left middle frontal gyrus, between the FEF and the right angular gyrus, and between the left intraparietal sulcus and the right middle temporal gyrus. Moreover, significant relationships between DFC alterations and symptom severity were observed. Furthermore, the genes associated with DFC changes in ASDs were identified by performing gene-wise across-sample spatial correlation analysis between gene expression extracted from six donors’ brain of the Allen Human Brain Atlas and case-control DFC difference. In enrichment analysis, these genes were enriched for processes associated with synaptic signaling and voltage-gated ion channels and calcium pathways; also, these genes were highly expressed in autistic disorder, chronic alcoholic intoxication and several disorders related to depression. These results not only demonstrated higher DFC in patients with ASDs but also provided novel insight into the molecular mechanisms underlying these alterations.

Altered temporal reachability highlights the role of sensory perception systems in major depressive disorder

BACKGROUND

The latest studies have considered the time-dependent structures in dynamic brain networks. However, the effect of periphery structures on the temporal flow of information remains unexplored in patients with major depressive disorder (MDD). In this work, we aimed to explore the pattern of interactions between brain regions in MDD across space and time.

METHODS

We concentrated on the temporal reachability of nodes in temporal brain networks derived from the resting-state functional magnetic resonance imaging (rs-fMRI) of 55 MDD patients and 62 sex-, age-matched healthy controls. Specifically, temporal connectedness and temporal efficiency (TEF) were estimated based on the length of temporal paths between node pairs. Subsequently, the temporal clustering coefficient (TCC) and temporal distance were jointly employed to explore the patterns in which a node's periphery structure affects its reachability.

RESULTS

Significantly higher TEF and lower TCC were found in temporal brain networks in MDD. Besides, significant between-group differences of nodal TCC were detected in regions of sensory perception systems. Considering the temporal paths that begin or end at these regions, MDD patients showed several altered temporal distances.

CONCLUSION

Our results showed that the temporal reachability of specific brain regions in MDD could be affected as their periphery structures evolve, which may explain the dysfunction of sensory perception systems in the spatiotemporal domain.

Alterations of Static and Dynamic Functional Connectivity of the Nucleus Accumbens in Patients With Major Depressive Disorder

BACKGROUND

Major depressive disorder (MDD) is associated with dysfunction of the reward system. As an important node in the reward system, the resting-state functional connectivity of the nucleus accumbens (NAc) is related to the etiology of MDD. However, an increasing number of recent studies propose that brain activity is dynamic over time, no study to date has examined whether the NAc dynamic functional connectivity (DFC) is changed in patients with MDD. Moreover, few studies have examined the impact of the clinical characteristics of patients with MDD.

METHODS

A total of 220 MDD patients and 159 healthy controls (HCs), group-matched for age, sex, and education level, underwent resting-state functional magnetic resonance imagining (rs-fMRI) scans. Seed-based resting-state functional connectivity (RSFC) and DFC of the NAc were conducted. Two sample t-tests were performed to alter RSFC/DFC of NAc. In addition, we examined the association between altered RSFC/DFC and depressive severity using Pearson correlation. Finally, we divided patients with MDD into different subgroups according to clinical characteristics and tested whether there were differences between the subgroups.

RESULTS

Compared with the HCs, MDD patients show reduced the NAc-based RSFC with the dorsolateral prefrontal cortex (DLPFC), hippocampus, middle temporal gyrus (MTG), inferior temporal gyrus (ITG), precuneus, and insula, and patients with MDD show reduced the NAc-based DFC with the DLPFC, ventromedial prefrontal cortex (VMPFC), ventrolateral prefrontal cortex (VLPFC), MTG, ITG, and insula. MDD severity was associated with RSFC between the NAc and precentral gyrus (r = 0.288, p = 0.002, uncorrected) and insula (r = 0.272, p = 0.003, uncorrected).

CONCLUSION

This study demonstrates abnormal RSFC and DFC between the NAc and distributed cerebral regions in MDD patients, characterized by decreased RSFC and DFC of the NAc connecting with the reward, executive, default-mode, and salience network. Our results expand previous descriptions of the NAc RSFC abnormalities in MDD, and the altered RSFC/DFC may reflect the disrupted function of the NAc.

Virtual Adversarial Training-Based Deep Feature Aggregation Network From Dynamic Effective Connectivity for MCI Identification

Dynamic functional connectivity (dFC) network inferred from resting-state fMRI reveals macroscopic dynamic neural activity patterns for brain disease identification. However, dFC methods ignore the causal influence between the brain regions. Furthermore, due to the complex non-Euclidean structure of brain networks, advanced deep neural networks are difficult to be applied for learning high-dimensional representations from brain networks. In this paper, a group constrained Kalman filter (gKF) algorithm is proposed to construct dynamic effective connectivity (dEC), where the gKF provides a more comprehensive understanding of the directional interaction within the dynamic brain networks than the dFC methods. Then, a novel virtual adversarial training convolutional neural network (VAT-CNN) is employed to extract the local features of dEC. The VAT strategy improves the robustness of the model to adversarial perturbations, and therefore avoids the overfitting problem effectively. Finally, we propose the high-order connectivity weight-guided graph attention networks (cwGAT) to aggregate features of dEC. By injecting the weight information of high-order connectivity into the attention mechanism, the cwGAT provides more effective high-level feature representations than the conventional GAT. The high-level features generated from the cwGAT are applied for binary classification and multiclass classification tasks of mild cognitive impairment (MCI). Experimental results indicate that the proposed framework achieves the classification accuracy of 90.9%, 89.8%, and 82.7% for normal control (NC) vs. early MCI (EMCI), EMCI vs. late MCI (LMCI), and NC vs. EMCI vs. LMCI classification respectively, outperforming the state-of-the-art methods significantly.

Altered Dynamic Functional Connectivity in Subcortical Ischemic Vascular Disease With Cognitive Impairment

Subcortical ischemic vascular disease (SIVD) can cause cognitive impairment and affect the static functional connectivity of resting functional magnetic resonance imaging (fMRI). Numerous previous studies have demonstrated that functional connectivities (FCs) fluctuate dynamically over time. However, little is known about the impact of cognitive impairment on brain dynamic functional connectivity (DFC) in SIVD patients with MCI. In the present study, the DFC analysis method was applied to the resting functional magnetic resonance imaging (fMRI) data of 37 SIVD controls (SIVD-Control) without cognitive impairment, 34 SIVD patients with amnestic MCI (SIVD-aMCI) and 30 SIVD patients with nonamnestic MCI (SIVD-naMCI). The results indicated that the cognitive impairment of SIVD mainly reduced the mean dwell time of State 3 with overall strong positive connections. The reduction degree of SIVD-aMCI was larger than that of SIVD-naMCI. The memory/execution function impairment of SIVD also changed the relationship between the mean dwell time of State 3 and the behavioral performance of the memory/execution task from significant to non-significant correlation. Moreover, SIVD-aMCI showed significantly lower system segregation of FC states than SIVD-Control and SIVD-naMCI. The system segregation of State 5 with overall weak connections was significantly positive correlated with the memory performance. The results may suggest that the mean dwell time of State 3 and the system segregation of State 5 may be used as important neural measures of cognitive impairments of SIVD.

Disrupted Functional Connectivity Within and Between Resting-State Networks in the Subacute Stage of Post-stroke Aphasia

Background: Post-stroke aphasia (PSA) results from brain network disorders caused by focal stroke lesions. However, it still remains largely unclear whether the impairment is present in intra- and internetwork functional connectivity (FC) within each resting-state network (RSN) and between RSNs in the subacute stage of PSA.

Objectives: This study aimed to investigate the resting-state FC within and between RSNs in patients with PSA and observe the relationships between FC alterations and Western Aphasia Battery (WAB) measures.

Methods: A total of 20 individuals with subacute PSA and 20 healthy controls (HCs) were recruited for functional MRI (fMRI) scanning, and only patients with PSA underwent WAB assessment. Independent component analysis was carried out to identify RSNs. Two-sample t-tests were used to calculate intra- and internetwork FC differences between patients with PSA and HCs. The results were corrected for multiple comparisons using the false discovery rate (FDR correction, p < 0.05). Partial correlation analysis was performed to observe the relationship between FC and WAB scores with age, gender, mean framewise displacement, and lesion volume as covariates (p < 0.05).

Results: Compared to HCs, patients with PSA showed a significant increase in intranetwork FC in the salience network (SN). For internetwork FC analysis, patients showed a significantly increased coupling between left frontoparietal network (lFPN) and SN and decreased coupling between lFPN and right frontoparietal network (rFPN) as well as between lFPN and posterior default mode network (pDMN) (FDR correction, p < 0.05). Finally, a significant positive correlation was found between the intergroup difference of FC (lFPN-rFPN) and auditory-verbal comprehension (p < 0.05).

Conclusion: Altered FC was revealed within and between multiple RSNs in patients with PSA at the subacute stage. Reduced FC between lFPN and rFPN was the key element participating in language destruction. These findings proved that PSA is a brain network disorder caused by focal lesions; besides, it may improve our understanding of the pathophysiological mechanisms of patients with PSA at the subacute stage.

Altered executive control network connectivity in anti-NMDA receptor encephalitis

Objective

The goal of this study was to examine whether the static functional connectivity (FC) of the executive control network (ECN) and the temporal properties of dynamic FC states in the ECN can characterize the underlying nature of anti‐N‐methyl‐d‐aspartate (anti‐NMDA) receptor encephalitis and their correlations with cognitive functions.

Methods

In total, 21 patients with anti‐NMDA receptor encephalitis past the acute stage and 23 healthy controls (HCs) underwent a set of neuropsychological tests and participated in a resting‐state fMRI study to analyse the static FC of the ECN and the temporal properties of dynamic FC states in the ECN. In addition, correlation analyses were performed to determine the correlations between the FC metrics and cognitive performance.

Results

Patients with anti‐NMDA receptor encephalitis past the acute stage showed significant cognitive impairments compared to HCs. In accord with the results of neuropsychological tests, static intrinsic FC alterations and changed dynamic FC metrics of ECN were observed in the patients. Importantly, we observed significant correlations between altered ECN metrics and working memory, information processing speed, executive function performance in the patients.

Interpretation

Our findings suggest that cognitive impairments in patients with anti‐NMDA receptor encephalitis past the acute stage are likely related to altered static and dynamic ECN connectivity. These observations may enhance our understanding of the pathophysiological mechanisms underlying cognitive function in this population.

Test-retest reliability of dynamic functional connectivity in naturalistic paradigm functional magnetic resonance imaging

Dynamic functional connectivity (dFC) has been increasingly used to characterize the brain transient temporal functional patterns and their alterations in diseased brains. Meanwhile, naturalistic neuroimaging paradigms have been an emerging approach for cognitive neuroscience with high ecological validity. However, the test–retest reliability of dFC in naturalistic paradigm neuroimaging is largely unknown. To address this issue, we examined the test–retest reliability of dFC in functional magnetic resonance imaging (fMRI) under natural viewing condition. The intraclass correlation coefficients (ICC) of four dFC statistics including standard deviation (Std), coefficient of variation (COV), amplitude of low frequency fluctuation (ALFF), and excursion (Excursion) were used to measure the test–retest reliability. The test–retest reliability of dFC in naturalistic viewing condition was then compared with that under resting state. Our experimental results showed that: (a) Global test–retest reliability of dFC was much lower than that of static functional connectivity (sFC) in both resting‐state and naturalistic viewing conditions; (b) Both global and local (including visual, limbic and default mode networks) test–retest reliability of dFC could be significantly improved in naturalistic viewing condition compared to that in resting state; (c) There existed strong negative correlation between sFC and dFC, weak negative correlation between dFC and dFC‐ICC (i.e., ICC of dFC), as well as weak positive correlation between dFC‐ICC and sFC‐ICC (i.e., ICC of sFC). The present study provides novel evidence for the promotion of naturalistic paradigm fMRI in functional brain network studies.

Prefrontal-limbic-striatum dysconnectivity associated with negative emotional endophenotypes in bipolar disorder during depressive episodes

BACKGROUND

The prefrontal-limbic-subcortical network has been suggested as an important circuitry in the pathophysiology underlying bipolar disorder during depressive episodes (BDD). However, the relationships between disrupted prefrontal-limbic-subcortical connection and the emotional endophenotypes in BDD patients remain largely unclear.

METHODS

Forty-three BDD patients and 63 matched healthy controls (HCs) underwent the resting-state functional magnetic resonance imaging scan. The altered clusters were first identified by using a spatial pairwise clustering method and then were extracted as regions of interest to calculate the functional connectivity (FC). Group comparisons were conducted to identify the abnormal FCs. Classification analysis was employed to examine whether the altered FCs could distinguish BDD from HCs. The relationships between FC alterations and the emotional endophenotypes as measured by the Affective Neuroscience Personality Scales (ANPS) were further detected in BDD.

RESULTS

Compared with HCs, BDD patients showed abnormal FCs in the prefrontal-limbic-striatum circuit. Importantly, the altered FCs yielded 84.91% accuracy (p< 1/5000) with 93.65% sensitivity and 72.09% specificity in differentiating between BDD and HCs. Moreover, the decreased FCs in the prefrontal-striatum and prefrontal-limbic systems were positively correlated with negative emotional endophenotypes of Sadness and Fear scores.

CONCLUSIONS

The findings demonstrated that prefrontal-limbic-striatum disconnection may be identified as a potential effective biomarker for BDD, which could help further explain the neurobiological mechanisms underlying BDD.

Probabilistic mapping of thalamic nuclei and thalamocortical functional connectivity in idiopathic generalised epilepsy

It is well established that abnormal thalamocortical systems play an important role in the generation and maintenance of primary generalised seizures. However, it is currently unknown which thalamic nuclei and how nuclear‐specific thalamocortical functional connectivity are differentially impacted in patients with medically refractory and non‐refractory idiopathic generalised epilepsy (IGE). In the present study, we performed structural and resting‐state functional magnetic resonance imaging (MRI) in patients with refractory and non‐refractory IGE, segmented the thalamus into constituent nuclear regions using a probabilistic MRI segmentation method and determined thalamocortical functional connectivity using seed‐to‐voxel connectivity analyses. We report significant volume reduction of the left and right anterior thalamic nuclei only in patients with refractory IGE. Compared to healthy controls, patients with refractory and non‐refractory IGE had significant alterations of functional connectivity between the centromedian nucleus and cortex, but only patients with refractory IGE had altered cortical connectivity with the ventral lateral nuclear group. Patients with refractory IGE had significantly increased functional connectivity between the left and right ventral lateral posterior nuclei and cortical regions compared to patients with non‐refractory IGE. Cortical effects were predominantly located in the frontal lobe. Atrophy of the anterior thalamic nuclei and resting‐state functional hyperconnectivity between ventral lateral nuclei and cerebral cortex may be imaging markers of pharmacoresistance in patients with IGE. These structural and functional abnormalities fit well with the known importance of thalamocortical systems in the generation and maintenance of primary generalised seizures, and the increasing recognition of the importance of limbic pathways in IGE.

A systematic review of resting-state and task-based fmri in juvenile myoclonic epilepsy

Functional neuroimaging modalities have enhanced our understanding of juvenile myoclonic epilepsy (JME) underlying neural mechanisms. Due to its non-invasive, sensitive and analytical nature, functional magnetic resonance imaging (fMRI) provides valuable insights into relevant functional brain networks and their segregation and integration properties. We systematically reviewed the contribution of resting-state and task-based fMRI to the current understanding of the pathophysiology and the patterns of seizure propagation in JME Altogether, despite some discrepancies, functional findings suggest that corticothalamo-striato-cerebellar network along with default-mode network and salience network are the most affected networks in patients with JME. However, further studies are required to investigate the association between JME's main deficiencies, e.g., motor and cognitive deficiencies and fMRI findings. Moreover, simultaneous electroencephalography-fMRI (EEG-fMRI) studies indicate that alterations of these networks play a role in seizure modulation but fall short of identifying a causal relationship between altered functional properties and seizure propagation. This review highlights the complex pathophysiology of JME, which necessitates the design of more personalized diagnostic and therapeutic strategies in this group.

Classification of Obsessive-Compulsive Disorder Using Distance Correlation on Resting-State Functional MRI Images

Both the Pearson correlation and partial correlation methods have been widely used in the resting-state functional MRI (rs-fMRI) studies. However, they can only measure linear relationship, although partial correlation excludes some indirect effects. Recent distance correlation can discover both the linear and non-linear dependencies. Our goal was to use the multivariate pattern analysis to compare the ability of such three correlation methods to distinguish between the patients with obsessive-compulsive disorder (OCD) and healthy control subjects (HCSs), so as to find optimal correlation method. The main process includes four steps. First, the regions of interest are defined by automated anatomical labeling (AAL). Second, functional connectivity (FC) matrices are constructed by the three correlation methods. Third, the best discriminative features are selected by support vector machine recursive feature elimination (SVM-RFE) with a stratified N-fold cross-validation strategy. Finally, these discriminative features are used to train a classifier. We had a total of 128 subjects out of which 61 subjects had OCD and 67 subjects were normal. All the three correlation methods with SVM have achieved good results, among which distance correlation is the best [accuracy = 93.01%, specificity = 89.71%, sensitivity = 95.08%, and area under the receiver-operating characteristic curve (AUC) = 0.94], followed by Pearson correlation and partial correlation is the last. The most discriminative regions of the brain for distance correlation are right dorsolateral superior frontal gyrus, orbital part of left superior frontal gyrus, orbital part of right middle frontal gyrus, right anterior cingulate and paracingulate gyri, left the supplementary motor area, and right precuneus, which are the promising biomarkers of OCD.

Alterations of Regional Homogeneity in Children With Congenital Sensorineural Hearing Loss: A Resting-State fMRI Study

Background: Brain functional alterations have been observed in children with congenital sensorineural hearing loss (CSNHL). The purpose of this study was to assess the alterations of regional homogeneity in children with CSNHL.

Methods: Forty-five children with CSNHL and 20 healthy controls were enrolled into this study. Brain resting-state functional MRI (rs-fMRI) for regional homogeneity including the Kendall coefficient consistency (KCC-ReHo) and the coherence-based parameter (Cohe-ReHo) was analyzed and compared between the two groups, i.e., the CSNHL group and the healthy control group.

Results: Compared to the healthy controls, children with CSNHL showed increased Cohe-ReHo values in left calcarine and decreased values in bilateral ventrolateral prefrontal cortex (VLPFC) and right dorsolateral prefrontal cortex (DLPFC). Children with CSNHL also had increased KCC-ReHo values in the left calcarine, cuneus, precentral gyrus, and right superior parietal lobule (SPL) and decreased values in the left VLPFC and right DLPFC. Correlations were detected between the ReHo values and age of the children with CSNHL. There were positive correlations between ReHo values in the pre-cuneus/pre-frontal cortex and age (p < 0.05). There were negative correlations between ReHo values in bilateral temporal lobes, fusiform gyrus, parahippocampal gyrus and precentral gyrus, and age (p < 0.05).

Conclusion: Children with CSNHL had RoHo alterations in the auditory, visual, motor, and other related brain cortices as compared to the healthy controls with normal hearing. There were significant correlations between ReHo values and age in brain regions involved in information integration and processing. Our study showed promising data using rs-fMRI ReHo parameters to assess brain functional alterations in children with CSNHL.

Altered Brain Functional Connectivity at Resting-State in Patients With Non-arteritic Anterior Ischemic Optic Neuropathy

Purpose: To investigate the possible changes in functional connectivity (FC) in patients with non-arteritic anterior ischemic optic neuropathy (NAION) using resting-state functional MRI (fMRI).

Methods: Thirty-one NAION patients and 31 healthy controls were recruited and underwent resting-state fMRI scans. Regions of interest (ROIs) were defined as bilateral Brodmann’s area 17 (BA17). FC analysis was performed between the ROIs and the rest of the brain regions, and the between group comparisons of FC were performed. We conducted correlation analysis between the FC changes and the clinical variables in NAION patients.

Results: Compared with healthy controls, patients with NAION showed significantly decreased FC between the left BA17 and the right inferior frontal gyrus, left caudate nucleus. As for the right BA17, patients exhibited significantly increased FC with the left olfactory gyrus and decreased FC with the right superior frontal gyrus (SFG), right insula. Moreover, FC values between the right insula and the right BA17 were positively correlated with the right side of mean sensitivity in the central visual field (r = 0.52, P < 0.01) and negatively correlated with the right side of mean defect in the central visual field (r = −0.55, P < 0.01).

Conclusion: Our study indicated that patients with NAION showed significantly abnormal functional reorganization between the primary visual cortex and several other brain regions not directly related to visual function, which supports that NAION may not only be an ophthalmic disease but also a neuro-ophthalmological disease.

Reconfiguration of Dynamic Functional Connectivity States in Patients With Lifelong Premature Ejaculation

Purpose: Neuroimaging has demonstrated altered static functional connectivity in patients with premature ejaculation (PE), while studies examining dynamic changes in spontaneous brain activity in PE patients are still lacking. We aimed to explore the reconfiguration of dynamic functional connectivity (DFC) states in lifelong PE (LPE) patients and to distinguish LPE patients from normal controls (NCs) using a machine learning method based on DFC state features. Methods: Thirty-six LPE patients and 23 NCs were recruited. Resting-state functional magnetic resonance imaging (fMRI) data, the clinical rating scores on the Chinese Index of PE (CIPE), and intravaginal ejaculatory latency time (IELT) were collected from each participant. DFC was calculated by the sliding window approach. Finally, the Lagrangian support vector machine (LSVM) classifier was applied to distinguish LPE patients from NCs using the DFC parameters. Two DFC state metrics (reoccurrence times and transition frequencies) were introduced and we assessed the correlations between DFC state metrics and clinical variables, and the accuracy, sensitivity, and specificity of the LSVM classifier. Results: By k-means clustering, four distinct DFC states were identified. The LPE patients showed an increase in the reoccurrence times for state 3 (p < 0.05, Bonferroni corrected) but a decrease for state 1 (p < 0.05, Bonferroni corrected) compared to the NCs. Moreover, the LPE patients had significantly less frequent transitions between state 1 and state 4 (p < 0.05, uncorrected) while more frequent transitions between state 3 and state 4 (p < 0.05, uncorrected) than the NCs. The reoccurrence times and transition frequencies showed significant associations with the CIPE scores and IELTs. The accuracy, sensitivity, and specificity of the LSVM classifier were 90.35, 87.59, and 85.59%, respectively. Conclusion: LPE patients were more inclined to be in DFC states reinforced intra-network and inter-network connection. These features correlated with clinical syndromes and can classify the LPE patients from NCs. Our results of reconfiguration of DFC states may provide novel insights for the understanding of central etiology underlying LPE, indicate neuroimaging biomarkers for the evaluation of clinical severity of LPE.

Renormalization of Thalamic Sub-Regional Functional Connectivity Contributes to Improvement of Cognitive Function after Liver Transplantation in Cirrhotic Patients with Overt Hepatic Encephalopathy

Objective

The role of preoperative overt hepatic encephalopathy (OHE) in the neurophysiological mechanism of cognitive improvement after liver transplantation (LT) remains elusive. This study aimed to explore changes in sub-regional thalamic functional connectivity (FC) after LT and their relationship with neuropsychological improvement using resting-state functional MRI (rs-fMRI) data in cirrhotic patients with and without a history of OHE.

Materials and Methods

A total of 51 cirrhotic patients, divided into the OHE group (n = 21) and no-OHE group (n = 30), and 30 healthy controls were enrolled in this prospective study. Each patient underwent rs-fMRI before and 1 month after LT. Using 16 bilateral thalamic subregions as seeds, we conducted a seed-to-voxel FC analysis to compare the thalamic FC alterations before and after LT between the OHE and no-OHE groups, as well as differences in FC between the two groups of cirrhotic patients and the control group. Correction for multiple comparisons was conducted using the false discovery rate (p < 0.05).

Results

We found abnormally increased FC between the thalamic sub-region and prefrontal cortex, as well as an abnormally decreased FC between the bilateral thalamus in both OHE and no-OHE cirrhotic patients before LT, which returned to normal levels after LT. Compared with the no-OHE group, the OHE group exhibited more extensive abnormalities prior to LT, and the increased FC between the right thalamic subregions and right inferior parietal lobe was markedly reduced to normal levels after LT.

Conclusion

The renormalization of FC in the cortico-thalamic loop might be a neuro-substrate for the recovery of cognitive function after LT in cirrhotic patients. In addition, hyperconnectivity between thalamic subregions and the inferior parietal lobe might be an important feature of OHE. Changes in FC in the thalamus might be used as potential biomarkers for recovery of cognitive function after LT in cirrhotic patients.

The neural foundation of associative memory: a dynamic functional connectivity study for right-handed young adults

The medial temporal lobe (MTL) is the core neural construction related to associative memory. This study sought to explore the dynamic functional connectivity (dFC) between the subdivisions of MTL and other regions in the whole brain. Additionally, it sought to determine relationships between connectivity stability and associative memory function, to elucidate the neural foundation of associative memory from the perspectives of dFC. A Wechsler Memory Scale China revised edition (WMS-RC) measurement and a resting-state functional magnetic resonance imaging were conducted to clarify adults' function of associative memory and dFC patterns in subdivisions of the MTL. A multiple regression analysis was carried out to analyze the relationships described above. The results demonstrated that (i) connectivity in the left brain included the anterior hippocampus (aHIP) and right fusiform (Fusiform_R), middle hippocampus (mHIP) and right inferior parietal lobule (IPL_R), posterior hippocampus (pHIP) and left inferior parietal lobule (IPL_L), perirhinal cortex (PRC) and left supramarginal gyrus (SMG_L), entorhinal cortex (ERC) and [left middle temporal gyrus (MTG_L), left superior parietal lobule (SPL_L), right fusiform (Fusiform_R)], anterior parahippocampal cortex (aPHC) and right precentral gyrus (PCG_R); (ii) connectivity in the right brain included the aHIP and right supramarginal gyrus (SMG_R), mHIP and left paracentral lobule (PCL_L), pHIP and left superior occipital gyrus (SOG_L), PRC and left middle occipital gyrus (MOG_L), ERC and right middle occipital gyrus (MOG_R); (iii) for most connectivity patterns, the more stable the dFC, the better are the associative memory functions. This study elucidates the neural foundations of associative memory in terms of dFC patterns.

Brain Function Network: Higher Order vs. More Discrimination

Brain functional network (BFN) has become an increasingly important tool to explore individual differences and identify neurological/mental diseases. For estimating a "good" BFN (with more discriminative information for example), researchers have developed various methods, in which the most popular and simplest is Pearson's correlation (PC). Despite its empirical effectiveness, PC only encodes the low-order (second-order) statistics between brain regions. To model high-order statistics, researchers recently proposed to estimate BFN by conducting two sequential PCs (denoted as PC ² in this paper), and found that PC ²-based BFN can provide additional information for group difference analysis. This inspires us to think about (1) what will happen if continuing the correlation operation to construct much higher-order BFN by PC ⁿ (n>2), and (2) whether the higher-order correlation will result in stronger discriminative ability. To answer these questions, we use PC ⁿ -based BFNs to predict individual differences (Female vs. Male) as well as identify subjects with mild cognitive impairment (MCI) from healthy controls (HCs). Through experiments, we have the following findings: (1) with the increase of n, the discriminative ability of PC ⁿ -based BFNs tends to decrease; (2) fusing the PC ⁿ -based BFNs (n>1) with the PC ¹-based BFN can generally improve the sensitivity for MCI identification, but fail to help the classification accuracy. In addition, we empirically find that the sequence of BFN adjacency matrices estimated by PC ⁿ (n = 1,2,3,⋯ ) will converge to a binary matrix with elements of ± 1.

Altered resting-state functional networks in patients with premenstrual syndrome: a graph-theoretical based study

Premenstrual syndrome (PMS) is a menstrual cycle-related disorder. Previous studies have indicated alterations of brain functional connectivity in PMS patients. However, little is known about the overall organization of brain network in PMS patients. Functional magnetic resonance imaging data deriving from 20 PMS patients and 21 healthy controls (HCs). Pearson correlation between mean time-series was used to estimate connectivity matrix between each paired regions of interest, and the connectivity matrix for each participant was then binarized. Graph theory analysis was applied to assess each participant's global and local topological properties of brain functional network. Correlation analysis was performed to evaluate relationships between the daily rating of severity of problems (DRSP) and abnormal network properties. PMS patients had lower small-worldness values than HCs. PMS-related alterations of nodal properties were mainly found in the posterior cingulate cortex, precuneus and angular gyrus. The PMS-related abnormal connectivity components were mainly associated with the thalamus, putamen and middle cingulate cortex. In the PMS group, the DRSP score were negatively correlated with the area under the curves of nodal local efficiency in the posterior cingulate cortex. Our study suggests that the graph-theory method may be one potential tool to detect disruptions of brain connections and may provide important evidence for understanding the PMS from the disrupted network organization perspective.

Abnormal white matter within brain structural networks is associated with high-impulse behaviour in codeine-containing cough syrup dependent users

Codeine-containing cough syrup (CCS) is considered as one of the most popular drug of dependence among adolescents because of its inexpensiveness and easy availability. However, its relationship with neurobiological effects remains sparsely explored. Herein, we examined how high-impulse behaviours relate to changes in the brain structural networks. Forty codeine-containing cough syrup dependent (CCSD) users and age-, gender-, and number of cigarettes smoked per day -matched forty healthy control (HC) subjects underwent structural brain imaging via MRI. High-impulse behaviour was assessed using the 30-item self-rated Barratt Impulsiveness Scale (BIS-11), and structural networks were constructed using diffusion tensor imaging and AAL-90 template. Between-group topological metrics were compared using nonparametric permutations. Benjamin-Hochberg false discovery rate correction was used to correct for multiple comparisons (P < 0.05). The relationships between abnormal network metrics and clinical characteristics of CCS dependent (BIS-11 total score, CCS- dependent duration and mean dose) were examined by Spearman's correlation. Structural networks of the CCSD group demonstrated lower small-world properties than those of the HC group. Abnormal changes in nodal properties among CCSD users were located mainly in the frontal gyrus, inferior parietal lobe and olfactory cortex. NBS analysis further indicated disrupted structural connections between the frontal gyrus and multiple brain regions. There were significant correlations between abnormal nodal properties of the frontal gyrus and clinical characteristics (BIS-11 total score, CCS dependent duration and mean dose) in the CCSD group. These findings suggest that the high-impulse behavioural expression in CCS addiction is associated with widespread brain regions, particularly within those in the frontal cortex. Aberrant brain regions and disrupted connectivity of structural network may be the bases of neuropathology for underlying symptoms of high-impulse behaviours in CCSD users, which may provide a novel sight to better treat and prevent codeine dependency in adolescents.

Altered dynamics of functional connectivity density associated with early and advanced stages of motor training in tennis and table tennis athletes

Until now, knowledge about the effects of motor training on the temporal dynamics of the brain functional organization is still limited. Here we combined dynamic functional connectivity density (dFCD) mapping and k-means clustering analyses to explore how early and advanced stages of motor training affected the brain dynamic FC architecture and dynamic states in little-ball athletes using resting-state functional magnetic resonance imaging (fMRI) data of student-athletes (SA), elite athletes (EA) and non-athlete healthy controls (NC). The ANOVA analysis demonstrated the levels of dFCD variability in the EA group had the trend to regress to the NC group levels in all statistically significant regions. Specifically, the brain regions responsible for the basic motor and sensory innervations showed more stabilized dFCD variability in EA and NC compared with SA. The results supported the idea of a stronger efficiency of functional networks and an automation process of new motor skills in EA. Furthermore, EA and NC had the increased dFCD variability in brain regions responsible for top-down visual-motor control compared with SA; while EA exhibited more flexible alterations in FCD status levels and the equilibrium probability in the long run compared with SA and NC. This suggested that regions involved in higher functions of visual-motor control exhibited more flexibility in functional regulation with other brain networks in EA. Our findings suggested the diversity and specialization of fluctuating dynamic brain adaption induced by motor training in different training stages, and highlighted the effect of motor training stages on brain functional adaption.

Altered static and dynamic functional network connectivity in temporal lobe epilepsy with different disease duration and their relationships with attention

The brain network alterations associated with temporal lobe epilepsy (TLE) progression are still unclear. The purpose of this study was to investigate altered patterns of static and dynamic functional network connectivity (sFNC and dFNC) in TLE with different durations of disease. In this study, 19 TLE patients with a disease duration of ≤5 years (TLE-SD), 24 TLE patients with a disease duration of >5 years (TLE-LD), and 21 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging and attention network test. We used group independent component analysis to determine the target resting-state networks. Sliding window correlation and k-means clustering analysis methods were used to obtain different dFNC states, temporal properties, and temporal variability. We then compared sFNC and dFNC between groups and found that compared with HCs, TLE-SD patients had increased sFNC between the dorsal attention network and sensorimotor network/visual network (VN), but decreased sFNC between the inferior-posterior default mode network and VN. In the strongly connected dFNC state, TLE-SD patients spent more time, had greater mean dwell time, and showed greater inconsistent abnormal network connectivity. There was a significant negative correlation between the temporal variability of auditory network- left fronto-parietal network connectivity and orienting effect. No significant differences in sFNC and dFNC were detected between TLE-LD and HC groups. These findings suggest that the damage and functional brain network abnormalities gradually occur in TLE patients after the onset of epilepsy, which might lead to functional network reorganization and compensatory remodeling as the disease progresses.

Intrinsic Network Brain Dysfunction Correlates With Temporal Complexity in Generalized Anxiety Disorder and Panic Disorder

Background: Generalized anxiety disorder (GAD) and panic disorder (PD) are the two severe subtypes of anxiety disorders (ADs), which are similar in clinical manifestation, pathogenesis, and treatment. Earlier studies have taken a whole-brain perspective on GAD and PD in the assumption that intrinsic fluctuations are static throughout the entire scan. However, it has recently been suggested that the dynamic alternations in functional connectivity (FC) may reflect the changes in macroscopic neural activity patterns underlying the critical aspects of cognition and behavior, and thus may act as biomarkers of disease. Methods: In this study, the resting-state functional MRI (fMRI) data were collected from 26 patients with GAD, 22 patients with PD, and 26 healthy controls (HCs). We investigated dynamic functional connectivity (DFC) by using the group spatial independent component analysis, a sliding window approach, and the k-means clustering methods. For group comparisons, the temporal properties of DFC states were analyzed statistically. Results: The dynamic analysis demonstrated two discrete connectivity "States" across the entire group, namely, a more segregated State I and a strongly integrated State II. Compared with HCs, patients with both GAD and PD spent more time in the weakly within-network State I, while performing fewer transitions and dwelling shorter in the integrated State II. Additionally, the analysis of DFC strength showed that connections associated with ADs were identified including the regions that belonged to default mode (DM), executive control (EC), and salience (SA) networks, especially the connections between SA and DM networks. However, no significant difference was found between the GAD and PD groups in temporal features and connection strength. Conclusions: More common but less specific alterations were detected in the GAD and PD groups, which implied that they might have similar state-dependent neurophysiological mechanisms and, in addition, could hopefully help us better understand their abnormal affective and cognitive performances in the clinic.

Superficial white-matter functional networks changes in bipolar disorder patients during depressive episodes

BACKGROUND

Bipolar disorder is a common psychiatric disorder characterized by insufficient or ineffective connections associated with white-matter (WM) abnormalities. Previous studies have detected the structural attributes of WM using magnetic resonance imaging (MRI) or diffusion tensor imaging, however, they failed to disentangle the dysfunctional organization within the WM.

METHODS

This study aimed to uncover the WM functional connectivity (FC) in 45 bipolar disorder patients during depressive episodes (BDD) and 45 healthy controls based on resting-state functional MRI. Eight WM functional networks were identified by using a clustering analysis of voxel-based correlation profiles, which were further classified into superficial, middle and deep layers of networks.

RESULTS

Group comparisons on the FCs among 8 WM networks showed that the superficial tempofrontal network (TFN) in BDD patients had increased FC with the superficial cerebellar network (CN) and with the superficial pre/post-central network (PCN). Further, support vector regression prediction analysis results revealed that the increased FCs of CN-TFN and PCN-TFN could be served as features to predict the numbers of depressive episode in BDD patients.

CONCLUSIONS

The current study extended our knowledge about the impaired WM functional connections associated with emotional and sensory-motor perception processing in BDD, which may facilitate the interpretation of the pathophysiology mechanisms underlying BDD.

Abnormal transitions of dynamic functional connectivity states in bipolar disorder: A whole-brain resting-state fMRI study

BACKGROUND

Dynamic functional connectivity (dFC) based on resting-state fMRI has attracted interest in the field of bipolar disorder (BD), because dFC can better capture the evolving processes of emotion and cognition, which are typically impaired in BD. However, previous dFC studies of BD have typically focused on specific seed brain regions or specific functional brain networks, and they have ignored global dynamic information interaction in the whole brain. This study is aimed to reveal aberrant and interpretable whole-brain dFC patterns of BD.

METHODS

The resting-state fMRI data collected from 35 euthymic BD patients and 30 healthy people. We developed a new dFC inference pipeline, including the sliding-window method, k-means clustering, a new permutation with zero-inflated Poisson regression method, and a similarity analysis for interpretable states, to examine the different patterns of dFC states between BD patients and healthy participants.

RESULTS

BD patients had significantly more frequent transitions between two specific dFC states, which were respectively close to high-level cognitive networks and low-level sensory networks, than healthy controls (p < 0.05, FDR).

LIMITATIONS

The size of samples and other BD types need to be expanded to validate the results of this study. Possible confounding effect of medication.

CONCLUSIONS

This study detected aberrant dFC pattern of BD, which indicated the increased lability of the processes of cognition and emotion in BD, and this finding could improve our understanding of the neuropathological mechanism of BD.

The Abnormal Functional Connectivity in the Locus Coeruleus-Norepinephrine System Associated With Anxiety Symptom in Chronic Insomnia Disorder

BACKGROUND

Mental syndromes such as anxiety and depression are common comorbidities in patients with chronic insomnia disorder (CID). The locus coeruleus noradrenergic (LC-NE) system is considered to be crucial for modulation of emotion and sleep/wake cycle. LC-NE system is also a critical mediator of the stress-induced anxiety. However, whether the LC-NE system contributes to the underlying mechanism linking insomnia and these comorbidities remain unclear. This study aimed to investigate the LC-NE system alterations in patients with insomnia and its relationship with depression and anxiety symptoms.

MATERIALS AND METHODS

Seventy patients with CID and 63 matched good sleep control (GSC) subjects were recruited and underwent resting-state functional MRI scan. LC-NE functional network was constructed by using seed-based functional connectivity (FC) analysis. The alterations in LC-NE FC network in patients with CID and their clinical significance was explored.

RESULTS

Compared with GSC group, the CID group showed decreased left LC-NE FC in the left inferior frontal gyrus, while they had increased LC-NE FC in the left supramarginal gyrus and the left middle occipital gyrus (MOG). For the right LC-NE FC network, decreased FC was found in left dorsal anterior cingulate cortex (dACC). Interesting, the increased LC-NE FC was located in sensory cortex, while decreased LC-NE FC was located in frontal control cortex. In addition, the FC between the left LC and left MOG was associated with the duration of the disease, while abnormal FC between right LC and left dACC was associated with the anxiety scores in patients with CID.

CONCLUSION

The present study found abnormal LC-NE functional network in patients with CID, and the altered LC-NE function in dACC was associated with anxiety symptoms in CID. The present study substantially extended our understanding of the neuropathological basis of CID and provided the potential treatment target for CID patients who also had anxiety.

Dynamic Functional Network Connectivity Changes Associated with fMRI Neurofeedback of Right Premotor Cortex

Neurofeedback of real-time functional magnetic resonance imaging (rtfMRI) can enable people to self-regulate motor-related brain regions and lead to alteration of motor performance and functional connectivity (FC) underlying motor execution tasks. Numerous studies suggest that FCs dynamically fluctuate over time. However, little is known about the impact of neurofeedback training of the motor-related region on the dynamic characteristics of FC underlying motor execution tasks. This study aims to investigate the mechanism of self-regulation of the right premotor area (PMA) on the underlying dynamic functional network connectivity (DFNC) of motor execution (ME) tasks and reveal the relationship between DFNC, training effect, and motor performance. The results indicate that the experimental group spent less time on state 2, with overall weak connections, and more time on state 6, having strong positive connections between motor-related networks than the control group after the training. For the experimental group’s state 2, the mean dwell time after the training showed negative correlation with the tapping frequency and the amount of upregulation of PMA. The findings show that rtfMRI neurofeedback can change the temporal properties of DFNC, and the DFNC changes in state with overall weak connections were associated with the training effect and the improvement in motor performance.

Increased resting state functional irregularity of T2DM brains with high HbA1c: sign for impaired verbal memory function?

Glycosylated hemoglobin A1c (HbA1c) has been considered as a key contributor to impaired cognition in type 2 diabetes mellitus (T2DM) brains. However, how does it affect the brain and whether the glucose controlling can slow down the process are still unknown. In the current study, T2DM patients with high glycosylated hemoglobin level (HGL) and controls with normal glycosylated hemoglobin level (NGL) were enrolled to investigate the relationships between HbA1c, brain imaging characteristics and cognitive function. First, a series of cognitive tests including California Verbal Learning Test (CVLT) were conducted. Then, the functional irregularity based on resting state functional magnetic resonance imaging data was evaluated via a new data-driven brain entropy (BEN) mapping analysis method. We found that the HGLs exhibited significantly increased BEN in the right precentral gyrus (PreCG.R), the right middle frontal gyrus (MFG.R), the triangular and opercular parts of the right inferior frontal gyrus (IFGtriang.R and IFGoperc.R). The strengths of the functional connections of PreCG.R with the brainstem/cerebellum were decreased. Partial correlation analysis showed that HbA1c had a strong positive correlation to regional BEN and negatively correlated with some CVLT scores. Negative correlations also existed between the BEN of PreCG.R/IFGoperc.R and some CVLT scores, suggesting the correspondence between higher HbA1c, increased BEN and decreased verbal memory function. This study demonstrated the potential of BEN in exploring the functional alterations affected by HbA1c and interpreting the verbal memory function decline. It will help understanding the neurophysiological mechanism of T2DM-induced cognitive decline and taking effective prevention or treatment measures.

Altered static and dynamic voxel-mirrored homotopic connectivity in subacute stroke patients: a resting-state fMRI study

Sixty-four subacute stroke patients and 55 age-matched healthy controls (HCs) underwent a resting-state functional magnetic resonance imaging scan using an echo-planar imaging sequence and high-resolution sagittal T1-weighted images using a three-dimensional magnetization-prepared rapid gradient echo sequence. Static and dynamic voxel-mirrored homotopic connectivity (VMHC) was computed, respectively. The relationships between the clinical measures, including National Institutes of Health Stroke Scale (NIHSS), illness duration, Fugl-Meyer assessment for upper and lower extremities (FMA-total) and size of lesion volume, and the static/ dynamic VMHC variability alterations in stroke patients were calculated. The stroke patients showed significantly increased static VMHC in the corpus callosum, middle occipital gyrus and inferior parietal gyrus, and decreased static VMHC in the inferior temporal gyrus and precentral gyrus (PreCG) compared with those of HCs. For dynamic VMHC variability, increased dynamic VMHC variability in the inferior temporal gyrus and PreCG was detected in stroke patients relative to that in HCs. Correlation analysis exhibited that significant negative correlations were shown between the FMA scores and dynamic VMHC variability in PreCG. The present study suggests that combined static and dynamic VMHC could be helpful to evaluate the motor function of stroke patients and understand the intrinsic differences of inter-hemispheric coordination after stroke.

Frequency-specific alternations in the moment-to-moment BOLD signals variability in schizophrenia

Variability of neuronal activity is considered as the fundamental mechanism for the flexible and optimal brain function. Moreover, different frequency neuro signal is related to specific function. While little is currently known regarding changes in spontaneous BOLD variability of schizophrenia. The current study used resting-state fMRI data from 53 chronic schizophrenic subjects and 67 healthy subjects to investigate this issue. The data-driven method was used to measure the BOLD variability (MSSD: mean square successive difference) in two different frequency bands respectively (slow-5: 0.01-0.027 Hz; slow-4:0.027-0.073 Hz). Schizophrenic subjects exhibited decreased BOLD variability in thalamus region, sensorimotor and visual networks, and increased BOLD variability in salience network compared to matched healthy controls. Moreover, the interaction effects between frequency and group were observed in thalamus and right dorsolateral prefrontal cortex (DLPFC). These findings identified that altered BOLD variability is frequency dependent in schizophrenia. Importantly, the severity of patients' negative symptom was related to the increased BOLD variability of DLPFC within slow-4 frequency band, highlighting the evidence that abnormal BOLD variability of frontal cortex is likely to have effects on the pathophysiology of negative symptom in schizophrenia.

The abnormal reward network associated with insomnia severity and depression in chronic insomnia disorder

Previous research has shown that acute sleep deprivation can influence the reward networks. However, it is unclear whether and how the intrinsic reward network is altered in chronic insomnia disorder (CID). In the present study, we aimed to investigate whether the reward network is altered in patients with CID using resting-state functional magnetic resonance imaging (fMRI) data. Forty-two patients with CID and 33 healthy controls (HCs) were enrolled and underwent resting-state fMRI. Nucleus accumbens (NAc) - based functional connectivity (NAFC) was evaluated to explore the differences in the reward network between the CID and HC groups. Pearson correlation analysis was used to evaluate the clinical significance of altered NAFC networks. Compared to those in the HC group, increased NAFC was found in the salience and limbic networks, while decreased NAFC was found in the default mode network (DMN) and within the reward circuit in patients with CID. In addition, decreased FC between the NAc and DMN was associated with insomnia severity, while NAFC within the reward network was associated with depression symptoms in patients with CID. These findings showed that the reward network is dysfunctional and associated with depression symptom in patients with CID. Future studies of CID should consider both insomnia and depression symptoms to disentangle the role of insomnia and depression in the relationship under study.

Altered resting-state functional networks in patients with hemodialysis: a graph-theoretical based study

Recent studies have demonstrated that hemodialysis patients exhibit disruptions in functional networks with invisible cerebral alterations. We explored the alterations of functional connectivity in hemodialysis patients using the graph-theory method. A total of 46 hemodialysis patients (53.11 ± 1.58 years, 28 males) and 47 healthy controls (55.57 ± 0.86 years, 22 males) were scanned by using resting-state functional magnetic resonance imaging. The brains of these patients were divided into 90 regions and functional connectivity was constructed with the automatic anatomical labeling atlas. In the defined threshold range, the graph-theory analysis was performed to compare the topological properties including global, regional and edge parameters between the hemodialysis and the healthy control groups. Both hemodialysis patients and healthy control subjects demonstrated common small-world property of the brain functional connections. At the global level, the parameters normalized clustering coefficients and small-worldness were significantly decreased in hemodialysis patients compared with those noted in healthy controls. At the regional level, abnormal nodal metrics (increased or decreased nodal degree, betweenness centrality and efficiency) were widely found in hemodialysis patients compared with those of healthy controls. The network-based statistical method was employed and two disrupted neural circuits with 18 nodes and 19 edges (P = 0.0139, corrected) and 10 nodes and 11 edges (P = 0.0399, corrected) were detected. Of note, the edge-increased functional connectivity was associated with the salience network and the frontal-temporal-basal ganglia connection, whereas the edge-decreased functional connectivity was associated with the frontoparietal network. The graph-theory method may be one of the potential tools to detect disruptions of cerebral functional connectivity and provide important evidence for understanding the neuropathology of hemodialysis patients from the disrupted network organization perspective.

Changes in the topological organization of the default mode network in autism spectrum disorder

Neuroimaging studies have demonstrated that autism spectrum disorder (ASD) is accompanied by abnormal functional and structural features in specific brain regions of the default mode network (DMN). However, little is known about the alterations of the topological organization and the functional connectivity (FC) of the DMN in ASD patients. Thirty-seven ASD patients and 38 healthy control (HC) participants underwent a resting-state functional magnetic resonance imaging scan. Twenty DMN subregions were specifically selected to construct the DMN architecture. We applied graph theory approaches to the topological configuration and compare the FC patterns of the DMN. We then examined the relationships between the neuroimaging measures of the DMN and clinical characteristics in patients with ASD. The current study revealed that both the ASD and HC participants showed a small-world regimen in the DMN; however there were no significant differences in global network measures. Compared with the HC group, the ASD group exhibited significantly decreased nodal centralities in the bilateral anterior medial prefrontal cortex and increased nodal centralities in the right lateral temporal cortex and the right retrosplenial cortex. Patients with ASD displayed significantly reduced and increased FC within the DMN. Our findings demonstrated that ASD patients showed a pattern of disrupted FC metrics and nodal network metrics in the DMN, which could be a potential biomarker for objective ASD diagnoses and for the level of autism spectrum traits. HIGHLIGHTS: We used graph theoretical approaches and functional connectivity (FC) to investigate the topological configuration and FC patterns of the DMN in ASD. The current study revealed that both ASD and HC participants exhibited small-world regimes in the DMN, however there were no significant differences in global network measures. The ASD group showed abnormal nodal centralities in the bilateral aMPFC, the right LTC and the Rsp of the DMN, and ASD was characterized by altered FC patterns, including decreased and increased FC within the DMN.