Characterizing microstructural patterns within the cortico-striato-thalamo-cortical circuit in Parkinson's disease.

PURPOSE: Parkinson's disease (PD) involves pathological alterations that include cortical impairments at levels of region and network. However, its microstructural abnormalities remain to be further elucidated via an appropriate diffusion neuroimaging approach. This study aimed to comprehensively demonstrate the microstructural patterns of PD as mapped by diffusion kurtosis imaging (DKI). METHODS: The microstructure of grey matter in both the PD group and the matched healthy control group was quantified by a DKI metric (mean kurtosis). The intergroup difference and classification performance of global microstructural complexity were analyzed in a voxelwise manner and via a machine learning approach, respectively. The patterns of information flows were explored in terms of structural connectivity, network covariance and modular connectivity. RESULTS: Patients with PD exhibited global microstructural impairments that served as an efficient diagnostic indicator. Disrupted structural connections between the striatum and cortices as well as between the thalamus and cortices were widely distributed in the PD group. Aberrant covariance of the striatocortical circuitry and thalamocortical circuitry was observed in patients with PD, who also showed disrupted modular connectivity within the striatum and thalamus as well as across structures of the cortex, striatum and thalamus. CONCLUSION: These findings verified the potential clinical application of DKI for the exploration of microstructural patterns in PD, contributing complementary imaging features that offer a deeper insight into the neurodegenerative process.

Early detection of dopaminergic dysfunction and glymphatic system impairment in Parkinson's disease.

PURPOSE: This study aimed to assess the glymphatic function and its correlation with clinical characteristics and the loss of dopaminergic neurons in Parkinson's disease (PD) using hybrid positron emission tomography (PET)-magnetic resonance imaging (MRI) combined with diffusion tensor image analysis along the perivascular space (DTI-ALPS), choroid plexus volume (CPV), and enlarged perivascular space (EPVS) volume. METHODS: Twenty-five PD patients and thirty matched healthy controls (HC) participated in the study. All participants underwent 18F-fluorodopa (18F-DOPA) PET-MRI scanning. The striatal standardized uptake value ratio (SUVR), DTI-ALPS index, CPV, and EPVS volume were calculated. Furthermore, we also analysed the relationship between the DTI-ALPS index, CPV, EPVS volume and striatal SUVR as well as clinical characteristics of PD patients. RESULTS: PD patients demonstrated significantly lower values in DTI-ALPS (t = 3.053, p = 0.004) and larger CPV (t = 2.743, p = 0.008) and EPVS volume (t = 2.807, p = 0.008) compared to HC. In PD group, the ALPS-index was negatively correlated with the Unified Parkinson's Disease Rating Scale III (UPDRS-III) scores (r = -0.730, p < 0.001), and positively correlated with the mean putaminal SUVR (r = 0.560, p = 0.007) and mean caudal SUVR (r = 0.459, p = 0.032). Moreover, the mean putaminal SUVR was negatively associated with the UPDRS-III scores (r = -0.544, p = 0.009). CONCLUSION: DTI-ALPS has the potential to uncover glymphatic dysfunction in patients with PD, with this dysfunction correlating strongly with the severity of disease, together with the mean putaminal and caudal SUVR. PET- MRI can serve as a potential multimodal imaging biomarker for early-stage PD.

Diffusion Kurtosis Imaging in Diagnosing Parkinson's Disease: A Preliminary Comparison Study Between Kurtosis Metric and Radiomic Features.

RATIONALE AND OBJECTIVES: Parkinson's disease (PD) shows small structural changes in nigrostriatal pathways, which can be sensitively captured through diffusion kurtosis imaging (DKI). However, the value of DKI and its radiomic features in the classification performance of PD still need confirmation. This study aimed to compare the diagnostic efficiency of DKI-derived kurtosis metric and its radiomic features with different machine learning models for PD classification. MATERIALS AND METHODS: 75 people with PD and 80 healthy individuals had their brains scanned using DKI. These images were pre-processed and the standard atlas were non-linearly registered to them. With the labels in atlas, different brain regions in nigrostriatal pathways, including the caudate nucleus, putamen, pallidum, thalamus, and substantia nigra, were chosen as the region of interests (ROIs) to warped to the native space to measure the mean kurtosis (MK). Additionally, new radiomic features were developed for comparison. To handle the large amount of data, a statistical method called Z-score normalization and another method called LASSO regression were used to simplify the information. From this, a few most important features were chosen, and a combined score called Radscore was calculated using LASSO regression. For the comprehensive analyses, three different conventional machine learning models were then created: logistic regression (LR), support vector machine (SVM), and random forest (RF). To ensure the models were accurate, a process called 10-fold cross-validation was used, where the data were split into 10 parts for training and testing. RESULTS: Using MK alone, the models achieved good results in correctly identifying PD in the validation set, with LR at 0.90, RF at 0.93, and SVM at 0.90. When the radiomic features were added, the models performed even better, with LR at 0.92, RF at 0.95, and SVM at 0.91. Additionally, a nomogram combining all the information was created to predict the likelihood of someone having PD, which had an AUC of 0.91. CONCLUSION: These findings suggest that the combination of DKI measurements and radiomic features can effectively diagnose PD by providing more detailed information about the brain's condition and the processes involved in the disease.

Topological disruption of low- and high-order functional networks in presbycusis.

Prior efforts have manifested that functional connectivity (FC) network disruptions are concerned with cognitive disorder in presbycusis. The present research was designed to investigate the topological reorganization and classification performance of low-order functional connectivity (LOFC) and high-order functional connectivity (HOFC) networks in patients with presbycusis. Resting-state functional magnetic resonance imaging (Rs-fMRI) data were obtained in 60 patients with presbycusis and 50 matched healthy control subjects (HCs). LOFC and HOFC networks were then constructed, and the topological metrics obtained from the constructed networks were compared to evaluate topological differences in global, nodal network metrics, modularity and rich-club organization between patients with presbycusis and HCs. The use of HOFC profiles boosted presbycusis classification accuracy, sensitivity and specificity compared to that using LOFC profiles. The brain networks in both patients with presbycusis and HCs exhibited small-world properties within the given threshold range, and striking differences between groups in topological metrics were discovered in the constructed networks (LOFC and HOFC). NBS analysis identified a subnetwork involving 26 nodes and 23 signally altered internodal connections in patients with presbycusis in comparison to HCs in HOFC networks. This study highlighted the topological differences between LOFC and HOFC networks in patients with presbycusis, suggesting that HOFC profiles may help to further identify brain network abnormalities in presbycusis.

Intracerebral hemodynamic abnormalities in patients with Parkinson's disease: Comparison between multi-delay arterial spin labelling and conventional single-delay arterial spin labelling.

PURPOSE: The purpose of this study was to analyze the intracerebral abnormalities of hemodynamics in patients with Parkinson's disease (PD) through arterial spin labelling (ASL) technique with multi-delay ASL (MDASL) and conventional single-delay ASL (SDASL) protocols and to verify the potential clinical application of these features for the diagnosis of PD. MATERIALS AND METHODS: Perfusion data of the brain obtained using MDASL and SDASL in patients with PD were compared to those obtained in healthy control (HC) subjects. Intergroup comparisons of z-scored cerebral blood flow (zCBF), arterial transit time (zATT) and cerebral blood volume (zCBV) were performed via voxel-based analysis. Performance of these perfusion metrics were estimated using area under the receiver operating characteristic curve (AUC) and compared using Delong test. RESULTS: A total of 47 patients with PD (29 men; 18 women; mean age, 69.0 ± 7.6 (standard deviation, [SD]) years; range: 50.0-84.0 years) and 50 HC subjects (28 men; 22 women; mean age, 70.1 ± 6.2 [SD] years; range: 50.0-93.0 years) were included. Relative to the uncorrected-zCBF map, the corrected-zCBF map further refined the distributed brain regions in the PD group versus the HC group, manifested as the extension of motor-related regions (PFWE < 0.001). Compared to the HC subjects, patients with PD had elevated zATT and zCBV in the right putamen, a shortened zATT in the superior frontal gyrus, and specific zCBV variations in the left precuneus and the right supplementary motor area (PFWE < 0.001). The corrected-zCBF (AUC, 0.90; 95% confidence interval [CI]: 0.84-0.96) showed better classification performance than uncorrected-zCBF (AUC, 0.84; 95% CI: 0.75-0.92) (P = 0.035). zCBV achieved an AUC of 0.89 (95% CI: 0.82-0.96) and zATT achieved an AUC of 0.66 (95% CI: 0.55-0.77). The integration model of hemodynamic features from MDASL provided improved performance (AUC, 0.97; 95% CI: 0.95-0.98) for the diagnosis of PD by comparison with each perfusion model (P < 0.001). CONCLUSION: ASL identifies impaired hemodynamics in patients with PD including regional abnormalities of CBF, CBV and ATT, which can better be mapped with MDASL compared to SDASL. These findings provide complementary depictions of perfusion abnormalities in patients with PD and highlight the clinical feasibility of MDASL.

Optimization of structural connectomes and scaled patterns of structural-functional decoupling in Parkinson's disease.

Parkinson's disease (PD) is manifested with disrupted topology of the structural connection network (SCN) and the functional connection network (FCN). However, the SCN and its interactions with the FCN remain to be further investigated. This multimodality study attempted to precisely characterize the SCN using diffusion kurtosis imaging (DKI) and further identify the neuropathological pattern of SCN-FCN decoupling, underscoring the neurodegeneration of PD. Diffusion-weighted imaging and resting-state functional imaging were available for network constructions among sixty-nine patients with PD and seventy demographically matched healthy control (HC) participants. The classification performance and topological prosperities of both the SCN and the FCN were analyzed, followed by quantification of the SCN-FCN couplings across scales. The SCN constructed by kurtosis metrics achieved optimal classification performance (area under the curve 0.89, accuracy 80.55 %, sensitivity 78.40 %, and specificity 80.65 %). Along with diverse alterations of structural and functional network topology, the PD group exhibited decoupling across scales including: reduced global coupling; increased nodal coupling within the sensorimotor network (SMN) and subcortical network (SN); higher intramodular coupling within the SMN and SN and lower intramodular coupling of the default mode network (DMN); decreased coupling between the modules of DMN-fronto-parietal network and DMN-visual network, but increased coupling between the SMN-SN module. Several associations between the coupling coefficient and topological properties of the SCN, as well as between network values and clinical scores, were observed. These findings validated the clinical implementation of DKI for structural network construction with better differentiation ability and characterized the SCN-FCN decoupling as supplementary insight into the pathological process underlying PD.

Drooling disrupts the brain functional connectivity network in Parkinson's disease.

AIMS: This study aimed to investigate the causal interaction between significant sensorimotor network (SMN) regions and other brain regions in Parkinson's disease patients with drooling (droolers). METHODS: Twenty-one droolers, 22 PD patients without drooling (non-droolers), and 22 matched healthy controls underwent 3T-MRI resting-state scans. We performed independent component analysis and Granger causality analysis to determine whether significant SMN regions help predict other brain areas. Pearson's correlation was computed between imaging characteristics and clinical characteristics. ROC curves were plotted to assess the diagnostic performance of effective connectivity (EC). RESULTS: Compared with non-droolers and healthy controls, droolers showed abnormal EC of the right caudate nucleus (CAU.R) and right postcentral gyrus to extensive brain regions. In droolers, increased EC from the CAU.R to the right middle temporal gyrus was positively correlated with MDS-UPDRS, MDS-UPDRS II, NMSS, and HAMD scores; increased EC from the right inferior parietal lobe to CAU.R was positively correlated with MDS-UPDRS score. ROC curve analysis showed that these abnormal ECs are of great significance in diagnosing drooling in PD. CONCLUSION: This study identified that PD patients with drooling have abnormal EC in the cortico-limbic-striatal-cerebellar and cortio-cortical networks, which could be potential biomarkers for drooling in PD.

Functional-structural large-scale brain networks are correlated with neurocognitive impairment in acute mild traumatic brain injury.

Background: This study was conducted to investigate topological changes in large-scale functional connectivity (FC) and structural connectivity (SC) networks in acute mild traumatic brain injury (mTBI) and determine their potential relevance to cognitive impairment. Methods: Seventy-one patients with acute mTBI (29 males, 42 females, mean age 43.54 years) from Nanjing First Hospital and 57 matched healthy controls (HC) (33 males, 24 females, mean age 46.16 years) from the local community were recruited in this prospective study. Resting-state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) were acquired within 14 days (mean 3.29 days) after the onset of mTBI. Then, large-scale FC and SC networks with 116 regions from the automated anatomical labeling (AAL) brain atlas were constructed. Graph theory analysis was used to analyze global and nodal metrics. Finally, correlations were assessed between topological properties and neurocognitive performances evaluated by the Montreal Cognitive Assessment (MoCA). Bonferroni correction was performed out for multiple comparisons in all involved analyses. Results: Compared with HC, acute mTBI patients had a higher normalized clustering coefficient (γ) for FC (Cohen's d=4.076), and higher γ and small worldness (σ) for SC (Cohen's d=0.390 and Cohen's d=0.395). The mTBI group showed aberrant nodal degree (Dc), nodal efficiency (Ne), and nodal local efficiency (Nloc) for FC and aberrant Dc, nodal betweenness (Bc), nodal clustering coefficient (NCp) and Ne for SC mainly in the frontal and temporal, cerebellum, and subcortical areas. Acute mTBI patients also had higher functional-structural coupling strength at both the group and individual levels (Cohen's d=0.415). These aberrant global and nodal topological properties at functional and structural levels were associated with attention, orientation, memory, and naming performances (all P<0.05). Conclusions: Our findings suggested that large-scale FC and SC network changes, higher correlation between FC and SC and cognitive impairment can be detected in the acute stage of mTBI. These network aberrances may be a compensatory mechanism for cognitive impairment in acute mTBI patients.

Topological disruption of high-order functional networks in cognitively preserved Parkinson's disease.

AIMS: This study aimed to characterize the topological alterations and classification performance of high-order functional connectivity (HOFC) networks in cognitively preserved patients with Parkinson's disease (PD), relative to low-order FC (LOFC) networks. METHODS: The topological metrics of the constructed networks (LOFC and HOFC) obtained from fifty-one cognitively normal patients with PD and 60 matched healthy control subjects were analyzed. The discriminative abilities were evaluated using machine learning approach. RESULTS: The HOFC networks in the PD group showed decreased segregation and integration. The normalized clustering coefficient and small-worldness in the HOFC networks were correlated to motor performance. The altered nodal centralities (distributed in the precuneus, putamen, lingual gyrus, supramarginal gyrus, motor area, postcentral gyrus and inferior occipital gyrus) and intermodular FC (frontoparietal and visual networks, sensorimotor and subcortical networks) were specific to HOFC networks. Several highly connected nodes (thalamus, paracentral lobule, calcarine fissure and precuneus) and improved classification performance were found based on HOFC profiles. CONCLUSION: This study identified disrupted topology of functional interactions at a high level with extensive alterations in topological properties and improved differentiation ability in patients with PD prior to clinical symptoms of cognitive impairment, providing complementary insights into complex neurodegeneration in PD.

Rich-club reorganization of functional brain networks in acute mild traumatic brain injury with cognitive impairment.

Background: Mild traumatic brain injury (mTBI) is typically characterized by temporally limited cognitive impairment and regarded as a brain connectome disorder. Recent findings have suggested that a higher level of organization named the "rich-club" may play a central role in enabling the integration of information and efficient communication across different systems of the brain. However, the alterations in rich-club organization and hub topology in mTBI and its relationship with cognitive impairment after mTBI have been scarcely elucidated. Methods: Resting-state functional magnetic resonance imaging (rs-fMRI) data were collected from 88 patients with mTBI and 85 matched healthy controls (HCs). Large-scale functional brain networks were established for each participant. Rich-club organizations and network properties were assessed and analyzed between groups. Finally, we analyzed the correlations between the cognitive performance and changes in rich-club organization and network properties. Results: Both mTBI and HCs groups showed significant rich-club organization. Meanwhile, the rich-club organization was aberrant, with enhanced functional connectivity (FC) among rich-club nodes and peripheral regions in acute mTBI. In addition, significant differences in partial global and local network topological property measures were found between mTBI patients and HCs (P<0.01). In patients with mTBI, changes in rich-club organization and network properties were found to be related to early cognitive impairment after mTBI (P<0.05). Conclusions: Our findings suggest that such patterns of disruption and reorganization will provide the basic functional architecture for cognitive function, which may subsequently be used as an earlier biomarker for cognitive impairment after mTBI.

Reorganized Brain Functional Network Topology in Presbycusis.

Purpose: Presbycusis is characterized by bilateral sensorineural hearing loss at high frequencies and is often accompanied by cognitive decline. This study aimed to identify the topological reorganization of brain functional network in presbycusis with/without cognitive decline by using graph theory analysis approaches based on resting-state functional magnetic resonance imaging (rs-fMRI). Methods: Resting-state fMRI scans were obtained from 30 presbycusis patients with cognitive decline, 30 presbycusis patients without cognitive decline, and 50 age-, sex-, and education-matched healthy controls. Graph theory was applied to analyze the topological properties of brain functional networks including global and nodal metrics, modularity, and rich-club organization. Results: At the global level, the brain functional networks of all participants were found to possess small-world properties. Also, significant group differences in global network metrics were observed among the three groups such as clustering coefficient, characteristic path length, normalized characteristic path length, and small-worldness. At the nodal level, several nodes with abnormal betweenness centrality, degree centrality, nodal efficiency, and nodal local efficiency were detected in presbycusis patients with/without cognitive decline. Changes in intra-modular connections in frontal lobe module and inter-modular connections in prefrontal subcortical lobe module were found in presbycusis patients exposed to modularity analysis. Rich-club nodes were reorganized in presbycusis patients, while the connections among them had no significant group differences. Conclusion: Presbycusis patients exhibited topological reorganization of the whole-brain functional network, and presbycusis patients with cognitive decline showed more obvious changes in these topological properties than those without cognitive decline. Abnormal changes of these properties in presbycusis patients may compensate for cognitive impairment by mobilizing additional neural resources.

Early disturbance of dynamic synchronization and neurovascular coupling in cognitively normal Parkinson's disease.

Pathological process in Parkinson's disease (PD) is accompanied with functional and metabolic alterations. The time-varying properties of functional coherence and their coupling to regional perfusion are still rarely elucidated. To investigate early disruption of dynamic regional homogeneity (dReho) and neurovascular coupling in cognitively normal PD patients, dynamic neuronal synchronization and regional perfusion were measured using dReho and cerebral blood flow (CBF), respectively. Neurovascular coupling was assessed by CBF-ReHo correlation coefficient and CBF/ReHo ratio. Multivariate pattern analysis was conducted for the differentiating ability of each feature. Relative to healthy controls (HC) subjects, PD patients demonstrated increased dReho in middle temporal gyrus (MTG), rectus gyrus, middle occipital gyrus, and precuneus, whereas reduced dReho in putamen and supplementary motor area (SMA); while higher CBF/dReho ratio was located in putamen, SMA, paracentral lobule, and postcentral gyrus, whereas lower CBF/dReho ratio in superior temporal gyrus, MTG, precuneus, and angular gyrus (AG). Global and regional CBF-Reho decoupling were both observed in PD groups. The CBF/Reho ratio features achieved more powerful classification performance than other features. From the view of dynamic neural synchronization and neurovascular coupling, this study reinforced the insights into neural basis underlying PD and the potential role in the disease diagnosis and differentiation.

Cerebral Blood Flow and its Connectivity Deficits in Patients With Lung Cancer After Chemotherapy.

Purpose: This study was performed to investigate the regional cerebral blood flow (CBF) and CBF connectivity in the chemotherapy-induced cognitive impairment of patients with lung cancer by using arterial spin labeling. Methods: Pseudocontinuous arterial spin labeling perfusion magnetic resonance imaging and neuropsychological tests were performed for 21 patients with non-small cell lung cancer who had received chemotherapy CT (+) and 25 non-small cell lung cancer patients who need chemotherapy but did not yet received CT (-). The CT (+) group previously received platinum-based therapy for 3 months to 6 months (the time from their first chemotherapy to the MRI scan). Group comparisons were performed in the regional normalized CBF and CBF connectivity, and the relationship between the regional normalized CBF and cognitive impairment were detected. Results: The CT (+) group exhibited higher CBF in the left insula, right caudate, right superior occipital gyrus, left superior temporal gyrus (STG), and right middle frontal gyrus (MFG). MoCA scores as well as the memory scores were negatively correlated with the increased CBF in the right MFG (r = -0.492, p = 0.023; r = -0.497, p = 0.022). Alterations in the CBF connectivity were detected only in the CT (+) group between the following: right MFG and the right precentral gyrus; the right caudate and the right lingual gyrus; right caudate and right precuneus; left STG and the bilateral MFG; and the left STG and the right middle cingulum. Conclusion: These findings indicated that chemotherapy is associated with abnormalities in the CBF and connectivity alterations, which may contribute to the cognitive impairment in patients with lung cancer.

Aberrant Static and Dynamic Functional Network Connectivity in Acute Mild Traumatic Brain Injury with Cognitive Impairment.

PURPOSE: This study aimed to investigate differences in static and dynamic functional network connectivity (FNC) and explore their association with neurocognitive performance in acute mild traumatic brain injury (mTBI). METHODS: A total of 76 patients with acute mTBI and 70 age-matched and sex-matched healthy controls were enrolled (age 43.79 ± 10.22 years vs. 45.63 ± 9.49 years; male/female: 34/42 vs. 38/32; all p > 0.05) and underwent resting-state functional magnetic resonance imaging (fMRI) scan (repetition time/echo time = 2000/30 ms, 230 volumes). Independent component analysis was conducted to evaluate static and dynamic FNC patterns on the basis of nine resting-state networks, namely, auditory network (AUDN), dorsal attention network (dAN), ventral attention network (vAN), default mode network (DMN), left frontoparietal network (LFPN), right frontoparietal network (RFPN), somatomotor network (SMN), visual network (VN), and salience network (SN). Spearman's correlation among aberrances in FNC values, and Montreal cognitive assessment (MoCA) scores was further measured in mTBI. RESULTS: Compared with controls, patients with mTBI showed wide aberrances of static FNC, such as reduced FNC in DMN-vAN and VN-vAN pairs. The mTBI patients exhibited aberrant dynamic FNC in state 2, involving reduced FNC aberrance in the vAN with AUDN, VN with DMN and dAN, and SN with SMN and vAN. Reduced dFNC in the SN-vAN pair was negatively correlated with the MoCA score. CONCLUSION: Our findings suggest that aberrant static and dynamic FNC at the acute stage may contribute to cognitive symptoms, which not only may expand knowledge regarding FNC cognition relations from the static perspective but also from the dynamic perspective.

Reduced functional network connectivity is associated with upper limb dysfunction in acute ischemic brainstem stroke.

This study aimed to detect alterations in intra- and inter-network functional connectivity (FC) of multiple networks in acute brainstem ischemic stroke patients, and the relationship between FC and movement assessment scores to assess their ability to predict upper extremity motor impairment. Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from acute brainstem ischemic stroke patients (n = 50) and healthy controls (HCs) (n = 45). Resting-state networks (RSNs) were established based on independent component analysis (ICA) and the functional network connectivity (FNC) analysis was performed. Subsequently, correlation analysis was subsequently used to explore the relationship between FNC abnormalities and upper extremity motor impairment. Altered FC within default mode network (DMN), executive control network (ECN), the salience network (SN), auditory network (AN), and cerebellum network (CN) were found in the acute brainstem ischemic stroke group relative to HCs. Moreover, different patterns of altered network interactions were found between the patients and HCs, including the SN-CN, SN-AN, and ECN-DMN connections. Correlations between functional disconnection and upper limb dysfunction measurements in acute brainstem ischemic stroke patients were also found. This study intimated that widespread FNC impairment and altered integration existed in brainstem ischemic stroke at acute stage, suggesting that FNC disruption may be applied for early diagnosis and prediction of upper limb dysfunction in acute brainstem ischemic stroke.

Topological features of limbic dysfunction in chronicity of tinnitus with intact hearing: New hypothesis for 'noise-cancellation' mechanism.

PURPOSE: The reorganization of the limbic regions extend to general cognitive network is believed to exist in the chronicity of tinnitus with particular 'hubs' contributing to a 'noise-cancellation' mechanism. To test this hypothesis, we investigated the topological brain network of tinnitus in different periods. METHODS: Resting-state functional magnetic resonance imaging were obtained from 32 patients with acute tinnitus, 41 patients with chronic tinnitus and 60 age- and gender- matched healthy controls (HC). The topological features of their brain networks were explored using graph theory analysis. RESULTS: Common small-world attributes were compared between the three groups, all showed a significantly increased values in Cp, Lp, λ (all p < 0.05). Significantly increased nodal centralities in the left superior frontal gyrus and the right precuneus, significantly decreased nodal centralities in the right inferior temporal gyrus were observed for acute tinnitus patients compared to HC. While for chronic tinnitus patients, there were significant increased nodal centralities in the left hippocampus, amygdala, and temporal pole, but decreased nodal centralities in the right inferior temporal gyrus. Additionally, significant higher nodal centralities were found in bilateral medial superior frontal gyrus for acute tinnitus patients compared to chronic tinnitus patients. Besides, alterations in rich-club organization were found in acute tinnitus patients and chronic tinnitus patients compared with HC, with increased functional connections among rich-club nodes and peripheral nodes in patients with tinnitus. CONCLUSIONS: Brain network topological properties altered across prefrontal-limbic-subcortical regions in tinnitus. The existed hubs in tinnitus might indicate an emotional and cognitive burden in 'noise-cancellation' mechanism.

Dynamic functional network connectivity reveals the brain functional alterations in lung cancer patients after chemotherapy.

This study aimed to investigate alterations of brain functional network connectivity (FNC) in lung cancer patients after chemotherapy and explore links between these FNC differences and cognitive impairment. Twenty-two lung cancer patients receiving chemotherapy and 26 healthy controls (HCs) underwent resting-state functional MRI (rs-fMRI) and neuropsychological testing. Group independent component analysis (GICA) was applied to rs-fMRI data to extract whole-brain resting state networks (RSNs). Static and dynamic FNC (dFNC) were constructed to reveal RSNs connectivity alterations between lung cancer patients and HCs group, and the correlations between the group differences in RSNs and cognitive performance were analyzed. Our findings revealed that chemotherapeutics can produce widespread connectivity abnormalities in RSNs, mainly focused on default mode network (DMN) and executive control network. Furthermore, the dFNC analysis help identify network configurations of each state and capture more chemotherapy-induced disorders of interactions between and within RSNs, which mainly includes sensorimotor network, attentional network and auditory network. In addition, after chemotherapy, the lung cancer patients spend shorter mean dwell time (MDT) in state 2. The decreased dFNC between DMN [independent component 5 (IC5)] and DMN (IC6) in the lung cancer patients after chemotherapy in state 4 was negatively correlated with Montreal Cognitive Assessment (MoCA) scores (r=-0.447, p=0.042). The dFNC analysis enrich our understanding of the neural mechanisms underlying the chemobrain, and suggested that the temporal dynamics of FNC could be a potential effective method to detect cognitive changes in lung cancer patients receiving chemotherapy.

The altered functional modular organization in systemic lupus erythematosus: an independent component analysis study.

The aim of this study was to investigate the abnormities in functional connectivity (FC) within each modular network and between modular networks in patients with systemic lupus erythematosus (SLE). Twelve meaningful modular networks were identified via independent component analysis from 41 patients and 40 volunteers. Parametric tests were used to compare the intra- and intermodular FC between the groups. Partial correlation analysis was used to seek the relationships between abnormal FCs and the clinical data. Compared to the controls, SLE patients showed decreased intramodular FC in the anterior default mode network (aDMN), posterior default mode network (pDMN), ventral attention network (VAN), and sensorimotor network (SMN) and increased intramodular FC in the medial visual network (mVN) and left frontoparietal network. In addition, SLE patients showed decreased intermodular FC between the SMN and the lateral visual network (lVN), between the SMN and the VAN, and between the pDMN and the lVN and exhibited increased intermodular FC between the SMN and the salience network (SAN), between the pDMN and the SAN, and between the aDMN and the VAN. Moreover, we found several correlations among the abnormal FCs and the Mini-Mental State Examination in SLE patients. Mild cognitive impairment is compensated by the hyperconnectivity between the aDMN and the VAN, while severe cognitive impairment tends to be compensated by the hyperconnectivity between the SMN and the SAN. The FC value between the SMN and the SAN and between the aDMN and the VAN may serve as neuroimaging markers for monitoring cognitive progression in SLE patients.

Region-Specific Neurovascular Decoupling Associated With Cognitive Decline in Parkinson's Disease.

Background: Cognitive deficits are prominent non-motor symptoms in Parkinson's disease (PD) and have been shown to involve the neurovascular unit (NVU). However, there is a lack of sufficient neuroimaging research on the associated modulating mechanisms. The objective of this study was to identify the contribution of neurovascular decoupling to the pathogenesis of cognitive decline in PD. Methods: Regional homogeneity (ReHo), a measure of neuronal activity, and cerebral blood flow (CBF), a measure of vascular responses, were obtained from patients with PD with mild cognitive impairment (MCI) and normal cognition (NC) as well as matched healthy controls (HCs). Imaging metrics of neurovascular coupling (global and regional CBF-ReHo correlation coefficients and CBF-ReHo ratios) were compared among the groups. Results: Neurovascular coupling was impaired in patients with PD-MCI with a decreased global CBF-ReHo correlation coefficient relative to HC subjects (P < 0.05). Regional dysregulation was specific to the PD-MCI group and localized to the right middle frontal gyrus, right middle cingulate cortex, right middle occipital gyrus, right inferior parietal gyrus, right supramarginal gyrus, and right angular gyrus (P < 0.05). Compared with HC subjects, patients with PD-MCI showed higher CBF-ReHo ratios in the bilateral lingual gyri (LG), bilateral putamen, and left postcentral gyrus and lower CBF-ReHo ratios in the right superior temporal gyrus, bilateral middle temporal gyri, bilateral parahippocampal gyri, and right inferior frontal gyrus. Relative to the HC and PD-NC groups, the PD-MCI group showed an increased CBF-ReHo ratio in the left LG, which was correlated with poor visual-spatial performance (r = -0.36 and P = 0.014). Conclusion: The involvement of neurovascular decoupling in cognitive impairment in PD is regionally specific and most prominent in the visual-spatial cortices, which could potentially provide a complementary understanding of the pathophysiological mechanisms underlying cognitive deficits in PD.

Altered static and dynamic functional network connectivity in post-traumatic headache.

BACKGROUND: Post-traumatic headache (PTH) is a very common symptom following mild traumatic brain injury (mTBI), yet much remains unknown about the underlying pathophysiological mechanisms of PTH. Neuroimaging studies suggest that aberrant functional network connectivity (FNC) may be an important factor in pain disorders. The present study aimed to investigate the functional characteristics of static FNC (sFNC) and dynamic FNC (dFNC) in mTBI patients with PTH. METHODS: With Institutional Review Board (IRB) approval, we prospectively recruited 50 mTBI patients with PTH, who were diagnosed with ICHD-3 beta diagnostic criteria and 39 mTBI without PTH who were well matched for age, gender and education. Resting-state functional magnetic resonance imaging (fMRI) scanning (3.0 T, Philips Medical Systems, Netherlands), Montreal Cognitive Assessment (MoCA) and headache symptom measurement (headache frequency and headache intensity) were performed. The resting-state fMRI sequence took 8 min and 10 s. Independent component analysis and sliding window method were applied to examine the FNC on the basis of nine resting-state networks, namely, default mode network (DMN), sensorimotor network (SMN), executive control network (ECN), auditory network (AuN), attention network (AN), salience network (SN), visual network (VN), and cerebellum network (CN). The differences in sFNC and dFNC were determined and correlated with clinical variables using Pearson rank correlation. RESULTS: For sFNC, compared with mTBI patients without PTH, mTB with PTH group showed four altered interactions, including decreased interactions in SN-SMN and VN-DMN pairs, increased sFNC in SN-ECN and SMN-DMN pairs. For dFNC, significant group differences were found in State 2, including increased connectivity alteration in the DMN with CN, DMN with SMN, and AuN with CN. Significant reduced connectivity changes in the DMN with VN was found in State 4. Furthermore, the number of transitions (r=0.394, p=0.005) between states was positively associated with headache frequency. Additionally, dwell time (r=-0.320, p=0.025) in State 1 was negatively correlated with MoCA score. CONCLUSIONS: MTBI patients with PTH are characterized with altered sFNC and dFNC, which could provide new perspective to understand the neuropathological mechanism underlying the PTH to determine more appropriate management, and may be a useful imaging biomarker for identifying and predicting mTBI with PTH.