Regional structural abnormalities in thalamus in idiopathic cervical dystonia.

BACKGROUND: The thalamus has a central role in the pathophysiology of idiopathic cervical dystonia (iCD); however, the nature of alterations occurring within this structure remain largely elusive. Using a structural magnetic resonance imaging (MRI) approach, we examined whether abnormalities differ across thalamic subregions/nuclei in patients with iCD. METHODS: Structural MRI data were collected from 37 patients with iCD and 37 healthy controls (HCs). Automatic parcellation of 25 thalamic nuclei in each hemisphere was performed based on the FreeSurfer program. Differences in thalamic nuclei volumes between groups and their relationships with clinical information were analysed in patients with iCD. RESULTS: Compared to HCs, a significant reduction in thalamic nuclei volume primarily in central medial, centromedian, lateral geniculate, medial geniculate, medial ventral, paracentral, parafascicular, paratenial, and ventromedial nuclei was found in patients with iCD (P < 0.05, false discovery rate corrected). However, no statistically significant correlations were observed between altered thalamic nuclei volumes and clinical characteristics in iCD group. CONCLUSION: This study highlights the neurobiological mechanisms of iCD related to thalamic volume changes.

Supplementary motor area driving changes of structural brain network in blepharospasm.

Blepharospasm is traditionally thought to be a movement disorder that results from basal ganglia dysfunction. Recently, accumulating morphometric studies have revealed structural alterations outside the basal ganglia, such as in the brainstem, cerebellum and sensorimotor cortex, suggesting that blepharospasm may result from network disorders. However, the temporal and causal relationships between structural alterations and whether there are disease duration-related hierarchical structural changes in these patients remain largely unknown. Structural MRI was performed in 62 patients with blepharospasm, 62 patients with hemifacial spasm and 62 healthy controls to assess the structural alterations using voxel-based morphology and structural covariance networks. The use of the causal structural covariance network, modularity analysis and functional decoding were subsequently performed to map the causal effect of grey matter change pattern, hierarchical topography and functional characterizations of the structural network throughout the disease duration of blepharospasm. Greater grey matter volume in the left and right supplementary motor areas was identified in patients with blepharospasm compared to that in patients with hemifacial spasm and healthy controls, whereas no significant difference was identified between patients with hemifacial spasm and healthy controls. In addition, increased grey matter volume covariance between the right supplementary motor area and right brainstem, left superior frontal gyrus, left supplementary motor area and left paracentral gyrus was found in patients with blepharospasm compared to healthy controls. Further causal structural covariance network, modularity analysis and functional decoding showed that the right supplementary motor area served as a driving core in patients with blepharospasm, extending greater grey matter volume to areas in the cortico-basal ganglia-brainstem motor pathway and cortical regions in the vision-motor integration pathway. Taken together, our results suggest that the right supplementary motor area is an early and important pathologically impaired region in patients with blepharospasm. With a longer duration of blepharospasm, increased grey matter volume extends from the right supplementary motor area to the cortico-basal ganglia motor and visual-motor integration pathways, showing a hierarchy of structural abnormalities in the disease progression of blepharospasm, which provides novel evidence to support the notion that blepharospasm may arise from network disorders and is associated with a wide range of grey matter abnormalities.

Volume of hippocampus-amygdala transition area predicts outcomes of electroconvulsive therapy in major depressive disorder: high accuracy validated in two independent cohorts.

BACKGROUND: Although many previous studies reported structural plasticity of the hippocampus and amygdala induced by electroconvulsive therapy (ECT) in major depressive disorder (MDD), yet the exact roles of both areas for antidepressant effects are still controversial. METHODS: In the current study, segmentation of amygdala and hippocampal sub-regions was used to investigate the longitudinal changes of volume, the relationship between volume and antidepressant effects, and prediction performances for ECT in MDD patients before and after ECT using two independent datasets. RESULTS: As a result, MDD patients showed selectively and consistently increased volume in the left lateral nucleus, right accessory basal nucleus, bilateral basal nucleus, bilateral corticoamygdaloid transition (CAT), bilateral paralaminar nucleus of the amygdala, and bilateral hippocampus-amygdala transition area (HATA) after ECT in both datasets, whereas marginally significant increase of volume in bilateral granule cell molecular layer of the head of dentate gyrus, the bilateral head of cornu ammonis (CA) 4, and left head of CA 3. Correlation analyses revealed that increased volume of left HATA was significantly associated with antidepressant effects after ECT. Moreover, volumes of HATA in the MDD patients before ECT could be served as potential biomarkers to predict ECT remission with the highest accuracy of 86.95% and 82.92% in two datasets (The predictive models were trained on Dataset 2 and the sensitivity, specificity and accuracy of Dataset 2 were obtained from leave-one-out-cross-validation. Thus, they were not independent and very likely to be inflated). CONCLUSIONS: These results not only suggested that ECT could selectively induce structural plasticity of the amygdala and hippocampal sub-regions associated with antidepressant effects of ECT in MDD patients, but also provided potential biomarkers (especially HATA) for effectively and timely interventions for ECT in clinical applications.

Delineating functional segregations of the human middle temporal gyrus with resting-state functional connectivity and coactivation patterns.

Although the middle temporal gyrus (MTG) has been parcellated into subregions with distinguished anatomical connectivity patterns, whether the structural topography of MTG can inform functional segregations of this area remains largely unknown. Accumulating evidence suggests that the brain's underlying organization and function can be directly and effectively delineated with resting-state functional connectivity (RSFC) by identifying putative functional boundaries between cortical areas. Here, RSFC profiles were used to explore functional segregations of the MTG and defined four subregions from anterior to posterior in two independent datasets, which showed a similar pattern with MTG parcellation scheme obtained using anatomical connectivity. The functional segregations of MTG were further supported by whole brain RSFC, coactivation, and specific RFSC, and coactivation mapping. Furthermore, the fingerprint with predefined 10 networks and functional characterizations of each subregion using meta-analysis also identified functional distinction between subregions. The specific connectivity analysis and functional characterization indicated that the bilateral most anterior subregions mainly participated in social cognition and semantic processing; the ventral middle subregions were involved in social cognition in left hemisphere and auditory processing in right hemisphere; the bilateral ventro-posterior subregions participated in action observation, whereas the left subregion was also involved in semantic processing; both of the dorsal subregions in superior temporal sulcus were involved in language, social cognition, and auditory processing. Taken together, our findings demonstrated MTG sharing similar structural and functional topographies and provide more detailed information about the functional organization of the MTG, which may facilitate future clinical and cognitive research on this area.

Alterations of the Brain Microstructure and Corresponding Functional Connectivity in Early-Blind Adolescents.

Although evidence from studies on blind adults indicates that visual deprivation early in life leads to structural and functional disruption and reorganization of the brain, whether young blind people show similar patterns remains unknown. Therefore, this study is aimed at exploring the structural and functional alterations of the brain of early-blind adolescents (EBAs) compared to normal-sighted controls (NSCs) and investigating the effects of residual light perception on brain microstructure and function in EBAs. We obtained magnetic resonance imaging (MRI) data from 23 EBAs (8 with residual light perception (LPs), 15 without light perception (NLPs)) and 21 NSCs (age range 11-19 years old). Whole-brain voxel-based analyses of diffusion tensor imaging metrics and region-of-interest analyses of resting-state functional connectivity (RSFC) were performed to compare patterns of brain microstructure and the corresponding RSFC between the groups. The results showed that structural disruptions of LPs and NLPs were mainly located in the occipital visual pathway. Compared with NLPs, LPs showed increased fractional anisotropy (FA) in the superior frontal gyrus and reduced diffusivity in the caudate nucleus. Moreover, the correlations between FA of the occipital cortices or mean diffusivity of the lingual gyrus and age were consistent with the development trajectory of the brain in NSCs, but inconsistent or even opposite in EBAs. Additionally, we found functional, but not structural, reorganization in NLPs compared with NSCs, suggesting that functional neuroplasticity occurs earlier than structural neuroplasticity in EBAs. Altogether, these findings provided new insights into the mechanisms underlying the neural reorganization of the brain in adolescents with early visual deprivation.

Automated chest screening based on a hybrid model of transfer learning and convolutional sparse denoising autoencoder.

OBJECTIVE: In this paper, we aim to investigate the effect of computer-aided triage system, which is implemented for the health checkup of lung lesions involving tens of thousands of chest X-rays (CXRs) that are required for diagnosis. Therefore, high accuracy of diagnosis by an automated system can reduce the radiologist's workload on scrutinizing the medical images. METHOD: We present a deep learning model in order to efficiently detect abnormal levels or identify normal levels during mass chest screening so as to obtain the probability confidence of the CXRs. Moreover, a convolutional sparse denoising autoencoder is designed to compute the reconstruction error. We employ four publicly available radiology datasets pertaining to CXRs, analyze their reports, and utilize their images for mining the correct disease level of the CXRs that are to be submitted to a computer aided triaging system. Based on our approach, we vote for the final decision from multi-classifiers to determine which three levels of the images (i.e. normal, abnormal, and uncertain cases) that the CXRs fall into. RESULTS: We only deal with the grade diagnosis for physical examination and propose multiple new metric indices. Combining predictors for classification by using the area under a receiver operating characteristic curve, we observe that the final decision is related to the threshold from reconstruction error and the probability value. Our method achieves promising results in terms of precision of 98.7 and 94.3% based on the normal and abnormal cases, respectively. CONCLUSION: The results achieved by the proposed framework show superiority in classifying the disease level with high accuracy. This can potentially save the radiologists time and effort, so as to allow them to focus on higher-level risk CXRs.

Anterior lens capsule and epithelium thickness measurements using spectral-domain optical coherence tomography.

BACKGROUND: To investigate the anterior lens capsule and epithelium thickness (defined as anterior lens capsular complex: ALCC) in normal Chinese subjects using spectral-domian optical coherence tomography (SD-OCT) and examine the factors that may influence the ALCC, such as age, gender, pupil diameter (PD) and signal strength index (SSI). METHODS: A prospective observational case series. One-hundred-thirty-four normal subjects (134 eyes) were included. The ALCCs were determined manually via SD-OCT. Using the pupil center as a reference position, the central ALCC (CALCC), nasal 1-mm ALCC (NALCC), temporal 1-mm ALCC (TALCC) and PD were measured manually. RESULTS: The mean CALCC, NALCC and TALCC were 33 ± 6 µm, 36 ± 7 µm and 34 ± 6 µm, respectively. The NALCC was significantly thicker than the CALCC (P < .001) and TALCC (P < .001). Moreover, CALCC was significantly thinner than TALCC (P = 0.013). Age was positively correlated with the CALCC (r = 0.292, P < .001), NALCC (r = 0.400, P < .001) and TALCC (r = 0.521, P < .001). PD, gender and SSI were not significantly correlated with the three ALCC parameters. CONCLUSIONS: The SD-OCT can be used to demonstrate the ALCC thickness, and age is positively correlated with the ALCC in the central, nasal and temporal sides.

Computational evaluation of smoothed particle hydrodynamics for implementing blood flow modelling through CT reconstructed arteries.

Simulation of blood flow in a stenosed artery using Smoothed Particle Hydrodynamics (SPH) is a new research field, which is a particle-based method and different from the traditional continuum modelling technique such as Computational Fluid Dynamics (CFD). Both techniques harness parallel computing to process hemodynamics of cardiovascular structures. The objective of this study is to develop and test a new robust method for comparison of arterial flow velocity contours by SPH with the well-established CFD technique, and the implementation of SPH in computed tomography (CT) reconstructed arteries. The new method was developed based on three-dimensional (3D) straight and curved arterial models of millimeter range with a 25% stenosis in the middle section. In this study, we employed 1,000 to 13,000 particles to study how the number of particles influences SPH versus CFD deviation for blood-flow velocity distribution. Because further increasing the particle density has a diminishing effect on this deviation, we have determined a critical particle density of 1.45 particles/mm2 based on Reynolds number (Re = 200) at the inlet for an arterial flow simulation. Using this critical value of particle density can avoid unnecessarily big computational expenses that have no further effect on simulation accuracy. We have particularly shown that the SPH method has a big potential to be used in the virtual surgery system, such as to simulate the interaction between blood flow and the CT reconstructed vessels, especially those with stenosis or plaque when encountering vasculopathy, and for employing the simulation results output in clinical surgical procedures.

Robust kernelized local information fuzzy C-means clustering for brain magnetic resonance image segmentation.

Brain tissue segmentation from magnetic resonance (MR) images is an importance task for clinical use. The segmentation process becomes more challenging in the presence of noise, grayscale inhomogeneity, and other image artifacts. In this paper, we propose a robust kernelized local information fuzzy C-means clustering algorithm (RKLIFCM). It incorporates local information into the segmentation process (both grayscale and spatial) for more homogeneous segmentation. In addition, the Gaussian radial basis kernel function is adopted as a distance metric to replace the standard Euclidean distance. The main advantages of the new algorithm are: efficient utilization of local grayscale and spatial information, robustness to noise, ability to preserve image details, free from any parameter initialization, and with high speed as it runs on image histogram. We compared the proposed algorithm with 7 soft clustering algorithms that run on both image histogram and image pixels to segment brain MR images. Experimental results demonstrate that the proposed RKLIFCM algorithm is able to overcome the influence of noise and achieve higher segmentation accuracy with low computational complexity.

Enhancing the clinical value of single-phase computed tomography angiography in the assessment of collateral circulation in acute ischemic stroke: A narrative review.

Acute ischemic stroke (AIS) condition assessment and clinical prognosis are significantly influenced by the compensatory state of cerebral collateral circulation. A standard clinical test known as single-phase computed tomography angiography (sCTA) is useful for quickly and accurately assessing the creation or opening of cerebral collateral circulation, which is crucial for the diagnosis and treatment of AIS. To improve the clinical application of sCTA in the clinical assessment of collateral circulation, we examine the present use of sCTA in AIS in this work.

Early Diagnosing and Transformation Prediction of Alzheimer's Disease Using Multi-Scaled Self-Attention Network on Structural MRI Images with Occlusion Sensitivity Analysis.

BACKGROUND: Structural magnetic resonance imaging (sMRI) is vital for early Alzheimer's disease (AD) diagnosis, though confirming specific biomarkers remains challenging. Our proposed Multi-Scale Self-Attention Network (MUSAN) enhances classification of cognitively normal (CN) and AD individuals, distinguishing stable (sMCI) from progressive mild cognitive impairment (pMCI). OBJECTIVE: This study leverages AD structural atrophy properties to achieve precise AD classification, combining different scales of brain region features. The ultimate goal is an interpretable algorithm for this method. METHODS: The MUSAN takes whole-brain sMRI as input, enabling automatic extraction of brain region features and modeling of correlations between different scales of brain regions, and achieves personalized disease interpretation of brain regions. Furthermore, we also employed an occlusion sensitivity algorithm to localize and visualize brain regions sensitive to disease. RESULTS: Our method is applied to ADNI-1, ADNI-2, and ADNI-3, and achieves high performance on the classification of CN from AD with accuracy (0.93), specificity (0.82), sensitivity (0.96), and area under curve (AUC) (0.95), as well as notable performance on the distinguish of sMCI from pMCI with accuracy (0.85), specificity (0.84), sensitivity (0.74), and AUC (0.86). Our sensitivity masking algorithm identified key regions in distinguishing CN from AD: hippocampus, amygdala, and vermis. Moreover, cingulum, pallidum, and inferior frontal gyrus are crucial for sMCI and pMCI discrimination. These discoveries align with existing literature, confirming the dependability of our model in AD research. CONCLUSION: Our method provides an effective AD diagnostic and conversion prediction method. The occlusion sensitivity algorithm enhances deep learning interpretability, bolstering AD research reliability.

The short-term effects of Jin's three needles in conjunction with mirror therapy on brain function in patients with upper limb disability following an ischemic stroke were evaluated using ReHo analysis.

BACKGROUND: Jin's three needle (JTN) is a commonly utilized treatment for ischemic stroke in China. Mirror therapy (MT) is also gradually transitioning from treating limb discomfort to restoring motor function in the damaged limb. Investigations into the 2 treatments' mechanisms of action are still ongoing. We used functional magnetic resonance imaging (fMRI) technique in this study to examine the effects of JTN combined with mirror therapy MT on brain function in patients with upper limb dysfunction in ischemic stroke, as well as potential central mechanisms. The goal was to provide a solid evidence-based medical basis to support the continued use of JTN combination MT. METHODS: This study will be a single-blind, randomized, and controlled experiment. Randomization was used to assign 20 patients who met the study's eligibility requirements to the JTN + MT treatment group or the JTN control group. Each intervention will last for 4 weeks, with 6 days of treatment per week. The JTN acupuncture points are 3 temporal acupuncture points on the opposite side of the wounded limb, 3 hand acupuncture points on the injured upper limb, 3 shoulder acupuncture points, Renzhong and Baihui, The (JTN + MT) group simultaneously takes MT for 30 minutes. fMRI of the brain using BOLD and T1-weighted images was done both before and after therapy. Brain areas exhibiting changes in regional homogeneity during the pre and posttreatment periods were analyzed. RESULTS: By the end of the treatment course, Jin three-needle therapy plus MT activated more relevant brain functional regions and increased cerebral blood oxygen perfusion than Jin three-needle therapy alone (P <.05). CONCLUSION: In patients with upper limb impairment following an ischemic stroke, JTN with MT may improve brain function reconstruction in the relevant areas.

Molecular mechanisms underlying structural plasticity of electroconvulsive therapy in major depressive disorder.

Although previous studies reported structural changes associated with electroconvulsive therapy (ECT) in major depressive disorder (MDD), the underlying molecular basis of ECT remains largely unknown. Here, we combined two independent structural MRI datasets of MDD patients receiving ECT and transcriptomic gene expression data from Allen Human Brain Atlas to reveal the molecular basis of ECT for MDD. We performed partial least square regression to explore whether/how gray matter volume (GMV) alterations were associated with gene expression level. Functional enrichment analysis was conducted using Metascape to explore ontological pathways of the associated genes. Finally, these genes were further assigned to seven cell types to determine which cell types contribute most to the structural changes in MDD patients after ECT. We found significantly increased GMV in bilateral hippocampus in MDD patients after ECT. Transcriptome-neuroimaging association analyses showed that expression levels of 726 genes were positively correlated with the increased GMV in MDD after ECT. These genes were mainly involved in synaptic signaling, calcium ion binding and cell-cell signaling, and mostly belonged to excitatory and inhibitory neurons. Moreover, we found that the MDD risk genes of CNR1, HTR1A, MAOA, PDE1A, and SST as well as ECT related genes of BDNF, DRD2, APOE, P2RX7, and TBC1D14 showed significantly positive associations with increased GMV. Overall, our findings provide biological and molecular mechanisms underlying structural plasticity induced by ECT in MDD and the identified genes may facilitate future therapy for MDD.

Focal cortical dysplasia lesion segmentation using multiscale transformer.

OBJECTIVES: Accurate segmentation of focal cortical dysplasia (FCD) lesions from MR images plays an important role in surgical planning and decision but is still challenging for radiologists and clinicians. In this study, we introduce a novel transformer-based model, designed for the end-to-end segmentation of FCD lesions from multi-channel MR images. METHODS: The core innovation of our proposed model is the integration of a convolutional neural network-based encoder-decoder structure with a multiscale transformer to augment the feature representation of lesions in the global field of view. Transformer pathways, composed of memory- and computation-efficient dual-self-attention modules, leverage feature maps from varying depths of the encoder to discern long-range interdependencies among feature positions and channels, thereby emphasizing areas and channels relevant to lesions. The proposed model was trained and evaluated on a public-open dataset including MR images of 85 patients using both subject-level and voxel-level metrics. RESULTS: Experimental results indicate that our model offers superior performance both quantitatively and qualitatively. It successfully identified lesions in 82.4% of patients, with a low false-positive lesion cluster rate of 0.176 ± 0.381 per patient. Furthermore, the model achieved an average Dice coefficient of 0.410 ± 0.288, outperforming five established methods. CONCLUSION: Integration of the transformer could enhance the feature presentation and segmentation performance of FCD lesions. The proposed model has the potential to serve as a valuable assistive tool for physicians, enabling rapid and accurate identification of FCD lesions. The source code and pre-trained model weights are available at https://github.com/zhangxd0530/MS-DSA-NET . CRITICAL RELEVANCE STATEMENT: This multiscale transformer-based model performs segmentation of focal cortical dysplasia lesions, aiming to help radiologists and clinicians make accurate and efficient preoperative evaluations of focal cortical dysplasia patients from MR images. KEY POINTS: The first transformer-based model was built to explore focal cortical dysplasia lesion segmentation. Integration of global and local features enhances the segmentation performance of lesions. A valuable benchmark for model development and comparative analyses was provided.

Progressive thalamic nuclear atrophy in blepharospasm and blepharospasm-oromandibular dystonia.

The thalamus is considered a key region in the neuromechanisms of blepharospasm. However, previous studies considered it as a single, homogeneous structure, disregarding potentially useful information about distinct thalamic nuclei. Herein, we aimed to examine (i) whether grey matter volume differs across thalamic subregions/nuclei in patients with blepharospasm and blepharospasm-oromandibular dystonia; (ii) causal relationships among abnormal thalamic nuclei; and (iii) whether these abnormal features can be used as neuroimaging biomarkers to distinguish patients with blepharospasm from blepharospasm-oromandibular dystonia and those with dystonia from healthy controls. Structural MRI data were collected from 56 patients with blepharospasm, 20 with blepharospasm-oromandibular dystonia and 58 healthy controls. Differences in thalamic nuclei volumes between groups and their relationships to clinical information were analysed in patients with dystonia. Granger causality analysis was employed to explore the causal effects among abnormal thalamic nuclei. Support vector machines were used to test whether these abnormal features could distinguish patients with different forms of dystonia and those with dystonia from healthy controls. Compared with healthy controls, patients with blepharospasm exhibited reduced grey matter volume in the lateral geniculate and pulvinar inferior nuclei, whereas those with blepharospasm-oromandibular dystonia showed decreased grey matter volume in the ventral anterior and ventral lateral anterior nuclei. Atrophy in the pulvinar inferior nucleus in blepharospasm patients and in the ventral lateral anterior nucleus in blepharospasm-oromandibular dystonia patients was negatively correlated with clinical severity and disease duration, respectively. The proposed machine learning scheme yielded a high accuracy in distinguishing blepharospasm patients from healthy controls (accuracy: 0.89), blepharospasm-oromandibular dystonia patients from healthy controls (accuracy: 0.82) and blepharospasm from blepharospasm-oromandibular dystonia patients (accuracy: 0.94). Most importantly, Granger causality analysis revealed that a progressive driving pathway from pulvinar inferior nuclear atrophy extends to lateral geniculate nuclear atrophy and then to ventral lateral anterior nuclear atrophy with increasing clinical severity in patients with blepharospasm. These findings suggest that the pulvinar inferior nucleus in the thalamus is the focal origin of blepharospasm, extending to pulvinar inferior nuclear atrophy and subsequently extending to the ventral lateral anterior nucleus causing involuntary lower facial and masticatory movements known as blepharospasm-oromandibular dystonia. Moreover, our results also provide potential targets for neuromodulation especially deep brain stimulation in patients with blepharospasm and blepharospasm-oromandibular dystonia.

Functional magnetic resonance imaging studies of acupuncture at ST36: a coordinate-based meta-analysis.

Background: Functional magnetic resonance imaging (fMRI) has been widely used to investigate the brain effect of acupuncture point Stomach 36 (ST36, Zusanli). However, inconsistent results have hindered our understanding of the neural mechanisms of acupuncture at ST36. Objective: To perform a meta-analysis of fMRI studies on acupuncture at ST36 to assess the brain atlas of acupuncture at ST36 from available studies. Method: Based on a preregistered protocol in PROSPERO (CRD42019119553), a large set of databases was searched up to August 9, 2021, without language restrictions. Peak coordinates were extracted from clusters that showed significant signal differences before and after acupuncture treatment. A meta-analysis was performed using seed-based d mapping with permutation of subject images (SDM-PSI), a newly improved meta-analytic method. Results: A total of 27 studies (27 ST36) were included. This meta-analysis found that ST36 could activate the left cerebellum, the bilateral Rolandic operculum, the right supramarginal gyrus, and the right cerebellum. Functional characterizations showed that acupuncture at ST36 was mainly associated with action and perception. Conclusion: Our results provide a brain atlas for acupuncture at ST36, which, besides offering a better understanding of the underlying neural mechanisms, also provides the possibility of future precision therapies.

Neural Correlates of Facial Emotion Recognition Impairment in Blepharospasm: A Functional Magnetic Resonance Imaging Study.

Selective impairment in recognizing facial expressions of disgust was reported in patients with focal dystonia several years ago, but the basic neural mechanisms remain largely unexplored. Therefore, we investigated whether dysfunction of the brain network involved in disgust recognition processing was related to this selective impairment in blepharospasm. Facial emotion recognition evaluations and resting-state functional magnetic resonance imaging were performed in 33 blepharospasm patients and 33 healthy controls (HCs). The disgust processing network was constructed, and modularity analyses were performed to identify sub-networks. Regional functional indexes and intra- and inter-functional connections were calculated and compared between the groups. Compared to HCs, blepharospasm patients demonstrated a worse performance in disgust recognition. In addition, functional connections within the sub-network involved in perception processing rather than recognition processing of disgust were significantly decreased in blepharospasm patients compared to HCs. Specifically, decreased functional connections were noted between the left fusiform gyrus (FG) and right middle occipital gyrus (MOG), the left FG and right FG, and the right FG and left MOG. We identified decreased functional activity in these regions, as indicated by a lower amplitude of low-frequency fluctuation in the left MOG, fractional amplitude of low-frequency fluctuation in the right FG, and regional homogeneity in the right FG and left MOG in blepharospasm patients versus HCs. Our results suggest that dysfunctions of the disgust processing network exist in blepharospasm. A deficit in disgust emotion recognition may be attributed to disturbances in the early perception of visual disgust stimuli in blepharospasm patients.

Cortico-basal ganglia networks dysfunction associated with disease severity in patients with idiopathic blepharospasm.

Background: Structural changes occur in brain regions involved in cortico-basal ganglia networks in idiopathic blepharospasm (iBSP); whether these changes influence the function connectivity patterns of cortico-basal ganglia networks remains largely unknown. Therefore, we aimed to investigate the global integrative state and organization of functional connections of cortico-basal ganglia networks in patients with iBSP. Methods: Resting-state functional magnetic resonance imaging data and clinical measurements were acquired from 62 patients with iBSP, 62 patients with hemifacial spasm (HFS), and 62 healthy controls (HCs). Topological parameters and functional connections of cortico-basal ganglia networks were evaluated and compared among the three groups. Correlation analyses were performed to explore the relationship between topological parameters and clinical measurements in patients with iBSP. Results: We found significantly increased global efficiency and decreased shortest path length and clustering coefficient of cortico-basal ganglia networks in patients with iBSP compared with HCs, however, such differences were not observed between patients with HFS and HCs. Further correlation analyses revealed that these parameters were significantly correlated with the severity of iBSP. At the regional level, the functional connectivity between the left orbitofrontal area and left primary somatosensory cortex and between the right anterior part of pallidum and right anterior part of dorsal anterior cingulate cortex was significantly decreased in patients with iBSP and HFS compared with HCs. Conclusion: Dysfunction of the cortico-basal ganglia networks occurs in patients with iBSP. The altered network metrics of cortico-basal ganglia networks might be served as quantitative markers for evaluation of the severity of iBSP.

Structural and Functional Trajectories of Middle Temporal Gyrus Sub-Regions During Life Span: A Potential Biomarker of Brain Development and Aging.

Although previous studies identified a similar topography pattern of structural and functional delineations in human middle temporal gyrus (MTG) using healthy adults, trajectories of MTG sub-regions across lifespan remain largely unknown. Herein, we examined gray matter volume (GMV) and resting-state functional connectivity (RSFC) using datasets from the Nathan Kline Institute (NKI), and aimed to (1) investigate structural and functional trajectories of MTG sub-regions across the lifespan; and (2) assess whether these features can be used as biomarkers to predict individual's chronological age. As a result, GMV of all MTG sub-regions followed U-shaped trajectories with extreme age around the sixth decade. The RSFC between MTG sub-regions and many cortical brain regions showed inversed U-shaped trajectories, whereas RSFC between MTG sub-regions and sub-cortical regions/cerebellum showed U-shaped way, with extreme age about 20 years earlier than those of GMV. Moreover, GMV and RSFC of MTG sub-regions could be served as useful features to predict individual age with high estimation accuracy. Together, these results not only provided novel insights into the dynamic process of structural and functional roles of MTG sub-regions across the lifespan, but also served as useful biomarkers to age prediction.

Acupuncture Treatment Modulate Regional Homogeneity of Dorsal Lateral Prefrontal Cortex in Patients with Amnesic Mild Cognitive Impairment.

BACKGROUND: Although acupuncture is widely used to improve cognitive and memory in the amnesic mild cognitive impairment (aMCI) patients with impressive effectiveness, its neural mechanism remains largely unclear. OBJECTIVE: We aimed to explore functional magnetic resonance imaging (fMRI) mechanism of acupuncture for aMCI. METHODS: A randomized, controlled, single-blind research was performed. A total of 46 aMCI patients were randomly assigned into verum and sham acupuncture group, who received a total of 24 times treatments (3 times/week, 8 weeks). Clinical evaluation and fMRI scanning were performed at baseline and after treatment for all aMCI patients. The interaction effects and inter-group effects of regional homogeneity (ReHo) were performed using mixed effect models, and the correlations between clinical improvement and neuroimaging changes before and after verum acupuncture treatment were analyzed using Pearson correlations. RESULTS: As a result, interaction effects showed increased ReHo value in left dorsal lateral prefrontal cortex (DLPFC), increased functional connectivity between left DLPFC and left precuneus, and decreased functional connectivity between left DLPFC and left inferior temporal gyrus after verum acupuncture but inversely after sham acupuncture in the aMCI. Condition effects showed increased ReHo in right lingual gyrus, and bilateral post-central gyrus after verum and sham acupuncture in the aMCI. In addition, the changed Montreal Cognitive Assessment scores in verum acupuncture group were significantly correlated with changed ReHo values in left DLPFC. CONCLUSION: Together, our findings further confirmed that acupuncture could be used as a promising complementary therapy for aMCI by modulating function of left DLPFC to improve cognitive symptoms.