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Studies have demonstrated the potential of repetitive transcranial magnetic stimulation (rTMS) to decrease smoking cravings in individuals with tobacco use disorder (TUD). However, the neural features underlying the effects of rTMS treatment, especially the dynamic attributes of brain networks associated with the treatment, remain unclear. Using dynamic functional connectivity analysis, this study first explored the differences in dynamic functional network features between 60 subjects with TUD and 64 nonsmoking healthy controls (HCs). Then, the left dorsolateral prefrontal cortex (DLPFC) was targeted for a five-day course of rTMS treatment in the 60 subjects with TUD (active rTMS in 42 subjects and sham treatment in 18 subjects). We explored the effect of rTMS on the dynamic network features associated with rTMS by comparing the actively treated group and the sham group. Compared to nonsmokers, TUD subjects exhibited an increased integration coefficient between the frontoparietal network (FPN) and the basal ganglia network (BGN) and a reduced integration coefficient between the medial frontal network (MFN) and the FPN. Analysis of variance revealed that rTMS treatment reduced the integration coefficient between the FPN and BGN and improved the recruitment coefficient of the FPN. This study involved a limited sample of young male smokers, and the findings may not generalize to older smokers or female smokers with an extensive history of smoking. rTMS treatment of the left DLPFC exhibited significant effectiveness in restructuring the neural circuits associated with TUD while significantly mitigating smoking cravings. • a five-day course of rTMS treatments over left DLPFC reduced cravings in smokers • The dynamic neural mechanism of rTMS in the treatment of smoking is revealed • rTMS treatment reconstructed the prefrontal-striatal circuit in smokers [ABSTRACT FROM AUTHOR]

Parkinson’s disease (PD) is a neurodegenerative disease with cognitive as well as motor impairments. While much is known about the brain networks leading to motor impairments in PD, less is known about the brain networks contributing to cognitive impairments. Here, we leveraged resting-state functional magnetic resonance imaging (rs-fMRI) data from the Parkinson’s Progression Marker Initiative (PPMI) to examine network dysfunction in PD patients with cognitive impairment. We focus on canonical cortical networks linked to cognition, including the salience network (SAL), frontoparietal network (FPN), and default mode network (DMN), as well as a subcortical basal ganglia network (BGN). We used the Montreal Cognitive Assessment (MoCA) as a continuous index of coarse cognitive function in PD. In 82 PD patients, we found that lower MoCA scores were linked with lower intra-network connectivity of the FPN. We also found that lower MoCA scores were linked with lower inter-network connectivity between the SAL and the BGN, the SAL and the DMN, as well as the FPN and the DMN. These data elucidate the relationship of cortical and subcortical functional connectivity with cognitive impairments in PD.

Ya-Jun Wu,1,&ast; Jie Rao,1,&ast; Xin Huang,2 Na Wu,1 Ling Shi,1 Hui Huang,1 Si-Yu Li,1 Xiao-Lin Chen,1 Shui-Qin Huang,1 Pei-Pei Zhong,1 Xiao-Rong Wu,1 Jun Wang3 1Department of Ophthalmology, The First Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province, People’s Republic of China; 2Department of Ophthalmology, Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, Jiangxi Province, People’s Republic of China; 3Department of Respiratory Disease, Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, Jiangxi Province, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jun Wang Email wangjun5087@163.comPurpose: Converging evidence demonstrated that bronchial asthma (BA) individuals with hypoxia were associated with functional and morphological reorganization in the brain. However, the alterations of the interhemispheric functional connectivity in BA individuals remain unknown. The purpose of this study was to assess the interhemispheric functional connectivity changes in individuals with hypoxia due to middle-aged BA using voxel-mirrored homotopic connectivity (VMHC) methods.Methods: In total, 31 BA individuals and 30 healthy controls (HCs) closely matched in age, sex, and education underwent resting-state magnetic resonance imaging (MRI) scans. VMHC analysis was performed to investigate differences in interhemispheric functional connectivity between the two groups. Then, a seed-based resting-state functional connectivity (rsFC) analysis was conducted to further reveal the abnormal functional connectivity between the altered VMHC regions and the whole brain.Results: Compared with HCs, BA individuals had significantly lower VMHC values in the bilateral basal ganglia/thalamus/insula, cuneus/calcarine/lingual gyrus, precentral and postcentral gyrus. [voxel level P < 0.01, Gaussian random field (GRF) correction, cluster level P < 0.05]. Taking VMHC altered brain areas as seed points, the rsFC values of left insula/supramarginal/postcentral gyrus (PostCG)/inferior parietal lobule (IPL) brain areas in BA were increased.Conclusion: The abnormal resting-state functional connectivity of middle-aged BA is altered in specific brain regions related to the basal ganglia network, visual network, and sensorimotor network, which may be related to the neuropathogenesis of asthma patients. Furthermore, these VMHC and FC values may be important clinical indicators for the diagnosis and treatment of asthma patients.Keywords: bronchial asthma, voxel-mirrored homotopic connectivity, functional magnetic resonance imaging, basal ganglia network, visual network, sensorimotor network

Deep brain stimulation (DBS) alleviates the symptoms of tremor, rigidity, and akinesia of the Parkinson's disease (PD). Over decades of the clinical experience, subthalamic nucleus (STN), globus pallidus externa (GPe) and globus pallidus internal (GPi) have been chosen as the common DBS target sites. However, how to design the DBS waveform is still a challenging problem. There is evidence that chronic high-frequency stimulation may cause long-term tissue damage and other side effects. In this paper, we apply a form of DBS with delayed rectangular waveform, denoted as pulse-delay-pulse (PDP) type DBS, on multiple-site based on a computational model of the basal ganglia-thalamus (BG-TH) network. We mainly investigate the effects of the stimulation frequency on relay reliability of the thalamus neurons, beta band oscillation of GPi nucleus and firing rate of the BG network. The results show that the PDP-type DBS at STN-GPe site results in better performance at lower frequencies, while the DBS at GPi-GPe site causes the number of spikes of STN to decline and deviate from the healthy status. Fairly good therapeutic effects can be achieved by PDP-type DBS at STN-GPi site only at higher frequencies. Thus, it is concluded that the application of multiple-site stimulation with PDP-type DBS at STN-GPe is of great significance in treating symptoms of neurological disorders in PD. [ABSTRACT FROM AUTHOR]

Summary: Parkinson’s disease is characterized by both hypokinetic and hyperkinetic symptoms. While increased subthalamic burst discharges have a direct causal relationship with the hypokinetic manifestations (e.g., rigidity and bradykinesia), the origin of the hyperkinetic symptoms (e.g., resting tremor and propulsive gait) has remained obscure. Neuronal burst discharges are presumed to be autonomous or less responsive to synaptic input, thereby interrupting the information flow. We, however, demonstrate that subthalamic burst discharges are dependent on cortical glutamatergic synaptic input, which is enhanced by A-type K+ channel inhibition. Excessive top-down-triggered subthalamic burst discharges then drive highly correlative activities bottom-up in the motor cortices and skeletal muscles. This leads to hyperkinetic behaviors such as tremors, which are effectively ameliorated by inhibition of cortico-subthalamic AMPAergic synaptic transmission. We conclude that subthalamic burst discharges play an imperative role in cortico-subcortical information relay, and they critically contribute to the pathogenesis of both hypokinetic and hyperkinetic parkinsonian symptoms.

Disruption of brain circuits is one of the core mechanisms of Parkinson’s disease (PD). Understanding structural connection alterations in PD is important for effective treatment. However, due to methodological limitations, most studies were unable to account for confounding factors such as crossing fibers and were unable to identify damages to specific fiber tracts. In the present study, we aimed to demonstrate tract-specific white matter structural changes in PD patients and their relationship with clinical symptoms. Ninety-eight PD patients, divided into early (ES) and middle stage (MS) groups, and 76 healthy controls (HCs) underwent brain magnetic resonance imaging scans and clinical assessments. Fixel-based analysis was used to investigate fiber tract alterations in PD patients. Compared to HCs, the PD patients showed decreased fiber density (FD) in the corpus callosum (CC), increased FD in the cortical spinal tract (CST), and increased fiber-bundle cross-section (FC, log-transformed: log-FC) in the superior cerebellar peduncle (SCP). Analysis of variance (ANOVA) revealed significant differences in FD in the CST and log-FC in the SCP among the three groups. Post-hoc analysis revealed that the mean FD values of the CST were higher in ES and MS patient groups compared to HCs, and the mean log-FC values of the SCP were higher in ES and MS patient groups compared to HCs. Additionally, the FD values of the CC in PD patients were negatively correlated with the Unified Parkinson’s Disease Rating Scale part-III (UPDRS-III) scores (r = -0.257, p = 0.032), Hamilton Depression Rating Scale 17 Items (HAMD-17) scores (r = -0.230, p = 0.033), and Hamilton Anxiety Scale (HAMA) scores (r = -0.248, p = 0.032). Moreover, log-FC values of the SCP (r = 0.274, p = 0.028) and FD values of the CST (r = 0.384, p

Deep brain stimulation (DBS) has been proven to be an effective treatment to deal with the symptoms of Parkinson’s disease (PD). Currently, the DBS is in an open-loop pattern with which the stimulation parameters remain constant regardless of fluctuations in the disease state, and adjustments of parameters rely mostly on trial and error of experienced clinicians. This could bring adverse effects to patients due to possible overstimulation. Thus closed-loop DBS of which stimulation parameters are automatically adjusted based on variations in the ongoing neurophysiological signals is desired. In this paper, we present a closed-loop DBS method based on reinforcement learning (RL) to regulate stimulation parameters based on a computational model. The network model consists of interconnected biophysically-based spiking neurons, and the PD state is described as distorted relay reliability of thalamus (TH). Results show that the RL-based closed-loop control strategy can effectively restore the distorted relay reliability of the TH but with less DBS energy expenditure. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a neurodegenerative disease with cognitive as well as motor impairments. While much is known about the brain networks leading to motor impairments in PD, less is known about the brain networks contributing to cognitive impairments. Here, we leveraged resting-state functional magnetic resonance imaging (rs-fMRI) data from the Parkinson's Progression Marker Initiative (PPMI) to examine network dysfunction in PD patients with cognitive impairment. We focus on canonical cortical networks linked to cognition, including the salience network (SAL), frontoparietal network (FPN), and default mode network (DMN), as well as a subcortical basal ganglia network (BGN). We used the Montreal Cognitive Assessment (MoCA) as a continuous index of coarse cognitive function in PD. In 82 PD patients, we found that lower MoCA scores were linked with lower intra-network connectivity of the FPN. We also found that lower MoCA scores were linked with lower inter-network connectivity between the SAL and the BGN, the SAL and the DMN, as well as the FPN and the DMN. These data elucidate the relationship of cortical and subcortical functional connectivity with cognitive impairments in PD., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Deep brain stimulation (DBS) has compelling results in the desynchronization of the basal ganglia neuronal activities and thus, is used in treating the motor symptoms of Parkinson's disease (PD). Accurate definition of DBS waveform parameters could avert tissue or electrode damage, increase the neuronal activity and reduce energy cost which will prolong the battery life, hence avoiding device replacement surgeries. This study considers the use of a charge balanced Gaussian waveform pattern as a method to disrupt the firing patterns of neuronal cell activity. A computational model was created to simulate ganglia cells and their interactions with thalamic neurons. From the model, we investigated the effects of modified DBS pulse shapes and proposed a delay period between the cathodic and anodic parts of the charge balanced Gaussian waveform to desynchronize the firing patterns of the GPe and GPi cells. The results of the proposed Gaussian waveform with delay outperformed that of rectangular DBS waveforms used in in-vivo experiments. The Gaussian Delay Gaussian (GDG) waveforms achieved lower number of misses in eliciting action potential while having a lower amplitude and shorter length of delay compared to numerous different pulse shapes. The amount of energy consumed in the basal ganglia network due to GDG waveforms was dropped by 22% in comparison with charge balanced Gaussian waveforms without any delay between the cathodic and anodic parts and was also 60% lower than a rectangular charged balanced pulse with a delay between the cathodic and anodic parts of the waveform. Furthermore, by defining a Synchronization Level metric, we observed that the GDG waveform was able to reduce the synchronization of GPi neurons more effectively than any other waveform. The promising results of GDG waveforms in terms of eliciting action potential, desynchronization of the basal ganglia neurons and reduction of energy consumption can potentially enhance the performance of DBS devices.

Deep brain stimulation (DBS) has compelling results in the desynchronization of the basal ganglia neuronal activities and thus, is used in treating the motor symptoms of Parkinson's disease (PD). Accurate definition of DBS waveform parameters could avert tissue or electrode damage, increase the neuronal activity and reduce energy cost which will prolong the battery life, hence avoiding device replacement surgeries. This study considers the use of a charge balanced Gaussian waveform pattern as a method to disrupt the firing patterns of neuronal cell activity. A computational model was created to simulate ganglia cells and their interactions with thalamic neurons. From the model, we investigated the effects of modified DBS pulse shapes and proposed a delay period between the cathodic and anodic parts of the charge balanced Gaussian waveform to desynchronize the firing patterns of the GPe and GPi cells. The results of the proposed Gaussian waveform with delay outperformed that of rectangular DBS waveforms used in in-vivo experiments. The Gaussian Delay Gaussian (GDG) waveforms achieved lower number of misses in eliciting action potential while having a lower amplitude and shorter length of delay compared to numerous different pulse shapes. The amount of energy consumed in the basal ganglia network due to GDG waveforms was dropped by 22% in comparison with charge balanced Gaussian waveforms without any delay between the cathodic and anodic parts and was also 60% lower than a rectangular charged balanced pulse with a delay between the cathodic and anodic parts of the waveform. Furthermore, by defining a Synchronization Level metric, we observed that the GDG waveform was able to reduce the synchronization of GPi neurons more effectively than any other waveform. The promising results of GDG waveforms in terms of eliciting action potential, desynchronization of the basal ganglia neurons and reduction of energy consumption can potentially enhance the performance of DBS devices. [ABSTRACT FROM AUTHOR]

The basal ganglia involve in a range of functions which are disturbed in schizophrenia. This study decomposed the resting-state data of 28 schizophrenia patients and 31 healthy controls with spatial independent component analysis and identified increased functional connectivity in the bilateral caudate nucleus in schizophrenia. Further, the caudate nucleus in schizophrenia showed altered functional connection with the prefrontal area and cerebellum. These results identified the importance of basal ganglia in schizophrenia. Clinical Trial Registration: Chinese Clinical Trial Registry. Registration number. ChiCTR-RCS-14004878.

Background: The symptoms and pathogenesis of Parkinson’s disease (PD) are complicated and accurate diagnosis is difficult, particularly in early-stage. Functional magnetic resonance imaging is noninvasive and characterized by the integration of different brain areas at functional connectivity (FC). Considering pain process in PD, we hypothesized that pain is one of the earliest symptoms and investigated whether FC of the pain network was disrupted in PD without pain.Methods: Fourteen early drug-naïve PD without pain and 17 age- and sex-matched healthy controls (HC) participated in our test. We investigate abnormalities in FC and in functional network connectivity in PD compared with HC during the task (51 °C heat pain stimuli) and at rest.Results: Compared with HC, PD showed decreased FC in basal ganglia network (BGN), salience network (SN) and sensorimotor network in two states respectively. FNC between the BGN and the SN are reduced during both states in PD compared with HC. In addition, the FNC associated with right frontoparietal network (RFPN) was also significantly disturbed during the task.Conclusion: These findings suggest that BGN plays a role in the pathological mechanisms of pain underlying PD, and RFPN likely contributes greatly to harmonization between intrinsic brain activity and external stimuli.

Resting state fMRI (rfMRI) is gaining in popularity, being easy to acquire and with promising clinical applications. However, rfMRI studies, especially those involving clinical groups, still lack reproducibility, largely due to the different analysis settings. This is particularly important for the development of imaging biomarkers. The aim of this work was to evaluate the reproducibility of our recent study regarding the functional connectivity of the basal ganglia network in early Parkinson's disease (PD) (Szewczyk-Krolikowski et al., 2014). In particular, we systematically analysed the influence of two rfMRI analysis steps on the results: the individual cleaning (artefact removal) of fMRI data and the choice of the set of independent components (template) used for dual regression. Our experience suggests that the use of a cleaning approach based on single-subject independent component analysis, which removes non neural-related sources of inter-individual variability, can help to increase the reproducibility of clinical findings. A template generated using an independent set of healthy controls is recommended for studies where the aim is to detect differences from a “healthy” brain, rather than an “average” template, derived from an equal number of patients and controls. While, exploratory analyses (e.g. testing multiple resting state networks) should be used to formulate new hypotheses, careful validation is necessary before promising findings can be translated into useful biomarkers. [ABSTRACT FROM AUTHOR]

Background: The symptoms and pathogenesis of Parkinson's disease (PD) are complicated and an accurate diagnosis of PD is difficult, particularly in early-stage. Because functional magnetic resonance imaging (fMRI) is non-invasive and is characterized by the integration of different brain areas in terms of functional connectivity (FC), fMRI has been widely used in PD research. Non-motor symptom (NMS) features are also frequently present in PD before the onset of classical motor symptoms with pain as the primary NMS. Considering that PD could affect the pain process at multiple levels, we hypothesized that pain is one of the earliest symptoms in PD and investigated whether FC of the pain network was disrupted in PD without pain. To better understand the pathogenesis of pain in PD, we combined resting state and pain-stimuli-induced task state fMRI to identify alterations in FC related to pain in PD. Methods: Fourteen early drug-naïve PD without pain and 17 age- and sex-matched healthy controls (HC) participated in our testing task. We used independent component analysis to select seven functional networks related to PD and pain. We focused on abnormalities in FC and in functional network connectivity (FNC) in PD compared with HC during the task (51°C heat pain stimuli) and at rest. Results: Compared with HC, PD showed decreased FC in putamen within basal ganglia network (BGN) in task state and decreased FC in putamen of salience network (SN) and mid-cingulate cortex of sensorimotor network in rest state. FNC between the BGN and the SN are reduced during both states in PD compared with HC. In addition, right frontoparietal network (RFPN), which is considered as a bridge between the SN and default-mode network, was significantly disturbed during the task. Conclusion: These findings suggest that BGN plays a role in the pathological mechanisms of pain underlying PD, and RFPN likely contributes greatly to harmonization between intrinsic brain activity and external stimuli. [ABSTRACT FROM AUTHOR]

There is significant evidence that in addition to reward-punishment based decision making, the Basal Ganglia (BG) contributes to risk-based decision making (Balasubramani et al., 2014). Despite this evidence, little is known about the computational principles and neural correlates of risk computation in this subcortical system. We have previously proposed a reinforcement learning (RL)-based model of the BG that simulates the interactions between dopamine (DA) and serotonin (5HT) in a diverse set of experimental studies including reward, punishment and risk based decision making (Balasubramani et al., 2014). Starting with the classical idea that the activity of mesencephalic DA represents reward prediction error, the model posits that serotoninergic activity in the striatum controls risk-prediction error. Our prior model of the BG was an abstract model that did not incorporate anatomical and cellular-level data. In this work, we expand the earlier model into a detailed network model of the BG and demonstrate the joint contributions of DA-5HT in risk and reward-punishment sensitivity. At the core of the proposed network model is the following insight regarding cellular correlates of value and risk computation. Just as DA D1 receptor (D1R) expressing medium spiny neurons (MSNs) of the striatum were thought to be the neural substrates for value computation, we propose that DA D1R and D2R co-expressing MSNs are capable of computing risk. Though the existence of MSNs that co-express D1R and D2R are reported by various experimental studies, prior existing computational models did not include them. Ours is the first model that accounts for the computational possibilities of these co-expressing D1R-D2R MSNs, and describes how DA and 5HT mediate activity in these classes of neurons (D1R-, D2R-, D1R-D2R- MSNs). Starting from the assumption that 5HT modulates all MSNs, our study predicts significant modulatory effects of 5HT on D2R and co-expressing D1R-D2R MSNs which in turn explains the multifarious functions of 5HT in the BG. The experiments simulated in the present study relates 5HT to risk sensitivity and reward-punishment learning. Furthermore, our model is shown to capture reward-punishment and risk based decision making impairment in Parkinson's Disease (PD). The model predicts that optimizing 5HT levels along with DA medications might be essential for improving the patients' reward-punishment learning deficits. [ABSTRACT FROM AUTHOR]

Human and animal studies on brain functions in subjects with autism spectrum disorder have confirmed the aberrant organization of functional networks. However, little is known about the neural features underlying these impairments. Using community structure analyses (recruitment and integration), the current study explored the functional network features of individuals with autism spectrum disorder from one database (101 individuals with autism spectrum disorder and 120 healthy controls) and tested the replicability in an independent database (50 individuals with autism spectrum disorder and 74 healthy controls). Additionally, the study divided subjects into different age groups and tested the features in different subgroups. As for recruitment, subjects with autism spectrum disorder had lower coefficients in the default mode network and basal ganglia network than healthy controls. The integration results showed that subjects with autism spectrum disorder had a lower coefficient than healthy controls in the default mode network-medial frontal network and basal ganglia network-limbic networks. The results for the default mode network were mostly replicated in the independent database, but the results for the basal ganglia network were not. The results for different age groups were also analysed, and the replicability was tested in different databases. The lower recruitment in subjects with autism spectrum disorder suggests that they are less efficient at engaging these networks when performing relevant tasks. The lower integration results suggest impaired flexibility in cognitive functions in individuals with autism spectrum disorder. All these findings might explain why subjects with autism spectrum disorder show impaired brain networks and have important therapeutic implications for developing potentially effective interventions., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)

Parkinson's disease is characterized by both hypokinetic and hyperkinetic symptoms. While increased subthalamic burst discharges have a direct causal relationship with the hypokinetic manifestations (e.g., rigidity and bradykinesia), the origin of the hyperkinetic symptoms (e.g., resting tremor and propulsive gait) has remained obscure. Neuronal burst discharges are presumed to be autonomous or less responsive to synaptic input, thereby interrupting the information flow. We, however, demonstrate that subthalamic burst discharges are dependent on cortical glutamatergic synaptic input, which is enhanced by A-type K+ channel inhibition. Excessive top-down-triggered subthalamic burst discharges then drive highly correlative activities bottom-up in the motor cortices and skeletal muscles. This leads to hyperkinetic behaviors such as tremors, which are effectively ameliorated by inhibition of cortico-subthalamic AMPAergic synaptic transmission. We conclude that subthalamic burst discharges play an imperative role in cortico-subcortical information relay, and they critically contribute to the pathogenesis of both hypokinetic and hyperkinetic parkinsonian symptoms. [Display omitted] • A-type K+ channels prominently modulate cortico-subthalamic synaptic transmission • Cortico-subthalamic glutamatergic input triggers burst firing in the subthalamic nucleus • Exaggerated bursts induce coherent oscillations in the motor cortex and skeletal muscles • Erroneous re-entrant information relay leads to parkinsonian hyperkinetic behaviors The origin of parkinsonian tremors remains obscure. In opposition to the conventional view that neuronal burst activities are autonomous, Huang et al. show that subthalamic burst discharges are dependent on input from the motor cortex, causing erroneous re-entrant information relays from cortico-subthalamic to pallido-thalamocortical loops and thus parkinsonian tremors. [ABSTRACT FROM AUTHOR]

Disruption of brain circuits is one of the core mechanisms of Parkinson's disease (PD). Understanding structural connection alterations in PD is important for effective treatment. However, due to methodological limitations, most studies were unable to account for confounding factors such as crossing fibers and were unable to identify damages to specific fiber tracts. In the present study, we aimed to demonstrate tract-specific white matter structural changes in PD patients and their relationship with clinical symptoms. Ninety-eight PD patients, divided into early (ES) and middle stage (MS) groups, and 76 healthy controls (HCs) underwent brain magnetic resonance imaging scans and clinical assessments. Fixel-based analysis was used to investigate fiber tract alterations in PD patients. Compared to HCs, the PD patients showed decreased fiber density (FD) in the corpus callosum (CC), increased FD in the cortical spinal tract (CST), and increased fiber-bundle cross-section (FC, log-transformed: log-FC) in the superior cerebellar peduncle (SCP). Analysis of variance (ANOVA) revealed significant differences in FD in the CST and log-FC in the SCP among the three groups. Post-hoc analysis revealed that the mean FD values of the CST were higher in ES and MS patient groups compared to HCs, and the mean log-FC values of the SCP were higher in ES and MS patient groups compared to HCs. Additionally, the FD values of the CC in PD patients were negatively correlated with the Unified Parkinson's Disease Rating Scale part-III (UPDRS-III) scores (r = -0.257, p = 0.032), Hamilton Depression Rating Scale 17 Items (HAMD-17) scores (r = -0.230, p = 0.033), and Hamilton Anxiety Scale (HAMA) scores (r = -0.248, p = 0.032). Moreover, log-FC values of the SCP (r = 0.274, p = 0.028) and FD values of the CST (r = 0.384, p < 0.001) were positively correlated with the UPDRS-III scores. We concluded that PD patients had both decreased and increased white matter integrity within specific fiber bundles. Additionally, these white matter alterations were different across disease stages, suggesting the occurrence of complex pathological and compensatory changes during the development of PD., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Summary Objectives Spasmodic dysphonia (SD) is considered a focal dystonia. However, the detailed pathophysiology of SD remains unclear, despite the detection of abnormal activity in several brain regions. The aim of this study was to clarify the pathophysiological background of SD. Study Design This is a case-control study. Methods Both task-related brain activity measured by functional magnetic resonance imaging by reading the five-digit numbers and resting-state functional connectivity (FC) measured by 150 T2-weighted echo planar images acquired without any task were investigated in 12 patients with adductor SD and in 16 healthy controls. Results The patients with SD showed significantly higher task-related brain activation in the left middle temporal gyrus, left thalamus, bilateral primary motor area, bilateral premotor area, bilateral cerebellum, bilateral somatosensory area, right insula, and right putamen compared with the controls. Region of interest voxel FC analysis revealed many FC changes within the cerebellum-basal ganglia-thalamus-cortex loop in the patients with SD. Of the significant connectivity changes between the patients with SD and the controls, the FC between the left thalamus and the left caudate nucleus was significantly correlated with clinical parameters in SD. Conclusion The higher task-related brain activity in the insula and cerebellum was consistent with previous neuroimaging studies, suggesting that these areas are one of the unique characteristics of phonation-induced brain activity in SD. Based on FC analysis and their significant correlations with clinical parameters, the basal ganglia network plays an important role in the pathogenesis of SD. [ABSTRACT FROM AUTHOR]

Unlabelled: The basal ganglia involve in a range of functions that are disturbed in schizophrenia patients. This study decomposed the resting-state data of 28 schizophrenia patients and 31 healthy controls with spatial independent component analysis and identified increased functional integration in the bilateral caudate nucleus in schizophrenia patients. Further, the caudate nucleus in patients showed altered functional connection with the prefrontal area and cerebellum. These results identified the importance of basal ganglia in schizophrenia patients., Clinical Trial Registration: Chinese Clinical Trial Registry. Registration number ChiCTR-RCS-14004878.

Background: The symptoms and pathogenesis of Parkinson's disease (PD) are complicated and an accurate diagnosis of PD is difficult, particularly in early-stage. Because functional magnetic resonance imaging (fMRI) is non-invasive and is characterized by the integration of different brain areas in terms of functional connectivity (FC), fMRI has been widely used in PD research. Non-motor symptom (NMS) features are also frequently present in PD before the onset of classical motor symptoms with pain as the primary NMS. Considering that PD could affect the pain process at multiple levels, we hypothesized that pain is one of the earliest symptoms in PD and investigated whether FC of the pain network was disrupted in PD without pain. To better understand the pathogenesis of pain in PD, we combined resting state and pain-stimuli-induced task state fMRI to identify alterations in FC related to pain in PD., Methods: Fourteen early drug-naïve PD without pain and 17 age- and sex-matched healthy controls (HC) participated in our testing task. We used independent component analysis to select seven functional networks related to PD and pain. We focused on abnormalities in FC and in functional network connectivity (FNC) in PD compared with HC during the task (51°C heat pain stimuli) and at rest., Results: Compared with HC, PD showed decreased FC in putamen within basal ganglia network (BGN) in task state and decreased FC in putamen of salience network (SN) and mid-cingulate cortex of sensorimotor network in rest state. FNC between the BGN and the SN are reduced during both states in PD compared with HC. In addition, right frontoparietal network (RFPN), which is considered as a bridge between the SN and default-mode network, was significantly disturbed during the task., Conclusion: These findings suggest that BGN plays a role in the pathological mechanisms of pain underlying PD, and RFPN likely contributes greatly to harmonization between intrinsic brain activity and external stimuli.