Altered resting state brain networks in Parkinson's disease

BASCO: a toolbox for task-related functional connectivity

BASCO (BetA Series COrrelation) is a user-friendly MATLAB toolbox with a graphical user interface (GUI) which allows investigating functional connectivity in event-related functional magnetic resonance imaging (fMRI) data. Connectivity analyses extend and compliment univariate activation analyses since the actual interaction between brain regions involved in a task can be explored. BASCO supports seed-based functional connectivity as well as brain network analyses. Although there are a multitude of advanced toolboxes for investigating resting-state functional connectivity, BASCO is the first toolbox for evaluating task-related whole-brain functional connectivity employing a large number of network nodes. Thus, BASCO allows investigating task-specific rather than resting-state networks. Here, we summarize the main features of the toolbox and describe the methods and algorithms.

Aberrant Brain Network Efficiency in Parkinson's Disease Patients with Tremor: A Multi-Modality Study

The coordination of spontaneous brain activity is widely enhanced relative to compensation activity in Parkinson’s disease (PD) with tremor; however, the associated topological organization remains unclear. This study collected magnetic resonance imaging data from 36 participants [i.e., 16 PD patients and 20 matched normal controls (NCs)] and constructed wavelet-based functional and morphological brain networks for individual participants. Graph-based network analysis indicated that the information translation efficiency in the functional brain network was disrupted within the wavelet scale 2 (i.e., 0.063–0.125 Hz) in PD patients. Compared with the NCs, the network local efficiency was decreased and the network global efficiency was increased in PD patients. Network local efficiency could effectively discriminate PD patients from the NCs using multivariate pattern analysis, and could also describe the variability of tremor based on a multiple linear regression model (MLRM). However, these observations were not identified in the network global efficiency. Notably, the global and local efficiency were both significantly increased in the morphological brain network of PD patients. We further found that the global and local network efficiency both worked well on PD classifications (i.e., using MVPA) and clinical performance descriptions (i.e., using MLRM). More importantly, functional and morphological brain networks were highly associated in terms of network local efficiency in PD patients. This study sheds lights on network disorganization in PD with tremor and helps for understanding the neural basis underlying this type of PD.

Resting-state functional brain networks in Parkinson's disease

The network approach is increasingly being applied to the investigation of normal brain function and its impairment. In the present review, we introduce the main methodological approaches employed for the analysis of resting‐state neuroimaging data in Parkinson's disease studies. We then summarize the results of recent studies that used a functional network perspective to evaluate the changes underlying different manifestations of Parkinson's disease, with an emphasis on its cognitive symptoms. Despite the variability reported by many studies, these methods show promise as tools for shedding light on the pathophysiological substrates of different aspects of Parkinson's disease, as well as for differential diagnosis, treatment monitoring and establishment of imaging biomarkers for more severe clinical outcomes.

Increased connectivity between sensorimotor and attentional areas in Parkinson's disease

INTRODUCTION

Our study is using Independent Component Analysis (ICA) to evaluate functional connectivity changes in Parkinson's disease (PD) in an unbiased manner.

METHODS

Resting-state functional magnetic resonance imaging (rs-fMRI) data was collected for 27 PD patients and 16 healthy subjects. Differences for intra- and inter-network connectivity between healthy subjects and patients were investigated using FMRIB Software Library (FSL) tools (Melodic ICA, dual regression, FSLNets).

RESULTS

Twenty-three ICA maps were identified as components of neuronal origin. For intra-network connectivity changes, eight components showed a significant connectivity increase in patients (p < 0.05); these were correlated with clinical scores and were largest for (sensori)motor networks. For inter-network connectivity changes, we found higher connectivity between the sensorimotor network and the spatial attention network (p = 0.0098) and lower connectivity between anterior and posterior default mode networks (DMN) (p =  0.024), anterior DMN and visual recognition networks (p = 0.026), as well as between visual attention and main dorsal attention networks (p = 0.03), for patients as compared to healthy subjects. The area under the Receiver Operating Characteristics (ROC) curve for the best predictor (partial correlation between sensorimotor and spatial attention networks) was 0.772. These functional alterations were not associated with any gray or white matter structural changes.

CONCLUSION

Our results show higher connectivity between sensorimotor and spatial attention areas in patients that may be related to the reduced movement automaticity in PD.

Hemispheric asymmetry of electroencephalography-based functional brain networks

Electroencephalography (EEG)-based functional brain networks have been investigated frequently in health and disease. It has been shown that a number of graph theory metrics are disrupted in brain disorders. EEG-based brain networks are often studied in the whole-brain framework, where all the nodes are grouped into a single network. In this study, we studied the brain networks in two hemispheres and assessed whether there are any hemispheric-specific patterns in the properties of the networks. To this end, resting state closed-eyes EEGs from 44 healthy individuals were processed and the network structures were extracted separately for each hemisphere. We examined neurophysiologically meaningful graph theory metrics: global and local efficiency measures. The global efficiency did not show any hemispheric asymmetry, whereas the local connectivity showed rightward asymmetry for a range of intermediate density values for the constructed networks. Furthermore, the age of the participants showed significant direct correlations with the global efficiency of the left hemisphere, but only in the right hemisphere, with local connectivity. These results suggest that only local connectivity of EEG-based functional networks is associated with brain hemispheres.

Putamen-midbrain functional connectivity is related to striatal dopamine transporter availability in patients with Lewy body diseases

Prior work has shown that functional connectivity between the midbrain and putamen is altered in patients with impairments in the dopamine system. This study examines whether individual differences in midbrain-striatal connectivity are proportional to the integrity of the dopamine system in patients with nigrostriatal dopamine loss (Parkinson's disease and dementia with Lewy bodies). We assessed functional connectivity of the putamen during resting state fMRI and dopamine transporter (DAT) availability in the striatum using 11C-Altropane PET in twenty patients. In line with the hypothesis that functional connectivity between the midbrain and the putamen reflects the integrity of the dopaminergic neurotransmitter system, putamen-midbrain functional connectivity was significantly correlated with striatal DAT availability even after stringent control for effects of head motion. DAT availability did not relate to functional connectivity between the caudate and thalamus/prefrontal areas. As such, resting state functional connectivity in the midbrain-striatal pathway may provide a useful indicator of underlying pathology in patients with nigrostriatal dopamine loss.

Experimentally induced thyrotoxicosis leads to increased connectivity in temporal lobe structures: a resting state fMRI study

Adult onset hyperthyroidism may impact on different cognitive domains, including attention and concentration, memory, perceptual function, language and executive function. Previous PET studies implicated changed functionality of limbic regions, the temporal and frontal lobes in hyperthyroidism, whereas it is unknown whether cognitive effects of hyperthyroidism may be due to changed brain connectivity. This study aimed to investigate the effect of experimentally induced short-term hyperthyroidism thyrotoxicosis on resting-state functional connectivity using functional magnetic resonance imaging. Twenty-nine healthy male right-handed subjects were examined twice, once prior and once after 8 weeks of oral administration of 250 μg levothyroxine per day. Resting-state fMRI was subjected to graph-theory based analysis methods to investigate whole-brain intrinsic functional connectivity. Despite a lack of subjective changes noticed by the subjects significant thyrotoxicosis was confirmed in all subjects. This induced a significant increase in resting-state functional connectivity specifically in the rostral temporal lobes (0.05 FDR corrected at the cluster level), which is caused by an increased connectivity to the cognitive control network. The increased connectivity between temporal poles and the cognitive control network shown here under experimental conditions supports an important function of thyroid hormones in the regulation of paralimbic structures.

Aberrant cerebral network topology and mild cognitive impairment in early Parkinson's disease

The aim of this study was to assess whether mild cognitive impairment (MCI) is associated with disruption in large-scale structural networks in newly diagnosed, drug-naïve patients with Parkinson's disease (PD). Graph theoretical analyses were applied to 3T MRI data from 123 PD patients and 56 controls from the Parkinson's progression markers initiative (PPMI). Thirty-three patients were classified as having Parkinson's disease with mild cognitive impairment (PD-MCI) using the Movement Disorders Society Task Force criteria, while the remaining 90 PD patients were classified as cognitively normal (PD-CN). Global measures (clustering coefficient, characteristic path length, global efficiency, small-worldness) and regional measures (regional clustering coefficient, regional efficiency, hubs) were assessed in the structural networks that were constructed based on cortical thickness and subcortical volume data. PD-MCI patients showed a marked reduction in the average correlation strength between cortical and subcortical regions compared with controls. These patients had a larger characteristic path length and reduced global efficiency in addition to a lower regional efficiency in frontal and parietal regions compared with PD-CN patients and controls. A reorganization of the highly connected regions in the network was observed in both groups of patients. This study shows that the earliest stages of cognitive decline in PD are associated with a disruption in the large-scale coordination of the brain network and with a decrease of the efficiency of parallel information processing. These changes are likely to signal further cognitive decline and provide support to the role of aberrant network topology in cognitive impairment in patients with early PD.

Discriminative analysis of Parkinson's disease based on whole-brain functional connectivity

Recently, there has been an increasing emphasis on applications of pattern recognition and neuroimaging techniques in the effective and accurate diagnosis of psychiatric or neurological disorders. In the present study, we investigated the whole-brain resting-state functional connectivity patterns of Parkinson's disease (PD), which are expected to provide additional information for the clinical diagnosis and treatment of this disease. First, we computed the functional connectivity between each pair of 116 regions of interest derived from a prior atlas. The most discriminative features based on Kendall tau correlation coefficient were then selected. A support vector machine classifier was employed to classify 21 PD patients with 26 demographically matched healthy controls. This method achieved a classification accuracy of 93.62% using leave-one-out cross-validation, with a sensitivity of 90.47% and a specificity of 96.15%. The majority of the most discriminative functional connections were located within or across the default mode, cingulo-opercular and frontal-parietal networks and the cerebellum. These disease-related resting-state network alterations might play important roles in the pathophysiology of this disease. Our results suggest that analyses of whole-brain resting-state functional connectivity patterns have the potential to improve the clinical diagnosis and treatment evaluation of PD.

Dopaminergic basis for impairments in functional connectivity across subdivisions of the striatum in Parkinson's disease

The pathological hallmark of Parkinson's disease is the degeneration of dopaminergic nigrostriatal neurons, leading to depletion of striatal dopamine. Recent neuroanatomical work has identified pathways for communication across striatal subdivisions, suggesting that the striatum provides a platform for integration of information across parallel corticostriatal circuits. The aim of this study was to investigate whether dopaminergic dysfunction in Parkinson's disease was associated with impairments in functional connectivity across striatal subdivisions, which could potentially reflect reduced integration across corticostriatal circuits. Utilizing resting-state functional magnetic resonance imaging (fMRI), we analyzed functional connectivity in 39 patients with Parkinson's disease, both "on" and "off" their regular dopaminergic medications, along with 40 age-matched healthy controls. Our results demonstrate widespread impairments in connectivity across subdivisions of the striatum in patients with Parkinson's disease in the "off" state. The administration of dopaminergic medication significantly improved connectivity across striatal subdivisions in Parkinson's disease, implicating dopaminergic deficits in the pathogenesis of impaired striatal interconnectivity. In addition, impaired striatal interconnectivity in the Parkinson's disease "off" state was associated with pathological decoupling of the striatum from the thalamic and sensorimotor (SM) networks. Specifically, we found that although the strength of striatal interconnectivity was positively correlated with both (i) the strength of internal thalamic connectivity, and (ii) the strength of internal SM connectivity, in both healthy controls and the Parkinson's disease "on" state, these relationships were absent in Parkinson's disease when in the "off" state. Taken together our findings emphasize the central role of dopamine in integrated striatal function and the pathological consequences of striatal dopamine denervation in Parkinson's disease.

Disconnection of network hubs and cognitive impairment after traumatic brain injury

Traumatic brain injury (TBI) affects brain connectivity, which disrupts the large-scale networks that support cognitive function. Fagerholm et al. use graph analysis, with brain regions as nodes and white matter tracts as connections, to show that TBI particularly disrupts the connectivity of hubs, and that this disconnection predicts cognitive impairment.

Traumatic brain injury affects brain connectivity by producing traumatic axonal injury. This disrupts the function of large-scale networks that support cognition. The best way to describe this relationship is unclear, but one elegant approach is to view networks as graphs. Brain regions become nodes in the graph, and white matter tracts the connections. The overall effect of an injury can then be estimated by calculating graph metrics of network structure and function. Here we test which graph metrics best predict the presence of traumatic axonal injury, as well as which are most highly associated with cognitive impairment. A comprehensive range of graph metrics was calculated from structural connectivity measures for 52 patients with traumatic brain injury, 21 of whom had microbleed evidence of traumatic axonal injury, and 25 age-matched controls. White matter connections between 165 grey matter brain regions were defined using tractography, and structural connectivity matrices calculated from skeletonized diffusion tensor imaging data. This technique estimates injury at the centre of tract, but is insensitive to damage at tract edges. Graph metrics were calculated from the resulting connectivity matrices and machine-learning techniques used to select the metrics that best predicted the presence of traumatic brain injury. In addition, we used regularization and variable selection via the elastic net to predict patient behaviour on tests of information processing speed, executive function and associative memory. Support vector machines trained with graph metrics of white matter connectivity matrices from the microbleed group were able to identify patients with a history of traumatic brain injury with 93.4% accuracy, a result robust to different ways of sampling the data. Graph metrics were significantly associated with cognitive performance: information processing speed (R² = 0.64), executive function (R² = 0.56) and associative memory (R² = 0.25). These results were then replicated in a separate group of patients without microbleeds. The most influential graph metrics were betweenness centrality and eigenvector centrality, which provide measures of the extent to which a given brain region connects other regions in the network. Reductions in betweenness centrality and eigenvector centrality were particularly evident within hub regions including the cingulate cortex and caudate. Our results demonstrate that betweenness centrality and eigenvector centrality are reduced within network hubs, due to the impact of traumatic axonal injury on network connections. The dominance of betweenness centrality and eigenvector centrality suggests that cognitive impairment after traumatic brain injury results from the disconnection of network hubs by traumatic axonal injury.

Widespread increase of functional connectivity in Parkinson's disease with tremor: a resting-state FMRI study

Parkinson’s disease (PD) is a clinically heterogeneous disease in the symptomatology dominated by tremor, akinesia, or rigidity. Focusing on PD patients with tremor, this study investigated their discoordination patterns of spontaneous brain activity by combining voxel-wise centrality, seed-based functional connectivity, and network efficiency methods. Sixteen patients and 20 matched healthy controls (HCs) were recruited and underwent structural and resting-state functional MRI scan. Compared with the HCs, the patients exhibited increased centrality in the frontal, parietal, and occipital regions while decreased centrality in the cerebellum anterior lobe and thalamus. Seeded at these regions, a distributed network was further identified that encompassed cortical (default mode network, sensorimotor cortex, prefrontal and occipital areas) and subcortical (thalamus and basal ganglia) regions and the cerebellum and brainstem. Graph-based analyses of this network revealed increased information transformation efficiency in the patients. Moreover, the identified network correlated with clinical manifestations in the patients and could distinguish the patients from HCs. Morphometric analyses revealed decreased gray matter volume in multiple regions that largely accounted for the observed functional abnormalities. Together, these findings provide a comprehensive view of network disorganization in PD with tremor and have important implications for understanding neural substrates underlying this specific type of PD.

Reduced Risk of Parkinson's Disease in Users of Calcium Channel Blockers: A Meta-Analysis

Aim. To pool the data currently available to determine the association between calcium channel blockers (CCBs) and risk of Parkinson's disease (PD). Methods. Literature search in PubMed, EBSCO, and Cochrane library was undertaken through March 2014, looking for observational studies evaluating the association between CCBs use and PD. Pooled relative risk (RR) estimates and 95% confidence intervals (CIs) were calculated using random-effects model. Subgroup analyses, sensitivity Analysis, and cumulative meta-analysis were also performed. Results. Six studies were included in our meta-analysis according to the selection criteria, including three cohort studies and three case-control studies involving 27,67,990 subjects including 11,941 PD cases. We found CCBs use was associated with significant decreased risk of PD, compared with not using CCBs (random effects model pooled RR, 0.81 (95% CI, 0.69–0.95)); a significant heterogeneity was found between studies (P = 0.031; I² 54.6%). Both the classes of CCB, that is, dihydropyridine calcium channel blockers (DiCCB) (0.80 (95% CI, 0.65–0.98) P = 0.032) and non-DiCCB (0.70 (95% CI, 0.53–0.92) P = 0.013), were found to be reducing the risk of PD. Conclusion. In our analysis, we found that CCBs use was associated with a Significantly decreased risk of PD compared with non-CCB use.

Reproducibility of graph-theoretic brain network metrics: a systematic review

This systematic review aimed to assess the reproducibility of graph-theoretic brain network metrics. Primary research studies of test-retest reliability conducted on healthy human subjects were included that quantified test-retest reliability using either the intraclass correlation coefficient (ICC) or the coefficient of variance. The MEDLINE, Web of Knowledge, Google Scholar, and OpenGrey databases were searched up to February 2014. Risk of bias was assessed with 10 criteria weighted toward methodological quality. Twenty-three studies were included in the review (n=499 subjects) and evaluated for various characteristics, including sample size (5-45), retest interval (<1 h to >1 year), acquisition method, and test-retest reliability scores. For at least one metric, ICCs reached the fair range (ICC 0.40-0.59) in one study, the good range (ICC 0.60-0.74) in five studies, and the excellent range (ICC>0.74) in 16 studies. Heterogeneity of methods prevented further quantitative analysis. Reproducibility was good overall. For the metrics having three or more ICCs reported for both functional and structural networks, six of seven were higher in structural networks, indicating that structural networks may be more reliable over time. The authors were also able to highlight and discuss a number of methodological factors affecting reproducibility.

Distinguishing patients with Parkinson's disease subtypes from normal controls based on functional network regional efficiencies

Many studies have demonstrated that the pathophysiology and clinical symptoms of Parkinson's disease (PD) are inhomogeneous. However, the symptom-specific intrinsic neural activities underlying the PD subtypes are still not well understood. Here, 15 tremor-dominant PD patients, 10 non-tremor-dominant PD patients, and 20 matched normal controls (NCs) were recruited and underwent resting-state functional magnetic resonance imaging (fMRI). Functional brain networks were constructed based on randomly generated anatomical templates with and without the cerebellum. The regional network efficiencies (i.e., the local and global efficiencies) were further measured and used to distinguish subgroups of PD patients (i.e., with tremor-dominant PD and non-tremor-dominant PD) from the NCs using linear discriminant analysis. The results demonstrate that the subtype-specific functional networks were small-world-organized and that the network regional efficiency could discriminate among the individual PD subgroups and the NCs. Brain regions involved in distinguishing between the study groups included the basal ganglia (i.e., the caudate and putamen), limbic regions (i.e., the hippocampus and thalamus), the cerebellum, and other cerebral regions (e.g., the insula, cingulum, and calcarine sulcus). In particular, the performances of the regional local efficiency in the functional network were better than those of the global efficiency, and the performances of global efficiency were dependent on the inclusion of the cerebellum in the analysis. These findings provide new evidence for the neurological basis of differences between PD subtypes and suggest that the cerebellum may play different roles in the pathologies of different PD subtypes. The present study demonstrated the power of the combination of graph-based network analysis and discrimination analysis in elucidating the neural basis of different PD subtypes.

Abnormal functional connectivity density in Parkinson's disease

The pathology of Parkinson's disease (PD) is not confined to the nigrostriatal pathway, but also involves widespread cerebral cortical areas. Using seed-based resting state functional connectivity, many previous studies have demonstrated that PD patients have abnormal functional integration. However, this technique strongly relies on a priori selection of the seed regions and may miss important unpredictable findings. Using an ultrafast voxel-wise functional connectivity density approach, this study performed a whole brain functional connectivity analysis to investigate the abnormal resting-state functional activities in PD patients. Compared with healthy controls, PD patients exhibited decreased short-range functional connectivity densities in regions that were mainly located in the ventral visual pathway and decreased long-range functional connectivity densities in the right middle and superior frontal gyrus, which have been speculated to be associated with visual hallucinations and cognitive dysfunction, respectively. PD patients also exhibited increased short- and long-range functional connectivity densities in the bilateral precuneus and posterior cingulate cortex, which may represent a compensatory process for maintaining normal brain function. The observed functional connectivity density alterations might be related to the disturbed structural connectivity of PD patients, leading to abnormal functional integration. Our results suggest that functional connectivity density mapping may provide a useful means to assess PD-related neurodegeneration and to study the pathophysiology of PD.

A global view of network of lncRNAs and their binding proteins

Recently, the long non-coding RNAs (lncRNAs) have obtained wide attention because they have broad and crucial functions in regulating complex biological processes. Many lncRNAs functioned by interfacing with corresponding RNA binding proteins and the complexity of lncRNAs' function was attributed to multiple lncRNA-protein interactions. To gain insights into the global relationship between lncRNAs and their binding proteins, here we constructed a lncRNA-protein network (LPN) based on experimentally determined functional interactions between them. This network included 177 lncRNAs, 92 proteins and 683 relationships between them. Cluster analysis of LPN revealed that some proteins (such as AGO and IGFBP families) and lncRNA (such as XIST and MALAT1) were densely connected, suggesting the potential co-regulated mechanism and functional cross-talk of different lncRNAs. We then characterized the lncRNA functions and found that lncRNA binding proteins (LBPs) enriched in many cancer or cancer-related pathways. Finally, we investigated the different topological properties of LBPs in PPIs network. Compared with disease proteins and average ones, LBPs tend to have significantly higher degree, betweenness, and closeness but a relatively lower clustering coefficient, indicating their centrality and essentiality in the context of a biological network.

Decreased limbic and increased fronto-parietal connectivity in unmedicated patients with obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) is characterized by recurrent intrusive thoughts and ritualized, repetitive behaviors, or mental acts. Convergent experimental evidence from neuroimaging and neuropsychological studies supports an orbitofronto-striato-thalamo-cortical dysfunction in OCD. Moreover, an over excitability of the amygdala and over monitoring of thoughts and actions involving the anterior cingulate, frontal and parietal cortex has been proposed as aspects of pathophysiology in OCD. We chose a data driven, graph theoretical approach to investigate brain network organization in 17 unmedicated OCD patients and 19 controls using resting-state fMRI. OCD patients showed a decreased connectivity of the limbic network to several other brain networks: the basal ganglia network, the default mode network, and the executive/attention network. The connectivity within the limbic network was also found to be decreased in OCD patients compared to healthy controls. Furthermore, we found a stronger connectivity of brain regions within the executive/attention network in OCD patients. This effect was positively correlated with disease severity. The decreased connectivity of limbic regions (amygdala, hippocampus) may be related to several neurocognitive deficits observed in OCD patients involving implicit learning, emotion processing and expectation, and processing of reward and punishment. Limbic disconnection from fronto-parietal regions relevant for (re)-appraisal may explain why intrusive thoughts become and/or remain threatening to patients but not to healthy subjects. Hyperconnectivity within the executive/attention network might be related to OCD symptoms such as excessive monitoring of thoughts and behavior as a dysfunctional strategy to cope with threat and uncertainty.

Age-related reorganizational changes in modularity and functional connectivity of human brain networks

The human brain undergoes both morphological and functional modifications across the human lifespan. It is important to understand the aspects of brain reorganization that are critical in normal aging. To address this question, one approach is to investigate age-related topological changes of the brain. In this study, we developed a brain network model using graph theory methods applied to the resting-state functional magnetic resonance imaging data acquired from two groups of normal healthy adults classified by age. We found that brain functional networks demonstrated modular organization in both groups with modularity decreased with aging, suggesting less distinct functional divisions across whole brain networks. Local efficiency was also decreased with aging but not with global efficiency. Besides these brain-wide observations, we also observed consistent alterations of network properties at the regional level in the elderly, particularly in two major functional networks-the default mode network (DMN) and the sensorimotor network. Specifically, we found that measures of regional strength, local and global efficiency of functional connectivity were increased in the sensorimotor network while decreased in the DMN with aging. These results indicate that global reorganization of brain functional networks may reflect overall topological changes with aging and that aging likely alters individual brain networks differently depending on the functional properties. Moreover, these findings highly correspond to the observation of decline in cognitive functions but maintenance of primary information processing in normal healthy aging, implying an underlying compensation mechanism evolving with aging to support higher-level cognitive functioning.

Reduced topological efficiency in cortical-basal Ganglia motor network of Parkinson's disease: a resting state fMRI study

Parkinson's disease (PD) is mainly characterized by dopamine depletion of the cortico-basal ganglia (CBG) motor circuit. Given that dopamine dysfunction could affect functional brain network efficiency, the present study utilized resting-state fMRI (rs-fMRI) and graph theoretical approach to investigate the topological efficiency changes of the CBG motor network in patients with PD during a relatively hypodopaminergic state (12 hours after a last dose of dopamimetic treatment). We found that PD compared with controls had remarkable decreased efficiency in the CBG motor network, with the most pronounced changes observed in rostral supplementary motor area (pre-SMA), caudal SMA (SMA-proper), primary motor cortex (M1), primary somatosensory cortex (S1), thalamus (THA), globus pallidus (GP), and putamen (PUT). Furthermore, reduced efficiency in pre-SMA, M1, THA and GP was significantly correlated with Unified Parkinson's Disease Rating Scale (UPDRS) motor scores in PD patients. Together, our results demonstrate that individuals with PD appear to be less effective at information transfer within the CBG motor pathway, which provides a novel perspective on neurobiological explanation for the motor symptoms in patients. These findings are in line with the pathophysiology of PD, suggesting that network efficiency metrics may be used to identify and track the pathology of PD.

Exercise alters resting-state functional connectivity of motor circuits in parkinsonian rats

Few studies have examined changes in functional connectivity after long-term aerobic exercise. We examined the effects of 4 weeks of forced running wheel exercise on the resting-state functional connectivity (rsFC) of motor circuits of rats subjected to bilateral 6-hydroxydopamine lesion of the dorsal striatum. Our results showed substantial similarity between lesion-induced changes in rsFC in the rats and alterations in rsFC reported in Parkinson's disease subjects, including disconnection of the dorsolateral striatum. Exercise in lesioned rats resulted in: (1) normalization of many of the lesion-induced alterations in rsFC, including reintegration of the dorsolateral striatum into the motor network; (2) emergence of the ventrolateral striatum as a new broadly connected network hub; and (3) increased rsFC among the motor cortex, motor thalamus, basal ganglia, and cerebellum. Our results showed for the first time that long-term exercise training partially reversed lesion-induced alterations in rsFC of the motor circuits, and in addition enhanced functional connectivity in specific motor pathways in the parkinsonian rats, which could underlie recovery in motor functions observed in these animals.

Intrinsic brain networks normalize with treatment in pediatric complex regional pain syndrome

Pediatric complex regional pain syndrome (P-CRPS) offers a unique model of chronic neuropathic pain as it either resolves spontaneously or through therapeutic interventions in most patients. Here we evaluated brain changes in well-characterized children and adolescents with P-CRPS by measuring resting state networks before and following a brief (median = 3 weeks) but intensive physical and psychological treatment program, and compared them to matched healthy controls. Differences in intrinsic brain networks were observed in P-CRPS compared to controls before treatment (disease state) with the most prominent differences in the fronto-parietal, salience, default mode, central executive, and sensorimotor networks. Following treatment, behavioral measures demonstrated a reduction of symptoms and improvement of physical state (pain levels and motor functioning). Correlation of network connectivities with spontaneous pain measures pre- and post-treatment indicated concomitant reductions in connectivity in salience, central executive, default mode and sensorimotor networks (treatment effects). These results suggest a rapid alteration in global brain networks with treatment and provide a venue to assess brain changes in CRPS pre- and post-treatment, and to evaluate therapeutic effects.

Function of basal ganglia in bridging cognitive and motor modules to perform an action

The basal ganglia (BG) are thought to be involved in the integration of multiple sources of information, and their dysfunction can lead to disorders such as Parkinson's disease (PD). PD patients show motor and cognitive dysfunction with specific impairments in the internal generation of motor actions and executive deficits, respectively. The role of the BG, then, would be to integrate information from several sources in order to make a decision on a resulting action adequate for the required task. Reanalyzing the data set from our previous study (Martinu et al., 2012), we investigated this hypothesis by applying a graph theory method to a series of fMRI data during the performance of self-initiated (SI) finger movement tasks obtained in healthy volunteers (HV) and early stage PD patients. Dorsally, connectivity strength between the medial prefrontal areas (mPFC) and cortical regions including the primary motor area (M1), the extrastriate visual cortex, and the associative cortex, was reduced in the PD patients. The connectivity strengths were positively correlated to activity in the striatum in both groups. Ventrally, all connectivity between the striatum, the thalamus, and the extrastriate visual cortex decreased in strength in the PD, as did the connectivity between the striatum and the ventrolateral PFC (VLPFC). Individual response time (RT) was negatively correlated to connectivity strength between the dorsolateral PFC (DLPFC) and the striatum and positively correlated to connectivity between the VLPFC and the striatum in the HV. These results indicate that the BG, with the mPFC and thalamus, are involved in integrating multiple sources of information from areas such as DLPFC, and VLPFC, connecting to M1, thereby determining a network that leads to the adequate decision and performance of the resulting action.

Parkinson's disease and risk of fracture: a meta-analysis of prospective cohort studies

Backgrounds/Objective

Parkinson’s disease (PD) is the second most common neurodegenerative disease among the elderly population. However, epidemiological evidence on the relationship of PD with risk of fracture has not been systematically assessed. Therefore, we performed this meta-analysis of prospective studies to explore the association between PD and risk of fracture.

Methods

PubMed, Embase, Web of Science and Cochrane Library up to February 26, 2014 were searched to identify eligible studies. Random-effects model was used to pool the results.

Results

Six studies that totally involved 69,387 participants were included for analysis. Overall, PD patients had an increased risk of fracture compared with control subjects (pooled hazard ratio = 2.66, 95% confidence interval: 2.10–3.36). No publication bias was observed across studies and the subgroup as well as sensitivity analysis suggested that the general results were robust.

Conclusion

The present study suggested that PD is associated with an increased risk of fracture. However, given the limited number and moderate quality of included studies, well-designed prospective cohort studies are required to confirm the findings from this meta-analysis.

Large-scale resting state network correlates of cognitive impairment in Parkinson's disease and related dopaminergic deficits

Cognitive impairment is a common non-motor feature of Parkinson's disease (PD). Understanding the neural mechanisms of this deficit is crucial for the development of efficient methods for treatment monitoring and augmentation of cognitive functions in PD patients. The current study aimed to investigate resting state fMRI correlates of cognitive impairment in PD from a large-scale network perspective, and to assess the impact of dopamine deficiency on these networks. Thirty PD patients with resting state fMRI were included from the Parkinson's Progression Marker Initiative (PPMI) database. Eighteen patients from this sample were also scanned with (123)I-FP-CIT SPECT. A standardized neuropsychological battery was administered, evaluating verbal memory, visuospatial, and executive cognitive domains. Image preprocessing was performed using an SPM8-based workflow, obtaining time-series from 90 regions-of-interest (ROIs) defined from the AAL brain atlas. The Brain Connectivity Toolbox (BCT) was used to extract nodal strength from all ROIs, and modularity of the cognitive circuitry determined using the meta-analytical software Neurosynth. Brain-behavior covariance patterns between cognitive functions and nodal strength were estimated using Partial Least Squares. Extracted latent variable (LV) scores were matched with the performances in the three cognitive domains (memory, visuospatial, and executive) and striatal dopamine transporter binding ratios (SBR) using linear modeling. Finally, influence of nigrostriatal dopaminergic deficiency on the modularity of the "cognitive network" was analyzed. For the range of deficits studied, better executive performance was associated with increased dorsal fronto-parietal cortical processing and inhibited subcortical and primary sensory involvement. This profile was also characterized by a relative preservation of nigrostriatal dopaminergic function. The profile associated with better memory performance correlated with increased prefronto-limbic processing, and was not associated with presynaptic striatal dopamine uptake. SBR ratios were negatively correlated with modularity of the "cognitive network," suggesting integrative effects of the preserved nigrostriatal dopamine system on this circuitry.

Altered resting-state functional connectivity in patients with chronic bilateral vestibular failure

Patients with bilateral vestibular failure (BVF) suffer from gait unsteadiness, oscillopsia and impaired spatial orientation. Brain imaging studies applying caloric irrigation to patients with BVF have shown altered neural activity of cortical visual-vestibular interaction: decreased bilateral neural activity in the posterior insula and parietal operculum and decreased deactivations in the visual cortex. It is unknown how this affects functional connectivity in the resting brain and how changes in connectivity are related to vestibular impairment. We applied a novel data driven approach based on graph theory to investigate altered whole-brain resting-state functional connectivity in BVF patients (n= 22) compared to age- and gender-matched healthy controls (n= 25) using resting-state fMRI. Changes in functional connectivity were related to subjective (vestibular scores) and objective functional parameters of vestibular impairment, specifically, the adaptive changes during active (self-guided) and passive (investigator driven) head impulse test (HIT) which reflects the integrity of the vestibulo-ocular reflex (VOR). BVF patients showed lower bilateral connectivity in the posterior insula and parietal operculum but higher connectivity in the posterior cerebellum compared to controls. Seed-based analysis revealed stronger connectivity from the right posterior insula to the precuneus, anterior insula, anterior cingulate cortex and the middle frontal gyrus. Excitingly, functional connectivity in the supramarginal gyrus (SMG) of the inferior parietal lobe and posterior cerebellum correlated with the increase of VOR gain during active as compared to passive HIT, i.e., the larger the adaptive VOR changes the larger was the increase in regional functional connectivity. Using whole brain resting-state connectivity analysis in BVF patients we show that enduring bilateral deficient or missing vestibular input leads to changes in resting-state connectivity of the brain. These changes in the resting brain are robust and task-independent as they were found in the absence of sensory stimulation and without a region-related a priori hypothesis. Therefore they may indicate a fundamental disease-related change in the resting brain. They may account for the patients' persistent deficits in visuo-spatial attention, spatial orientation and unsteadiness. The relation of increasing connectivity in the inferior parietal lobe, specifically SMG, to improvement of VOR during active head movements reflects cortical plasticity in BVF and may play a clinical role in vestibular rehabilitation.