Reduced specificity of functional connectivity in the aging brain during task performance

The importance of studying connectivity in the aging brain is increasingly recognized. Recent studies have shown that connectivity within the default mode network is reduced with age and have demonstrated a clear relation of these changes with cognitive functioning. However, research on age‐related changes in other functional networks is sparse and mainly focused on prespecified functional networks. Using functional magnetic resonance imaging, we investigated age‐related changes in functional connectivity during a visual oddball task in a range of functional networks. It was found that compared with young participants, elderly showed a decrease in connectivity between areas belonging to the same functional network. This was found in the default mode network and the somatomotor network. Moreover, in all identified networks, elderly showed increased connectivity between areas within these networks and areas belonging to different functional networks. Decreased connectivity within functional networks was related to poorer cognitive functioning in elderly. The results were interpreted as a decrease in the specificity of functional networks in older participants. Hum Brain Mapp 35:319–330, 2014. © 2012 Wiley Periodicals, Inc.     

Altered resting-state functional connectivity of the cerebellum in schizophrenia

Structural and functional abnormalities of the cerebellum in schizophrenia have been reported. Most previous studies investigating resting-state functional connectivity (rsFC) have relied on a priori restrictions on seed regions or specific networks, which may bias observations. In this study, we aimed to elicit the connectivity alterations of the cerebellum in schizophrenia in a hypothesis-free approach. Ninety-five schizophrenia patients and 93 sex- and age-matched healthy controls underwent resting-state functional magnetic resonance imaging (fMRI). A voxel-wise data-driven method, resting-state functional connectivity density (rsFCD), was used to investigate cerebellar connectivity changes in schizophrenia patients. Regions with altered rsFCD were chosen as seeds to perform seed-based resting-state functional connectivity (rsFC) analyses. We found that schizophrenia patients exhibited decreased rsFCD in the right hemispheric VI; moreover, this cerebellar region showed increased rsFC with the prefrontal cortex and subcortical nuclei and decreased rsFC with the visual cortex and sensorimotor cortex. In addition, some rsFC changes were associated with positive symptoms. These findings suggest that abnormalities of the cerebellar hub and cerebellar-subcortical-cortical loop may be the underlying mechanisms of schizophrenia.     

Functionally specific changes in resting-state sensorimotor networks after motor learning

Motor learning changes the activity of cortical motor and subcortical areas of the brain, but does learning affect sensory systems as well? We examined in humans the effects of motor learning using fMRI measures of functional connectivity under resting conditions and found persistent changes in networks involving both motor and somatosensory areas of the brain. We developed a technique that allows us to distinguish changes in functional connectivity that can be attributed to motor learning from those that are related to perceptual changes that occur in conjunction with learning. Using this technique, we identified a new network in motor learning involving second somatosensory cortex, ventral premotor cortex, and supplementary motor cortex whose activation is specifically related to perceptual changes that occur in conjunction with motor learning. We also found changes in a network comprising cerebellar cortex, primary motor cortex, and dorsal premotor cortex that were linked to the motor aspects of learning. In each network, we observed highly reliable linear relationships between neuroplastic changes and behavioral measures of either motor learning or perceptual function. Motor learning thus results in functionally specific changes to distinct resting-state networks in the brain.     

Brain connectivity during resting state and subsequent working memory task predicts behavioural performance

Brain regions simultaneously activated during any cognitive process are functionally connected, forming large-scale networks. These functional networks can be examined during active conditions [i.e., task-functional magnetic resonance imaging (fMRI)] and also in passive states (resting-fMRI), where the default mode network (DMN) is the most widely investigated system. The role of the DMN remains unclear, although it is known to be responsible for the shift between resting and focused attention processing. There is also some evidence for its malleability in relation to previous experience. Here we investigated brain connectivity patterns in 16 healthy young subjects by using an n-back task with increasing levels of memory load within the fMRI context. Prior to this working memory (WM) task, participants were trained outside fMRI with a shortened test version. Immediately after, they underwent a resting-state fMRI acquisition followed by the full fMRI n-back test. We observed that the degree of intrinsic correlation within DMN and WM networks was maximal during the most demanding n-back condition (3-back). Furthermore, individuals showing a stronger negative correlation between the two networks under both conditions exhibited better behavioural performance. Interestingly, and despite the fact that we considered eight different resting-state fMRI networks previously identified in humans, only the connectivity within the posteromedial parts of the DMN (precuneus) prior to the fMRI n-back task predicted WM execution. Our results using a data-driven probabilistic approach for fMRI analysis provide the first evidence of a direct relationship between behavioural performance and the degree of negative correlation between the DMN and WM networks. They further suggest that in the context of expectancy for an imminent cognitive challenge, higher resting-state activity in the posteromedial parietal cortex may be related to increased attentional preparatory resources.     

Cerebellar Neural Circuits Involving Executive Control Network Predict Response to Group Cognitive Behavior Therapy in Social Anxiety Disorder

Some intrinsic connectivity networks including the default mode network (DMN) and executive control network (ECN) may underlie social anxiety disorder (SAD). Although the cerebellum has been implicated in the pathophysiology of SAD and several networks relevant to higher-order cognition, it remains unknown whether cerebellar areas involved in DMN and ECN exhibit altered resting-state functional connectivity (rsFC) with cortical networks in SAD. Forty-six patients with SAD and 64 healthy controls (HC) were included and submitted to the baseline resting-state functional magnetic resonance imaging (fMRI). Seventeen SAD patients who completed post-treatment clinical assessments were included after group cognitive behavior therapy (CBT). RsFC of three cerebellar subregions in both groups was assessed respectively in a voxel-wise way, and these rsFC maps were compared by two-sample t tests between groups. Whole-brain voxel-wise regression was performed to examine whether cerebellar connectivity networks can predict response to CBT. Lower rsFC circuits of cerebellar subregions compared with HC at baseline (p < 0.05, corrected by false discovery rate) were revealed. The left Crus I rsFC with dorsal medial prefrontal cortex was negatively correlated with symptom severity. The clinical assessments in SAD patients were significantly decreased after CBT. Higher pretreatment cerebellar rsFC with angular gyrus and dorsal lateral frontal cortex corresponded with greater symptom improvement following CBT. Cerebellar rsFC circuits involving DMN and ECN are possible neuropathologic mechanisms of SAD. Stronger pretreatment cerebellar rsFC circuits involving ECN suggest potential neural markers to predict CBT response.     

Sparse temporally dynamic resting-state functional connectivity networks for early MCI identification

In conventional resting-state functional MRI (R-fMRI) analysis, functional connectivity is assumed to be temporally stationary, overlooking neural activities or interactions that may happen within the scan duration. Dynamic changes of neural interactions can be reflected by variations of topology and correlation strength in temporally correlated functional connectivity networks. These connectivity networks may potentially capture subtle yet short neural connectivity disruptions induced by disease pathologies. Accordingly, we are motivated to utilize disrupted temporal network properties for improving control-patient classification performance. Specifically, a sliding window approach is firstly employed to generate a sequence of overlapping R-fMRI sub-series. Based on these sub-series, sliding window correlations, which characterize the neural interactions between brain regions, are then computed to construct a series of temporal networks. Individual estimation of these temporal networks using conventional network construction approaches fails to take into consideration intrinsic temporal smoothness among successive overlapping R-fMRI sub-series. To preserve temporal smoothness of R-fMRI sub-series, we suggest to jointly estimate the temporal networks by maximizing a penalized log likelihood using a fused sparse learning algorithm. This sparse learning algorithm encourages temporally correlated networks to have similar network topology and correlation strengths. We design a disease identification framework based on the estimated temporal networks, and group level network property differences and classification results demonstrate the importance of including temporally dynamic R-fMRI scan information to improve diagnosis accuracy of mild cognitive impairment patients.     

Mapping the changed hubs and corresponding functional connectivity in idiopathic restless legs syndrome

ObjectiveThe hubs of the brain network play a key role in integrating and transferring information between different functional modules. However, whether the changed pattern in functional network hubs contributes to the onset of leg discomfort symptoms in restless legs syndrome (RLS) patients remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI) and graph theory methods, we investigated whether alterations of hubs can be detected in RLS.MethodsFirst, we constructed the whole-brain voxelwise functional connectivity and calculated a functional connectivity strength (FCS) map in each of 16 drug-naive idiopathic RLS patients and 26 gender- and age-matched healthy control (HC) subjects. Next, a two-sample t test was applied to compare the FCS maps between HC and RLS patients, and to identify significant changes in FCS in RLS patients. To further elucidate the corresponding changes in the functional connectivity patterns of the aberrant hubs in RLS patients, whole-brain resting-state functional connectivity analyses for the hub areas were performed.ResultsThe hub analysis revealed decreased FCS in the cuneus, fusiform gyrus, paracentral lobe, and precuneus, and increased FCS in the superior frontal gyrus and thalamus in idiopathic drug-naive RLS patients. Subsequent functional connectivity analyses revealed decreased functional connectivity in sensorimotor and visual processing networks and increased functional connectivity in the affective cognitive network and cerebellar–thalamic circuit. Furthermore, the mean FCS value in the superior frontal gyrus was significantly correlated with Hamilton Anxiety Rating Scale scores in RLS patients, and the mean FCS value in the fusiform gyrus was significantly correlated with Hamilton Depression Rating Scale scores.ConclusionsThese findings may provide novel insight into the pathophysiology of RLS.     

Baseline frontostriatal‐limbic connectivity predicts reward‐based memory formation

Reward mediates the acquisition and long‐term retention of procedural skills in humans. Yet, learning under rewarded conditions is highly variable across individuals and the mechanisms that determine interindividual variability in rewarded learning are not known. We postulated that baseline functional connectivity in a large‐scale frontostriatal‐limbic network could predict subsequent interindividual variability in rewarded learning. Resting‐state functional MRI was acquired in two groups of subjects (n = 30) who then trained on a visuomotor procedural learning task with or without reward feedback. We then tested whether baseline functional connectivity within the frontostriatal‐limbic network predicted memory strength measured immediately, 24 h and 1 month after training in both groups. We found that connectivity in the frontostriatal‐limbic network predicted interindividual variability in the rewarded but not in the unrewarded learning group. Prediction was strongest for long‐term memory. Similar links between connectivity and reward‐based memory were absent in two control networks, a fronto‐parieto‐temporal language network and the dorsal attention network. The results indicate that baseline functional connectivity within the frontostriatal‐limbic network successfully predicts long‐term retention of rewarded learning. Hum Brain Mapp 35:5921–5931, 2014. © 2014 Wiley Periodicals, Inc.     

Salience and default‐mode network connectivity during threat and safety processing in older adults

The appropriate assessment of threat and safety is important for decision‐making but might be altered in old age due to neurobiological changes. The literature on threat and safety processing in older adults is sparse and it is unclear how healthy ageing affects the brain's functional networks associated with affective processing. We measured skin conductance responses as an indicator of sympathetic arousal and used functional magnetic resonance imaging and independent component analysis to compare young and older adults' functional connectivity in the default mode (DMN) and salience networks (SN) during a threat conditioning and extinction task. While our results provided evidence for differential threat processing in both groups, they also showed that functional connectivity within the SN – but not the DMN – was weaker during threat processing in older compared to young adults. This reduction of within‐network connectivity was accompanied by an age‐related decrease in low frequency spectral power in the SN and a reduction in inter‐network connectivity between the SN and DMN during threat and safety processing. Similarly, we found that skin conductance responses were generally lower in older compared to young adults. Our results are the first to demonstrate age‐related changes in brain activation during aversive conditioning and suggest that the ability to adaptively filter affective information is reduced in older adults.     

Comparison of ApoE-related brain connectivity differences in early MCI and normal aging populations: an fMRI study

In this study, we used resting-state functional magnetic resonance imaging (rs-fMRI) scans from subjects with early mild cognitive impairment (EMCI) and control subjects to study functional network connectivity. The scans were acquired by the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We used genetic data from the ADNI database to further subdivide the EMCI and control groups into genotype groups with or without the Apolipoprotein E allele e4 (APOE e4). Region of interest (ROI)-to-ROI resting-state functional connectivity was measured using Freesurfer and the Functional Connectivity Toolbox for Matlab (CONN). In our analysis, we compared whole-brain ROI connectivity strength and ROI-to-ROI functional network connectivity strength between EMCI, control and genotype subject groups. We found that the ROI network properties were disrupted in EMCI and APOE e4 carrier groups. Notably, we show that (1) EMCI disrupts functional connectivity strength in many important functionally-linked areas; (2) APOE e4 disrupts functional connectivity strength in similar areas to EMCI; and (3) the differences in functional connectivity between groups shows a multifactor contribution to functional network dysfunction along the trajectory leading to dementia.     

Reorganization of brain functional small-world networks during finger movements

A functional measure of brain organization is the efficiency of functional connectivity. The degree of functional connectivity can differ during a task compared to the rest, and to study this issue, we investigated the functional connectivity networks in healthy subjects during a simple, right-handed, sequential finger-tapping task using graph theoretic measures. EEGs were recorded from 58 channels in 15 healthy subjects at rest and during a motor task. We estimated mutual information values of wavelet coefficients to create an association matrix between EEG electrodes and produced a series of adjacency matrices or graphs, A, by thresholding with network cost. These graphs are called small-world networks, and we assessed their efficiency measures. We found economical small-world properties in brain functional connectivity networks in the alpha and beta band networks. The efficiency of the brain networks was enhanced during the task in the beta band networks, but not in the alpha band networks. A regional efficiency analysis during the task showed that the bilateral primary motor and left sensory areas showed increased nodal efficiency, Enodal, whereas decreased Enodal was found over the posterior parietal areas. The present study provides evidence for the reorganization of brain functional connectivity networks in a motor task with the greatest increase in Enodal in motor executive areas.     

Connectivity disruptions in resting-state functional brain networks in children with temporal lobe epilepsy

Functional resting-state connectivity has been shown to be altered in certain adult epilepsy populations, but few connectivity studies have been performed on pediatric epilepsy patients. Here functional connectivity was measured in pediatric, non-lesional temporal lobe epilepsy patients with normal intelligence and compared with that in age and gender-matched healthy controls using the independent component analysis method. We hypothesized that children with non-lesional temporal lobe epilepsy have disrupted functional connectivity within resting-state networks. Significant differences were demonstrated between the two groups, pointing to a decrease in connectivity. When the results were analyzed according to the interictal electroencephalogram findings, however, the connectivity disruptions were seen in different networks. In addition, increased connectivity and abnormally anti-correlated thalamic activity was detected only in the patients with abnormal electroencephalograms. In summary, connectivity disruptions are already to be seen at an early stage of epilepsy, and epileptiform activity seems to affect connectivity differently. The results indicate that interictal epileptiform activity may lead to reorganization of the resting-state brain networks, but further studies would be needed in order to understand the pathophysiology behind this phenomenon.     

Effect of prior cognitive state on resting state networks measured with functional connectivity

To address the extent to which functional connectivity measures an absolute brain state, we observed the effect of prior performance of a language task on resting-state networks in regions associated with language. Six subjects were imaged during rest before and after a block-design language task. Connectivity maps were generated for each of four language regions (identified from analysis of the language activation portion of the study) in each subject for both rest periods. Conjunction analysis demonstrated distinct networks of voxels for each seed region, indicating separate functional subnetworks associated with the different regions. In a comparison of rest before and after the activation task widespread and significant changes were observed in all individuals, suggesting that the measured resting state network reflects a dynamic image of the current brain state. At the group level, an extended network was observed that was largely persistent over time. Even at the group level an increase in connectivity was observed between left and right middle frontal gyri, and between posterior cingulate cortex and medial frontal cortex in the rest after the language task. These results suggest that functional connectivity may be a powerful measure of cognitive state, sensitive to differences between controls and patients together with the particular cognitive processing occurring during the rest state.     

Mapping the altered patterns of cerebellar resting-state function in longitudinal amnestic mild cognitive impairment patients

The cerebellum is known to be a relatively well preserved structure, but subtle alterations may occur early in the evolution of Alzheimer's disease (AD). Amnestic mild cognitive impairment (aMCI) patients appear to be particularly vulnerable to AD. However, little is currently known whether altered patterns of cerebellar function occur in aMCI patients. 26 aMCI patients and 18 well-matched healthy controls underwent a baseline resting-state functional magnetic resonance imaging (fMRI) scan. After a mean follow-up period of 20 months, the subjects who successfully completed baseline fMRI scans underwent a further follow-up scan, while spontaneous activation and functional connectivity of the cerebellum were explored by using resting-state fMRI. Compared to controls, increased amplitude of low frequency fluctuation of the posterior cerebellar lobe may contribute to the underlying mechanisms affected, while greater decreased functional connections to the posterior cerebellar lobe were identified in the longitudinal study of aMCI patients. This suggests that abnormal functional connectivity of the cerebellum may offer a more sensitive and possibly preferred index of functional disturbance than regional activity measures in aMCI patients. The cerebellum may be partly related to the underlying mechanisms of aMCI, and it could help guide subsequent investigations designed to specify the precise functional role of cerebellum in aMCI patients.     

Using spatial multiple regression to identify intrinsic connectivity networks involved in working memory performance

Many researchers have noted that the functional architecture of the human brain is relatively invariant during task performance and the resting state. Indeed, intrinsic connectivity networks (ICNs) revealed by resting-state functional connectivity analyses are spatially similar to regions activated during cognitive tasks. This suggests that patterns of task-related activation in individual subjects may result from the engagement of one or more of these ICNs; however, this has not been tested. We used a novel analysis, spatial multiple regression, to test whether the patterns of activation during an N-back working memory task could be well described by a linear combination of ICNs delineated using Independent Components Analysis at rest. We found that across subjects, the cingulo-opercular Set Maintenance ICN, as well as right and left Frontoparietal Control ICNs, were reliably activated during working memory, while Default Mode and Visual ICNs were reliably deactivated. Further, involvement of Set Maintenance, Frontoparietal Control, and Dorsal Attention ICNs was sensitive to varying working memory load. Finally, the degree of left Frontoparietal Control network activation predicted response speed, while activation in both left Frontoparietal Control and Dorsal Attention networks predicted task accuracy. These results suggest that a close relationship between resting-state networks and task-evoked activation is functionally relevant for behavior, and that spatial multiple regression analysis is a suitable method for revealing that relationship.     

Neural Substrates of Muscle Co-contraction during Dynamic Motor Adaptation

As we learn to perform a motor task with novel dynamics, the central nervous system must adapt motor commands and modify sensorimotor transformations. The objective of the current research is to identify the neural mechanisms underlying the adaptive process. It has been shown previously that an increase in muscle co-contraction is frequently associated with the initial phase of adaptation and that co-contraction is gradually reduced as performance improves. Our investigation focused on the neural substrates of muscle co-contraction during the course of motor adaptation using a resting-state fMRI approach in healthy human subjects of both genders. We analyzed the functional connectivity in resting-state networks during three phases of adaptation, corresponding to different muscle co-contraction levels and found that change in the strength of functional connectivity in one brain network was correlated with a metric of co-contraction, and in another with a metric of motor learning. We identified the cerebellum as the key component for regulating muscle co-contraction, especially its connection to the inferior parietal lobule, which was particularly prominent in early stage adaptation. A neural link between cerebellum, superior frontal gyrus and motor cortical regions was associated with reduction of co-contraction during later stages of adaptation. We also found reliable changes in the functional connectivity of a network involving primary motor cortex, superior parietal lobule and cerebellum that were specifically related to the motor learning.SIGNIFICANCE STATEMENT It is well known that co-contracting muscles is an effective strategy for providing postural stability by modulating mechanical impedance and thereby allowing the central nervous system to compensate for unfamiliar or unexpected physical conditions until motor commands can be appropriately adapted. The present study elucidates the neural substrates underlying the ability to modulate the mechanical impedance of a limb as we learn during motor adaptation. Using resting-state fMRI analysis we demonstrate that a distributed cerebellar-parietal-frontal network functions to regulate muscle co-contraction with the cerebellum as its key component.     

Rhythmic auditory cues shape neural network recruitment in Parkinson's disease during repetitive motor behavior

It is well established clinically that rhythmic auditory cues can improve gait and other motor behaviors in Parkinson's disease (PD) and other disorders. However, the neural systems underlying this therapeutic effect are largely unknown. To investigate this question we scanned people with PD and age‐matched healthy controls using functional magnetic resonance imaging (fMRI). All subjects performed a rhythmic motor behavior (right hand finger tapping) with and without simultaneous auditory rhythmic cues at two different speeds (1 and 4 Hz). We used spatial independent component analysis (ICA) and regression to identify task‐related functional connectivity networks and assessed differences between groups in intra‐ and inter‐network connectivity. Overall, the control group showed greater intra‐network connectivity in perceptual and motor related networks during motor tapping both with and without rhythmic cues. The PD group showed greater inter‐network connectivity between the auditory network and the executive control network, and between the executive control network and the motor/cerebellar network associated with the motor task performance. We interpret our results as indicating that the temporal rhythmic auditory information may assist compensatory mechanisms through network‐level effects, reflected in increased interaction between auditory and executive networks that in turn modulate activity in cortico‐cerebellar networks.     

Detection of PCC functional connectivity characteristics in resting-state fMRI in mild Alzheimer's disease

Resting-state networks dissociate in the early stage of Alzheimer's disease (AD). The posterior cingulate cortex (PCC) in AD brain is vulnerable to isolation from the rest of brain. However, it remains unclear how this functional connectivity is related to PCC changes. We employed resting-state functional MRI (fMRI) to examine brain regions with a functional connection to PCC in a mild AD group compared with matched control subjects. PCC connectivity was gathered by investigating synchronic low frequency fMRI signal fluctuations with a temporal correlation method. We found asymmetric PCC-left hippocampus, right dorsal-lateral prefrontal cortex and right thalamus connectivity disruption. In addition, some other regions such as the bilateral visual cortex, the infero-temporal cortex, the posterior orbital frontal cortex, the ventral medial prefrontal cortex and the precuneus showed decreased functional connectivity to the PCC. There were also some regions, primarily in the left frontal-parietal cortices, that showed increased connectivity. These regions included the medial prefrontal cortex, bilateral dorsal-lateral prefrontal cortex, the left basal ganglia and the left primary motor cortex. Impairments to memory, high vision-related functions and olfaction in AD can be explained by a disruption to the functional connection of resting-state networks. The results of increased connectivity may support the compensatory-recruitment hypothesis. Our findings suggest that the characteristics of resting-state functional connectivity could plausibly provide an early imaging biomarker for AD.     

Resting-state functional connectivity in major depression: abnormally increased contributions from subgenual cingulate cortex and thalamus.

BACKGROUND: Positron emission tomography (PET) studies of major depression have revealed resting-state abnormalities in the prefrontal and cingulate cortices. Recently, fMRI has been adapted to examine connectivity within a specific resting-state neural network--the default-mode network--that includes medial prefrontal and anterior cingulate cortices. The goal of this study was to examine resting-state, default-mode network functional connectivity in subjects with major depression and in healthy controls. METHODS: Twenty-eight subjects with major depression and 20 healthy controls underwent 5-min fMRI scans while resting quietly. Independent component analysis was used to isolate the default-mode network in each subject. Group maps of the default-mode network were compared. A within-group analysis was performed in the depressed group to explore effects of depression refractoriness on functional connectivity. RESULTS: Resting-state subgenual cingulate and thalamic functional connectivity with the default-mode network were significantly greater in the depressed subjects. Within the depressed group, the length of the current depressive episode correlated positively with functional connectivity in the subgenual cingulate. CONCLUSIONS: This is the first study to explore default-mode functional connectivity in major depression. The findings provide cross-modality confirmation of PET studies demonstrating increased thalamic and subgenual cingulate activity in major depression. Further, the within-subject connectivity analysis employed here brings these previously isolated regions of hypermetabolism into the context of a disordered neural network. The correlation between refractoriness and subgenual cingulate functional connectivity within the network suggests that a quantitative, resting-state fMRI measure could be used to guide therapy in individual subjects.     

The association between alterations of eye movement control and cerebral intrinsic functional connectivity in Parkinson’s disease

Patients with Parkinson’s disease (PD) present with eye movement disturbances that accompany the cardinal motor symptoms. Previous studies have consistently found evidence that large-scale functional networks are critically involved in eye movement control. We challenged the hypothesis that altered eye movement control in patients with PD is closely related to alterations of whole-brain functional connectivity in association with the neurodegenerative process. Saccadic and pursuit eye movements by video-oculography and ‘resting-state’ functional MRI (3 Tesla) were recorded from 53 subjects, i.e. 31 patients with PD and 22 matched healthy controls. Video-oculographically, a broad spectrum of eye movement impairments was demonstrated in PD patients vs. controls, including interrupted smooth pursuit, hypometric saccades, and a high distractibility in anti-saccades. Significant correlations between altered oculomotor parameters and functional connectivity measures were observed, i.e. the worse the oculomotor performance was, the more the regional functional connectivity in cortical, limbic, thalamic, cerebellar, and brainstem areas was decreased. Remarkably, decreased connectivity between major nodes of the default mode network was tightly correlated with the prevalence of saccadic intrusions as a measure for distractability. In conclusion, dysfunctional eye movement control in PD seems to be primarily associated with (cortical) executive deficits, rather than being related to the ponto-cerebellar circuits or the oculomotor brainstem nuclei. Worsened eye movement performance together with the potential pathophysiological substrate of decreased intrinsic functional connectivity in predominantly oculomotor-associated cerebral functional networks may constitute a behavioral marker in PD.