Overlapping and segregated resting‐state functional connectivity in patients with major depressive disorder with and without childhood neglect

Many studies have suggested that childhood maltreatment increase risk of adulthood major depressive disorder (MDD) and predict its unfavorable treatment outcome, yet the neural underpinnings associated with childhood maltreatment in MDD remain poorly understood. Here, we seek to investigate the whole‐brain functional connectivity patterns in MDD patients with childhood maltreatment. Resting‐state functional magnetic resonance imaging was used to explore intrinsic or spontaneous functional connectivity networks of 18 MDD patients with childhood neglect, 20 MDD patients without childhood neglect, and 20 healthy controls. Whole‐brain functional networks were constructed by measuring the temporal correlations of every pairs of brain voxels and were further analyzed by using graph‐theory approaches. Relative to the healthy control group, the two MDD patient groups showed overlapping reduced functional connectivity strength in bilateral ventral medial prefrontal cortex/ventral anterior cingulate cortex. However, compared with MDD patients without a history of childhood maltreatment, those patients with such a history displayed widespread reduction of functional connectivity strength primarily in brain regions within the prefrontal‐limbic‐thalamic‐cerebellar circuitry, and these reductions significantly correlated with measures of childhood neglect. Together, we showed that the MDD groups with and without childhood neglect exhibited overlapping and segregated functional connectivity patterns in the whole‐brain networks, providing empirical evidence for the contribution of early life stress to the pathophysiology of MDD. Hum Brain Mapp 35:1154–1166, 2014. © 2013 Wiley Periodicals, Inc.     

Alterations in amplitude of low frequency fluctuation in treatment‐naïve major depressive disorder measured with resting‐state fMRI

There are limited resting‐state functional magnetic resonance imaging (fMRI) studies in major depressive disorder (MDD). Of these studies, functional connectivity analyses are mostly used. However, a new method based on the magnitude of low frequency fluctuation (LFF) during resting‐state fMRI may provide important insight into MDD. In this study, we examined the amplitude of LFF (ALFF) within the whole brain during resting‐state fMRI in 30 treatment‐naïve MDD subjects and 30 healthy control (HC) subjects. When compared with HC, MDD subjects showed increased ALFF in the frontal cortex (including the bilateral ventral/dorsal anterior cingulate cortex, orbitofrontal cortex, premotor cortex, ventral prefrontal cortex, left dorsal lateral frontal cortex, left superior frontal cortex), basal ganglia (including the right putamen and left caudate nucleus), left insular cortex, right anterior entorhinal cortex and left inferior parietal cortex, together with decreased ALFF in the bilateral occipital cortex, cerebellum hemisphere, and right superior temporal cortex. These findings may relate to characteristics of MDD, such as excessive self‐referential processing and deficits in cognitive control of emotional processing, which may contribute to the persistent and recurrent nature of the disorder. Hum Brain Mapp 35:4979–4988, 2014. © 2014 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.     

Improved correspondence of resting‐state networks after macroanatomical alignment

Resting state brain activity, as measured with functional magnetic resonance imaging (fMRI) in the absence of stimulation, is widely investigated in clinical, pharmacological, developmental and cross‐species neuroscience research. However, despite the general and broad interest in understating the nature of resting state networks (RSNs), there has not been a thorough investigation into the relationship between these functional networks and their adherence to underling brain anatomy. We acquired resting state fMRI data from 10 subjects and extracted individual and group RSN maps respectively using independent component analysis (ICA) and self organising group‐level ICA (sogICA). Cortex based alignment (CBA), an advanced surface based alignment technique which uses individual curvature information to align individual subjects' brains to a dynamic group average, was used to maximise anatomical correspondence across subjects. Cross subject spatial correlations of the RSN maps (independent components) were carried out with and without CBA. Seven RSNs, which are amongst the most reported and studied networks, were identified. We observed a systematic gain in the spatial correlation in all of them following CBA, although this gain was not uniform across RSNs. The observed increase in similarity of the functional RSNs after anatomical alignment illustrates that these functional networks are indeed related to underlying macroanatomical features. Moreover, our results demonstrate that by correcting for individual anatomical differences, advanced surface based alignment techniques increase the overlap of corresponding resting state networks across subjects, thereby providing a useful means to improve resting state group statistics with no need for substantial smoothing. Hum Brain Mapp 35:673–682, 2014. © 2012 Wiley Periodicals, Inc.     

Functionally linked resting‐state networks reflect the underlying structural connectivity architecture of the human brain

During rest, multiple cortical brain regions are functionally linked forming resting‐state networks. This high level of functional connectivity within resting‐state networks suggests the existence of direct neuroanatomical connections between these functionally linked brain regions to facilitate the ongoing interregional neuronal communication. White matter tracts are the structural highways of our brain, enabling information to travel quickly from one brain region to another region. In this study, we examined both the functional and structural connections of the human brain in a group of 26 healthy subjects, combining 3 Tesla resting‐state functional magnetic resonance imaging time‐series with diffusion tensor imaging scans. Nine consistently found functionally linked resting‐state networks were retrieved from the resting‐state data. The diffusion tensor imaging scans were used to reconstruct the white matter pathways between the functionally linked brain areas of these resting‐state networks. Our results show that well‐known anatomical white matter tracts interconnect at least eight of the nine commonly found resting‐state networks, including the default mode network, the core network, primary motor and visual network, and two lateralized parietal‐frontal networks. Our results suggest that the functionally linked resting‐state networks reflect the underlying structural connectivity architecture of the human brain. Hum Brain Mapp 2009. © 2009 Wiley‐Liss, Inc.     

Altered resting‐state activity in seasonal affective disorder

At present, our knowledge about seasonal affective disorder (SAD) is based mainly up on clinical symptoms, epidemiology, behavioral characteristics and light therapy. Recently developed measures of resting‐state functional brain activity might provide neurobiological markers of brain disorders. Studying functional brain activity in SAD could enhance our understanding of its nature and possible treatment strategies. Functional network connectivity (measured using ICA‐dual regression), and amplitude of low‐frequency fluctuations (ALFF) were measured in 45 antidepressant‐free patients (39.78 ± 10.64, 30 ♀, 15 ♂) diagnosed with SAD and compared with age‐, gender‐ and ethnicity‐matched healthy controls (HCs) using resting‐state functional magnetic resonance imaging. After correcting for Type 1 error at high model orders (inter‐RSN correction), SAD patients showed significantly increased functional connectivity in 11 of the 47 identified RSNs. Increased functional connectivity involved RSNs such as visual, sensorimotor, and attentional networks. Moreover, our results revealed that SAD patients compared with HCs showed significant higher ALFF in the visual and right sensorimotor cortex. Abnormally altered functional activity detected in SAD supports previously reported attentional and psychomotor symptoms in patients suffering from SAD. Further studies, particularly under task conditions, are needed in order to specifically investigate cognitive deficits in SAD. Hum Brain Mapp 35:161–172, 2014. © 2012 Wiley Periodicals, Inc.     

Genetic influences on resting‐state functional networks: A twin study

Alterations in resting‐state networks (RSNs) are often associated with psychiatric and neurologic disorders. Given this critical linkage, it has been hypothesized that RSNs can potentially be used as endophenotypes for brain diseases. To validate this notion, a critical step is to show that RSNs exhibit heritability. However, the investigation of the genetic basis of RSNs has only been attempted in the default‐mode network at the region‐of‐interest level, while the genetic control on other RSNs has not been determined yet. Here, we examined the genetic and environmental influences on eight well‐characterized RSNs using a twin design. Resting‐state functional magnetic resonance imaging data in 56 pairs of twins were collected. The genetic and environmental effects on each RSN were estimated by fitting the functional connectivity covariance of each voxel in the RSN to the classic ACE twin model. The data showed that although environmental effects accounted for the majority of variance in wide‐spread areas, there were specific brain sites that showed significant genetic control for individual RSNs. These results suggest that part of the human brain functional connectome is shaped by genomic constraints. Importantly, this information can be useful for bridging genetic analysis and network‐level assessment of brain disorders. Hum Brain Mapp 36:3959–3972, 2015. © 2015 Wiley Periodicals, Inc.     

Apolipoprotein E ε4 modulates functional brain connectome in Alzheimer's disease

The apolipoprotein E (APOE) ?4 allele is a well‐established genetic risk factor for Alzheimer's disease (AD). Recent research has demonstrated an APOE ?4‐mediated modulation of intrinsic functional brain networks in cognitively normal individuals. However, it remains largely unknown whether and how APOE ?4 affects the brain's functional network architecture in patients with AD. Using resting‐state functional MRI and graph‐theory approaches, we systematically investigated the topological organization of whole‐brain functional networks in 16 APOE ?4 carriers and 26 matched noncarriers with AD at three levels: global whole‐brain, intermediate module, and regional node/connection. Neuropsychological analysis showed that the APOE ?4 carriers performed worse on delayed memory but better on a late item generation of a verbal fluency task (associated with executive function) than noncarriers. Whole‐brain graph analyses revealed that APOE ?4 significantly disrupted whole‐brain topological organization as characterized by (i) reduced parallel information transformation efficiency; (ii) decreased intramodular connectivity within the posterior default mode network (pDMN) and intermodular connectivity of the pDMN and executive control network (ECN) with other neuroanatomical systems; and (iii) impaired functional hubs and their rich‐club connectivities that primarily involve the pDMN, ECN, and sensorimotor systems. Further simulation analysis indicated that these altered connectivity profiles of the pDMN and ECN largely accounted for the abnormal global network topology. Finally, the changes in network topology exhibited significant correlations with the patients' cognitive performances. Together, our findings suggest that the APOE genotype modulates large‐scale brain networks in AD and shed new light on the gene‐connectome interaction in this disease. Hum Brain Mapp 36:1828–1846, 2015. © 2015 Wiley Periodicals, Inc .     

Preprocessing strategy influences graph‐based exploration of altered functional networks in major depression

Resting‐state fMRI studies have gained widespread use in exploratory studies of neuropsychiatric disorders. Graph metrics derived from whole brain functional connectivity studies have been used to reveal disease‐related variations in many neuropsychiatric disorders including major depression (MDD). These techniques show promise in developing diagnostics for these often difficult to identify disorders. However, the analysis of resting‐state datasets is increasingly beset by a myriad of approaches and methods, each with underlying assumptions. Choosing the most appropriate preprocessing parameters a priori is difficult. Nevertheless, the specific methodological choice influences graph‐theoretical network topologies as well as regional metrics. The aim of this study was to systematically compare different preprocessing strategies by evaluating their influence on group differences between healthy participants (HC) and depressive patients. We thus investigated the effects of common preprocessing variants, including global mean‐signal regression (GMR), temporal filtering, detrending, and network sparsity on group differences between brain networks of HC and MDD patients measured by global and nodal graph theoretical metrics. Occurrence of group differences in global metrics was absent in the majority of tested preprocessing variants, but in local graph metrics it is sparse, variable, and highly dependent on the combination of preprocessing variant and sparsity threshold. Sparsity thresholds between 16 and 22% were shown to have the greatest potential to reveal differences between HC and MDD patients in global and local network metrics. Our study offers an overview of consequences of methodological decisions and which neurobiological characteristics of MDD they implicate, adding further caution to this rapidly growing field. Hum Brain Mapp 37:1422‐1442, 2016. © 2016 Wiley Periodicals, Inc.     

Changes in resting‐state functionally connected parietofrontal networks after videogame practice

Neuroimaging studies provide evidence for organized intrinsic activity under task‐free conditions. This activity serves functionally relevant brain systems supporting cognition. Here, we analyze changes in resting‐state functional connectivity after videogame practice applying a test–retest design. Twenty young females were selected from a group of 100 participants tested on four standardized cognitive ability tests. The practice and control groups were carefully matched on their ability scores. The practice group played during two sessions per week across 4 weeks (16 h total) under strict supervision in the laboratory, showing systematic performance improvements in the game. A group independent component analysis (GICA) applying multisession temporal concatenation on test–retest resting‐state fMRI, jointly with a dual‐regression approach, was computed. Supporting the main hypothesis, the key finding reveals an increased correlated activity during rest in certain predefined resting state networks (albeit using uncorrected statistics) attributable to practice with the cognitively demanding tasks of the videogame. Observed changes were mainly concentrated on parietofrontal networks involved in heterogeneous cognitive functions. Hum Brain Mapp 34:3143–3157, 2013. © 2012 Wiley Periodicals, Inc.     

Disrupted brain network topology in pediatric posttraumatic stress disorder: A resting‐state fMRI study

Children exposed to natural disasters are vulnerable to the development of posttraumatic stress disorder (PTSD). Recent studies of other neuropsychiatric disorders have used graph‐based theoretical analysis to investigate the topological properties of the functional brain connectome. However, little is known about this connectome in pediatric PTSD. Twenty‐eight pediatric PTSD patients and 26 trauma‐exposed non‐PTSD patients were recruited from 4,200 screened subjects after the 2008 Sichuan earthquake to undergo a resting‐state functional magnetic resonance imaging scan. Functional connectivity between 90 brain regions from the automated anatomical labeling atlas was established using partial correlation coefficients, and the whole‐brain functional connectome was constructed by applying a threshold to the resultant 90 * 90 partial correlation matrix. Graph theory analysis was then used to examine the group‐specific topological properties of the two functional connectomes. Both the PTSD and non‐PTSD control groups exhibited “small‐world” brain network topology. However, the functional connectome of the PTSD group showed a significant increase in the clustering coefficient and a normalized characteristic path length and local efficiency, suggesting a shift toward regular networks. Furthermore, the PTSD connectomes showed both enhanced nodal centralities, mainly in the default mode‐ and salience‐related regions, and reduced nodal centralities, mainly in the central‐executive network regions. The clustering coefficient and nodal efficiency of the left superior frontal gyrus were positively correlated with the Clinician‐Administered PTSD Scale. These disrupted topological properties of the functional connectome help to clarify the pathogenesis of pediatric PTSD and could be potential biomarkers of brain abnormalities. Hum Brain Mapp 36:3677–3686, 2015. © 2015 Wiley Periodicals, Inc .     

Multimodal analysis of cortical chemoarchitecture and macroscale fMRI resting‐state functional connectivity

The cerebral cortex is well known to display a large variation in excitatory and inhibitory chemoarchitecture, but the effect of this variation on global scale functional neural communication and synchronization patterns remains less well understood. Here, we provide evidence of the chemoarchitecture of cortical regions to be associated with large‐scale region‐to‐region resting‐state functional connectivity. We assessed the excitatory versus inhibitory chemoarchitecture of cortical areas as an ExIn ratio between receptor density mappings of excitatory (AMPA, M₁) and inhibitory (GABA_A, M₂) receptors, computed on the basis of data collated from pioneering studies of autoradiography mappings as present in literature of the human (2 datasets) and macaque (1 dataset) cortex. Cortical variation in ExIn ratio significantly correlated with total level of functional connectivity as derived from resting‐state functional connectivity recordings of cortical areas across all three datasets (human I: P = 0.0004; human II: P = 0.0008; macaque: P = 0.0007), suggesting cortical areas with an overall more excitatory character to show higher levels of intrinsic functional connectivity during resting‐state. Our findings are indicative of the microscale chemoarchitecture of cortical regions to be related to resting‐state fMRI connectivity patterns at the global system's level of connectome organization. Hum Brain Mapp 37:3103–3113, 2016. © 2016 Wiley Periodicals, Inc.     

The influence of mild carbon dioxide on brain functional homotopy using resting‐state fMRI

Homotopy reflects the intrinsic functional architecture of the brain through synchronized spontaneous activity between corresponding bilateral regions, measured as voxel mirrored homotopic connectivity (VMHC). Hypercapnia is known to have clear impact on brain hemodynamics through vasodilation, but have unclear effect on neuronal activity. This study investigates the effect of hypercapnia on brain homotopy, achieved by breathing 5% carbon dioxide (CO₂) gas mixture. A total of 14 healthy volunteers completed three resting state functional MRI (RS‐fMRI) scans, the first and third under normocapnia and the second under hypercapnia. VMHC measures were calculated as the correlation between the BOLD signal of each voxel and its counterpart in the opposite hemisphere. Group analysis was performed between the hypercapnic and normocapnic VMHC maps. VMHC showed a diffused decrease in response to hypercapnia. Significant regional decreases in VMHC were observed in all anatomical lobes, except for the occipital lobe, in the following functional hierarchical subdivisions: the primary sensory‐motor, unimodal, heteromodal, paralimbic, as well as in the following functional networks: ventral attention, somatomotor, default frontoparietal, and dorsal attention. Our observation that brain homotopy in RS‐fMRI is affected by arterial CO₂ levels suggests that caution should be used when comparing RS‐fMRI data between healthy controls and patients with pulmonary diseases and unusual respiratory patterns such as sleep apnea or chronic obstructive pulmonary disease. Hum Brain Mapp 36:3912–3921, 2015. © 2015 Wiley Periodicals, Inc.     

Intrinsic resting‐state activity predicts working memory brain activation and behavioral performance

Although resting‐state brain activity has been demonstrated to correspond with task‐evoked brain activation, the relationship between intrinsic and evoked brain activity has not been fully characterized. For example, it is unclear whether intrinsic activity can also predict task‐evoked deactivation and whether the rest–task relationship is dependent on task load. In this study, we addressed these issues on 40 healthy control subjects using resting‐state and task‐driven [N‐back working memory (WM) task] functional magnetic resonance imaging data collected in the same session. Using amplitude of low‐frequency fluctuation (ALFF) as an index of intrinsic resting‐state activity, we found that ALFF in the middle frontal gyrus and inferior/superior parietal lobules was positively correlated with WM task‐evoked activation, while ALFF in the medial prefrontal cortex, posterior cingulate cortex, superior frontal gyrus, superior temporal gyrus, and fusiform gyrus was negatively correlated with WM task‐evoked deactivation. Further, the relationship between the intrinsic resting‐state activity and task‐evoked activation in lateral/superior frontal gyri, inferior/superior parietal lobules, superior temporal gyrus, and midline regions was stronger at higher WM task loads. In addition, both resting‐state activity and the task‐evoked activation in the superior parietal lobule/precuneus were significantly correlated with the WM task behavioral performance, explaining similar portions of intersubject performance variance. Together, these findings suggest that intrinsic resting‐state activity facilitates or is permissive of specific brain circuit engagement to perform a cognitive task, and that resting activity can predict subsequent task‐evoked brain responses and behavioral performance. Hum Brain Mapp 34:3204–3215, 2013. © 2012 Wiley Periodicals, Inc.     

Dynamic functional connectivity reveals altered variability in functional connectivity among patients with major depressive disorder

Resting‐state fMRI (RS‐fMRI) has become a useful tool to investigate the connectivity structure of mental health disorders. In the case of major depressive disorder (MDD), recent studies regarding the RS‐fMRI have found abnormal connectivity in several regions of the brain, particularly in the default mode network (DMN). Thus, the relevance of the DMN to self‐referential thoughts and ruminations has made the use of the resting‐state approach particularly important for MDD. The majority of such research has relied on the grand averaged functional connectivity measures based on the temporal correlations between the BOLD time series of various brain regions. We, in our study, investigated the variations in the functional connectivity over time at global and local level using RS‐fMRI BOLD time series of 27 MDD patients and 27 healthy control subjects. We found that global synchronization and temporal stability were significantly increased in the MDD patients. Furthermore, the participants with MDD showed significantly increased overall average (static) functional connectivity (sFC) but decreased variability of functional connectivity (vFC) within specific networks. Static FC increased to predominance among the regions pertaining to the default mode network (DMN), while the decreased variability of FC was observed in the connections between the DMN and the frontoparietal network. Hum Brain Mapp 37:2918–2930, 2016. © 2016 Wiley Periodicals, Inc.     

Sub‐hubs of baseline functional brain networks are related to early improvement following two‐week pharmacological therapy for major depressive disorder

Accumulating evidence suggests that early improvement after two‐week antidepressant treatment is predictive of later outcomes of patients with major depressive disorder (MDD); however, whether this early improvement is associated with baseline neural architecture remains largely unknown. Utilizing resting‐state functional MRI data and graph‐based network approaches, this study calculated voxel‐wise degree centrality maps for 24 MDD patients at baseline and linked them with changes in the Hamilton Rating Scale for Depression (HAMD) scores after two weeks of medication. Six clusters exhibited significant correlations of their baseline degree centrality with treatment‐induced HAMD changes for the patients, which were mainly categorized into the posterior default‐mode network (i.e., the left precuneus, supramarginal gyrus, middle temporal gyrus, and right angular gyrus) and frontal regions. Receiver operating characteristic curve and logistic regression analyses convergently revealed excellent performance of these regions in discriminating the early improvement status for the patients, especially the angular gyrus (sensitivity and specificity of 100%). Moreover, the angular gyrus was identified as the optimal regressor as determined by stepwise regression. Interestingly, these regions possessed higher centrality than others in the brain (P < 10^?3) although they were not the most highly connected hubs. Finally, we demonstrate a high reproducibility of our findings across several factors (e.g., threshold choice, anatomical distance, and temporal cutting) in our analyses. Together, these preliminary exploratory analyses demonstrate the potential of neuroimaging‐based network analysis in predicting the early therapeutic improvement of MDD patients and have important implications in guiding earlier personalized therapeutic regimens for possible treatment‐refractory depression. Hum Brain Mapp 36:2915–2927, 2015. © 2015 Wiley Periodicals, Inc.     

Functional connectivity associated with gait velocity during walking and walking‐while‐talking in aging: A resting‐state fMRI study

Gait decline is common among older adults and is a risk factor for adverse outcomes. Poor gait performance in dual‐task conditions, such as walking while performing a secondary cognitive interference task, is associated with increased risk of frailty, disability, and death. Yet, the functional neural substrates that support locomotion are not well established. We examined the functional connectivity associated with gait velocity in single‐ (normal pace walking) and dual‐task (walking while talking) conditions using resting‐state functional Magnetic Resonance Imaging (fMRI). We acquired 6 minutes of resting‐state fMRI data in 30 cognitively healthy older adults. Independent components analyses were performed to separate resting‐state fMRI data into group‐level statistically independent spatial components that correlated with gait velocity in single‐ and dual‐task conditions. Gait velocity in both task conditions was associated with similar functional connectivity in sensorimotor, visual, vestibular, and left fronto‐parietal cortical areas. Compared to gait velocity in the single‐task condition, the networks associated with gait velocity in the dual‐task condition were associated with greater functional connectivity in supplementary motor and prefrontal regions. Our findings show that there are partially overlapping functional networks associated with single‐ and dual‐task walking conditions. These initial findings encourage the future use of resting‐state fMRI as tool in developing a comprehensive understanding of age‐related mobility impairments. Hum Brain Mapp 36:1484–1493, 2015. © 2014 Wiley Periodicals, Inc.     

Dopaminergic modulation of resting‐state functional connectivity in de novo patients with Parkinson's disease

Parkinson's disease (PD) is characterized by degenerative changes of nigral dopamine neurons, resulting in the dopaminergic denervation of the striatum. Resting state networks studies have demonstrated that dopamine modulates distinct network connectivity patterns in both a linear and a nonlinear fashion, but quantitative analyses of dopamine‐dependent functional connectivity secondary to PD pathology were less informative. In the present study, we performed a correlation analysis between striatal dopamine levels assessed quantitatively by FP‐CIT positron emission tomography imaging and resting‐state functional connectivity in 23 drug naïve de novo patients with PD to elucidate dopamine‐dependent functional networks. The major finding is that the patterns of dopamine‐dependent positive functional connectivity varied depending on the location of striatal seeds. Dopamine‐dependent functional connectivity with the caudate predominantly overlay pericentral cortical areas, whereas dopamine‐dependent structures functionally connected with the posterior putamen predominantly involved cerebellar areas. The dorsolateral frontal area overlapped as a dopamine‐dependent cortical region that was positively connected with the anterior and posterior putamen. On the other hand, cortical areas where functional connectivity from the posterior cingulate was negatively correlated with dopaminergic status in the posterior putamen were localized in the left anterior prefrontal area and the parietal area. Additionally, functional connectivity between the anterior putamen and mesiofrontal areas was negatively coupled with striatal dopamine levels. The present study demonstrated that dopamine‐dependent functional network connectivity secondary to PD pathology mainly exhibits a consistent pattern, albeit with some variation. These patterns may reflect the diverse effects of dopaminergic medication on parkinsonian‐related motor and cognitive performance. Hum Brain Mapp 35:5431–5441, 2014. © 2014 Wiley Periodicals, Inc .     

Resting‐state functional connectivity and motor imagery brain activation

Motor imagery (MI) relies on the mental simulation of an action without any overt motor execution (ME), and can facilitate motor learning and enhance the effect of rehabilitation in patients with neurological conditions. While functional magnetic resonance imaging (fMRI) during MI and ME reveals shared cortical representations, the role and functional relevance of the resting‐state functional connectivity (RSFC) of brain regions involved in MI is yet unknown. Here, we performed resting‐state fMRI followed by fMRI during ME and MI with the dominant hand. We used a behavioral chronometry test to measure ME and MI movement duration and compute an index of performance (IP). Then, we analyzed the voxel‐matched correlation between the individual MI parameter estimates and seed‐based RSFC maps in the MI network to measure the correspondence between RSFC and MI fMRI activation. We found that inter‐individual differences in intrinsic connectivity in the MI network predicted several clusters of activation. Taken together, present findings provide first evidence that RSFC within the MI network is predictive of the activation of MI brain regions, including those associated with behavioral performance, thus suggesting a role for RSFC in obtaining a deeper understanding of neural substrates of MI and of MI ability. Hum Brain Mapp 37:3847–3857, 2016. © 2016 Wiley Periodicals, Inc.