The effects of methylphenidate on whole brain intrinsic functional connectivity

Methylphenidate (MPH) is an indirect dopaminergic and noradrenergic agonist that is used to treat attention deficit hyperactivity disorder and that has shown therapeutic potential in neuropsychiatric diseases such as depression, dementia, and Parkinson's disease. While effects of MPH on task‐induced brain activation have been investigated, little is known about how MPH influences the resting brain. To investigate the effects of 40 mg of oral MPH on intrinsic functional connectivity, we used resting state fMRI in 54 healthy male subjects in a double‐blind, randomized, placebo‐controlled study. Functional connectivity analysis employing ICA revealed seven resting state networks (RSN) of interest. Connectivity strength between the dorsal attention network and the thalamus was increased after MPH intake. Other RSN located in association cortex areas, such as the left and right frontoparietal networks and the executive control network, showed MPH‐induced connectivity increase to sensory‐motor and visual cortex regions and connectivity decrease to cortical and subcortical components of cortico‐striato‐thalamo‐cortical circuits (CST). RSN located in sensory‐motor cortex areas showed the opposite pattern with MPH‐induced connectivity increase to CST components and connectivity decrease to sensory‐motor and visual cortex regions. Our results provide evidence that MPH does not only alter intrinsic connectivity between brain areas involved in sustained attention, but that it also induces significant changes in the cortico‐cortical and cortico‐subcortical connectivity of many other cognitive and sensory‐motor RSN. Hum Brain Mapp 35:5379–5388, 2014. © 2014 Wiley Periodicals, Inc.     

Dynamic functional network connectivity in Huntington's disease and its associations with motor and cognitive measures

Dynamic functional network connectivity (dFNC) is an expansion of traditional, static FNC that measures connectivity variation among brain networks throughout scan duration. We used a large resting‐state fMRI (rs‐fMRI) sample from the PREDICT‐HD study (N = 183 Huntington disease gene mutation carriers [HDgmc] and N = 78 healthy control [HC] participants) to examine whole‐brain dFNC and its associations with CAG repeat length as well as the product of scaled CAG length and age, a variable representing disease burden. We also tested for relationships between functional connectivity and motor and cognitive measurements. Group independent component analysis was applied to rs‐fMRI data to obtain whole‐brain resting state networks. FNC was defined as the correlation between RSN time‐courses. Dynamic FNC behavior was captured using a sliding time window approach, and FNC results from each window were assigned to four clusters representing FNC states, using a k‐means clustering algorithm. HDgmc individuals spent significantly more time in State‐1 (the state with the weakest FNC pattern) compared to HC. However, overall HC individuals showed more FNC dynamism than HDgmc. Significant associations between FNC states and genetic and clinical variables were also identified. In FNC State‐4 (the one that most resembled static FNC), HDgmc exhibited significantly decreased connectivity between the putamen and medial prefrontal cortex compared to HC, and this was significantly associated with cognitive performance. In FNC State‐1, disease burden in HDgmc participants was significantly associated with connectivity between the postcentral gyrus and posterior cingulate cortex, as well as between the inferior occipital gyrus and posterior parietal cortex.     

Localized reductions in resting‐state functional connectivity in children with prenatal alcohol exposure

Fetal alcohol spectrum disorders (FASD) are characterized by impairment in cognitive function that may or may not be accompanied by craniofacial anomalies, microcephaly, and/or growth retardation. Resting‐state functional MRI (rs‐fMRI), which examines the low‐frequency component of the blood oxygen level dependent (BOLD) signal in the absence of an explicit task, provides an efficient and powerful mechanism for studying functional brain networks even in low‐functioning and young subjects. Studies using independent component analysis (ICA) have identified a set of resting‐state networks (RSNs) that have been linked to distinct domains of cognitive and perceptual function, which are believed to reflect the intrinsic functional architecture of the brain. This study is the first to examine resting‐state functional connectivity within these RSNs in FASD. Rs‐fMRI scans were performed on 38 children with FASD (19 with either full fetal alcohol syndrome (FAS) or partial FAS (PFAS), 19 nonsyndromal heavily exposed (HE)), and 19 controls, mean age 11.3 ± 0.9 years, from the Cape Town Longitudinal Cohort. Nine resting‐state networks were generated by ICA. Voxelwise group comparison between a combined FAS/PFAS group and controls revealed localized dose‐dependent functional connectivity reductions in five regions in separate networks: anterior default mode, salience, ventral and dorsal attention, and R executive control. The former three also showed lower connectivity in the HE group. Gray matter connectivity deficits in four of the five networks appear to be related to deficits in white matter tracts that provide intra‐RSN connections. Hum Brain Mapp 38:5217–5233, 2017. © 2017 Wiley Periodicals, Inc.     

Fluctuations of the EEG‐fMRI correlation reflect intrinsic strength of functional connectivity in default mode network

Both functional magnetic resonance imaging (fMRI) and electrophysiological recordings have revealed that resting‐state functional connectivity is temporally variable in human brain. Combined full‐band electroencephalography‐fMRI (fbEEG‐fMRI) studies have shown that infraslow (<.1 Hz) fluctuations in EEG scalp potential are correlated with the blood‐oxygen‐level‐dependent (BOLD) fMRI signals and that also this correlation appears variable over time. Here, we used simultaneous fbEEG‐fMRI to test the hypothesis that correlation dynamics between BOLD and fbEEG signals could be explained by fluctuations in the activation properties of resting‐state networks (RSNs) such as the extent or strength of their activation. We used ultrafast magnetic resonance encephalography (MREG) fMRI to enable temporally accurate and statistically robust short‐time‐window comparisons of infra‐slow fbEEG and BOLD signals. We found that the temporal fluctuations in the fbEEG‐BOLD correlation were dependent on RSN connectivity strength, but not on the mean signal level or magnitude of RSN activation or motion during scanning. Moreover, the EEG‐fMRI correlations were strongest when the intrinsic RSN connectivity was strong and close to the pial surface. Conversely, weak fbEEG‐BOLD correlations were attributable to periods of less coherent or spatially more scattered intrinsic RSN connectivity, or RSN activation in deeper cerebral structures. The results thus show that the on‐average low correlations between infra‐slow EEG and BOLD signals are, in fact, governed by the momentary coherence and depth of the underlying RSN activation, and may reach systematically high values with appropriate source activities. These findings further consolidate the notion of slow scalp potentials being directly coupled to hemodynamic fluctuations.     

Aberrant brain network connectivity in presymptomatic and manifest Huntington's disease: A systematic review

Resting‐state functional magnetic resonance imaging (rs‐fMRI) has the potential to shed light on the pathophysiological mechanisms of Huntington's disease (HD), paving the way to new therapeutic interventions. A systematic literature review was conducted in three online databases according to PRISMA guidelines, using keywords for HD, functional connectivity, and rs‐fMRI. We included studies investigating connectivity in presymptomatic (pre‐HD) and manifest HD gene carriers compared to healthy controls, implementing seed‐based connectivity, independent component analysis, regional property, and graph analysis approaches. Visual network showed reduced connectivity in manifest HD, while network/areas underpinning motor functions were consistently altered in both manifest HD and pre‐HD, showing disease stage‐dependent changes. Cognitive networks underlying executive and attentional functions showed divergent anterior–posterior alterations, possibly reflecting compensatory mechanisms. The involvement of these networks in pre‐HD is still unclear. In conclusion, aberrant connectivity of the sensory‐motor network is observed in the early stage of HD while, as pathology spreads, other networks might be affected, such as the visual and executive/attentional networks. Moreover, sensory‐motor and executive networks exhibit hyper‐ and hypo‐connectivity patterns following different spatiotemporal trajectories. These findings could potentially help to implement future huntingtin‐lowering interventions.     

Functional connectivity‐based identification of subdivisions of the basal ganglia and thalamus using multilevel independent component analysis of resting state fMRI

This study aimed to identify subunits of the basal ganglia and thalamus and to investigate the functional connectivity among these anatomically segregated subdivisions and the cerebral cortex in healthy subjects. For this purpose, we introduced multilevel independent component analysis (ICA) of the resting‐state functional magnetic resonance imaging (fMRI). After applying ICA to the whole brain gray matter, we applied second‐level ICA restrictively to the basal ganglia and the thalamus area to identify discrete functional subunits of those regions. As a result, the basal ganglia and the thalamus were parcelled into 31 functional subdivisions according to their temporal activity patterns. The extracted parcels showed functional network connectivity between hemispheres, between subdivisions of the basal ganglia and thalamus, and between the extracted subdivisions and cerebral functional components. Grossly, these findings correspond to cortico‐striato‐thalamo‐cortical circuits in the brain. This study also showed the utility of multilevel ICA of resting state fMRI in brain network research. Hum Brain Mapp, 2013. © 2012 Wiley Perodicals, Inc.     

Intrinsic network activity in tinnitus investigated using functional MRI

Tinnitus is an increasingly common disorder in which patients experience phantom auditory sensations, usually ringing or buzzing in the ear. Tinnitus pathophysiology has been repeatedly shown to involve both auditory and non‐auditory brain structures, making network‐level studies of tinnitus critical. In this magnetic resonance imaging (MRI) study, two resting‐state functional connectivity (RSFC) approaches were used to better understand functional network disturbances in tinnitus. First, we demonstrated tinnitus‐related reductions in RSFC between specific brain regions and resting‐state networks (RSNs), defined by independent components analysis (ICA) and chosen for their overlap with structures known to be affected in tinnitus. Then, we restricted ICA to data from tinnitus patients, and identified one RSN not apparent in control data. This tinnitus RSN included auditory–sensory regions like inferior colliculus and medial Heschl's gyrus, as well as classically non‐auditory regions like the mediodorsal nucleus of the thalamus, striatum, lateral prefrontal, and orbitofrontal cortex. Notably, patients' reported tinnitus loudness was positively correlated with RSFC between the mediodorsal nucleus and the tinnitus RSN, indicating that this network may underlie the auditory–sensory experience of tinnitus. These data support the idea that tinnitus involves network dysfunction, and further stress the importance of communication between auditory–sensory and fronto‐striatal circuits in tinnitus pathophysiology. Hum Brain Mapp 37:2717–2735, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc .     

Disrupted thalamocortical connectivity in PSP: a resting-state fMRI, DTI, and VBM study

Progressive supranuclear palsy (PSP) is associated with pathological changes along the dentatorubrothalamic tract and in premotor cortex. We aimed to assess whether functional neural connectivity is disrupted along this pathway in PSP, and to determine how functional changes relate to changes in structure and diffusion. Eighteen probable PSP subjects and 18 controls had resting-state (task-free) fMRI, diffusion tensor imaging and structural MRI. Functional connectivity was assessed between thalamus and the rest of the brain, and within the basal ganglia, salience and default mode networks (DMN). Patterns of atrophy were assessed using voxel-based morphometry, and patterns of white matter tract degeneration were assessed using tract-based spatial statistics. Reduced in-phase functional connectivity was observed between the thalamus and premotor cortex including supplemental motor area (SMA), striatum, thalamus and cerebellum in PSP. Reduced connectivity in premotor cortex, striatum and thalamus were observed in the basal ganglia network and DMN, with subcortical salience network reductions. Tract degeneration was observed between cerebellum and thalamus and in superior longitudinal fasciculus, with grey matter loss in frontal lobe, premotor cortex, SMA and caudate nucleus. SMA functional connectivity correlated with SMA volume and measures of cognitive and motor dysfunction, while thalamic connectivity correlated with degeneration of superior cerebellar peduncles. PSP is therefore associated with disrupted thalamocortical connectivity that is associated with degeneration of the dentatorubrothalamic tract and the presence of cortical atrophy.     

Oscillations,networks, and their development: MEG connectivity changes with age

Magnetoencephalographic (MEG) investigations of inter‐regional amplitude correlations have yielded new insights into the organization and neurophysiology of resting‐state networks (RSNs) first identified using fMRI. Inter‐regional MEG amplitude correlations in adult RSNs have been shown to be most prominent in alpha and beta frequency ranges and to express strong congruence with RSN topologies found using fMRI. Despite such advances, little is known about how oscillatory connectivity in RSNs develops throughout childhood and adolescence. This study used a novel fMRI‐guided MEG approach to investigate the maturation of resting‐state amplitude correlations in physiologically relevant frequency ranges within and among six RSNs in 59 participants, aged 6–34 years. We report age‐related increases in inter‐regional amplitude correlations that were largest in alpha and beta frequency bands. In contrast to fMRI reports, these changes were observed both within and between the various RSNs analyzed. Our results provide the first evidence of developmental changes in spontaneous neurophysiological connectivity in source‐resolved RSNs, which indicate increasing integration within and among intrinsic functional brain networks throughout childhood, adolescence, and early adulthood. Hum Brain Mapp 35:5249–5261, 2014. © 2014 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.     

Functional segmentation of the brain cortex using high model order group PICA

Baseline activity of resting state brain networks (RSN) in a resting subject has become one of the fastest growing research topics in neuroimaging. It has been shown that up to 12 RSNs can be differentiated using an independent component analysis (ICA) of the blood oxygen level dependent (BOLD) resting state data. In this study, we investigate how many RSN signal sources can be separated from the entire brain cortex using high dimension ICA analysis from a group dataset. Group data from 55 subjects was analyzed using temporal concatenation and a probabilistic independent component analysis algorithm. ICA repeatability testing verified that 60 of the 70 computed components were robustly detectable. Forty‐two independent signal sources were identifiable as RSN, and 28 were related to artifacts or other noninterest sources (non‐RSN). The depicted RSNs bore a closer match to functional neuroanatomy than the previously reported RSN components. The non‐RSN sources have significantly lower temporal intersource connectivity than the RSN (P < 0.0003). We conclude that the high model order ICA of the group BOLD data enables functional segmentation of the brain cortex. The method enables new approaches to causality and connectivity analysis with more specific anatomical details. Hum Brain Mapp, 2009. © 2009 Wiley‐Liss, Inc.     

Altered resting‐state connectivity during interictal generalized spike‐wave discharges in drug‐naïve childhood absence epilepsy

Purpose: To investigate the intrinsic brain connections at the time of interictal generalized spike‐wave discharges (GSWDs) to understand their mechanism of effect on brain function in untreated childhood absence epilepsy (CAE). Methods: The EEG‐functional MRI (fMRI) was used to measure the resting state functional connectivity during interictal GSWDs in drug‐naïve CAE, and three different brain networks—the default mode network (DMN), cognitive control network (CCN), and affective network (AN)—were investigated. Results: Cross‐correlation functional connectivity analysis with priori seed revealed decreased functional connectivity within each of these three networks in the CAE patients during interictal GSWDS. It included precuneus‐dorsolateral prefrontal cortex (DLPFC), dorsomedial prefrontal cortex (DMPFC), and inferior parietal lobule in the DMN; DLPFC‐inferior frontal junction (IFJ), and pre‐supplementary motor area (pre‐SMA) subregions connectivity disruption in CCN; ACC‐ventrolateral prefrontal cortex (VLPFC) and DMPFC in AN; There were also some regions, primarily the parahippcampus, paracentral in AN, and the left frontal mid orb in the CCN, which showed increased connectivity. Conclusions: The current findings demonstrate significant alterations of resting‐state networks in drug naïve CAE subjects during interictal GSWDs and interictal GSWDs can cause dysfunction in specific networks important for psychosocial function. Impairment of these networks may cause deficits both during and between seizures. Our study may contribute to the understanding of neuro‐pathophysiological mechanism of psychosocial function impairments in patients with CAE. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.     

Dynamic changes of ICA‐derived EEG functional connectivity in the resting state

An emerging issue in neuroscience is how to identify baseline state(s) and accompanying networks termed “resting state networks” (RSNs). Although independent component analysis (ICA) in fMRI studies has elucidated synchronous spatiotemporal patterns during cognitive tasks, less is known about the changes in EEG functional connectivity between eyes closed (EC) and eyes open (EO) states, two traditionally used baseline indices. Here we investigated healthy subjects (n = 27) in EC and EO employing a four‐step analytic approach to the EEG: (1) group ICA to extract independent components (ICs), (2) standardized low‐resolution tomography analysis (sLORETA) for cortical source localization of IC network nodes, followed by (3) graph theory for functional connectivity estimation of epochwise IC band‐power, and (4) circumscribing IC similarity measures via hierarchical cluster analysis and multidimensional scaling (MDS). Our proof‐of‐concept results on alpha‐band power demonstrate five statistically clustered groups with frontal, central, parietal, occipitotemporal, and occipital sources. Importantly, during EO compared with EC, graph analyses revealed two salient functional networks with frontoparietal connectivity: a more medial network with nodes in the mPFC/precuneus which overlaps with the “default‐mode network” (DMN), and a more lateralized network comprising the middle frontal gyrus and inferior parietal lobule, coinciding with the “dorsal attention network” (DAN). Furthermore, a separate MDS analysis of ICs supported the emergence of a pattern of increased proximity (shared information) between frontal and parietal clusters specifically for the EO state. We propose that the disclosed component groups and their source‐derived EEG functional connectivity maps may be a valuable method for elucidating direct neuronal (electrophysiological) RSNs in healthy people and those suffering from brain disorders. Hum Brain Mapp, 2013. © 2012 Wiley Periodicals, Inc.     

Aberrant connectivity of lateral prefrontal networks in presymptomatic Huntington's disease

In clinically presymptomatic individuals with the Huntington's disease (HD) gene mutation, functional neuroimaging data have suggested a dysfunction of multiple cortical and subcortical regions including the prefrontal and parietal cortex, as well as the striatum. Although it has been hypothesized that these activation differences most likely reflect aberrant corticostriatal circuits, the functional coupling of neural networks associated with cognitive performance has not been investigated so far. In this study, we used functional magnetic resonance imaging (fMRI) and multivariate analytic techniques to investigate memory-related patterns of functional connectivity in healthy controls (n = 16) and pre-HD individuals (n = 16). Independent component analyses (ICA) revealed distinct bilateral frontostriatal and frontoparietal networks that were activated during a verbal working memory paradigm in both healthy controls and pre-HD subjects. Compared with healthy controls, pre-HD individuals exhibited lower functional connectivity in left lateral prefrontal and parietal regions as well as in the bilateral putamen. Functional connectivity indices in the left putamen were negatively correlated with the CAG repeat size and the UHDRS behavioral score, and positively correlated with the predicted years to manifest symptom onset. The connectivity of the right putamen was negatively correlated with the UHDRS motor score. In pre-HD individuals, these results suggest an early frontostriatal and frontoparietal deficit of dissociable functional networks associated with executive processing.     

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.     

Functional centrality of amygdala,striatum and hypothalamus in a “small‐world” network underlying joy: An fMRI study with music

Current knowledge about small‐world networks underlying emotions is sparse, and confined to functional magnetic resonance imaging (fMRI) studies using resting‐state paradigms. This fMRI study applied Eigenvector Centrality Mapping (ECM) and functional connectivity analysis to reveal neural small‐world networks underlying joy and fear. Joy and fear were evoked using music, presented in 4‐min blocks. Results show that the superficial amygdala (SF), laterobasal amygdala (LB), striatum, and hypothalamus function as computational hubs during joy. Out of these computational hubs, the amygdala nuclei showed the highest centrality values. The SF showed functional connectivity during joy with the mediodorsal thalamus (MD) and nucleus accumbens (Nac), suggesting that SF, MD, and Nac modulate approach behavior in response to positive social signals such as joyful music. The striatum was functionally connected during joy with the LB, as well as with premotor cortex, areas 1 and 7a, hippocampus, insula and cingulate cortex, showing that sensorimotor, attentional, and emotional processes converge in the striatum during music perception. The hypothalamus showed functional connectivity during joy with hippocampus and MD, suggesting that hypothalamic endocrine activity is modulated by hippocampal and thalamic activity during sustained periods of music‐evoked emotion. Our study indicates high centrality of the amygdala nuclei groups within a functional network underlying joy, suggesting that these nuclei play a central role for the modulation of emotion‐specific activity within this network. Hum Brain Mapp 35:3485–3498, 2014. © 2013 Wiley Periodicals, Inc .     

From “rest” to language task: Task activation selects and prunes from broader resting‐state network

Resting‐state networks (RSNs) show spatial patterns generally consistent with networks revealed during cognitive tasks. However, the exact degree of overlap between these networks has not been clearly quantified. Such an investigation shows promise for decoding altered functional connectivity (FC) related to abnormal language functioning in clinical populations such as temporal lobe epilepsy (TLE). In this context, we investigated the network configurations during a language task and during resting state using FC. Twenty‐four healthy controls, 24 right and 24 left TLE patients completed a verb generation (VG) task and a resting‐state fMRI scan. We compared the language network revealed by the VG task with three FC‐based networks (seeding the left inferior frontal cortex (IFC)/Broca): two from the task (ON, OFF blocks) and one from the resting state. We found that, for both left TLE patients and controls, the RSN recruited regions bilaterally, whereas both VG‐on and VG‐off conditions produced more left‐lateralized FC networks, matching more closely with the activated language network. TLE brings with it variability in both task‐dependent and task‐independent networks, reflective of atypical language organization. Overall, our findings suggest that our RSN captured bilateral activity, reflecting a set of prepotent language regions. We propose that this relationship can be best understood by the notion of pruning or winnowing down of the larger language‐ready RSN to carry out specific task demands. Our data suggest that multiple types of network analyses may be needed to decode the association between language deficits and the underlying functional mechanisms altered by disease. Hum Brain Mapp 38:2540–2552, 2017. © 2017 Wiley Periodicals, Inc.     

Sex differences in normal age trajectories of functional brain networks

Resting‐state functional magnetic resonance image (rs‐fMRI) is increasingly used to study functional brain networks. Nevertheless, variability in these networks due to factors such as sex and aging is not fully understood. This study explored sex differences in normal age trajectories of resting‐state networks (RSNs) using a novel voxel‐wise measure of functional connectivity, the intrinsic connectivity distribution (ICD). Males and females showed differential patterns of changing connectivity in large‐scale RSNs during normal aging from early adulthood to late middle‐age. In some networks, such as the default‐mode network, males and females both showed decreases in connectivity with age, albeit at different rates. In other networks, such as the fronto‐parietal network, males and females showed divergent connectivity trajectories with age. Main effects of sex and age were found in many of the same regions showing sex‐related differences in aging. Finally, these sex differences in aging trajectories were robust to choice of preprocessing strategy, such as global signal regression. Our findings resolve some discrepancies in the literature, especially with respect to the trajectory of connectivity in the default mode, which can be explained by our observed interactions between sex and aging. Overall, results indicate that RSNs show different aging trajectories for males and females. Characterizing effects of sex and age on RSNs are critical first steps in understanding the functional organization of the human brain. Hum Brain Mapp 36:1524–1535, 2015. © 2014 Wiley Periodicals, Inc.     

l‐Dopa responsiveness is associated with distinctive connectivity patterns in advanced Parkinson's disease

Background : Neuronal loss and dopamine depletion alter motor signal processing between cortical motor areas, basal ganglia, and the thalamus, resulting in the motor manifestations of Parkinson's disease. Dopamine replacement therapy can reverse these manifestations with varying degrees of improvement. Methods : To evaluate functional connectivity in patients with advanced Parkinson's disease and changes in functional connectivity in relation to the degree of response to l ‐dopa, 19 patients with advanced Parkinson's disease underwent resting‐state functional magnetic resonance imaging in the on‐medication state. Scans were obtained on a 3‐Tesla scanner in 3 × 3 × 2.5 mm³ voxels. Seed‐based bivariate regression analyses were carried out with atlas‐defined basal ganglia regions as seeds, to explore relationships between functional connectivity and improvement in the motor section of the UPDRS‐III following an l ‐dopa challenge. False discovery rate‐corrected P was set at < 0.05 for a 2‐tailed t test. Results : A greater improvement in UPDRS‐III scores following l ‐dopa administration was characterized by higher resting‐state functional connectivity between the prefrontal cortex and the striatum (P = 0.001) and lower resting‐state functional connectivity between the pallidum (P = 0.001), subthalamic nucleus (P = 0.003), and the paracentral lobule (supplementary motor area, mesial primary motor, and primary sensory areas). Conclusions : Our findings show characteristic basal ganglia resting‐state functional connectivity patterns associated with different degrees of l‐ dopa responsiveness in patients with advanced Parkinson's disease. l‐ Dopa exerts a graduated influence on remapping connectivity in distinct motor control networks, potentially explaining some of the variance in treatment response. © 2017 International Parkinson and Movement Disorder Society     

Altered intra‐ and inter‐network functional coupling of resting‐state networks associated with motor dysfunction in stroke

Motor functions are supported through functional integration across the extended motor system network. Individuals following stroke often show deficits on motor performance requiring coordination of multiple brain networks; however, the assessment of connectivity patterns after stroke was still unclear. This study aimed to investigate the changes in intra‐ and inter‐network functional connectivity (FC) of multiple networks following stroke and further correlate FC with motor performance. Thirty‐three left subcortical chronic stroke patients and 34 healthy controls underwent resting‐state functional magnetic resonance imaging. Eleven resting‐state networks were identified via independent component analysis (ICA). Compared with healthy controls, the stroke group showed abnormal FC within the motor network (MN), visual network (VN), dorsal attention network (DAN), and executive control network (ECN). Additionally, the FC values of the ipsilesional inferior parietal lobule (IPL) within the ECN were negatively correlated with the Fugl‐Meyer Assessment (FMA) scores (hand + wrist). With respect to inter‐network interactions, the ipsilesional frontoparietal network (FPN) decreased FC with the MN and DAN; the contralesional FPN decreased FC with the ECN, but it increased FC with the default mode network (DMN); and the posterior DMN decreased FC with the VN. In sum, this study demonstrated the coexistence of intra‐ and inter‐network alterations associated with motor‐visual attention and high‐order cognitive control function in chronic stroke, which might provide insights into brain network plasticity following stroke.