Neuroimaging evidence suggests that executive functions (EF) depend on brain regions that are not closely tied to specific cognitive demands but rather to a wide range of behaviors. A multiple-demand ...(MD) system has been proposed, consisting of regions showing conjoint activation across multiple demands. Additionally, a number of studies defining networks specific to certain cognitive tasks suggest that the MD system may be composed of a number of sub-networks each subserving specific roles within the system. We here provide a robust definition of an extended MDN (eMDN) based on task-dependent and task-independent functional connectivity analyses seeded from regions previously shown to be convergently recruited across neuroimaging studies probing working memory, attention and inhibition, i.e., the proposed key components of EF. Additionally, we investigated potential sub-networks within the eMDN based on their connectional and functional similarities. We propose an eMDN network consisting of a core whose integrity should be crucial to performance of most operations that are considered higher cognitive or EF. This then recruits additional areas depending on specific demands.
•A neurobiological substrate for executive processes is proposed.•Proposed network consists of a core, crucial to performance of executive functions.•Core network in turn recruits other brain regions depending on specific demands.•Hierarchical clustering grouped regions into three cliques each with specific roles.
Although characteristic motor symptoms of Parkinson's disease such as bradykinesia typically improve under dopaminergic medication, deficits in higher motor control are less responsive. We here ...investigated the dopaminergic modulation of network dynamics underlying basic motor performance, i.e. finger tapping, and higher motor control, i.e. internally and externally cued movement preparation and selection. Twelve patients, assessed ON and OFF medication, and 12 age-matched healthy subjects underwent functional magnetic resonance imaging. Dynamic causal modelling was used to assess effective connectivity in a motor network comprising cortical and subcortical regions. In particular, we investigated whether impairments in basic and higher motor control, and the effects induced by dopaminergic treatment are due to connectivity changes in (i) the mesial premotor loop comprising the supplementary motor area; (ii) the lateral premotor loop comprising lateral premotor cortex; and (iii) cortico-subcortical interactions. At the behavioural level, we observed a marked slowing of movement preparation and selection when patients were internally as opposed to externally cued. Preserved performance during external cueing was associated with enhanced connectivity between prefrontal cortex and lateral premotor cortex OFF medication, compatible with a context-dependent compensatory role of the lateral premotor loop in the hypodopaminergic state. Dopaminergic medication significantly improved finger tapping speed in patients, which correlated with a drug-induced coupling increase of prefrontal cortex with the supplementary motor area, i.e. the mesial premotor loop. In addition, only in the finger tapping condition, patients ON medication showed enhanced excitatory influences exerted by cortical premotor regions and the thalamus upon the putamen. In conclusion, the amelioration of bradykinesia by dopaminergic medication seems to be driven by enhanced connectivity within the mesial premotor loop and cortico-striatal interactions. In contrast, medication did not improve internal motor control deficits concurrent to missing effects at the connectivity level. This differential effect of dopaminergic medication on the network dynamics underlying motor control provides new insights into the clinical finding that in Parkinson's disease dopaminergic drugs especially impact on bradykinesia but less on executive functions.
Older individuals typically display stronger regional brain activity than younger subjects during motor performance. However, knowledge regarding age-related changes of motor network interactions ...between brain regions remains scarce. We here investigated the impact of ageing on the interaction of cortical areas during movement selection and initiation using dynamic causal modelling (DCM). We found that age-related psychomotor slowing was accompanied by increases in both regional activity and effective connectivity, especially for ‘core’ motor coupling targeting primary motor cortex (M1). Interestingly, younger participants within the older group showed strongest connectivity targeting M1, which steadily decreased with advancing age. Conversely, prefrontal influences on the motor system increased with advancing age, and were inversely correlated with reduced parietal influences and core motor coupling. Interestingly, higher net coupling within the prefrontal-premotor-M1 axis predicted faster psychomotor speed in ageing. Hence, as opposed to a uniform age-related decline, our findings are compatible with the idea of different age-related compensatory mechanisms, with an important role of the prefrontal cortex compensating for reduced coupling within the core motor network.
•Enhanced motor network activity and connectivity in ageing•Parietal-premotor and premotor-M1 coupling decreases with advancing age.•Prefrontal influences on the motor system increase with advancing age.•Prefrontal cortex compensates for age-related decline in other motor connections.•Prefrontal-premotor-M1 coupling predicts psychomotor speed in ageing.
Schizophrenia and depression are prevalent psychiatric disorders, but their underlying neural bases remains poorly understood. Neuroimaging evidence has pointed towards the relevance of functional ...connectivity aberrations in default mode network (DMN) hubs, dorso-medial prefrontal cortex and precuneus, in both disorders, but commonalities and differences in resting state functional connectivity of those two regions across disorders has not been formally assessed. Here, we took a transdiagnostic approach to investigate resting state functional connectivity of those two regions in 75 patients with schizophrenia and 82 controls from 4 scanning sites and 102 patients with depression and 106 controls from 3 sites. Our results demonstrate common dysconnectivity patterns as indexed by a significant reduction of functional connectivity between precuneus and bilateral superior parietal lobe in schizophrenia and depression. Furthermore, our findings highlight diagnosis-specific connectivity reductions of the parietal operculum in schizophrenia relative to depression. In light of evidence that points towards the importance of the DMN for social cognitive abilities and well documented impairments of social interaction in both patient groups, it is conceivable that the observed transdiagnostic connectivity alterations may contribute to interpersonal difficulties, but this could not be assessed directly in our study as measures of social behavior were not available. Given the operculum's role in somatosensory integration, diagnosis-specific connectivity reductions may indicate a pathophysiological mechanism for basic self-disturbances that is characteristic of schizophrenia, but not depression.
Healthy aging is accompanied by a decrease in cognitive and motor capacities. In a network associated with movement initiation, we investigated age-related changes of functional connectivity (FC) as ...well as regional atrophy in a sample of 232 healthy subjects (age range 18–85 years). To this end, voxel-based morphometry and whole-brain resting-state FC were analyzed for the supplementary motor area (SMA), anterior midcingulate cortex (aMCC) and bilateral striatum (Str). To assess the specificity of age-related effects, bilateral primary sensorimotor cortex (S1/M1) closely associated with motor execution was used as control seeds. All regions showed strong reduction of gray matter volume with age. Corrected for this regional atrophy, the FC analysis revealed an age × seed interaction for each of the bilateral Str nodes against S1/M1 with consistent age-related decrease in FC with bilateral caudate nucleus and anterior putamen. Specific age-dependent FC decline of SMA was found in bilateral central insula and the adjacent frontal operculum. aMCC showed exclusive age-related decoupling from the anterior cingulate motor area. The present study demonstrates network as well as node-specific age-dependent FC decline of the SMA and aMCC to highly integrative cortical areas involved in cognitive motor control. FC decrease in addition to gray matter atrophy within the Str may provide a substrate for the declining motor control in elderly. Finally, age-related FC changes in both the network for movement initiation as well as the network for motor execution are not explained by regional atrophy in the healthy aging brain.
Introduction Visual motion processing on one hand and ocular motor functions on the other are rarely studied together in vivo in humans. The interrelation of these functional networks is rather ...unclear, even though their functional dependence seems obvious. In several fMRI studies the essential nodes of both networks could be localized using voluntary optokinetic (’look’) nystagmus (OKN) in the horizontal plane incorporating visual motion tracking ( Dieterich et al., 2009 ). Here, functional connectivity (FC) between these nodes representing both networks was studies using resting-state FC. Methods Resting-state fMRI data of 200 healthy adults (age 44.1 ± 17.9; 79 male) were included in the cross correlation analysis of 9 bilateral nodes including frontal (FEF), supplementary (SEF), cingulate (CEF) and parietal eye fields (PEF), V5 and V6, as well as the superior colliculus (SupCol), the lateral geniculate body (CGL) and the globus pallidus (GlobPal). The necessary ROIs were obtained in a separate OKN fmri experiment with 21 healthy subjects. After spatial preprocessing and confound removal using 24 motion regression and mean signal within white matter and cerebral spinal fluid and band-pass filtering (0.01–0.08 Hz), each ROI was represented by the first eigenvariate of the respective voxels’ time-series. For each node pair partial correlations were computed within subjects and Fisher Z transformed for one group t -tests corrected for the influence of age and gender resulting in an 18 × 18 cross correlation matrix. Subsequently, hierarchical cluster analysis was applied to analyze sub-clustering within the overall network. Results The analysis showed consistent FC between each regions respective homotopical partner. Hierarchical clustering revealed an overall split between one cluster comprising SEF, FEF, CEF and GlobPal and a second including CGL, SubCol, V6 as well as PEF and V5. Conclusion This new approach revealed an observer- and task-indepedent separation of the cortical eye fields into two main groups either responsible for voluntary ocular motor control (SEF, FEF, CEF, and GlobPal) or involved in visual motion target tracking streams (CGL, SupCol, PEF, V5, and V6). The further subgrouping of PEF and V5 together with area V6 representing an isolated cluster within the second group seem to reflect their order and importance along the dorsal visual stream known from lesion studies ( Pierrot-Deseilligny et al., 2004 ). The other subgroup of CGL and SupCol may represent the early nodes of the network involved in voluntary and reflexive ocular motor control. In sum, these neuroscientifically sound network findings for visual motion and ocular motor control derived from task-free data give a promising outlook for the novel concept of hierarchical clustering ( Figs. 1 and 2 ).
Key nodes of neural networks for ocular motor control and visual motion processing have been localized using saccades, smooth pursuit, and optokinetic nystagmus (OKN). Within the context of an ...independent fMRI study using OKN, 9 bilateral network nodes were localized comprising cortical eye fields in frontal (FEF), supplementary motor (SEF), cingulate (CEF) and parietal cortex (PEF), visual motion centers MT+ and V6, the superior colliculus (SC), the lateral geniculate nucleus (LGN) and the globus pallidus (GP). Here, we examined the network’s functional hierarchy as present in the structural co-variation (SCoV) and resting-state (RS) fMRI, and the effect of RS condition (eyes open/closed) on its’ functional connectivity (FC). Two publicly available samples were analyzed consisting of the enhanced NKI sample with RS (TR 1.4s) and structural MR data ( n = 124; age 46.7 ± 17.6; 40 male) and the “Beijing: eyes open eyes closed sample” measuring RS (TR 2s; n = 48; age 22.5 ± 2.2; 24 male). For the FC analysis, ICA-based denoising (FSL) was applied before spatial preprocessing (SPM) and band-pass filtering. Each bilateral ROI was represented by the first eigenvariate of the respective voxels’ time-series and partial correlation were computed using FSLNets. One group t-tests were computed over Fisher’s z transformed correlation coefficients. Each ROIs volume was approximated with voxel-based morphometry (VBM8) using non-linearly modulated gray matter density and partial correlations were computed for SCoV. Hierarchical cluster analysis was applied to determine sub-clustering within the OKN network. Edge-wise comparisons between RS conditions were performed using permutation testing and Bonferroni correction. Both FC and SCoV revealed two major subcluster. MT+ and V6 were similar to LGN and SC. The cortical eye fields clustered together with the GP. As effect of RS condition, with eyes closed the CEF switched to the visual subcluster. The edge-wise comparison revealed generally higher FC with eyes open and in particular a decrease of FC between MT+ and PEF, FEF and SEF as well as between V6 and SEF. Hierarchical clustering based on RS and structural data revealed a task-independent sub-division of the network for ocular-motor control and visual motion processing into two streams either involved in top-down (efferent voluntary) ocular-motor control (FEF, PEF, SEF, GP) and in more bottom-up visual target tracking (MT+, V6, LGN, SC) streams. This general network hierarchy was equally present in the RS with eyes open and eyes closed, with the CEF fulfilling a condition specific role in the network. The edge-wise comparison between RS conditions strengthens the evidence for a specific influence of MT+ on the ocular-motor control subcluster. These findings indicate a systematic influence of the resting condition not only on FC of the visual system, but on the state of the whole OKN network, while a general system hierarchy is omnipresent independent of RS condition.
Functional magnetic resonance imaging (fMRI) plays a vital role in understanding normal and clinical brain function and relies on detecting changes in blood oxygenation (i.e., BOLD). Synchronized ...signal fluctuations can be observed even when the subject is at rest, i.e., without performing any task. Therefore, analyzing resting-state data has become one way of studying ongoing brain activity and interrelation of brain regions. Apparent brain activity can be influenced by unwanted signals including system noise, thermal noise and noise induced by non-neuronal physiological processes. The latter induced noise is mostly the unwanted noise that affects the BOLD signal. Globally influencing nuisance regressors are derived from either whole brain or specific tissues types and removed from the main signal ( Behzadi et al., 2007; Murphy et al., 2009 ). Removal of various global nuisance regressors alters the variance of the residual signal. Functional connectivity (FC) in general measures, how well different regions in the brain relate to each other. It estimates the common variance of the signal fluctuations within these regions by linear correlation. In this study, we tested the reliability of FC after removing confounding noise regressors. Here we focused on the effects of various commonly used confound removals in the resting state studies, such as PCA de-noising, global mean signal regression including white matter (WM) and CSF mean signal regression, tissue signal regression (Grey matter (GM), WM and CSF). Additionally, we examined GM specific time series extraction from seed regions. We conducted a seed based FC analysis on 42 subjects scanned twice with an interval of 100–250 day and tested the reliability between scans. In order to compute the seed based functional connectivity, a priori defined networks were analyzed (extended socioaffective default mode network and the working-memory network). Both these networks show robust within network resting state connectivity, as well as anti-correlation between each other. The reliability of functional connectivity is measured using two different measures i.e., by computing the spearman correlations and the absolute differences of the functional connectivity scores. Our results ( Fig. 1 ) showed that GM masking of the seed regions based on the group-average GM probabilities is advisable. Also, PCA de-noising reduces the reliability of connectivity estimates. Finally, with respect to global signal regression, we observed that refraining from this approach enhances test-retest reliability but comes at the expense of potentially poorer biological validity, indicated by missing anti-correlations between what has been previously described as antagonistic networks. Here removal of global WM and CSF signals seems to provide a good compromise, as this approach yielded reliable and meaningful estimates of within and between-network connections. Importantly, reliability showed correlation with the retained variance, presumably including structured noise. Consequently, noise removal from fMRI data requires a compromise between maximizing the test-retest reliability and removing variance that may be attributable to non-neuronal sources.
Emotion regulation (ER) and action regulation (AR) have been shown to rely on two broad networks ( Langner et al., 2014 ). While ER and AR networks (ERN/ARN) are mostly distinct from each other, ...there are also overlapping regions supporting a common underlying cognitive control mechanism. Several studies in schizophrenic patients (SZ) provide evidence for deficits in ER and AR ( van der Meer et al., 2014; Minzenberg et al., 2009 ). Given these dysfunctions, we examined functional connectivity (FC) aberrations within these networks in SZ and associations with behavior. We used data from 60 SZ and 51 healthy controls (HC) obtained from the COBRE study ( COBRE ). ER ability was assessed with MSCEIT™ (Managing Emotions) questionnaire. AR was assessed using the following tasks: simple and complex working memory span, identical-pairs continuous performance task (CPT-IP). Resting-state fMRI data were preprocessed and de-noised ( COBRE ; Salimi-Khorshidi et al., 2014 ). For both ERN and ARN, FC between each pair of network nodes was determined by intercorrelating the eigenvariate of each seed region’s BOLD time series. Confounds of age, gender and movement were removed as were outliers in behavioural measures and FC. For each network, permutation tests were used to test for group differences in FC between all those nodes whose connectivity was of at least medium effect size ( r ⩾ .24) in either or both groups. Pearson correlation analyses were performed to investigate whether ER abilities and behavioral measures of AR were associated with FC between ERN and ARN nodes, respectively. Results revealed significantly reduced scores in SZ (vs. HC) for ER and AR abilities. FC analysis showed several significant (FWE-corrected) group differences (SZ vs. HC) for both networks: For the ERN, FC between left amygdala (lAmy) and posteromedial prefrontal cortex (pmPFC) as well as lAmy and left Inferior frontal gyrus was decreased in SZ. For the ARN, FC of left dorsolateral prefrontal cortex (lDLPFC) with left inferior temporal gyrus (lITG), right intraparietal sulcus, right dorsal premotor cortex (rPMd), of left insula with right temporo-parietal junction (rTPJ) and rPMd, as well as of right insula with rTPJ was decreased in SZ. Furthermore, FC between lAmy and pmPFC in the ERN as well as lDLPFC and lITG in the ARN was positively correlated with CPT-IP scores. Our results indicate hypoconnectivities within the ERN and ARN in SZ and associations of attention with FC in both networks. In particular, the FC of the ARN’s lDLPFC node appears to play a major role in SZ. This could indicate a disturbance of neural mechanisms of top-down modulation, required for appropriate AR. Hypoconnectivity between lAmy and frontal regions within the ERN suggests aberrant cognitive control processes in ER, in line with previous research ( van der Meer et al., 2014 ). The positive correlation of CPT-IP performance with FC between lAmy and pmPFC within the ERN and with FC between lDLPFC and lITG within the ARN, suggests that successfully sustaining attention may depend on the efficient cognitive control of both emotion and action.
Introduction Healthy elderly adults typically show greater regional activity in frontoparietal brain regions relative to young adults when performing motor control tasks ( Ward and Frackowiak, 2003; ...Vallesi et al., 2011 ). However, the functional role of enhanced activity within the motor network is still a matter of debate. One hypothesis is that higher levels of neural activity reflect a compensatory mechanism to account for age-related decline in neural networks. We, therefore, used a systems-level approach to investigate networks dynamics underlying motor control in young and elderly subjects. We hypothesized that advanced aging is associated with reduced connectivity in the basic motor network, which is compensated by stronger influence of non-primary motor areas like prefrontal cortex. Methods We scanned 12 young (age 22–33) and 12 elderly subjects (age 52–74) employing a computerized task involving both basic (finger tapping) and higher motor control processing (internally and externally cued movement selection and initiation). Dynamic Causal Modelling (DCM) for fMRI was used to assess effective connectivity in a bilateral frontoparietal network comprising dorsolateral prefrontal cortex, dorsal premotor cortex, intraparietal cortex and primary motor cortex. Results Elderly subjects showed a significant slowing in movement selection and initiation. This slowing was accompanied by increases in both regional brain activity and effective connectivity between frontoparietal brain regions in elderly compared to young subjects. However, within the group of elderly subjects, coupling strengths of premotor cortex with primary motor cortex and intraparietal cortex decreased with advancing age, whereas connectivity between prefrontal and premotor cortex increased as a function of age. Discussion Network interactions underlying visuomotor transformation (parietal-premotor) and motor execution (premotor-primary motor cortex) follow an U-curve relationship: Connectivity is generally elevated in old relative to young subjects, yet decreases with advanced aging. In contrast, prefrontal influences on premotor cortex increase with advanced aging. These findings are in line with the ”posterior to anterior shift theory” described for regional brain activity, thereby extending it to network interactions related to higher motor control ( Davis et al., 2008 ).
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