Aberrant functional network connectivity in psychopathy from a large (N = 985) forensic sample

Psychopathy is a personality disorder characterized by antisocial behavior, lack of remorse and empathy, and impaired decision making. The disproportionate amount of crime committed by psychopaths has severe emotional and economic impacts on society. Here we examine the neural correlates associated with psychopathy to improve early assessment and perhaps inform treatments for this condition. Previous resting‐state functional magnetic resonance imaging (fMRI) studies in psychopathy have primarily focused on regions of interest. This study examines whole‐brain functional connectivity and its association to psychopathic traits. Psychopathy was hypothesized to be characterized by aberrant functional network connectivity (FNC) in several limbic/paralimbic networks. Group‐independent component and regression analyses were applied to a data set of resting‐state fMRI from 985 incarcerated adult males. We identified resting‐state networks (RSNs), estimated FNC between RSNs, and tested their association to psychopathy factors and total summary scores (Factor 1, interpersonal/affective; Factor 2, lifestyle/antisocial). Factor 1 scores showed both increased and reduced functional connectivity between RSNs from seven brain domains (sensorimotor, cerebellar, visual, salience, default mode, executive control, and attentional). Consistent with hypotheses, RSNs from the paralimbic system—insula, anterior and posterior cingulate cortex, amygdala, orbital frontal cortex, and superior temporal gyrus—were related to Factor 1 scores. No significant FNC associations were found with Factor 2 and total PCL‐R scores. In summary, results suggest that the affective and interpersonal symptoms of psychopathy (Factor 1) are associated with aberrant connectivity in multiple brain networks, including paralimbic regions.     

Large‐scale functional brain network changes in taxi drivers: Evidence from resting‐state fMRI

Driving a car in the environment is a complex behavior that involves cognitive processing of visual information to generate the proper motor outputs and action controls. Previous neuroimaging studies have used virtual simulation to identify the brain areas that are associated with various driving‐related tasks. Few studies, however, have focused on the specific patterns of functional organization in the driver's brain. The aim of this study was to assess differences in the resting‐state networks (RSNs) of the brains of drivers and nondrivers. Forty healthy subjects (20 licensed taxi drivers, 20 nondrivers) underwent an 8‐min resting‐state functional MRI acquisition. Using independent component analysis, three sensory (primary and extrastriate visual, sensorimotor) RSNs and four cognitive (anterior and posterior default mode, left and right frontoparietal) RSNs were retrieved from the data. We then examined the group differences in the intrinsic brain activity of each RSN and in the functional network connectivity (FNC) between the RSNs. We found that the drivers had reduced intrinsic brain activity in the visual RSNs and reduced FNC between the sensory RSNs compared with the nondrivers. The major finding of this study, however, was that the FNC between the cognitive and sensory RSNs became more positively or less negatively correlated in the drivers relative to that in the nondrivers. Notably, the strength of the FNC between the left frontoparietal and primary visual RSNs was positively correlated with the number of taxi‐driving years. Our findings may provide new insight into how the brain supports driving behavior. Hum Brain Mapp 36:862–871, 2015. © 2014 Wiley Periodicals, Inc.     

The organization of intrinsic brain activity differs between genders: A resting‐state fMRI study in a large cohort of young healthy subjects

Objectives: To investigate, using resting state (RS) functional MRI (fMRI), gender‐related differences of functional connectivity (FC) and functional network connectivity (FNC) of the human brain. Experimental design: One‐hundred and four young healthy subjects (48/56 men/women), aged between 20 and 29 years, underwent a 10‐min RS fMRI acquisition. Independent component analysis (ICA) and statistical parametric mapping were used to assess gender‐related differences in RSNs, with and without correction for regional gray matter (GM) volume. The relationships among all RSNs was also assessed using a FNC method. Principal observations: For all networks, significant between‐group differences of RS activity were found. Between‐group comparisons of RSNs changed when adjusting for GM volume, as follows: (1) there was only marginal effect on the analysis of sensory (i.e., sensorimotor, visual, and auditory) networks; and (2) there was a significantly increased difference when cognitive networks (apart from one related to attention) were considered. Compared with women, men experienced increased FC in parietal and occipital regions in most RSNs, whereas women experienced a higher RS FC in frontal and temporal regions, and in the cerebellum. When compared to women, increased FNC was found in men between several cognitive and sensory networks, whereas women showed an increased FNC only between attention and right working‐memory networks. Conclusions: The organization of intrinsic FC and FNC differ between genders. The detected differences could contribute to the understanding of the known between‐gender variation in task‐related recruitments, and the patterns of abnormalities detected in neurologic and psychiatric diseases with a gender prevalence. Hum Brain Mapp, 2013. © 2012 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.     

Altered resting‐state network connectivity in congenital blind

The brain of congenital blind (CB) has experienced a series of structural and functional alterations, either undesirable outcomes such as atrophy of the visual pathway due to sight loss from birth, or compensatory plasticity to interact efficiently with the environment. However, little is known, so far, about alterations in the functional architecture of resting‐state networks (RSNs) in CB. This study aimed to investigate intra‐ and internetwork connectivity differences between CB and sighted controls (SC), using independent component analysis (ICA) on resting state functional MRI data. Compared with SC, CB showed significantly increased network connectivity within the salience network (SN) and the occipital cortex. Moreover, CB exhibited enhanced internetwork connectivity between the SN and the frontoparietal network (FPN) and between the FPN and the occipital cortex; however, they showed decreased internetwork connectivity between the occipital cortex and the sensorimotor network. These findings suggest that CB experience large scale reorganization at the level of the functional network. More importantly, the enhanced intra‐ and internetwork connectivity of the SN, FPN, and occipital cortex in CB may improve their abilities to identify salient stimuli, to initiate the executive function, and to top‐down control of attention, which are critical for the CB to guide appropriate behavior and to better adaption to the environment. Hum Brain Mapp 35:2573–2581, 2014. © 2013 Wiley Periodicals, Inc .     

Dynamic functional network connectivity reveals unique and overlapping profiles of insula subdivisions

The human insular cortex consists of functionally diverse subdivisions that engage during tasks ranging from interoception to cognitive control. The multiplicity of functions subserved by insular subdivisions calls for a nuanced investigation of their functional connectivity profiles. Four insula subdivisions (dorsal anterior, dAI; ventral, VI; posterior, PI; middle, MI) derived using a data‐driven approach were subjected to static‐ and dynamic functional network connectivity (s‐FNC and d‐FNC) analyses. Static‐FNC analyses replicated previous work demonstrating a cognition‐emotion‐interoception division of the insula, where the dAI is functionally connected to frontal areas, the VI to limbic areas, and the PI and MI to sensorimotor areas. Dynamic‐FNC analyses consisted of k‐means clustering of sliding windows to identify variable insula connectivity states. The d‐FNC analysis revealed that the most frequently occurring dynamic state mirrored the cognition‐emotion‐interoception division observed from the s‐FNC analysis, with less frequently occurring states showing overlapping and unique subdivision connectivity profiles. In two of the states, all subdivisions exhibited largely overlapping profiles, consisting of subcortical, sensory, motor, and frontal connections. Two other states showed the dAI exhibited a unique connectivity profile compared with other insula subdivisions. Additionally, the dAI exhibited the most variable functional connections across the s‐FNC and d‐FNC analyses, and was the only subdivision to exhibit dynamic functional connections with regions of the default mode network. These results highlight how a d‐FNC approach can capture functional dynamics masked by s‐FNC approaches, and reveal dynamic functional connections enabling the functional flexibility of the insula across time. Hum Brain Mapp 37:1770–1787, 2016. © 2016 Wiley Periodicals, Inc .     

Resting state basal ganglia network in idiopathic generalized epilepsy

The basal ganglia, a brain structure related to motor control, is implicated in the modulation of epileptic discharges generalization in patients with idiopathic generalized epilepsy (IGE). Using group independent component analysis (ICA) on resting-state fMRI data, this study identified a resting state functional network that predominantly consisted of the basal ganglia in both healthy controls and patients with IGE. In order to gain a better understanding of the basal ganglia network(BGN) in IGE patients, we compared the BGN functional connectivity of controls with that of epilepsy patients, either with interictal epileptic discharges (with-discharge period, WDP) or without epileptic discharge (nondischarge period, NDP) while scanning. Compared with controls, functional connectivity of BGN in IGE patients demonstrated significantly more integration within BGN except cerebellum and supplementary motor area (SMA) during both periods. Compared with the NDP group, the increased functional connectivity was found in bilateral caudate nucleus and the putamen, and decreases were observed in the bilateral cerebellum and SMA in WDP group. In accord with the proposal that the basal ganglia modulates epileptic discharge activity, the results showed that the modulation enhanced the integration in BGN of patients, and modulation during WDP was stronger than that during NDP. Furthermore, reduction of functional connectivity in cerebellum and SMA, the abnormality might be further aggravated during WDP, was consistent with the behavioral manifestations with disturbed motor function in IGE. These resting-state fMRI findings in the current study provided evidence confirming the role of the BGN as an important modulator in IGE.     

Functional connectivity in patients with idiopathic generalized epilepsy

Purpose: Idiopathic generalized epilepsy (IGE) is characterized by electroencephalography (EEG) recordings with generalized spike wave discharges (GSWDs) arising from normal background activity. Although GSWDs are the result of highly synchronized activity in the thalamocortical network, EEG without GSWDs is believed to represent normal brain activity. The aim of this study was to investigate whether thalamocortical interactions are altered even during GSWD‐free EEG periods in patients with IGE. Methods: A GSWD‐related group analysis was performed in 12 IGE patients to define seeds in areas involved during GSWDs. EEG–functional magnetic resonance imaging (fMRI) datasets from 22 IGE patients without GSWDs during the investigation and 30 age‐matched healthy controls were then selected to investigate functional connectivity in GSWD‐related areas. Blood oxygen level dependent (BOLD) signal changes were extracted from seeds defined by the GSWD‐related group analysis. The averaged time course within each seed was used to detect brain regions with BOLD signal correlated with the seed. Group differences between patients and controls were estimated. Key Findings: The GSWD‐related group analysis showed BOLD activation in the thalamus, the frontomesial cortex, and the cerebellum and BOLD deactivation in default mode areas. For the connectivity analysis, eight seeds were placed bilaterally in the thalamus, mesial frontal cortex, precuneus, and cerebellum. The functional connectivity analysis of these seeds did not show clearly altered functional connectivity for patients versus controls. Significance: The results underscore the paroxysmal nature of GSWDs: Although GSWDs are characterized by highly synchronized activity in the thalamocortical network, the functional connectivity in areas involved during GSWDs does not demonstrate abnormality in GSWD‐free periods.     

Hearing voices in the resting brain: A review of intrinsic functional connectivity research on auditory verbal hallucinations

Resting state networks (RSNs) are thought to reflect the intrinsic functional connectivity of brain regions. Alterations to RSNs have been proposed to underpin various kinds of psychopathology, including the occurrence of auditory verbal hallucinations (AVH). This review outlines the main hypotheses linking AVH and the resting state, and assesses the evidence for alterations to intrinsic connectivity provided by studies of resting fMRI in AVH. The influence of hallucinations during data acquisition, medication confounds, and movement are also considered. Despite a large variety of analytic methods and designs being deployed, it is possible to conclude that resting connectivity in the left temporal lobe in general and left superior temporal gyrus in particular are disrupted in AVH. There is also preliminary evidence of atypical connectivity in the default mode network and its interaction with other RSNs. Recommendations for future research include the adoption of a common analysis protocol to allow for more overlapping datasets and replication of intrinsic functional connectivity alterations.     

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.     

Complex discharge‐affecting networks in juvenile myoclonic epilepsy: A simultaneous EEG‐fMRI study

Juvenile myoclonic epilepsy (JME) is a common subtype of idiopathic generalized epilepsies (IGEs) and is characterized by myoclonic jerks, tonic‐clonic seizures and infrequent absence seizures. The network notion has been proposed to better characterize epilepsy. However, many issues remain not fully understood in JME, such as the associations between discharge‐affecting networks and the relationships among resting‐state networks. In this project, eigenspace maximal information canonical correlation analysis (emiCCA) and functional network connectivity (FNC) analysis were applied to simultaneous EEG‐fMRI data from JME patients. The main findings of our study are as follows: discharge‐affecting networks comprising the default model (DMN), self‐reference (SRN), basal ganglia (BGN) and frontal networks have linear and nonlinear relationships with epileptic discharge information in JME patients; the DMN, SRN and BGN have dense/specific associations with discharge‐affecting networks as well as resting‐state networks; and compared with controls, significantly increased FNCs between the salience network (SN) and resting‐state networks are found in JME patients. These findings suggest that the BGN, DMN and SRN may play intermediary roles in the modulation and propagation of epileptic discharges. These roles further tend to disturb the switching function of the SN in JME patients. We also postulate that emiCCA and FNC analysis may provide a potential analysis platform to provide insights into our understanding of the pathophysiological mechanism of epilepsy subtypes such as JME. Hum Brain Mapp 37:3515–3529, 2016. © 2016 Wiley Periodicals, Inc.     

Flexible connectivity in the aging brain revealed by task modulations

Recent studies have shown that aging has a large impact on connectivity within and between functional networks. An open question is whether elderly still have the flexibility to adapt functional network connectivity (FNC) to the demands of the task at hand. To study this, we collected fMRI data in younger and older participants during resting state, a selective attention (SA) task and an n‐back working memory task with varying levels of difficulty. Spatial independent component (IC) analysis was used to identify functional networks over all participants and all conditions. Dual regression was used to obtain participant and task specific time‐courses per IC. Subsequently, functional connectivity was computed between all ICs in each of the tasks. Based on these functional connectivity matrices, a scaled version of the eigenvector centrality (SEC) was used to measure the total influence of each IC in the complete graph of ICs. The results demonstrated that elderly remain able to adapt FNC to task demands. However, there was an age‐related shift in the impetus for FNC change. Older participants showed the maximal change in SEC patterns between resting state and the SA task. Young participants, showed the largest shift in SEC patterns between the less demanding SA task and the more demanding 2‐back task. Our results suggest that increased FNC changes from resting state to low demanding tasks in elderly reflect recruitment of additional resources, compared with young adults. The lack of change between the low and high demanding tasks suggests that elderly reach a resource ceiling. Hum Brain Mapp 35:3788–3804, 2014. © 2013 Wiley Periodicals, 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.     

Alterations of Functional Connectivity Among Resting‐State Networks in Hypothyroidism

Hypothyroidism affects brain functioning as suggested by various neuroimaging studies. The primary focus of the present study was to examine whether hypothyroidism would impact connectivity among resting‐state networks (RSNs) using resting‐state functional magnetic resonance imaging (rsfMRI). Twenty‐two patients with hypothyroidism and 22 healthy controls were recruited and scanned using rsfMRI. The data were analysed using independent component analysis and a dual regression approach that was applied on five RSNs that were identified using fsl software ( http://fsl.fmrib.ox.ac.uk ). Hypothyroid patients showed significantly decreased functional connectivity in the regions of the right frontoparietal network (frontal pole), the medial visual network (lateral occipital gyrus, precuneus cortex and cuneus) and the motor network (precentral gyrus, postcentral gyrus, precuneus cortex, paracingulate gyrus, cingulate gyrus and supramarginal gyrus) compared to healthy controls. The reduced functional connectivity in the right frontoparietal network, the medial visual network and the motor network suggests neurocognitive alterations in hypothyroid patients in the corresponding functions. However, the study would be further continued to investigate the effects of thyroxine treatment and correlation with neurocognitive scores. The findings of the present study provide further interesting insights into our understanding of the action of thyroid hormone on the adult human brain.     

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 .     

Resting‐state networks show dynamic functional connectivity in awake humans and anesthetized macaques

Characterization of large‐scale brain networks using blood‐oxygenation‐level‐dependent functional magnetic resonance imaging is typically based on the assumption of network stationarity across the duration of scan. Recent studies in humans have questioned this assumption by showing that within‐network functional connectivity fluctuates on the order of seconds to minutes. Time‐varying profiles of resting‐state networks (RSNs) may relate to spontaneously shifting, electrophysiological network states and are thus mechanistically of particular importance. However, because these studies acquired data from awake subjects, the fluctuating connectivity could reflect various forms of conscious brain processing such as passive mind wandering, active monitoring, memory formation, or changes in attention and arousal during image acquisition. Here, we characterize RSN dynamics of anesthetized macaques that control for these accounts, and compare them to awake human subjects. We find that functional connectivity among nodes comprising the “oculomotor (OCM) network” strongly fluctuated over time during awake as well as anaesthetized states. For time dependent analysis with short windows (<60 s), periods of positive functional correlations alternated with prominent anticorrelations that were missed when assessed with longer time windows. Similarly, the analysis identified network nodes that transiently link to the OCM network and did not emerge in average RSN analysis. Furthermore, time‐dependent analysis reliably revealed transient states of large‐scale synchronization that spanned all seeds. The results illustrate that resting‐state functional connectivity is not static and that RSNs can exhibit nonstationary, spontaneous relationships irrespective of conscious, cognitive processing. The findings imply that mechanistically important network information can be missed when using average functional connectivity as the single network measure. Hum Brain Mapp 34:2154–2177, 2013. © 2011 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.     

Comparison of continuously acquired resting state and extracted analogues from active tasks

Functional connectivity analysis of brain networks has become an important tool for investigation of human brain function. Although functional connectivity computations are usually based on resting‐state data, the application to task‐specific fMRI has received growing attention. Three major methods for extraction of resting‐state data from task‐related signal have been proposed (1) usage of unmanipulated task data for functional connectivity; (2) regression against task effects, subsequently using the residuals; and (3) concatenation of baseline blocks located in‐between task blocks. Despite widespread application in current research, consensus on which method best resembles resting‐state seems to be missing. We, therefore, evaluated these techniques in a sample of 26 healthy controls measured at 7 Tesla. In addition to continuous resting‐state, two different task paradigms were assessed (emotion discrimination and right finger‐tapping) and five well‐described networks were analyzed (default mode, thalamus, cuneus, sensorimotor, and auditory). Investigating the similarity to continuous resting‐state (Dice, Intraclass correlation coefficient (ICC), R²) showed that regression against task effects yields functional connectivity networks most alike to resting‐state. However, all methods exhibited significant differences when compared to continuous resting‐state and similarity metrics were lower than test‐retest of two resting‐state scans. Omitting global signal regression did not change these findings. Visually, the networks are highly similar, but through further investigation marked differences can be found. Therefore, our data does not support referring to resting‐state when extracting signals from task designs, although functional connectivity computed from task‐specific data may indeed yield interesting information. Hum Brain Mapp 36:4053–4063, 2015. © 2015 The Authors Human Brain Mapping Published by 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.