Phenotypic Variability in Resting-State Functional Connectivity: Current Status

Summary

Superior intelligence depends upon higher within-network integration and cross-network segregation of the frontoparietal and default networks.

Visual performance

In the context of face processing, greater connectivity between two canonical face-processing regions in the visual network, the occipital face area and the fusiform face area in the FG, predicted a greater face inversion effect, indicating increased holistic processing of faces and superior face recognition abilities in healthy individuals (Zhu et al., 2011). In the context of visual–spatial attention, weaker interhemispheric connectivity of the dorsal attention network (left and right intraparietal sulcus [IPS]) was associated with worse spatial attention performance in patients with right-hemispheric stroke (Carter et al., 2010). Further, inappropriate sensory experience in synesthesia relates to greater connectivity between visual and other networks. In individuals with grapheme-color and phoneme-color synesthesia—a condition in which words and grayscale letters are involuntarily perceived as being colored—abnormally increased connectivity between the visual network and the auditory and frontoparietal networks predicted more consistent synesthetic experiences (Dovern et al., 2012).

Motor performance

Convergent lines of evidence suggest that connectivity within the somatomotor network is associated with motor function. First, greater connectivity within the left than the right side of the somatomotor network (including connections between primary motor cortex [M1], supplementary motor area [SMA], cerebellum, thalamus, and putamen) predicted faster motor performance, less overflow, and less dysrhythmia on a standardized test of motor skills in healthy right-handed children (Barber et al., 2012). Second, weaker interhemispheric connectivity within the somatomotor network predicted worse performance on a variety of hand- and wrist-based motor function measures in patients with stroke (Carter et al., 2010) and less recovery of motor function after 6 months (Park et al., 2011). Third, greater interconnectedness of the somatomotor network (indexed by higher clustering coefficient) predicted faster progression of symptoms of amyotrophic lateral sclerosis (ALS), a progressive disease characterized by degeneration of motor neurons, resulting in rapidly increasing motor weakness and loss of motor control (Verstraete et al., 2010). Thus, while a strongly connected somatomotor network may facilitate motor function, it may also facilitate the spread of ALS symptoms.

In addition to within-network connectivity, connectivity between the somatomotor and other networks is associated with motor function. First, weaker connectivity between the somatomotor network and the contralateral frontoparietal network (and thalamus) predicted less recovery of motor function 6 months after the stroke (Park et al., 2011). Second, a mixed pattern of reduced and increased connectivity degree (a measure of the overall connectedness of a region) of specific nodes of the somatomotor network with other regions predicted the severity of motor symptoms in Parkinson's disease (PD; indexed by the Unified Parkinson's Disease Rating-scale motor score) (Wu et al., 2009). Specifically, worse motor function was associated with reduced connectivity degree of regions that nominally have widespread connectivity with other brain regions (thalamus, putamen, SMA node of the somatomotor network, and frontoparietal network) and increased connectivity degree of regions that usually have focal connectivity (M1, primary somatosensory cortex [S1], premotor nodes of the somatomotor network, and cerebellum). Thus, these findings suggest that degeneration in dopamine signaling in PD may induce motor dysfunction by reducing widespread connectivity and over-generalizing focal connectivity.

Visual–motor integration

Visual–motor processing speed has been associated with the cingulo-opercular, frontoparietal, and default networks. In patients with cognitive dysfunction due to hepatic encephalopathy, a liver disease, reduced connectivity within a frontoparietal ICA component was associated with slower performance on a number trail-making task (Qi et al., 2012). In the same patients, the default ICA component showed associations with both increased and reduced connectivity such that increased posterior connectivity predicted slower performance on the number trail-making task, while reduced anterior connectivity predicted slower digit–symbol matching performance. Further, increased connectivity of the putamen within the cingulo-opercular network was related to slower digit–symbol matching performance across both lean and obese adults (García-García et al., 2012). Higher-order visual–motor integration was associated with the cingulo-opercular network such that increased connectivity between the left anterior insula (aIns) and the rest of the cingulo-opercular network across older and younger adults predicted higher block-design performance indexing visuospatial intelligence (Onoda et al., 2012).

Summary

Individual differences in visual and motor functions were associated with connectivity strength within their respective modality-specific networks, such as visual and somatomotor. Similarly, pathological integration across modalities as in synesthesia was correlated with the extent of connectivity between the relevant modality-specific networks, visual and auditory. Further, shifting visual attention in space was associated with a network encompassing parietal regions known to subserve spatial attention, termed the dorsal attention network. In contrast, integration of visual and motor processes was associated with neither of these modality-specific networks, but rather with networks integrating multiple heteromodal cortical regions such as the cingulo-opercular, frontoparietal, and default networks. Further, connectivity across the somatomotor and frontal-parietal networks was important for predicting loss or recovery of motor function.

Working memory

Working memory refers to the ability to maintain and manipulate information for a short period of time. Working memory function was associated with both whole-brain connectivity and with selective networks, including default, frontoparietal, and cingulo-opercular. Global measures such as increased small worldness (network efficiency) predicted superior working memory capacity, and degree of modularity predicted variability in memory capacity across sessions (Stevens et al., 2012a). Superior working memory was also related to increased connectivity within the default network, from ventromedial prefrontal cortex and adjacent regions (vmPFC) to posterior cingulate cortex (PCC) (Hampson et al., 2006, 2010), with increased connectivity of PCC in default-network ICA components (Sala-Llonch et al., 2012), with increased connectivity between the frontoparietal network and the cerebellum across both controls and schizophrenics (Repovs et al., 2011), with increased connectivity between the cingulo-opercular network and the putamen across both controls and schizophrenics (Tu et al., 2012), and with reduced connectivity between default and frontoparietal networks (Hampson et al., 2010). In addition to cortical connectivity, reduced connectivity between subcortical structures such as the thalamus and striatal regions (bilateral globus pallidus and putamen) was associated with better working memory across both children with and without attention-deficit hyperactivity disorder (ADHD) (Mills et al., 2012). Thus, working memory function was associated with stronger connectivity within default and cingulo-opercular regions and also between the frontoparietal network and cerebellum, a region often activated during working memory performance, as well as with weaker connectivity between default and frontoparietal networks and among subcortical regions such as the basal ganglia and thalamus.

Sustained attention

Sustained attention is defined as the ability to consistently maintain attention to goal-relevant stimuli. Individual differences in attention have been linked to both increased and decreased connectivity between the default and task-positive networks. Decreased intertrial variability in response time (an indicator of reduced attention lapses) was linked to less negative connectivity between default and task-positive networks (Kelly et al., 2008). However, better performance on a sustained visual attention task was linked to increased connectivity between the PCC-default node and the inferior frontal gyrus (IFG)/temporal–parietal junction frontoparietal nodes (Pagnoni, 2012). These disparate results suggest that direction of association may differ by the type of attentional process.

Inhibitory control

Connectivity of default, frontoparietal, and cingulo-opercular networks has been associated with variability in inhibitory control. Using the stop-signal task to operationalize response inhibition, better inhibitory control across both healthy children and those with ADHD, a disorder defined by inhibitory deficits, was associated with more positive connectivity among cingulo-opercular nodes (pre-SMA and ACC) and more negative connectivity of cingulo-opercular nodes (ACC and pre-SMA) with nodes of other networks, including subcortical (thalamus) and frontoparietal (middle frontal gyrus [MFG]) nodes (Mennes et al., 2011). Furthermore, diagnosis of ADHD modulated relationships of connectivity and inhibitory performance, such that worse inhibitory control in ADHD children, was related to increased connectivity between cingulo-opercular nodes (pre-SMA, SMA, supramarginal gyrus [SMG], insula, and ACC) and nodes of other networks, including dorsal attention (parietal operculum), visual (lateral occipital cortex), frontoparietal (superior frontal), and striatal (putamen and caudate) nodes. Thus, the cingulo-opercular network and its connectivity with other networks predicted inhibitory control.

In addition to these observed relationships with long-distance connectivity, local connectivity was also associated with stop-signal performance (Tian et al., 2012). Superior inhibitory control was associated with increased ReHo in sensory networks, including visual (bilateral occipital cortex and inferior temporal regions), and auditory (posterior insula [pIns]) and reduced ReHo in default (vmPFC and precuneus) and frontoparietal (bilateral IFG and left inferior parietal lobule [IPL]) network regions.

Inhibitory control in everyday life, indexed by self-reported behaviors reflecting impulsivity, is predicted by cross-network relationships. In healthy adults, increased impulsivity (i.e., worse inhibitory control) as measured by the Barratt Impulsivity Scale was associated with increased density of functional connectivity within visual and default networks, and between cingulo-opercular and amygdala networks (Davis et al., 2012). However, increased impulsivity was also associated with decreased connectivity density between visual and default networks, and between visual and amygdala networks. In patients with Borderline personality disorder, higher impulsivity was associated with increased connectivity of the mPFC node in the default-network ICA component (Wolf et al., 2011). In incarcerated juvenile offenders, bilateral premotor connectivity predicted impulsivity, as measured by the Hare Psychopathy Checklist, such that higher impulsivity was associated with increased connectivity with the default network and reduced connectivity with the dorsal attention and frontoparietal networks (Shannon et al., 2011). In heroin-dependent subjects, higher impulsivity was associated with increased connectivity between the amygdala and the default network, auditory network, and the thalamus, as well as with reduced connectivity between the amygdala and the FG in the visual network (Xie et al., 2011). Thus, across diverse populations, connectivity within the default network, as well as connectivity across networks, was associated with trait-level impulsivity.

Verbal fluency

Fluency refers to the ability to list many objects within a defined category without repeating objects. Across controls and schizophrenics, superior verbal fluency was associated with several metrics of whole-brain connectivity, including average connectivity strength across all regions, clustering, degree distribution, and small worldness (Lynall et al., 2010).

Task switching

A key component of executive control is the ability to flexibly shift from the demands of one task to another. Such task switching has been strongly linked to the frontoparietal network. Superior task-switching abilities have been associated with increased connectivity between bilateral IPL and the rest of the frontoparietal network (Seeley et al., 2007), with increased connectivity between bilateral MFG in children (Gordon et al., 2011), with increased connectivity between frontoparietal network nodes and the cerebellum across controls and schizophrenics (Repovs et al., 2011), and with increased connectivity within frontoparietal ICA components across controls and patients with medial temporal lobe epilepsy (Zhang et al., 2009).

Summary

Two themes emerge from reviewing the large body of work examining associations with executive function. First, in addition to the connectivity of task-positive and default networks, connectivity of subcortical structures such as the striatum, amygdala, thalamus, and cerebellum was also important for predicting individual differences. Second, cross-network relationships were relevant to executive functioning, such that superior function was predicted by more segregation among task-positive networks and between task-positive and default networks in most studies. Further, in some studies, superior function was also associated with more integration between selective task-positive networks (e.g., frontoparietal and dorsal attention), as well as more integration between some networks and subcortical regions (e.g., between visual network and amygdala; between frontoparietal network and cerebellum).

Attention-deficit hyperactivity disorder

Symptoms of ADHD, such as inattention, hyperactivity, and impulsivity, have been associated with connectivity of default, dorsal attention, and cingulo-opercular networks, as well as among subcortical regions. Higher externalizing symptoms (e.g., aggressive and oppositional defiant behaviors) as measured by the Child Behavior Checklist were associated with reduced positive connectivity within default network regions, including between temporal pole and precuneus, between PCC and superior frontal gyrus (SFG), and between posterior IPL and frontal pole (Chabernaud et al., 2012). Further, connectivity of the left putamen, a subcortical motor region, predicted symptoms measured by the ADHD Rating Scale, such that increased symptoms were associated with reduced connectivity with right subcallosal gyrus/nucleus accumbens and increased connectivity with right global pallidus/thalamus (Cao et al., 2009).

Schizophrenia

Schizophrenia is characterized by the presence of positive symptoms (disrupted or disorganized thought and behavior) and negative symptoms (poverty of speech, thought, or affect), and resting-state connectivity studies have primarily linked individual differences in these symptoms to abnormal connectivity of default and frontoparietal networks.

The severity of positive symptoms has been most frequently linked to increased connectivity between default and frontoparietal networks. More severe positive symptoms were particularly predicted by increased connectivity between default-network nodes (such as vmPFC, PCC, precuneus, and retrosplenial cortex) and lateral frontal frontoparietal nodes (Bluhm et al., 2007, 2009; Skudlarski et al., 2010). Interestingly, while increased connectivity between default and frontoparietal connectivity predicted more severe positive symptoms, it also predicted less-severe negative symptoms (Bluhm et al., 2007; Cole et al., 2011; Venkataraman et al., 2012). This suggests that the positive or negative symptomatic manifestation of schizophrenia may be dependent on the intrinsic connections between these two networks.

More severe positive symptoms were also predicted by increased connectivity between default network and a variety of other networks, including somatomotor, frontotemporal (Bluhm et al., 2007, 2009; Venkataraman et al., 2012), and visual (Bluhm et al., 2009; Meda et al., 2012). Positive symptoms have additionally been linked to connectivity within the default network, though the direction of the effect has not been consistent, with reports of increased symptoms being linked to both reduced (Rotarska-Jagiela et al., 2010; Jang et al., 2011 in healthy relatives of schizophrenics) and increased (Whitfield-Gabrieli et al., 2009) within-network connectivity.

Frontoparietal network connectivity with other networks predicted both positive and negative symptoms. Increased positive symptoms were associated with reduced connectivity within the frontoparietal network (Cole et al., 2011), reduced connectivity between the frontoparietal and auditory networks (Cole et al., 2011) and the cerebellum (Repovs et al., 2011), increased connectivity between frontoparietal and visual/somatomotor networks (Cole et al., 2011), and increased asymmetry of connectivity in the frontoparietal networks (Ke et al., 2010). Increased negative symptoms were associated with increased connectivity between frontoparietal and somatomotor network/cerebellum (Cole et al., 2011), as well as with decreased asymmetry of connectivity in default network (Ke et al., 2010).

Finally, a few studies have suggested that connections not involving the default or frontoparietal networks may be relevant for symptom severity. Increased positive symptoms were predicted by reduced connectivity within the frontotemporal network and by increased connectivity in the auditory network (Rotarska-Jagiela et al., 2010), by reduced connectivity between frontotemporal and somatomotor networks (Skudlarski et al., 2010), and by increased asymmetry of connectivity in cingulo-opercular and visual networks (Ke et al., 2010). Increased negative symptoms were predicted by reduced connectivity between cingulo-opercular network and putamen (Tu et al., 2012), as well as by increased connectivity between amygdala and frontotemporal networks (Meda et al., 2012). More severe negative symptoms were also predicted by greater clustering coefficients and efficiency of the visual network, by longer characteristic path length in the somatomotor network, and by longer path length and reduced efficiency of the whole brain (Yu et al., 2011).

Summary

Individual differences in the severity of symptoms were associated with connectivity of many task-positive and default networks. For both ADHD and schizophrenia, both within-network and cross-network relationships predicted symptom severity. In addition to cortical connectivity, several subcortical regions, including striatal structures and amygdala, correlated with symptoms. In both disorders, these relationships included brain regions that are consistent with affected behavioral domains, including motor (e.g., putamen) and reward (e.g., nucleus accumbens) functions in ADHD, as well as sensory-motor (e.g., somatomotor, visual, and auditory) and emotion (e.g., amygdala) functions in schizophrenia. While studies of ADHD symptom-connectivity were few, those of schizophrenia were many and are riddled with mixed findings, perhaps reflective of the high heterogeneity among patients in the duration of the disorder, medication history, and the nature of behavioral dysfunction.

Motor learning

Force-field motor learning was associated with connectivity of default, somatomotor, and visual networks and cerebellum (Vahdat et al., 2011). Relative to a prelearning resting scan, increases in the perceptual indices of learning 1 h after force-field learning were associated with increases in connectivity strength within the somatomotor network and between the cerebellum and the mPFC default node, as well as with decreases in connectivity between the cerebellum and visual network. Further, decreases in connectivity between the cerebellum and the somatomotor and visual networks predicted increases in the ability to accurately perform a motor task under force-field conditions.

Visual–spatial learning

Decreases in connectivity strength between the visual network and the frontal eye fields in the dorsal attention network from a prelearning resting scan were associated with greater improvements in accuracy and speed after training on a novel visual discrimination task (searching for T-target among rotated L-distractors for 4 days, 2/3 h/day) (Lewis et al., 2009). These same subjects also showed that the status of prelearning resting-state connectivity of the visual network predicted the amount of subsequent visual learning (Baldassarre et al., 2012). Specifically, the strength of connectivity within the visual network, between heterotopic (i.e., above and below the calcarine sulcus within and across hemispheres), but not homotopic (e.g., above the calcarine across hemispheres) visual regions before training was positively correlated with better learning. Further, the strength of connectivity between visual regions and the left aIns node of the cingulo-opercular network and the vmPFC default-network node was negatively correlated with better learning. Together, these findings suggest that better communication among visual regions and weaker communication between visual and frontal regions involved in detecting and evaluating salient information may facilitate parsing of task-relevant and task-irrelevant visual information in subsequent experience.

Individual differences in navigational ability, as measured by the Santa Barbara Sense of Direction Scale, correlated with learning-related changes in connectivity of the bilateral PHC, a default-network node (Wegman and Janzen, 2011). Specifically, connectivity changes were compared between resting scans performed before and after a route-learning task. Subjects with better navigational ability had increased learning-related connectivity with the right hippocampus, but decreased learning-related connectivity with the right caudate. Thus, consolidation of spatial learning reflected in ICN plasticity depended upon spatial ability.

Pain adaptation

Connectivity of the somatomotor network and the vmPFC default node was associated with individual differences in both retrospective and prospective aspects of learning about painful experience (Riedl et al., 2011). Connectivity in somatosensory and posterior parietal cortex nodes of the somatomotor network correlated positively with pain intensity ratings, both immediately after heat pain was applied to the forearm and after 11 days of exposure to the noxious stimulation. Further, the extent to which subjects adapted to pain over the 11 days correlated positively with connectivity between the vmPFC default-network node and the somatomotor ICA component after the extended exposure to the noxious stimulation, but not before it. Interestingly, this correlation was observed before exposure to the heat pain on the 11th day, which indicates that this somatomotor-default connectivity predicted how much pain the subject anticipated experiencing on the last day.

Summary

Individual variability in learning ability, as well as consolidation of the learning experience, was associated with connectivity of the ICNs associated with the modality or domain of the learning experience (i.e., somatomotor for sensorimotor learning or adaptation and visual for visual–spatial learning). Further, postlearning changes in connectivity also included modality-specific subcortical regions such as the cerebellum for motor function, cortical regions important for set maintenance such as the cingulo-opercular network for visual learning, and the default network.

Autobiographical memory

Subjects who spent a greater percentage of time thinking about their past or future during a resting-scan session had stronger connectivity between the medial temporal default node and other default regions (including vmPFC, restrosplenial cortex, and posterior IPS) (Andrews-Hanna et al., 2010). Thus, at least one function of the default network may be retrieving autobiographical information.

Episodic memory

Studies examining association with episodic memory can be divided into two classes: (i) those examining ICNs after encoding of the to-be-remembered material; and (ii) those examining ICNs before encoding of the to-be-remembered material or some standardized measure of memory ability. These two study types provide different information about memory: the former elucidates circuits that support consolidation of mnemonic information, and the latter elucidates circuits that predict mnemonic ability.

Differences in consolidation are associated with the strength of connectivity between stimulus-selective posterior cortices and frontoparietal and default-network nodes. Immediately after incidental encoding of scenes and faces, better memory for those stimuli was associated with stronger connectivity between right IFG and category-selective seed regions in the default (PHC, for scenes) and visual (FG, for faces) networks (Stevens et al., 2010). Stronger connectivity between hippocampus and right lateral occipital cortex on a resting scan done after encoding of object–face pairs relative to one before encoding predicted better memory for the object–face pairs measured after the scanning sessions (Tambini et al., 2010). A similar brain–behavior relationship was not observed for face–scene pairs, which were not remembered, as well as the object–face pairs. Hippocampal-to-lateral occipital connectivity at baseline did not correlate with subsequent memory performance, which suggests that changes in connectivity during encoding of the material predicted how well the material was later consolidated. Together, these findings suggest that regions involved in the encoding of an experience are sensitive to consolidation of that experience in the time period after the experience.

Differences in mnemonic ability are predicted by higher connectivity within and between default and frontoparietal networks, and lower connectivity among subcortical regions. Better memory performance, as measured by neuropsychological tests such as the Wechsler Memory Scale and California Verbal Learning Test (CVLT), was associated with stronger connectivity between the frontoparietal network and the cerebellum in a combined group of schizophrenic subjects and healthy controls and healthy siblings of both groups (Repovs et al., 2011). Better memory for line drawings of common objects and animals was associated with stronger connectivity between default-network nodes in left and right hippocampi (Wang et al., 2010b). Further, better memory for the face–name pairs and on the Wechsler Memory Scale was associated with stronger connectivity between the hippocampus and PCC/precuneus nodes of the default network in healthy elderly subjects (Wang et al., 2010a). In contrast to these findings of positive correlation with cortical regions, reduced connectivity of subcortical regions (both within thalamus and putamen ICA components and between putamen, thalamus, and caudate components) predicted higher scores on CVLT in elderly subjects (Ystad et al., 2010).

Summary

Connectivity of the default network, particularly between the midline and medial temporal nodes, was important for predicting consolidation of remembered material as well as the ability to remember subsequently encoded material. In addition, these mnemonic functions also depended upon the connectivity of default-network regions with material-specific posterior temporal cortices and the frontoparietal network.

AD and MCI

Reduced connectivity within the default ICA component predicted reduced scores on the Mini-Mental State Examination (MMSE) in patients with AD (Wu et al., 2011b), as did decreased ReHo of the PCC-default node (He et al., 2007). Similarly, in individuals with MCI, reduced PCC-seed- and angular gyrus (AG)-seed-based default connectivity predicted reduced MMSE scores and episodic memory abilities (Liang et al., 2012; Wang et al., 2012a).

The connectivity of several other networks has also been linked to AD symptoms in MCI, possibly reflecting the more variable nature of MCI compared to AD. As in the default network, reduced connectivity within the frontoparietal network predicted reduced MMSE scores (Liang et al., 2011, 2012), while reduced connectivity both within the cingulo-opercular network and between the cingulo-opercular and frontoparietal networks predicted worse episodic memory (Xie et al., 2012a). Additionally, reduced connectivity between default and frontotemporal networks also predicted worse episodic memory, and reduced connectivity between default and frontoparietal networks predicted slower processing speed, but reduced connectivity between default network and caudate predicted better episodic memory (Han et al., 2012).

Interestingly, treatment of patients with AD with the acetylcholinesterase inhibitor donepezil has been shown to reverse these connectivity disruptions, and the degree of connectivity increase has been linked to cognitive improvements. Reductions in AD symptoms were predicted by donepezil-related connectivity increases within the default network (Goveas et al., 2011b; Li et al., 2012a) as well as by connectivity decreases between the hippocampal default node and the frontoparietal and cingulo-opercular networks (Goveas et al., 2011b). This suggests that the observed relationships between connectivity disruptions and symptom severity are highly relevant to disease treatment.

Multiple sclerosis

Multiple sclerosis (MS) is a progressive demyelinating condition that often results in general information-processing deficits as well as episodic memory problems. In patients with MS, worse performance on tests of information processing and episodic memory was associated with reduced connectivity of the PCC and mPFC nodes of a default-network ICA component (Rocca et al., 2010). Further, in patients with MS who underwent cognitive rehabilitation therapy, increases in connectivity between the ACC node of the cingulo-opercular network and the right lateral prefrontal and parietal nodes of the frontoparietal network predicted improvements in information-processing abilities (Parisi et al., 2012).

Traumatic brain injury

Traumatic brain injury (TBI) results from physical trauma to the head, and in mild, closed-head cases, it produces marked, but usually transient, cognitive dysfunction that includes episodic memory problems. In patients with TBI, slower reaction time on a simple choice-reaction time task was predicted by lower connectivity of the PCC within a default-network ICA component (Sharp et al., 2011). Further, worse cognitive symptoms in mild TBI were predicted both by reduced connectivity within the default network and by increased cross-network connectivity between default and frontoparietal networks (Mayer et al., 2011).

However, as TBI-related damage (e.g., diffuse axonal injury) (Scheid et al., 2003) is usually distributed throughout the brain rather than localized to specific regions or networks, ICN alterations ought to be more pervasive. Indeed, patients with mild TBI demonstrated abnormally increased and abnormally asymmetric thalamic connectivity with widespread cortical regions encompassing many networks; the degree of increased connectivity predicted increased memory impairment, while the degree of increased asymmetry predicted increased postconcussive symptoms (Tang et al., 2011). Moreover, in a more comprehensive ICA examining all the brain networks in patients with mild TBI, the degree of postconcussive symptoms was predicted by both increases and decreases in connectivity across virtually all networks, in both within- and across-network connections (Stevens et al., 2012b).

Epilepsy

The chronic nature of epilepsy disrupted the organization of the default network such that patients with higher duration of illness (years from time of first seizure to time of scan) had increased connectivity between the PCC and bilateral parahippocampal regions in the anterior temporal lobes and reduced connectivity of the PCC with dorsomedial prefrontal cortex (dmPFC) (McGill et al., 2012). Reduced rate of retention of verbal information in patients with temporal-lobe epilepsy was associated with increased connectivity between the left medial temporal lobe and PCC in those with seizure focus in the left hemisphere. However, patients with right hemisphere seizure focus appear to compensate, such that higher episodic memory for nonverbal material (faces) was associated with higher connectivity of the intact left medial temporal lobe and anterior mPFC (Doucet et al., 2012).

Wernicke's encephalopathy

Wernicke's encephalopathy, a result of chronic severe alcoholism, includes degeneration of brainstem and medial thalamic nuclei, mammillary bodies, and cerebellum. If left untreated via thiamine replacement therapy, the disease may progress into Korsakoff's syndrome. Within patients undergoing treatment, associations have been found between the severity of verbal memory impairment and the degree of connectivity between the anterior thalamus and mammillary bodies (Kim et al., 2009). The authors suggest that mammilothalamic connectivity may thus index the success of the treatment, suggesting the possibility of individual differences in the reversibility of the disorder.

Summary

In a variety of neurological conditions whose primary symptoms include episodic dysfunction, episodic memory abilities depended upon connectivity within medial temporal, PCC, and mPFC default-network nodes. Further, weaker connectivity between the default network and frontoparietal and cingulo-opercular networks was associated with reduced episodic memory, and response to treatment that improved episodic memory included strengthening of those connections. Further, connectivity of subcortical structures such as thalamus and mammillary bodies was also responsive to treatment, improving memory function.

Summary

Higher language competence on a variety of indices was associated with stronger connectivity within frontotemporal networks, as well as with its connectivities with other networks. While semantic abilities were associated with more integration of the frontotemporal nodes with default network, reading competence was associated with less integration with default-network nodes, frontoparietal nodes, and extrastriate visual regions. Further, associations between language ability and cross-network relationships were reversed in childhood, suggesting that changes in cross-network relationships define the developmental trajectory of reading competence.

Internalizing/externalizing problems

Higher internalizing scores (e.g., behavior reflective of anxiety, depression, and social withdrawal) showed a positive association with stronger connectivity among all default nodes, as well as a negative association with connectivity between default network and both frontoparietal network (anterior mPFC to IFG and premotor cortex) and cingulo-opercular network (retrosplenial cortex to insula, dACC, and SMA) (Chabernaud et al., 2012). Further, higher externalizing scores (e.g., aggressive behaviors) were associated with connectivity between default and task-positive networks, positively with the cingulo-opercular network (AG/posterior IPL to the dACC and SMA) and negatively with the dorsal attention network (restrosplenial cortex to posterior parietal/dorsal occipital cortex). The presence of ADHD moderated connectivity of the default network such that higher externalizing scores in children with ADHD were associated with less-positive connectivity within the default network (temporal poles to PCC, precuneus, and SFG, and AG/posterior IPL to frontal poles), while the opposite relationship was observed in control children.

Anxiety

The level of anxiety experienced at the time of the resting scan alters the connectivity strength of default, cingulo-opercular, and amygdala networks. In healthy subjects, state anxiety measured by the State Trait Anxiety Inventory was positively correlated with right amygdala–dmPFC connectivity and negatively correlated with right amygdala–vmPFC connectivity (Kim et al., 2011). Similarly, a negative correlation with left amygdala–ventral mPFC and PCC/precuneus connectivity was also observed in a combined group of healthy controls and patients with social anxiety disorder or panic disorder (Hahn et al., 2011). Connectivity of the aIns, a cingular-opercular node, was also implicated in two studies in which subjects rated how anxious they felt before or during the scan. First, connectivity from aIns to other cingulo-opercular regions such as dACC and left SFG was stronger in individuals with higher anxiety (Seeley et al., 2007). Second, connectivity between a default ICA component and the left aIns was stronger in adolescents and adults with higher anxiety; additional regions showing a positive correlation included the caudate in adolescents, and the right IFG, left PHC, and left PCC in adults (Dennis et al., 2011).

Empathy

Individual differences in empathy are predicted by differences in connectivity of regions involved in emotional, social-cognitive, and interoceptive functions that comprise the default, cingulo-opercular, frontotemporal, and amygdala networks, as well as brainstem regions. One behavior indicative of empathy is the extent to which one feels another's pain. Ratings of how much one felt the physical pain depicted in pictures correlated positively with connectivity of vmPFC and subgenual ACC regions of the default network (Otti et al., 2010). Empathy can also be classified into affective (e.g., visceral reaction to others' emotional state) and cognitive (e.g., ability to take others' perspective) aspects. Their relative dominance, measured by the Interpersonal Reactivity Index, was predicted by the strength of connectivity among default, cingulo-opercular, and amygdala networks (Cox et al., 2011). Specifically, higher dominance of affective over cognitive aspects was associated with increased connectivity among social–emotional processing regions such as ventral aIns (cingulo-opercular), vmPFC (default), and amygdala, whereas higher relative dominance of cognitive aspects was associated with increased connectivity among social-cognitive and interoceptive regions such as brainstem, superior temporal gyrus (STG) (frontotemporal), and aIns (cingulo-opercular).

Personality traits

Personality research has identified five independent domains representing traits that vary substantially across individuals. These domains, as measured by the NEO-PI-R (Costa and McCrae, 1992), are neuroticism, extraversion, openness to experience, agreeableness, and conscientiousness. These personality domains predicted seed-based connectivity of dACC and precuneus with all major networks, as follows (Adelstein et al., 2011): Neuroticism predicted connectivity with dmPFC, middle temporal gyrus, and temporal pole, regions known to be engaged during self-referential processing and fearful anticipation and negative emotion; extraversion predicted connectivity with limbic regions known to be involved in reward and motivation, as well as FG, known to be involved in face processing; openness to experience predicted connectivity with mPFC, PCC/precuneus, and dorsolateral prefrontal cortex (dlPFC), regions involved in processing of the self and the external environment; agreeableness predicted connectivity with posteromedial extrastriate regions and sensorimotor cortex, regions known to be involved in social and emotional attention; and conscientiousness predicted connectivity with medial temporal lobe regions known to be involved in future-oriented processing. In another study that focused upon agreeableness, a temperament trait thought to be associated with reactivity to conflict, connectivity of the PCC with cingulo-opercular (ACC and SMG) and visual (cuneus, left middle occipital, and right lingual gyrus) networks was positively correlated with agreeableness (Ryan et al., 2011). Further, this study found that higher blood pressure responsivity to cognitive demands was associated with connectivity of the ACC, and that this relationship was mediated by agreeableness.

Some behaviors displayed by people with Autism such as difficulty with social interaction/communication, restricted interests, and repetitive behaviors can be considered personality traits that also vary among healthy individuals. Increased autistic-like traits in healthy individuals (measured by the Social Responsiveness Scale [SRS]) were associated with reduced connectivity of a pregenual ACC-default seed with bilateral aIns (part of the cingulo-opercular network) and increased connectivity with left superior parietal lobule (SPL) and lateral occipital cortex (part of the dorsal attention network) and AG (part of the default network) (Di Martino et al., 2009). However, across both groups of subjects with Autism Spectrum Disorders (ASD) and healthy controls, higher autistic traits (measured by the Autism Spectrum Quotient [AQ]) were associated with reduced connectivity within the default network (vmPFC–bilateral AG), even when group membership was factored out (Von dem Hagen et al., 2012). This finding of negative correlation within default regions with autistic traits conflicts with that of Di Martino and colleagues (2009) showing a positive correlation of autistic traits with connectivity within default regions (PCC-AG) and may be attributable to differences in the measure of autistic traits (AQ being self-report and SRS being other report, usually a significant other/family member) or the choice of seed region [an ICA component in Von dem Hagen et al. (2012), but a region of hypoactivation in previous ASD studies in Di Martino et al. (2009)].

The extent to which one is willing to take risks is a personality trait that is associated with psychopathology, such that low- or high-risk seeking predisposes one to anxiety disorders or pathological gambling/addiction, respectively. Higher risk taking (measured by the Cognitive Appraisal of Risky Events Questionnaire [CARE]) was predicted by reduced connectivity between the frontoparietal right IFG node and the cingulo-opercular right aIns node, as well as by more negative connectivity between the left nucleus accumbens, a region involved in reward and motivation, and parieto-occipital regions belonging to three networks (cingulo-opercular: SMG; dorsal attention: lateral occipital cortex and SPL; default: precuneus and AG) (Cox et al., 2010). Thus, the interaction of these different networks at rest is predicted by a personality trait relevant to decision making, cognitive control, and motivational functions.

Summary

Two themes are evident in the results from studies examining associations between resting-state connectivity and behaviors associated with emotional function: First, connectivity of the default network, both within selective nodes and with task-positive or subcortical regions, was associated with behavior regardless of whether it emphasized unitary emotional functions (e.g., anxiety) or those with multiple dimensions that included motivational and cognitive functions. Second, connections showing brain–behavior associations included regions known to subserve socioemotional or sociocognitive functions based upon task-evoked studies.

Depression

Among individuals with major depressive disorder (MDD), increased connectivity within the default network has been consistently associated with severity of the disorder. More severe depressive episodes were also predicted by increased node centrality of the hippocampus (Zhang et al., 2011), as well as by greater connectivity between the hippocampus and the rest of the default network (Goveas et al., 2011a) in older adults. Increased rumination—a key feature of MDD—was predicted by increased connectivity between PCC- and vmPFC-default nodes (Berman et al., 2011), as well as between the ICA-generated default-network component and the vmPFC and prefrontal cortex (Zhu et al., 2012). Longer depressive episodes were predicted by greater connectivity between PCC and vmPFC (Greicius et al., 2007), by increased node centrality of the hippocampus (Zhang et al., 2011), and by reduced ReHo of the precuneus default-network node (Wu et al., 2011a), suggesting that increased long-distance default connectivity in MDD might be accompanied by decreased local connectivity.

By contrast, in a minority of studies, increased default connectivity predicted reduced depressive symptoms, particularly in older adults. Increased connectivity between the ICA-generated default-network component and the precuneus/AG predicted less over-general autobiographical memory (Zhu et al., 2012). In a study examining cognitive impairment associated with MDD, reduced connectivity between the PCC and the cerebellum predicted lower episodic memory (measured by recall for complex figures) in older adults with remitted MDD who were carriers of the angiotensin-converting enzyme D gene, a risk genotype for dementia (Wang et al., 2012b).

A few studies have also found associations between MDD symptoms and connectivity of extra-default regions—both between default and non-default regions and outside the default network entirely. Higher connectivity degree of the amygdala (i.e., greater connectivity to other brain regions) was associated with longer duration of illness among adolescents (Jin et al., 2011). While this approach could not reveal which specific amygdalar circuits are abnormally enhanced in MDD, other work has shown that increased severity of depressive symptoms was associated with increased connectivity between amygdala and default-network regions (precuneus, SFG, and lateral temporal cortex) across both controls and patients with MCI (Xie et al., 2012b). Increased connectivity both within frontoparietal network (between MFG and IFG) as well as between frontoparietal and default networks (between MFG and SFG) predicted longer duration and increased severity of depressive episodes (Zhou et al., 2010b). By contrast, increased connectivity within the cingulo-opercular network predicted greater subsequent remission of depressive symptoms, as well as reduced apathy and dysexecutive behavior, after treatment with escitalopram (Alexopoulos et al., 2012). Finally, increased node centrality of the caudate predicted longer and more severe depressive episodes (Zhang et al., 2011), whereas reduced degree and betweenness centrality of the left dlPFC in the frontoparietal network predicted greater early-life stress, a risk factor for later MDD (Cisler et al., 2012).

Social anxiety disorder

Differences in long-range and local connectivity of default, visual, frontoparietal, frontotemporal, and dorsal attention networks are associated with severity of social anxiety, as measured by the Liebowitz social anxiety scale. Higher social anxiety was associated with increased connectivity of the frontoparietal ICA component in right inferior/orbital gyrus and reduced connectivity of frontoparietal and visual networks in left SPL and inferior occipital gyrus, respectively (Liao et al., 2010). Higher social anxiety was also associated with increased connectivity between the mPFC node of the default network and multiple bilateral nodes of the visual network (e.g., calcarine, lingual, FG, and middle occipital gyri) and reduced connectivity between the mPFC and the right STG node of the frontotemporal network (Ding et al., 2011). Further, local connectivity of the visual, dorsal attention, and frontoparietal networks also showed correlations with anxiety (Qiu et al., 2011). Higher social anxiety was associated with increased ReHo in left middle occipital gyrus and cuneus (nodes of the visual network) and bilateral lateral parietal cortex (nodes of the dorsal attention network), and with reduced ReHo in left dmPFC (part of the default network), bilateral dlPFC (part of the frontoparietal network), and putamen.

Generalized anxiety disorder

Lower anxiety measured by the Beck's Anxiety Inventory was associated with higher connectivity between the amygdala and right dlPFC, part of the frontoparietal network, suggesting compensatory mechanisms drawing upon executive control processes (Etkin et al., 2009).

Obsessive compulsive disorder

Connectivity of default and cingulo-opercular networks with subcortical regions predicted obsessive compulsive disorder (OCD) symptoms, as measured by the Yale-Brown Obsessive Compulsive Scale (Y-BOCS). More severe OCD was predicted by reduced connectivity between the right aIns node of the cingulo-opercular network and right thalamus (Stern et al., 2012), as well as by reduced connectivity between left dorsal caudate and the rostral ACC node of the default network (Fitzgerald et al., 2011). Reduced connectivity between the PCC default-network node and the right putamen predicted higher general anxiety on the Beck anxiety inventory score in patients with OCD (Jang et al., 2010). In contrast, increased connectivity between a ventral striatal seed and right anterior orbital frontal cortex (part of the default network) was associated with more severe OCD symptoms (Harrison et al., 2009).

Default network connectivity, both within-network and its connection with the visual network, was also sensitive to OCD symptoms. Higher Y-BOCS scores in patients with OCD and in substance-abuse patients, separately and together, were associated with reduced global connectivity of the mPFC default-network node (Meunier et al., 2012). Further, connectivity within the default network, between the mPFC and PCC nodes, predicted specific dimensions of the Y-BOCS, such that connectivity was positively correlated with the cleaning dimension, but negatively correlated with the obsessions/checking dimension. Additionally, connectivity between the PCC node and visual network regions was positively correlated with the symmetry dimension (Jang et al., 2010).

Borderline personality disorder

Patients with a higher score on the Dissociative Tension Scale had higher connectivity of the left aIns, a cingulo-opercular node, and lower connectivity of the cuneus, a visual network node (Wolf et al. 2011).

Post-traumatic stress disorder

Connectivity of the default network predicted current as well as prospective symptom severity (Lanius et al., 2010). Specifically, increased connectivity between the PCC and pregenual ACC nodes was associated with more severe post-traumatic stress disorder (PTSD) symptoms, as measured by the Clinician-Administered PTSD Scale at the time of scanning. Further, increased connectivity between the PCC node and the right amygdala was associated with more severe symptoms 6 weeks later.

Drug addiction

Substance dependence can alter the functional connectivity of the brain, and that altered connectivity has been shown to predict behavioral consequences of the substance dependence in three different domains. First, the strength of functional connectivity has been associated with the severity of the dependence and with the amount of previous substance use. In nicotine-addicted individuals, reduced connectivity between the cingulo-opercular network and bilateral putamen predicted more severe nicotine addiction (Hong et al., 2009). In individuals addicted to the analgesic ketamine, decreased ReHo in the somatomotor network predicted both increased cravings for ketamine and increased total lifetime usage of ketamine (Liao et al., 2012). In heroin-dependent individuals, greater degree of connectivity in the PHC node of the default network, in putamen, and in the cerebellum was associated with longer previous heroin use, while shorter absolute path length in the same regions was also associated with longer previous heroin use (Yuan et al., 2010).

Second, the strength of connectivity has been associated with success in abstaining from the substance. In alcohol-dependent subjects, a longer time remaining sober was associated with greater local efficiency in the cerebellum (Chanraud et al., 2011), while in nicotine-dependent subjects undergoing nicotine replacement, greater nicotine administration-induced reductions in connectivity between default and cingulo-opercular networks predicted greater reductions in withdrawal symptoms such as difficulty concentrating (Cole et al., 2010).

Third, the strength of connectivity has been associated with the cognitive sequelae of the addiction, with abnormally increased connectivity commonly predicting impaired cognition. In cocaine-dependent individuals, greater connectivity between default and frontoparietal networks predicted worse performance on tasks measuring reward-based decision making (e.g., reversal learning and delay discounting) (Camchong et al., 2011).

Autism spectrum disorders

ASD symptoms are associated with default-network connectivity, although the specific nature of findings is mixed across studies. Worse social interaction measured by the Autism Diagnostic Interview (ADI) was consistently associated with reduced default-network connectivity, including between the PCC and SFG nodes (Monk et al., 2009; Weng et al., 2010), and between lateral temporal and PHC-default nodes (Weng et al., 2010). However, for symptoms in the communication domain, findings vary across studies. Worse social communication, measured by the Autism Disorder Observation Schedule or the SRS, was associated with reduced connectivity within a default ICA component (Assaf et al., 2010) and reduced connectivity between default network and the amygdala, frontotemporal, and dorsal attention networks (Gotts et al., 2012). However, verbal communication, as measured by the ADI, was associated with increased connectivity of the PCC-default node with temporal nodes (bilateral lateral temporal lobe and right PHC), and nonverbal communication was associated with increased connectivity between bilateral SFG and lateral temporal lobe-default nodes (Weng et al., 2010). Findings for repetitive behaviors are also mixed, such that more repetitive behaviors were associated with reduced connectivity between PCC and frontal-temporal default nodes (including bilateral SFG, temporal lobe, vmPFC, and dmPFC) (Weng et al., 2010), but with increased connectivity between PCC- and right hippocampal default nodes (Monk et al., 2009). One important difference across studies is the composition of samples, with some studies including only adults or adolescents or children, and others a wide range including adolescents and adults.

Behavioral-variant frontotemporal dementia

Fronto-temporal dementia is a broad class of neurological disorders involving significant neural degeneration in frontal and temporal lobes. Behavioral-variant frontotemporal dementia is a disorder involving disruptions in social–emotional functioning and control of behavior, which has been linked specifically to degeneration in the cingulo-opercular network (Seeley, 2008). Patients with worse symptoms had reduced connectivity of the cingulo-opercular network and increased connectivity within the default network (Zhou et al., 2010a), suggesting that cingulo-opercular disruption may have resulted in reciprocal enhancements in default function.

Summary

Three general observations emerge across a wide variety of conditions that are defined by emotional dysfunction: First, connectivity of the default network, either within its nodes or with task-positive network regions, was associated with disorder severity. While this may be an artifact of methodological approach, as most studies have focused upon default network regions exclusively, it may also highlight the central role that putative default-network functions such as self-referential processing and autobiographical memory may play in disorders of emotion. Second, connectivity with the cingulo-opercular network was the second most commonly observed network predicting symptom domains. This finding is not surprising, as functions thought to be subserved by the network, including detection of salience, interoceptive processing, and set maintenance, are part of the cognitive sequelae of many of the reviewed disorders. Third, across diverse disorders, symptom domains showed associations with connectivity of visual network regions. While this finding was not expected because visual regions are not commonly implicated in emotional functioning, it highlights the fact that connectivity studies may provide a new insight into behavioral function.