Large-scale Intrinsic Connectivity Networks Research Articles

Sex-dependent structure of socioemotional salience, executive control, and default mode networks in preschool-aged children with autism

The structure of large-scale intrinsic connectivity networks is atypical in adolescents diagnosed with autism spectrum disorder (ASD or autism). However, the degree to which alterations occur in younger children, and whether these differences vary by sex, is unknown. We utilized structural magnetic resonance imaging (MRI) data from a sex- and age- matched sample of 122 autistic and 122 typically developing (TD) children (2–4 years old) to investigate differences in underlying network structure in preschool-aged autistic children within three large scale intrinsic connectivity networks implicated in ASD: the Socioemotional Salience, Executive Control, and Default Mode Networks. Utilizing structural covariance MRI (scMRI), we report network-level differences in autistic versus TD children, and further report preliminary findings of sex-dependent differences within network topology.

Alterations in Large-Scale Intrinsic Connectivity Networks in the Parkinson's Disease-Associated Cognitive Impairment Continuum: A Systematic Review.

Cognitive impairment is common in the course of Parkinson's disease (PD) and displays a continuum from subjective cognitive impairment to dementia. Illuminating the pathophysiological processes associated with the continuum may help create follow-up and new treatment approaches. In this context, large-scale intrinsic connectivity networks are widely investigated to elucidate the neural processes underlying PD and are promising as non-invasive biomarkers. This systematic review aims to examine the alterations in large-scale intrinsic connectivity networks in the continuum of PD-associated cognitive impairment. ScienceDirect, Web of Science, and PubMed databases were searched with the specified keywords. The studies obtained as a result of this review were investigated by the PRISMA criteria, which were taken as a basis for the systematic review and writing of meta-analyses. A total of 974 studies were obtained from three databases. Twenty studies were included in the systematic review based on predetermined eligibility criteria. Among the large-scale connectivity networks examined in these studies, it was found that sensory-motor networks decreased their connectivity in the continuum of PD-associated cognitive impairment, and there were conflicting results in terms of cognitive networks. Well-designed longitudinal studies are needed to clarify the alterations in the intrinsic connectivity networks in the PD cognitive impairment continuum. In these studies, it is necessary to define the cognitive disorder groups well, to control the connectivity changes that may occur due to dopaminergic treatment, and to evaluate Parkinson's patients with subjective cognitive impairment and dementia within the continuum.

Large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder.

Accumulating evidence suggests brain network dysfunction in attention-deficit/hyperactivity disorder (ADHD). Whether large-scale brain network connectivity patterns reflect clinical heterogeneity in ADHD remains to be fully understood. This study aimed to characterize the differential within- and between-network functional connectivity (FC) changes in children with ADHD combined (ADHD-C) or inattentive (ADHD-I) subtypes and their associations with ADHD symptoms. We studied the task-free functional magnetic resonance imaging (fMRI) data of 58 boys with ADHD and 28 demographically matched healthy controls. We measured within- and between-network connectivity of both low-level (sensorimotor) and high-level (cognitive) large-scale intrinsic connectivity networks and network modularity. We found that children with ADHD-C but not those with ADHD-I exhibited hyper-connectivity within the anterior default mode network (DMN) compared with controls. Additionally, children with ADHD-C had higher inter-network FC between the left executive control (ECN) and the salience (SN) networks, between subcortical and visual networks, and between the DMN and left auditory networks than controls, while children with ADHD-I did not show differences compared with controls. Similarly, children with ADHD-C but not ADHD-I showed lower network modularity compared with controls. Importantly, these observed abnormal inter-network connectivity and network modularity metrics were associated with Child Behavioral Checklist (CBCL) attention-deficit/hyperactivity problems and internalizing problems in children with ADHD. This study revealed relatively greater loss of brain functional network segregation in childhood ADHD combined subtype compared to the inattentive subtype, suggesting differential large-scale functional brain network topology phenotype underlying childhood ADHD heterogeneity.

Brain state and polarity dependent modulation of brain networks by transcranial direct current stimulation.

Despite its widespread use in cognitive studies, there is still limited understanding of whether and how transcranial direct current stimulation (tDCS) modulates brain network function. To clarify its physiological effects, we assessed brain network function using functional magnetic resonance imaging (fMRI) simultaneously acquired during tDCS stimulation. Cognitive state was manipulated by having subjects perform a Choice Reaction Task or being at “rest.” A novel factorial design was used to assess the effects of brain state and polarity. Anodal and cathodal tDCS were applied to the right inferior frontal gyrus (rIFG), a region involved in controlling activity large‐scale intrinsic connectivity networks during switches of cognitive state. tDCS produced widespread modulation of brain activity in a polarity and brain state dependent manner. In the absence of task, the main effect of tDCS was to accentuate default mode network (DMN) activation and salience network (SN) deactivation. In contrast, during task performance, tDCS increased SN activation. In the absence of task, the main effect of anodal tDCS was more pronounced, whereas cathodal tDCS had a greater effect during task performance. Cathodal tDCS also accentuated the within‐DMN connectivity associated with task performance. There were minimal main effects of stimulation on network connectivity. These results demonstrate that rIFG tDCS can modulate the activity and functional connectivity of large‐scale brain networks involved in cognitive function, in a brain state and polarity dependent manner. This study provides an important insight into mechanisms by which tDCS may modulate cognitive function, and also has implications for the design of future stimulation studies.

Alterations of Intrinsic Connectivity Networks in Antipsychotic-Naïve First-Episode Schizophrenia.

BackgroundThe investigation of large-scale intrinsic connectivity networks in antipsychotic-naïve first-episode schizophrenia increases our understanding of system-level cerebral dysfunction in schizophrenia while enabling control of confounding effects of medication and disease progression. Reports on functional connectivity in antipsychotic-naïve patients have been mixed and the relation between network alterations, psychopathology and cognition is unclear.MethodsA total number of 47 patients with first-episode schizophrenia who had never received antipsychotic medication and 47 healthy controls were scanned with functional magnetic resonance imaging under resting conditions. Main outcome measures were differences in functional connectivity between groups and the relationship between network alterations, psychopathology and cognition.ResultsAltered connectivity was found between right central executive network (CEN) and right ventral attention network (VAN) (patients > controls, P = .001), left CEN and left VAN (P = .002), and between posterior default mode network and auditory network (P = .006). Association between network connectivity and clinical characteristics was found as interactions between the effects of group and sustained attention (P = .005) and between group and processing speed (P = .007) on the connectivity between right CEN and right VAN.ConclusionsOur findings suggest that the early phase of schizophrenia is characterized by increased connectivity between fronto-parietal networks suggested to be involved in the control of cognitive and sensory functions. Moreover, the present study suggests that the problem of not disengaging the VAN leads to difficulties with attention and possibly subjective awareness.

Predictive models of minimal hepatic encephalopathy for cirrhotic patients based on large-scale brain intrinsic connectivity networks

We aimed to find the most representative connectivity patterns for minimal hepatic encephalopathy (MHE) using large-scale intrinsic connectivity networks (ICNs) and machine learning methods. Resting-state fMRI was administered to 33 cirrhotic patients with MHE and 43 cirrhotic patients without MHE (NMHE). The connectivity maps of 20 ICNs for each participant were obtained by dual regression. A Bayesian machine learning technique, called Graphical Model-based Multivariate Analysis, was applied to determine ICN regions that characterized group differences. The most representative ICNs were evaluated by the performance of three machine learning methods (support vector machines (SVMs), multilayer perceptrons (MLP), and C4.5). The clinical significance of these potential biomarkers was further tested. The temporal lobe network (TLN), and subcortical network (SCN), and sensorimotor network (SMN) were selected as representative ICNs. The distinct functional integration patterns of the representative ICNs were significantly correlated with behavior criteria and Child-Pugh scores. Our findings suggest the representative ICNs based on GAMMA can distinguish MHE from NMHE and provide supplementary information to current MHE diagnostic criteria.

19 Brain imaging after tbi

Professor David Sharp is a consultant neurologist and was awarded one of the UKs first round of National Institute of Health Research (NIHR) Professorships. He is the Head of the Centre for Restorative Neuroscience at Imperial and Scientific Director of the Imperial College Clinical Imaging Facility. His research programme aims to improve clinical outcome after traumatic brain injury (TBI), focusing on common cognitive impairments in domains such as memory and attention. He uses advanced neuroimaging to investigate the effect of brain injury on brain network function and the effects of inflammation and neurodegeneration after TBI. His NIHR research programme will use changes in network function to guide the development of novel treatment strategies for cognitive impairment. He leads TBI research within the Royal British Legion Centre for Blast Injury Studies and collaborates with The Royal Centre for Defence Medicine to study the effects of blast exposure military personnel. Diffuse axonal injury after traumatic brain injury (TBI) produces neurological impairment by disconnecting brain networks. This structural damage can be mapped using diffusion MRI, and its functional effects can be investigated in large-scale intrinsic connectivity networks (ICNs). Here, we review evidence that TBI substantially disrupts ICN function, and that this disruption predicts cognitive impairment. We focus on two ICNs—the salience network and the default mode network. The activity of these ICNs is normally tightly coupled, which is important for attentional control. Damage to the structural connectivity of these networks produces predictable abnormalities of network function and cognitive control. For example, the brain normally shows a ‘small-world architecture’ that is optimised for information processing, but TBI shifts network function away from this organisation. The effects of TBI on network function are likely to be complex, and we discuss how advanced approaches to modelling brain dynamics can provide insights into the network dysfunction. We highlight how structural network damage caused by axonal injury might interact with neuroinflammation and neurodegeneration in the pathogenesis of Alzheimer disease and chronic traumatic encephalopathy, which are late complications of TBI. Finally, we discuss how network-level diagnostics could inform diagnosis, prognosis and treatment development following TBI. Reference . David J Sharp, et al. Network dysfunction after traumatic brain injury. Nature Reviews Neurology2014;10:156–166. Published online 11 February 2014.

Mind-Body Practice Changes Fractional Amplitude of Low Frequency Fluctuations in Intrinsic Control Networks.

Cognitive control impairment is a typical symptom largely reported in populations with neurological disorders. Previous studies have provided evidence about the changes in cognitive control induced by mind-body training. However, the neural correlates underlying the effect of extensive mind-body practice on cognitive control remain largely unknown. Using resting-state functional magnetic resonance imaging, we characterized dynamic fluctuations in large-scale intrinsic connectivity networks associated with mind-body practice, and examined their differences between healthy controls and Tai Chi Chuan (TCC) practitioners. Compared with a control group, the TCC group revealed significantly decreased fractional Amplitude of Low Frequency Fluctuations (fALFF) in the bilateral frontoparietal network, default mode network and dorsal prefrontal-angular gyri network. Furthermore, we detected a significant association between mind-body practice experience and fALFF in the default mode network, as well as an association between cognitive control performance and fALFF of the frontoparietal network. This provides the first evidence of large-scale functional connectivity in brain networks associated with mind-body practice, shedding light on the neural network changes that accompany intensive mind-body training. It also highlights the functionally plastic role of the frontoparietal network in the context of the “immune system” of mental health recently developed in relation to flexible hub theory.

Exploring influence of subliminal interoception on whole-brain functional network connectivity dynamics.

Recent fMRI studies have highlighted a dynamic relation across large-scale intrinsic connectivity networks (ICNs) of human brain. The origin of such temporal variations in functional connectivity especially during the task-free (resting-state) fMRI is still a matter of debate and ongoing investigation. In this exploratory study, we sought to determine whether subliminal differences in interoception (e.g., distention pressure on the viscera) can influence the dynamics of whole-brain functional network connectivity. A group of healthy right-handed female subjects, close in age (n = 15, mean age ± SD = 30.33 ± 8.7 years) underwent a series of eyes-open resting-state fMRI scans under different interoceptive conditions including catheterization and partial bladder filling. Using a high-dimensional independent component analysis, the functional imaging data were parcellated into 75 components, out of which 33 were identified as non-artifactual ICNs. Changes in dynamic functional network connectivity (dFNC) were evaluated using the sliding-time window approach and k-means clustering algorithm. We used subject medians for each cluster state and compared differences in dFNC correlations using a paired t-test. Following a false discovery rate multiple comparison correction threshold of p<;0.05, no significant differences in dFNC were found. However, different dwell times for each (pseudo-)resting-state were observed. More liberal statistical criteria (uncorrected p<;0.005) also indicated differences in dFNC between ICN pairs especially involving the salience, subcortical, sensorimotor, cerebellar and brainstem networks. Further investigations of the effect of internal (bodily) sensations on the time-varying aspects of functional connectivity can improve our understanding of the nature of temporal fluctuations in interrelations between intrinsic brain networks.

Intrinsic Connectivity Networks in post-traumatic stress disorder during sub- and supraliminal processing of threat-related stimuli.

To investigate the functional connectivity of large-scale intrinsic connectivity networks (ICNs) in post-traumatic stress disorder (PTSD) during subliminal and supraliminal presentation of threat-related stimuli. Group independent component analysis was utilized to study functional connectivity within the ICNs most correlated with the Default-mode Network (DMN), Salience Network (SN), and Central Executive Network (CEN) in PTSD participants (n = 26) as compared to healthy controls (n = 20) during sub- and supraliminal processing of threat-related stimuli. Comparing patients with PTSD with healthy participants, prefrontal and anterior cingulate cortex involved in top-down regulation showed increased integration during subliminal threat processing within the CEN and SN and during supraliminal threat processing within the DMN. The right amygdala showed increased connectivity with the DMN during subliminal processing in PTSD as compared to controls. Brain regions associated with self-awareness and consciousness exhibited decreased connectivity during subliminal threat processing in PTSD as compared to controls: the claustrum within the SN and the precuneus within the DMN. Key nodes of the ICNs showed altered functional connectivity in PTSD as compared to controls, and differential results characterized sub- and supraliminal processing of threat-related stimuli. These findings enhance our understanding of ICNs underlying PTSD at different levels of conscious threat perception.

Regional amyloid burden and intrinsic connectivity networks in cognitively normal elderly subjects.

Although previous studies demonstrated decreased functional connectivity in the default mode network in the cognitively normal older adults with amyloid burden, effects of amyloid burden in the other large-scale intrinsic connectivity networks are not yet clear. The aim of this study was to investigate the distinctive association pattern of amyloid-β deposition on the three large-scale intrinsic connectivity networks (the default mode network, salience network and central executive network) in older adults with normal cognition. Fifty-six older adults with normal cognition underwent functional magnetic resonance imaging and were dichotomized using 11C-labelled Pittsburgh compound B positron emission tomography imaging into subjects with (PiB+; n=27) and without (PiB-; n=29) detectable amyloid burden. We found that the functional connectivities of (i) the default mode network were greater; (ii) the salience network were not different; and (iii) the central executive network were lower in the Pittsburgh compound B positive group, compared with the Pittsburgh compound B negative group. Anterior cingulate cortex Pittsburgh compound B retention was negatively correlated with the functional connectivities of the posterior default mode network, and positively correlated with fronto-parietal functional connectivity (within the central executive network) in the Pittsburgh compound B positive group. The anti-correlation strength between the default mode network and the central executive network was negatively correlated with the anterior cingulate cortex Pittsburgh compound B levels. Additionally, significant group × episodic memory interactions with functional connectivities in the posterior default mode network, and the frontal default mode network were observed. Our results of aberrant default mode network functional connectivity and distinctive correlation patterns between the Pittsburgh compound B retention in the anterior cingulate cortex and functional connectivities in the default mode network and central executive network in the Pittsburgh compound B positive group might reflect a detrimental effect of amyloid retention on functional changes in the course of Alzheimer's disease progression.

Disrupted Intrinsic Networks Link Amyloid-β Pathology and Impaired Cognition in Prodromal Alzheimer's Disease.

Amyloid-β pathology (Aβ) and impaired cognition characterize Alzheimer's disease (AD); however, neural mechanisms that link Aβ-pathology with impaired cognition are incompletely understood. Large-scale intrinsic connectivity networks (ICNs) are potential candidates for this link: Aβ-pathology affects specific networks in early AD, these networks show disrupted connectivity, and they process specific cognitive functions impaired in AD, like memory or attention. We hypothesized that, in AD, regional changes of ICNs, which persist across rest- and cognitive task-states, might link Aβ-pathology with impaired cognition via impaired intrinsic connectivity. Pittsburgh compound B (PiB)-positron emission tomography reflecting in vivo Aβ-pathology, resting-state fMRI, task-fMRI, and cognitive testing were used in patients with prodromal AD and healthy controls. In patients, default mode network's (DMN) functional connectivity (FC) was reduced in the medial parietal cortex during rest relative to healthy controls, relatively increased in the same region during an attention-demanding task, and associated with patients' cognitive impairment. Local PiB-uptake correlated negatively with DMN connectivity. Importantly, corresponding results were found for the right lateral parietal region of an attentional network. Finally, structural equation modeling confirmed a direct influence of DMN resting-state FC on the association between Aβ-pathology and cognitive impairment. Data provide evidence that disrupted intrinsic network connectivity links Aβ-pathology with cognitive impairment in early AD.

Network dysfunction after traumatic brain injury

Diffuse axonal injury after traumatic brain injury (TBI) produces neurological impairment by disconnecting brain networks. This structural damage can be mapped using diffusion MRI, and its functional effects can be investigated in large-scale intrinsic connectivity networks (ICNs). Here, we review evidence that TBI substantially disrupts ICN function, and that this disruption predicts cognitive impairment. We focus on two ICNs--the salience network and the default mode network. The activity of these ICNs is normally tightly coupled, which is important for attentional control. Damage to the structural connectivity of these networks produces predictable abnormalities of network function and cognitive control. For example, the brain normally shows a 'small-world architecture' that is optimized for information processing, but TBI shifts network function away from this organization. The effects of TBI on network function are likely to be complex, and we discuss how advanced approaches to modelling brain dynamics can provide insights into the network dysfunction. We highlight how structural network damage caused by axonal injury might interact with neuroinflammation and neurodegeneration in the pathogenesis of Alzheimer disease and chronic traumatic encephalopathy, which are late complications of TBI. Finally, we discuss how network-level diagnostics could inform diagnosis, prognosis and treatment development following TBI.

Intrinsic functional connectivity networks in healthy elderly subjects: a multiparametric approach with structural connectivity analysis.

Intrinsic functional connectivity magnetic resonance imaging (iFCMRI) provides an encouraging approach for mapping large-scale intrinsic connectivity networks (ICNs) in the “resting” brain. Structural connections as measured by diffusion tensor imaging (DTI) are a major constraint on the identified ICNs. This study aimed at the combined investigation of ten well-defined ICNs in healthy elderly subjects at single subject level as well as at the group level, together with the underlying structural connectivity. IFCMRI and DTI data were acquired in twelve subjects (68 ± 7 years) at a 3T scanner and were studied using the tensor imaging and fiber tracking software package. The seed-based iFCMRI analysis approach was comprehensively performed with DTI analysis, following standardized procedures including an 8-step processing of iFCMRI data. Our findings demonstrated robust ICNs at the single subject level and conclusive brain maps at the group level in the healthy elderly sample, supported by the complementary fiber tractography. The findings demonstrated here provide a methodological framework for future comparisons of pathological (e.g., neurodegenerative) conditions with healthy controls on the basis of multiparametric functional connectivity mapping.

Volitional regulation of emotions produces distributed alterations in connectivity between visual, attention control, and default networks

The ability to volitionally regulate emotions is critical to health and well-being. While patterns of neural activation during emotion regulation have been well characterized, patterns of connectivity between regions remain less explored. It is increasingly recognized that the human brain is organized into large-scale intrinsic connectivity networks (ICNs) whose interrelationships are altered in characteristic ways during psychological tasks. In this fMRI study of 54 healthy individuals, we investigated alterations in connectivity within and between ICNs produced by the emotion regulation strategy of reappraisal. In order to gain a comprehensive picture of connectivity changes, we utilized connectomic psychophysiological interactions (PPI), a whole-brain generalization of standard single-seed PPI methods. In particular, we quantified PPI connectivity pair-wise across 837 ROIs placed throughout the cortex. We found that compared to maintaining one's emotional responses, engaging in reappraisal produced robust and distributed alterations in functional connections involving visual, dorsal attention, frontoparietal, and default networks. Visual network in particular increased connectivity with multiple ICNs including dorsal attention and default networks. We interpret these findings in terms of the role of these networks in mediating critical constituent processes in emotion regulation, including visual processing, stimulus salience, attention control, and interpretation and contextualization of stimuli. Our results add a new network perspective to our understanding of the neural underpinnings of emotion regulation, and highlight that connectomic methods can play a valuable role in comprehensively investigating modulation of connectivity across task conditions.