A MATLAB toolbox for multivariate analysis of brain networks

Complex brain networks formed via structural and functional interactions among brain regions are believed to underlie information processing and cognitive function. A growing number of studies indicate that altered brain network topology is associated with physiological, behavioral, and cognitive abnormalities. Graph theory is showing promise as a method for evaluating and explaining brain networks. However, multivariate frameworks that provide statistical inferences about how such networks relate to covariates of interest, such as disease phenotypes, in different study populations are yet to be developed. We have developed a freely available MATLAB toolbox with a graphical user interface that bridges this important gap between brain network analyses and statistical inference. The modeling framework implemented in this toolbox utilizes a mixed‐effects multivariate regression framework that allows assessing brain network differences between study populations as well as assessing the effects of covariates of interest such as age, disease phenotype, and risk factors on the density and strength of brain connections in global (i.e., whole‐brain) and local (i.e., subnetworks) brain networks. Confounding variables, such as sex, are controlled for through the implemented framework. A variety of neuroimaging data such as fMRI, EEG, and DTI can be analyzed with this toolbox, which makes it useful for a wide range of studies examining the structure and function of brain networks. The toolbox uses SAS, R, or Python (depending on software availability) to perform the statistical modeling. We also provide a clustering‐based data reduction method that helps with model convergence and substantially reduces modeling time for large data sets.     

Reorganization of functionally connected brain subnetworks in high‐functioning autism

Previous functional connectivity studies have found both hypo‐ and hyper‐connectivity in brains of individuals having autism spectrum disorder (ASD). Here we studied abnormalities in functional brain subnetworks in high‐functioning individuals with ASD during free viewing of a movie containing social cues and interactions. Twenty‐six subjects (13 with ASD) watched a 68‐min movie during functional magnetic resonance imaging. For each subject, we computed Pearson's correlation between haemodynamic time‐courses of each pair of 6‐mm isotropic voxels. From the whole‐brain functional networks, we derived individual and group‐level subnetworks using graph theory. Scaled inclusivity was then calculated between all subject pairs to estimate intersubject similarity of connectivity structure of each subnetwork. Additional 54 individuals (27 with ASD) from the ABIDE resting‐state database were included to test the reproducibility of the results. Between‐group differences were observed in the composition of default‐mode and ventro‐temporal‐limbic (VTL) subnetworks. The VTL subnetwork included amygdala, striatum, thalamus, parahippocampal, fusiform, and inferior temporal gyri. Further, VTL subnetwork similarity between subject pairs correlated significantly with similarity of symptom gravity measured with autism quotient. This correlation was observed also within the controls, and in the reproducibility dataset with ADI‐R and ADOS scores. Our results highlight how the reorganization of functional subnetworks in individuals with ASD clarifies the mixture of hypo‐ and hyper‐connectivity findings. Importantly, only the functional organization of the VTL subnetwork emerges as a marker of inter‐individual similarities that co‐vary with behavioral measures across all participants. These findings suggest a pivotal role of ventro‐temporal and limbic systems in autism. Hum Brain Mapp 37:1066–1079, 2016. © 2015 Wiley Periodicals, Inc .     

The independent influences of age and education on functional brain networks and cognition in healthy older adults

Healthy aging is accompanied by a constellation of changes in cognitive processes and alterations in functional brain networks. The relationships between brain networks and cognition during aging in later life are moderated by demographic and environmental factors, such as prior education, in a poorly understood manner. Using multivariate analyses, we identified three latent patterns (or modes) linking resting‐state functional connectivity to demographic and cognitive measures in 101 cognitively normal elders. The first mode (P = 0.00043) captures an opposing association between age and core cognitive processes such as attention and processing speed on functional connectivity patterns. The functional subnetwork expressed by this mode links bilateral sensorimotor and visual regions through key areas such as the parietal operculum. A strong, independent association between years of education and functional connectivity loads onto a second mode (P = 0.012), characterized by the involvement of key hub regions. A third mode (P = 0.041) captures weak, residual brain–behavior relations. Our findings suggest that circuits supporting lower level cognitive processes are most sensitive to the influence of age in healthy older adults. Education, and to a lesser extent, executive functions, load independently onto functional networks—suggesting that the moderating effect of education acts upon networks distinct from those vulnerable with aging. This has important implications in understanding the contribution of education to cognitive reserve during healthy aging. Hum Brain Mapp 38:5094–5114, 2017. © 2017 Wiley Periodicals, Inc.     

Fronto‐Parietal Subnetworks Flexibility Compensates For Cognitive Decline Due To Mental Fatigue

Fronto‐parietal subnetworks were revealed to compensate for cognitive decline due to mental fatigue by community structure analysis. Here, we investigate changes in topology of subnetworks of resting‐state fMRI networks due to mental fatigue induced by prolonged performance of a cognitively demanding task, and their associations with cognitive decline. As it is well established that brain networks have modular organization, community structure analyses can provide valuable information about mesoscale network organization and serve as a bridge between standard fMRI approaches and brain connectomics that quantify the topology of whole brain networks. We developed inter‐ and intramodule network metrics to quantify topological characteristics of subnetworks, based on our hypothesis that mental fatigue would impact on functional relationships of subnetworks. Functional networks were constructed with wavelet correlation and a data‐driven thresholding scheme based on orthogonal minimum spanning trees, which allowed detection of communities with weak connections. A change from pre‐ to posttask runs was found for the intermodule density between the frontal and the temporal subnetworks. Seven inter‐ or intramodule network metrics, mostly at the frontal or the parietal subnetworks, showed significant predictive power of individual cognitive decline, while the network metrics for the whole network were less effective in the predictions. Our results suggest that the control‐type fronto‐parietal networks have a flexible topological architecture to compensate for declining cognitive ability due to mental fatigue. This community structure analysis provides valuable insight into connectivity dynamics under different cognitive states including mental fatigue.     

Network component analysis reveals developmental trajectories of structural connectivity and specific alterations in autism spectrum disorder

The structural organization of the brain can be characterized as a hierarchical ensemble of segregated modules linked by densely interconnected hub regions that facilitate distributed functional interactions. Disturbances to this network may be an important marker of abnormal development. Recently, several neurodevelopmental disorders, including autism spectrum disorder (ASD), have been framed as disorders of connectivity but the full nature and timing of these disturbances remain unclear. In this study, we use non‐negative matrix factorization, a data‐driven, multivariate approach, to model the structural network architecture of the brain as a set of superposed subnetworks, or network components. In an openly available dataset of 196 subjects scanned between 5 and 85 years we identify a set of robust and reliable subnetworks that develop in tandem with age and reflect both anatomically local and long‐range, network hub connections. In a second experiment, we compare network components in a cohort of 51 high‐functioning ASD adolescents to a group of age‐matched controls. We identify a specific subnetwork representing an increase in local connection strength in the cingulate cortex in ASD (t = 3.44, P < 0.001). This work highlights possible long‐term implications of alterations to the developmental trajectories of specific cortical subnetworks. Hum Brain Mapp 38:4169–4184, 2017. © 2017 Wiley Periodicals, Inc.     

Different brain networks underlying intelligence in autism spectrum disorders

There has been sustained clinical and cognitive neuroscience research interest in how network correlates of brain‐behavior relationships might be altered in Autism Spectrum Disorders (ASD) and other neurodevelopmental disorders. As previous work has mostly focused on adults, the nature of whole‐brain connectivity networks underlying intelligence in pediatric cohorts with abnormal neurodevelopment requires further investigation. We used network‐based statistics (NBS) to examine the association between resting‐state functional Magnetic Resonance Imaging (fMRI) connectivity and fluid intelligence ability in male children (n = 50) with Autism Spectrum Disorders (ASD; M = 10.45, SD = 1.58 years and in controls (M = 10.38, SD = 0.96 years) matched on fluid intelligence performance, age and sex. Repeat analyses were performed in independent sites for validation and replication. Despite being equivalent on fluid intelligence ability to strictly matched neurotypical controls, boys with ASD displayed a subnetwork of significantly increased associations between functional connectivity and fluid intelligence. Between‐group differences remained significant at higher edge thresholding, and results were validated in independent‐site replication analyses in an equivalent age and sex‐matched cohort with ASD. Regions consistently implicated in atypical connectivity correlates of fluid intelligence in ASD were the angular gyrus, posterior middle temporal gyrus, occipital and temporo‐occipital regions. Development of fluid intelligence neural correlates in young ASD males is aberrant, with an increased strength in intrinsic connectivity association during childhood. Alterations in whole‐brain network correlates of fluid intelligence in ASD may be a compensatory mechanism that allows equal task performance to neurotypical peers.     

Altered structural and functional brain network overall organization predict human intertemporal decision‐making

Intertemporal decision‐making is naturally ubiquitous to us: individuals always make a decision with different consequences occurring at different moments. These choices are invariably involved in life‐changing outcomes regarding marriage, education, fertility, long‐term well‐being, and even public policy. Previous studies have clearly uncovered the neurobiological mechanism of the intertemporal decision in the schemes of regional location or sub‐network. However, it still remains unclear how to characterize intertemporal behavior with multimodal whole‐brain network metrics to date. Here, we combined diffusion tensor image and resting‐state functional connectivity MRI technology, in conjunction with graph‐theoretical analysis, to explore the link between topological properties of integrated structural and functional whole‐brain networks and intertemporal decision‐making. Graph‐theoretical analysis illustrated that the participants with steep discounting rates exhibited the decreased global topological organizations including small‐world and rich‐club regimes in both functional and structural connectivity networks, and reflected the dreadful local topological dynamics in the modularity of functional connectome. Furthermore, in the cross‐modalities configuration, the same relationship was predominantly observed for the coupling of structural–functional connectivity as well. Above topological metrics are commonly indicative of the communication pattern of simultaneous global and local parallel information processing, and it thus reshapes our accounts on intertemporal decision‐making from functional regional/sub‐network scheme to multimodal brain overall organization.     

On the integrity of functional brain networks in schizophrenia,Parkinson's disease,and advanced age: Evidence from connectivity‐based single‐subject classification

Previous whole‐brain functional connectivity studies achieved successful classifications of patients and healthy controls but only offered limited specificity as to affected brain systems. Here, we examined whether the connectivity patterns of functional systems affected in schizophrenia (SCZ), Parkinson's disease (PD), or normal aging equally translate into high classification accuracies for these conditions. We compared classification performance between pre‐defined networks for each group and, for any given network, between groups. Separate support vector machine classifications of 86 SCZ patients, 80 PD patients, and 95 older adults relative to their matched healthy/young controls, respectively, were performed on functional connectivity in 12 task‐based, meta‐analytically defined networks using 25 replications of a nested 10‐fold cross‐validation scheme. Classification performance of the various networks clearly differed between conditions, as those networks that best classified one disease were usually non‐informative for the other. For SCZ, but not PD, emotion‐processing, empathy, and cognitive action control networks distinguished patients most accurately from controls. For PD, but not SCZ, networks subserving autobiographical or semantic memory, motor execution, and theory‐of‐mind cognition yielded the best classifications. In contrast, young–old classification was excellent based on all networks and outperformed both clinical classifications. Our pattern‐classification approach captured associations between clinical and developmental conditions and functional network integrity with a higher level of specificity than did previous whole‐brain analyses. Taken together, our results support resting‐state connectivity as a marker of functional dysregulation in specific networks known to be affected by SCZ and PD, while suggesting that aging affects network integrity in a more global way. Hum Brain Mapp 38:5845–5858, 2017. © 2017 Wiley Periodicals, Inc.     

Reliable local dynamics in the brain across sessions are revealed by whole‐brain modeling of resting state activity

Resting state fMRI is a tool for studying the functional organization of the human brain. Ongoing brain activity at “rest” is highly dynamic, but procedures such as correlation or independent component analysis treat functional connectivity (FC) as if, theoretically, it is stationary and therefore the fluctuations observed in FC are thought as noise. Consequently, FC is not usually used as a single‐subject level marker and it is limited to group studies. Here we develop an imaging‐based technique capable of reliably portraying information of local dynamics at a single‐subject level by using a whole‐brain model of ongoing dynamics that estimates a local parameter, which reflects if each brain region presents stable, asynchronous or transitory oscillations. Using 50 longitudinal resting‐state sessions of one single subject and single resting‐state sessions from a group of 50 participants we demonstrate that brain dynamics can be quantified consistently with respect to group dynamics using a scanning time of 20 min. We show that brain hubs are closer to a transition point between synchronous and asynchronous oscillatory dynamics and that dynamics in frontal areas have larger heterogeneity in its values compared to other lobules. Nevertheless, frontal regions and hubs showed higher consistency within the same subject while the inter‐session variability found in primary visual and motor areas was only as high as the one found across subjects. The framework presented here can be used to study functional brain dynamics at group and, more importantly, at individual level, opening new avenues for possible clinical applications.     

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.     

Partitioning heritability analyses unveil the genetic architecture of human brain multidimensional functional connectivity patterns

Resting‐state functional connectivity profiles have been increasingly shown to be important endophenotypes that are tightly linked to human cognitive functions and psychiatric diseases, yet the genetic architecture of this multidimensional trait is barely understood. Using a unique sample of 1,704 unrelated, young and healthy Chinese Han individuals, we revealed a significant heritability of functional connectivity patterns in the whole brain and several subnetworks. We further proposed a partitioned heritability analysis for multidimensional functional connectivity patterns, which revealed the common and unique enrichment patterns of the genetic contributions to brain connectivity patterns for several gene sets linked to brain functions, including the genes expressed preferentially in the central nervous system and those associated with intelligence, educational attainment, attention‐deficit/hyperactivity disorder, and schizophrenia. These results for the first time reveal the genetic architecture of multidimensional brain connectivity patterns across different networks and advance our understanding of the complex relationship between gene sets, neural networks, and behaviors.     

Functionally connected brain regions in the network activated during capsaicin inhalation

Coughing and the urge‐to‐cough are important mechanisms that protect the patency of the airways, and are coordinated by the brain. Inhaling a noxious substance leads to a widely distributed network of responses in the brain that are likely to reflect multiple functional processes requisite for perceiving, appraising, and behaviorally responding to airway challenge. The broader brain network responding to airway challenge likely contains subnetworks that are involved in the component functions required for coordinated protective behaviors. Functional connectivity analyses were used to determine whether brain responses to airway challenge could be differentiated regionally during inhalation of the tussive substance capsaicin. Seed regions were defined according to outcomes of previous activation studies that identified regional brain responses consistent with cough suppression, stimulus intensity coding, and perception of urge‐to‐cough. The subnetworks during continuous inhalation of capsaicin recapitulated the distributed regions previously implicated in discrete functional components of airway challenge. The outcomes of this study highlight the central representation of airways defence as a distributed network. Hum Brain Mapp 35:5341–5355, 2014. © 2014 Wiley Periodicals, Inc .     

From hippocampus to whole‐brain: The role of integrative processing in episodic memory retrieval

Multivariate functional connectivity analyses of neuroimaging data have revealed the importance of complex, distributed interactions between disparate yet interdependent brain regions. Recent work has shown that topological properties of functional brain networks are associated with individual and group differences in cognitive performance, including in episodic memory. After constructing functional whole‐brain networks derived from an event‐related fMRI study of memory retrieval, we examined differences in functional brain network architecture between forgotten and remembered words. This study yielded three main findings. First, graph theory analyses showed that successfully remembering compared to forgetting was associated with significant changes in the connectivity profile of the left hippocampus and a corresponding increase in efficient communication with the rest of the brain. Second, bivariate functional connectivity analyses indicated stronger interactions between the left hippocampus and a retrieval assembly for remembered versus forgotten items. This assembly included the left precuneus, left caudate, bilateral supramarginal gyrus, and the bilateral dorsolateral superior frontal gyrus. Integrative properties of the retrieval assembly were greater for remembered than forgotten items. Third, whole‐brain modularity analyses revealed that successful memory retrieval was marginally significantly associated with a less segregated modular architecture in the network. The magnitude of the decreases in modularity between remembered and forgotten conditions was related to memory performance. These findings indicate that increases in integrative properties at the nodal, retrieval assembly, and whole‐brain topological levels facilitate memory retrieval, while also underscoring the potential of multivariate brain connectivity approaches for providing valuable new insights into the neural bases of memory processes. Hum Brain Mapp 38:2242–2259, 2017. © 2017 Wiley Periodicals, Inc.     

Anomalous single‐subject based morphological cortical networks in drug‐naive,first‐episode major depressive disorder

Major depressive disorder (MDD) has been associated with disruptions in the topological organization of brain morphological networks in group‐level data. Such disruptions have not yet been identified in single‐patients, which is needed to show relations with symptom severity and to evaluate their potential as biomarkers for illness. To address this issue, we conducted a cross‐sectional structural brain network study of 33 treatment‐naive, first‐episode MDD patients and 33 age‐, gender‐, and education‐matched healthy controls (HCs). Weighted graph‐theory based network models were used to characterize the topological organization of brain networks between the two groups. Compared with HCs, MDD patients exhibited lower normalized global efficiency and higher modularity in their whole‐brain morphological networks, suggesting impaired integration and increased segregation of morphological brain networks in the patients. Locally, MDD patients exhibited lower efficiency in anatomic organization for transferring information predominantly in default‐mode regions including the hippocampus, parahippocampal gyrus, precuneus and superior parietal lobule, and higher efficiency in the insula, calcarine and posterior cingulate cortex, and in the cerebellum. Morphological connectivity comparisons revealed two subnetworks that exhibited higher connectivity strength in MDD mainly involving neocortex‐striatum‐thalamus‐cerebellum and thalamo‐hippocampal circuitry. MDD‐related alterations correlated with symptom severity and differentiated individuals with MDD from HCs with a sensitivity of 87.9% and specificity of 81.8%. Our findings indicate that single subject grey matter morphological networks are often disrupted in clinically relevant ways in treatment‐naive, first episode MDD patients. Circuit‐specific changes in brain anatomic network organization suggest alterations in the efficiency of information transfer within particular brain networks in MDD. Hum Brain Mapp 38:2482–2494, 2017. © 2017 Wiley Periodicals, Inc.     

Neural network correlates of high‐altitude adaptive genetic variants in Tibetans: A pilot,exploratory study

Although substantial progress has been made in the identification of genetic substrates underlying physiology, neuropsychology, and brain organization, the genotype–phenotype associations remain largely unknown in the context of high‐altitude (HA) adaptation. Here, we related HA adaptive genetic variants in three gene loci (EGLN1, EPAS1, and PPARA) to interindividual variance in a set of physiological characteristics, neuropsychological tests, and topological attributes of large‐scale structural and functional brain networks in 135 indigenous Tibetan highlanders. Analyses of individual HA adaptive single‐nucleotide polymorphisms (SNPs) revealed that specific SNPs selectively modulated physiological characteristics (erythrocyte level, ratio between forced expiratory volume in the first second to forced vital capacity, arterial oxygen saturation, and heart rate) and structural network centrality (the left anterior orbital gyrus) with no effects on neuropsychology or functional brain networks. Further analyses of genetic adaptive scores, which summarized the overall degree of genetic adaptation to HA, revealed significant correlations only with structural brain networks with respect to local interconnectivity of the whole networks, intermodule communication between the right frontal and parietal module and the left occipital module, nodal centrality in several frontal regions, and connectivity strength of a subnetwork predominantly involving in intramodule edges in the right temporal and occipital module. Moreover, the associations were dependent on gene loci, weight types, or topological scales. Together, these findings shed new light on genotype–phenotype interactions under HA hypoxia and have important implications for developing new strategies to optimize organism and tissue responses to chronic hypoxia induced by extreme environments or diseases.     

Analysis of structure–function network decoupling in the brain systems of spastic diplegic cerebral palsy

Manifestation of the functionalities from the structural brain network is becoming increasingly important to understand a brain disease. With the aim of investigating the differential structure–function couplings according to network systems, we investigated the structural and functional brain networks of patients with spastic diplegic cerebral palsy with periventricular leukomalacia compared to healthy controls. The structural and functional networks of the whole brain and motor system, constructed using deterministic and probabilistic tractography of diffusion tensor magnetic resonance images and Pearson and partial correlation analyses of resting‐state functional magnetic resonance images, showed differential embedding of functional networks in the structural networks in patients. In the whole‐brain network of patients, significantly reduced global network efficiency compared to healthy controls were found in the structural networks but not in the functional networks, resulting in reduced structural–functional coupling. On the contrary, the motor network of patients had a significantly lower functional network efficiency over the intact structural network and a lower structure–function coupling than the control group. This reduced coupling but reverse directionality in the whole‐brain and motor networks of patients was prominent particularly between the probabilistic structural and partial correlation‐based functional networks. Intact (or less deficient) functional network over impaired structural networks of the whole brain and highly impaired functional network topology over the intact structural motor network might subserve relatively preserved cognitions and impaired motor functions in cerebral palsy. This study suggests that the structure–function relationship, evaluated specifically using sparse functional connectivity, may reveal important clues to functional reorganization in cerebral palsy. Hum Brain Mapp 38:5292–5306, 2017. © 2017 Wiley Periodicals, Inc.     

Altered brain network integrity after childhood maltreatment: A structural connectomic DTI‐study

Childhood maltreatment is associated with alterations in neural architecture that potentially put these children at increased risk for psychopathology. Alterations in white matter (WM) tracts have been reported, however no study to date has investigated WM connectivity in brain networks in maltreated children to quantify global and local abnormalities through graph theoretical analyses of DTI data. We aimed for a multilevel investigation examining the DTI‐based structural connectome and its associations with basal cortisol levels of 25 children with documented maltreatment experiences before age 3, and 24 matched controls (age: 10.6 ± 1.75 years). On the global and lobar level, maltreated children showed significant reductions in global connectivity strength, local connectivity and increased path length, suggesting deviations from the small‐world network architecture previously associated with psychopathology. Reductions in global connectivity were associated with placement instability, attenuated cortisol secretion and higher levels of internalizing and externalizing behaviours. Regional measures revealed lower connectivity strength especially in regions within the ventromedial prefrontal cortex (vMPFC) in maltreated children. These findings show that childhood maltreatment is associated with systemic global neurodevelopmental alterations in WM networks next to regional alterations in areas involved in the regulation of affect. These alterations in WM organization could underlie global functional deficits and multi‐symptom patterns frequently observed in children with maltreatment experiences. Hum Brain Mapp 38:855–868, 2017. © 2016 Wiley Periodicals, Inc.     

Apolipoprotein E ε4 modulates functional brain connectome in Alzheimer's disease

The apolipoprotein E (APOE) ?4 allele is a well‐established genetic risk factor for Alzheimer's disease (AD). Recent research has demonstrated an APOE ?4‐mediated modulation of intrinsic functional brain networks in cognitively normal individuals. However, it remains largely unknown whether and how APOE ?4 affects the brain's functional network architecture in patients with AD. Using resting‐state functional MRI and graph‐theory approaches, we systematically investigated the topological organization of whole‐brain functional networks in 16 APOE ?4 carriers and 26 matched noncarriers with AD at three levels: global whole‐brain, intermediate module, and regional node/connection. Neuropsychological analysis showed that the APOE ?4 carriers performed worse on delayed memory but better on a late item generation of a verbal fluency task (associated with executive function) than noncarriers. Whole‐brain graph analyses revealed that APOE ?4 significantly disrupted whole‐brain topological organization as characterized by (i) reduced parallel information transformation efficiency; (ii) decreased intramodular connectivity within the posterior default mode network (pDMN) and intermodular connectivity of the pDMN and executive control network (ECN) with other neuroanatomical systems; and (iii) impaired functional hubs and their rich‐club connectivities that primarily involve the pDMN, ECN, and sensorimotor systems. Further simulation analysis indicated that these altered connectivity profiles of the pDMN and ECN largely accounted for the abnormal global network topology. Finally, the changes in network topology exhibited significant correlations with the patients' cognitive performances. Together, our findings suggest that the APOE genotype modulates large‐scale brain networks in AD and shed new light on the gene‐connectome interaction in this disease. Hum Brain Mapp 36:1828–1846, 2015. © 2015 Wiley Periodicals, Inc .