Neurocognitive Networks Research Articles

Altered task-modulated functional connectivity during emotional face processing in euthymic bipolar patients: A whole-brain psychophysiological interaction study

BackgroundPatients with bipolar disorder (BD) show deficits of facial emotion processing even in the euthymic phase. However, the large-scale functional brain network mechanism underlying the emotional deficit of BD remains unclear. Specifically, it is of importance to understand how the task-modulated functional connectivity (FC) was alternated over distributed brain networks in BD. MethodsIn this study, we analyzed functional MRI data of a face-matching task from 29 euthymic BD patients and 29 healthy controls (HC), and performed whole-brain psychophysiological interaction (PPI) analysis to obtain task-modulated FC. Abnormal FC patterns were identified through support vector machine-based classification. The topological organization of task-modulated FC networks was estimated by the graph theoretical analysis and compared between BD and HC. ResultsBD exhibited widely distributed aberrant task-modulated FC patterns not only in core neurocognitive intrinsic brain networks (the fronto-parietal, cingulo-opercular, and default mode networks), but also in the cerebellum and primary processing networks (sensorimotor and visual). Furthermore, the local efficiency of the frontal-parietal network was significantly increased in BD. LimitationsThe modest sample size. Only face pictures with negative emotion were used. Only unidirectional task-modulated FC was investigated. ConclusionsBD patients showed a widely distributed aberrant task-modulated FC pattern. Particularly, the fronto-parietal network, as one of the core neurocognitive intrinsic brain networks, was the primary network that demonstrated changes of both FC strength and local efficiency in BD. These findings on the task-modulated FC between these intrinsic brain networks might be considered an endophenotype of the BD condition persistent in the euthymic state.

Disrupted coupling between salience network segregation and glucose metabolism is associated with cognitive decline in Alzheimer's disease – A simultaneous resting-state FDG-PET/fMRI study

The aberrant organization and functioning of three core neurocognitive networks (NCNs), i.e., default-mode network (DMN), central executive network (CEN), and salience network (SN), are among the prominent features in Alzheimer’s disease (AD). The dysregulation of both intra- and inter-network functional connectivities (FCs) of the three NCNs contributed to AD-related cognitive and behavioral abnormalities. Brain functional network segregation, integrating intra- and inter-network FCs, is essential for maintaining the energetic efficiency of brain metabolism. The association of brain functional network segregation, together with glucose metabolism, with age-related cognitive decline was recently shown. Yet how these joint functional-metabolic biomarkers relate to cognitive decline along with mild cognitive impairment (MCI) and AD remains to be elucidated. In this study, under the framework of the triple-network model, we performed a hybrid FDG-PET/fMRI study to evaluate the concurrent changes of resting-state brain intrinsic FCs and glucose metabolism of the three NCNs across cognitively normal (CN) (N = 24), MCI (N = 21), and AD (N = 21) groups. Lower network segregation and glucose metabolism were observed in all three NCNs in patients with AD. More interestingly, in the SN, the coupled relationship between network segregation and glucose metabolism existed in the CN group (r = 0.523, p = 0.013) and diminished in patients with MCI (r = 0.431, p = 0.065) and AD (r = 0.079, p = 0.748). Finally, the glucose metabolism of the DMN (r = 0.380, p = 0.017) and the network segregation of the SN (r = 0.363, p = 0.023) were significantly correlated with the general cognitive status of the patients. Our findings suggest that the impaired SN segregation and its uncoupled relationship with glucose metabolism contribute to the cognitive decline in AD.

ENHANCE: The Center for Enhancing Neurocognitive Health, Abilities, Networks, & Community Engagement

Approximately 9 % of those aged 65 and over have a cognitive impairment due to a variety of causes including Alzheimer’s disease and other forms of dementia, Mild Cognitive Impairment (MCI), Parkinson’s disease, traumatic brain injury (TBI), and stroke. Few technology solutions have been directed towards supporting older adults with cognitive impairments and the literature regarding the efficacy of these solutions is sparse. In this symposium, we describe our new Center called ENHANCE (Enhancing Neurocognitive Health, Abilities, Networks, and Community Engagement), which is focused on developing technology support for aging adults with a cognitive impairment due to MCI, TBI, and Stroke. Sara Czaja will provide an overview of the conceptual framework, goals, and structure of ENHANCE, and describe the STRUMM project, that focuses on the design and evaluation of an innovative intelligent adaptive software package aimed at providing cognitive and social support to aging adults with cognitive impairments. Wendy Rogers will discuss the ENACT project, a longitudinal needs assessment focusing on understanding the needs, challenges, and support preferences of our target population and informal caregivers. Neil Charness will describe the AUGMENT development project, which is concerned with developing an instructional support tool for mobility activities, such as wayfinding, locating, and using transportation services. Finally, Walter Boot will discuss the DREAM development project, which is focused on developing a technology-based cognitive aid to support prospective memory activities. Michelle Bourgeois will serve as the discussant for the symposium and highlight the unique opportunities and challenges associated with ENHANCE.

Lifelong bilingualism and mechanisms of neuroprotection inAlzheimer dementia.

Lifelong bilingualism is associated with delayed dementia onset, suggesting a protective effect on the brain. Here, we aim to study the effects of lifelong bilingualism as a dichotomous and continuous phenomenon, on brain metabolism and connectivity in individuals with Alzheimer's dementia. Ninety‐eight patients with Alzheimer's dementia (56 monolinguals; 42 bilinguals) from three centers entered the study. All underwent an [18F]‐fluorodeoxyglucose positron emission tomography (PET) imaging session. A language background questionnaire measured the level of language use for conversation and reading. Severity of brain hypometabolism and strength of connectivity of the major neurocognitive networks was compared across monolingual and bilingual individuals, and tested against the frequency of second language life‐long usage. Age, years of education, and MMSE score were included in all above mentioned analyses as nuisance covariates. Cerebral hypometabolism was more severe in bilingual compared to monolingual patients; severity of hypometabolism positively correlated with the degree of second language use. The metabolic connectivity analyses showed increased connectivity in the executive, language, and anterior default mode networks in bilingual compared to monolingual patients. The change in neuronal connectivity was stronger in subjects with higher second language use. All effects were most pronounced in the left cerebral hemisphere. The neuroprotective effects of lifelong bilingualism act both against neurodegenerative processes and through the modulation of brain networks connectivity. These findings highlight the relevance of lifelong bilingualism in brain reserve and compensation, supporting bilingual education and social interventions aimed at usage, and maintenance of two or more languages, including dialects, especially crucial in the elderly people.

Hemodynamic activity characterization of resting-state networks (RSNS) by fractal analysis in episodic migraine

It is believed that the hypothalamus plays an important role during the prodromal phase of a migraine attack. Less is known about the role played by the hypothalamus during the pain-free period and its relationship with the different neurocognitive networks that were previously involved in migraine pathophysiology.

Hypothalamic structural integrity and temporal complexity of cortical information processing at rest in migraine without aura patients between attacks

The hypothalamus has been attributed an important role during the premonitory phase of a migraine attack. Less is known about the role played by the hypothalamus in the interictal period and its relationship with the putative neurocognitive networks previously identified in the pathophysiology of migraine. Our aim was to test whether the hypothalamic microstructure would be altered during the interictal period and whether this co-existed with aberrant connectivity at cortical level. We collected multimodal MRI data from 20 untreated patients with migraine without aura between attacks (MO) and 20 healthy controls (HC) and studied fractional anisotropy, mean (MD), radial (RD), and axial diffusivity of the hypothalamus ROI as a whole from diffusion tensor imaging (DTI). Moreover, we performed an exploratory analysis of the same DTI metrics separately for the anterior and posterior hypothalamic ROIs bilaterally. From resting-state functional MRI, we estimated the Higuchi’s fractal dimension (FD), an index of temporal complexity sensible to describe non-periodic patterns characterizing BOLD signature. Finally, we correlated neuroimaging findings with migraine clinical features. In comparison to HC, MO had significantly higher MD, AD, and RD values within the hypothalamus. These findings were confirmed also in the exploratory analysis on the sub-regions of the hypothalamus bilaterally, with the addition of lower FA values on the posterior ROIs. Patients showed higher FD values within the salience network (SN) and the cerebellum, and lower FD values within the primary visual (PV) network compared to HC. We found a positive correlation between cerebellar and SN FD values and severity of migraine. Our findings of hypothalamic abnormalities between migraine attacks may form part of the neuroanatomical substrate that predisposes the onset of the prodromal phase and, therefore, the initiation of an attack. The peculiar fractal dimensionality we found in PV, SN, and cerebellum may be interpreted as an expression of abnormal efficiency demand of brain networks devoted to the integration of sensory, emotional, and cognitive information related to the severity of migraine.

Exploring the neurocognome: Neurocognitive network organization in healthy young adults

Conventional neurocognitive assessment does not account for the complex interplay between neurocognitive functions that gives rise to (goal-directed) behavior. This study aims to explore the value of the application of network analysis to individual neurocognitive data, in order to investigate neurocognitive network organization (i.e., the neurocognome). Participants were healthy young adults (N = 51, average age: 26 years [range: 18–34], 49% female) that underwent a single comprehensive neurocognitive assessment. To allow implementation of network analysis, we developed a new measure of connectivity between neurocognitive functions that can be calculated on a single neurocognitive assessment. Connectivity values between all possible pairs of neurocognitive functions were used to reconstruct individual neurocognitive networks. Graph theory was applied to extract measures of global and local network organization from neurocognitive networks at the individual level. The results confirmed the expectation that neurocognitive connectivity values should be higher for connections between neurocognitive functions that are more closely related (i.e., within neurocognitive domains) than for connections between neurocognitive functions that are less closely related (i.e., across neurocognitive domains). The results further showed that reconstruction of the neurocognitive network at the individual level has considerable agreement with a group-based approach, providing preliminary evidence for the validity of our approach. The reconstructed neurocognitive network also showed considerable consistency among (randomly selected) independent subgroups, supporting the stability of our approach. Lastly, neurocognitive network parameters were related to intelligence and behavior problems, reflecting relevance of neurocognitive network organization for other important domains of functioning. Moreover, local network parameters (i.e., the relative importance of neurocognitive functions in the network) may have stronger relevance for behavioral functioning than conventional measures of neurocognitive functioning (i.e., z-scores reflecting performance on individual neurocognitive tests). Taken together, this study indicates that analysis of individual neurocognitive network organization has potential value for neurocognitive assessment in research and clinical practice.

The organization of functional neurocognitive networks in focal epilepsy correlates with domain-specific cognitive performance.

Understanding and diagnosing cognitive impairment in epilepsy remains a prominent challenge. New etiological models suggest that cognitive difficulties might not be directly linked to seizure activity, but are rather a manifestation of a broader brain pathology. Consequently, treating seizures is not sufficient to alleviate cognitive symptoms, highlighting the need for novel diagnostic tools. Here, we investigated whether the organization of three intrinsic, resting-state functional connectivity networks was correlated with domain-specific cognitive test performance. Using individualized EEG source reconstruction and graph theory, we examined the association between network small worldness and cognitive test performance in 23 patients with focal epilepsy and 17 healthy controls, who underwent a series of standardized pencil-and-paper and digital cognitive tests. We observed that the specific networks robustly correlated with test performance in distinct cognitive domains. Specifically, correlations were evident between the default mode network and memory in patients, the central-executive network and executive functioning in controls, and the salience network and social cognition in both groups. Interestingly, the correlations were evident in both groups, but in different domains, suggesting an alteration in these functional neurocognitive networks in focal epilepsy. The present findings highlight the potential clinical relevance of functional brain network dysfunction in cognitive impairment.

Nicotine acutely alters temporal properties of resting brain states

BackgroundNicotine-dependent individuals have altered activity in neurocognitive networks such as the default mode (DMN), salience (SN) and central executive networks (CEN). One theory suggests that, among chronic tobacco smokers, nicotine abstinence drives more DMN-related internal processing while nicotine replacement suppresses DMN and enhances SN and CEN. Whether acute nicotine impacts network dynamics in non-smokers is, however, unknown. MethodsIn a randomized double-blind crossover study, 17 healthy non-smokers (8 females) were administered placebo and nicotine (2-mg lozenge) on two different days prior to collecting resting-state functional magnetic resonance imaging (fMRI). Previously defined brain states in 462 individuals that spatially overlap with well-characterized resting-state networks including the DMN, SN, and CEN were applied to compute state-specific dynamics at rest: total time spent in state, persistence in each state after entry, and frequency of state transitions. We examined whether nicotine acutely alters these resting-state dynamics. ResultsA significant drug-by-state interaction emerged; post-hoc analyses clarified that, relative to placebo, nicotine suppressed time spent in a frontoinsular-DMN state (posterior cingulate cortex, medial prefrontal cortex, anterior insula, striatum and orbitofrontal cortex) and enhanced time spent in a SN state (anterior cingulate cortex and insula). No significant findings were observed for persistence and frequency. ConclusionsIn non-smokers, nicotine biases resting-state brain function away from the frontoinsular-DMN and toward the SN, which may reduce internally focused cognition and enhance salience processing. While past work suggests nicotine impacts DMN activity, the current work shows nicotinic influences on a specific DMN-like network that has been linked with rumination and depression.

Brain Dynamics Underlying Cognitive Flexibility Across the Lifespan.

The neural mechanisms contributing to flexible cognition and behavior and how they change with development and aging are incompletely understood. The current study explored intrinsic brain dynamics across the lifespan using resting-state fMRI data (n = 601, 6-85years) and examined the interactions between age and brain dynamics among three neurocognitive networks (midcingulo-insular network, M-CIN; medial frontoparietal network, M-FPN; and lateral frontoparietal network, L-FPN) in relation to behavioral measures of cognitive flexibility. Hierarchical multiple regression analysis revealed brain dynamics among a brain state characterized by co-activation of the L-FPN and M-FPN, and brain state transitions, moderated the relationship between quadratic effects of age and cognitive flexibility as measured by scores on the Delis-Kaplan Executive Function System (D-KEFS) test. Furthermore, simple slope analyses of significant interactions revealed children and older adults were more likely to exhibit brain dynamic patterns associated with poorer cognitive flexibility compared with younger adults. Our findings link changes in cognitive flexibility observed with age with the underlying brain dynamics supporting these changes. Preventative and intervention measures should prioritize targeting these networks with cognitive flexibility training to promote optimal outcomes across the lifespan.

Right Frontoinsular Cortex: A Potential Imaging Biomarker to Evaluate T2DM-Induced Cognitive Impairment.

Cognitive impairment in type 2 diabetes mellitus (T2DM) is associated with functional and structural abnormalities in the intrinsic brain network. The salience network (SN) is a neurocognitive network that maintains normal cognitive function, but it has received little attention in T2DM. We explored SN changes in patients with T2DM with normal cognitive function (DMCN) and in patients with T2DM with mild cognitive impairment (DMCI). Sixty-five T2DM patients and 31 healthy controls (HCs) underwent a neuropsychological assessment, independent component analysis (ICA), and voxel-based morphometry (VBM) analysis. The ICA extracted the SN for VBM to compare SN functional connectivity (FC) and gray matter (GM) volume (GMV) between groups. A correlation analysis examined the relationship between abnormal FC and GMV and clinical/cognitive variables. Compared with HCs, DMCN patients demonstrated increased FC in the left frontoinsular cortex (FIC), right anterior insula, and putamen, while DMCI patients demonstrated decreased right middle/inferior frontal gyrus FC. Compared with DMCN patients, DMCI patients showed decreased right FIC FC. There was no significant difference in SN GMV in DMCN and DMCI patients compared with HCs. FIC GMV was decreased in the DMCI patients compared with DMCN patients. In addition, right FIC FC and SN GMV positively correlated with Montreal Cognitive Assessment and Mini-Mental State Examination (MMSE) scores. These findings indicate that changes in SN FC, and GMV are complex non-linear processes accompanied by increased cognitive dysfunction in patients with T2DM. The right FIC may be a useful imaging biomarker for supplementary assessment of early cognitive dysfunction in patients with T2DM.

Neurocognitive basis of deductive reasoning in children varies with parental education.

The neurocognitive basis of elementary academic skills varies with parental socioeconomic status (SES). Little is known, however, about SES‐related differences underlying higher‐order cognitive skills that are critical for school success, such as reasoning. Here we used fMRI to examine how the neurocognitive basis of deductive reasoning varies as a function of parental education in school‐aged children. Higher parental education was associated with greater reliance on the left inferior frontal gyrus when solving set‐inclusion problems, consistent with other work suggesting that these problems might more heavily rely on verbal systems in the brain. In addition, children who are at the lower end of the parental education continuum, but have higher nonverbal skills relied on right parietal areas to a greater degree than their peers for solving set‐inclusion problems. Finally, lower parental education children with higher verbal or nonverbal skill engaged dorsolateral prefrontal regions to a greater degree for set‐inclusion and linear‐order relations than their peers. These findings suggest that children with lower parental education rely on spatial and cognitive control mechanisms to achieve parity with their peers with parents who have more education. Better understanding variability in the neurocognitive networks that children recruit as a function of their parental factors might benefit future individualized interventions that best match children's characteristics.

The development of structural covariance networks during the transition from childhood to adolescence

Structural covariance conceptualizes how morphologic properties of brain regions are related to one another (across individuals). It can provide unique information to cortical structure (e.g., thickness) about the development of functionally meaningful networks. The current study investigated how structural covariance networks develop during the transition from childhood to adolescence, a period characterized by marked structural re-organization. Participants (N = 192; scans = 366) completed MRI assessments between 8.5 and 14.5 years of age. A sliding window approach was used to create “age-bins”, and structural covariance networks (based on cortical thickness) were created for each bin. Next, generalized additive models were used to characterize trajectories of age-related changes in network properties. Results revealed nonlinear trajectories with “peaks” in mean correlation and global density that are suggestive of a period of convergence in anatomical properties across the cortex during early adolescence, prior to regional specialization. “Hub” regions in sensorimotor cortices were present by late childhood, but the extent and strength of association cortices as “hubs” increased into mid-adolescence. Moreover, these regional changes were found to be related to rates of thinning across the cortex. In the context of neurocognitive networks, the frontoparietal, default mode, and attention systems exhibited age-related increases in within-network and between-network covariance. These regional and modular developmental patterns are consistent with continued refinement of socioemotional and other complex executive functions that are supported by higher-order cognitive networks during early adolescence.

Reconfiguration of Directed Functional Connectivity Among Neurocognitive Networks with Aging: Considering the Role of Thalamo-Cortical Interactions.

A complete picture of how subcortical nodes, such as the thalamus, exert directional influence on large-scale brain network interactions across age remains elusive. Using directed functional connectivity and weighted net causal outflow on resting-state fMRI data, we provide evidence of a comprehensive reorganization within and between neurocognitive networks (default mode: DMN, salience: SN, and central executive: CEN) associated with age and thalamocortical interactions. We hypothesize that thalamus subserves both modality-specific and integrative hub role in organizing causal weighted outflow among large-scale neurocognitive networks. To this end, we observe that within-network directed functional connectivity is driven by thalamus and progressively weakens with age. Secondly, we find that age-associated increase in between CEN- and DMN-directed functional connectivity is driven by both the SN and the thalamus. Furthermore, left and right thalami act as a causal integrative hub exhibiting substantial interactions with neurocognitive networks with aging and play a crucial role in reconfiguring network outflow. Notably, these results were largely replicated on an independent dataset of matched young and old individuals. Our findings strengthen the hypothesis that the thalamus is a key causal hub balancing both within- and between-network connectivity associated with age and maintenance of cognitive functioning with aging.

Self-reported Mind Wandering and Response Time Variability Differentiate Prestimulus Electroencephalogram Microstate Dynamics during a Sustained Attention Task.

Brain activity continuously and spontaneously fluctuates during tasks of sustained attention. This spontaneous activity reflects the intrinsic dynamics of neurocognitive networks, which have been suggested to differentiate moments of externally directed task focus from episodes of mind wandering. However, the contribution of specific electrophysiological brain states and their millisecond dynamics to the experience of mind wandering is still unclear. In this study, we investigated the association between electroencephalogram microstate temporal dynamics and self-reported mind wandering. Thirty-six participants completed a sustained attention to response task in which they were asked to respond to frequently occurring upright faces (nontargets) and withhold responses to rare inverted faces (targets). Intermittently, experience sampling probes assessed whether participants were focused on the task or whether they were mind wandering (i.e., off-task). Broadband electroencephalography was recorded and segmented into a time series of brain electric microstates based on data-driven clustering of topographic voltage patterns. The strength, prevalence, and rate of occurrence of specific microstates differentiated on- versus off-task moments in the prestimulus epochs of trials preceding probes. Similar associations were also evident between microstates and variability in response times. Together, these findings demonstrate that distinct microstates and their millisecond dynamics are sensitive to the experience of mind wandering.

Altered Neurocognitive Functional Connectivity and Activation Patterns Underlie Psychopathology in Preadolescence

BackgroundNeurocognitive deficits are common among youth with mental disorders, and patterns of aberrant brain function generally cross diagnostic boundaries. This study investigated associations between functional neurocircuitry and broad transdiagnostic psychopathology dimensions in the critical preadolescent period when psychopathology is emerging. MethodsParticipants were 9- to 10-year-olds from the Adolescent Brain Cognitive Development Study. Factor scores of general psychopathology, externalizing, internalizing, and thought disorder dimensions were calculated from a higher-order model of psychopathology using confirmatory factor analysis (N = 11,721) and entered as explanatory variables into linear mixed models to examine associations with resting-state functional connectivity (n = 9074) and neural activation during the emotional n-back task (n = 6146) when covarying for sex, race/ethnicity, parental education, and cognitive function. ResultsAll dimensions of psychopathology were commonly characterized by hypoconnectivity within the dorsal attention and retrosplenial-temporal networks, hyperconnectivity between the frontoparietal and ventral attention networks and between the dorsal attention network and amygdala, and hypoactivation of the caudal middle frontal gyrus. Externalizing pathology was uniquely associated with hyperconnectivity between the salience and ventral attention networks and hyperactivation of the cingulate and striatum. Internalizing pathology was uniquely characterized by hypoconnectivity between the default mode and cingulo-opercular networks. Connectivity between the cingulo-opercular network and putamen was uniquely higher for internalizing pathology and lower for thought disorder pathology. ConclusionsThese findings provide novel evidence that broad psychopathology dimensions are characterized by common and dissociable patterns, particularly for externalizing pathology, of functional connectivity and task-evoked activation throughout neurocognitive networks in preadolescence.

Identifying the brain's connector hubs at the voxel level using functional connectivity overlap ratio

Neuroimaging studies have shown that the brain is functionally organized into several large-scale brain networks. Within these networks are regions that are widely connected to several other regions within and/or outside the network. Regions that connect to several other networks, known as connector hubs, are believed to be crucial for information transfer and between-network communication within the brain. To identify regions with high between-network connectivity at the voxel level, we introduced a novel metric called functional connectivity overlap ratio (FCOR), which quantifies the spatial extent of a region's connection to a given network. Using resting state functional magnetic resonance imaging data, FCOR maps were generated for several well-known large-scale resting state networks (RSNs) and used to examine the relevant associations among different RSNs, identify connector hub regions in the cerebral cortex, and elucidate the hierarchical functional organization of the brain. Constructed FCOR maps revealed a strong association among the core neurocognitive networks (default mode, salience, and executive control) as well as among primary processing networks (sensorimotor, auditory, and visual). Prominent connector hubs were identified in the bilateral middle frontal gyrus, posterior cingulate, lateral parietal, middle temporal, dorsal anterior cingulate, and anterior insula, among others, regions mostly associated with the core neurocognitive networks. Finally, clustering the whole brain using FCOR features yielded a topological organization that arranges brain regions into a hierarchy of information processing systems with the primary processing systems at one end and the heteromodal systems comprising connector hubs at the other end.

Temporal Dynamics of Large-Scale Networks Predict Neural Cue Reactivity and Cue-Induced Craving

BackgroundCue reactivity, a core characteristic of substance use disorders, commonly recruits brain regions that are key nodes in neurocognitive networks, including the default mode network (DMN) and salience network (SN). Whether resting-state temporal dynamic properties of these networks relate to subsequent cue reactivity and cue-induced craving is unknown. MethodsThe resting-state data of 46 nicotine-dependent participants were assessed to define temporal dynamic properties of DMN and SN states. Temporal dynamics focused on the total time across the scan session that brain activity resides in these specific states. Using regression models, we examined how the total time in each state related to neural reactivity to smoking cues within key DMN (posterior cingulate cortex, medial prefrontal cortex) or SN (anterior insula, dorsal anterior cingulate cortex) nodes. Mediation analyses were subsequently conducted to study how neural cue reactivity mediates the relationship between total time in state at rest and subjective cue-induced craving. ResultsIncreased time spent in the DMN state and decreased time spent in the SN state predicted subsequent cue-induced increases in the anterior insula and dorsal anterior cingulate cortex, respectively. Cue-induced anterior insula and dorsal anterior cingulate cortex activity significantly mediated the relationship between time spent in DMN/SN and cue-induced subjective craving. ConclusionsOur findings showed a significant relationship between resting-state dynamics of the DMN/SN and task-activated SN nodes that together predicted cue-induced craving changes in nicotine-dependent individuals. These findings propose a neurobiological pathway for cue-induced craving that begins with resting-state temporal dynamics, suggesting that brain responding to external stimuli is driven by resting temporal dynamics.

Increased functional dynamics in civil aviation pilots: Evidence from a neuroimaging study.

Civil aviation is a distinctive career. Pilots need to monitor the entire system in real time. However, the psychophysiological mechanism of flying is largely unknown. The human brain is a large-scale interconnected organization, and many stable intrinsic large-scale brain networks have been identified. Among them are three core neurocognitive networks: default mode network (DMN), central executive network (CEN), and salience network (SN). These three networks play a critical role in human cognition. This study aims to examine the dynamic properties of the three large-scale brain networks in civil aviation pilots. We collected resting-state functional magnetic resonance imaging data from pilots. Independent component analysis, which is a data-driven approach, was combined with sliding window dynamic functional connectivity analysis to detect the dynamic properties of large-scale brain networks. Our results revealed that pilots exhibit an increased interaction of the CEN with the DMN and the SN along with a decreased interaction within the CEN. In addition, the temporal properties of functional dynamics (number of transitions) increased in pilots compared to healthy controls. In general, pilots exhibited increased between-network functional connectivity, decreased within-network functional connectivity, and a higher number of transitions. These findings suggest that pilots might have better functional dynamics and cognitive flexibility.

Integrity of Neurocognitive Networks in Dementing Disorders as Measured with Simultaneous PET/Functional MRI.

Functional MRI (fMRI) studies have reported altered integrity of large-scale neurocognitive networks (NCNs) in dementing disorders. However, findings on the specificity of these alterations in patients with Alzheimer disease (AD) and behavioral-variant frontotemporal dementia (bvFTD) are still limited. Recently, NCNs have been successfully captured using PET with 18F-FDG. Methods: Network integrity was measured in 72 individuals (38 male) with mild AD or bvFTD, and in healthy controls, using a simultaneous resting-state fMRI and 18F-FDG PET. Indices of network integrity were calculated for each subject, network, and imaging modality. Results: In either modality, independent-component analysis revealed 4 major NCNs: anterior default-mode network (DMN), posterior DMN, salience network, and right central executive network (CEN). In fMRI data, the integrity of the posterior DMN was found to be significantly reduced in both patient groups relative to controls. In the AD group the anterior DMN and CEN appeared to be additionally affected. In PET data, only the integrity of the posterior DMN in patients with AD was reduced, whereas 3 remaining networks appeared to be affected only in patients with bvFTD. In a logistic regression analysis, the integrity of the anterior DMN as measured with PET alone accurately differentiated between the patient groups. A correlation between indices of 2 imaging modalities was low overall. Conclusion: FMRI and 18F-FDG PET capture partly different aspects of network integrity. A higher disease specificity for NCNs as derived from PET data supports metabolic connectivity imaging as a promising diagnostic tool.