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Thoughts and actions are often driven by a decision to either explore new avenues with unknown outcomes, or to exploit known options with predictable outcomes. Yet, the neural mechanisms underlying this exploration-exploitation trade-off in humans remain poorly understood. This is attributable to variability in the operationalization of exploration and exploitation as psychological constructs, as well as the heterogeneity of experimental protocols and paradigms used to study these choice behaviours. To address this gap, here we present a comprehensive review of the literature to investigate the neural basis of explore-exploit decision-making in humans. We first conducted a systematic review of functional magnetic resonance imaging (fMRI) studies of exploration-versus exploitation-based decision-making in healthy adult humans during foraging, reinforcement learning, and information search. Eleven fMRI studies met inclusion criterion for this review. Adopting a network neuroscience framework, synthesis of the findings across these studies revealed that exploration-based choice was associated with the engagement of attentional, control, and salience networks. In contrast, exploitation-based choice was associated with engagement of default network brain regions. We interpret these results in the context of a network architecture that supports the flexible switching between externally and internally directed cognitive processes, necessary for adaptive, goal-directed behaviour. To further investigate potential neural mechanisms underlying the exploration-exploitation trade-off we next surveyed studies involving neurodevelopmental, neuropsychological, and neuropsychiatric disorders, as well as lifespan development, and neurodegenerative diseases. We observed striking differences in patterns of explore-exploit decision-making across these populations, again suggesting that these two decision-making modes are supported by independent neural circuits. Taken together, our review highlights the need for precision-mapping of the neural circuitry and behavioural correlates associated with exploration and exploitation in humans. Characterizing exploration versus exploitation decision-making biases may offer a novel, trans-diagnostic approach to assessment, surveillance, and intervention for cognitive decline and dysfunction in normal development and clinical populations., Competing Interests: Declaration of competing interest The authors of this work declare no conflicts of interest., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Our ability to consciously perceive information from the visual scene relies on a myriad of intrinsic neural mechanisms. Functional neuroimaging studies have sought to identify the neural correlates of conscious visual processing and to further dissociate from those pertaining to preconscious and unconscious visual processing. However, delineating what core brain regions are involved in eliciting a conscious percept remains a challenge, particularly regarding the role of prefrontal-parietal regions. We performed a systematic search of the literature that yielded a total of 54 functional neuroimaging studies. We conducted two quantitative meta-analyses using activation likelihood estimation to identify reliable patterns of activation engaged by i. conscious (n = 45 studies, comprising 704 participants) and ii. unconscious (n = 16 studies, comprising 262 participants) visual processing during various task performances. Results of the meta-analysis specific to conscious percepts quantitatively revealed reliable activations across a constellation of regions comprising the bilateral inferior frontal junction, intraparietal sulcus, dorsal anterior cingulate, angular gyrus, temporo-occipital cortex and anterior insula. Neurosynth reverse inference revealed conscious visual processing to be intertwined with cognitive terms related to attention, cognitive control and working memory. Results of the meta-analysis on unconscious percepts revealed consistent activations in the lateral occipital complex, intraparietal sulcus and precuneus. These findings highlight the notion that conscious visual processing readily engages higher-level regions including the inferior frontal junction and unconscious processing reliably recruits posterior regions, mainly the lateral occipital complex., Competing Interests: Declaration of Competing Interest None., (Copyright © 2023. Published by Elsevier Inc.)

The intrinsic functional organization of the brain changes into older adulthood. Age differences are observed at multiple spatial scales, from global reductions in modularity and segregation of distributed brain systems, to network-specific patterns of dedifferentiation. Whether dedifferentiation reflects an inevitable, global shift in brain function with age, circumscribed, experience-dependent changes, or both, is uncertain. We employed a multimethod strategy to interrogate dedifferentiation at multiple spatial scales. Multi-echo (ME) resting-state fMRI was collected in younger (n = 181) and older (n = 120) healthy adults. Cortical parcellation sensitive to individual variation was implemented for precision functional mapping of each participant while preserving group-level parcel and network labels. ME-fMRI processing and gradient mapping identified global and macroscale network differences. Multivariate functional connectivity methods tested for microscale, edge-level differences. Older adults had lower BOLD signal dimensionality, consistent with global network dedifferentiation. Gradients were largely age-invariant. Edge-level analyses revealed discrete, network-specific dedifferentiation patterns in older adults. Visual and somatosensory regions were more integrated within the functional connectome; default and frontoparietal control network regions showed greater connectivity; and the dorsal attention network was more integrated with heteromodal regions. These findings highlight the importance of multiscale, multimethod approaches to characterize the architecture of functional brain aging., (© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Neuroimaging using more ecologically valid stimuli such as audiobooks has advanced our understanding of natural language comprehension in the brain. However, prior naturalistic stimuli have typically been restricted to a single language, which limited generalizability beyond small typological domains. Here we present the Le Petit Prince fMRI Corpus (LPPC-fMRI), a multilingual resource for research in the cognitive neuroscience of speech and language during naturalistic listening (OpenNeuro: ds003643). 49 English speakers, 35 Chinese speakers and 28 French speakers listened to the same audiobook The Little Prince in their native language while multi-echo functional magnetic resonance imaging was acquired. We also provide time-aligned speech annotation and word-by-word predictors obtained using natural language processing tools. The resulting timeseries data are shown to be of high quality with good temporal signal-to-noise ratio and high inter-subject correlation. Data-driven functional analyses provide further evidence of data quality. This annotated, multilingual fMRI dataset facilitates future re-analysis that addresses cross-linguistic commonalities and differences in the neural substrate of language processing on multiple perceptual and linguistic levels., (© 2022. The Author(s).)

The relationship between structural and functional connectivity in the brain is a key question in systems neuroscience. Modern accounts assume a single global structure-function relationship that persists over time. Here we study structure-function coupling from a dynamic perspective, and show that it is regionally heterogeneous. We use a temporal unwrapping procedure to identify moment-to-moment co-fluctuations in neural activity, and reconstruct time-resolved structure-function coupling patterns. We find that patterns of dynamic structure-function coupling are region-specific. We observe stable coupling in unimodal and transmodal cortex, and dynamic coupling in intermediate regions, particularly in insular cortex (salience network) and frontal eye fields (dorsal attention network). Finally, we show that the variability of a region's structure-function coupling is related to the distribution of its connection lengths. Collectively, our findings provide a way to study structure-function relationships from a dynamic perspective., (© 2022. The Author(s).)

Central to understanding human behavior is a comprehensive mapping of brain-behavior relations within the context of lifespan development. Reproducible discoveries depend upon well-powered samples of reliable data. We provide to the scientific community two, 10-minute, multi-echo functional MRI (ME-fMRI) runs, and structural MRI (T1-MPRAGE), from 181 healthy younger (ages 18-34 y) and 120 older adults (ages 60-89 y). T2-FLAIR MRIs and behavioral assessments are available in a majority subset of over 250 participants. Behavioral assessments include fluid and crystallized cognition, self-reported measures of personality, and socioemotional functioning. Initial quality control and validation of these data is provided. This dataset will be of value to scientists interested in BOLD signal specifically isolated from ME-fMRI, individual differences in brain-behavioral associations, and cross-sectional aging effects in healthy adults. Demographic and behavioral data are available within the Open Science Framework project "Goal-Directed Cognition in Older and Younger Adults" ( http://osf.io/yhzxe/ ), which will be augmented over time; neuroimaging data are available on OpenNeuro ( https://openneuro.org/datasets/ds003592 )., (© 2022. The Author(s).)

Neuronal variability patterns promote the formation and organization of neural circuits. Macroscale similarities in regional variability patterns may therefore be linked to the strength and topography of inter-regional functional connections. To assess this relationship, we used multi-echo resting-state fMRI and investigated macroscale connectivity-variability associations in 154 adult humans (86 women; mean age = 22yrs). We computed inter-regional measures of moment-to-moment BOLD signal variability and related them to inter-regional functional connectivity. Region pairs that showed stronger functional connectivity also showed similar BOLD signal variability patterns, independent of inter-regional distance and structural similarity. Connectivity-variability associations were predominant within all networks and followed a hierarchical spatial organization that separated sensory, motor and attention systems from limbic, default and frontoparietal control association networks. Results were replicated in a second held-out fMRI run. These findings suggest that macroscale BOLD signal variability is an organizational feature of large-scale functional networks, and shared inter-regional BOLD signal variability may underlie macroscale brain network dynamics., Competing Interests: Declaration of Competing Interest The authors declare no competing financial interests., (Copyright © 2021. Published by Elsevier Inc.)

Social exclusion refers to the experience of being disregarded or rejected by others and has wide-ranging negative consequences for well-being and cognition. Cyberball, a game where a ball is virtually tossed between players, then leads to the exclusion of the research participant, is a common method used to examine the experience of social exclusion. The neural correlates of social exclusion remain a topic of debate, particularly with regards to the role of the dorsal anterior cingulate cortex (dACC) and the concept of social pain. Here we conducted a quantitative meta-analysis using activation likelihood estimation (ALE) to identify brain activity reliably engaged by social exclusion during Cyberball task performance (Studies = 53; total N = 1,817 participants). Results revealed consistent recruitment in ventral anterior cingulate and posterior cingulate cortex, inferior and superior frontal gyri, posterior insula, and occipital pole. No reliable activity was observed in dACC. Using a probabilistic atlas to define dACC, fewer than 15% of studies reported peak coordinates in dACC. Meta-analytic connectivity mapping suggests patterns of co-activation are consistent with the topography of the default network. Reverse inference for cognition associated with reliable Cyberball activity computed in Neurosynth revealed social exclusion to be associated with cognitive terms Social, Autobiographical, Mental States, and Theory of Mind. Taken together, these findings highlight the role of the default network in social exclusion and warns against interpretations of the dACC as a key region involved in the experience of social exclusion in humans., (Copyright © 2020. Published by Elsevier Inc.)

The macro-scale intrinsic functional network architecture of the human brain has been well characterized. Early studies revealed robust and enduring patterns of static connectivity, while more recent work has begun to explore the temporal dynamics of these large-scale brain networks. Little work to date has investigated directed connectivity within and between these networks, or the temporal patterns of afferent (input) and efferent (output) connections between network nodes. Leveraging a novel analytic approach, prediction correlation, we investigated the causal interactions within and between large-scale networks of the brain using resting state fMRI. This technique allows us to characterize information transfer between brain regions in both the spatial (direction) and temporal (duration) scales. Using data from the Human Connectome Project (N = 200) we applied prediction correlation techniques to four resting-state fMRI scans (each scan has TRs = 1200). Three central observations emerged. First, the strongest and longest duration connections were observed within the somatomotor, visual, and dorsal attention networks. Second, the short duration connections were observed for high-degree nodes in the visual and default networks, as well as in the hippocampus. Specifically, the connectivity profile of the highest-degree nodes was dominated by efferent connections to multiple cortical areas. Moderate high-degree nodes, particularly in hippocampal regions, showed an afferent connectivity profile. Finally, multimodal association nodes in lateral prefrontal brain regions demonstrated a short duration, bidirectional connectivity profile, consistent with this region's role in integrative and modulatory processing. These results provide novel insights into the spatiotemporal dynamics of human brain function., (Copyright © 2020. Published by Elsevier Inc.)

Complex social interplay is a defining property of the human species. In social neuroscience, many experiments have sought to first define and then locate 'perspective taking', 'empathy', and other psychological concepts to specific brain circuits. Seldom, bottom-up studies were conducted to first identify explanatory patterns of brain variation, which are then related to psychological concepts; perhaps due to a lack of large population datasets. In this spirit, we performed a systematic de-construction of social brain morphology into its elementary building blocks, involving ~10,000 UK Biobank participants. We explored coherent representations of structural co-variation at population scale within a recent social brain atlas, by translating autoencoder neural networks from deep learning. The learned subnetworks revealed essential patterns of structural relationships between social brain regions, with the nucleus accumbens, medial prefrontal cortex, and temporoparietal junction embedded at the core. Some of the uncovered subnetworks contributed to predicting examined social traits in general, while other subnetworks helped predict specific facets of social functioning, such as the experience of social isolation. As a consequence of our population-level evidence, spatially overlapping subsystems of the social brain probably relate to interindividual differences in everyday social life.

Humans survive and thrive through social exchange. Yet, social dependency also comes at a cost. Perceived social isolation, or loneliness, affects physical and mental health, cognitive performance, overall life expectancy, and increases vulnerability to Alzheimer's disease-related dementias. Despite severe consequences on behavior and health, the neural basis of loneliness remains elusive. Using the UK Biobank population imaging-genetics cohort (n = ~40,000, aged 40-69 years when recruited, mean age = 54.9), we test for signatures of loneliness in grey matter morphology, intrinsic functional coupling, and fiber tract microstructure. The loneliness-linked neurobiological profiles converge on a collection of brain regions known as the 'default network'. This higher associative network shows more consistent loneliness associations in grey matter volume than other cortical brain networks. Lonely individuals display stronger functional communication in the default network, and greater microstructural integrity of its fornix pathway. The findings fit with the possibility that the up-regulation of these neural circuits supports mentalizing, reminiscence and imagination to fill the social void.

In young adults, mentalizing about known others engages the default network, with differential brain response modulated by social closeness. While the functional integrity of the default network changes with age, few studies have investigated how these changes impact the representation of known others, across levels of closeness. Young (N = 29, 16 females) and older (N = 27, 12 females) adults underwent functional magnetic resonance imaging (fMRI) scanning while making trait judgments for social others varying in closeness. Multivariate analyses (partial least squares) identified default network activation for trait judgments across both age cohorts. For young adults, romantic partner and self-judgments differed from other levels of social closeness and were associated with activity in default and salience networks. In contrast, default network interactivity was not modulated by social closeness for older adults. In two functional connectivity analyses, both age groups demonstrated connectivity between dorsal and ventral medial prefrontal cortex and other default network regions during trait judgments. However older, but not young, adults also showed increased functional coupling between medial and lateral prefrontal brain regions that did not vary by category of known other. Mentalizing about others engages default and frontal brain regions in older adulthood, and this coupling is poorly modulated by social closeness., (© The Author(s) 2020. Published by Oxford University Press.)

Schizophrenia (SCZ) is recognized as a disorder of distributed brain dysconnectivity. While progress has been made delineating large-scale functional networks in SCZ, little is known about alterations in grey matter integrity of these networks. We used a multivariate approach to identify the structural covariance of the salience, default, motor, visual, fronto-parietal control, and dorsal attention networks. We derived individual scores reflecting covariance in each structural image for a given network. Seed-based multivariate analyses were conducted on structural images in a discovery (n = 90) and replication (n = 74) sample of SCZ patients and healthy controls. We first validated patterns across all networks, consistent with well-established functional connectivity reports. Next, across two SCZ samples, we found reliable and robust reductions in structural integrity of the fronto-parietal control and salience networks, but not default, dorsal attention, motor and sensory networks. Well-powered exploratory analyses failed to identify relationships with symptoms. These findings provide evidence of selective structural decline in associative networks in SCZ. Such decline may be linked with recently identified functional disturbances in associative networks, providing more sensitive multi-modal network-level probes in SCZ. Absence of symptom effects suggests that identified disturbances may underlie a trait-type marker in SCZ., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Aging is characterized by accumulation of structural and metabolic changes in the brain. Recent studies suggest transmodal brain networks are especially sensitive to aging, which, we hypothesize, may be due to their apical position in the cortical hierarchy. Studying an open-access healthy cohort (n = 102, age range = 30-89 years) with MRI and Aβ PET data, we estimated age-related cortical thinning, hippocampal atrophy and Aβ deposition. In addition to carrying out surface-based morphological and metabolic mapping experiments, we stratified effects along neocortical and hippocampal resting-state functional connectome gradients derived from independent datasets. The cortical gradient depicts an axis of functional differentiation from sensory-motor regions to transmodal regions, whereas the hippocampal gradient recapitulates its long-axis. While age-related thinning and increased Aβ deposition occurred across the entire cortical topography, increased Aβ deposition was especially pronounced toward higher-order transmodal regions. Age-related atrophy was greater toward the posterior end of the hippocampal long-axis. No significant effect of age on Aβ deposition in the hippocampus was observed. Imaging markers correlated with behavioral measures of fluid intelligence and episodic memory in a topography-specific manner, confirmed using both univariate as well as multivariate analyses. Our results strengthen existing evidence of structural and metabolic change in the aging brain and support the use of connectivity gradients as a compact framework to analyze and conceptualize brain-based biomarkers of aging., (© 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.)

The past decade has witnessed a proliferation of studies aimed at characterizing the human connectome. These projects map the brain regions comprising large-scale systems underlying cognition using non-invasive neuroimaging approaches and advanced analytic techniques adopted from network science. While the idea that the human brain is composed of multiple macro-scale functional networks has been gaining traction in cognitive neuroscience, the field has yet to reach consensus on several key issues regarding terminology. What constitutes a functional brain network? Are there "core" functional networks, and if so, what are their spatial topographies? What naming conventions, if universally adopted, will provide the most utility and facilitate communication amongst researchers? Can a taxonomy of functional brain networks be delineated? Here we survey the current landscape to identify six common macro-scale brain network naming schemes and conventions utilized in the literature, highlighting inconsistencies and points of confusion where appropriate. As a minimum recommendation upon which to build, we propose that a scheme incorporating anatomical terminology should provide the foundation for a taxonomy of functional brain networks. A logical starting point in this endeavor might delineate systems that we refer to here as "occipital", "pericentral", "dorsal frontoparietal", "lateral frontoparietal", "midcingulo-insular", and "medial frontoparietal" networks. We posit that as the field of network neuroscience matures, it will become increasingly imperative to arrive at a taxonomy such as that proposed here, that can be consistently referenced across research groups.

The global signal in resting-state functional MRI data is considered to be dominated by physiological noise and artifacts, yet a growing literature suggests that it also carries information about widespread neural activity. The biological relevance of the global signal remains poorly understood. Applying principal component analysis to a large neuroimaging dataset, we found that individual variation in global signal topography recapitulates well-established patterns of large-scale functional brain networks. Using canonical correlation analysis, we delineated relationships between individual differences in global signal topography and a battery of phenotypes. The first canonical variate of the global signal, resembling the frontoparietal control network, was significantly related to an axis of positive and negative life outcomes and psychological function. These results suggest that the global signal contains a rich source of information related to trait-level cognition and behavior. This work has significant implications for the contentious debate over artifact removal practices in neuroimaging.

Some of the closest reciprocal relationships are between parents and their children. As part of the attachment characterizing many parent-child bonds, individuals form mental representations that are chronically accessible and calibrate expectations for future relationships. We predict that there exist unique neural signatures of this chronic accessibility. Young (N = 29, 16 females) and older adults (N = 27, 12 females) made trait judgments for parent or child, respectively, during fMRI scanning. Multivariate analysis identified whole-brain patterns of activation that covaried with the magnitude of parent-child attachment when thinking about that individual. Higher levels of parent and child attachment were associated with lower neural recruitment in anterior cingulate cortex, amygdala, posterior cingulate cortex, medial temporal lobe, and occipital face area. Results provide novel evidence for neural signatures of chronic accessibility, as bringing to mind one's attached parent or child requires less engagement of brain regions involved in distress relief, memory, and facial processing.

Cognitive aging is often described in the context of loss or decline. Emerging research suggests that the story is more complex, with older adults showing both losses and gains in cognitive ability. With increasing age, declines in controlled, or fluid, cognition occur in the context of gains in crystallized knowledge of oneself and the world. This inversion in cognitive capacities, from greater reliance on fluid abilities in young adulthood to increasingly crystallized or semanticized cognition in older adulthood, has profound implications for cognitive and real-world functioning in later life. The shift in cognitive architecture parallels changes in the functional network architecture of the brain. Observations of greater functional connectivity between lateral prefrontal brain regions, implicated in cognitive control, and the default network, implicated in memory and semantic processing, led us to propose the default-executive coupling hypothesis of aging . In this review we provide evidence that these changes in the functional architecture of the brain serve as a neural mechanism underlying the shifting cognitive architecture from younger to older adulthood. We incorporate findings spanning cognitive aging and cognitive neuroscience to present an integrative model of cognitive and brain aging, describing its antecedents, determinants, and implications for real-world functioning.

Aging is associated with increased difficulty in facial emotion identification, possibly due to age-related network change. The neuropeptide oxytocin (OT) facilitates emotion identification, but this is understudied in aging. To determine the effects of OT on dynamic facial emotion identification across adulthood, 46 young and 48 older participants self-administered intranasal OT or a placebo in a randomized, double-blind procedure. Older participants were slower and less accurate in identifying emotions. Although there was no behavioral treatment effect, partial least squares analysis supported treatment effects on brain patterns during emotion identification that varied by age and emotion. For young participants, OT altered the processing of sadness and happiness, whereas for older participants, OT only affected the processing of sadness (15.3% covariance, p = 0.004). Furthermore, seed partial least squares analysis showed that older participants in the OT group recruited a large-scale amygdalar network that was positively correlated for anger, fear, and happiness, whereas older participants in the placebo group recruited a smaller, negatively correlated network (7% covariance, p = 0.002). Advancing the literature, these findings show that OT alters brain activity and amygdalar connectivity by age and emotion., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Social relationships imbue life with meaning, whereas loneliness diminishes one's sense of meaning in life. Yet the extent of interdependence between these psychological constructs remains poorly understood. We took a multivariate network approach to examine resting-state fMRI functional connectivity's association with loneliness and meaning in a large cohort of adults (N = 942). Loneliness and meaning in life were negatively correlated with one another. In their relationship with individually parcelled whole-brain measures of functional connectivity, a significant and reliable pattern was observed. Greater loneliness was associated with dense, and less modular, connections between default, frontoparietal, attention and perceptual networks. A greater sense of life meaning was associated with increased, and more modular, connectivity between default and limbic networks. Low loneliness was associated with more modular brain connectivity, and lower life meaning was associated with higher between-network connectivity. These findings advance our understanding of loneliness and life meaning as distinct, yet interdependent, features of sociality. The results highlight a potential role of the default network as a central hub, providing a putative neural mechanism for shifting between feelings of isolation and purpose., (© The Author(s) 2019. Published by Oxford University Press.)

We investigated sex differences in the association between a measure of physical health, cardiorespiratory fitness (CRF), and brain function using resting-state functional connectivity fMRI. We examined these sex differences in the default, frontoparietal control, and cingulo-opercular networks, assemblies of functionally connected brain regions known to be impacted by both age and fitness level. Healthy older adults ( n = 49; 29 women) were scanned to obtain measures of intrinsic connectivity within and across these 3 networks. We calculated global efficiency (a measure of network integration) and local efficiency (a measure of network specialization) using graph theoretical methods. Across all three networks combined, local efficiency was positively associated with CRF, and this was more robust in male versus female older adults. Furthermore, global efficiency was negatively associated with CRF, but only in males. Our findings suggest that in older adults, associations between brain network integrity and physical health are sex-dependent. These results underscore the importance of considering sex differences when examining associations between fitness and brain function in older adulthood. NEW & NOTEWORTHY We examined the association between cardiorespiratory fitness and resting state functional connectivity in several brain networks known to be impacted by age and fitness level. We found significant associations between fitness and measures of network integration and network specialization, but in a sex-dependent manner, highlighting the interplay between sex differences, fitness, and aging brain health. Our findings underscore the importance of considering sex differences when examining associations between fitness and brain function in older adulthood.

Creativity refers to the ability to generate novel associations and has been linked to better problem-solving and real-world functional abilities. In younger adults, creative cognition has been associated with functional connectivity among brain networks implicated in executive control [fronto-parietal network (FPN) and salience network (SN)] and associative or elaborative processing default network (DN). Here, we investigate whether creativity is associated with the intrinsic network architecture of the brain and how these associations may differ for younger and older adults. Young (mean age: 24.76, n = 22) and older (mean age: 70.03, n = 44) adults underwent multi-echo functional magnetic resonance image scanning at rest and completed a divergent-thinking task to assess creative cognition outside the scanner. Divergent thinking in older adults, compared to young adults, was associated with functional connectivity between the default and both executive control networks (FPN and SN) as well as more widespread default-executive coupling. Finally, the ventromedial prefrontal cortex appears to be a critical node involved in within- and between-network connectivity associated with creative cognition in older adulthood. Patterns of intrinsic network coupling revealed here suggest a putative neural mechanism underlying a greater role for mnemonic processes in creative cognition in older adulthood., (© The Author(s) 2019. Published by Oxford University Press.)

Recent investigations in neuroscience elucidate the neural basis of close other cognitive representations, which serve functions central to our health and happiness. Yet, there are persistent barriers to this research, including disparate research methods and the absence of a common theoretical background. The present review connects neuroimaging and attachment theory within a novel social, cognitive and affective framework. We apply attachment theory to understand why we would expect cognitive representations of close others to be different from other social neural representations. Developing reliable markers of attachment is a critical step in mapping close other neural representations. We then examine existing neuroimaging literature on close other representations, highlighting the recruitment of neural systems supporting reward, motivation and distress alleviation, in addition to the mirror neuron system, default network and salience network. We then review the methodologies of past studies, revealing a diverse array of self-report measures assessing `closeness' and social cognitive tasks that, taken together, preclude meaningful synthesis of findings. Lastly, we discuss specific behavioral measures of attachment and closeness with recommendations for the field. This attachment framework integrates brain and behavioral sciences and unites theoretical principles with empirical methods to further our understanding of how the brain represents close others., (© The Author(s) 2019. Published by Oxford University Press.)

Creative thinking is associated with connectivity between the default and executive control networks in the young brain. In aging, this pattern of functional coupling has been observed across multiple tasks. We have described this as the Default-Executive Coupling Hypothesis of Aging and suggest that this connectivity pattern may also be associated with creativity in older adulthood. However, age differences in brain networks implicated in creativity have yet to be investigated. The overarching goal of the present study was to examine age-related changes to functional brain networks associated with creativity. Specifically, we explored functional connectivity patterns among default and executive control brain regions associated with creative thoughts in older and younger adults. In a cross-sectional design, young (mean age = 21 y; n = 30) and older (mean age = 70 y; n = 25) participants completed a divergent thinking task during fMRI, which was examined using region of interest functional connectivity analyses. Consistent with predictions, analyses demonstrated that default and executive networks are more functionally coupled during creative thinking for older than younger adults. Critically, despite similar performance on an in-scanner creativity task, increased network efficiency was associated with creative ability for older adults only. These findings provide novel evidence of default-executive coupling as a putative mechanism associated with creative ability in later life., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Mild cognitive impairment (MCI) of the amnestic type is considered to be a transitionary stage between healthy aging and Alzheimer's disease (AD). Previous studies have demonstrated that intrinsic functional connectivity of the default network (DN) is altered in normal aging and AD and impacts both within- and between-network connectivity. Although changes within the DN have been reported in MCI, it remains uncertain how interactions with other large-scale brain networks are altered in this prodromal stage of AD. We investigated within- and between-network connectivity in healthy older adults (HOAs) and older adults with MCI across 3 canonical brain networks: DN, dorsal attention network, and frontoparietal control network. We also assessed how patterns of functional connectivity among the 3 networks predicted cognitive status and age using multivariate partial least squares. A total of 91 MCI and 71 HOA resting-state scans were analyzed from the Alzheimer's Disease Neuroimaging Initiative. There were 3 key findings. First, a circumscribed pattern of greater between-network and interhemispheric connectivity was associated with higher cognitive status in HOAs. Second, for individuals with MCI, cognitive status was positively associated with a more distributed, less-differentiated pattern of intrinsic functional connectivity across the 3 networks. Finally, greater within-network functional connectivity was positively associated with cognitive status for HOAs irrespective of age; however, this compensation-like effect diminished with increasing age for participants with MCI. Although reliable differences between healthy aging and MCI in the intrinsic network architecture of the brain are apparent, these differences emerge as shifting associations between network interactivity, cognitive functioning, and age., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Counterfactual thinking (CFT) is the process of mentally simulating alternative versions of known facts. In the past decade, cognitive neuroscientists have begun to uncover the neural underpinnings of CFT, particularly episodic CFT (eCFT), which activates regions in the default network (DN) also activated by episodic memory (eM) recall. However, the engagement of DN regions is different for distinct kinds of eCFT. More plausible counterfactuals and counterfactuals about oneself show stronger activity in DN regions compared to implausible and other- or object-focused counterfactuals. The current study sought to identify a source for this difference in DN activity. Specifically, self-focused counterfactuals may also be more plausible, suggesting that DN core regions are sensitive to the plausibility of a simulation. On the other hand, plausible and self-focused counterfactuals may involve more episodic information than implausible and other-focused counterfactuals, which would imply DN sensitivity to episodic information. In the current study, we compared episodic and semantic counterfactuals generated to be plausible or implausible against episodic and semantic memory reactivation using fMRI. Taking multivariate and univariate approaches, we found that the DN is engaged more during episodic simulations, including eM and all eCFT, than during semantic simulations. Semantic simulations engaged more inferior temporal and lateral occipital regions. The only region that showed strong plausibility effects was the hippocampus, which was significantly engaged for implausible CFT but not for plausible CFT, suggestive of binding more disparate information. Consequences of these findings for the cognitive neuroscience of mental simulation are discussed., (Published by Elsevier Inc.)

Episodic simulation is an adaptive process that can support goal-directed activity and planning success. We investigated the neural architecture associated with the episodic simulation improvement to the likelihood of carrying out future actions by isolating the brain regions associated with this facilitation in a prospective memory paradigm. Participants performed a lexical decision task by making word/non-word judgments, with rarely occurring prospective memory target words requiring a pre-specified manual response. Prior to scanning, participants were given exposure to two lists of prospective memory targets: animals and tools. In a fully counterbalanced design, participants generated a rhyme to one target list and imagined their subsequent encounter (episodic simulation) with target words on the other list. Replicating prior behavioral work, episodic simulation improved subsequent prospective memory performance. Brain activation was assessed in a multivariate partial least squares analysis. Relative to lexical decision blocks with no prospective memory demand, sustained prospective memory replicated prior observations of frontal polar activation. Critically, maintaining the intention to respond to simulated targets, over and above rhyme targets, engaged middle frontal and angular gyri, and medial parietal and prefrontal cortices. Transient activity associated with prospective memory target hits revealed activation for simulated targets in medial prefrontal cortex, posterior cingulate, lateral temporal lobe and inferior parietal lobule. In contrast, rhyme target hits engaged more left lateralized dorsolateral prefrontal cortex and anterior insula. Episodic simulation, thus effectively shifts executive control strategy and boosts task performance. These results are consistent with a growing body of evidence implicating executive control and default network region interactions in adaptive, goal-directed behavior., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

As we age, the architecture of cognition undergoes a fundamental transition. Fluid intellectual abilities decline while crystalized abilities remain stable or increase. This shift has a profound impact across myriad cognitive and functional domains, yet the neural mechanisms remain under-specified. We have proposed that greater connectivity between the default network and executive control regions in lateral prefrontal cortex may underlie this shift, as older adults increasingly rely upon accumulated knowledge to support goal-directed behavior. Here we provide direct evidence for this mechanism within the domain of autobiographical memory. In a large sample of healthy adult participants (n = 103 Young; n = 80 Old) the strength of default - executive coupling reliably predicted more semanticized, or knowledge-based, recollection of autobiographical memories in the older adult cohort. The findings are consistent with the default - executive coupling hypothesis of aging and identify this shift in network dynamics as a candidate neural mechanism associated with crystalized cognition in later life that may signal adaptive capacity in the context of declining fluid cognitive abilities., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Behavioral studies using delay and social discounting as indices of self-control and altruism, respectively, have revealed functional similarities between farsighted and social decisions. However, neural evidence for this functional link is lacking. Twenty-five young adults completed a delay and social discounting task during fMRI scanning. A spatiotemporal partial least squares analysis revealed that both forms of discounting were well characterized by a pattern of brain activity in areas comprising frontoparietal control, default, and mesolimbic reward networks. Both forms of discounting appear to draw on common neurocognitive mechanisms, regardless of whether choices involve intertemporal or interpersonal outcomes. We also observed neural profiles differentiating between high and low discounters. High discounters were well characterized by increased medial temporal lobe and limbic activity. In contrast, low discount rates were associated with activity in the medial prefrontal cortex and right temporoparietal junction. This pattern may reflect biological mechanisms underlying behavioral heterogeneity in discount rates., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background: Age-related brain changes leading to altered socioemotional functioning may increase vulnerability to financial exploitation. If confirmed, this would suggest a novel mechanism leading to heightened financial exploitation risk in older adults. Development of predictive neural markers could facilitate increased vigilance and prevention. In this preliminary study, we sought to identify structural and functional brain differences associated with financial exploitation in older adults., Methods: Financially exploited older adults (n = 13, 7 female) and a matched cohort of older adults who had been exposed to, but avoided, a potentially exploitative situation (n = 13, 7 female) were evaluated. Using magnetic resonance imaging, we examined cortical thickness and resting state functional connectivity. Behavioral data were collected using standardized cognitive assessments, self-report measures of mood and social functioning., Results: The exploited group showed cortical thinning in anterior insula and posterior superior temporal cortices, regions associated with processing affective and social information, respectively. Functional connectivity encompassing these regions, within default and salience networks, was reduced, while between network connectivity was increased. Self-reported anger and hostility was higher for the exploited group., Conclusions: We observed financial exploitation associated with brain differences in regions involved in socioemotional functioning. These exploratory and preliminary findings suggest that alterations in brain regions implicated in socioemotional functioning may be a marker of financial exploitation risk. Large-scale, prospective studies are necessary to validate this neural mechanism, and develop predictive markers for use in clinical practice., (© The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America.)

Cortical parcellation based on resting fMRI is an important tool for investigating the functional organization and connectivity of the cerebral cortex. Group parcellation based on co-registration of anatomical images to a common atlas will inevitably result in errors in the locations of the boundaries of functional parcels when they are mapped back from the atlas to the individual. This is because areas of functional specialization vary across individuals in a manner that cannot be fully determined from the sulcal and gyral anatomy that is used for mapping between atlas and individual. We describe a method that avoids this problem by refining an initial group parcellation so that for each subject the parcel boundaries are optimized with respect to that subject's resting fMRI. Initialization with a common parcellation results in automatic correspondence between parcels across subjects. Further, by using a group sparsity constraint to model connectivity, we exploit group similarities in connectivity between parcels while optimizing their boundaries for each individual. We applied this approach with initialization on both high and low density group cortical parcellations and used resting fMRI data to refine across a group of individuals. Cross validation studies show improved homogeneity of resting activity within the refined parcels. Comparisons with task-based localizers show consistent reduction of variance of statistical parametric maps within the refined parcels relative to the group-based initialization indicating improved delineation of regions of functional specialization. This method enables a more accurate estimation of individual subject functional areas, facilitating group analysis of functional connectivity, while maintaining consistency across individuals with a standardized topological atlas., (Copyright © 2017 Elsevier Inc. All rights reserved.)

The human brain tracks dynamic changes within the social environment, forming and updating representations of individuals in our social milieu. This mechanism of social navigation builds an increasingly complex map of persons with whom we are familiar and form attachments to guide adaptive social behaviors. We examined the neural representation of known others along a continuum of attachment using fMRI. Heterosexual adults (N = 29, 16 females), in romantic relationships for more than 2 years, made trait judgments for a romantic partner, parent, close friend, familiar acquaintance and self-during scanning. Multivariate analysis, partial least squares, was used to identify whole-brain patterns of brain activation associated with trait judgments of known others across a continuum of attachment. Across conditions, trait judgments engaged the default network and lateral prefrontal cortex. Judgments about oneself and a partner were associated with a common activation pattern encompassing anterior and middle cingulate, posterior superior temporal sulcus, as well as anterior insula. Parent and close friend judgments engaged medial and anterior temporal lobe regions. These results provide novel evidence that mentalizing about known familiar others results in differential brain activity. We provide initial evidence that the representation of adult attachment is a distinguishing feature of these differences., (© The Author (2017). Published by Oxford University Press.)

Moral cognition is associated with activation of the default network, regions implicated in mentalizing about one's own actions or the intentions of others. Yet little is known about the initial detection of moral information. We examined the neural correlates of moral processing during a narrative completion task, which included an implicit moral salience manipulation. During fMRI scanning, participants read a brief vignette and selected the most semantically congruent sentence from two options to complete the narrative. The options were immoral, moral or neutral statements. RT was fastest for the selection of neutral statements and slowest for immoral statements. Neuroimaging analyses revealed that responses involving morally laden content engaged default and executive control network brain regions including medial and rostral prefrontal cortex, and core regions of the salience network, including anterior insula and dorsal anterior cingulate. Immoral vs moral conditions additionally engaged the salience network. These results implicate the salience network in the detection of moral information, which may modulate downstream default and frontal control network interactions in the service of complex moral reasoning and decision-making processes. These findings suggest that moral cognition involves both bottom-up and top-down attentional processes, mediated by discrete large-scale brain networks and their interactions., (© The Author (2017). Published by Oxford University Press.)

Most research on mind-wandering has characterized it as a mental state with contents that are task unrelated or stimulus independent. However, the dynamics of mind-wandering - how mental states change over time - have remained largely neglected. Here, we introduce a dynamic framework for understanding mind-wandering and its relationship to the recruitment of large-scale brain networks. We propose that mind-wandering is best understood as a member of a family of spontaneous-thought phenomena that also includes creative thought and dreaming. This dynamic framework can shed new light on mental disorders that are marked by alterations in spontaneous thought, including depression, anxiety and attention deficit hyperactivity disorder.

To engage in purposeful behavior, it is important to make plans, which organize subsequent actions. Most studies of planning involve "look-ahead" puzzle tasks that are unrelated to personal goals. We developed a task to assess autobiographical planning, which involves the formulation of personal plans in response to real-world goals, and examined autobiographical planning in 63 adults during fMRI scanning. Autobiographical planning was found to engage the default network, including medial-temporal lobe and midline structures, and executive control regions in lateral pFC and parietal cortex and caudate. To examine how specific qualitative features of autobiographical plans modulate neural activity, we performed parametric modulation analyses. Ratings of plan detail, novelty, temporal distance, ease of plan formulation, difficulty in goal completion, and confidence in goal accomplishment were used as covariates in six hierarchical linear regression models. This modeling procedure removed shared variance among the ratings, allowing us to determine the independent relationship between ratings of interest and trial-wise BOLD signal. We found that specific autobiographical planning, describing a detailed, achievable, and actionable planning process for attaining a clearly envisioned future, recruited both default and frontoparietal brain regions. In contrast, abstract autobiographical planning, plans that were constructed from more generalized semantic or affective representations of a less tangible and distant future, involved interactions among default, sensory perceptual, and limbic brain structures. Specific qualities of autobiographical plans are important predictors of default and frontoparietal control network engagement during plan formation and reflect the contribution of mnemonic and executive control processes to autobiographical planning.

The neural basis and cognitive functions of various spontaneous thought processes, particularly mind-wandering, are increasingly being investigated. Although strong links have been drawn between the occurrence of spontaneous thought processes and activation in brain regions comprising the default mode network (DMN), spontaneous thought also appears to recruit other, non-DMN regions just as consistently. Here we present the first quantitative meta-analysis of neuroimaging studies of spontaneous thought and mind-wandering in order to address the question of their neural correlates. Examining 24 functional neuroimaging studies of spontaneous thought processes, we conducted a meta-analysis using activation likelihood estimation (ALE). A number of key DMN areas showed consistent recruitment across studies, including medial prefrontal cortex, posterior cingulate cortex, medial temporal lobe, and bilateral inferior parietal lobule. Numerous non-DMN regions, however, were also consistently recruited, including rostrolateral prefrontal cortex, dorsal anterior cingulate cortex, insula, temporopolar cortex, secondary somatosensory cortex, and lingual gyrus. These meta-analytic results indicate that DMN activation alone is insufficient to adequately capture the neural basis of spontaneous thought; frontoparietal control network areas, and other non-DMN regions, appear to be equally central. We conclude that further progress in the cognitive and clinical neuroscience of spontaneous thought will therefore require a re-balancing of our view of the contributions of various regions and networks throughout the brain, and beyond the DMN., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

Substantial neuroimaging evidence suggests that spontaneous engagement of the default network impairs performance on tasks requiring executive control. We investigated whether this impairment depends on the congruence between executive control demands and internal mentation. We hypothesized that activation of the default network might enhance performance on an executive control task if control processes engage long-term memory representations that are supported by the default network. Using fMRI, we scanned 36 healthy young adult humans on a novel two-back task requiring working memory for famous and anonymous faces. In this task, participants (1) matched anonymous faces interleaved with anonymous face, (2) matched anonymous faces interleaved with a famous face, or (3) matched a famous faces interleaved with an anonymous face. As predicted, we observed a facilitation effect when matching famous faces, compared with anonymous faces. We also observed greater activation of the default network during these famous face-matching trials. The results suggest that activation of the default network can contribute to task performance during an externally directed executive control task. Our findings provide evidence that successful activation of the default network in a contextually relevant manner facilitates goal-directed cognition., (Copyright © 2014 the authors 0270-6474/14/3414108-07$15.00/0.)

The behaviors of other people are often central to envisioning the future. The ability to accurately predict the thoughts and actions of others is essential for successful social interactions, with far-reaching consequences. Despite its importance, little is known about how the brain represents people in order to predict behavior. In this functional magnetic resonance imaging study, participants learned the unique personality of 4 protagonists and imagined how each would behave in different scenarios. The protagonists' personalities were composed of 2 traits: Agreeableness and Extraversion. Which protagonist was being imagined was accurately inferred based solely on activity patterns in the medial prefrontal cortex using multivariate pattern classification, providing novel evidence that brain activity can reveal whom someone is thinking about. Lateral temporal and posterior cingulate cortex discriminated between different degrees of agreeableness and extraversion, respectively. Functional connectivity analysis confirmed that regions associated with trait-processing and individual identities were functionally coupled. Activity during the imagination task, and revealed by functional connectivity, was consistent with the default network. Our results suggest that distinct regions code for personality traits, and that the brain combines these traits to represent individuals. The brain then uses this "personality model" to predict the behavior of others in novel situations., (© The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Though only a decade has elapsed since the default network (DN) was first defined as a large-scale brain system, recent years have brought great insight into the network's adaptive functions. A growing theme highlights the DN as playing a key role in internally directed or self-generated thought. Here, we synthesize recent findings from cognitive science, neuroscience, and clinical psychology to focus attention on two emerging topics as current and future directions surrounding the DN. First, we present evidence that self-generated thought is a multifaceted construct whose component processes are supported by different subsystems within the network. Second, we highlight the dynamic nature of the DN, emphasizing its interaction with executive control systems when regulating aspects of internal thought. We conclude by discussing clinical implications of disruptions to the integrity of the network, and consider disorders when thought content becomes polarized or network interactions become disrupted or imbalanced., (© 2014 New York Academy of Sciences.)

Background and Objectives: Human morality has been investigated using a variety of tasks ranging from judgments of hypothetical dilemmas to viewing morally salient stimuli. These experiments have provided insight into neural correlates of moral judgments and emotions, yet these approaches reveal important differences in moral cognition. Moral reasoning tasks require active deliberation while moral emotion tasks involve the perception of stimuli with moral implications. We examined convergent and divergent brain activity associated with these experimental paradigms taking a quantitative meta-analytic approach., Data Source: A systematic search of the literature yielded 40 studies. Studies involving explicit decisions in a moral situation were categorized as active (n = 22); studies evoking moral emotions were categorized as passive (n = 18). We conducted a coordinate-based meta-analysis using the Activation Likelihood Estimation to determine reliable patterns of brain activity., Results & Conclusions: Results revealed a convergent pattern of reliable brain activity for both task categories in regions of the default network, consistent with the social and contextual information processes supported by this brain network. Active tasks revealed more reliable activity in the temporoparietal junction, angular gyrus and temporal pole. Active tasks demand deliberative reasoning and may disproportionately involve the retrieval of social knowledge from memory, mental state attribution, and construction of the context through associative processes. In contrast, passive tasks reliably engaged regions associated with visual and emotional information processing, including lingual gyrus and the amygdala. A laterality effect was observed in dorsomedial prefrontal cortex, with active tasks engaging the left, and passive tasks engaging the right. While overlapping activity patterns suggest a shared neural network for both tasks, differential activity suggests that processing of moral input is affected by task demands. The results provide novel insight into distinct features of moral cognition, including the generation of moral context through associative processes and the perceptual detection of moral salience.

Significant progress has been made uncovering functional brain networks, yet little is known about the corresponding structural covariance networks. The default network's functional architecture has been shown to change over the course of healthy and pathological aging. We examined cross-sectional and longitudinal datasets to reveal the structural covariance of the human default network across the adult lifespan and through the progression of Alzheimer's disease (AD). We used a novel approach to identify the structural covariance of the default network and derive individual participant scores that reflect the covariance pattern in each brain image. A seed-based multivariate analysis was conducted on structural images in the cross-sectional OASIS (N = 414) and longitudinal Alzheimer's Disease Neuroimaging Initiative (N = 434) datasets. We reproduced the distributed topology of the default network, based on a posterior cingulate cortex seed, consistent with prior reports of this intrinsic connectivity network. Structural covariance of the default network scores declined in healthy and pathological aging. Decline was greatest in the AD cohort and in those who progressed from mild cognitive impairment to AD. Structural covariance of the default network scores were positively associated with general cognitive status, reduced in APOEε4 carriers versus noncarriers, and associated with CSF biomarkers of AD. These findings identify the structural covariance of the default network and characterize changes to the network's gray matter integrity across the lifespan and through the progression of AD. The findings provide evidence for the large-scale network model of neurodegenerative disease, in which neurodegeneration spreads through intrinsically connected brain networks in a disease specific manner.

Personality neuroscience involves examining relations between cognitive or behavioral variability and neural variables like brain structure and function. Such studies have uncovered a number of fascinating associations but require large samples, which are expensive to collect. Here, we propose a system that capitalizes on neuroimaging data commonly collected for separate purposes and combines it with new behavioral data to test novel hypotheses. Specifically, we suggest that groups of researchers compile a database of structural (i.e., anatomical) and resting-state functional scans produced for other task-based investigations and pair these data with contact information for the participants who contributed the data. This contact information can then be used to collect additional cognitive, behavioral, or individual-difference data that are then reassociated with the neuroimaging data for analysis. This would allow for novel hypotheses regarding brain-behavior relations to be tested on the basis of large sample sizes (with adequate statistical power) for low additional cost. This idea can be implemented at small scales at single institutions, among a group of collaborating researchers, or perhaps even within a single lab. It can also be implemented at a large scale across institutions, although doing so would entail a number of additional complications.

Background: Functional neuroimaging is increasingly used in rehabilitation research to map the neural mechanisms subserving training targets. These data can inform intervention design and improve evaluation of treatment outcomes. Reliable neural markers may provide standard metrics of treatment impact and allow consideration of behavioral outcomes in the context of functional brain changes., Objective: To identify common patterns of functional brain changes associated with training across a diverse range of intervention protocols. Reliable brain changes could inform development of candidate neural markers to guide intervention research., Methods: Taking a quantitative meta-analytic approach, we review the functional neuroimaging studies of cognitive and motor skills training interventions in healthy young adults (N = 38)., Results: Reliable decreases in functional brain activity from pretraining to posttraining were observed in brain regions commonly associated with cognitive control processes, including lateral prefrontal, left anterior inferior parietal lobule, and dorsal anterior cingulate cortex. Training-related increases were observed in the medial prefrontal cortex and posterior cingulate and angular gyrus, core regions of the default network. Activity within the subcortical striatum also showed reliable increases pretraining to posttraining., Conclusions: These data suggest that altered engagement of large-scale, spatially distributed cortical brain networks and subcortical striatal brain regions may serve as candidate neural markers of training interventions. The development of reliable metrics based on activity and functional connectivity among large-scale brain networks may prove fruitful in identifying interactions between domain-general and -specific changes in brain activity that affect behavioral outcomes.

Human cognition is increasingly characterized as an emergent property of interactions among distributed, functionally specialized brain networks. We recently demonstrated that the antagonistic "default" and "dorsal attention" networks--subserving internally and externally directed cognition, respectively--are modulated by a third "frontoparietal control" network that flexibly couples with either network depending on task domain. However, little is known about the intrinsic functional architecture underlying this relationship. We used graph theory to analyze network properties of intrinsic functional connectivity within and between these three large-scale networks. Task-based activation from three independent studies were used to identify reliable brain regions ("nodes") of each network. We then examined pairwise connections ("edges") between nodes, as defined by resting-state functional connectivity MRI. Importantly, we used a novel bootstrap resampling procedure to determine the reliability of graph edges. Furthermore, we examined both full and partial correlations. As predicted, there was a higher degree of integration within each network than between networks. Critically, whereas the default and dorsal attention networks shared little positive connectivity with one another, the frontoparietal control network showed a high degree of between-network interconnectivity with each of these networks. Furthermore, we identified nodes within the frontoparietal control network of three different types--default-aligned, dorsal attention-aligned, and dual-aligned--that we propose play dissociable roles in mediating internetwork communication. The results provide evidence consistent with the idea that the frontoparietal control network plays a pivotal gate-keeping role in goal-directed cognition, mediating the dynamic balance between default and dorsal attention networks.

During the past few years, there has been a dramatic increase in research examining the role of memory in imagination and future thinking. This work has revealed striking similarities between remembering the past and imagining or simulating the future, including the finding that a common brain network underlies both memory and imagination. Here, we discuss a number of key points that have emerged during recent years, focusing in particular on the importance of distinguishing between temporal and nontemporal factors in analyses of memory and imagination, the nature of differences between remembering the past and imagining the future, the identification of component processes that comprise the default network supporting memory-based simulations, and the finding that this network can couple flexibly with other networks to support complex goal-directed simulations. This growing area of research has broadened our conception of memory by highlighting the many ways in which memory supports adaptive functioning., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Over the past two decades a relatively large number of studies have investigated the functional neuroanatomy of posttraumatic stress disorder (PTSD). However, findings are often inconsistent, thus challenging traditional neurocircuitry models of PTSD. As evidence mounts that cognition and behavior is an emergent property of interacting brain networks, the question arises whether PTSD can be understood by examining dysfunction in large-scale, spatially distributed neural networks. We used the activation likelihood estimation quantitative meta-analytic technique to synthesize findings across functional neuroimaging studies of PTSD that either used a non-trauma (N=20) or trauma-exposed (N=19) comparison control group. In line with neurocircuitry models, our findings support hyperactive amygdala and hypoactive medial prefrontal regions, but suggest hyperactive hippocampi. Characterization of additional regions under a triple network model showed functional alterations that largely overlapped with the salience network, central executive network, and default network. However, heterogeneity was observed within and across the neurocircuitry and triple network models, and between results based on comparisons to non-trauma and trauma-exposed control groups. Nonetheless, these results warrant further exploration of the neurocircuitry and large-scale network models in PTSD using connectivity analyses., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Studies of neurocognitive aging report altered patterns of brain activity in older versus younger adults performing executive function tasks. We review the extant literature, using activation likelihood estimation meta-analytic methods, to compare age-related differences in the pattern of brain activity across studies examining 2 categories of tasks associated with executive control processing: working memory and inhibition. In a direct contrast of young and older adult activations, older adults engaged bilateral regions of dorsolateral prefrontal cortex as well as supplementary motor cortex and left inferior parietal lobule during working memory. In contrast, age-related changes during inhibitory control were observed in right inferior frontal gyrus and presupplementary motor area. Additionally, when we examined task-related differences within each age group we observed the predicted pattern of differentiated neural response in the younger subjects: lateral prefrontal cortex activity associated with working memory versus right anterior insula/frontal opercular activity associated with inhibition. This separation was largely maintained in older subjects. These data provide the first quantitative meta-analytic evidence that age-related patterns of functional brain change during executive functioning depend on the specific control process being challenged., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Occupation has been associated with cognitive reserve in healthy aging and Alzheimer's disease. Here we assess the relationship between cerebral metabolic deficits in behavioral variant frontotemporal dementia (bvFTD) and occupation characteristics. Using factor analysis, we derived verbal, physical and visuospatial occupation scores from the US Department of Labor, Occupational Information Network and related these scores to regional cerebral metabolic rate of glucose utilization in 31 patients diagnosed with behavioral variant bvFTD, controlling for cognitive status (CERAD neuropsychological assessment battery), gender and education. Regression analyses showed a marked inverse association between glucose metabolism and (a) verbal occupation scores in left prefrontal cortex and, (b) physical occupation characteristics in right supplementary motor area. We concluded that, consistent with the cognitive reserve hypothesis, lifelong occupation characteristics are related to focal cerebral metabolic deficits in bvFTD. Specific occupation demands spanning decades may strengthen cognitive resistance to pathology., (Copyright © 2011 Elsevier Ltd. All rights reserved.)

Mental simulations are often focused on a goal in the future or a problem to be solved. Recent neuroimaging studies have associated mental simulations of the future with default network activity, but the simulations in these studies were not typically directed toward achieving a particular goal. Goal-directed simulation requires cognitive control to maintain information, make decisions, and coordinate abstract action sequences. Therefore, it should recruit not only the default network, but also executive regions. To investigate whether default network and executive regions can be coactive in the context of goal-directed simulation, we designed a problem-solving task in which participants simulated solving several specific problems in imaginary scenarios while in the MRI scanner. We analyzed brain activity during simulation relative to a semantic elaboration task and found that goal-directed simulation engaged core regions of the default network and executive dorsolateral prefrontal cortex. A functional connectivity analysis with posterior cingulate and dorsolateral prefrontal cortex seeds revealed that activity in these regions was coupled throughout the goal-directed simulation period and associated with a distributed network of other default and executive regions, including medial prefrontal cortex, medial temporal, and parietal regions., (Copyright © 2011 Elsevier Inc. All rights reserved.)

We conducted a systematic review of the neuroimaging literature examining cognition in old and young adults and quantified these findings in a series of meta-analyses using the activation likelihood estimation technique. In 80 independent samples, we assessed significant convergent and divergent patterns of brain activity across all studies; where task performance was equated or different between age groups; and in four specific cognitive domains (perception, memory encoding, memory retrieval and executive function). Age differences across studies predominantly involved regions within the 'task-positive network' of the brain, a set of interconnected regions engaged during a variety of externally driven cognitive tasks. Old adults engaged prefrontal regions more than young adults. When performance was equivalent, old adults engaged left prefrontal cortex; poorly performing old adults engaged right prefrontal cortex. Young adults engaged occipital regions more than old adults, particularly when performance was unequal and during perceptual tasks. No age-related differences were found in the parietal lobes. We discuss the reliable differences in brain activation with regards to current theories of neurocognitive aging.