Down but not out in posterior cingulate cortex: Deactivation yet functional coupling with prefrontal cortex during demanding semantic cognition

Distinctive and Complementary Roles of Default Mode Network Subsystems in Semantic Cognition

The default mode network (DMN) typically deactivates to external tasks, yet supports semantic cognition. It comprises medial temporal (MT), core, and frontotemporal (FT) subsystems, but its functional organization is unclear: the requirement for perceptual coupling versus decoupling, input modality (visual/verbal), type of information (social/spatial), and control demands all potentially affect its recruitment. We examined the effect of these factors on activation and deactivation of DMN subsystems during semantic cognition, across four task-based human functional magnetic resonance imaging (fMRI) datasets, and localized these responses in whole-brain state space defined by gradients of intrinsic connectivity. FT showed activation consistent with a central role across domains, tasks, and modalities, although it was most responsive to abstract, verbal tasks; this subsystem uniquely showed more "tuned" states characterized by increases in both activation and deactivation when semantic retrieval demands were higher. MT also activated to both perceptually coupled (scenes) and decoupled (autobiographical memory) tasks and showed stronger responses to picture associations, consistent with a role in scene construction. Core DMN consistently showed deactivation, especially to externally oriented tasks. These diverse contributions of DMN subsystems to semantic cognition were related to their location on intrinsic connectivity gradients: activation was closer to the sensory-motor cortex than deactivation, particularly for FT and MT, while activation for core DMN was distant from both visual cortex and cognitive control. These results reveal distinctive yet complementary DMN responses: MT and FT support different memory-based representations that are accessed externally and internally, while deactivation in core DMN is associated with demanding, external semantic tasks.

Modeling the neurocognitive dynamics of language across the lifespan

Healthy aging is associated with a heterogeneous decline across cognitive functions, typically observed between language comprehension and language production (LP). Examining resting-state fMRI and neuropsychological data from 628 healthy adults (age 18-88) from the CamCAN cohort, we performed state-of-the-art graph theoretical analysis to uncover the neural mechanisms underlying this variability. At the cognitive level, our findings suggest that LP is not an isolated function but is modulated throughout the lifespan by the extent of inter-cognitive synergy between semantic and domain-general processes. At the cerebral level, we show that default mode network (DMN) suppression coupled with fronto-parietal network (FPN) integration is the way for the brain to compensate for the effects of dedifferentiation at a minimal cost, efficiently mitigating the age-related decline in LP. Relatedly, reduced DMN suppression in midlife could compromise the ability to manage the cost of FPN integration. This may prompt older adults to adopt a more cost-efficient compensatory strategy that maintains global homeostasis at the expense of LP performances. Taken together, we propose that midlife represents a critical neurocognitive juncture that signifies the onset of LP decline, as older adults gradually lose control over semantic representations. We summarize our findings in a novel synergistic, economical, nonlinear, emergent, cognitive aging model, integrating connectomic and cognitive dimensions within a complex system perspective.

A common neural code for meaning in discourse production and comprehension

How does the brain code the meanings conveyed by language? Neuroimaging studies have investigated this by linking neural activity patterns during discourse comprehension to semantic models of language content. Here, we applied this approach to the production of discourse for the first time. Participants underwent fMRI while producing and listening to discourse on a range of topics. We used a distributional semantic model to quantify the similarity between different speech passages and identified where similarity in neural activity was predicted by semantic similarity. When people produced discourse, speech on similar topics elicited similar activation patterns in a widely distributed and bilateral brain network. This network was overlapping with, but more extensive than, the regions that showed similarity effects during comprehension. Critically, cross-task neural similarities between comprehension and production were also predicted by similarities in semantic content. This result suggests that discourse semantics engages a common neural code that is shared between comprehension and production. Effects of semantic similarity were bilateral in all three RSA analyses, even while univariate activation contrasts in the same data indicated left-lateralised BOLD responses. This indicates that right-hemisphere regions encode semantic properties even when they are not activated above baseline. We suggest that right-hemisphere regions play a supporting role in processing the meaning of discourse during both comprehension and production.

The Involvement of the Multiple Demand and Default Mode Networks in a Trial-by-Trial Cognitive Control

Adaptive behavior in the environment requires a high level of cognitive control to bias limited processing resources to behaviorally significant stimuli. Such control has been associated with a set of brain regions located in the fronto-parietal cortex (multiple demand network), whose activity was found to increase as the control demand for a task increases. In contrast, another set of regions, default mode network regions, were found to be deactivated during top-down processing of task stimuli. Despite this dissociation in their activation amplitudes, it is possible that activation patterns of these regions commonly encode specific task features. In two independent neuroimaging datasets, involving a total of 40 human samples, we found that the performance of an attentional task evoked positive activity of the MDN and deactivation of the DMN. Consistent with previous studies, task features could be decoded from the fronto-parietal cognitive regions. Importantly, the regions of the DMN also encoded task features when the task set had to be rapidly reconfigured in a transient, trial-by-trial manner, along with the MDN regions. These results suggest that the two separate brain networks ultimately co-ordinate for the effective establishment of top-down cognitive control.

Structural and functional neural substrates underlying the concreteness effect

The concreteness effect refers to the advantage in speed and accuracy of processing concrete words over abstract words. Previous studies have shown that the processing of the two types of words is mediated by distinct neural mechanisms, but these studies were mainly conducted with task-based functional magnetic resonance imaging. This study investigates the associations between the concreteness effect and grey matter volume (GMV) of brain regions as well as resting-state functional connectivity (rsFC) of these identified regions. The results show that the GMV of left inferior frontal gyrus (IFG), right middle temporal gyrus (MTG), right supplementary motor area and right anterior cingulate cortex (ACC) negatively correlates with the concreteness effect. The rsFC of the left IFG, the right MTG and the right ACC with the nodes, mainly in default mode network, frontoparietal network and dorsal attention network positively correlates with the concreteness effect. The GMV and rsFC jointly and respectively predict the concreteness effect in individuals. In conclusion, stronger connectivity amongst functional networks and higher coherent engagement of the right hemisphere predict a greater difference in the verbal memory of abstract and concrete words.

Default mode network scaffolds immature frontoparietal network in cognitive development

The default mode network (DMN) is a workspace for convergence of internal and external information. The frontal parietal network (FPN) is indispensable to executive functioning. Yet, how they interplay to support cognitive development remains elusive. Using longitudinal developmental fMRI with an n-back paradigm, we show a heterogeneity of maturational changes in multivoxel activity and network connectivity among DMN and FPN nodes in 528 children and 103 young adults. Compared with adults, children exhibited prominent longitudinal improvement but still inferior behavioral performance, which paired with less pronounced DMN deactivation and weaker FPN activation in children, but stronger DMN coupling with FPN regions. Children's DMN reached an adult-like level earlier than FPN at both multivoxel activity pattern and intranetwork connectivity levels. Intrinsic DMN-FPN internetwork coupling in children mediated the relationship between age and working memory-related functional coupling of these networks, with posterior cingulate cortex (PCC)-dorsolateral prefrontal cortex (DLPFC) coupling emerging as most prominent pathway. Coupling of PCC-DLPFC may further work together with task-invoked activity in PCC to account for longitudinal improvement in behavioral performance in children. Our findings suggest that the DMN provides a scaffolding effect in support of an immature FPN that is critical for the development of executive functions in children.

Distinct patterns of cortical manifold expansion and contraction underlie human sensorimotor adaptation

Sensorimotor learning is a dynamic, systems-level process that involves the combined action of multiple neural systems distributed across the brain. Although much is known about the specialized cortical systems that support specific components of action (such as reaching), we know less about how cortical systems function in a coordinated manner to facilitate adaptive behavior. To address this gap, our study measured human brain activity using functional MRI (fMRI) while participants performed a classic sensorimotor adaptation task and used a manifold learning approach to describe how behavioral changes during adaptation relate to changes in the landscape of cortical activity. During early adaptation, areas in the parietal and premotor cortices exhibited significant contraction along the cortical manifold, which was associated with their increased covariance with regions in the higher-order association cortex, including both the default mode and fronto-parietal networks. By contrast, during Late adaptation, when visuomotor errors had been largely reduced, a significant expansion of the visual cortex along the cortical manifold was associated with its reduced covariance with the association cortex and its increased intraconnectivity. Lastly, individuals who learned more rapidly exhibited greater covariance between regions in the sensorimotor and association cortices during early adaptation. These findings are consistent with a view that sensorimotor adaptation depends on changes in the integration and segregation of neural activity across more specialized regions of the unimodal cortex with regions in the association cortex implicated in higher-order processes. More generally, they lend support to an emerging line of evidence implicating regions of the default mode network (DMN) in task-based performance.

Creativity in verbal associations is linked to semantic control

Although memory is known to play a key role in creativity, previous studies have not isolated the critical component processes and networks. We asked participants to generate links between words that ranged from strongly related to completely unrelated in long-term memory, delineating the neurocognitive processes that underpin more unusual versus stereotypical patterns of retrieval. More creative responses to strongly associated word-pairs were associated with greater engagement of episodic memory: in highly familiar situations, semantic, and episodic stores converge on the same information enabling participants to form a personal link between items. This pattern of retrieval was associated with greater engagement of core default mode network (DMN). In contrast, more creative responses to weakly associated word-pairs were associated with the controlled retrieval of less dominant semantic information and greater recruitment of the semantic control network, which overlaps with the dorsomedial subsystem of DMN. Although both controlled semantic and episodic patterns of retrieval are associated with activation within DMN, these processes show little overlap in activation. These findings demonstrate that controlled aspects of semantic cognition play an important role in verbal creativity.

Age-related reorganization of functional network architecture in semantic cognition

Cognitive aging is associated with widespread neural reorganization processes in the human brain. However, the behavioral impact of such reorganization is not well understood. The current neuroimaging study investigated age differences in the functional network architecture during semantic word retrieval in young and older adults. Combining task-based functional connectivity, graph theory and cognitive measures of fluid and crystallized intelligence, our findings show age-accompanied large-scale network reorganization even when older adults have intact word retrieval abilities. In particular, functional networks of older adults were characterized by reduced decoupling between systems, reduced segregation and efficiency, and a larger number of hub regions relative to young adults. Exploring the predictive utility of these age-related changes in network topology revealed high, albeit less efficient, performance for older adults whose brain graphs showed stronger dedifferentiation and reduced distinctiveness. Our results extend theoretical accounts on neurocognitive aging by revealing the compensational potential of the commonly reported pattern of network dedifferentiation when older adults can rely on their prior knowledge for successful task processing. However, we also demonstrate the limitations of such compensatory reorganization and show that a youth-like network architecture in terms of balanced integration and segregation is associated with more economical processing.

Disruption of Functional Brain Networks Underlies the Handwriting Deficit in Children With Developmental Dyslexia

Developmental dyslexia (DD) is a neurological-based learning disorder that affects 5-17.5% of children. Handwriting difficulty is a prevailing symptom of dyslexia, but its neural mechanisms remain elusive. Using functional magnetic resonance imaging (fMRI), this study examined functional brain networks associated with handwriting in a copying task in Chinese children with DD (n = 17) and age-matched children (n = 36). We found that dyslexics showed reduced network connectivity between the sensory-motor network (SMN) and the visual network (VN), and between the default mode network (DMN) and the ventral attention network (VAN) during handwriting, but not during drawing geometric figures. Moreover, the connectivity strength of the networks showing group differences was correlated with handwriting speed, reading and working memory, suggesting that the handwriting deficit in DD is linked with disruption of a large-scale brain network supporting motoric, linguistic and executive control processes. Taken together, this study demonstrates the alternations of functional brain networks that underly the handwriting deficit in Chinese dyslexia, providing a new clue for the neural basis of DD.

A voice without a mouth no more: The neurobiology of language and consciousness

Most research on the neurobiology of language ignores consciousness and vice versa. Here, language, with an emphasis on inner speech, is hypothesised to generate and sustain self-awareness, i.e., higher-order consciousness. Converging evidence supporting this hypothesis is reviewed. To account for these findings, a 'HOLISTIC' model of neurobiology of language, inner speech, and consciousness is proposed. It involves a 'core' set of inner speech production regions that initiate the experience of feeling and hearing words. These take on affective qualities, deriving from activation of associated sensory, motor, and emotional representations, involving a largely unconscious dynamic 'periphery', distributed throughout the whole brain. Responding to those words forms the basis for sustained network activity, involving 'default mode' activation and prefrontal and thalamic/brainstem selection of contextually relevant responses. Evidence for the model is reviewed, supporting neuroimaging meta-analyses conducted, and comparisons with other theories of consciousness made. The HOLISTIC model constitutes a more parsimonious and complete account of the 'neural correlates of consciousness' that has implications for a mechanistic account of mental health and wellbeing.

Simulated Attack Reveals How Lesions Affect Network Properties in Poststroke Aphasia

Aphasia is a prevalent cognitive syndrome caused by stroke. The rarity of premorbid imaging and heterogeneity of lesion obscures the links between the local effects of the lesion, global anatomic network organization, and aphasia symptoms. We applied a simulated attack approach in humans to examine the effects of 39 stroke lesions (16 females) on anatomic network topology by simulating their effects in a control sample of 36 healthy (15 females) brain networks. We focused on measures of global network organization thought to support overall brain function and resilience in the whole brain and within the left hemisphere. After removing lesion volume from the network topology measures and behavioral scores [the Western Aphasia Battery Aphasia Quotient (WAB-AQ), four behavioral factor scores obtained from a neuropsychological battery, and a factor sum], we compared the behavioral variance accounted for by simulated poststroke connectomes to that observed in the randomly permuted data. Global measures of anatomic network topology in the whole brain and left hemisphere accounted for 10% variance or more of the WAB-AQ and the lexical factor score beyond lesion volume and null permutations. Streamline networks provided more reliable point estimates than FA networks. Edge weights and network efficiency were weighted most highly in predicting the WAB-AQ for FA networks. Overall, our results suggest that global network measures provide modest statistical value beyond lesion volume when predicting overall aphasia severity, but less value in predicting specific behaviors. Variability in estimates could be induced by premorbid ability, deafferentation and diaschisis, and neuroplasticity following stroke.SIGNIFICANCE STATEMENT Poststroke, the remaining neuroanatomy maintains cognition and supports recovery. However, studies often use small, cross-sectional samples that cannot fully model the interactions between lesions and other variables that affect networks in stroke. Alternate methods are required to account for these effects. "Simulated attack" models are computational approaches that apply virtual damage to the brain and measure their putative consequences. Using a simulated attack model, we estimated how simulated damage to anatomic networks could account for language performance. Overall, our results reveal that global network measures can provide modest statistical value predicting overall aphasia severity, but less value in predicting specific behaviors. These findings suggest that more theoretically precise network models could be necessary to robustly predict individual outcomes in aphasia.

Tasks activating the default mode network map multiple functional systems

Recent developments in network neuroscience suggest reconsidering what we thought we knew about the default mode network (DMN). Although this network has always been seen as unitary and associated with the resting state, a new deconstructive line of research is pointing out that the DMN could be divided into multiple subsystems supporting different functions. By now, it is well known that the DMN is not only deactivated by tasks, but also involved in affective, mnestic, and social paradigms, among others. Nonetheless, it is starting to become clear that the array of activities in which it is involved, might also be extended to more extrinsic functions. The present meta-analytic study is meant to push this boundary a bit further. The BrainMap database was searched for all experimental paradigms activating the DMN, and their activation likelihood estimation maps were then computed. An additional map of task-induced deactivations was also created. A multidimensional scaling indicated that such maps could be arranged along an anatomo-psychological gradient, which goes from midline core activations, associated with the most internal functions, to that of lateral cortices, involved in more external tasks. Further multivariate investigations suggested that such extrinsic mode is especially related to reward, semantic, and emotional functions. However, an important finding was that the various activation maps were often different from the canonical representation of the resting-state DMN, sometimes overlapping with it only in some peripheral nodes, and including external regions such as the insula. Altogether, our findings suggest that the intrinsic-extrinsic opposition may be better understood in the form of a continuous scale, rather than a dichotomy.

Generalizable predictive modeling of semantic processing ability from functional brain connectivity

Semantic processing (SP) is one of the critical abilities of humans for representing and manipulating conceptual and meaningful information. Neuroimaging studies of SP typically collapse data from many subjects, but its neural organization and behavioral performance vary between individuals. It is not yet understood whether and how the individual variabilities in neural network organizations contribute to the individual differences in SP behaviors. We aim to identify the neural signatures underlying SP variabilities by analyzing functional connectivity (FC) patterns based on a large‐sample Human Connectome Project (HCP) dataset and rigorous predictive modeling. We used a two‐stage predictive modeling approach to build an internally cross‐validated model and to test the model's generalizability with unseen data from different HCP samples and other out‐of‐sample datasets. FC patterns within a putative semantic brain network were significantly predictive of individual SP scores summarized from five SP‐related behavioral tests. This cross‐validated model can be used to predict unseen HCP data. The model generalizability was enhanced in the language task compared with other tasks used during scanning and was better for females than males. The model constructed from the HCP dataset can be partially generalized to two independent cohorts that participated in different semantic tasks. FCs connecting to the Perisylvian language network show the most reliable contributions to predictive modeling and the out‐of‐sample generalization. These findings contribute to our understanding of the neural sources of individual differences in SP, which potentially lay the foundation for personalized education for healthy individuals and intervention for SP and language deficits patients.

The olfactory bulb coordinates the ventral hippocampus-medial prefrontal cortex circuit during spatial working memory performance

Neural oscillations synchronize the activity of brain regions during cognitive functions, such as spatial working memory. Olfactory bulb (OB) oscillations are ubiquitous rhythms that can modulate neocortical and limbic regions. However, the functional connectivity between the OB and areas contributing to spatial working memory, such as the ventral hippocampus (vHPC) and medial prefrontal cortex (mPFC), is less understood. Hence, we investigated functional interaction between OB and the vHPC-mPFC circuit during the spatial working memory performance in rats. To this end, we analyzed the simultaneously recorded local field potentials from OB, vHPC, and mPFC when rats explored the Y-maze and compared the brain activities of correct trials vs. wrong trials. We found that coupling between the vHPC and mPFC was augmented during correct trials. The enhanced coherence of OB activity with the vHPC-mPFC circuit at delta (< 4 Hz) and gamma (50-80 Hz) ranges were observed during correct trials. The cross-frequency analysis revealed that the OB delta phase increased the mPFC gamma power within corrected trials, indicating a modulatory role of OB oscillations on mPFC activity during correct trials. Moreover, the correlation between OB oscillations and the vHPC-mPFC circuit was increased at the delta range during correct trials, exhibiting enhanced synchronized activity of these regions during the cognitive task. We demonstrated a functional engagement of OB connectivity with the vHPC-mPFC circuit during spatial working memory task performance.

Involvement of the default mode network under varying levels of cognitive effort

Everyday cognitive functioning is characterized by constant alternations between different modes of information processing, driven by constant fluctuations in environmental demands. At the neural level, this is realized through corresponding dynamic shifts in functional activation and network connectivity. A distinction is often made between resting and task processing and between task-negative and task-positive functional networks. The Default Mode Network (DMN) is classically considered as a resting state (i.e. task-negative) network, upregulated in the absence of cognitive demands. In contrast, task-positive networks have been labelled the Extrinsic Mode Network (EMN). We investigated changes in brain activation and functional network connectivity in an experimental situation of repeated alterations between levels of cognitive effort, following a block-design. Using fMRI and a classic Stroop paradigm, participants switched back and forth between periods of no effort (resting), low effort (word reading, i.e. automatic processing based on learned internal representations and rules) and high effort (color naming, i.e. cognitively controlled perceptual processing of specific features of external stimuli). Results showed an expected EMN-activation for task versus resting contrasts, and DMN-activation for rest versus task contrasts. The DMN was in addition more strongly activated during periods of low effort contrasted with high effort, suggesting a gradual up- and down-regulation of the DMN network, depending on the level of demand and the type of processing required. The often reported “anti-correlation” between DMN and EMN was strongest during periods of low effort, indicating intermittent contributions of both networks. Taken together, these results challenge the traditional view of the DMN as solely a task-negative network. Instead, both the EMN and DMN may contribute to low-effort cognitive processing. In contrast, periods of resting and high effort are dominated by the DMN and EMN, respectively.

Intrinsic connectivity of left ventrolateral prefrontal cortex predicts individual differences in controlled semantic retrieval

Control processes allow us to constrain the retrieval of semantic information from long-term memory so that it is appropriate for the task or context. Control demands are influenced by the strength of the target information itself and by the circumstances in which it is retrieved, with more control needed when relatively weak aspects of knowledge are required and after the sustained retrieval of related concepts. To investigate the neurocognitive basis of individual differences in these aspects of semantic control, we used resting-state fMRI to characterise the intrinsic connectivity of left ventrolateral prefrontal cortex (VLPFC), implicated in controlled retrieval, and examined associations on a paced serial semantic task, in which participants were asked to detect category members amongst distractors. This task manipulated both the strength of target associations and the requirement to sustain retrieval within a narrow semantic category over time. We found that individuals with stronger connectivity between VLPFC and medial prefrontal cortex within the default mode network (DMN) showed better retrieval of strong associations (which are thought to be recalled more automatically). Stronger connectivity between the same VLPFC seed and another DMN region in medial parietal cortex was associated with larger declines in retrieval over the course of the category. In contrast, participants with stronger connectivity between VLPFC and cognitive control regions within the ventral attention network (VAN) had better controlled retrieval of weak associations and were better able to sustain their comprehension throughout the category. These effects overlapped in left insular cortex within the VAN, indicating that a common pattern of connectivity is associated with different aspects of controlled semantic retrieval induced by both the structure of long-term knowledge and the sustained retrieval of related information.

Network Analysis of Human Brain Connectivity Reveals Neural Fingerprints of a Compositionality Bias in Signaling Systems

Compositionality is a hallmark of human language and other symbolic systems: a finite set of meaningful elements can be systematically combined to convey an open-ended array of ideas. Compositionality is not uniformly distributed over expressions in a language or over individuals' communicative behavior: at both levels, variation is observed. Here, we investigate the neural bases of interindividual variability by probing the relationship between intrinsic characteristics of brain networks and compositional behavior. We first collected functional resting-state and diffusion magnetic resonance imaging data from a large participant sample (N = 51). Subsequently, participants took part in two signaling games. They were instructed to learn and reproduce an auditory symbolic system of signals (tone sequences) associated with affective meanings (human faces expressing emotions). Signal-meaning mappings were artificial and had to be learned via repeated signaling interactions. We identified a temporoparietal network in which connection length was related to the degree of compositionality introduced in a signaling system by each player. Graph-theoretic analysis of resting-state functional connectivity revealed that, within that network, compositional behavior was associated with integration measures in 2 semantic hubs: the left posterior cingulate cortex and the left angular gyrus. Our findings link individual variability in compositional biases to variation in the anatomy of semantic networks and in the functional topology of their constituent units.

Age-Dependent Contribution of Domain-General Networks to Semantic Cognition

Aging is characterized by a decline of cognitive control. In semantic cognition, this leads to the paradox that older adults usually show poorer task performance than young adults despite their greater semantic knowledge. So far, the underlying neural changes of these behavioral differences are poorly understood. In the current neuroimaging study, we investigated the interaction of domain-specific and domain-general networks during verbal semantic fluency in young and older adults. Across age groups, task processing was characterized by a strong positive integration within the multiple-demand as well as between the multiple-demand and the default mode network during semantic fluency. However, the behavioral relevance of strengthened connectivity differed between groups: While within-network functional connectivity in both networks predicted greater efficiency in semantic fluency in young adults, it was associated with slower performance in older adults. Moreover, only young adults profited from connectivity between networks for their semantic memory performance. Our results suggest that the functional coupling of usually anticorrelated networks is critical for successful task processing, independent of age, when access to semantic memory is required. Furthermore, our findings lend novel support to the notion of reduced efficiency in the aging brain due to neural dedifferentiation in semantic cognition.

The default mode network in cognition: a topographical perspective

The default mode network (DMN) is a set of widely distributed brain regions in the parietal, temporal and frontal cortex. These regions often show reductions in activity during attention-demanding tasks but increase their activity across multiple forms of complex cognition, many of which are linked to memory or abstract thought. Within the cortex, the DMN has been shown to be located in regions furthest away from those contributing to sensory and motor systems. Here, we consider how our knowledge of the topographic characteristics of the DMN can be leveraged to better understand how this network contributes to cognition and behaviour.

Second-language word recognition in noise: Interdependent neuromodulatory effects of semantic context and crosslinguistic interactions driven by word form similarity

Spoken language comprehension is a fundamental component of our cognitive skills. We are quite proficient at deciphering words from the auditory input despite the fact that the speech we hear is often masked by noise such as background babble originating from talkers other than the one we are attending to. To perceive spoken language as intended, we rely on prior linguistic knowledge and context. Prior knowledge includes all sounds and words that are familiar to a listener and depends on linguistic experience. For bilinguals, the phonetic and lexical repertoire encompasses two languages, and the degree of overlap between word forms across languages affects the degree to which they influence one another during auditory word recognition. To support spoken word recognition, listeners often rely on semantic information (i.e., the words we hear are usually related in a meaningful way). Although the number of multilinguals across the globe is increasing, little is known about how crosslinguistic effects (i.e., word overlap) interact with semantic context and affect the flexible neural systems that support accurate word recognition. The current multi-echo functional magnetic resonance imaging (fMRI) study addresses this question by examining how prime-target word pair semantic relationships interact with the target word's form similarity (cognate status) to the translation equivalent in the dominant language (L1) during accurate word recognition of a non-dominant (L2) language. We tested 26 early-proficient Spanish-Basque (L1-L2) bilinguals. When L2 targets matching L1 translation-equivalent phonological word forms were preceded by unrelated semantic contexts that drive lexical competition, a flexible language control (fronto-parietal-subcortical) network was upregulated, whereas when they were preceded by related semantic contexts that reduce lexical competition, it was downregulated. We conclude that an interplay between semantic and crosslinguistic effects regulates flexible control mechanisms of speech processing to facilitate L2 word recognition, in noise.

Semantic Clustering During Verbal List Learning Is Associated With Employment Status in a Community Sample

The ability to learn and remember verbal information is highly relevant to many work roles and environments, but we know little about the underlying cognitive mechanisms of those associations. This study examined the hypothesis that unemployment is associated with decreased spontaneous use of higher-order encoding strategies deployed during list learning and recall. Participants were 120 employed and 59 unemployed community-dwelling adults who completed the California Verbal Learning Test-Second Edition (CVLT-II) as part of a broader neuropsychological assessment. Standardized measures of semantic, serial, and subjective clustering were generated from the CVLT-II. After adjusting for data-driven covariates, a significant interaction emerged between employment status and clustering strategy, whereby participants in the employed group exhibited significantly higher scores on semantic clustering, but not serial or subjective clustering, than the unemployed group. The semantic clustering slope score was higher among the employed group and was positively associated with executive functions and declarative memory. These findings suggest that higher-order semantic organizational strategies during supraspan list learning may be relevant to maintaining gainful employment (e.g., mentally organizing work-related instructions and task lists). Future studies might examine semantic clustering in relation to employment changes and work performance, as well as the potential benefit of metacognitive interventions for learning and employment success.

A Functional MRI Paradigm for Efficient Mapping of Memory Encoding Across Sensory Conditions

We introduce a new and time-efficient memory-encoding paradigm for functional magnetic resonance imaging (fMRI). This paradigm is optimized for mapping multiple contrasts using a mixed design, using auditory (environmental/vocal) and visual (scene/face) stimuli. We demonstrate that the paradigm evokes robust neuronal activity in typical sensory and memory networks. We were able to detect auditory and visual sensory-specific encoding activities in auditory and visual cortices. Also, we detected stimulus-selective activation in environmental-, voice-, scene-, and face-selective brain regions (parahippocampal place and fusiform face area). A subsequent recognition task allowed the detection of sensory-specific encoding success activity (ESA) in both auditory and visual cortices, as well as sensory-unspecific positive ESA in the hippocampus. Further, sensory-unspecific negative ESA was observed in the precuneus. Among others, the parallel mixed design enabled sustained and transient activity comparison in contrast to rest blocks. Sustained and transient activations showed great overlap in most sensory brain regions, whereas several regions, typically associated with the default-mode network, showed transient rather than sustained deactivation. We also show that the use of a parallel mixed model had relatively little influence on positive or negative ESA. Together, these results demonstrate a feasible, versatile, and brief memory-encoding task, which includes multiple sensory stimuli to guarantee a comprehensive measurement. This task is especially suitable for large-scale clinical or population studies, which aim to test task-evoked sensory-specific and sensory-unspecific memory-encoding performance as well as broad sensory activity across the life span within a very limited time frame.

Knowing what you need to know in advance: The neural processes underpinning flexible semantic retrieval of thematic and taxonomic relations

Semantic retrieval is flexible, allowing us to focus on subsets of features and associations that are relevant to the current task or context: for example, we use taxonomic relations to locate items in the supermarket (carrots are a vegetable), but thematic associations to decide which tools we need when cooking (carrot goes with peeler). We used fMRI to investigate the neural basis of this form of semantic flexibility; in particular, we asked how retrieval unfolds differently when participants have advanced knowledge of the type of link to retrieve between concepts (taxonomic or thematic). Participants performed a semantic relatedness judgement task: on half the trials, they were cued to search for a taxonomic or thematic link, while on the remaining trials, they judged relatedness without knowing which type of semantic relationship would be relevant. Left inferior frontal gyrus showed greater activation when participants knew the trial type in advance. An overlapping region showed a stronger response when the semantic relationship between the items was weaker, suggesting this structure supports both top-down and bottom-up forms of semantic control. Multivariate pattern analysis further revealed that the neural response in left inferior frontal gyrus reflects goal information related to different conceptual relationships. Top-down control specifically modulated the response in visual cortex: when the goal was unknown, there was greater deactivation to the first word, and greater activation to the second word. We conclude that top-down control of semantic retrieval is primarily achieved through the gating of task-relevant 'spoke' regions.

Functional parcellation of the right cerebellar lobule VI in children with normal or impaired reading

Neuroimaging studies have reported that the right cerebellar lobule VI is engaged in reading, but its role is unclear. The goal of our study was to identify functionally-dissociable subregions in the right lobule VI and how these subregions contribute to reading in children with normal or impaired reading. In Experiment I, typically developing children performed an orthographic task and a phonological task during functional magnetic resonance imaging (fMRI). We classified the voxels in the right lobule VI into seven zones based on the patterns of functional connectivity with the cerebrum across both tasks. In Experiment II, we compared the brain activation and cerebro-cerebellar connectivities of each subregion between children readers with different reading levels. We did not find significant group differences in cerebellar activation. However, we found that impaired readers had considerably higher functional connectivity between R1 and the right angular gyrus and the right precuneus compared to the control group in the phonological task. These findings show that the right cerebellar lobule VI is functionally parceled and its subregions might be differentially connected with the cerebrum between children with normal reading abilities and those with impaired reading.

Evoked and intrinsic brain network dynamics in children with autism spectrum disorder

OBJECTIVE

Brain dynamics underlie flexible cognition and behavior, yet little is known regarding this relationship in autism spectrum disorder (ASD). We examined time-varying changes in functional co-activation patterns (CAPs) across rest and task-evoked brain states to characterize differences between children with ASD and typically developing (TD) children and identify relationships with severity of social behaviors and restricted and repetitive behaviors.

METHOD

17 children with ASD and 27 TD children ages 7-12 completed a resting-state fMRI scan and four runs of a non-cued attention switching task. Metrics indexing brain dynamics were generated from dynamic CAPs computed across three major large-scale brain networks: midcingulo-insular (M-CIN), medial frontoparietal (M-FPN), and lateral frontoparietal (L-FPN).

RESULTS

Five time-varying CAPs representing dynamic co-activations among network nodes were identified across rest and task fMRI datasets. Significant Diagnosis × Condition interactions were observed for the dwell time of CAP 3, representing co-activation between nodes of the M-CIN and L-FPN, and the frequency of CAP 1, representing co-activation between nodes of the L-FPN. A significant brain-behavior association between dwell time of CAP 5, representing co-activation between nodes of the M-FPN, and social abilities was also observed across both groups of children.

CONCLUSION

Analysis of brain co-activation patterns reveals altered dynamics among three core networks in children with ASD, particularly evident during later stages of an attention task. Dimensional analyses demonstrating relationships between M-FPN dwell time and social abilities suggest that metrics of brain dynamics may index individual differences in social cognition and behavior.

Oxytocin modulates the effective connectivity between the precuneus and the dorsolateral prefrontal cortex

Our social activity is heavily influenced by the process of introspection, with emerging research suggesting a role for the Default Mode Network (DMN) in social cognition. We hypothesize that oxytocin, a neuropeptide with an important role in social behaviour, can effectively alter the connectivity of the DMN. We test this hypothesis using a randomized, double-blind, crossover, placebo-controlled trial where 15 healthy male participants received 24 IU oxytocin or placebo prior to a resting-state functional MRI scan. We used Granger Causality Analysis for the first time to probe the role of oxytocin on brain networks and found that oxytocin reverses the pattern of effective connectivity between the bilateral precuneus and the left dorsolateral prefrontal cortex (dlPFC), a key central executive network (CEN) region. Under placebo, the bilateral precuneus exerted a significant negative causal influence on the left dlPFC and the left dlPFC exerted a significant positive causal influence on the bilateral precuneus. However, under oxytocin, these patterns were reversed, i.e. positive causal influence from the bilateral precuneus to the left dlPFC and negative causal influence from the left dlPFC to the bilateral precuneus (with statistically significant effects for the right precuneus). We propose that these oxytocin-induced effects could be a mechanistic process by which it modulates social cognition. These results provide a measurable target for the physiological effects of oxytocin in the brain and offer oxytocin as a potential agent to enhance the cooperative role of the predominantly 'task-inactive' 'default mode' brain regions in both healthy and patient populations.

Age-related change in episodic memory: role of functional and structural connectivity between the ventral posterior cingulate and the parietal cortex

While the neural correlates of age-related episodic memory decline have been extensively studied, the precise involvement of the Posterior Cingulate Cortex (PCC) and posterior parietal cortex (the precuneus and the angular gyrus), remains unclear. The present study examined functional and structural neural correlates of age-related episodic memory change assessed over 12 years in 120 older adults (range 76-90 years). Episodic memory performance was measured using the Free and Cued Selective Reminding Test (FCSRT); functional connectivity metrics were computed from resting-state fMRI images and structural connectivity metrics were assessed through microstructural properties of reconstructed tract using a native space pipeline. We found that FCSRT change was significantly associated with the functional connectivity between the ventral PCC and three parietal regions, the ventral superior, the inferior part of the precuneus, and the rostro dorsal part of the angular gyrus. This association was independent of hippocampal volume. In addition, we found the that change in FCSRT scores was associated with fractional anisotropy of the tract connecting the ventral PCC and the ventral superior part of the precuneus. Change in episodic memory in aging was therefore related to a combination of high functional connectivity and low structural connectivity between the ventral PCC and the ventral superior part of the precuneus.

Atypical age-related changes in cortical thickness in autism spectrum disorder

Recent longitudinal neuroimaging and neurophysiological studies have shown that tracking relative age-related changes in neural signals, rather than a static snapshot of a neural measure, could offer higher sensitivity for discriminating typically developing (TD) individuals from those with autism spectrum disorder (ASD). It is not clear, however, which aspects of age-related changes (trajectories) would be optimal for identifying atypical brain development in ASD. Using a large cross-sectional data set (Autism Brain Imaging Data Exchange [ABIDE] repository; releases I and II), we aimed to explore age-related changes in cortical thickness (CT) in TD and ASD populations (age range 6–30 years old). Cortical thickness was estimated from T1-weighted MRI images at three scales of spatial coarseness (three parcellations with different numbers of regions of interest). For each parcellation, three polynomial models of age-related changes in CT were tested. Specifically, to characterize alterations in CT trajectories, we compared the linear slope, curvature, and aberrancy of CT trajectories across experimental groups, which was estimated using linear, quadratic, and cubic polynomial models, respectively. Also, we explored associations between age-related changes with ASD symptomatology quantified as the Autism Diagnostic Observation Schedule (ADOS) scores. While no overall group differences in cortical thickness were observed across the entire age range, ASD and TD populations were different in terms of age-related changes, which were located primarily in frontal and tempo-parietal areas. These atypical age-related changes were also associated with ADOS scores in the ASD group and used to predict ASD from TD development. These results indicate that the curvature is the most reliable feature for localizing brain areas developmentally atypical in ASD with a more pronounced effect with symptomatology and is the most sensitive in predicting ASD development.

The role of default mode network in semantic cue integration

Recent accounts of large-scale cortical organisation suggest that the default mode network (DMN) is positioned at the top of a principal gradient, reflecting the separation between heteromodal and unimodal sensory-motor regions in patterns of connectivity and in geodesic distance along the cortical surface (Margulies et al., 2016). This isolation of DMN from external inputs might allow the integration of disparate sources of information that can constrain subsequent cognition. We tested this hypothesis by manipulating the degree to which semantic decisions for ambiguous words (e.g. jam) were constrained by preceding visual cues depicting relevant spatial contexts (e.g. supermarket or road) and/or facial emotions (e.g. happy vs. frustrated). We contrasted (i) the effects of a single preceding cue with a no-cue condition employing scrambled images, and (ii) convergent spatial and emotion cues with single cues. Single cues elicited stronger activation in the multiple demand network relative to no cues, consistent with the requirement to maintain information in working memory. The availability of two convergent cues elicited stronger activation within DMN regions (bilateral angular gyrus, middle temporal gyrus, medial prefrontal cortex, and posterior cingulate), even though behavioural performance was unchanged by cueing – consequently task difficulty is unlikely to account for the observed differences in brain activation. A regions-of-interest analysis along the unimodal-to-heteromodal principal gradient revealed maximal activation for the convergent cue condition at the heteromodal end, corresponding to the DMN. Our findings are consistent with the view that regions of DMN support states of information integration that constrain ongoing cognition and provide a framework for understanding the location of these effects at the heteromodal end of the principal gradient.

Revealing the neural networks that extract conceptual gestalts from continuously evolving or changing semantic contexts

Reading a book, understanding the news reports or any other behaviour involving the processing of meaningful stimuli requires the semantic system to have two main features: being active during an extended period of time and flexibly adapting the internal representation according to the changing environment. Despite being key features of many everyday tasks, formation and updating of the semantic “gestalt” are still poorly understood. In this fMRI study we used naturalistic stimuli and task manipulations to identify the neural network that forms and updates conceptual gestalts during time-extended integration of meaningful stimuli. Univariate and multivariate techniques allowed us to draw a distinction between networks that are crucial for the formation of a semantic gestalt (meaning integration) and those that instead are important for linking incoming cues about the current context (e.g., time and space cues) into a schema representation. Specifically, we revealed that time-extended formation of the conceptual gestalt was reflected in the neuro-computations of the anterior temporal lobe accompanied by multi-demand areas and hippocampus, with a key role of brain structures in the right hemisphere. This “semantic gestalt network” was strongly recruited when an update of the current semantic representation was required during narrative processing. A distinct fronto-parietal network, instead, was recruited for context integration, independently from the meaning associations between words (semantic coherence). Finally, in contrast with accounts positing that the default mode network (DMN) may have a crucial role in semantic cognition, our findings revealed that DMN activity was sensitive to task difficulty, but not to semantic integration. The implications of these findings for neurocognitive models of semantic cognition and the literature on narrative processing are discussed.

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fMRI revealed areas and networks for semantic integration during narrative reading.

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ATL has a key role in the formation of the conceptual gestalt.

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IFG, pMTG and dAG support the update of the conceptual gestalt.

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Left AG (mid-PGp) has a key role in context integration.

Reorganisation of Brain Hubs across Altered States of Consciousness

Patterns of functional interactions across distributed brain regions are suggested to provide a scaffold for the conscious processing of information, with marked topological alterations observed in loss of consciousness. However, establishing a firm link between macro-scale brain network organisation and conscious cognition requires direct investigations into neuropsychologically-relevant architectural modifications across systematic reductions in consciousness. Here we assessed both global and regional disturbances to brain graphs in a group of healthy participants across baseline resting state fMRI as well as two distinct levels of propofol-induced sedation. We found a persistent modular architecture, yet significant reorganisation of brain hubs that formed parts of a wider rich-club collective. Furthermore, the reduction in the strength of rich-club connectivity was significantly associated with the participants’ performance in a semantic judgment task, indicating the importance of this higher-order topological feature for conscious cognition. These results highlight a remarkable interplay between global and regional properties of brain functional interactions in supporting conscious cognition that is relevant to our understanding of clinical disorders of consciousness.

A systematic review of brain functional connectivity patterns involved in episodic and semantic memory

The study of functional connectivity and declarative memory has lately been focused on finding biomarkers of neuropsychological diseases. However, little is known about its patterns in healthy brains. Thus, in this systematic review we analyze and integrate the findings of 81 publications regarding functional connectivity (measured by fMRI during both task and resting-state) and semantic and episodic memory in healthy adults. Moreover, we discriminate and analyze the main areas and links found in specific memory phases (encoding, storage or retrieval) based on several criteria, such as time length, depth of processing, rewarding value of the information, vividness and amount or kind of details retrieved. There is a certain degree of overlap between the networks of episodic and semantic memory and between the encoding and retrieval stages. Although several differences are pointed out during the article, this calls to attention the need for further empirical studies that actively compare both types of memory, particularly using other baseline conditions apart from the traditional resting state. Indeed, the active involvement of the default mode network in both declarative memory and resting condition suggests the possibility that during rest there is an on-going memory processing. We find support for the 'attention to memory' hypothesis, the memory differentiation model and the appropriate transfer hypothesis, but some evidence is inconsistent with the traditional hub-and-spoke model.

Hello, is that me you are looking for? A re-examination of the role of the DMN in social and self relevant aspects of off-task thought

Neural activity within the default mode network (DMN) is widely assumed to relate to processing during off-task states, however it remains unclear whether this association emerges from a shared role in self or social content that is common in these conditions. In the current study, we examine the possibility that the role of the DMN in ongoing thought emerges from contributions to specific features of off-task experience such as self-relevant or social content. A group of participants described their experiences while performing a laboratory task over a period of days. In a different session, neural activity was measured while participants performed Self/Other judgements (e.g., Does the word ‘Honest’ apply to you (Self condition) or Barack Obama (Other condition)). Despite the prominence of social and personal content in off-task reports, there was no association with neural activity during off-task trait adjective judgements. Instead, during both Self and Other judgements we found recruitment of caudal posterior cingulate cortex—a core DMN hub—was above baseline for individuals whose laboratory experiences were characterised as detailed. These data provide little support for a role of the DMN in self or other content in the off-task state and instead suggest a role in how on-going thought is represented.

The relationship between bilingual experience and gyrification in adulthood: A cross-sectional surface-based morphometry study

Neuroimaging evidence suggests that bilingualism may act as a source of neural plasticity. However, prior work has mostly focused on bilingualism-induced alterations in gray matter volume and white matter tract microstructure, with additional effects related to other neurostructural indices that might have remained undetected. The degree of cortical folding or gyrification is a morphometric parameter which provides information about changes on the brain's surface during development, aging and disease. We used Surface-based Morphometry (SBM) to investigate the contribution of bilingual experience to gyrification from early adulthood to old age in a sample of bilinguals and monolingual controls. Despite widespread cortical folding reductions for all participants with increasing age, preserved gyrification exclusive to bilinguals was detected in the right cingulate and entorhinal cortices, regions vulnerable with normal and pathological brain aging. Our results provide novel insights on experience-related cortical reshaping and bilingualism-induced cortical plasticity in adulthood.

Dynamic up- and down-regulation of the default (DMN) and extrinsic (EMN) mode networks during alternating task-on and task-off periods

Using fMRI, Hugdahl et al. (2015) reported the existence of a general-domain cortical network during active task-processing which was non-specific to the cognitive task being processed. They labelled this network the extrinsic mode network (EMN). The EMN would be predicted to be negatively, or anti-correlated with the classic default mode network (DMN), typically observed during periods of rest, such that while the EMN should be down-regulated and the DMN up-regulated in the absence of demands for task-processing, the reverse should occur when demands change from resting to task-processing. This would require alternating periods of task-processing and resting and analyzing data continuously when demands change from active to passive periods and vice versa. We were particularly interested in how the networks interact in the critical transition points between conditions. For this purpose, we used an auditory task with multiple cognitive demands in a standard fMRI block-design. Task-present (ON) blocks were alternated with an equal number of task-absent, or rest (OFF) blocks to capture network dynamics across time and changing environmental demands. To achieve this, we specified the onset of each block, and used a finite-impulse response function (FIR) as basis function for estimation of the fMRI-BOLD response. During active (ON) blocks, the results showed an initial rapid onset of activity in the EMN network, which remained throughout the period, and faded away during the first scan of the OFF-block. During OFF blocks, activity in the DMN network showed an initial time-lag where neither the EMN nor the DMN was active, after which the DMN was up-regulated. Studying network dynamics in alternating passive and active periods may provide new insights into brain network interaction and regulation.

Event Representations and Predictive Processing: The Role of the Midline Default Network Core

The human brain is tightly coupled to the world through its sensory‐motor systems—but it also spends a lot of its metabolism talking to itself. One important function of this intrinsic activity is the establishment and updating of event models—representations of the current situation that can predictively guide perception, learning, and action control. Here, we propose that event models largely depend on the default network (DN) midline core that includes the posterior cingulate and anterior medial prefrontal cortex. An increasing body of data indeed suggests that this subnetwork can facilitate stimuli processing during both naturalistic event comprehension and cognitive tasks in which mental representations of prior situations, trials, and task rules can predictively guide attention and performance. This midline core involvement in supporting predictions through event models can make sense of an otherwise complex and conflicting pattern of results regarding the possible cognitive functions subserved by the DN.

Stawarczyk, Bezdek, and Zacks offer neuroscience evidence for a midline default network core, which appears to coordinate internal, top‐down mentation with externally‐triggered, bottom‐up attention in a push‐pull relationship. The network may enable the flexible pursuance of thoughts tuned into or detached from the current environment.

Individual variation in patterns of task focused, and detailed, thought are uniquely associated within the architecture of the medial temporal lobe

Understanding the neural processes that support different patterns of ongoing thought is an important goal of contemporary cognitive neuroscience. Early accounts assumed the default mode network (DMN) was especially important for conscious attention to task-irrelevant/personally relevant materials. However, simple task-negative accounts of the DMN are incompatible with more recent evidence that neural patterns within the system can be related to ongoing processing during active task states. To better characterise the contribution of the DMN to ongoing thought, we conducted a cross-sectional analysis of the relationship between the structural organisation of the brain, as indexed by cortical thickness, and patterns of experience, identified using experience sampling in the cognitive laboratory. In a sample of 181 healthy individuals (mean age 20 years, 117 females) we identified an association between cortical thickness in the anterior parahippocampus and patterns of task focused thought, as well as an adjacent posterior region in which cortical thickness was associated with experiences with higher levels of subjective detail. Both regions fell within regions of medial temporal lobe associated with the DMN, yet varied in their functional connectivity: the time series of signals in the 'on-task' region were more correlated with systems important for external task-relevant processing (as determined by meta-analysis) including the dorsal and ventral attention, and fronto-parietal networks. In contrast, connectivity within the region linked to subjective 'detail' was more correlated with the medial core of the DMN (posterior cingulate and the medial pre-frontal cortex) and regions of primary visual cortex. These results provide cross-sectional evidence that confirms a role of the DMN in how detailed experiences are and so provide further evidence that the role of this system in experience is not simply task-irrelevant. Our results also highlight processes within the medial temporal lobe, and their interactions with other regions of cortex, as important in determining multiple aspects of how human cognition unfolds.

Reduced semantic control in older adults is linked to intrinsic DMN connectivity

Ageing provides an interesting window into semantic cognition: while younger adults generally outperform older adults on many cognitive tasks, knowledge continues to accumulate over the lifespan and consequently, the semantic store (i.e., vocabulary size) remains stable (or even improves) during healthy ageing. Semantic cognition involves the interaction of at least two components - a semantic store and control processes that interact to ensure efficient and context-relevant use of representations. Given older adults perform less well on tasks measuring executive control, their ability to access the semantic store in a goal driven manner may be compromised. Older adults also consistently show reductions in intrinsic brain connectivity, and we examined how these brain changes relate to age-related changes in semantic performance. We found that while older participants outperformed their younger counterparts on tests of vocabulary size (i.e., NART), younger participants were faster and more accurate in tasks requiring semantic control, and these age differences correlated with measures of intrinsic connectivity between the anterior temporal lobe (ATL) and medial prefrontal cortex (mPFC), within the default mode network. Higher intrinsic connectivity from right ATL to mPFC at rest related to better performance on verbal (but not picture) semantic tasks, and older adults showed an exaggerated version of this pattern, suggesting that this within-DMN connectivity may become more important for conceptual access from words as we age. However, this appeared to be at the expense of control over semantic retrieval - there was little relationship between connectivity and performance for strong associations in either group, but older adults with stronger connectivity showed particularly inefficient retrieval of weak associations. Older adults may struggle to harness the default mode network to support demanding patterns of semantic retrieval, resulting in a performance cost.

The effects of psychiatric history and age on self-regulation of the default mode network

Real-time neurofeedback enables human subjects to learn to regulate their brain activity, effecting behavioral changes and improvements of psychiatric symptomatology. Neurofeedback up-regulation and down-regulation have been assumed to share common neural correlates. Neuropsychiatric pathology and aging incur suboptimal functioning of the default mode network. Despite the exponential increase in real-time neuroimaging studies, the effects of aging, pathology and the direction of regulation on neurofeedback performance remain largely unknown. Using real-time fMRI data shared through the Rockland Sample Real-Time Neurofeedback project (N = 136) and open-access analyses, we first modeled neurofeedback performance and learning in a group of subjects with psychiatric history (n_a = 74) and a healthy control group (n_b = 62). Subsequently, we examined the relationship between up-regulation and down-regulation learning, the relationship between age and neurofeedback performance in each group and differences in neurofeedback performance between the two groups. For interpretative purposes, we also investigated functional connectomics prior to neurofeedback. Results show that in an initial session of default mode network neurofeedback with real-time fMRI, up-regulation and down-regulation learning scores are negatively correlated. This finding is related to resting state differences in the eigenvector centrality of the posterior cingulate cortex. Moreover, age correlates negatively with default mode network neurofeedback performance, only in absence of psychiatric history. Finally, adults with psychiatric history outperform healthy controls in default mode network up-regulation. Interestingly, the performance difference is related to no up-regulation learning in controls. This finding is supported by marginally higher default mode network centrality during resting state, in the presence of psychiatric history.

People got lost in solving a set of similar problems

A mental set generally refers to the human brain's tendency to persist with a familiar solution and stubbornly ignore alternatives. However, if a familiar solution is unable to solve a problem similar to a previous problem, does it continue to hinder alternative solutions, and if so, how and why? To answer these questions, a Chinese character decomposition task was adopted in this study. Participants were asked to perform a practice problem that could be solved by a familiar loose chunk decomposition (LCD) solution followed by a test problem that was similar to the practice problem but could only be solved by an unfamiliar tight chunk decomposition (TCD) solution or were asked to repeatedly perform 3-5 practice problems followed by a test problem; the former is the base-set condition, and the latter is the enhanced-set condition. The results showed that the test problem recruited more activation of the inferior frontal gyrus (IFG), middle occipital cortex (MOG), superior parietal lobule (SPL) and dorsal anterior cingulate cortex (dACC) than the practice problem in the latter operation and verification stage, but almost equal activation of the dACC occurred in the early exploration stage. This likely implied that people did not think that the familiar but currently invalid LCD solution could not be used to solve the test problem; thus, it continuously competed for attention with the unfamiliar TCD solution, which required more executive control to suppress. Moreover, compared with the base-set condition, the test problem in the enhanced-set condition recruited greater activations of the IFG, SPL and dACC in the latter verification stage but less activations of regions in the left IFG and MOG in the early exploration stage. These results revealed that people less actively explored and had to work harder to operate the unfamiliar TCD solution, particularly to resolve competition from the familiar but currently invalid LCD solution. In conclusion, people lost the ability to identify errors in the familiar but currently invalid solution, which in turn decreased the exploration efforts and increased the processing demands associated with alternative solutions in the form of attentional bias and competition. This finding broadly explains the dilemma of creative problem solving.

Creative aging: functional brain networks associated with divergent thinking in older and younger adults

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.