Resting-state networks predict individual differences in common and specific aspects of executive function

Alterations within and between intrinsic connectivity networks in cognitive interference resolution

Cognitive interference resolution (CIR) is the process of maintaining goal-directed focus despite the presence of distractions. While CIR has been extensively studied through localized activation analyses, its network-level dynamics remain underexplored with sufficient methodological diversity. In this study, we investigated the task-modulated intrinsic connectivity networks (ICNs) and their dynamic interactions with detailed subnetwork segmentation during CIR using fMRI data from 27 healthy adults performing the Multi-Source Interference Task (MSIT). We applied high-order group independent component analysis (ICA) to extract ICN subcomponents, followed by task-modulated component identification and dynamic functional connectivity analysis to examine network interactions. Our results reveal that the dorsal attention network (DAN) and cognitive control network (CCN) show increased activation and connectivity, while the default mode network (DMN) and limbic network exhibit decreased activation and connectivity. Additionally, the visual and cerebellum networks emerge as key intermediaries in CIR, as DAN and CCN strengthen their connectivity with these networks rather than directly interacting with each other. Furthermore, network reconfiguration patterns suggest functional segregation within the somatomotor network and CCN, indicating specialized subcomponent contributions. These findings provide a granular understanding of ICN activations and dynamic inter-network communication during CIR, offering new insights into the flexible reorganization of brain networks in response to cognitive interference.

Prefrontal cortex intrinsic functional connectivity and executive function in early childhood and early adulthood using fNIRS

Executive function (EF) is crucial for goal-directed behavior and predicts overall wellbeing, academic and interpersonal success. Intrinsic (i.e., non-evoked) resting state functional connectivity (rsFC) during naturalistic paradigms offers insight into neural mechanisms underlying EF. However, few studies have explored EF-rsFC associations using functional near-infrared spectroscopy (fNIRS) across age groups. This cross-sectional study validates a naturalistic viewing paradigm (Inscapes) using fNIRS and examines the link between rsFC in the prefrontal cortex (PFC) and EF in children ages 4-5 and in young adults ages 18-22. Adults were presented with two rsFC paradigms in a counterbalanced within-subjects design: a traditional static crosshair and Inscapes. Representational similarity analysis revealed robustly similar rsFC patterns between the crosshair and Inscapes conditions, and both were associated with EF (Stroop performance). Children were presented with Inscapes to assess rsFC, and exhibited high compliance using fNIRS. Importantly, rsFC assessed with Inscapes in children was associated with EF (Stroop-like Day-Night Task performance). Age-related differences showed intrinsic functional connections within the PFC strengthening over development. This study uses child-friendly, noninvasive optical neuroimaging and a publicly available rsFC paradigm to elucidate the role of the PFC in EF development, illuminating practical methodological approaches to study the developmental trajectory and neural underpinnings of EF.

Differentiation of executive functions during adolescence: Converging evidence from behavioral, genetic and neural data

Executive functions (EF) have been found to differentiate from a single component to three distinct components (i.e., updating, shifting, and inhibition) during development. However, there is still much debate regarding when such differentiation takes place and biological evidence is needed. Here we used the longitudinal and multimodality data from the ABCD study to address this question at two age groups (9-10 and 13-14). Three tasks (i.e., List, Card and Flanker tasks) were used to represent the three EF components respectively at baseline, and two tasks (Flanker and List) at 4th year follow up. Genes associated with each task were identified by whole genome and transcriptome association analyses and were then used for genetic similarity calculation; structural and functional brain indices related to each task were identified and used to assess neural similarity. We found that at baseline (9-10 years old), the three EF components were behaviorally highly inter-correlated and were associated with many of the same genes and the same brain regions. Four years later, the follow-up data (with Flanker and List tasks only) still showed significant but smaller behavioral/genetic/neural similarity. This study is the first to chart the path of EF differentiation during adolescence by combining behavioral, genetic, and neural data, and this approach may be relevant to the study of development of other cognitive abilities.

Cognitive Dysfunction in the Addictions (CDiA): protocol for a neuron-to-neighbourhood collaborative research program

Substance use disorders (SUDs), including Alcohol Use Disorder, are pressing global public health problems. Executive functions (EFs) are prominently featured in mechanistic models of addiction. However, significant gaps remain in our understanding of EFs in SUDs, including the dimensional relationships of EFs to underlying neural circuits, molecular biomarkers, disorder heterogeneity, and functional ability. Transforming health outcomes for people with SUDs requires an integration of clinical, biomedical, preclinical, and health services research. Through such interdisciplinary research, we can develop policies and interventions that align with biopsychosocial models of addiction, addressing the complex cognitive concerns of people with SUDs in a more holistic and effective way. Here, we introduce the design and procedures underlying Cognitive Dysfunction in the Addictions (CDiA), an integrative research program, which aims to fill these knowledge gaps and facilitate research discoveries to enhance treatments for people living with SUDs. The CDiA Program comprises seven interdisciplinary projects that aim to evaluate the central thesis that EF has a crucial role in functional outcomes in SUDs. The projects draw on a diverse sample of adults aged 18-60 (target N=400) seeking treatment for SUD, who are followed over one year to identify specific EF domains most associated with improved functioning. Projects 1-3 investigate SUD symptoms, brain circuits, and blood biomarkers and their associations with key EF domains (inhibition, working memory, and set-shifting) and functional outcomes (disability, quality of life). Projects 4 and 5 evaluate interventions for SUDs and their impacts on EF: a clinical trial of repetitive transcranial magnetic stimulation and a preclinical study of potential new pharmacological treatments in rodents. Project 6 links EF to healthcare utilization and is supplemented with a qualitative investigation of EF-related barriers to treatment engagement. Project 7 uses whole-person modeling to integrate the multi-modal data generated across projects, applying clustering and deep learning methods to identify patient subtypes and drive future cross-disciplinary initiatives. The CDiA Program will bring scientific domains together to uncover novel ways in which EFs are linked to SUD severity and functional recovery, and facilitate future discoveries to improve health outcomes in individuals living with SUDs.

Network segregation is associated with processing speed in the cognitively healthy oldest-old

The brain is organized into systems and networks of interacting components. The functional connections among these components give insight into the brain's organization and may underlie some cognitive effects of aging. Examining the relationship between individual differences in brain organization and cognitive function in older adults who have reached oldest-old ages with healthy cognition can help us understand how these networks support healthy cognitive aging. We investigated functional network segregation in 146 cognitively healthy participants aged 85+ in the McKnight Brain Aging Registry (MBAR). We found that the segregation of the association system and the individual networks within the association system (the fronto-parietal network , cingulo-opercular network, and default mode network), has strong associations with overall cognition and processing speed. We also provide a healthy oldest-old (85+) cortical parcellation that can be used in future work in this age group. This study shows that network segregation of the oldest-old brain is closely linked to cognitive performance. This work adds to the growing body of knowledge about differentiation in the aged brain by demonstrating that cognitive ability is associated with differentiated functional networks in very old individuals representing successful cognitive aging.

Distinct effects of early-stage and late-stage socioeconomic factors on brain and behavioral traits

Socioeconomic status (SES) is a time-varying multidimensional construct with ill-defined dimension-specific and age-specific effects on brain and behavior. We investigated these effects in 4,228 young adults. From 16 socioeconomic indicators, assessed for early (0-10 years) and late (>10 years) stages, we constructed family, provincial, family adverse and neighborhood adverse socioeconomic dimensions. Generally, family SES was associated with brain structure and connectivity along with cognitive function, whereas family adverse and neighborhood adverse SES were associated with personality and emotion. Most associations were observed for both early and late-stage SES; however, adjusting for the effect of early stage SES revealed late-stage-specific SES effects. Changes in SES were associated with personality and cognitive function. Cerebellar and medial frontal volumes and functional connectivity within the left frontoparietal network mediated the associations between family SES and memory and openness. These results inform both more precise interventions for reducing the consequences of adverse SES and experimental designs for excluding confounding socioeconomic effects on human health.

Connectome-based Predictive Models of General and Specific Executive Functions

Executive functions, the set of cognitive control processes that facilitate adaptive thoughts and actions, are composed primarily of three distinct yet interrelated cognitive components: Inhibition, Shifting, and Updating. While prior research has examined the nature of different components as well as their inter-relationships, fewer studies examined whole-brain connectivity to predict individual differences for the three cognitive components and associated tasks. Here, using the Connectome-based Predictive Modelling (CPM) approach and open-access data from the Human Connectome Project, we built brain network models to successfully predict individual performance differences on the Flanker task, the Dimensional Change Card Sort task, and the 2-back task, each putatively corresponding to Inhibition, Shifting, and Updating. We focused on grayordinate fMRI data collected during the 2-back tasks after confirming superior predictive performance over resting-state and volumetric data. High cross-task prediction accuracy as well as joint recruitment of canonical networks, such as the frontoparietal and default-mode networks, suggest the existence of a common executive function factor. To investigate the relationships among the three executive function components, we developed new measures to disentangle their shared and unique aspects. Our analysis confirmed that a shared executive function component can be predicted from functional connectivity patterns densely located around the frontoparietal, default-mode and dorsal attention networks. The Updating-specific component showed significant cross-prediction with the general executive function factor, suggesting a relatively stronger role than the other components. In contrast, the Shifting-specific and Inhibition-specific components exhibited lower cross-prediction performance, indicating more distinct and specialized roles. Given the limitation that individual behavioral measures do not purely reflect the intended cognitive constructs, our study demonstrates a novel approach to infer common and specific components of executive function.

Simultaneous tACS-fMRI reveals state- and frequency-specific modulation of hippocampal-cortical functional connectivity

Non-invasive indirect hippocampal-targeted stimulation is of broad scientific and clinical interest. Transcranial alternating current stimulation (tACS) is appealing because it allows oscillatory stimulation to study hippocampal theta (3-8 Hz) activity. We found that tACS administered during functional magnetic resonance imaging yielded a frequency-, mental state- and topologically-specific effect of theta stimulation (but not other frequencies) enhancing right (but not left) hippocampal-cortical connectivity during resting blocks but not during task blocks. Control analyses showed that this effect was not due to possible stimulation-induced changes in signal quality or head movement. Our findings are promising for targeted network modulations of deep brain structures for research and clinical intervention.

Time Dependent Effects of Cerebellar tDCS on Cerebello-cortical Connectivity Networks in Young Adults

The cerebellum is involved in non-motor processing, supported by topographically distinct cerebellar activations and closed-loop circuits between the cerebellum and the cortex. Disruptions to cerebellar function may negatively impact prefrontal function and processing. Cerebellar resources may be important for offloading cortical processing, providing crucial scaffolding for normative performance and function. Here, we used transcranial direct current stimulation (tDCS) to temporarily alter cerebellar function and subsequently investigated resting state network connectivity. Critically, what happens to these circuits if the cerebellum is not functioning optimally, or after stimulation, remains relatively unknown. We employed a between-subjects design with 74 participants total (38 female; M = 22.0 years, SD = 3.45), applying anodal (n = 25), cathodal (n = 25), or sham (n = 24) stimulation to the cerebellum to examine the effect of stimulation on cerebello-cortical resting state connectivity in young adults. We predicted increased functional connectivity following cathodal stimulation and decreased functional connectivity following anodal stimulation. We found, anodal stimulation resulted in increased connectivity in both ipsilateral and contralateral regions of the cortex, perhaps indicative of a compensatory response to degraded cerebellar output. Additionally, a window analysis also demonstrated a time dependent nature to the impacts of cerebellar tDCS on connectivity, particularly with cognitive regions of the cerebral cortex. This work suggests that when cerebellar outputs are degraded, in this case by tDCS, the cerebellum offloads its processing responsibility which encourages more cortical regions to engage to compensate for the degraded cerebellar output. This results in in differences in cortical activation patterns and performance deficits. These results might inform and update existing compensatory models, which focus primarily on the cortex, to include the cerebellum as a vital structure involved in the scaffolding of cortical processing.

NEBULA101: an open dataset for the study of language aptitude in behaviour, brain structure and function

This paper introduces the "NEBULA101 - Neuro-behavioural Understanding of Language Aptitude" dataset, which comprises behavioural and brain imaging data from 101 healthy adults to examine individual differences in language and cognition. Human language, a multifaceted behaviour, varies significantly among individuals, at different processing levels. Recent advances in cognitive science have embraced an integrated approach, combining behavioural and brain studies to explore these differences comprehensively. The NEBULA101 dataset offers brain structural, diffusion-weighted, task-based and resting-state MRI data, alongside extensive linguistic and non-linguistic behavioural measures to explore the complex interaction of language and cognition in a highly multilingual sample. By sharing this multimodal dataset, we hope to promote research on the neuroscience of language, cognition and multilingualism, enabling the field to deepen its understanding of the multivariate panorama of individual differences and ultimately contributing to open science.

Prenatal chronic inflammation and children's executive function development

Fetal inflammation, typically measured indirectly through prenatal maternal cytokine markers, has been shown to impact early childhood executive functions (EFs), which are central to later cognitive and life outcomes. Here, we assessed the impact of prenatal inflammation on EF developmental trajectories using direct placenta histopathology measures in 131 mothers who predominantly self-identified as Black (90.8% Black; 0.8% Asian American, 1.5% biracial, 0.8% Latinx, 3.1% White, 3.1% Missing). We found that placental measures of inflammation were associated with limited gain in EF development from 3 to 5 years old. In follow up analyses, we addressed whether screening questionnaires in infancy might aid in classification of infants as higher risk for subsequent EF problems. We found that parent responses to the Ages & Stages Questionnaire and the Infant/Toddler Sensory Profile at 12 months predict the development of EF abilities in children exposed to chronic inflammation. These findings open promising opportunities for early screening of children at risk for poor executive functioning in children exposed to prenatal inflammation.

Association of Exercise with Better Olfactory Performance and Higher Functional Connectivity Between the Olfactory Cortex and the Prefrontal Cortex: A Resting-State Functional Near-Infrared Spectroscopy Study

Background: Olfactory deterioration is suggested to be a predictor of some neurodegenerative diseases. Recent studies indicate that physical exercise has a positive relationship with olfactory performance, and a subregion in the prefrontal cortex (PFC) may play an important role in olfactory processing. The PFC is not only related to olfactory function but it also engages in complex functions such as cognition and emotional processing. Methodology: Our study compared the functional connectivity between the olfactory cortex and the PFC in healthy individuals who exercised regularly and healthy persons who did not. Those who exercised more than three times/week for at least 30 min each time were considered the exercise group, and those who did not meet this exercise criteria were considered the nonexercise group. We also assessed their odor threshold. Participants were aged 55 years or older, and the two groups were balanced for age, sex, body mass index, and educational level. Results: We found that compared with individuals who did not exercise, exercisers had a significantly lower threshold for detecting odors. In addition, the olfactory cortex had stronger connectivity with the PFC in exercisers than in nonexercisers. More specifically, when the PFC was grouped into three subregions, namely, the ventrolateral prefrontal cortex (VLPFC), dorsolateral prefrontal cortex (DLPFC), and frontopolar cortex (FPA), Pearson correlation analysis revealed stronger connectivity between the VLPFC and the orbitofrontal cortex (OFC), between the OFC and the FPA, and between the left and right OFC hemispheres in the exercisers. In addition, Granger causality indicated higher directional connectivity from the DLPFC to the OFC in exercisers than in nonexercisers. Conclusion: Our findings indicated that the exercise group not only had better olfactory performance but also had stronger functional connectivity between the olfactory cortex and the PFC than nonexercise group.

Cognitive Dysfunction in the Addictions (CDiA): A Neuron to Neighbourhood Collaborative Research Program on Executive Dysfunction and Functional Outcomes in Outpatients Seeking Treatment for Addiction

Background

Substance use disorders (SUDs) are pressing global public health problems. Executive functions (EFs) are prominently featured in mechanistic models of addiction. However, there remain significant gaps in our understanding of EFs in SUDs, including the dimensional relationships of EFs to underlying neural circuits, molecular biomarkers, disorder heterogeneity, and functional ability. To improve health outcomes for people with SUDs, interdisciplinary clinical, preclinical and health services research is needed to inform policies and interventions aligned with biopsychosocial models of addiction. Here, we introduce Cognitive Dysfunction in the Addictions (CDiA), an integrative team-science and translational research program, which aims to fill these knowledge gaps and facilitate research discoveries to enhance treatments for people living with SUDs.

Methods

The CDiA Program comprises seven complementary interdisciplinary projects that aim to progress understanding of EF in SUDs and investigate new biological treatment approaches. The projects draw on a diverse sample of adults aged 18-60 (target N=400) seeking treatment for addiction, who are followed prospectively over one year to identify EF domains crucial to recovery. Projects 1-3 investigate SUD symptoms, brain circuits, and blood biomarkers and their associations with both EF domains (inhibition, working memory, and set-shifting) and functional outcomes (disability, quality of life). Projects 4 and 5 evaluate interventions for addiction and their impacts on EF: a clinical trial of repetitive transcranial magnetic stimulation and a preclinical study of potential new pharmacological treatments in rodents. Project 6 links EF to healthcare utilization and is supplemented with a qualitative investigation of EF-related barriers to treatment engagement for those with substance use concerns. Project 7 uses innovative whole-person modeling to integrate the multi-modal data generated across projects, applying clustering and deep learning methods to identify patient subtypes and drive future cross-disciplinary initiatives.

Discussion

The CDiA program has promise to bring scientific domains together to uncover the diverse ways in which EFs are linked to SUD severity and functional recovery. These findings, supported by emerging clinical, preclinical, health service, and whole-person modeling investigations, will facilitate future discoveries about cognitive dysfunction in addiction and could enhance the future clinical care of individuals seeking treatment for SUDs.

Network connectivity differences in music listening among older adults following a music-based intervention

Music-based interventions are a common feature in long-term care with clinical reports highlighting music's ability to engage individuals with complex diagnoses. While these findings are promising, normative findings from healthy controls are needed to disambiguate treatment effects unique to pathology and those seen in healthy aging. The present study examines brain network dynamics during music listening in a sample of healthy older adults before and after a music-based intervention. We found intervention effects from hidden Markov model-estimated fMRI network data. Following the intervention, participants demonstrated greater occupancy (the amount of time a network was occupied) in a temporal-mesolimbic network. We conclude that network dynamics in healthy older adults are sensitive to music-based interventions. We discuss these findings' implications for future studies with individuals with neurodegeneration.

Functional correlates of executive dysfunction in primary progressive aphasia: a systematic review

Introduction

Recent research has recognized executive dysfunction as another component affected in Primary Progressive Aphasia (PPA). This systematic review aimed to examine what information distinctive neurophysiological markers can provide in the evaluation of executive function (EF) deficits in PPA, and to what effect executive function deficits can be assessed through the characteristics of functional markers.

Methods

We conducted a systematic literature search following the PRISMA guidelines across studies that employed neuropsychological assessments and neurophysiological imaging techniques (EEG, MEG; PET, SPECT, fMRI, fNIRS) to investigate executive dysfunction correlates in PPA.

Results

Findings from nine articles including a total number of 111 individuals with PPA met our inclusion criteria and were synthesized. Although research on the neural correlates of EF deficits is scarce, MEG studies revealed widespread oscillatory slowing, with increased delta and decreased alpha power, where alterations in alpha, theta, and beta activities were significant predictors of executive function deficits. PET findings demonstrated significant correlations between executive dysfunction and hypometabolism in frontal brain regions. fMRI results indicated elevated homotopic connectivity in PPA patients, with a broader and more anterior distribution of abnormal hippocampal connections of which were associated with reduced executive performance.

Conclusion

Our study provides indirect support for the assumption regarding the significance of the frontal regions and inferior frontal junction in executive control and demonstrates that neurophysiological tools can be a useful aid to further investigate clinical-neurophysiological correlations in PPA.

Can we enhance working memory? Bias and effectiveness in cognitive training studies

Meta-analyses have found that working memory (WM) can be improved with cognitive training; however, some authors have suggested that these improvements are mostly driven by biases in the measurement of WM, especially the use of similar tasks for assessment and training. In the present meta-analysis, we investigated whether WM, fluid intelligence, executive functions, and short-term memory can be improved by cognitive training and evaluated the impact of possible sources of bias. We performed a risk of bias assessment of the included studies and took special care in controlling for practice effects. Data from 52 independent comparisons were analyzed, including cognitive training aimed at different cognitive functions. Our results show small improvements in WM after training (SMD = 0.18). Much larger effects were observed when the analysis was restricted to assessment tasks similar to those used for training (SMD = 1.15). Fluid intelligence was not found to improve as a result of training, and improvements in WM were not related to changes in fluid intelligence. Our analyses did however indicate that cognitive training can improve specific executive functions. Contrary to expectations, a set of meta-regressions indicated that characteristics of the training programme, such as dosage and type of training, do not have an impact on the effectiveness of training. The risk of bias assessment revealed some concerns in the randomization process and possible selective reporting among studies. Overall, our results identified various potential sources of bias, with the most significant being the choice of assessment tasks.

The degenerate coding of psychometric profiles through functional connectivity archetypes

Introduction

Degeneracy in the brain-behavior code refers to the brain's ability to utilize different neural configurations to support similar functions, reflecting its adaptability and robustness. This study aims to explore degeneracy by investigating the non-linear associations between psychometric profiles and resting-state functional connectivity (RSFC).

Methods

The study analyzed RSFC data from 500 subjects to uncover the underlying neural configurations associated with various psychometric outcomes. Self-organized maps (SOM), a type of unsupervised machine learning algorithm, were employed to cluster the RSFC data. And identify distinct archetypal connectivity profiles characterized by unique within- and between-network connectivity patterns.

Results

The clustering analysis using SOM revealed several distinct archetypal connectivity profiles within the RSFC data. Each archetype exhibited unique connectivity patterns that correlated with various cognitive, physical, and socioemotional outcomes. Notably, the interaction between different SOM dimensions was significantly associated with specific psychometric profiles.

Discussion

This study underscores the complexity of brain-behavior interactions and the brain's capacity for degeneracy, where different neural configurations can lead to similar behavioral outcomes. These findings highlight the existence of multiple brain architectures capable of producing similar behavioral outcomes, illustrating the concept of neural degeneracy, and advance our understanding of neural degeneracy and its implications for cognitive and emotional health.

Brain topology underlying executive functions across the lifespan: focus on the default mode network

Introduction

While traditional neuroimaging approaches to the study of executive functions (EFs) have typically employed task-evoked paradigms, resting state studies are gaining popularity as a tool for investigating inter-individual variability in the functional connectome and its relationship to cognitive performance outside of the scanner.

Method

Using resting state functional magnetic resonance imaging data from the Human Connectome Project Lifespan database, the present study capitalized on graph theory to chart cross-sectional variations in the intrinsic functional organization of the frontoparietal (FPN) and the default mode (DMN) networks in 500 healthy individuals (from 10 to 100 years of age), to investigate the neural underpinnings of EFs across the lifespan.

Results

Topological properties of both the FPN and DMN were associated with EF performance but not with a control task of picture naming, providing specificity in support for a tight link between neuro-functional and cognitive-behavioral efficiency within the EF domain. The topological organization of the DMN, however, appeared more sensitive to age-related changes relative to that of the FPN.

Discussion

The DMN matures earlier in life than the FPN and it ıs more susceptible to neurodegenerative changes. Because its activity is stronger in conditions of resting state, the DMN might be easier to measure in noncompliant populations and in those at the extremes of the life-span curve, namely very young or elder participants. Here, we argue that the study of its functional architecture in relation to higher order cognition across the lifespan might, thus, be of greater interest compared with what has been traditionally thought.

A principled framework to assess the information-theoretic fitness of brain functional sub-circuits

In systems and network neuroscience, many common practices in brain connectomic analysis are often not properly scrutinized. One such practice is mapping a predetermined set of sub-circuits, like functional networks (FNs), onto subjects' functional connectomes (FCs) without adequately assessing the information-theoretic appropriateness of the partition. Another practice that goes unchallenged is thresholding weighted FCs to remove spurious connections without justifying the chosen threshold. This paper leverages recent theoretical advances in Stochastic Block Models (SBMs) to formally define and quantify the information-theoretic fitness (e.g., prominence) of a predetermined set of FNs when mapped to individual FCs under different fMRI task conditions. Our framework allows for evaluating any combination of FC granularity, FN partition, and thresholding strategy, thereby optimizing these choices to preserve important topological features of the human brain connectomes. By applying to the Human Connectome Project with Schaefer parcellations at multiple levels of granularity, the framework showed that the common thresholding value of 0.25 was indeed information-theoretically valid for group-average FCs despite its previous lack of justification. Our results pave the way for the proper use of FNs and thresholding methods and provide insights for future research in individualized parcellations.

Network connectivity differences in music listening among older adults following a music-based intervention

Music-based interventions are a common feature in long-term care with clinical reports highlighting music's ability to engage individuals with complex diagnoses. While these findings are promising, normative findings from healthy controls are needed to disambiguate treatment effects unique to pathology and those seen in healthy aging. The present study examines brain network dynamics during music listening in a sample of healthy older adults before and after a music-based intervention. We found intervention effects from hidden Markov model-estimated fMRI network data. Following the intervention, participants demonstrated greater occupancy (the amount of time a network was occupied) in a temporal-mesolimbic network. We conclude that network dynamics in healthy older adults are sensitive to music-based interventions. We discuss these findings' implications for future studies with individuals with neurodegeneration.

Orienting role of the putative human posterior infero-temporal area in visual attention

The dorsal attention network (DAN) is a network of brain regions essential for attentional orienting, which includes the lateral intraparietal area (LIP) and frontal eye field (FEF). Recently, the putative human dorsal posterior infero-temporal area (phPITd) has been identified as a new node of the DAN. However, its functional relationship with other areas of the DAN and its specific role in visual attention remained unclear. In this study, we analyzed a large publicly available neuroimaging dataset to investigate the intrinsic functional connectivities (FCs) of the phPITd with other brain areas. The results showed that the intrinsic FCs of the phPITd with the areas of the visual network and the DAN were significantly stronger than those with the ventral attention network (VAN) areas and areas of other networks. We further conducted individual difference analyses with a sample size of 295 participants and a series of attentional tasks to investigate which attentional components each phPITd-based DAN edge predicts. Our findings revealed that the intrinsic FC of the left phPITd with the LIPv could predict individual ability in attentional orienting, but not in alerting, executive control, and distractor suppression. Our results not only provide direct evidence of the phPITd's functional relationship with the LIPv, but also offer a comprehensive understanding of its specific role in visual attention.

Multivariate Assessment of Inhibitory Control in Youth: Links With Psychopathology and Brain Function

Inhibitory control is central to many theories of cognitive and brain development, and impairments in inhibitory control are posited to underlie developmental psychopathology. In this study, we tested the possibility of shared versus unique associations between inhibitory control and three common symptom dimensions in youth psychopathology: attention-deficit/hyperactivity disorder (ADHD), anxiety, and irritability. We quantified inhibitory control using four different experimental tasks to estimate a latent variable in 246 youth (8-18 years old) with varying symptom types and levels. Participants were recruited from the Washington, D.C., metro region. Results of structural equation modeling integrating a bifactor model of psychopathology revealed that inhibitory control predicted a shared or general psychopathology dimension, but not ADHD-specific, anxiety-specific, or irritability-specific dimensions. Inhibitory control also showed a significant, selective association with global efficiency in a frontoparietal control network delineated during resting-state functional magnetic resonance imaging. These results support performance-based inhibitory control linked to resting-state brain function as an important predictor of comorbidity in youth psychopathology.

Mapping neurodevelopmental diversity in executive function

Executive function, an umbrella term used to describe the goal-directed regulation of thoughts, actions, and emotions, is an important dimension implicated in neurodiversity and established malleable predictor of multiple adult outcomes. Neurodevelopmental differences have been linked to both executive function strengths and weaknesses, but evidence for associations between specific profiles of executive function and specific neurodevelopmental conditions is mixed. In this exploratory study, we adopt an unsupervised machine learning approach (self-organising maps), combined with k-means clustering to identify data-driven profiles of executive function in a transdiagnostic sample of 566 neurodivergent children aged 8-18 years old. We include measures designed to capture two distinct aspects of executive function: performance-based tasks designed to tap the state-like efficiency of cognitive skills under optimal conditions, and behaviour ratings suited to capturing the trait-like application of cognitive control in everyday contexts. Three profiles of executive function were identified: one had consistent difficulties across both types of assessments, while the other two had inconsistent profiles of predominantly rating- or predominantly task-based difficulties. Girls and children without a formal diagnosis were more likely to have an inconsistent profile of primarily task-based difficulties. Children with these different profiles had differences in academic achievement and mental health outcomes and could further be differentiated from a comparison group of children on both shared and profile-unique patterns of neural white matter organisation. Importantly, children's executive function profiles were not directly related to diagnostic categories or to dimensions of neurodiversity associated with specific diagnoses (e.g., hyperactivity, inattention, social communication). These findings support the idea that the two types of executive function assessments provide non-redundant information related to children's neurodevelopmental differences and that they should not be used interchangeably. The findings advance our understanding of executive function profiles and their relationship to behavioural outcomes and neural variation in neurodivergent populations.

Resting state network connectivity is associated with cognitive flexibility performance in youth in the Adolescent Brain Cognitive Development Study

Cognitive flexibility is an executive functioning skill that develops in childhood, and when impaired, has transdiagnostic implications for psychiatric disorders. To identify how intrinsic neural architecture at rest is linked to cognitive flexibility performance, we used the data-driven method of independent component analysis (ICA) to investigate resting state networks (RSNs) and their whole-brain connectivity associated with levels of cognitive flexibility performance in children. We hypothesized differences by cognitive flexibility performance in RSN connectivity strength in cortico-striatal circuitry, which would manifest via the executive control network, right and left frontoparietal networks (FPN), salience network, default mode network (DMN), and basal ganglia network. We selected participants from the Adolescent Brain Cognitive Development (ABCD) Study who scored at the 25th, ("CF-Low"), 50th ("CF-Average"), or 75th percentiles ("CF-High") on a cognitive flexibility task, were early to middle puberty, and did not exhibit significant psychopathology (n = 967, 47.9% female; ages 9-10). We conducted whole-brain ICA, identifying 14 well-characterized RSNs. Groups differed in connectivity strength in the right FPN, anterior DMN, and posterior DMN. Planned comparisons indicated CF-High had stronger connectivity between right FPN and supplementary motor/anterior cingulate than CF-Low. CF-High had more anti-correlated connectivity between anterior DMN and precuneus than CF-Average. CF-Low had stronger connectivity between posterior DMN and supplementary motor/anterior cingulate than CF-Average. Post-hoc correlations with reaction time by trial type demonstrated significant associations with connectivity. In sum, our results suggest childhood cognitive flexibility performance is associated with DMN and FPN connectivity strength at rest, and that there may be optimal levels of connectivity associated with task performance that vary by network.

Executive control of language in schizophrenia patients with history of auditory verbal hallucinations: A neuropsychological and resting-state fMRI study

BACKGROUND

As demonstrated by a plethora of studies, compromised executive functions (EF) and language are implicated in mechanisms of auditory verbal hallucinations (AVH), but the contribution of their interaction to AVH remains unclear. We hypothesized that schizophrenia patients with history of AVH (AVHh+) vs. without history of AVH (AVHh-) have a specific deficit of executive control of language and alterations in functional connectivity (FC) between the brain regions involved in EF and language, and these neuropsychological and neurophysiological traits are associated with each other.

METHODS

To explore the executive control of language and its contribution to AVH, we used an integrative approach involving analysis of neuropsychological and resting-state fMRI data of 34 AVHh+, 16 AVHh-, and 40 healthy controls. We identified the neuropsychological and FC measures that differentiated between AVHh+, AVHh-, and HC, and tested the associations between them.

RESULTS

AVHh+ were characterized by decreased category and phonological verbal fluency, utterance length, productivity in the planning tasks, and poorer retelling. AVHh+ had decreased FC between the left inferior frontal gyrus and the anterior cingulate cortex. Productivity in category verbal fluency was associated with the FC between these regions.

CONCLUSIONS

Poor executive control of word retrieval and deficient programming of sentence and narrative related to more general deficits of planning may be the neuropsychological traits specific for AVHh+. A neurophysiological trait specific for AVHh+ may be a decreased FC between regions involved in language production and differentiation between alien- vs. self-generated speech and between language production vs. comprehension.

Sparse Bayesian modeling of hierarchical independent component analysis: Reliable estimation of individual differences in brain networks

Independent component analysis (ICA) is one of the leading approaches for studying brain functional networks. There is increasing interest in neuroscience studies to investigate individual differences in brain networks and their association with demographic characteristics and clinical outcomes. In this work, we develop a sparse Bayesian group hierarchical ICA model that offers significant improvements over existing ICA techniques for identifying covariate effects on the brain network. Specifically, we model the population-level ICA source signals for brain networks using a Dirichlet process mixture. To reliably capture individual differences on brain networks, we propose sparse estimation of the covariate effects in the hierarchical ICA model via a horseshoe prior. Through extensive simulation studies, we show that our approach performs considerably better in detecting covariate effects in comparison with the leading group ICA methods. We then perform an ICA decomposition of a between-subject meditation study. Our method is able to identify significant effects related to meditative practice in brain regions that are consistent with previous research into the default mode network, whereas other group ICA approaches find few to no effects.

Predicting executive functioning from brain networks: modality specificity and age effects

Healthy aging is associated with structural and functional network changes in the brain, which have been linked to deterioration in executive functioning (EF), while their neural implementation at the individual level remains unclear. As the biomarker potential of individual resting-state functional connectivity (RSFC) patterns has been questioned, we investigated to what degree individual EF abilities can be predicted from the gray-matter volume (GMV), regional homogeneity, fractional amplitude of low-frequency fluctuations (fALFF), and RSFC within EF-related, perceptuo-motor, and whole-brain networks in young and old adults. We examined whether the differences in out-of-sample prediction accuracy were modality-specific and depended on age or task-demand levels. Both uni- and multivariate analysis frameworks revealed overall low prediction accuracies and moderate-to-weak brain-behavior associations (R2 < 0.07, r < 0.28), further challenging the idea of finding meaningful markers for individual EF performance with the metrics used. Regional GMV, well linked to overall atrophy, carried the strongest information about individual EF differences in older adults, whereas fALFF, measuring functional variability, did so for younger adults. Our study calls for future research analyzing more global properties of the brain, different task-states and applying adaptive behavioral testing to result in sensitive predictors for young and older adults, respectively.

Functional Connectivity and Microstructural Network Correlates of Interindividual Variability in Distinct Executive Functions of Healthy Older Adults

Executive functions, essential for daily life, are known to be impaired in older age. Some executive functions, including working memory updating and value-based decision-making, are specifically sensitive to age-related deterioration. While their neural correlates in young adults are well-described, a comprehensive delineation of the underlying brain substrates in older populations, relevant to identify targets for modulation against cognitive decline, is missing. Here, we assessed letter updating and Markov decision-making task performance to operationalize these trainable functions in 48 older adults. Resting-state functional magnetic resonance imaging was acquired to quantify functional connectivity (FC) in task-relevant frontoparietal and default mode networks. Microstructure in white matter pathways mediating executive functions was assessed with diffusion tensor imaging and quantified by tract-based fractional anisotropy (FA). Superior letter updating performance correlated with higher FC between dorsolateral prefrontal cortex and left frontoparietal and hippocampal areas, while superior Markov decision-making performance correlated with decreased FC between basal ganglia and right angular gyrus. Furthermore, better working memory updating performance was related to higher FA in the cingulum bundle and the superior longitudinal fasciculus. Stepwise linear regression showed that cingulum bundle FA added significant incremental contribution to the variance explained by fronto-angular FC alone. Our findings provide a characterization of distinct functional and structural connectivity correlates associated with performance of specific executive functions. Thereby, this study contributes to the understanding of the neural correlates of updating and decision-making functions in older adults, paving the way for targeted modulation of specific networks by modulatory techniques such as behavioral interventions and non-invasive brain stimulation.

Better together: novel methods for measuring and modeling development of executive function diversity while accounting for unity

INTRODUCTION

Executive functions (EFs) are linked to positive outcomes across the lifespan. Yet, methodological challenges have prevented precise understanding of the developmental trajectory of their organization.

METHODS

We introduce novel methods to address challenges for both measuring and modeling EFs using an accelerated longitudinal design with a large, diverse sample of students in middle childhood (N = 1,286; ages 8 to 14). We used eight adaptive assessments hypothesized to measure three EFs, working memory, context monitoring, and interference resolution. We deployed adaptive assessments to equate EF challenge across ages and a data-driven, network analytic approach to reveal the evolving diversity of EFs while simultaneously accounting for their unity.

RESULTS AND DISCUSSION

Using this methodological paradigm shift brought new precision and clarity to the development of these EFs, showing these eight tasks are organized into three stable components by age 10, but refinement of composition of these components continues through at least age 14.

Predicting Executive Functioning from Brain Networks: Modality Specificity and Age Effects

Healthy aging is associated with structural and functional network changes in the brain, which have been linked to deterioration in executive functioning (EF), while their neural implementation at the individual level remains unclear. As the biomarker potential of individual resting-state functional connectivity (RSFC) patterns has been questioned, we investigated to what degree individual EF abilities can be predicted from gray-matter volume (GMV), regional homogeneity, fractional amplitude of low-frequency fluctuations (fALFF), and RSFC within EF-related, perceptuo-motor, and whole-brain networks in young and old adults. We examined whether differences in out-of-sample prediction accuracy were modality-specific and depended on age or task-demand levels. Both uni- and multivariate analysis frameworks revealed overall low prediction accuracies and moderate to weak brain-behavior associations (R2 < .07, r < .28), further challenging the idea of finding meaningful markers for individual EF performance with the metrics used. Regional GMV, well linked to overall atrophy, carried the strongest information about individual EF differences in older adults, whereas fALFF, measuring functional variability, did so for younger adults. Our study calls for future research analyzing more global properties of the brain, different task-states and applying adaptive behavioral testing to result in sensitive predictors for young and older adults, respectively.

Time dependent effects of cerebellar tDCS on cerebello-cortical connectivity networks in young adults

The cerebellum is involved in non-motor processing, supported by topographically distinct cerebellar activations and closed loop circuits between the cerebellum and the cortex. Disruptions to cerebellar function and network connectivity in aging or disease may negatively impact prefrontal function and processing. Cerebellar resources may be important for offloading cortical processing, providing crucial scaffolding for normative performance and function. Here, we used transcranial direct current stimulation (tDCS) to temporarily alter cerebellar function and subsequently investigated resting state network connectivity. This allows us to investigate network changes that may parallel what is seen in aging and clinical populations, providing additional insights into these key circuits. Critically, what happens to these circuits if the cerebellum is not functioning optimally remains relatively unknown. We employed a between-subjects design applying anodal (n=25), cathodal (n=25), or sham (n=24) stimulation to the cerebellum to examine the effect of stimulation on cerebello-cortical resting state connectivity in young adults. We predicted increased functional connectivity following cathodal stimulation and decreased functional connectivity following anodal stimulation. We found, anodal stimulation resulted in increased connectivity in both ipsilateral and contralateral regions of the cortex, perhaps indicative of a compensatory response to degraded cerebellar output. Additionally, a sliding window analysis also demonstrated a time dependent nature to the impacts of cerebellar tDCS on connectivity, particularly in cognitive region in the cortex. Assuming the difference in connectivity and network-behavior relationships here parallels what occurs in aging or disease, this may provide a mechanism whereby offloading of function to the cerebellum is negatively impacted, resulting in subsequent differences in prefrontal cortical activation patterns and performance deficits. These results might inform and update existing compensatory models of function to include the cerebellum as a vital structure needed for scaffolding.

Predicting executive functioning from functional brain connectivity: network specificity and age effects

Healthy aging is associated with altered executive functioning (EF). Earlier studies found age-related differences in EF performance to be partially accounted for by changes in resting-state functional connectivity (RSFC) within brain networks associated with EF. However, it remains unclear which role RSFC in EF-associated networks plays as a marker for individual differences in EF performance. Here, we investigated to what degree individual abilities across 3 different EF tasks can be predicted from RSFC within EF-related, perceptuo-motor, whole-brain, and random networks separately in young and old adults. Specifically, we were interested if (i) young and old adults differ in predictability depending on network or EF demand level (high vs. low), (ii) an EF-related network outperforms EF-unspecific networks when predicting EF abilities, and (iii) this pattern changes with demand level. Both our uni- and multivariate analysis frameworks analyzing interactions between age × demand level × networks revealed overall low prediction accuracies and a general lack of specificity regarding neurobiological networks for predicting EF abilities. This questions the idea of finding markers for individual EF performance in RSFC patterns and calls for future research replicating the current approach in different task states, brain modalities, different, larger samples, and with more comprehensive behavioral measures.

Resting-state functional connectivity in deaf and hearing individuals and its link to executive processing

Sensory experience shapes brain structure and function, and it is likely to influence the organisation of functional networks of the brain, including those involved in cognitive processing. Here we investigated the influence of early deafness on the organisation of resting-state networks of the brain and its relation to executive processing. We compared resting-state connectivity between deaf and hearing individuals across 18 functional networks and 400 ROIs. Our results showed significant group differences in connectivity between seeds of the auditory network and most large-scale networks of the brain, in particular the somatomotor and salience/ventral attention networks. When we investigated group differences in resting-state fMRI and their link to behavioural performance in executive function tasks (working memory, inhibition and switching), differences between groups were found in the connectivity of association networks of the brain, such as the salience/ventral attention and default-mode networks. These findings indicate that sensory experience influences not only the organisation of sensory networks, but that it also has a measurable impact on the organisation of association networks supporting cognitive processing. Overall, our findings suggest that different developmental pathways and functional organisation can support executive processing in the adult brain.

Genetic and environmental factors influencing neonatal resting-state functional connectivity

Functional magnetic resonance imaging has been used to identify complex brain networks by examining the correlation of blood-oxygen-level-dependent signals between brain regions during the resting state. Many of the brain networks identified in adults are detectable at birth, but genetic and environmental influences governing connectivity within and between these networks in early infancy have yet to be explored. We investigated genetic influences on neonatal resting-state connectivity phenotypes by generating intraclass correlations and performing mixed effects modeling to estimate narrow-sense heritability on measures of within network and between-network connectivity in a large cohort of neonate twins. We also used backwards elimination regression and mixed linear modeling to identify specific demographic and medical history variables influencing within and between network connectivity in a large cohort of typically developing twins and singletons. Of the 36 connectivity phenotypes examined, only 6 showed narrow-sense heritability estimates greater than 0.10, with none being statistically significant. Demographic and obstetric history variables contributed to between- and within-network connectivity. Our results suggest that in early infancy, genetic factors minimally influence brain connectivity. However, specific demographic and medical history variables, such as gestational age at birth and maternal psychiatric history, may influence resting-state connectivity measures.

Individually tuned theta HD-tACS improves spatial performance

BACKGROUND

Using transcranial alternating current stimulation (tACS) to improve visuospatial working memory (vsWM) has received considerable attention over the past few years. However, fundamental issues remain, such as the optimal frequency, the generality of behavioral effects, and the anatomical specificity of stimulation.

OBJECTIVES

Here we examined the effects of two theory-driven tACS protocols for improving vsWM on behavioral and electroencephalogram (EEG) measures.

METHODS

Twenty adults each completed 3 HD-tACS conditions (Tuned, Slow, and Sham) on two separate days. The Tuned condition refers to a situation in which the frequency of tACS is tuned to individual theta peak measured during a vsWM task. By contrast, the frequency was fixed to 4 Hz in the Slow condition. A high-definition tACS was deployed to target smaller frontal and parietal regions for increasing their phase-locking values. During each tACS condition, participants performed vsWM, mental rotation (MR), and arithmetic tasks. Resting-state EEG (rs-EEG) was recorded before and after each condition.

RESULTS

Compared with Sham, Tuned but not Slow improved both vsWM and MR but not arithmetics. The rs-EEG recording showed an increased fronto-parietal synchrony for Tuned, and this increase in synchronicity was correlated with the behavioral improvement. A follow-up study showed no behavioral improvement in Tuned with an anti-phase setting.

CONCLUSION

We provide the first evidence that simulating right fronto-parietal network with the tuned frequency increases the interregional synchronicity and improves performance on two spatial tasks. The results provide insight into the structure of spatial abilities as well as suggestions for stimulating the fronto-parietal network.

Longitudinal investigation of executive function development employing task-based, teacher reports, and fNIRS multimethodology in 4- to 5-year-old children

Increased focus on resting-state functional connectivity (rsFC) and the use and accessibility of functional near-infrared spectroscopy (fNIRS) have advanced knowledge on the interconnected nature of neural substrates underlying executive function (EF) development in adults and clinical populations. Less is known about the relationship between rsFC and developmental changes in EF during preschool years in typically developing children, a gap the present study addresses employing task-based assessment, teacher reports, and fNIRS multimethodology. This preregistered study contributes to our understanding of the neural basis of EF development longitudinally with 41 children ages 4-5. Changes in prefrontal cortex (PFC) rsFC utilizing fNIRS, EF measured with a common task-based assessment (Day-Night task), and teacher reports of behavior (BRIEF-P) were monitored over multiple timepoints: Initial Assessment, 72 h follow-up, 1 Month Follow-up, and 4 Month Follow-up. Measures of rsFC were strongly correlated 72 h apart, providing evidence of high rsFC measurement reliability using fNIRS with preschool-aged children. PFC rsFC was positively correlated with performance on task-based and report-based EF assessments. Children's PFC functional connectivity at rest uniquely predicted later EF, controlling for verbal IQ, age, and sex. Functional connectivity at rest using fNIRS may potentially show the rapid changes in EF development in young children, not only neurophysiologically, but also as a correlate of task-based EF performance and ecologically-relevant teacher reports of EF in a classroom context.

Oxytocin modulates social brain network correlations in resting and task state

The effects of oxytocin (OT) on the social brain can be tracked upon assessing the neural activity in resting and task states, and developing a system-level framework for characterizing the state-based functional relationships of its distinct effect. Here, we contribute to this framework by examining how OT modulates social brain network correlations during resting and task states, using fMRI. First, we investigated network activation, followed by an analysis of the relationships between networks and individual differences. Subsequently, we evaluated the functional connectivity in both states. Finally, the relationship between networks across states was represented by the predictive power of networks in the resting state for task-evoked activities. The differences in the predicted accuracy between the subjects displayed individual variations in this relationship. Our results showed that the activity of the dorsal default mode network in the resting state had the largest predictive power for task-evoked activation of the precuneus network (PN) only in the OT group. The results also demonstrated that OT reduced the individual variation in PN in the prediction process. These findings suggest a distributed but modulatory effect of OT on the association between resting and task-dependent brain networks.

A cognitive neurogenetic approach to uncovering the structure of executive functions

One central mission of cognitive neuroscience is to understand the ontology of complex cognitive functions. We addressed this question with a cognitive neurogenetic approach using a large-scale dataset of executive functions (EFs), whole-brain resting-state functional connectivity, and genetic polymorphisms. We found that the bifactor model with common and shifting-specific components not only was parsimonious but also showed maximal dissociations among the EF components at behavioral, neural, and genetic levels. In particular, the genes with enhanced expression in the middle frontal gyrus (MFG) and the subcallosal cingulate gyrus (SCG) showed enrichment for the common and shifting-specific component, respectively. Finally, High-dimensional mediation models further revealed that the functional connectivity patterns significantly mediated the genetic effect on the common EF component. Our study not only reveals insights into the ontology of EFs and their neurogenetic basis, but also provides useful tools to uncover the structure of complex constructs of human cognition.

Resting state networks mediate the association between both cardiovascular fitness and gross motor skills with neurocognitive functioning

Recent evidence suggests that cardiovascular fitness and gross motor skill performance are related to neurocognitive functioning by influencing brain structure and functioning. This study investigates the role of resting-state networks (RSNs) in the relation of cardiovascular fitness and gross motor skills with neurocognitive functioning in healthy 8- to 11-year-old children (n = 90, 45 girls, 10% migration background). Cardiovascular fitness and gross motor skills were related to brain activity in RSNs. Furthermore, brain activity in RSNs mediated the relation of both cardiovascular fitness (Frontoparietal network and Somatomotor network) and gross motor skills (Somatomotor network) with neurocognitive functioning. The results indicate that brain functioning may contribute to the relation between both cardiovascular fitness and gross motor skills with neurocognitive functioning.

Dissociable multi-scale patterns of development in personalized brain networks

The brain is organized into networks at multiple resolutions, or scales, yet studies of functional network development typically focus on a single scale. Here, we derive personalized functional networks across 29 scales in a large sample of youths (n = 693, ages 8-23 years) to identify multi-scale patterns of network re-organization related to neurocognitive development. We found that developmental shifts in inter-network coupling reflect and strengthen a functional hierarchy of cortical organization. Furthermore, we observed that scale-dependent effects were present in lower-order, unimodal networks, but not higher-order, transmodal networks. Finally, we found that network maturation had clear behavioral relevance: the development of coupling in unimodal and transmodal networks are dissociably related to the emergence of executive function. These results suggest that the development of functional brain networks align with and refine a hierarchy linked to cognition.

Intra-individual cognitive variability in neuropsychological assessment: a sign of neural network dysfunction

Intra-Individual Cognitive Variability (IICV) predicts progression in neurocognitive disorders . Given important clinical applications, we investigated the association between IICV and multiple brain metrics across 17 networks to better understand the brain mechanisms underlying this performance measure. Sixty-three middle-aged and older adults without dementia underwent a neuropsychological battery, resting-state fMRI, and structural MRI scans. In a linear mixed effect model, higher IICV was associated with lower functional connectivity in control C network relative to medial occipital network (the reference). A multivariate partial least squares analysis revealed that lower mean and higher variability were both associated with lower connectivity in sensorimotor and default mode networks, while higher mean and higher variability were associated with lower volume in default mode and limbic networks. This study suggests that IICV signals widespread network dysfunction across multiple brain networks. These brain abnormalities offer new insights into mechanisms of early cognitive dysfunction. Clinical implications are discussed.

Individual differences in mental imagery modulate effective connectivity of scene-selective regions during resting state

Successful navigation relies on the ability to identify, perceive, and correctly process the spatial structure of a scene. It is well known that visual mental imagery plays a crucial role in navigation. Indeed, cortical regions encoding navigationally relevant information are also active during mental imagery of navigational scenes. However, it remains unknown whether their intrinsic activity and connectivity reflect the individuals' ability to imagine a scene. Here, we primarily investigated the intrinsic causal interactions among scene-selective brain regions such as Parahipoccampal Place Area (PPA), Retrosplenial Complex, and Occipital Place Area (OPA) using Dynamic Causal Modelling for resting-state functional magnetic resonance data. Second, we tested whether resting-state effective connectivity parameters among scene-selective regions could reflect individual differences in mental imagery in our sample, as assessed by the self-reported Vividness of Visual Imagery Questionnaire. We found an inhibitory influence of occipito-medial on temporal regions, and an excitatory influence of more anterior on more medial and posterior brain regions. Moreover, we found that a key role in imagery is played by the connection strength from OPA to PPA, especially in the left hemisphere, since the influence of the signal between these scene-selective regions positively correlated with good mental imagery ability. Our investigation contributes to the understanding of the complexity of the causal interaction among brain regions involved in navigation and provides new insight in understanding how an essential ability, such as mental imagery, can be explained by the intrinsic fluctuation of brain signal.

Need for cognitive closure is associated with different intra-network functional connectivity patterns: A resting state EEG study

Need for Cognitive Closure (NCC) is a construct referring to the desire for predictability, unambiguity and firm answers to issues. Neuroscientific literature about NCC processes has mainly focused on task-related brain activity. According to the Triple Network model (TN), the main aim of the current study was to investigate resting state (RS) electroencephalographic (EEG) intra-network dynamics associated with NCC. Fifty-two young adults (39 females) were enrolled and underwent EEG recordings during RS. Functional connectivity analysis was computed through exact Low-Resolution Electromagnetic Tomography (eLORETA) software. Our results showed that higher levels of NCC were associated with both i) decreased alpha EEG connectivity within the Central Executive Network (CEN), and ii) increased delta connectivity within the Default Mode Network (DMN). No significant correlations were observed between NCC and functional connectivity in the Salience Network (SN). Our data would seem to suggest that high levels of NCC are characterized by a specific communication pattern within the CEN and the DMN during RS. These neurophysiological patterns might reflect several typical NCC-related cognitive characteristics (e.g., lower flexibility and preference for habitual and rigid response schemas).

The Relationship Between Default Mode and Dorsal Attention Networks Is Associated With Depressive Disorder Diagnosis and the Strength of Memory Representations Acquired Prior to the Resting State Scan

Previous research indicates that individuals with depressive disorders (DD) have aberrant resting state functional connectivity and may experience memory dysfunction. While resting state functional connectivity may be affected by experiences preceding the resting state scan, little is known about this relationship in individuals with DD. Our study examined this question in the context of object memory. 52 individuals with DD and 45 healthy controls (HC) completed clinical interviews, and a memory encoding task followed by a forced-choice recognition test. A 5-min resting state fMRI scan was administered immediately after the forced-choice task. Resting state networks were identified using group Independent Component Analysis across all participants. A network modeling analysis conducted on 22 networks using FSLNets examined the interaction effect of diagnostic status and memory accuracy on the between-network connectivity. We found that this interaction significantly affected the relationship between the network comprised of the medial prefrontal cortex, posterior cingulate cortex, and hippocampal formation and the network comprised of the inferior temporal, parietal, and prefrontal cortices. A stronger positive correlation between these two networks was observed in individuals with DD who showed higher memory accuracy, while a stronger negative correlation (i.e., anticorrelation) was observed in individuals with DD who showed lower memory accuracy prior to resting state. No such effect was observed for HC. The former network cross-correlated with the default mode network (DMN), and the latter cross-correlated with the dorsal attention network (DAN). Considering that the DMN and DAN typically anticorrelate, we hypothesize that our findings indicate aberrant reactivation and consolidation processes that occur after the task is completed. Such aberrant processes may lead to continuous "replay" of previously learned, but currently irrelevant, information and underlie rumination in depression.

Changes in ventromedial prefrontal cortex functional connectivity are correlated with increased risk-taking after total sleep deprivation

There is evidence indicating that people are more likely to take risks when they are sleep-deprived than during resting wakefulness (RW). The ventromedial prefrontal cortex (vmPFC) could have a crucial psychophysiological role in this phenomenon. However, the intrinsic patterns of functional organization of the human vmPFC and their relationship with risk-taking during sleep deprivation (SD) are unclear. This study investigated the relationship between functional connectivity in the vmPFC and cerebral cortex and the risk-taking tendency after SD. The study participants were 21 healthy college students who underwent functional magnetic resonance imaging twice in the resting state, once during RW and once after 36 h of SD. The vmPFC was analyzed bilaterally for functional connectivity between the regions of interest. Correlation analysis was performed to evaluate changes in functional connectivity between the vmPFC and the cerebral cortex and risk-taking before and after SD. A single night of SD produced a definite deficit in functional connectivity between the vmPFC and thalamus bilaterally and an increase in functional connectivity between the vmPFC and dorsolateral prefrontal cortex (dlPFC) and the parietal lobe. We also found that the likelihood of risk-taking was positively correlated with increased functional connectivity between the vmPFC and dlPFC and negatively correlated with decreased functional connectivity between the vmPFC and thalamus bilaterally. These results demonstrate that lack of sleep substantially impairs functional connectivity between the vmPFC and the cerebral cortex, which in turn predicts the risk-taking behavior found after SD.

Musical memories in newborns: A resting-state functional connectivity study

Music is known to induce emotions and activate associated memories, including musical memories. In adults, it is well known that music activates both working memory and limbic networks. We have recently discovered that as early as during the newborn period, familiar music is processed differently from unfamiliar music. The present study evaluates music listening effects at the brain level in newborns, by exploring the impact of familiar or first‐time music listening on the subsequent resting‐state functional connectivity in the brain. Using a connectome‐based framework, we describe resting‐state functional connectivity (RS‐FC) modulation after music listening in three groups of newborn infants, in preterm infants exposed to music during their neonatal‐intensive‐care‐unit (NICU) stay, in control preterm, and full‐term infants. We observed modulation of the RS‐FC between brain regions known to be implicated in music and emotions processing, immediately following music listening in all newborn infants. In the music exposed group, we found increased RS‐FC between brain regions known to be implicated in familiar and emotionally arousing music and multisensory processing, and therefore implying memory retrieval and associative memory. We demonstrate a positive correlation between the occurrence of the prior music exposure and increased RS‐FC in brain regions implicated in multisensory and emotional processing, indicating strong engagement of musical memories; and a negative correlation with the Default Mode Network, indicating disengagement due to the aforementioned cognitive processing. Our results describe the modulatory effect of music listening on brain RS‐FC that can be linked to brain correlates of musical memory engrams in preterm infants.

The role of prefrontal cortex in cognitive control and executive function

Concepts of cognitive control (CC) and executive function (EF) are defined in terms of their relationships with goal-directed behavior versus habits and controlled versus automatic processing, and related to the functions of the prefrontal cortex (PFC) and related regions and networks. A psychometric approach shows unity and diversity in CC constructs, with 3 components in the most commonly studied constructs: general or common CC and components specific to mental set shifting and working memory updating. These constructs are considered against the cellular and systems neurobiology of PFC and what is known of its functional neuroanatomical or network organization based on lesioning, neurochemical, and neuroimaging approaches across species. CC is also considered in the context of motivation, as "cool" and "hot" forms. Its Common CC component is shown to be distinct from general intelligence (g) and closely related to response inhibition. Impairments in CC are considered as possible causes of psychiatric symptoms and consequences of disorders. The relationships of CC with the general factor of psychopathology (p) and dimensional constructs such as impulsivity in large scale developmental and adult populations are considered, as well as implications for genetic studies and RDoC approaches to psychiatric classification.

Topographical functional correlates of interindividual differences in executive functions in young healthy twins

Executive functions (EF) are a set of higher-order cognitive abilities that enable goal-directed behavior by controlling lower-level operations. In the brain, those functions have been traditionally associated with activity in the Frontoparietal Network, but recent neuroimaging studies have challenged this view in favor of more widespread cortical involvement. In the present study, we aimed to explore whether the network that serves as critical hubs at rest, which we term network reliance, differentiate individuals as a function of their level of EF. Furthermore, we investigated whether such differences are driven by genetic as compared to environmental factors. For this purpose, resting-state functional magnetic resonance imaging data and the behavioral testing of 453 twins from the Colorado Longitudinal Twins Study were analyzed. Separate indices of EF performance were obtained according to a bifactor unity/diversity model, distinguishing between three independent components representing: Common EF, Shifting-specific and Updating-specific abilities. Through an approach of step-wise in silico network lesioning of the individual functional connectome, we show that interindividual differences in EF are associated with different dependencies on neural networks at rest. Furthermore, these patterns show evidence of mild heritability. Such findings add knowledge to the understanding of brain states at rest and their connection with human behavior, and how they might be shaped by genetic influences.

Specificity of anhedonic alterations in resting-state network connectivity and structure: A transdiagnostic approach

Anhedonia is a prominent characteristic of depression and related pathology that is associated with a prolonged course of mood disturbance and treatment resistance. However, the neurobiological mechanisms of anhedonia are poorly understood as few studies have disentangled the specific effects of anhedonia from other co-occurring symptoms. Here, we take a transdiagnostic, dimensional approach to distinguish anhedonia alterations from other internalizing symptoms on intrinsic functional brain circuits. 53 adults with varying degrees of anxiety and/or depression completed resting-state fMRI. Neural networks were identified through independent components analysis. Dual regression was used to characterize within-network functional connectivity alterations associated with individual differences in anhedonia. Modulation of between-network functional connectivity by anhedonia was tested using region-of-interest to region-of-interest correlational analyses. Anhedonia was associated with visual network hyperconnectivity and expansion of the visual, dorsal attention, and default networks. Additionally, anhedonia was associated with decreased between-network connectivity among default, salience, dorsal attention, somatomotor, and visual networks. Findings suggest that anhedonia is associated with aberrant connectivity and structural alterations in resting-state networks that contribute to impairments in reward learning, low motivation, and negativity bias characteristic of depression. Results reveal dissociable effects of anhedonia on resting-state network dynamics, characterizing possible neurocircuit mechanisms for intervention.