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• Substance use and abuse are risk factors for disability and premature loss of life. • Neuroimmune research can generate integrative models of risk for substance use. • Participants completed MRI scan of executive control neural activity and blood draw. • Low executive control and high inflammation associated with higher substance use. • Implications for understanding psychological, neural, and immunological risk. Individuals with substance use problems show lower executive control and alterations in prefrontal brain systems supporting emotion regulation and impulse control. A separate literature suggests that heightened inflammation also increases risk for substance use, in part, through targeting brain systems involved in executive control. Research on neural and inflammatory signaling in substance use, however, has occurred in parallel. Drawing on recent neuroimmune network models, we used fMRI to examine the relationships between executive control-related brain activity (as elicited by an n-back working memory task), peripheral inflammation, as quantified by inflammatory cytokines and C-reactive protein (CRP), and substance use for the past month in 93 participants [mean age = 24.4 (SD = 0.6)]. We operationalized low executive control as a neural inefficiency during the n-back task to achieve normative performance, as reflected in higher working memory-related brain activity and lower activity in the default mode network (DMN). Consistent with prediction, individuals with low executive control and high inflammation reported more substance use over the past month, controlling for behavioral performance on the n-back, sex, time between assessments, body-mass-index (BMI), and personal socioeconomic status (SES) (interaction between inflammation and working memory-related brain activity, b = 0.210, p = 0.005; interaction between inflammation and DMN, b = -0.219, p < 0.001). Findings suggest that low executive control and high inflammation may be associated with higher substance use. This has implications for understanding psychological, neural, and immunological risk for substance use problems and the development of interventions to target each of these components. [ABSTRACT FROM AUTHOR]

• Neurobiological link of default mode network connectivity in somatic symptom disorder. • Affective symptoms bridge links between neurobiological markers and somatic symptom. • Anxiety/anger mediate relation between default mode network and somatic symptom. • Depression/anger connect serotonin marker with somatic symptom. • Neuroimmune markers tie default mode network to affective symptom. Somatic symptom disorder (SSD) is characterized by physical symptoms and associated functional impairments that are often comorbid with depression and anxiety disorders. In this study, we explored relationships between affective symptoms and the functional connectivity of the default mode network (DMN) in SSD patients, as well as the impact of peripheral inflammation. We employed mediation analyses to investigate the potential pathways between these factors. We recruited a total of 119 individuals (74 unmedicated SSD patients and 45 healthy controls), who were subjected to comprehensive psychiatric and clinical evaluations, blood tests, and resting-state functional magnetic resonance imaging scanning. We assessed neuroimmune markers (interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), tumor necrosis factor-α (TNF-α), tryptophan, serotonin, and 5-hydroxyindoleacetic acid (5-HIAA)), clinical indicators of somatic symptoms, depression, anxiety, anger, alexithymia, and functional connectivity (FC) within the DMN regions. Data were analyzed using correlation and mediation analysis, with a focus on exploring potential relations between clinical symptoms, blood indices, and DMN FCs. Patients with SSD had higher clinical scores as well as IL-6 and TNF-α levels compared with those in the control group (P < 0.05). The SSD group exhibited lower FC strength between the left inferior parietal lobule and left prefrontal cortex (P false discovery rate (FDR) < 0.05). Exploratory correlation analysis revealed that somatic symptom scores were positively correlated with affective symptom scores, negatively correlated with the FC strength between the intra prefrontal cortex regions, and correlated with levels of IL-6, TNF- α, and tryptophan (uncorrected P < 0.01). Mediation analysis showed that levels of anxiety and trait anger significantly mediated the relations between DMN FC strength and somatic symptoms. In addition, the DMN FC mediated the level of trait anger with respect to somatic symptoms (all P FDR < 0.05). The levels of depression and trait anger exhibited significant mediating effects as suppressors of the relations between the level of 5-HIAA and somatic symptom score (all P FDR < 0.05). Further, the level of 5-HIAA had a mediating effect as a suppressor on the relation between DMN FC and state anger. Meanwhile, the levels of hs-CRP and IL-6 had full mediating effects as suppressors when explaining the relations of DMN FC strengths with the level of depression (all P FDR < 0.05). The patterns of valid mediation pathways were different in the control group. Affective symptoms may indirectly mediate the associations between DMN connectivity, somatic symptoms, and neuroimmune markers. Inflammatory markers may also mediate the impact of DMN connectivity on affective symptoms. These results emphasize the importance of affective dysregulation in understanding the mechanisms of SSD and have potential implications for the development of tailored therapeutic approaches for SSD patients with affective symptoms. Furthermore, in SSD research using DMN FC or neuroimmune markers, considering and incorporating such mediating effects of affective symptoms suggests the possibility of more accurate prediction and explanation. [ABSTRACT FROM AUTHOR]

• Morphometric similarity networks characterized structural brain network integrity. • Brain network integrity is lower among youth living with perinatally acquired HIV. • Emotional symptoms were associated with higher global efficiency in the salience network and lower global efficiency in the default mode network. • Inflammatory and cardiac markers were associated with structural network integrity. Perinatally acquired HIV infection (PHIV) currently affects approximately 1.7 million children worldwide. Youth with PHIV (YPHIV) are at increased risk for emotional and behavioral symptoms, yet few studies have examined relationships between these symptoms and brain structure. Previous neuroimaging studies in YPHIV report alterations within the salience network (SN), cognitive control network (CCN), and default mode network (DMN). These areas have been associated with social and emotional processing, emotion regulation, and executive function. We examined structural brain network integrity from MRI using morphometric similarity networks and graph theoretical measures of segregation (transitivity), resilience (assortativity), and integration (global efficiency). We examined brain network integrity of 40 YPHIV compared to 214 youths without HIV exposure or infection. Amongst YPHIV, we related structural brain network metrics to the Emotional Symptoms Index of the Behavioral Assessment System for Children, 2nd edition. We also examined the relationship of inflammatory biomarkers in YPHIV to brain network integrity. YPHIV had significantly lower global efficiency in the SN, DMN, and the whole brain network compared to controls. YPHIV also demonstrated lower assortativity or resilience (i.e., network robustness) compared to controls in the DMN and whole brain network. Further, higher emotional symptom score was associated with higher global efficiency in the SN and lower global efficiency in the DMN, signaling more emotional challenges. A significant association was also found between several inflammatory and cardiac markers with structural network integrity. These findings suggest an impact of HIV on developing brain networks, and potential dysfunction of the SN and DMN in relation to network efficiency. [ABSTRACT FROM AUTHOR]

• Data driven inflammatory subgroups show connectivity differences in psychosis. • High inflammation subgroup has lower DMNa activity vs the low inflammation group. • High inflammation subgroup has lower DMNa functional connectivity vs the low group. • High inflammation subgroup has lower multiplex participation vs the low group. • Network findings in high inflammation subgroups correlate with worse cognition. High-inflammation subgroups of patients with psychosis demonstrate cognitive deficits and neuroanatomical alterations. Systemic inflammation assessed using IL-6 and C-reactive protein may alter functional connectivity within and between resting-state networks, but the cognitive and clinical implications of these alterations remain unknown. We aim to determine the relationships of elevated peripheral inflammation subgroups with resting-state functional networks and cognition in psychosis spectrum disorders. Serum and resting-state fMRI were collected from psychosis probands (schizophrenia, schizoaffective, psychotic bipolar disorder) and healthy controls (HC) from the B-SNIP1 (Chicago site) study who were stratified into inflammatory subgroups based on factor and cluster analyses of 13 cytokines (HC Low n = 32, Proband Low n = 65, Proband High n = 29). Nine resting-state networks derived from independent component analysis were used to assess functional and multilayer connectivity. Inter-network connectivity was measured using Fisher z-transformation of correlation coefficients. Network organization was assessed by investigating networks of positive and negative connections separately, as well as investigating multilayer networks using both positive and negative connections. Cognition was assessed using the Brief Assessment of Cognition in Schizophrenia. Linear regressions, Spearman correlations, permutations tests and multiple comparison corrections were used for analyses in R. Anterior default mode network (DMNa) connectivity was significantly reduced in the Proband High compared to Proband Low (Cohen's d = -0.74, p = 0.002) and HC Low (d = -0.85, p = 0.0008) groups. Inter-network connectivity between the DMNa and the right-frontoparietal networks was lower in Proband High compared to Proband Low (d = -0.66, p = 0.004) group. Compared to Proband Low, the Proband High group had lower negative (d = 0.54, p = 0.021) and positive network (d = 0.49, p = 0.042) clustering coefficient, and lower multiplex network participation coefficient (d = -0.57, p = 0.014). Network findings in high inflammation subgroups correlate with worse verbal fluency, verbal memory, symbol coding, and overall cognition. These results expand on our understanding of the potential effects of peripheral inflammatory signatures and/or subgroups on network dysfunction in psychosis and how they relate to worse cognitive performance. Additionally, the novel multiplex approach taken in this study demonstrated how inflammation may disrupt the brain's ability to maintain healthy co-activation patterns between the resting-state networks while inhibiting certain connections between them. [ABSTRACT FROM AUTHOR]

• GPT was associated with present fatalism and trait impulsivity but not with state impulsivity. • Functional activation strengths and patterns in the DMPFC, SPL, and cerebellum when processing delay time length of future options were critical for GPT. • Spontaneous brain activity patterns in the DMN, FPN, and VIS support the formation of dispositional greed. • Greedy individuals exhibit specific white matter characteristics. The interplay between personality traits and impulsivity has long been a central theme in psychology and psychiatry. However, the potential association between Greed Personality Traits (GPT) and impulsivity, encompassing both trait and state impulsivity and future time perspective, remains largely unexplored. To address these issues, we employed questionnaires and an inter-temporal choice task to estimate corresponding trait/state impulsivity and collected multi-modal neuroimaging data (resting-state functional imaging: n = 430; diffusion-weighted imaging: n = 426; task-related functional imaging: n = 53) to investigate the underlying microstructural and functional substrates. Behavioral analyses revealed that GPT mediated the association between time perspective (e.g., present fatalism) and trait impulsivity (e.g., motor impulsivity). Functional imaging analyses further identified that brain activation strengths and patterns related to delay length, particularly in the dorsomedial prefrontal cortex, superior parietal lobule, and cerebellum, were associated with GPT. Moreover, individuals with similar levels of greed exhibited analogous spontaneous brain activity patterns, predominantly in the Default Mode Network (DMN), Fronto-Parietal Network (FPN), and Visual Network (VIS). Diffusion imaging analysis observed specific microstructural characteristics in the spinocerebellar/pontocerebellar fasciculus, internal/external capsule, and corona radiata that support the formation of GPT. Furthermore, the corresponding neural activation pattern, spontaneous neural activity pattern, and analogous functional couplings among the aforementioned brain regions mediated the relationships between time perspective and GPT and between GPT and motor impulsivity. These findings provide novel insights into the possible pathway such as time perspective → dispositional greed → impulsivity and uncover their underlying microstructural and functional substrates. [ABSTRACT FROM AUTHOR]

• Meta-analysis synthesizes neuroimaging studies on escalated aggression. • Regions involved localized in subcortical, default mode, and salience networks. • Identified regions linked to emotion processing, mentalizing, cognitive control. • Findings refine theoretical models and provide insight into escalated aggressive populations. Escalated aggression represents a frequent and severe form of violence, sometimes manifesting as antisocial behavior. Driven by the pressures of modern life, escalated aggression is of particular concern due to its rising prevalence and its destructive impact on both individual well-being and socioeconomic stability. However, a consistent neural circuitry underpinning it remains to be definitively identified. Here, we addressed this issue by comparing brain alterations between individuals with escalated aggression and those without such behavioral manifestations. We first conducted a meta-analysis to synthesize previous neuroimaging studies on functional and structural alterations of escalated aggression (325 experiments, 2997 foci, 16,529 subjects). Following-up network and functional decoding analyses were conducted to provide quantitative characterizations of the identified brain regions. Our results revealed that brain regions constantly involved in escalated aggression were localized in the subcortical network (amygdala and lateral orbitofrontal cortex) associated with emotion processing, the default mode network (dorsal medial prefrontal cortex and middle temporal gyrus) associated with mentalizing, and the salience network (anterior cingulate cortex and anterior insula) associated with cognitive control. These findings were further supported by additional meta-analyses on emotion processing, mentalizing, and cognitive control, all of which showed conjunction with the brain regions identified in the escalated aggression. Together, these findings advance the understanding of the risk biomarkers of escalated aggressive populations and refine theoretical models of human aggression. [ABSTRACT FROM AUTHOR]

• We reviewed and meta-analyzed regional homogeneity studies about MCI and AD. • We present a novel Bayesian implementation for the activation likelihood estimation method. • Distinctive and non-overlapping short-range connectivity changes were found for MCI and AD. • ReHo variations are localized within hub nodes of the default mode network. • Functional aberrations are statistically associated with memory, language, and social functioning domains. Functional magnetic resonance imaging research employing regional homogeneity (ReHo) analysis has uncovered aberrant local brain connectivity in individuals with mild cognitive impairment (MCI) and Alzheimer's disease (AD) in comparison with healthy controls. However, the precise localization, extent, and possible overlap of these aberrations are still not fully understood. To bridge this gap, we applied a novel meta-analytic and Bayesian method (minimum Bayes Factor Activation Likelihood Estimation, mBF-ALE) for a systematic exploration of local functional connectivity alterations in MCI and AD brains. We extracted ReHo data via a standardized MEDLINE database search, which included 35 peer-reviewed experiments, 1,256 individuals with AD or MCI, 1,118 healthy controls, and 205 x-y-z coordinates of ReHo variation. We then separated the data into two distinct datasets: one for MCI and the other for AD. Two mBF-ALE analyses were conducted, thresholded at "very strong evidence" (mBF ≥ 150), with a minimum cluster size of 200 mm³. We also assessed the spatial consistency and sensitivity of our Bayesian results using the canonical version of the ALE algorithm. For MCI, we observed two clusters of ReHo decrease and one of ReHo increase. Decreased local connectivity was notable in the left precuneus (Brodmann area – BA 7) and left inferior temporal gyrus (BA 20), while increased connectivity was evident in the right parahippocampal gyrus (BA 36). The canonical ALE confirmed these locations, except for the inferior temporal gyrus. In AD, one cluster each of ReHo decrease and increase were found, with decreased connectivity in the right posterior cingulate cortex (BA 30 extending to BA 23) and increased connectivity in the left posterior cingulate cortex (BA 31). These locations were confirmed by the canonical ALE. The identification of these distinct functional connectivity patterns sheds new light on the complex pathophysiology of MCI and AD, offering promising directions for future neuroimaging-based interventions. Additionally, the use of a Bayesian framework for statistical thresholding enhances the robustness of neuroimaging meta-analyses, broadening its applicability to small datasets. [ABSTRACT FROM AUTHOR]

• The study informs on the differentiation of cerebral cortex areas in neonates. • A novel approach was used to map the functional structure of local connections. • The existence of measurable connections does not necessarily indicate full maturity. • A long developmental journey the neonatal brain must undergo to reach adulthood. Neuroimaging research on functional connectivity can provide valuable information on the developmental differentiation of the infant cerebral cortex into its functional areas. We examined healthy neonates to comprehensively map brain functional connectivity using a combination of local measures that uniquely capture the rich spatial structure of cerebral cortex functional connections. Optimal functional MRI scans were obtained in 61 neonates. Local functional connectivity maps were based on Iso-Distance Average Correlation (IDAC) measures. Single distance maps and maps combining three distinct IDAC measures were used to assess different levels of cortical area functional differentiation. A set of brain areas showed higher connectivity than the rest of the brain parenchyma in each local distance map. These areas were consistent with those supporting basic aspects of the neonatal repertoire of adaptive behaviors and included the sensorimotor, auditory and visual cortices, the frontal operculum/anterior insula (relevant for sucking, swallowing and the sense of taste), paracentral lobule (processing anal and urethral sphincter activity), default mode network (relevant for self-awareness), and limbic-emotional structures such as the anterior cingulate cortex, amygdala and hippocampus. However, the results also indicate that brain areas presumed to be actively developing may not necessarily be mature. In fact, combined distance, second-level maps confirmed that the functional differentiation of the cerebral cortex into functional areas in neonates is far from complete. Our results provide a more comprehensive understanding of the developing brain systems, while also highlighting the substantial developmental journey that the neonatal brain must undergo to reach adulthood. [ABSTRACT FROM AUTHOR]

• Our findings provide novel intracranial electrophysiological evidence supporting the network model of intrinsic brain architecture. • Our phase-amplitude coupling analysis revealed that the low-frequency phase in the DMN modulates the high-frequency amplitude envelopes within the FPN. • Our work sheds light on the frequency-dependent oscillatory communications of intrinsic brain networks. Non-invasive neuroimaging has revealed specific network-based resting-state dynamics in the human brain, yet the underlying neurophysiological mechanism remains unclear. We employed intracranial electroencephalography to characterize local field potentials within the default mode network (DMN), frontoparietal network (FPN), and salience network (SN) in 42 participants. We identified stronger within-network phase coherence at low frequencies (θ and α band) within the DMN, and at high frequencies (γ band) within the FPN. Hidden Markov modeling indicated that the DMN exhibited preferential low frequency phase coupling. Phase-amplitude coupling (PAC) analysis revealed that the low-frequency phase in the DMN modulated the high-frequency amplitude envelopes of the FPN, suggesting frequency-dependent characterizations of intrinsic brain networks at rest. These findings provide intracranial electrophysiological evidence in support of the network model for intrinsic organization of human brain and shed light on the way brain networks communicate at rest. [ABSTRACT FROM AUTHOR]

• Early deprivation was associated with long-term impacts on behavioral and brain measures of executive function. • Later-adopted youth showed poorer accuracy than earlier- and non-adopted (NA) youth despite similar brain activity. • Youth with a history of early deprivation recruited additional frontoparietal brain regions compared to NA youth. • Duration of deprivation was negatively associated with task-related activity in the default mode network. • This study is among the first to use fMRI measures to examine the impact of early deprivation on executive function and brain development. Children reared in institutional settings experience early deprivation that has lasting implications for multiple aspects of neurocognitive functioning, including executive function (EF). Changes in brain development are thought to contribute to these persistent EF challenges, but little research has used fMRI to investigate EF-related brain activity in children with a history of early deprivation. This study examined behavioral and neural data from a response conflict task in 12–14-year-olds who spent varying lengths of time in institutional care prior to adoption (N = 84; age at adoption – mean: 15.85 months, median: 12 months, range: 4–60 months). In initial analyses, earlier- and later-adopted (EA, LA) youth were compared to a group of children raised in their biological families (non-adopted, NA). NA youth performed significantly more accurately than LA youth, with EA youth falling in between. Imaging data suggested that previously institutionalized (PI) youth activated additional frontoparietal regions, including dorsolateral prefrontal cortex, as compared to NA youth. In addition, EA youth uniquely activated medial prefrontal regions, and LA uniquely activated parietal regions during this task. A separate analysis in a larger group of PI youth examined whether behavioral or brain measures of EF varied with the duration of deprivation experienced. Duration of deprivation was negatively associated with activation of default mode network (DMN) regions. Overall, results suggest that there are lasting effects of deprivation on EF, but that those who are removed from institutional care earlier may be able to recruit additional neural resources as a compensatory mechanism. [ABSTRACT FROM AUTHOR]

• Dynamic windows and modularity algorithms track brain changes in young children • Mixed-effects model links age with brain metrics across mixed time points • Mediation analysis reveals how brain efficiency relates to network dynamics Modular dynamic graph theory metrics effectively capture the patterns of dynamic information interaction during human brain development. While existing research has employed modular algorithms to examine the overall impact of dynamic changes in community structure throughout development, there is a notable gap in understanding the cross-community dynamic changes within different functional networks during early childhood and their potential contributions to the efficiency of brain information transmission. This study seeks to address this gap by tracing the trajectories of cross-community structural changes within early childhood functional networks and modeling their contributions to information transmission efficiency. We analyzed 194 functional imaging scans from 83 children aged 2 to 8 years, who participated in passive viewing functional magnetic resonance imaging sessions. Utilizing sliding windows and modular algorithms, we evaluated three spatiotemporal metrics—temporal flexibility, spatiotemporal diversity, and within-community spatiotemporal diversity—and four centrality metrics: within-community degree centrality, eigenvector centrality, between-community degree centrality, and between-community eigenvector centrality. Mixed-effects linear models revealed significant age-related increases in the temporal flexibility of the default mode network (DMN), executive control network (ECN), and salience network (SN), indicating frequent adjustments in community structure within these networks during early childhood. Additionally, the spatiotemporal diversity of the SN also displayed significant age-related increases, highlighting its broad pattern of cross-community dynamic interactions. Conversely, within-community spatiotemporal diversity in the language network exhibited significant age-related decreases, reflecting the network's gradual functional specialization. Furthermore, our findings indicated significant age-related increases in between-community degree centrality across the DMN, ECN, SN, language network, and dorsal attention network, while between-community eigenvector centrality also increased significantly for the DMN, ECN, and SN. However, within-community eigenvector centrality remained stable across all functional networks during early childhood. These results suggest that while centrality of cross-community interactions in early childhood functional networks increases, centrality within communities remains stable. Finally, mediation analysis was conducted to explore the relationships between age, brain dynamic graph metrics, and both global and local efficiency based on community structure. The results indicated that the dynamic graph metrics of the SN primarily mediated the relationship between age and the decrease in global efficiency, while those of the DMN, language network, ECN, dorsal attention network, and SN primarily mediated the relationship between age and the increase in local efficiency. This pattern suggests a developmental trajectory in early childhood from global information integration to local information segregation, with the SN playing a pivotal role in this transformation. This study provides novel insights into the mechanisms by which early childhood brain functional development impacts information transmission efficiency through cross-community adjustments in functional networks. [ABSTRACT FROM AUTHOR]

• The neural basis of homophily is measured as increased similarity in brain activity. • Watching a movie, sisters' brain activity is more similar than that of friends. • Higher-order brain areas including the default mode network show correlated activity. • Similarity in brain activity is stronger the closer the relationship between people. • Increased ISC could not be explained by genetic relation between sisters. Relationships between humans are essential for how we see the world. Using fMRI, we explored the neural basis of homophily, a sociological concept that describes the tendency to bond with similar others. Our comparison of brain activity between sisters, friends and acquaintances while they watched a movie, indicate that sisters' brain activity is more similar than that of friends and friends' activity is more similar than that of acquaintances. The increased similarity in brain activity measured as inter-subject correlation (ISC) was found both in higher-order brain areas including the default-mode network (DMN) and sensory areas. Increased ISC could not be explained by genetic relation between sisters neither by similarities in eye-movements, emotional experiences, and physiological activity. Our findings shed light on the neural basis of homophily by revealing that similarity in brain activity in the DMN and sensory areas is the stronger the closer is the relationship between the people. [ABSTRACT FROM AUTHOR]

• Happiness is divided into two main parts: an individual factor and a social factor. • Happiness mediated the effect of personality on aggression. • Happy people exhibit similar neural activation patterns in visual pathway but not emotional network when processing fearful faces. • Happy people are associated with similar morphological patterns within the DMN, FPN, VIS, and AN. A fundamental question in the study of happiness is whether there is neural evidence to support a well-known hypothesis that happy people are always similar while unfortunate people have their own misfortunes. To investigate this, we employed several happiness-related questionnaires to identify potential components of happiness, and further investigated and confirmed their associations with personality, mood, aggressive behaviors, and amygdala reactivity to fearful faces within a substantial sample size of college students (n = 570). Additionally, we examined the functional and morphological similarities and differences among happy individuals using the inter-subject representational similarity analysis (IS-RSA). IS-RSA emphasizes the geometric properties in a high-dimensional space constructed by brain or behavioral patterns and focuses on individual subjects. Our behavioral findings unveiled two factors of happiness: individual and social, both of which mediated the effect of personality traits on individual aggression. Subsequently, mood mediated the impact of happiness on aggressive behaviors across two subgroup splits. Functional imaging data revealed that individuals with higher levels of happiness exhibited reduced amygdala reactivity to fearful faces, as evidenced by a conventional face-matching task (n = 104). Moreover, IS-RSA demonstrated that these participants manifested similar neural activation patterns when processing fearful faces within the visual pathway, but not within the emotional network (e.g., amygdala). Morphological observations (n = 425) indicated that individuals with similar high happiness levels exhibited comparable gray matter volume patterns within several networks, including the default mode network, fronto-parietal network, visual network, and attention network. Collectively, these findings offer early neural evidence supporting the proposition that happy individuals may share common neural characteristics. [ABSTRACT FROM AUTHOR]

• Structural and functional connectivity were validated by two datasets. • A reproducible association was found between the PCC and the right hippocampus. • These altered connection indices were correlated with cognitive ability. Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by progressive dementia, and amnestic mild cognitive impairment (aMCI) has been defined as a transitional stage between normal aging and AD. Accumulating evidence has shown that altered functional connectivity (FC) and structural connectivity (SC) in the default mode network (DMN) is the prominent hallmarks of AD. However, the relationship between the changes in SC and FC of the DMN is not yet clear. In the present study, we derived the FC and SC matrices of the DMN with functional magnetic resonance imaging (fMRI) and diffusion-weighted imaging (DWI) data and further assessed FC and SC abnormalities within a discovery dataset of 120 participants (39 normal controls, 34 patients with aMCI and 47 patients with AD), as well as a replication dataset of 122 participants (43 normal controls, 37 patients with aMCI and 42 patients with AD). Disrupted SC and FC were found among DMN components (e.g., the posterior cingulate cortex (PCC), medial prefrontal cortex (mPFC), and hippocampus) in patients in the aMCI and AD groups in the discovery dataset; most of the disrupted connections were also identified in the replication dataset. More importantly, some SC and FC elements were significantly correlated with the cognitive ability of patients with aMCI and AD. In addition, we found structural–functional decoupling between the PCC and the right hippocampus in patients in the aMCI and AD groups. These findings of the alteration of DMN connectivity in neurodegenerative cohorts deepen our understanding of the pathophysiological mechanisms of AD. [ABSTRACT FROM AUTHOR]

• Resting-state fMRI BOLD signal of the human brain is a superposition of EM and DM. • EM (essential mode) is asymmetric and the most dominant mode for individuals. • DM (DMN-like mode) is the second dominant mode that holds the default mode network. • Both EM and DM are activated with low-frequency oscillations in the below 0.2 Hz. • The changes in active regions of the brain during motor-task are reflected in EM. Resting-state of the human brain has been described by a combination of various basis modes including the default mode network (DMN) identified by fMRI BOLD signals in human brains. Whether DMN is the most dominant representation of the resting-state has been under question. Here, we investigated the unexplored yet fundamental nature of the resting-state. In the absence of global signal regression for the analysis of brain-wide spatial activity pattern, the fMRI BOLD spatiotemporal signals during the rest were completely decomposed into time-invariant spatial-expression basis modes (SEBMs) and their time-evolution basis modes (TEBMs). Contrary to our conventional concept above, similarity clustering analysis of the SEBMs from 166 human brains revealed that the most dominant SEBM cluster is an asymmetric mode where the distribution of the sign of the components is skewed in one direction, for which we call essential mode (EM), whereas the second dominant SEBM cluster resembles the spatial pattern of DMN. Having removed the strong 1/f noise in the power spectrum of TEBMs, the genuine oscillatory behavior embedded in TEBMs of EM and DMN-like mode was uncovered around the low-frequency range below 0.2 Hz. [ABSTRACT FROM AUTHOR]

• Lower reading skills are associated with greater functional connectivity between EF networks (default mode network and memory network), and between the auditory and memory networks for the stories with vs without the visual stimulation. • Lower reading scores were associated with a greater difference in functional connectivity between the conditions. Narrative comprehension relies on basic sensory processing abilities, such as visual and auditory processing, with recent evidence for utilizing executive functions (EF), which are also engaged during reading. EF was previously related to the "supporter" of engaging the auditory and visual modalities in different cognitive tasks, with evidence of lower efficiency in this process among those with reading difficulties in the absence of a visual stimulus (i.e. while listening to stories). The current study aims to fill out the gap related to the level of reliance on these neural circuits while visual aids (pictures) are involved during story listening in relation to reading skills. Functional MRI data were collected from 44 Hebrew-speaking children aged 8–12 years while listening to stories with vs without visual stimuli (i.e., pictures). Functional connectivity of networks supporting reading was defined in each condition and compared between the conditions against behavioral reading measures. Lower reading skills were related to greater functional connectivity values between EF networks (default mode and memory networks), and between the auditory and memory networks for the stories with vs without the visual stimulation. A greater difference in functional connectivity between the conditions was related to lower reading scores. We conclude that lower reading skills in children may be related to a need for greater scaffolding, i.e., visual stimulation such as pictures describing the narratives when listening to stories, which may guide future intervention approaches. [ABSTRACT FROM AUTHOR]

• Provides a thorough understanding of brain activation during/immediately after prefrontal TMS. • The prefrontal cortex, insula, striatum, anterior cingulate and thalamus are engaged. • The target engagement (local and remote regions) is inconsistent among studies. This systematic review investigates how prefrontal transcranial magnetic stimulation (TMS) immediately influences neuronal excitability based on oxygenation changes measured by functional magnetic resonance imaging (fMRI) or functional near-infrared spectroscopy (fNIRS). A thorough understanding of TMS-induced excitability changes may enable clinicians to adjust TMS parameters and optimize treatment plans proactively. Five databases were searched for human studies evaluating brain excitability using concurrent TMS/fMRI or TMS/fNIRS. Thirty-seven studies (13 concurrent TMS/fNIRS studies, 24 concurrent TMS/fMRI studies) were included in a qualitative synthesis. Despite methodological inconsistencies, a distinct pattern of activated nodes in the frontoparietal central executive network, the cingulo-opercular salience network, and the default-mode network emerged. The activated nodes included the prefrontal cortex (particularly dorsolateral prefrontal cortex), insula cortex, striatal regions (especially caudate, putamen), anterior cingulate cortex, and thalamus. High-frequency repetitive TMS most consistently induced expected facilitatory effects in these brain regions. However, varied stimulation parameters (e.g., intensity, coil orientation, target sites) and the inter- and intra-individual variability of brain state contribute to the observed heterogeneity of target excitability and co-activated regions. Given the considerable methodological and individual variability across the limited evidence, conclusions should be drawn with caution. [ABSTRACT FROM AUTHOR]

The clinical symptoms of progressive supranuclear palsy (PSP) may be mediated by aberrant dynamic functional network connectivity (dFNC). While earlier research has found altered functional network connections in PSP patients, the majority of those studies have concentrated on static functional connectivity. Nevertheless, in this study, we sought to evaluate the modifications in dynamic characteristics and establish the correlation between these disease-related changes and clinical variables. In our study, we conducted a study on 53 PSP patients and 65 normal controls. Initially, we employed a group independent component analysis (ICA) to derive resting-state networks (RSNs), while employing a sliding window correlation approach to produce dFNC matrices. The K-means algorithm was used to cluster these matrices into distinct dynamic states, and then state analysis was subsequently employed to analyze the dFNC and temporal metrics between the two groups. Finally, we made a correlation analysis. PSP patients showed increased connectivity strength between medulla oblongata (MO) and visual network (VN) /cerebellum network (CBN) and decreased connections were found between default mode network (DMN) and VN/CBN, subcortical cortex network (SCN) and CBN. In addition, PSP patients spend less fraction time and shorter dwell time in a diffused state, especially the MO and SCN. Finally, the fraction time and mean dwell time in the distributed connectivity state (state 2) is negatively correlated with duration, bulbar and oculomotor symptoms. Our findings were that the altered connectivity was mostly concentrated in the CBN and MO. In addition, PSP patients had different temporal dynamics, which were associated with bulbar and oculomotor symptoms in PSPRS. It suggest that variations in dynamic functional network connectivity properties may represent an essential neurological mechanism in PSP. • We investigated altered dynamic functional network connectivity in progressive supranuclear palsy. • Progressive supranuclear palsy may be related with the disruption of cerebellum network. • We observed medulla oblongata exhibited paradoxically enhanced connectivity with cerebellum network and visual network. • Progressive supranuclear palsy decreases medulla oblongata and subcortical cortex network state time. • The time index of dFNC relate to bulbar and oculomotor symptoms. [ABSTRACT FROM AUTHOR]

• Patients with KOA have altered static and dynamic functional network connectivity. • KOA have abnormal pain-related information processing of the default mode network, sensorimotor network, cognitive control network. • Although abnormalities in dFNCs of KOA patients have been found using the common window size, but the results were not robust. This study aimed to investigate altered static and dynamic functional network connectivity (FNC) and its correlation with clinical symptoms in patients with knee osteoarthritis (KOA). One hundred and fifty-nine patients with KOA and 73 age- and gender-matched healthy subjects (HS) underwent resting-state functional magnetic resonance imaging (rs-fMRI) and clinical evaluations. Group independent component analysis (GICA) was applied, and seven resting-state networks were identified. Patients with KOA had decreased static FNC within the default mode network (DM), visual network (VS), and cerebellar network (CB) and increased static FNC between the subcortical network (SC) and VS (p < 0.05, FDR corrected). Four reoccurring FNC states were identified using k -means clustering analysis. Although abnormalities in dynamic FNCs of KOA patients have been found using the common window size (22 TR, 44 s), but the results of the clustering analysis were inconsistent when using different window sizes, suggesting dynamic FNCs might be an unstable method to compare brain function between KOA patients and HS. These recent findings illustrate that patients with KOA have a wide range of abnormalities in the static and dynamic FNCs, which provided a reference for the identification of potential central nervous therapeutic targets for KOA treatment and might shed light on the other musculoskeletal pain neuroimaging studies. [ABSTRACT FROM AUTHOR]

• TP was lower in older adults with MCI compared with NHCs. • Lower TP in MCI was associated with higher sensitivity to probability of betrayal. • The strength of TP-related RSFC was decreased in MCI. • Negative CPM models with high SN contribution significantly predicted TP in MCI. • Positive CPM models with high DMN contribution significantly predicted TP in NHCs. Trust propensity (TP) relies more on social than economic rationality to transform the perceived probability of betrayal into positive reciprocity expectations in older adults with normal cognition. While deficits in social rationality have been observed in older adults with mild cognitive impairment (MCI), there is limited research on TP and its associated resting-state functional connectivity (RSFC) mechanisms in this population. To measure TP and related psychological functions (affect, motivation, executive cognition, and social cognition), MCI (n = 42) and normal healthy control (NHC, n = 115) groups completed a one-shot trust game and additional assessments of related psychological functions. RSFC associated with TP was analyzed using connectome-based predictive modeling (CPM) and lesion simulations. Our behavioral results showed that the MCI group trusted less (i.e., had lower TP) than the NHC group, with lower TP associated with higher sensitivity to the probability of betrayal in the MCI group. In the MCI group, only negative CPM models (RSFC negatively correlated with TP) significantly predicted TP, with a high salience network (SN) contribution. In contrast, in the NHC group, positive CPM models (RSFC positively correlated with TP) significantly predicted TP, with a high contribution from the default mode network (DMN). In addition, the total network strength of the NHC-specific positive network was lower in the MCI group than in the NHC group. Our findings demonstrated a decrease in TP in the MCI group compared to the NHC group, which is associated with deficits in social rationality (social cognition, associated with DMN) and increased sensitivity to betrayal (affect, associated with SN) in a trust dilemma. In conclusion, our study contributes to understanding MCI-related alterations in trust and their underlying neural mechanisms. [ABSTRACT FROM AUTHOR]

Olfactory dysfunction indicates a higher risk of developing dementia. However, the potential structural and functional changes are still largely unknown. A total of 236 participants were enrolled, including 45 Alzheimer's disease (AD) individuals and 191dementia-free individuals. Detailed study methods, comprising neuropsychological assessment and olfactory identification test (University of Pennsylvania smell identification test, UPSIT), as well as structural and functional magnetic resonance imaging (MRI) were applied in this research. The dementia-free individuals were divided into two sub-groups based on olfactory score: dementia-free with olfactory dysfunction (DF-OD) sub-group and dementia-free without olfactory dysfunction (DF-NOD) sub-group. The results were analyzed for subsequent intergroup comparisons and correlations. The cognitive assessment was conducted again three years later. (i) At dementia-free stage, there was a positive correlation between olfactory score and cognitive function. (ii) In dementia-free group, the volume of crucial brain structures involved in olfactory recognition and processing (such as amygdala, entorhinal cortex and basal forebrain volumes) are positively associated with olfactory score. (iii) Compared to the DF-NOD group, the DF-OD group showed a significant reduction in olfactory network (ON) function. (iv) Compared to DF-NOD group, there were significant functional connectivity (FC) decline between PCun_L(R)_4_1 in the precuneus of posterior default mode network (pDMN) and the salience network (SN) in DF-OD group, and the FC values decreased with falling olfactory scores. Moreover, in DF-OD group, the noteworthy reduction in FC were observed between PCun_L(R)_4_1 and amygdala, which was a crucial component of ON. (v) The AD conversion rate of DF-OD was 29.41%, while the DF-NOD group was 12.50%. The structural and functional changes in the precuneus were also observed in AD and were more severe. In addition to the olfactory circuit, the precuneus is a critical structure in the odor identification process, whose abnormal function underlies the olfactory identification impairment of dementia-free individuals. • The olfactory circuit is impaired in olfactory dysfunction among dementia-free. • Abnormal function of precuneus causes olfactory dysfunction in dementia-free. • The precuneus's structure and function also change in Alzheimer's disease. • Olfactory identification ability can be a clinical marker for Alzheimer's disease. [ABSTRACT FROM AUTHOR]

Exposure to childhood trauma (CT) is associated with cognitive impairment in schizophrenia, and deficits in social cognition in particular. Here, we sought to test whether IL-6 mediated the association between CT and social cognition both directly, and sequentially via altered default mode network (DMN) connectivity. Three-hundred-and-eleven participants (104 patients and 207 healthy participants) were included, with MRI data acquired in a subset of n = 147. CT was measured using the childhood trauma questionnaire (CTQ). IL-6 was measured in both plasma and in toll like receptor (TLR) stimulated whole blood. The CANTAB emotion recognition task (ERT) was administered to assess social cognition, and cortical connectivity was assessed based on resting DMN connectivity. Higher IL-6 levels, measured both in plasma and in toll-like receptor (TLR-2) stimulated blood, were significantly correlated with higher CTQ scores and lower cognitive and social cognitive function. Plasma IL-6 was further observed to partly mediate the association between higher CT scores and lower emotion recognition performance (CTQ total: β indirect −0.0234, 95% CI: −0.0573 to −0.0074; CTQ physical neglect: β indirect = −0.0316, 95% CI: −0.0741 to −0.0049). Finally, sequential mediation was observed between plasma IL-6 levels and DMN connectivity in mediating the effects of higher CTQ on lower social cognitive function (β indirect = −0.0618, 95% CI: −0.1523 to −0.285). This work suggests that previous associations between CT and social cognition may be partly mediated via an increased inflammatory response. IL-6′s association with changes in DMN activity further suggest at least one cortical network via which CT related effects on cognition may be transmitted. [ABSTRACT FROM AUTHOR]

• fMRI neurofeedback procedure is validated using counterbalanced active-sham design. • Left DLPFC fMRI activity was upregulated using neurofeedback during cognitive tasks. • The target activity was significantly higher for active than for sham neurofeedback. • Significant active-vs-sham connectivity changes occurred for major brain networks. • Counterbalanced active-sham design helps to elucidate neurofeedback mechanisms. Investigation of neural mechanisms of real-time functional MRI neurofeedback (rtfMRI-nf) training requires an efficient study control approach. A common rtfMRI-nf study design involves an experimental group, receiving active rtfMRI-nf, and a control group, provided with sham rtfMRI-nf. We report the first study in which rtfMRI-nf procedure is controlled through counterbalancing training runs with active and sham rtfMRI-nf for each participant. Healthy volunteers (n = 18) used rtfMRI-nf to upregulate fMRI activity of an individually defined target region in the left dorsolateral prefrontal cortex (DLPFC) while performing tasks that involved mental generation of a random numerical sequence and serial summation of numbers in the sequence. Sham rtfMRI-nf was provided based on fMRI activity of a different brain region, not involved in these tasks. The experimental procedure included two training runs with the active rtfMRI-nf and two runs with the sham rtfMRI-nf, in a randomized order. The participants achieved significantly higher fMRI activation of the left DLPFC target region during the active rtfMRI-nf conditions compared to the sham rtfMRI-nf conditions. fMRI functional connectivity of the left DLPFC target region with the nodes of the central executive network was significantly enhanced during the active rtfMRI-nf conditions relative to the sham conditions. fMRI connectivity of the target region with the nodes of the default mode network was similarly enhanced. fMRI connectivity changes between the active and sham conditions exhibited meaningful associations with individual performance measures on the Working Memory Multimodal Attention Task, the Approach-Avoidance Task, and the Trail Making Test. Our results demonstrate that the counterbalanced active-sham study design can be efficiently used to investigate mechanisms of active rtfMRI-nf in direct comparison to those of sham rtfMRI-nf. Further studies with larger group sizes are needed to confirm the reported findings and evaluate clinical utility of this study control approach. [ABSTRACT FROM AUTHOR]

• A decomposed convolutional neural network model was established based on rs-fMRI connectivity. • The model paired with the Dos_160 atlas can be effectively applied to the diagnosis of tinnitus. • This study pinpointed key brain regions for subjective tinnitus using a data-driven approach. Many studies have investigated aberrant functional connectivity (FC) using resting-state functional MRI (rs-fMRI) in subjective tinnitus patients. However, no studies have verified the efficacy of resting-state FC as a diagnostic imaging marker. We established a convolutional neural network (CNN) model based on rs-fMRI FC to distinguish tinnitus patients from healthy controls, providing guidance and fast diagnostic tools for the clinical diagnosis of subjective tinnitus. A CNN architecture was trained on rs-fMRI data from 100 tinnitus patients and 100 healthy controls using an asymmetric convolutional layer. Additionally, a traditional machine learning model and a transfer learning model were included for comparison with the CNN, and each of the three models was tested on three different brain atlases. Of the three models, the CNN model outperformed the other two models with the highest area under the curve, especially on the Dos_160 atlas (AUC = 0.944). Meanwhile, the model with the best classification performance highlights the crucial role of the default mode network, salience network, and sensorimotor network in distinguishing between normal controls and patients with subjective tinnitus. Our CNN model could appropriately tackle the diagnosis of tinnitus patients using rs-fMRI and confirmed the diagnostic value of FC as measured by rs-fMRI. [ABSTRACT FROM AUTHOR]

· Healthy aging is associated to increased risk of cognitive decline. · Resting state DMN functional connectivity is considerably affected by aging. · We used computational modeling to investigate DMN effective connectivity. · Effective connectivity in temporal and posterior DMN hubs was reduced. · Lifetime attained education reversed these changes, indicating cognitive reserve. Aging is a major risk factor for neurodegenerative diseases like dementia and Alzheimer's disease. Even in non-pathological aging, decline in cognitive functioning is observed in the majority of the elderly population, necessitating the importance of studying the processes involved in healthy aging in order to identify brain biomarkers that promote the conservation of functioning. The default mode network (DMN) has been of special interest to aging research due to its vulnerability to atrophy and functional decline over the course of aging. Prior work has focused almost exclusively on functional (i.e. undirected) connectivity, yet converging findings are scarce. Therefore, we set out to use spectral dynamic causal modeling to investigate changes in the effective (i.e. directed) connectivity within the DMN and to discover changes in information flow in a sample of cognitively normal adults spanning from 48 to 89 years (n = 63). Age was associated to reduced verbal memory performance. Modeling of effective connectivity revealed a pattern of age-related downregulation of posterior DMN regions driven by inhibitory connections from the hippocampus and middle temporal gyrus. Additionally, there was an observed decline in the hippocampus' susceptibility to network inputs with age, effectively disconnecting itself from other regions. The estimated effective connectivity parameters were robust and able to predict the age in out of sample estimates in a leave-one-out cross-validation. Attained education moderated the effects of aging, largely reversing the observed pattern of inhibitory connectivity. Thus, medial prefrontal cortex, hippocampus and posterior DMN regions formed an excitatory cycle of extrinsic connections related to the interaction of age and education. This suggests a compensatory role of years of education in effective connectivity, stressing a possible target for interventions. Our findings suggest a connection to the concept of cognitive reserve, which attributes a protective effect of educational level on cognitive decline in aging (Stern, 2009). [ABSTRACT FROM AUTHOR]

Epilepsy is a chronic neurologic disorder characterized by abnormal functioning of brain networks, making it a complex research topic. Recent advancements in neuroimaging technology offer an effective approach to unraveling the intricacies of the human brain. Within different types of epilepsy, there is growing recognition regarding ongoing changes in the default mode network (DMN). However, little is known about the shared and distinct alterations of static functional connectivity (sFC) and dynamic functional connectivity (dFC) in DMN among epileptic subtypes, especially in children with epilepsy. Here, 110 children with epilepsy at a single center, including idiopathic generalized epilepsy (IGE), frontal lobe epilepsy (FLE), temporal lobe epilepsy (TLE), and parietal lobe epilepsy (PLE), as well as 84 healthy controls (HC) underwent resting-state functional magnetic resonance imaging (fMRI) scan. We investigated both sFC and dFC between groups of the DMN. Decreased static and dynamic connectivity within the DMN subsystem were shared by all subtypes. In each epilepsy subtype, children with epilepsy displayed significant and distinct patterns of DMN connectivity compared to the control group: the IGE group showed reduced interhemispheric connectivity, the FLE group consistently demonstrated disturbances in frontal region connectivity, the TLE group exhibited significant disruptions in hippocampal connectivity, and the PLE group displayed a notable decrease in parietal-temporal connectivity within the DMN. Some state-specific FC disruptions (decreased dFC) were observed in each epilepsy subtype that cannot detect by sFC. To determine their uniqueness within specific subtypes, bootstrapping methods were employed and found the significant results (IGE: between PCC and bilateral precuneus, FLE: between right middle frontal gyrus and bilateral middle temporal gyrus, TLE: between left Hippocampus and right fusiform, PLE: between left angular and cingulate cortex). Furthermore, only children with IGE exhibited dynamic features associated with clinical variables. Our findings highlight both shared and distinct FC alterations within the DMN in children with different types of epilepsy. Furthermore, our work provides a novel perspective on the functional alterations in the DMN of pediatric patients, suggesting that combined sFC and dFC analysis can provide valuable insights for deepening our understanding of the neuronal mechanism underlying epilepsy in children. • Decreased static and dynamic connectivity within the DMN subsystem were shared by all children with epilepsy • State-specific FC disruptions were observed in each patient group that were not detected by state FC • Epilepsy children in each subtype also showed unique connectivity patterns of the DMN that reflect their epilepsy types • The findings of static and dynamic functional abnormalities in DMN confirmed the essential role of DMN in children with epilepsy [ABSTRACT FROM AUTHOR]

• Selfhood consists of pre-reflective and reflective self-experience and is essential to human consciousness. • Event-related potentials of pre-reflective and reflective self-experience can be differentiated at around 300 ms post-stimulus onset with an EEG-based lexical task. • Both self-experience components involve areas in the default mode network and in the cortical midline structures. • Pre-reflective self-experience also involves the right medial prefrontal cortex and areas of the bottom-up ventral attention network. • The findings enhance our understanding of the distinct components of self-experience and are promising for clinical applications in diagnosing and treating self-disorders. The neural underpinnings of selfhood encompass pre-reflective and reflective self-experience. The former refers to a basic, immediate experience of being a self, while the latter involves cognition and introspection. Although neural correlates of reflective self-experience have been studied, the pre-reflective remains underinvestigated. This research aims to bridge this gap by comparatively investigating ERP correlates of reading first- vs. third-person pronouns – approximating pre-reflective self-experience – and self- vs. other-related adjectives – approximating reflective self-experience – in 30 healthy participants. We found differential neural engagement between pre-reflective and reflective self-experience at 254–310 ms post-stimulus onset. Source estimation suggested that our sensor-level results could be plausibly explained by the involvement of cortical midline structures and default mode network in the general sense of self but selective recruitment of anterior cingulate and top-down dorsal attention network in the pre-reflective self. These findings offer a deeper understanding of the experiential self, especially pre-reflective, providing a foundation for investigating self-disorders. [ABSTRACT FROM AUTHOR]

• We examined the neural correlates of 6 semantic dimensions in narrative processing. • Specific and overlapping neural correlates for different dimensions were identified. • Specific areas were found both outside and inside the general semantic network. • Overlapping areas were found mainly in the default mode network. • Left anterior superior temporal gyrus and angular gyrus were found as hub areas. Multiple sensory-motor and non-sensory-motor dimensions have been proposed for semantic representation, but it remains unclear how the semantic system is organized along them in the human brain. Using naturalistic fMRI data and large-scale semantic ratings, we investigated the overlaps and dissociations between the neural correlates of six semantic dimensions: vision, motor, socialness, emotion, space, and time. Our findings revealed a more complex semantic atlas than what is predicted by current neurobiological models of semantic representation. Brain regions that are selectively sensitive to specific semantic dimensions were found both within and outside the brain networks assumed to represent multimodal general and/or abstract semantics. Overlaps between the neural correlates of different semantic dimensions were mainly found inside the default mode network, concentrated in the left anterior superior temporal gyrus and angular gyrus, which have been proposed as two connector hubs that bridge the multimodal experiential semantic system and the language-supported semantic system. [ABSTRACT FROM AUTHOR]

The theory of mental gravity posits that phenomenological, cognitive, and affective states of an embodied self are structured according to the experience of physical gravity (i.e., internal gravity model). The theory draws a behavioral analogy between external (physical), internal (mental), and relational (socio-emotional) environments to argue that physical gravity serves as a mental template to express socio-emotional aspects of the self-world relationship. The theory is based on the principle of cognitive gravitropism, whereby being "up" and "aligned" to the gravitational field confers survival, adaptive, emotional, and social value. The theory explains how mental gravity manifests in cognition and behavior, emotion and personality, large-scale brain networks, and the phenomenology of selfhood. On a surface level, the template for mental gravity derives from an embodied simulation of gravity's physiological effects. At a deeper level, the theory describes the underlying neural, cognitive, and phenomenological processes driving the mental simulation of physical gravity. Neuroanatomy of mental gravity focuses on the vestibular, salience, default mode, and central executive networks. On the basis of default mode activity, the self is viewed as the brain's autobiographical "centre of mental gravity". The self interacts with the socio-emotional environment from this reference frame, communicating feelings associated with the self-world relationship by simulating the effects of physical gravity through affect, behavior, and language. A continuum of mental gravity states is hypothesised to range from positive "up" and "down" states like ecstasy and mindfulness to negative "up" and "down" states like anxiety and depression, respectively. • Mental gravity draws parallels between physical, mental, and socio-emotional environments. • A simulated internal gravity model structures the embodied and narrative sense of self. • Being "up" and "aligned" to the gravitational field confers verticality value. • A continuum of mental gravity ranges across positive and negative affective states. • Neuroanatomy focuses on vestibular, salience, and default mode networks. [ABSTRACT FROM AUTHOR]

• To better preserve the integrity of the spatio-temporal features of 4D Rs-fMRI, we corrected the deviation information learned by the attention mechanism. The proposed shallow attention feature enrichment module in this study enhances the capacity to concentrate on and characterize the detailed features of 4D fMRI and can provide guidance for subsequent temporal feature extraction. • We dexterously use spatiotemporal fusion information, original temporal information, and feature extracted temporal information as the input of the temporal multi-head attention block. This operation not only enriches the temporal features and reduces the risk of overfitting but also achieves feature learning constraints for spatial pattern modeling. • To our knowledge, this is one of the earliest studies to personally model the spatio-temporal feature patterns of abnormal brain DMN in EMCI patients and correlate this methodology with clinical research. This study is expected to provide a framework and approach for the characterization and construction of abnormal brain DMNs in the future. Designing a comprehensive four-dimensional resting-state functional magnetic resonance imaging (4D Rs-fMRI) based default mode network (DMN) modeling methodology to reveal the spatio-temporal patterns of individual DMN, is crucial for understanding the cognitive mechanisms of the brain and the pathogenesis of psychiatric disorders. However, there are still two limitations of existing approaches for DMN modeling. The approaches either (1) simply split the spatio-temporal components and ignore the overall character of the spatio-temporal patterns or (2) are biased in the process of feature extraction for DMN modeling, and their spatio-temporal accuracy is thus not warranted. To this end, we propose a novel Spatio-Temporal Brain Attention Skip Network (STBAS-Net) to model the personalized spatio-temporal patterns of the DMN. STBAS-Net consists of spatial and temporal components, where the multi-head attention skip connection block in the spatial component achieves detailed feature extraction and enhancement in the shallow stage. Under the guidance of spatial information, we technically fuse multiple spatio-temporal information in the temporal component, which dexterously exploits the overall spatio-temporal features and achieves mutual constraints of spatio-temporal patterns to characterize the spatio-temporal patterns of the DMN. We verify the proposed STBAS-Net on a publicly released 4D Rs-fMRI dataset and an EMCI dataset. The experimental results show that compared with existing advanced methods, the proposed network can more accurately model the personalized spatio-temporal patterns of the human brain DMN and successfully identify abnormal spatio-temporal patterns in EMCI patients. This study provides a potential tool for revealing the spatio-temporal patterns of the human brain DMN and is expected to provide an effective methodological framework for future exploration of abnormal brain spatio-temporal patterns and modeling of other functional brain networks. [ABSTRACT FROM AUTHOR]

• Probabilistic fiber tracking and functional connectivity (FC) analysis were performed to investigate brain network changes in epilepsy. • The left precuneus volumes in epilepsy groups were lower than that in healthy controls. • Temporal lobe epilepsy (TLE) patients and frontal lobe epilepsy (FLE) patients showed structural and functional changes in the DMN. • Compared with FLE patients, TLE patients showed reduced structural and functional connection strengths between the left hippocampus and precuneus. • We provided new insights into the underlying pathological changes in TLE patients. To investigate brain network properties and connectivity abnormalities of the default mode network (DMN) in drug-resistant epilepsy (DRE). The study was based on probabilistic fiber tracking and functional connectivity (FC) analysis, to explore the structural and functional connectivity patterns change between frontal lobe epilepsy (FLE) and temporal lobe epilepsy (TLE). A total of 33 DRE patients (18 TLE and 15 FLE) and 30 healthy controls (HCs) were recruited. The volume fraction of the septal brain region of the DMN in DRE was calculated using FreeSurfer. The FC analysis was performed using Data Processing and Analysis for Brain Imaging in MATLAB. The structural connections between brain regions of the DMN were calculated based on probabilistic fiber tracking. The left precuneus (PCUN) volumes in epilepsy groups were lower than that in HCs. Compared with FLE, TLE showed reduced FC between the left hippocampus (HIP) and PCUN/medial frontal gyrus, and between the right inferior parietal lobule (IPL) and right superior temporal gyrus. Compared with HCs, FLE showed increased FCs between the right IPL and occipital lobe, and between the left superior frontal gyrus (SFG) and bilateral superior temporal gyrus. In terms of structural connectivity, TLE exhibited increased connectivity strength between the left SFG and left PCUN, and showed reduced connection strength between the left HIP and left posterior cingulate gyrus/left PCUN, when compared with the FLE. TLE and FLE patients showed structural and functional changes in the DMN. Compared with FLE patients, the TLE patients showed reduced structural and functional connection strengths between the left HIP and PCUN. These alterations in connection strengths holds promise for the identification of TLE and FLE. [ABSTRACT FROM AUTHOR]

• Little is known about how the gut microbiome contributes to early development. • We investigated the link between gut microbiome, brain, and behavior. • Microbiota composition was a associated with brain network connectivity. • This points to the remarkably early influence of the gut microbiome. The gut microbiome appears to play an important role in human health and disease. However, only little is known about how variability in the gut microbiome contributes to individual differences during early and sensitive stages of brain and behavioral development. The current study examined the link between gut microbiome, brain, and behavior in newborn infants (N = 63; M [age] = 25 days). Infant gut microbiome diversity was measured from stool samples using metagenomic sequencing, infant functional brain network connectivity was assessed using a resting state functional near infrared spectroscopy (rs-fNIRS) procedure, and infant behavioral temperament was assessed using parental report. Our results show that gut microbiota composition is linked to individual variability in brain network connectivity, which in turn mediated individual differences in behavioral temperament, specifically negative emotionality, among infants. Furthermore, virulence factors, possibly indexing pathogenic activity, were associated with differences in brain network connectivity linked to negative emotionality. These findings provide novel insights into the early developmental origins of the gut microbiome-brain axis and its association with variability in important behavioral traits. This suggests that the gut microbiome is an important biological factor to consider when studying human development and health. [ABSTRACT FROM AUTHOR]

• Inflammation is associated with brain functional connectivity in older adults. • Inflammation linked to lower default mode and dorsal attention network connectivity. • Association of inflammation with functional connectivity magnified by APOE ε4. • Brain β-amyloid did not modify the inflammation-functional connectivity association. Systemic inflammation has emerged as a risk factor for cognitive decline and Alzheimer's disease, but inflammation's effect on distributed brain networks is unclear. We examined the relationship between peripheral inflammatory markers and subsequent functional connectivity within five large-scale cognitive networks and evaluated the modifying role of cortical amyloid and APOE ε4 status. Blood levels of soluble tumor necrosis factor-alpha receptor-1 and interleukin 6 were assessed in 176 participants (at baseline mean age: 65 (SD 9) years; 63% women; 85% cognitively normal, 15% mild cognitive impairment (MCI)) and were combined to derive an Inflammatory Index. Approximately six years later, participants underwent resting-state functional magnetic resonance imaging to quantify functional connectivity; a subset of 137 participants also underwent 11C Pittsburgh compound-B (PiB) PET imaging to assess cortical amyloid burden. Using linear regression models adjusted for demographic characteristics and cardiovascular risk factors, a higher Inflammatory Index was associated with lower connectivity within the Default Mode (β = −0.013; 95% CI: −0.023, −0.003) and the Dorsal Attention Networks (β = −0.017; 95% CI: −0.028, −0.006). The strength of these associations did not vary by amyloid status (positive/negative). However, there was a significant interaction between Inflammatory Index and APOE ε4 status, whereby ε4-positive participants with a higher Inflammatory Index demonstrated lower connectivity. Inflammatory Index was unrelated to connectivity within other large-scale cognitive networks (Control, Limbic, and Salience/Ventral Attention networks). Peripheral pro-inflammatory signaling in older adults without dementia, especially among APOE ε4-positive individuals, is associated with altered connectivity within two large-scale cognitive networks. [ABSTRACT FROM AUTHOR]

• We studied structure-function coupling in autism using a Riemannian optimization. • Higher coupling was observed when polysynaptic mechanisms were accounted for. • Compensation was lower in autism, particularly in transmodal association systems. • Structure-function differences in autism reflected autistic symptoms intelligence. Autism spectrum disorder (ASD) is one of the most common neurodevelopmental diagnoses. Although incompletely understood, structural and functional network alterations are increasingly recognized to be at the core of the condition. We utilized multimodal imaging and connectivity modeling to study structure-function coupling in ASD and probed mono- and polysynaptic mechanisms on structurally-governed network function. We examined multimodal magnetic resonance imaging data in 80 ASD and 61 neurotypical controls from the Autism Brain Imaging Data Exchange (ABIDE) II initiative. We predicted intrinsic functional connectivity from structural connectivity data in each participant using a Riemannian optimization procedure that varies the times that simulated signals can unfold along tractography-derived personalized connectomes. In both ASD and neurotypical controls, we observed improved structure-function prediction at longer diffusion time scales, indicating better modeling of brain function when polysynaptic mechanisms are accounted for. Prediction accuracy differences (∆prediction accuracy) were marked in transmodal association systems, such as the default mode network, in both neurotypical controls and ASD. Differences were, however, lower in ASD in a polysynaptic regime at higher simulated diffusion times. We compared regional differences in ∆prediction accuracy between both groups to assess the impact of polysynaptic communication on structure-function coupling. This analysis revealed that between-group differences in ∆prediction accuracy followed a sensory-to-transmodal cortical hierarchy, with an increased gap between controls and ASD in transmodal compared to sensory/motor systems. Multivariate associative techniques revealed that structure-function differences reflected inter-individual differences in autistic symptoms and verbal as well as non-verbal intelligence. Our network modeling approach sheds light on atypical structure-function coupling in autism, and suggests that polysynaptic network mechanisms are implicated in the condition and that these can help explain its wide range of associated symptoms. [ABSTRACT FROM AUTHOR]

• Precuneus may play a crucial role in the interactions of various brain functions. • Sleep deprivation will weaken negative precuneus-related functional connectivity. • Weakened precuneus-related function may lead to a decline in cognitive performance. Intra-individual variability (IIV) in cognitive performance is thought to reflect the efficiency with which attentional resources are allocated in different circumstances requiring cognitive control. IIV in cognitive performance is associated with the strength of the negative correlation between task-positive network and default mode network (DMN) activity. In this study, we investigated the impact of sleep deprivation (SD) on functional connectivity (FC) between the DMN and psychomotor vigilance task-related network (PVT-RN), and its relationship with IIV in cognitive performance. Two analyses, network-level independent component analysis (NL-ICA) and region-level (RL)-ICA, were employed to compare the coefficient of variation (CV) of the PVT between normal sleep and SD conditions across 67 healthy participants. After SD, in NL-ICA, the FC between the PVT-RN and DMN was positively correlated with the CV of the PVT, as well as the changes therein, compared with normal sleep. Using a mask derived from the DMN and PVT-RN, the RL-ICA revealed that 12 edges/connections between DMN and PVT independent components were associated with the CV of the PVT, with nine of these connections involving the precuneus. These findings suggest that the precuneus may play a crucial role in the interactions of various brain functions during the PVT, with the connections between the precuneus and frontoparietal and somatosensory networks being significantly altered after SD. Moreover, following SD, weakened negative FC between the precuneus and bilateral inferior parietal lobule may disrupt the balance between cognitive and executive control functions, leading to a decline in cognitive performance. [ABSTRACT FROM AUTHOR]

• Frequency-specific brain activities within the sensorimotor network (SMN), visual network (VN), and default mode network (DMN) that were associated with the varying degrees of symptom severity in DCM patients. • Frequency-specific brain activity within the SMN correlated with functional recovery in DCM patients. • A spatial correlation between the brain-wide expression of genes involved in neuronal migration and the brain functional activity pattern was discovered and associated with symptom severity in DCM patients. Neuroimaging techniques provide insights into the brain abnormalities secondary to degenerative cervical myelopathy (DCM) and their association with neurological deficits. However, the neural correlates underlying the discrepancy between symptom severity and the degree of spinal cord compression, as well as the transcriptional correlates of these cortical abnormalities, remain unknown in DCM patients. In this cross-sectional study, which collected resting-state functional MRI (rs-fMRI) images and the Japanese Orthopedic Association (JOA) score, enrolled 104 participants (54 patients and 50 healthy controls). The frequency-dependent amplitude of low-frequency fluctuation (ALFF) was obtained for all participants. We investigated the ALFF differences between mild-symptom DCM patients and severe-symptom DCM patients while carefully matching the degree of compression between these two groups via both univariate comparison and searchlight classification for three frequency bands (e.g., Slow-4, Slow-5, and Full-band). Additionally, we identified genes associated with symptom severity in DCM patients by linking the spatial patterns of gene expression of Allen Human Brain Atlas and brain functional differences between mild symptom and severe symptom groups. (1) We found that the frequency-specific brain activities within the sensorimotor network (SMN), visual network (VN), and default mode network (DMN) were associated with the varying degrees of functional impairment in DCM patients; (2) the frequency-specific brain activity within the SMN correlated with the functional recovery in patients with DCM; (3) a spatial correlation between the brain-wide expression of genes involved in neuronal migration and the brain functional activities associated with symptom severity was identified in DCM patients. In conclusion, our study bridges gaps between genes, cell classes, biological processes, and brain functional correlates of DCM. While our findings are correlational in nature, they suggest that the neural activities of sensorimotor cortices in DCM are associated with the severity of symptoms and might be associated with neuronal migration within the brain. [ABSTRACT FROM AUTHOR]

• DKI is feasible for SCN construction with improved classification performance. • SCN and FCN in PD were topologically impaired at levels of global, nodal and modular. • Patients with PD exhibited SCN-FCN decoupling across scales. • SCN-FCN coupling in PD was constrained by corresponding microstructural alterations. Parkinson's disease (PD) is manifested with disrupted topology of the structural connection network (SCN) and the functional connection network (FCN). However, the SCN and its interactions with the FCN remain to be further investigated. This multimodality study attempted to precisely characterize the SCN using diffusion kurtosis imaging (DKI) and further identify the neuropathological pattern of SCN-FCN decoupling, underscoring the neurodegeneration of PD. Diffusion-weighted imaging and resting-state functional imaging were available for network constructions among sixty-nine patients with PD and seventy demographically matched healthy control (HC) participants. The classification performance and topological prosperities of both the SCN and the FCN were analyzed, followed by quantification of the SCN-FCN couplings across scales. The SCN constructed by kurtosis metrics achieved optimal classification performance (area under the curve 0.89, accuracy 80.55 %, sensitivity 78.40 %, and specificity 80.65 %). Along with diverse alterations of structural and functional network topology, the PD group exhibited decoupling across scales including: reduced global coupling; increased nodal coupling within the sensorimotor network (SMN) and subcortical network (SN); higher intramodular coupling within the SMN and SN and lower intramodular coupling of the default mode network (DMN); decreased coupling between the modules of DMN-fronto-parietal network and DMN-visual network, but increased coupling between the SMN-SN module. Several associations between the coupling coefficient and topological properties of the SCN, as well as between network values and clinical scores, were observed. These findings validated the clinical implementation of DKI for structural network construction with better differentiation ability and characterized the SCN-FCN decoupling as supplementary insight into the pathological process underlying PD. [ABSTRACT FROM AUTHOR]

Cognitive control (CC) is essential for problem-solving in everyday life, and CC-related deficits occur alongside costly and debilitating disorders. The tri-partite model suggests that CC comprises multiple behaviors, including switching, inhibiting, and updating. Activity within the fronto-parietal control network B (FPCN-B), the dorsal attention network (DAN), the cingulo-opercular network (CON), and the lateral default-mode network (L-DMN) is related to switching and inhibiting behaviors. However, our understanding of how these brain regions interact to bring about cognitive switching and inhibiting in individuals is unclear. In the current study, subjects performed two in-scanner tasks that required switching and inhibiting. We used support vector regression (SVR) models containing individually-estimated functional connectivity between the FPCN-B, DAN, CON and L-DMN to predict switching and inhibiting behaviors. We observed that: inter-network connectivity can predict inhibiting and switching behaviors in individuals, and the L-DMN plays a role in switching and inhibiting behaviors. Therefore, individually estimated inter-network connections are markers of CC behaviors, and CC behaviors may arise due to interactions between a set of networks. • Cognitive control is essential for completing everyday activities. • Previous work suggests multiple functional brain networks are associated with executing cognitive control behaviors. • We used the interactions between multiple individually estimated functional brain networks to predict cognitive switching and inhibiting behaviors. • Our results suggest that the dynamics between functional brain networks are essential for cognitive control behaviors. [ABSTRACT FROM AUTHOR]

Cases with the limbic-predominant age-related TAR DNA-binding protein 43 (TDP-43) encephalopathy neuropathologic change (LATE-NC), Alzheimer's disease (AD), and mixed AD+TDP-43 pathology (AD+LATE-NC) share similar symptoms, which makes it a challenge for accurate diagnosis. Exploring the patterns of gray matter structural covariance networks (SCNs) in these three types may help to clarify the underlying mechanism and provide a basis for clinical interventions. We included ante-mortem MRI data of 10 LATE-NC, 39 AD, and 25 AD+LATE-NC from the ADNI autopsy sample. We used four regions of interest (left posterior cingulate cortex, right entorhinal cortex, frontoinsular and dorsolateral prefrontal cortex) to anchor the default mode network (DMN), salience network (SN), and executive control network (ECN). Finally, we assessed the SCN alternations using a multi-regression model-based linear-interaction analysis. Cases with autopsy-confirmed LATE-NC and AD showed increased structural associations involving DMN, ECN, and SN. Cases with AD+LATE-NC showed increased structural association within DMN while decreased structural association between DMN and ECN. The volume of peak clusters showed significant associations with cognition and AD pathology. This study showed different SCN patterns in the cases with LATE-NC, AD, and AD+LATE-NC, and indicated the network disconnection mechanism underlying these three neuropathological progressions. Further, SCN may serve as an effective biomarker to distinguish between different types of dementia. • This study showed different SCN patterns in the cases with LATE-NC, AD, and AD+LATE-NC. • These SCNs changes were related to specific pathological distribution and can help to illuminate the cognitive changes. • This study indicated the network disconnection mechanism underlying these three neuropathological progressions [ABSTRACT FROM AUTHOR]

Research suggests that social support has a protective effect on emotional health and emotionally induced overeating. Women are especially more sensitive to benefits from social support when facing eating problems. Although it has been demonstrated that social support can affect the neural processes of emotion regulation and reward perception, it is unclear how social support alters synergistic patterns in large-scale brain networks associated with negative emotions and overeating. We used a large sample of young women aged 17–22 years (N = 360) to examine how social support influences the synchrony of five intrinsic networks (executive control network [ECN], default mode network, salience network [SN], basal ganglia network, and precuneus network [PN]) and how these networks influence negative affect and overeating. Additionally, we explored these analyses in another sample of males (N = 136). After statistically controlling for differences in age and head movement, we observed significant associations of higher levels of social support with increased intra- and inter-network functional synchrony, particularly for ECN-centered network connectivity. Subsequent chain-mediated analyses showed that social support predicted overeating through the ECN−SN and ECN−PN network connectivity and negative emotions. However, these results were not found in men. These findings suggest that social support influences the synergistic patterns within and between intrinsic networks related to inhibitory control, emotion salience, self-referential thinking, and reward sensitivity. Furthermore, they reveal that social support and its neural markers may play a key role in young women's emotional health and eating behavior. [ABSTRACT FROM AUTHOR]

[Display omitted] • JAE patients had altered striatal-related functional network dynamics. • The striatal-subcortical networks showed decreased dFC variability in JAE. • The stability of striatal-thalamic circuit was increased with epilepsy duration. • JAE patients showed stable affective circuit but variable executive circuit. • The default mode network was involved in altered striatal-cortical networks in JAE. To explore the features of dynamic functional connectivity (dFC) variability of striatal-cortical/subcortical networks in juvenile absence epilepsy (JAE). We collected resting-state functional magnetic imaging data from 18 JAE patients and 28 healthy controls. The striatum was divided into six pairs of regions: the inferior-ventral striatum (VSi), superior-ventral striatum (VSs), dorsal-caudal putamen, dorsal-rostral putamen, dorsal-caudate (DC) and ventral-rostral putamen. We assessed the dFC variability of each subdivision in the whole brain using the sliding-window method, and correlated altered circuit with clinical variables in JAE patients. We found altered dFC variability of striatal-cortical/subcortical networks in patients with JAE. The VSs exhibited decreased dFC variability with subcortical regions, and dFC variability between VSs and thalamus was negatively correlated with epilepsy duration. For the striatal-cortical networks, the dFC variability was decreased in VSi-affective network but increased in DC-executive network. The altered dynamics of striatal-cortical networks involved crucial nodes of the default mode network (DMN). JAE patients exhibit excessive stability in the striatal-subcortical networks. For striatal-cortical networks in JAE, the striatal-affective circuit was more stable, while the striatal-executive circuit was more variable. Furthermore, crucial nodes of DMN were changed in striatal-cortical networks in JAE. [ABSTRACT FROM AUTHOR]

• A functional ultrasound imaging in an fMRI-like environment with acoustic noise. • Positive rCBV response in auditory cortex and negative response in motor cortex. • Greater acoustic noise reduces functional connectivity in auditory and motor networks. • Functional connectivity by rsfUS under acoustic noise is similar to that by rsfMRI. Loud acoustic noise from the scanner during functional magnetic resonance imaging (fMRI) can affect functional connectivity (FC) observed in the resting state, but the exact effect of the MRI acoustic noise on resting state FC is not well understood. Functional ultrasound (fUS) is a neuroimaging method that visualizes brain activity based on relative cerebral blood volume (rCBV), a similar neurovascular coupling response to that measured by fMRI, but without the audible acoustic noise. In this study, we investigated the effects of different acoustic noise levels (silent, 80 dB, and 110 dB) on FC by measuring resting state fUS (rsfUS) in awake mice in an environment similar to fMRI measurement. Then, we compared the results to those of resting state fMRI (rsfMRI) conducted using an 11.7 Tesla scanner. RsfUS experiments revealed a significant reduction in FC between the retrosplenial dysgranular and auditory cortexes (0.56 ± 0.07 at silence vs 0.05 ± 0.05 at 110 dB, p =.01) and a significant increase in FC anticorrelation between the infralimbic and motor cortexes (−0.21 ± 0.08 at silence vs −0.47 ± 0.04 at 110 dB, p =.017) as acoustic noise increased from silence to 80 dB and 110 dB, with increased consistency of FC patterns between rsfUS and rsfMRI being found with the louder noise conditions. Event-related auditory stimulation experiments using fUS showed strong positive rCBV changes (16.5% ± 2.9% at 110 dB) in the auditory cortex, and negative rCBV changes (−6.7% ± 0.8% at 110 dB) in the motor cortex, both being constituents of the brain network that was altered by the presence of acoustic noise in the resting state experiments. Anticorrelation between constituent brain regions of the default mode network (such as the infralimbic cortex) and those of task-positive sensorimotor networks (such as the motor cortex) is known to be an important feature of brain network antagonism, and has been studied as a biological marker of brain disfunction and disease. This study suggests that attention should be paid to the acoustic noise level when using rsfMRI to evaluate the anticorrelation between the default mode network and task-positive sensorimotor network. [ABSTRACT FROM AUTHOR]

• Preserved intrinsic network connectivity underlies cognitive reserve in bilingualism. • Lower gray matter integrity in bilinguals than cognitively matched monolinguals. • gray matter integrity correlated with cognition in monolinguals, but not bilinguals. • Lower default-executive coupling in bilinguals than cognitively matched monolinguals. • Second language proficiency correlated with intrinsic functional network integrity. Cognitive Reserve (CR) refers to the preservation of cognitive function in the face of age- or disease-related neuroanatomical decline. While bilingualism has been shown to contribute to CR, the extent to which, and what particular aspect of, second language experience contributes to CR are debated, and the underlying neural mechanism(s) unknown. Intrinsic functional connectivity reflects experience-dependent neuroplasticity that occurs across timescales ranging from minutes to decades, and may be a neural mechanism underlying CR. To test this hypothesis, we used voxel-based morphometry and resting-state functional connectivity analyses of MRI data to compare structural and functional brain integrity between monolingual and bilingual older adults, matched on cognitive performance, and across levels of second language proficiency measured as a continuous variable. Bilingualism, and degree of second language proficiency specifically, were associated with lower gray matter integrity in a hub of the default mode network – a region that is particularly vulnerable to decline in aging and dementia – but preserved intrinsic functional network organization. Bilingualism moderated the association between neuroanatomical differences and cognitive decline, such that lower gray matter integrity was associated with lower executive function in monolinguals, but not bilinguals. Intrinsic functional network integrity predicted executive function when controlling for group differences in gray matter integrity and language status. Our findings confirm that lifelong bilingualism is a CR factor, as bilingual older adults performed just as well as their monolingual peers on tasks of executive function, despite showing signs of more advanced neuroanatomical aging, and that this is a consequence of preserved intrinsic functional network organization. [ABSTRACT FROM AUTHOR]

Electrophysiological studies revealed that different neuronal oscillations, among which the alpha (8-13 Hz) rhythm in particular, but also the beta (13-30 Hz) and gamma (30-80 Hz) rhythms, are modulated during rest in the default mode network (DMN). Little is known, however, about the role of these rhythms in supporting DMN connectivity. Biophysical studies suggest that lower and higher frequencies mediate long- and short-range connectivity, respectively. Accordingly, we hypothesized that interactions between all DMN areas are supported by the alpha rhythm, and that the connectivity between specific DMN areas is established through other frequencies, mainly in the beta and/or gamma bands. To test this hypothesis, we used high-density electroencefalographic data collected in 19 healthy volunteers at rest. We analyzed frequency-dependent functional interactions between four main DMN nodes in a broad (1-80 Hz) frequency range. In line with our hypothesis, we found that the frequency-dependent connectivity profile between pairs of DMN nodes had a peak at 9-11 Hz. Also, the connectivity profile showed other peaks at higher frequencies, which depended on the specific connection. Overall, our findings suggest that frequency-dependent connectivity analysis may be a powerful tool to better understand how different neuronal oscillations support connectivity within and between brain networks. • We studied functional connectivity in the DMN using high-density EEG data. • We found seed-based connectivity to be dependent on the frequency being considered. • Long-range communication within the DMN is mediated by neural activity in the alpha band. • Selective communication between pairs of nodes primarily occurs at higher frequencies. [ABSTRACT FROM AUTHOR]

Type 2 diabetes mellitus (T2DM) is a significant risk factor for mild cognitive impairment (MCI) and the acceleration of MCI to dementia. The high glucose level induce disturbance of neurovascular (NV) coupling is suggested to be one potential mechanism, however, the neuroimaging evidence is still lacking. To assess the NV decoupling pattern in early diabetic status, 33 T2DM without MCI patients and 33 healthy control subjects were prospectively enrolled. Then, they underwent resting state functional MRI and arterial spin labeling imaging to explore the hub-based networks and to estimate the coupling of voxel-wise cerebral blood flow (CBF)-degree centrality (DC), CBF-mean amplitude of low-frequency fluctuation (mALFF) and CBF- mean regional homogeneity (mReHo). We further evaluated the relationship between NV coupling pattern and cognitive performance (false discovery rate corrected). T2DM without MCI patients displayed significant decrease in the absolute CBF-mALFF, CBF-mReHo coupling of CBFnetwork and in the CBF-DC coupling of DCnetwork. Besides, networks which involved CBF and DC hubs mainly located in the default mode network (DMN). Furthermore, less severe disease and better cognitive performance in T2DM patients were significantly correlated with higher coupling of CBF-DC, CBF-mALFF or CBF-mReHo, especially for the cognitive dimensions of general function and executive function. Thus, coupling of CBF-DC, CBF-mALFF and CBF-mReHo may serve as promising indicators to reflect NV coupling state and to explain the T2DM related early cognitive impairment. Image 1 [ABSTRACT FROM AUTHOR]

Prism adaptation (PA) is a procedure used for studying visuomotor plasticity in healthy individuals, as well as for alleviating spatial neglect in patients. The adaptation is achieved by performing goal-directed movements while wearing prismatic lenses that induce a lateral displacement of visual information. This results in an initial movement error that is compensated by a recalibration of sensory-motor coordinates; consequently, a lateral bias in both motor and perceptual measurements occurs after prism removal, i.e., after effects. Neuroimaging studies have shown that a brief exposure to a rightward-shifting prism changes the activations in the inferior parietal lobule (IPL) and modulates interhemispheric balance during attention tasks. However, it is yet unknown how PA changes global interplay between cortical networks as evident from task-free resting state connectivity. Thus we compared resting state functional connectivity patterns before ('Pre') and after ('Post') participants performed a session of pointing movements with a rightward-shifting prism (N = 14) or with neutral lenses (as a control condition; N = 12). Global connectivity analysis revealed significant decreases in functional connectivity following PA in two nodes of the Default Mode Network (DMN), and in the left anterior insula. Further analyses of these regions showed specific connectivity decrease between either of the DMN nodes and areas within the attentional networks, including the inferior frontal gyrus, the anterior insula and the right superior temporal sulcus. On the other hand, the anterior insula decreased its connectivity to a large set of areas, all within the boundaries of the DMN. These results demonstrate that a brief exposure to PA enhances the decoupling between the DMN and the attention networks. The change in interplay between those pre-existing networks might be the basis of the rapid and wide-ranged behavioural changes induce by PA in healthy individuals. Image 1 • We assess resting state functional connectivity modulations after prism adaptation. • Prism adaptation reduced global connectivity in DMN and in anterior insula. • DMN nodes reduced connectivity to temporo-frontal attention and action regions. • Left anterior insula reduced connectivity to multiple DMN regions. • We found enhanced decoupling between DMN and attentional networks. [ABSTRACT FROM AUTHOR]

The habenula (Hb) inhibits dopaminergic reward signaling in response to negative outcomes and has been linked to numerous functional domains relevant to mental health, including reward prediction, motivation, and aversion processing. Despite its important neuroscientific and clinical implications, however, the human Hb remains poorly understood due to its small size and the associated technical hurdles to in vivo functional magnetic resonance imaging (fMRI) investigation. Using high-resolution 3 T fMRI data from 68 healthy young adults acquired through the Human Connectome Project, we developed a rigorous approach for mapping the whole-brain resting-state functional connectivity of the human Hb. Our study combined an optimized strategy for defining subject-level connectivity seeds to maximize Hb blood-oxygen-level-dependent (BOLD) signal sensitivity with high-quality surface-based alignment for robust functional localization and cortical sensitivity. We identified significant positive Hb connectivity with: (i) conserved brainstem targets, including the dopaminergic ventral tegmental area, serotonergic raphe nuclei, and periaqueductal gray; (ii) subcortical structures related to reward and motor function, including the nucleus accumbens, dorsal striatum, pallidum, thalamus, and cerebellum; and (iii) cortical areas associated with the Salience Network and early sensory processing, including the dorsal anterior cingulate, anterior insula, and primary visual and auditory cortices. Hb connectivity was strongly biased towards task-positive brain regions, with weak or negative connectivity observed throughout the task-negative Default Mode Network. Our study provides a detailed characterization of Hb resting-state functional connectivity in healthy young adults, demonstrating both the feasibility and clinical potential of studying the human Hb using high-resolution 3 T fMRI. Image 1 [ABSTRACT FROM AUTHOR]

The default mode network is a large-scale brain network that is active during rest and internally focused states and deactivates as well as desynchronizes during externally oriented (top-down) attention demanding cognitive tasks. However, it is not sufficiently understood if salient stimuli, able to trigger bottom-up attentional processes, could also result in similar reduction of activity and functional connectivity in the DMN. In this study, we investigated whether bottom-up sensory processing could influence the default mode-like network (DMLN) in rats. DMLN activity was examined using block-design visual functional magnetic resonance imaging (fMRI) while its synchronization was investigated by comparing functional connectivity during a resting versus a continuously stimulated brain state by unpredicted light flashes. We demonstrated that the BOLD response in DMLN regions was decreased during visual stimulus blocks and increased during blanks. Furthermore, decreased inter-network functional connectivity between the DMLN and visual networks as well as decreased intra-network functional connectivity within the DMLN was observed during the continuous visual stimulation. These results suggest that triggering of bottom-up attention mechanisms in sedated rats can lead to a cascade similar to top-down orienting of attention in humans and is able to deactivate and desynchronize the DMLN. • Bottom-up sensory processing can influence the default mode-like network in rats. • Block design visual stimulation induces negative bold responses in nodes of the DMLN. • Continuous visual stimulation reduces intra- and inter-DMLN functional connectivity. [ABSTRACT FROM AUTHOR]

Both psychedelics and meditation exert profound modulatory effects on consciousness, perception and cognition, but their combined, possibly synergistic effects on neurobiology are unknown. Accordingly, we conducted a randomized, double-blind, placebo-controlled study with 38 participants following a single administration of the psychedelic psilocybin (315 μg/kg p.o.) during a 5-day mindfulness retreat. Brain dynamics were quantified directly pre- and post-intervention by functional magnetic resonance imaging during the resting state and two meditation forms. The analysis of functional connectivity identified psilocybin-related and mental state–dependent alterations in self-referential processing regions of the default mode network (DMN). Notably, decoupling of medial prefrontal and posterior cingulate cortices, which is thought to mediate sense of self, was associated with the subjective ego dissolution effect during the psilocybin-assisted mindfulness session. The extent of ego dissolution and brain connectivity predicted positive changes in psycho-social functioning of participants 4 months later. Psilocybin, combined with meditation, facilitated neurodynamic modulations in self-referential networks, subserving the process of meditation by acting along the anterior–posterior DMN connection. The study highlights the link between altered self-experience and subsequent behavioral changes. Understanding how interventions facilitate transformative experiences may open novel therapeutic perspectives. Insights into the biology of discrete mental states foster our understanding of non-ordinary forms of human self-consciousness and their concomitant brain substrate. • Study investigates the psychedelic effects of psilocybin within a mindfulness retreat. • Drug-specific modulations in self-referential brain areas were found post-intervention. • Reduced antero-posterior DMN connectivity was linked to drug-induced ego dissolution. • Extent of altered self-experience and connectivity predicted lasting positive changes. [ABSTRACT FROM AUTHOR]