Multilevel Kernel Density Analysis Research Articles

A meta-analysis of cognitive flexibility in aging: Perspective from functional network and lateralization.

Cognitive flexibility, the ability to switch between mental processes to generate appropriate behavioral responses, is reduced with typical aging. Previous studies have found that age-related declines in cognitive flexibility are often accompanied by variations in the activation of multiple regions. However, no meta-analyses have examined the relationship between cognitive flexibility in aging and age-related variations in activation within large-scale networks. Here, we conducted a meta-analysis employing multilevel kernel density analysis to identify regions with different activity patterns between age groups, and determined how these regions fall into functional networks. We also employed lateralization analysis to explore the spatial distribution of regions exhibiting group differences in activation. The permutation tests based on Monte Carlo simulation were used to determine the significance of the activation and lateralization results. The results showed that cognitive flexibility in aging was associated with both decreased and increased activation in several functional networks. Compared to young adults, older adults exhibited increased activation in the default mode, dorsal attention, ventral attention, and somatomotor networks, while displayed decreased activation in the visual network. Moreover, we found a global-level left lateralization for regions with decreased activation, but no lateralization for regions with higher activation in older adults. At the network level, the regions with decreased activation were left-lateralized, while the regions with increased activation showed varying lateralization patterns within different networks. To sum up, we found that networks that support various mental functions contribute to age-related variations in cognitive flexibility. Additionally, the aging brain exhibited network-dependent activation and lateralization patterns in response to tasks involving cognitive flexibility. We highlighted that the comprehensive meta-analysis in this study offered new insights into understanding cognitive flexibility in aging from a network perspective.

Neural Abnormalities in Panic Disorder and Agoraphobia: A Meta-Analysis of Functional Activation Studies

IntroductionPanic disorder (PD) and agoraphobia (AG) are highly comorbid anxiety disorders with an increasing prevalence that have a significant clinical and public health impact but are not adequately recognized and treated. Although the current functional neuroimaging literature has documented a range of neural abnormalities in these disorders, primary studies are often not sufficiently powered and their findings have been inconsistent.ObjectivesThis meta-analysis aims to advance our understanding of the neural underpinnings of PD and AG by identifying the most robust patterns of differential neural activation that differentiate individuals diagnosed with one of or both these disorders from age-matched healthy controls.MethodsWe conducted a comprehensive literature search in the PubMed database for all peer-reviewed, whole-brain, task-based functional magnetic resonance imaging (fMRI) activation studies that compared adults diagnosed with PD and/or AG with age-matched healthy controls. Each of these articles was screened by two independent coding teams using formal inclusion criteria and according to current PRISMA guidelines. We then performed a voxelwise, whole-brain, meta-analytic comparison of PD/AG participants with age-matched healthy controls using multilevel kernel density analysis (MKDA) with ensemble thresholding (p<0.05-0.0001) to minimize cluster size detection bias and 10,000 Monte Carlo simulations to correct for multiple comparisons.ResultsWith data from 34 primary studies and a substantial sample size (N=2138), PD/AG participants, relative to age-matched healthy controls, exhibited a reliable pattern of statistically significant, (p<.05-0.0001; FWE-corrected) abnormal neural activation in multiple brain regions of the cerebral cortex and basal ganglia across a variety of experimental tasks.ConclusionsIn this meta-analysis we found robust patterns of differential neural activation in participants diagnosed with PD/AG relative to age-matched healthy controls. These findings advance our understanding of the neural underpinnings of PD and AG and inform the development of brain-based clinical interventions such as non-invasive brain stimulation (NIBS) and treatment prediction and matching algorithms. Future studies should also investigate the neural similarities and differences between PD and AG to increase our understanding of possible differences in their etiology, diagnosis, and treatment.Disclosure of InterestNone Declared

A Meta-Analysis of fMRI Activation Studies of Ketamine in Healthy Participants

IntroductionThere has been rapidly growing interest in understanding the pharmaceutical and clinical properties of psychedelic and dissociative drugs, with a particular focus on ketamine. This compound, long known for its anesthetic and dissociative properties, has garnered attention due to its potential to rapidly alleviate symptoms of depression, especially in individuals with treatment-resistant depression (TRD) or acute suicidal ideation or behavior. However, while ketamine’s psychopharmacological effects are increasingly well-documented, the specific patterns of its neural impact remain a subject of exploration and basic questions remain about its effects on functional activation in both clinical and healthy populations.ObjectivesThis meta-analysis seeks to contribute to the evolving landscape of neuroscience research on dissociative drugs such as ketamine by comprehensively examining the effects of acute ketamine administration on neural activation, as measured by functional magnetic resonance imaging (fMRI), in healthy participants.MethodsWe conducted a meta-analysis of existing fMRI activation studies of ketamine using multilevel kernel density analysis (MKDA). Following a comprehensive PubMed search, we quantitatively synthesized all published primary fMRI whole-brain activation studies of the effects of ketamine in healthy subjects with no overlapping samples (N=18). This approach also incorporated ensemble thresholding (α=0.05-0.0001) to minimize cluster-size detection bias and Monte Carlo simulations to correct for multiple comparisons.ResultsOur meta-analysis revealed statistically significant (p<0.05-0.0001; FWE-corrected) alterations in neural activation in multiple cortical and subcortical regions following the administration of ketamine to healthy participants (N=306).ConclusionsThese results offer valuable insights into the functional neuroanatomical effects caused by acute ketamine administration. These findings may also inform development of therapeutic applications of ketamine for various psychiatric and neurological conditions. Future studies should investigate the neural effects of ketamine administration, including both short-term and long-term effects, in clinical populations and their relation to clinical and functional improvements.Disclosure of InterestNone Declared

Neural Abnormalities in Bipolar Disorder: A Meta-Analysis of Functional Neuroimaging Studies

IntroductionBipolar I disorder (BD-I) is a chronic and recurrent mood disorder characterized by alternating episodes of depression and mania; it is also associated with substantial morbidity and mortality and with clinically significant functional impairments. While previous studies have used functional magnetic resonance imaging (fMRI) to examine neural abnormalities associated with BD-I, they have yielded mixed findings, perhaps due to differences in sampling and experimental design, including highly variable mood states at the time of scan.ObjectivesThe purpose of this study is to advance our understanding of the neural basis of BD-I and mania, as measured by fMRI activation studies, and to inform the development of more effective brain-based diagnostic systems and clinical treatments.MethodsWe conducted a large-scale meta-analysis of whole-brain fMRI activation studies that compared participants with BD-I, assessed during a manic episode, to age-matched healthy controls. Following PRISMA guidelines, we conducted a comprehensive PubMed literature search using two independent coding teams to evaluate primary studies according to pre-established inclusion criteria. We then used multilevel kernel density analysis (MKDA), a well-established, voxel-wise, whole-brain, meta-analytic approach, to quantitatively synthesize all qualifying primary fMRI activation studies of mania. We used ensemble thresholding (p<0.05-0.0001) to minimize cluster size detection bias, and 10,000 Monte Carlo simulations to correct for multiple comparisons.ResultsWe found that participants with BD-I (N=2,042), during an active episode of mania and relative to age-matched healthy controls (N=1,764), exhibit a pattern of significantly (p<0.05-0.0001; FWE-corrected) different activation in multiple brain regions of the cerebral cortex and basal ganglia across a variety of experimental tasks.ConclusionsThis study supports the formulation of a robust neural basis for BD-I during manic episodes and advances our understanding of the pattern of abnormal activation in this disorder. These results may inform the development of novel brain-based clinical tools for bipolar disorder such as diagnostic biomarkers, non-invasive brain stimulation, and treatment-matching protocols. Future studies should compare the neural signatures of BD-I to other related disorders to facilitate the development of protocols for differential diagnosis and improve treatment outcomes in patients with BD-I.Disclosure of InterestNone Declared

Large-scale network abnormality in behavioral addiction

BackgroundResearchers have endeavored to ascertain the network dysfunction associated with behavioral addiction (BA) through the utilization of resting-state functional connectivity (rsFC). Nevertheless, the identification of aberrant patterns within large-scale networks pertaining to BA has proven to be challenging. MethodsWhole-brain seed-based rsFC studies comparing subjects with BA and healthy controls (HC) were collected from multiple databases. Multilevel kernel density analysis was employed to ascertain brain networks in which BA was linked to hyper-connectivity or hypo-connectivity with each prior network. ResultsFifty-six seed-based rsFC publications (1755 individuals with BA and 1828 HC) were included in the meta-analysis. The present study indicate that individuals with BAs exhibit (1) hypo-connectivity within the fronto-parietal network (FN) and hypo- and hyper-connectivity within the ventral attention network (VAN); (2) hypo-connectivity between the FN and regions of the VAN, hypo-connectivity between the VAN and regions of the FN and default mode network (DMN), hyper-connectivity between the DMN and regions of the FN; (3) hypo-connectivity between the reward system and regions of the sensorimotor network (SS), DMN and VAN; (4) hypo-connectivity between the FN and regions of the SS, hyper-connectivity between the VAN and regions of the SS. ConclusionsThese findings provide impetus for a conceptual framework positing a model of BA characterized by disconnected functional coordination among large-scale networks.

Unpacking reappraisal: A systematic review of fMRI studies of distancing and reinterpretation.

In recent decades, a substantial volume of work has examined the neural mechanisms of cognitive reappraisal. Distancing and reinterpretation are two frequently-used tactics through which reappraisal can be implemented. Theoretical frameworks and prior evidence have suggested that the specific tactic through which one employs reappraisal entails differential neural and psychological mechanisms. Thus, we were motivated to assess the neural mechanisms of this distinction by examining the overlap and differentiation exhibited by the neural correlates of distancing (specifically via objective appraisal) and reinterpretation. We analyzed 32 published fMRI studies in healthy adults using multilevel kernel density analysis. Results showed that distancing relative to reinterpretation uniquely recruited right DLPFC and left posterior parietal cortex, previously associated with mentalizing, selective attention, and working memory. Reinterpretation relative to distancing uniquely recruited left VLPFC, previously associated with response selection and inhibition. Further, distancing relative to reinterpretation was associated with greater prevalence of bilateral amygdala attenuation during reappraisal. Finally, a behavioral meta-analysis showed efficacy for both reappraisal tactics. These results are consistent with prior theoretical models for the functional neural architecture of reappraisal via distancing and reinterpretation and suggest potential future applications in region-of-interest specification and neural network analysis in studies focusing on specific reappraisal tactics.

Regional abnormalities of spontaneous brain activity in migraine: A coordinate-based meta-analysis.

Many resting-state functional magnetic resonance imaging (rs-fMRI) studies have explored abnormal regional spontaneous brain activity in migraine. However, these results are inconsistent. To identify the consistent regions with abnormal neural activity, we meta-analyzed these studies. We gathered whole-brain rs-fMRI studies measuring differences in the amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF), or regional homogeneity (ReHo) methods. Then, we performed a voxel-wise meta-analysis to identify consistent abnormal neural activity in migraine by anisotropic effect size seed-based d mapping (AES-SDM). To confirm the AES-SDM meta-analysis results, we conducted two meta-analyses: activation likelihood estimation (ALE) and multi-level kernel density analysis (MKDA). We found that migraine showed increased regional neural activities in the bilateral postcentral gyrus (PoCG), left hippocampus (HIP.L), right pons, left superior frontal gyrus (SFG.L), triangular part of right inferior frontal gyrus (IFGtriang.R), right middle frontal gyrus (MFG.R), and left precentral gyrus (PreCG.L) and decreased regional intrinsic brain activities were exhibited in the right angular gyrus (ANG.R), left superior occipital gyrus (SOG.L), right lingual gyrus (LING.R). Moreover, the meta-analysis of ALE further validated the abnormal neural activities in the PoCG, right pons, ANG.R, and HIP. Meta-regression demonstrated that headache intensity was positively associated with the abnormal activities in the HIP.L, ANG.R, and LING.R. These findings suggest that migraine is associated with abnormal spontaneous brain activities of some pain-related regions, which may contribute to a deeper understanding of the neural mechanism of migraine.

Major Depressive Disorder in Youth: A Meta-Analysis of Functional Magnetic Resonance Imaging Studies

IntroductionMajor depressive disorder (MDD) is a highly prevalent mental illness that frequently originates in early development and is pervasive during adolescence. Despite its high prevalence and early age of onset, our understanding of the potentially unique neural basis of MDD in this age group is still not well understood, and the existing primary literature on the topic includes many new and divergent results. This limited understanding of MDD in youth presents a critical need to further investigate its neural basis in youth and presents an opportunity to also improve clinical treatments that target its neural abnormalities.ObjectivesThe present study aims to advance our understanding of the neural basis of MDD in youth by identifying abnormal functional activation in various brain regions compared with healthy controls.MethodsWe conducted a meta-analysis of functional magnetic resonance imaging (fMRI) studies of MDD by using a well-established method, multilevel kernel density analysis (MKDA) with ensemble thresholding, to quantitatively combine all existing whole-brain fMRI studies of MDD in youth compared with healthy controls. This method involves a voxel-wise, whole-brain approach, that compares neural activation of patients with MDD to age-matched healthy controls across variations of task-based conditions, which we subcategorize into affective processing, executive functioning, positive valence, negative valence, and symptom provocation tasks.ResultsYouth with MDD exhibited statistically significant (p<0.05; FWE-corrected) hyperactivation and hypoactivation in multiple brain regions compared with age-matched healthy controls. These results include significant effects that are stable across various tasks as well as some that appear to depend on task conditions.ConclusionsThis study strengthens our understanding of the neural basis of MDD in youth and may also be used to help identify possible similarities and differences between youth and adults with depression. It may also help inform the development of new treatment interventions and tools for predicting unique treatment responses in youth with depression.Disclosure of InterestNone Declared

Neural Abnormalities Associated with Generalized Anxiety Disorder: A Meta-Analysis of Functional Magnetic Resonance Imaging Activation Studies

IntroductionGeneralized anxiety disorder (GAD) is a highly prevalent mental illness that is associated with clinically significant distress, functional impairment, and poor emotional regulation. Primary functional magnetic resonance imaging (fMRI) studies of GAD report neural abnormalities in comparison to healthy controls. However, many of these findings in the primary literature are inconsistent, and it is unclear whether they are specific to GAD or shared transdiagnostically across related disorders.ObjectivesThis meta-analysis seeks to establish the most reliable neural abnormalities observed in individuals with GAD, as reported in the primary fMRI activation literature.MethodsWe conducted an exhaustive literature search in PubMed to identify primary studies that met our pre-specified inclusion criteria and then extracted relevant data from primary, whole-brain fMRI activation studies of GAD that reported coordinates in Talairach or MNI space. We then used multilevel kernel density analysis (MKDA) with ensemble thresholding to examine the differences between adults with GAD and healthy controls in order to identify brain regions that reached statistical significance across primary studies.ResultsPatients with GAD showed statistically significant (α=0.05–0.0001; family-wise-error-rate corrected) neural activation in various regions of the cerebral cortex and basal ganglia across a variety of experimental tasks.ConclusionsThese results inform our understanding of the neural basis of GAD and are interpreted using a frontolimbic model of anxiety as well as specific clinical symptoms of this disorder and its relation to other mood and anxiety disorders. These results also suggest possible novel targets for emerging neurostimulation therapies (e.g., transcranial magnetic stimulation) and may be used to advance our understanding of the effects of current pharmaceutical treatments and ways to improve treatment selection and symptom-targeting for patients diagnosed with GAD.Disclosure of InterestNone Declared

Establishing Disorder-Specific and Transdiagnostic Neural Features of Psychiatric Disorders Through Large-Scale Functional Magnetic Resonance Imaging Meta-Analyses

IntroductionMeta-analyses of functional magnetic resonance imaging (fMRI) studies have been used to elucidate the most reliable neural features associated with various psychiatric disorders. However, it has not been well-established whether each of these neural features is linked to a specific disorder or is transdiagnostic across multiple disorders and disorder categories, including mood, anxiety, and anxiety-related disorders.ObjectivesThis project aims to advance our understanding of the disorder-specific and transdiagnostic neural features associated with mood, anxiety, and anxiety-related disorders as well as to refine the methodology used to compare multiple disorders.MethodsWe conducted an exhaustive PubMed literature search followed by double-screening, double-extraction, and cross-checking to identify all whole-brain, case-control fMRI activation studies of mood, anxiety, and anxiety-related disorders in order to construct a large-scale meta-analytic database of primary studies of these disorders. We then employed multilevel kernel density analysis (MKDA) with Monte-Carlo simulations to correct for multiple comparisons as well as ensemble thresholding to reduce cluster size bias to analyze primary fMRI studies of mood, anxiety, and anxiety-related disorders followed by application of triple subtraction techniques and a second-order analysis to elucidate the disorder-specificity of the previously identified neural features.ResultsWe found that participants diagnosed with mood, anxiety, and anxiety-related disorders exhibited statistically significant (p < .05 – 0.0001; FWE-corrected) differences in neural activation relative to healthy controls throughout the cerebral cortex, limbic system, and basal ganglia. In addition, each of these psychiatric disorders exhibited a particular profile of neural features that ranged from disorder-specific, to category-specific, to transdiagnostic.ConclusionsThese findings indicate that psychiatric disorders exhibit a complex profile of neural features that vary in their disorder-specificity and can be detected with large-scale fMRI meta-analytic techniques. This approach has potential to fundamentally transform neuroimaging investigations of clinical disorders by providing a novel procedure for establishing disorder-specificity of observed results, which can be then used to advance our understanding of individual disorders as well as broader nosological issues related to diagnosis and classification of psychiatric disorders.Disclosure of InterestNone Declared

The Effects of Serotonergic Psychedelics on Neural Activity: A Meta-Analysis of Task-Based Functional Neuroimaging Studies

IntroductionCuriosity toward the effects of psychedelic drugs on neural activation has increased due to their potential therapeutic benefits, particularly serotonergic psychedelics that act as 5-HT2A receptor agonists such as LSD, psilocybin, and MDMA. However, the pattern of their effects on neural activity in various brain regions in both clinical and healthy populations is still not well understood, and primary studies addressing this issue have sometimes generated inconsistent results.ObjectivesThe present meta-analysis aims to advance our understanding of the most widely used serotonergic psychedelics – LSD, psilocybin, and MDMA – by examining their effects on the functional activation throughout the whole brain among both clinical and healthy participants.MethodsWe conducted this meta-analysis by applying multilevel kernel density analysis (MKDA) with ensemble thresholding to quantitatively combine existing functional magnetic resonance imaging (fMRI) studies that examined whole-brain functional activation of clinical or healthy participants who were administered a serotonergic psychedelic.ResultsSerotonergic psychedelics, including LSD, psilocybin, and MDMA, exhibited significant effects (α=0.05) on neural activation in several regions throughout the cerebral cortex and basal ganglia, including effects that may be common across and unique within each drug.ConclusionsThese observed effects of serotonergic psychedelics on neural activity advance our understanding of the functional neuroanatomy associated with their administration and may inform future studies of both their adverse and therapeutic effects, including emerging clinical applications for the treatment of several psychiatric disorders.Disclosure of InterestNone Declared

Community-level explicit racial prejudice potentiates whites’ neural responses to black faces: A spatial meta-analysis

ABSTRACT We evaluated the hypothesis that neural responses to racial out-group members vary systematically based on the level of racial prejudice in the surrounding community. To do so, we conducted a spatial meta-analysis, which included a comprehensive set of studies (k = 22; N = 481). Specifically, we tested whether community-level racial prejudice moderated neural activation to Black (vs. White) faces in primarily White participants. Racial attitudes, obtained from Project Implicit, were aggregated to the county (k = 17; N = 10,743) in which each study was conducted. Multi-level kernel density analysis demonstrated that significant differences in neural activation to Black (vs. White) faces in right amygdala, dorsal anterior cingulate cortex, and dorsolateral prefrontal cortex were detected more often in communities with higher (vs. lower) levels of explicit (but not implicit) racial prejudice. These findings advance social-cognitive neuroscience by identifying aspects of macro-social contexts that may alter neural responses to out-group members.

Distinct neural activation patterns of age in subcomponents of inhibitory control: A fMRI meta-analysis.

Inhibitory control (IC) is a fundamental cognitive function showing age-related change across the healthy lifespan. Since different cognitive resources are needed in the two subcomponents of IC (cognitive inhibition and response inhibition), regions of the brain are differentially activated. In this study, we aimed to determine whether there is a distinct age-related activation pattern in these two subcomponents. A total of 278 fMRI articles were included in the current analysis. Multilevel kernel density analysis was used to provide data on brain activation under each subcomponent of IC. Contrast analyses were conducted to capture the distinct activated brain regions for the two subcomponents, whereas meta-regression analyses were performed to identify brain regions with distinct age-related activation patterns in the two subcomponents of IC. The results showed that the right inferior frontal gyrus and the bilateral insula were activated during the two IC subcomponents. Contrast analyses revealed stronger activation in the superior parietal lobule during cognitive inhibition, whereas stronger activation during response inhibition was observed primarily in the right inferior frontal gyrus, bilateral insula, and angular gyrus. Furthermore, regression analyses showed that activation of the left anterior cingulate cortex, left inferior frontal gyrus, bilateral insula, and left superior parietal lobule increased and decreased with age during cognitive inhibition and response inhibition, respectively. The results showed distinct activation patterns of aging for the two subcomponents of IC, which may be related to the differential cognitive resources recruited. These findings may help to enhance knowledge of age-related changes in the activation patterns of IC.

Shared network-level functional alterations across substance use disorders: A multi-level kernel density meta-analysis of resting-state functional connectivity studies.

An increasing number of neuroimaging studies indicate functional alterations in cortico-striatal loops in individuals with substance use disorders (SUD). Dysregulations in these circuits may contribute to drug-seeking and drug-consuming behaviour by impeding inhibitory control, habit formation, and reward processing. Despite evidence of network-level changes in SUD, a shared pattern of functional alterations within and between spatially distributed brain networks has not been systematically investigated. The present meta-analytic investigation aims at identifying common alterations in resting-state functional connectivity patterns across different SUD, including stimulant, heroin, alcohol, cannabis, and nicotine use. To this aim, seed-based whole-brain connectivity maps for different functional networks were extracted and subjected to multi-level kernel density analysis to identify dysfunctional networks in individuals with SUD compared with healthy controls. In addition, an exploratory analysis examined substance-specific effects as well as the influence of drug use status on the main findings. Our findings indicate a hypoconnectivity pattern for the limbic, salience, and frontoparietal networks in individuals with SUD as compared with healthy controls. The default mode network additionally exhibited a complex pattern of hypo- and hyperconnectivity across the studies. The observed disrupted connectivity between networks in SUD may associate with deficient inhibitory control mechanisms that are thought to contribute to excessive craving and automatic drug-related behaviour as well as failure in substance use cessation. The identified network-based alterations in SUD represent potential treatment targets for neuromodulation, for example, network-based real-time functional magnetic resonance imaging (fMRI) neurofeedback. Such interventions can evaluate the behavioural relevance of the identified neural circuits.

Prediction of Treatment Response in Patients with Major Depressive Disorder: A Meta-Analysis of Functional Magnetic Resonance Imaging Studies

IntroductionIdentifying the optimal treatment for individuals with major depressive disorder (MDD) is often a long and complicated process. Functional magnetic resonance imaging (fMRI) studies have been used to help predict and explain differences in treatment response among individuals with MDD.ObjectivesWe conducted a comprehensive meta-analysis of treatment prediction studies utilizing fMRI in patients with MDD to provide evidence that neural activity can be used to predict response to antidepressant treatment.MethodsA multi-level kernel density analysis was applied to these primary fMRI studies, in which we analyzed brain activation patterns of depressed patients (N= 364) before receiving antidepressant treatment.ResultsThe results of this analysis demonstrated that hyperactivity in six brain regions significantly predicted treatment response in patients with MDD: the right anterior cingulate, right cuneus, left fusiform gyrus, left middle frontal gyrus, right cingulate gyrus, and left superior frontal gyrus.ConclusionsThis study provides evidence that neural activity, as measured by standard fMRI paradigms, can be used to successfully predict response to antidepressant treatment. This may be used in the future clinically to improve decision-making processes and treatment outcomes for patients.DisclosureNo significant relationships.

The inter-relationships of the neural basis of rumination and inhibitory control: neuroimaging-based meta-analyses.

Rumination, as a clinical manifestation and pathogenic factor of depression, has long been the focus of psychological research regarding its causes and ameliorating approaches. Behavioral studies have shown that rumination is related to inhibitory control deficits, which provides ideas for reducing it. However, the neural relationship between them has not been clearly discussed. In this study, we first used multi-level kernel density analysis to conduct two meta-analyses of published functional magnetic resonance imaging studies: one was rumination comprising 17 studies with 180 foci, and the other was inhibitory control comprising 205 studies with 3791 foci. Conjunction analysis was then performed to explore the common brain regions and further decode them through Neurosynth to confirm the cognitive specificity. Results showed that rumination was mainly related to the default mode network (DMN), while inhibitory control was associated with the frontoparietal network (FPN). In addition, the common activation areas were mainly concentrated in the bilateral precuneus, right superior frontal gyrus, bilateral median cingulate, paracingulate gyri, and the left triangular part of inferior frontal gyrus (IFG). Decoding results also revealed they were involved in inhibition, memory retrieval, and self-related processes. Our findings support that rumination is associated with inhibitory control and can be explained neurologically by an antagonistic relationship between the DMN and FPN. In sum, inhibitory control may be related to rumination via inhibiting task-unrelated attention and controlling self-related processing. This research will help us understand and predict rumination from the perspective of inhibitory control and reduce rumination through behavioral training of inhibitory control or the application of neuromodulation techniques to common activation regions.

Brain network dysfunctions in addiction: a meta-analysis of resting-state functional connectivity

Resting-state functional connectivity (rsFC) provides novel insights into variabilities in neural networks associated with the use of addictive drugs or with addictive behavioral repertoire. However, given the broad mix of inconsistent findings across studies, identifying specific consistent patterns of network abnormalities is warranted. Here we aimed at integrating rsFC abnormalities and systematically searching for large-scale functional brain networks in substance use disorder (SUD) and behavioral addictions (BA), through a coordinate-based meta-analysis of seed-based rsFC studies. A total of fifty-two studies are eligible in the meta-analysis, including 1911 SUD and BA patients and 1580 healthy controls. In addition, we performed multilevel kernel density analysis (MKDA) for the brain regions reliably involved in hyperconnectivity and hypoconnectivity in SUD and BA. Data from fifty-two studies showed that SUD was associated with putamen, caudate and middle frontal gyrus hyperconnectivity relative to healthy controls. Eight BA studies showed hyperconnectivity clusters within the putamen and medio-temporal lobe relative to healthy controls. Altered connectivity in salience or emotion-processing areas may be related to dysregulated affective and cognitive control-related networks, such as deficits in regulating elevated sensitivity to drug-related stimuli. These findings confirm that SUD and BA might be characterized by dysfunctions in specific brain networks, particularly those implicated in the core cognitive and affective functions. These findings might provide insight into the development of neural mechanistic biomarkers for SUD and BA.

Time is body: Multimodal evidence of crosstalk between interoception and time estimation

Theoretical approaches propose a blending between interoception and time estimation. Interoception might constitute a neurophysiological mechanism for encoding duration. However, no study has assessed the convergence between interoception and time estimation using behavioral, neurophysiological, and functional anatomy signatures. We examined the multimodal convergence between interoception and time estimation using a two-fold approach. In study 1, we developed a dual design combining interoception (measuring heartbeat detection - HBD, and heartbeat evoked potential - HEP) with a time estimation paradigm (TEP, estimation of duration of a 120 s interval). In study 2, we performed a conjoint metanalysis (Multi-level Kernel Density Analysis, MKDA) of neuroimaging, including reports of interoception and time estimation. Both studies provide convergent evidence of time estimation's significant involvement in behavioral, electrophysiological (enhanced HEP), and neuroimaging (overlapping cluster in the right insula and operculum) signatures of interoception. Convergent results from both studies offer direct support for a shared mechanism of interoception and time estimation.

Affect in the Aging Brain: A Neuroimaging Meta-Analysis of Older Vs. Younger Adult Affective Experience and Perception.

We report the first functional neuroimaging meta-analysis on age-related differences in adult neural activity during affect. We identified and coded experimental contrasts from 27 studies (published 1997-2018) with 490 older adults (55-87years, M age = 69years) and 470 younger adults (18-39years, M age = 24years). Using multilevel kernel density analysis, we assessed functional brain activation contrasts for older vs. younger adult affect across in-scanner tasks (i.e., affect induction and perception). Relative to older adults, younger adults showed more reliable activation in subcortical structures (e.g., amygdala, thalamus, caudate) and in relatively more posterior aspects of specific brain structures (e.g., posterior insula, mid- and posterior cingulate). In contrast, older adults exhibited more reliable activation in the prefrontal cortex and more anterior aspects of specific brain structures (e.g., anterior insula, anterior cingulate). Meta-analytic coactivation network analyses further revealed that in younger adults, the amygdala and mid-cingulate were more central, locally efficient network nodes, whereas in older adults, regions in the superior and medial prefrontal cortex were more central, locally efficient network nodes. Collectively, these findings help characterize age differences in the brain basis of affect and provide insights for future investigations into the neural mechanisms underlying affective aging.

Simultaneously decreased temporal variability and enhanced variability-strength coupling of emotional network connectivities are related to positive symptoms in patients with schizophrenia.

We hypothesize that decreased temporal variability of emotional network connectivities, corresponding to a continual state of hyperactivity, may play a role in mediating symptoms in schizophrenia. Resting-state magnetic resonance data were collected from 64 subjects, including 21 positive symptom profile schizophrenia patients (PSZ group), 19 negative symptom profile schizophrenia patients (NSZ group), and 24 healthy controls. The emotional brain network was defined based on the coordinates obtained from multi-level kernel density analysis. The temporal variability of intra-network functional connectivities (FCs) was calculated by constructing networks from blood oxygen level-dependent signals at successive, non-overlapping time windows, and was compared between groups. The results showed that the mean FC-variability of the whole emotional network (P = 0.021), and the FC-variabilities in the bilateral anterior insula (both, P < 0.001) were significantly decreased in the PSZ group compared with the control and NSZ groups. Abnormally enhanced negative coupling between variability and FC strength (V-S coupling) was observed in the PSZ group (P = 0.027). In summary, this study found a relation between the positive symptoms of schizophrenia and decreased variability of emotional network connectivities. These findings may help us better understand the neurobiological effect of the time-varying properties of the brain network in schizophrenia patients, and the underlying relation to the generation of psychosis.