Differences Between Resting State fMRI BOLD Variability and Default Mode Network Connectivity in Healthy Older and Younger Adults.

BACKGROUND: Resting state fMRI analyses have been used to examine functional connectivity in the aging brain. Recently, fluctuations in the fMRI BOLD signal have been used as a potential marker of integrity in neural systems. Despite its increasing popularity, the results of BOLD variability analyses and mean based functional connectivity analyses have rarely been compared. The current study examined fMRI BOLD signal variability and default mode network seed-based analyses in healthy older and younger adults to better understand the unique contributions of these methodological approaches. METHODS: 34 healthy participants were separated into a younger adult group (age 25-35, n=17) and an older adult group (age 65+, n=17). For each participant, a map of the standard deviation of the BOLD signal (SDBOLD) was derived. Group comparisons examined differences in resting-state SDBOLD in younger versus older adults. Seed-based analyses were used to examine differences between younger and older adults in the default mode network. RESULTS: Between-group comparisons revealed significantly greater BOLD variability in widespread brain regions in older relative to younger adults. There were no significant differences between younger and older adults in the default mode network connectivity. CONCLUSION: The current findings align with an increasing number of studies reporting greater BOLD variability in older relative to younger adults. The current results also suggest that the traditional resting state examination methods may not detect nuanced age-related differences. Further large-scale studies in an adult lifespan sample are needed to better understand the functional relevance of the BOLD variability in normative aging.

Assistive tools for classifying neurological disorders using fMRI and deep learning: A guide and example.

BACKGROUND: Deep-learning (DL) methods are rapidly changing the way researchers classify neurological disorders. For example, combining functional magnetic resonance imaging (fMRI) and DL has helped researchers identify functional biomarkers of neurological disorders (e.g., brain activation and connectivity) and pilot innovative diagnostic models. However, the knowledge required to perform DL analyses is often domain-specific and is not widely taught in the brain sciences (e.g., psychology, neuroscience, and cognitive science). Conversely, neurological diagnoses and neuroimaging training (e.g., fMRI) are largely restricted to the brain and medical sciences. In turn, these disciplinary knowledge barriers and distinct specializations can act as hurdles that prevent the combination of fMRI and DL pipelines. The complexity of fMRI and DL methods also hinders their clinical adoption and generalization to real-world diagnoses. For example, most current models are not designed for clinical settings or use by nonspecialized populations such as students, clinicians, and healthcare workers. Accordingly, there is a growing area of assistive tools (e.g., software and programming packages) that aim to streamline and increase the accessibility of fMRI and DL pipelines for the diagnoses of neurological disorders. OBJECTIVES AND METHODS: In this study, we present an introductory guide to some popular DL and fMRI assistive tools. We also create an example autism spectrum disorder (ASD) classification model using assistive tools (e.g., Optuna, GIFT, and the ABIDE preprocessed repository), fMRI, and a convolutional neural network. RESULTS: In turn, we provide researchers with a guide to assistive tools and give an example of a streamlined fMRI and DL pipeline. CONCLUSIONS: We are confident that this study can help more researchers enter the field and create accessible fMRI and deep-learning diagnostic models for neurological disorders.

Salience Network Segregation Mediates the Effect of Tau Pathology on Mild Behavioral Impairment.

INTRODUCTION: A recently developed mild behavioral impairment (MBI) diagnostic framework standardizes the early characterization of neuropsychiatric symptoms in older adults. However, the links between MBI, brain function, and Alzheimer's disease (AD) biomarkers are unclear. METHODS: Using data from 128 participants with diagnosis of amnestic mild cognitive impairment and mild dementia - Alzheimer's type, we test a novel model assessing direct relationships between AD biomarker status and MBI symptoms, as well as mediated effects through segregation of the salience and default-mode networks. RESULTS: We identified a mediated effect of tau positivity on MBI through functional segregation of the salience network from the other high-level, association networks. There were no direct effects of AD biomarkers status on MBI. DISCUSSION: Our findings suggest an indirect role of tau pathology in MBI through brain network dysfunction and emphasize the role of the salience network in mediating relationships between neuropathological changes and behavioral manifestations.

Neural adaptations to congenital deafness: enhanced tactile discrimination through cross-modal neural plasticity - an fMRI study.

BACKGROUND: This study explores the compensatory neural mechanisms associated with congenital deafness through an examination of tactile discrimination abilities using high-resolution functional magnetic resonance imaging (fMRI). OBJECTIVE: To analyze the neural substrates underlying tactile processing in congenitally deaf individuals and compare them with hearing controls. METHODS: Our participant pool included thirty-five congenitally deaf individuals and thirty-five hearing controls. All participants engaged in tactile discrimination tasks involving the identification of common objects by touch. We utilized an analytical suite comprising voxel-based statistics, functional connectivity multivariate/voxel pattern analysis (fc-MVPA), and seed-based connectivity analysis to examine neural activity. RESULTS: Our findings revealed pronounced neural activity in congenitally deaf participants within regions typically associated with auditory processing, including the bilateral superior temporal gyrus, right middle temporal gyrus, and right rolandic operculum. Additionally, unique activation and connectivity patterns were observed in the right insula and bilateral supramarginal gyrus, indicating a strategic reorganization of neural pathways for tactile information processing. Behaviorally, both groups demonstrated high accuracy in the tactile tasks, exceeding 90%. However, the deaf participants outperformed their hearing counterparts in reaction times, showcasing significantly enhanced efficiency in tactile information processing. CONCLUSION: These insights into the brain's adaptability to sensory loss through compensatory neural reorganization highlight the intricate mechanisms by which tactile discrimination is enhanced in the absence of auditory input. Understanding these adaptations can help develop strategies to harness the brain's plasticity to improve sensory processing in individuals with sensory impairments, ultimately enhancing their quality of life through improved tactile perception and sensory integration.

Topological Organization of the Brain Network in Patients with Primary Angle-closure Glaucoma Through Graph Theory Analysis.

Primary angle-closure glaucoma (PACG) is a sight-threatening eye condition that leads to irreversible blindness. While past neuroimaging research has identified abnormal brain function in PACG patients, the relationship between PACG and alterations in brain functional networks has yet to be explored. This study seeks to examine the influence of PACG on brain networks, aiming to advance knowledge of its neurobiological processes for better diagnostic and therapeutic approaches utilizing graph theory analysis. A cohort of 44 primary angle-closure glaucoma (PACG) patients and 44 healthy controls participated in this study. Functional brain networks were constructed using fMRI data and the Automated Anatomical Labeling 90 template. Subsequently, graph theory analysis was employed to evaluate global metrics, nodal metrics, modular organization, and network-based statistics (NBS), enabling a comparative analysis between PACG patients and the control group. The analysis of global metrics, including small-worldness and network efficiency, did not exhibit significant differences between the two groups. However, PACG patients displayed elevated nodal metrics, such as centrality and efficiency, in the left frontal superior medial, right frontal superior medial, and right posterior central brain regions, along with reduced values in the right temporal superior gyrus region compared to healthy controls. Furthermore, Module 5 showed notable disparities in intra-module connectivity, while Module 1 demonstrated substantial differences in inter-module connectivity with both Module 7 and Module 8. Noteworthy, the NBS analysis unveiled a significantly altered network when comparing the PACG and healthy control groups. The study proposes that PACG patients demonstrate variations in nodal metrics and modularity within functional brain networks, particularly affecting the prefrontal, occipital, and temporal lobes, along with cerebellar regions. However, an analysis of global metrics suggests that the overall connectivity patterns of the entire brain network remain unaltered in PACG patients. These results have the potential to serve as early diagnostic and differential markers for PACG, and interventions focusing on brain regions with high degree centrality and nodal efficiency could aid in optimizing therapeutic approaches.

Revealing the mechanism of central pain hypersensitivity in primary dysmenorrhea: evidence from neuroimaging.

Background: Primary dysmenorrhea (PDM) is the most common problem in menstruating women. A number of functional magnetic resonance imaging (fMRI) study have revealed that the brain plays a crucial role in the pathophysiology of PDM. However, these results have been inconsistent, and there is a lack of a comprehensive fMRI study to clarify the onset and long-term effects of PDM. The aim of this study was thus to investigate the onset and long-term effects of PDM in a cohort of patients with PDM. Methods: This study employed a cross-sectional design with prospective data collection, in which 25 patients with PDM and 20 healthy controls (HCs) were recruited. The patients with PDM underwent fMRI scans both during the PDM during the pain phase (PDM-P) and nonpain phase (PDM-NP). The long-term effects of PDM on the brain was assessed by comparing PDM-NP findings with those of HCs, and the central mechanism of PDM was assessed by comparing the PDM-P findings with those of PDM-NP. To identify changes in brain function, the amplitude of low-frequency fluctuations and the regional homogeneity (ReHo) were measured. To assess changes in brain structure, voxel-based morphometry (VBM) was applied. The periaqueductal gray (PAG) was set as a region of for conducting seed-based whole-brain functional connectivity (FC) analysis. Subsequently, Pearson correlation analyses were employed to evaluate the associations between the abnormal brain region and the clinical information of the patients. Results: There were neither functional nor structural differences between patients in the PDM-NP and HCs. Compared with those in PDM-NP, those in PDM-P showed increased ReHo in the left dorsolateral prefrontal cortex (DLPFC) but decreased FC between PAG and right superior parietal gyrus, bilateral inferior parietal gyrus, right calcarine gyrus, left superior occipital gyrus, left precentral gyrus, right DLPFC, and left crus I of the cerebellar hemisphere. Conclusions: The results from this study suggest that the mechanism of central pain hypersensitivity of PDM may be related to the disorder of the FC between the PAG and descending pain modulation system, default mode network (DMN), and occipital lobe. These findings could help us better understand the pathophysiology of PDM from a neuroimaging perspective.

BPI-GNN: Interpretable brain network-based psychiatric diagnosis and subtyping.

Converging evidence increasingly suggests that psychiatric disorders, such as major depressive disorder (MDD) and autism spectrum disorder (ASD), are not unitary diseases, but rather heterogeneous syndromes that involve diverse, co-occurring symptoms and divergent responses to treatment. This clinical heterogeneity has hindered the progress of precision diagnosis and treatment effectiveness in psychiatric disorders. In this study, we propose BPI-GNN, a new interpretable graph neural network (GNN) framework for analyzing functional magnetic resonance images (fMRI), by leveraging the famed prototype learning. In addition, we introduce a novel generation process of prototype subgraph to discover essential edges of distinct prototypes and employ total correlation (TC) to ensure the independence of distinct prototype subgraph patterns. BPI-GNN can effectively discriminate psychiatric patients and healthy controls (HC), and identify biological meaningful subtypes of psychiatric disorders. We evaluate the performance of BPI-GNN against 11 popular brain network classification methods on three psychiatric datasets and observe that our BPI-GNN always achieves the highest diagnosis accuracy. More importantly, we examine differences in clinical symptom profiles and gene expression profiles among identified subtypes and observe that our identified brain-based subtypes have the clinical relevance. It also discovers the subtype biomarkers that align with current neuro-scientific knowledge.

Impaired Cortico-Thalamo-Cerebellar Integration Across Schizophrenia, Bipolar II, and Attention Deficit Hyperactivity Disorder Patients Suggests Potential Neural Signatures for Psychiatric Illness.

Understanding aberrant functional changes between brain regions has shown promise for characterizing and differentiating the symptoms associated with progressive psychiatric disorders. The functional integration between the thalamus and cerebellum significantly influences learning and memory in cognition. Observed in schizophrenic patients, dysfunction within the corticalthalamocerebellar (CTC) circuitry is linked to challenges in prioritizing, processing, coordinating, and responding to information. This study explored whether abnormal CTC functional network connectivity patterns are present across schizophrenia (SCHZ) patients, bipolar II disorder (BIPOL) patients, and ADHD patients by examining both task- and task-free conditions compared to healthy volunteers (HC). Leveraging fMRI data from 135 participants (39 HC, 27 SCHZ patients, 38 BIPOL patients, and 31 ADHD patients), we analyzed functional network connectivity (FNC) patterns across 115 cortical, thalamic, subcortical, and cerebellar regions of interest (ROIs). Guiding our investigation: First, do the brain regions of the CTC circuit exhibit distinct abnormal patterns at rest in SCHZ, ADHD, and BIPOL? Second, do working memory tasks in these patients engage common regions of the circuit in similar or unique patterns? Consistent with previous findings, our observations revealed FNC patterns constrained in the cerebellar, thalamic, striatal, hippocampal, medial prefrontal and insular cortices across all three psychiatric cohorts when compared to controls in both task and task-free conditions. Post hoc analysis suggested a predominance in schizophrenia and ADHD patients during rest, while the task condition demonstrated effects across all three disorders. Factor-by-covariance GLM MANOVA further specified regions associated with clinical symptoms and trait assessments. Our study provides evidence suggesting that dysfunctional CTC circuitry in both task-free and task-free conditions may be an important broader neural signature of psychiatric illness.

Sex Differences in Response Inhibition-Related Neural Predictors of Posttraumatic Stress Disorder in Civilians With Recent Trauma.

BACKGROUND: Females are more likely to develop posttraumatic stress disorder (PTSD) than males. Impaired inhibition has been identified as a mechanism for PTSD development, but studies on potential sex differences in this neurobiological mechanism and how it relates to PTSD severity and progression are relatively rare. Here, we examined sex differences in neural activation during response inhibition and PTSD following recent trauma. METHODS: Participants (n = 205, 138 female sex assigned at birth) were recruited from emergency departments within 72 hours of a traumatic event. PTSD symptoms were assessed 2 weeks and 6 months posttrauma. A Go/NoGo task was performed 2 weeks posttrauma in a 3T magnetic resonance imaging scanner to measure neural activity during response inhibition in the ventromedial prefrontal cortex, right inferior frontal gyrus, and bilateral hippocampus. General linear models were used to examine the interaction effect of sex on the relationship between our regions of interest and the whole brain, PTSD symptoms at 6 months, and symptom progression between 2 weeks and 6 months. RESULTS: Lower response inhibition-related ventromedial prefrontal cortex activation 2 weeks posttrauma predicted more PTSD symptoms at 6 months in females but not in males, while greater response inhibition-related right inferior frontal gyrus activation predicted lower PTSD symptom progression in males but not females. Whole-brain interaction effects were observed in the medial temporal gyrus and left precentral gyrus. CONCLUSIONS: There are sex differences in the relationship between inhibition-related brain activation and PTSD symptom severity and progression. These findings suggest that sex differences should be assessed in future PTSD studies and reveal potential targets for sex-specific interventions.

Human brain activity and functional connectivity associated with verbal long-term memory consolidation across 1 month.

Introduction: Declarative memories are initially dependent on the hippocampus and become stabilized through the neural reorganization of connections between the medial temporal lobe and neocortex. The exact time-course of these neural changes is not well established, although time-dependent changes in retrieval-related brain function can be detected across relatively short time periods in humans (e.g., hours to months). Methods: In a study involving older adults with normal cognition (N = 24), we investigated changes in brain activity and functional connectivity associated with the long-term memory consolidation of verbal material over one month. Participants studied fact-like, three-word sentences at 1-month, 1-week, 1-day, and 1-hour intervals before a recognition memory test inside an MRI scanner. Old/new recognition with confidence ratings and response times were recorded. We examined whole-brain changes in retrieval-related brain activity, as well as functional connectivity of the hippocampus and ventromedial prefrontal cortex (vmPFC), as memories aged from 1 hour to 1 month. Secondary analyses minimized the effect of confounding factors affected by memory age (i.e., changes in confidence and response time or re-encoding of targets). Results: Memory accuracy, confidence ratings, and response times changed with memory age. A memory age network was identified where retrieval-related brain activity in cortical regions increased or decreased as a function of memory age. Hippocampal brain activity in an anatomical region of interest decreased with memory age. Importantly, these changes in retrieval-related activity were not confounded with changes in activity related to concomitant changes in behavior or encoding. Exploratory analyses of vmPFC functional connectivity as a function of memory age revealed increased connectivity with the posterior parietal cortex, as well as with the vmPFC itself. In contrast, hippocampal functional connectivity with the vmPFC and orbitofrontal cortex decreased with memory age. Discussion: The observed changes in retrieval-related brain activity and functional connectivity align with the predictions of standard systems consolidation theory. These results suggest that processes consistent with long-term memory consolidation can be identified over short time periods using fMRI, particularly for verbal material.

The effective connectivity analysis of fMRI based on asymmetric detection of transfer brain entropy.

It is important to explore causal relationships in functional magnetic resonance imaging study. However, the traditional effective connectivity analysis method is easy to produce false causality, and the detection accuracy needs to be improved. In this paper, we introduce a novel functional magnetic resonance imaging effective connectivity method based on the asymmetry detection of transfer entropy, which quantifies the disparity in predictive information between forward and backward time, subsequently normalizing this disparity to establish a more precise criterion for detecting causal relationships while concurrently reducing computational complexity. Then, we evaluate the effectiveness of this method on the simulated data with different level of nonlinearity, and the results demonstrated that the proposed method outperforms others methods on the detection of both linear and nonlinear causal relationships, including Granger Causality, Partial Granger Causality, Kernel Granger Causality, Copula Granger Causality, and traditional transfer entropy. Furthermore, we applied it to study the effective connectivity of brain functional activities in seafarers. The results showed that there are significantly different causal relationships between different brain regions in seafarers compared with non-seafarers, such as Temporal lobe related to sound and auditory information processing, Hippocampus related to spatial navigation, Precuneus related to emotion processing as well as Supp_Motor_Area associated with motor control and coordination, which reflects the occupational specificity of brain function of seafarers.

The truth is in there: Belief processes in the human brain.

Belief, defined by William James as the mental state or function of cognizing reality, is a core psychological function with strong influence on emotion and behavior. Furthermore, strong and aberrant beliefs about the world and oneself play important roles in mental disorders. The underlying processes of belief have been the matter of a long debate in philosophy and psychology, and modern neuroimaging techniques can provide insight into the underlying neural processes. Here, we conducted a functional magnetic resonance imaging study with N = 30 healthy participants in which we presented statements about facts, politics, religion, conspiracy theories, and superstition. Participants judged whether they considered them as true (belief) or not (disbelief) and reported their certainty in the decision. We found belief-associated activations in bilateral dorsolateral prefrontal cortex, left superior parietal cortex, and left lateral frontopolar cortex. Disbelief-associated activations were found in an anterior temporal cluster extending into the amygdala. We found a larger deactivation for disbelief than belief in the ventromedial prefrontal cortex that was most pronounced during decisions, suggesting a role of the vmPFC in belief-related decision-making. As a category-specific effect, we found disbelief-associated activation in retrosplenial cortex and parahippocampal gyrus for conspiracy theory statements. Exploratory analyses identified networks centered at anterior cingulate cortex for certainty, and dorsomedial prefrontal cortex for uncertainty. The uncertainty effect identifies a neural substrate for Alexander Bain's notion from 1859 of uncertainty as the real opposite of belief. Taken together, our results suggest a two-factor neural process model of belief with falsehood/veracity and uncertainty/certainty factors.

Lateralisation of nasal cycle is not reflected in the olfactory bulb volumes and cerebral activations.

Nasal cycle (NC) is a rhythmic change of lateralised nasal airflow mediated by the autonomous nervous system. Previous studies reported the dependence of NC dominance or more patent side on handedness and hemispheric cerebral activity. We aimed to investigate firstly the possible lateralised effect of NC on olfactory bulb volume and secondly the association of NC with the lateralised cerebral dominance in terms of olfactory processing. Thirty-five subjects (22 women and 13 men, mean age 26 ± 3 years) participated in the study. NC was ascertained using a portable rhino-flowmeter. Structural and functional brain measurements were assessed using a 3T MR scanner. Vanillin odorant was presented during functional scans using a computer-controlled olfactometer. NC was found to be independent of the olfactory bulb volumes. Also, cerebral activations were found independent of the NC during odorant perception. NC potency is not associated with lateralised structural or functional differences in the cerebral olfactory system.

The association between posterior resting-state EEG alpha rhythms and functional MRI connectivity in older adults with subjective memory complaint.

Resting-state eyes-closed electroencephalographic (rsEEG) alpha rhythms are dominant in posterior cortical areas in healthy adults and are abnormal in subjective memory complaint (SMC) persons with Alzheimer's disease amyloidosis. This exploratory study in 161 SMC participants tested the relationships between those rhythms and seed-based resting-state functional magnetic resonance imaging (rs-fMRI) connectivity between thalamus and visual cortical networks as a function of brain amyloid burden, revealed by positron emission tomography and cognitive reserve, measured by educational attainment. The SMC participants were divided into 4 groups according to 2 factors: Education (Edu+ and Edu-) and Amyloid burden (Amy+ and Amy-). There was a statistical interaction (p < 0.05) between the two factors, and the subgroup analysis using estimated marginal means showed a positive association between the mentioned rs-fMRI connectivity and the posterior rsEEG alpha rhythms in the SMC participants with low brain amyloidosis and high CR (Amy-/Edu+). These results suggest that in SMC persons, early Alzheimer's disease amyloidosis may contrast the beneficial effects of cognitive reserve on neurophysiological oscillatory mechanisms at alpha frequencies and connectivity between the thalamus and visual cortical networks.

Neurovascular coupling in eye-open-eye-close task and resting state: Spectral correspondence between concurrent EEG and fMRI.

Neurovascular coupling serves as an essential neurophysiological mechanism in functional neuroimaging, which is generally presumed to be robust and invariant across different physiological states, encompassing both task engagement and resting state. Nevertheless, emerging evidence suggests that neurovascular coupling may exhibit state dependency, even in normal human participants. To investigate this premise, we analyzed the cross-frequency spectral correspondence between concurrently recorded electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) data, utilizing them as proxies for neurovascular coupling during the two conditions: an eye-open-eye-close (EOEC) task and a resting state. We hypothesized that given the state dependency of neurovascular coupling, EEG-fMRI spectral correspondences would change between the two conditions in the visual system. During the EOEC task, we observed a negative phase-amplitude-coupling (PAC) between EEG alpha-band and fMRI visual activity. Conversely, in the resting state, a pronounced amplitude-amplitude-coupling (AAC) emerged between EEG and fMRI signals, as evidenced by the spectral correspondence between the EEG gamma-band of the midline occipital channel (Oz) and the high-frequency fMRI signals (0.15-0.25 Hz) in the visual network. This study reveals distinct scenarios of EEG-fMRI spectral correspondence in healthy participants, corroborating the state-dependent nature of neurovascular coupling.

Experiential grounding of abstract concepts: Processing of abstract mental state concepts engages brain regions involved in mentalizing, automatic speech, and lip movements.

concepts like mental state concepts lack a physical referent, which can be directly perceived. Classical theories therefore claim that abstract concepts require amodal representations detached from experiential brain systems. However, grounded cognition approaches suggest an involvement of modal experiential brain regions in the processing of abstract concepts. In the present functional magnetic resonance imaging study, we investigated the relation of the processing of abstract mental state concepts to modal experiential brain systems in a fine-grained fashion. Participants performed lexical decisions on abstract mental state as well as on verbal association concepts as control category. Experiential brain systems related to the processing of mental states, generating verbal associations, automatic speech as well as hand and lip movements were determined by corresponding localizer tasks. Processing of abstract mental state concepts neuroanatomically overlapped with activity patterns associated with processing of mental states, generating verbal associations, automatic speech and lip movements. Hence, mental state concepts activate the mentalizing brain network, complemented by perceptual-motor brain regions involved in simulation of visual or action features associated with social interactions, linguistic brain regions as well as face-motor brain regions recruited for articulation. The present results provide compelling evidence for the rich grounding of abstract mental state concepts in experiential brain systems related to mentalizing, verbal communication and mouth action.

Aberrant neural computation of social controllability in nicotine-dependent humans.

Social controllability, defined as the ability to exert influence when interacting with others, is crucial for optimal decision-making. Inability to do so might contribute to maladaptive behaviors such as drug use, which often takes place in social settings. Here, we examined nicotine-dependent humans using fMRI, as they made choices that could influence the proposals from simulated partners. Computational modeling revealed that smokers under-estimated the influence of their actions and self-reported a reduced sense of control, compared to non-smokers. These findings were replicated in a large independent sample of participants recruited online. Neurally, smokers showed reduced tracking of forward projected choice values in the ventromedial prefrontal cortex, and impaired computation of social prediction errors in the midbrain. These results demonstrate that smokers were less accurate in estimating their personal influence when the social environment calls for control, providing a neurocomputational account for the social cognitive deficits in this population.

Responding to threat: Associations between neural reactivity to and behavioral avoidance of threat in pediatric anxiety.

BACKGROUND: Despite broad recognition of the central role of avoidance in anxiety, a lack of specificity in its operationalization has hindered progress in understanding this clinically significant construct. The current study uses a multimodal approach to investigate how specific measures of avoidance relate to neural reactivity to threat in youth with anxiety disorders. METHODS: Children with anxiety disorders (ages 6-12 years; n = 65 for primary analyses) completed laboratory task- and clinician-based measures of avoidance, as well as a functional magnetic resonance imaging task probing neural reactivity to threat. Primary analyses examined the ventral anterior insula (vAI), amygdala, and ventromedial prefrontal cortex (vmPFC). RESULTS: Significant but distinct patterns of association with task- versus clinician-based measures of avoidance emerged. Clinician-rated avoidance was negatively associated with right and left vAI reactivity to threat, whereas laboratory-based avoidance was positively associated with right vAI reactivity to threat. Moreover, left vAI-right amygdala and bilateral vmPFC-right amygdala functional connectivity were negatively associated with clinician-rated avoidance but not laboratory-based avoidance. LIMITATIONS: These results should be considered in the context of the restricted range of our treatment-seeking sample, which limits the ability to draw conclusions about these associations across children with a broader range of symptomatology. In addition, the limited racial and ethnic diversity of our sample may limit the generalizability of findings. CONCLUSION: These findings mark an important step towards bridging neural findings and behavioral patterns using a multimodal approach. Advancing understanding of behavioral avoidance in pediatric anxiety may guide future treatment optimization by identifying individual-specific targets for treatment.

Developmental changes in brain activation during novel grammar learning in 8-25-year-olds.

While it is well established that grammar learning success varies with age, the cause of this developmental change is largely unknown. This study examined functional MRI activation across a broad developmental sample of 165 Dutch-speaking individuals (8-25 years) as they were implicitly learning a new grammatical system. This approach allowed us to assess the direct effects of age on grammar learning ability while exploring its neural correlates. In contrast to the alleged advantage of children language learners over adults, we found that adults outperformed children. Moreover, our behavioral data showed a sharp discontinuity in the relationship between age and grammar learning performance: there was a strong positive linear correlation between 8 and 15.4 years of age, after which age had no further effect. Neurally, our data indicate two important findings: (i) during grammar learning, adults and children activate similar brain regions, suggesting continuity in the neural networks that support initial grammar learning; and (ii) activation level is age-dependent, with children showing less activation than older participants. We suggest that these age-dependent processes may constrain developmental effects in grammar learning. The present study provides new insights into the neural basis of age-related differences in grammar learning in second language acquisition.

L-DOPA and oxytocin influence the neural correlates of performance monitoring for self and others.

RATIONALE: The ability to monitor the consequences of our actions for others is imperative for flexible and adaptive behavior, and allows us to act in a (pro)social manner. Yet, little is known about the neurochemical mechanisms underlying alterations in (pro)social performance monitoring. OBJECTIVE: The aim of this functional magnetic resonance imaging (fMRI) study was to improve our understanding of the role of dopamine and oxytocin and their potential overlap in the neural mechanisms underlying performance monitoring for own versus others' outcomes. METHOD: Using a double-blind placebo-controlled cross-over design, 30 healthy male volunteers were administered oxytocin (24 international units), the dopamine precursor L-DOPA (100 mg + 25 mg carbidopa), or placebo in three sessions. Participants performed a computerized cannon shooting game in two recipient conditions where mistakes resulted in negative monetary consequences for (1) oneself or (2) an anonymous other participant. RESULTS: Results indicated reduced error-correct differentiation in the ventral striatum after L-DOPA compared to placebo, independent of recipient. Hence, pharmacological manipulation of dopamine via L-DOPA modulated performance-monitoring activity in a brain region associated with reward prediction and processing in a domain-general manner. In contrast, oxytocin modulated the BOLD response in a recipient-specific manner, such that it specifically enhanced activity for errors that affected the other in the pregenual anterior cingulate cortex (pgACC), a region previously implicated in the processing of social rewards and prediction errors. Behaviorally, we also found reduced target sizes-indicative of better performance-after oxytocin, regardless of recipient. Moreover, after oxytocin lower target sizes specifically predicted higher pgACC activity when performing for others. CONCLUSIONS: These different behavioral and neural patterns after oxytocin compared to L-DOPA administration highlight a divergent role of each neurochemical in modulating the neural mechanisms underlying social performance monitoring.