Automatic independent component labeling for artifact removal in fMRI

Atlas-Based Labeling of Resting-State fMRI

Background: Functional magnetic resonance imaging (fMRI) has the potential to provide noninvasive functional mapping of the brain with high spatial and temporal resolution. However, fMRI independent components (ICs) must be manually inspected, selected, and interpreted, requiring time and expertise. We propose a novel approach for automated labeling of fMRI ICs by establishing their characteristic spatio-functional relationship. Methods: The approach identifies 9 resting-state networks and 45 ICs and generates a functional activation feature map that quantifies the spatial distribution, relative to an anatomical labeled atlas, of the z-scores of each IC across a cohort of 176 subjects. The cosine-similarity metric was used to classify unlabeled ICs based on the similarity to the spatial distribution of activation with the pregenerated feature map. The approach was tested on three fMRI datasets from the 1000 functional connectome projects, consisting of 280 subjects, that were not included in feature map generation. Results: The results demonstrate the effectiveness of the approach in classifying ICs based on their spatial features with an accuracy of better than 95%. Conclusions: The approach significantly reduces expert time and computation time required for labeling ICs, while improving reliability and accuracy. The spatio-functional relationship also provides an explainable relationship between the functional activation and the anatomically defined regions.

Age-related changes in ventrolateral prefrontal cortex activation are associated with daily prosocial behaviors two years later

As adolescents acquire agency and become contributing members of society, it is necessary to understand how they help their community. Yet, it is unknown how prosocial behavior develops in the context of community-based prosocial behaviors that are relevant to adolescents, such as donating time to charities. In this longitudinal functional magnetic resonance imaging study, adolescents (N=172; mean age at wave 1=12.8) completed a prosocial task annually for three years (N=422 and 375 total behavioral and neural data points, respectively), and 14 days of daily diaries reporting on their prosocial behaviors two years later. During the task, adolescents decided how many minutes they would donate to a variety of local charities. We found that adolescents donated less time to charities from early to mid adolescence. Longitudinal whole-brain analyses revealed declines in ventrolateral prefrontal cortex (vlPFC) activation, as well as inverted U-shaped changes in precuneus activation when adolescents donated their time from early to mid adolescence. A less steep decrease in vlPFC activation predicted greater real-life prosocial behaviors in youth's daily lives two years later. Our study elucidates the neurodevelopmental mechanisms of prosocial behavior from early to mid adolescence that have enduring effects on daily prosocial behaviors in late adolescence.

Neural Tracking of Perceived Parent, but Not Peer, Norms Is Associated with Longitudinal Changes in Adolescent Attitudes about Externalizing Behaviors

Adolescents' perceptions of parent and peer norms about externalizing behaviors influence the extent to which they adopt similar attitudes, yet little is known about how the trajectories of perceived parent and peer norms are related to trajectories of personal attitudes across adolescence. Neural development of midline regions implicated in self-other processing may underlie developmental changes in parent and peer influence. Here, we examined whether neural processing of perceived parent and peer norms in midline regions during self-evaluations would be associated with trajectories of personal attitudes about externalizing behaviors. Trajectories of adolescents' perceived parent and peer norms were examined longitudinally with functional neuroimaging (n = 165; ages 11-16 years across three waves; 86 girls, 79 boys; 29.7% White, 21.8% Black, 35.8% Latinx, 12.7% other/multiracial). Behavioral results showed perceived parent norms were less permissive than adolescents' own attitudes about externalizing behaviors, whereas perceived peer norms were more permissive than adolescents' own attitudes, effects that increased from early to middle adolescence. Although younger adolescents reported less permissive attitudes when they spontaneously tracked perceived parent norms in the ventromedial and medial pFCs during self-evaluations, this effect weakened as they aged. No brain-behavior effects were found when tracking perceived peer norms. These findings elucidate how perceived parent and peer norms change in parallel with personal attitudes about externalizing behaviors from early to middle adolescence and underscore the importance of spontaneous neural tracking of perceived parent norms during self-evaluations for buffering permissive personal attitudes, particularly in early adolescence.

Neurobiological sensitivity to popular peers moderates daily links between social media use and affect

Social media behaviors increase during adolescence, and quantifiable feedback metrics (e.g., likes, followers) may amplify the value of social status for teens. Social media's impact on adolescents' daily affect may be exacerbated given the neurodevelopmental changes that increase youths' sensitivity to socio-emotional information. This study examines whether neurobiological sensitivity to popularity moderates daily links between social media use and affect. Adolescents (N = 91, Mage=13.6 years, SDage=0.6 years) completed an fMRI task in which they viewed faces of their high (>1 SD above the mean) and low (<1 SD below the mean) popular peers based on peer-nominated sociometric ratings from their school social networks. Two years later, adolescents reported their time spent on social media and affect daily for two weeks. Neural tracking of popularity in the ventromedial and dorsomedial prefrontal cortex moderated the association between time on social media and affect. Specifically, adolescents who tracked high popular peers in the vmPFC reported more positive affect on days when they used social media more. Adolescents who tracked low popular peers in the vmPFC and dmPFC reported more negative affect on days when they used social media more. Results suggest that links between social media and affect depend on individual differences in neural sensitivity to popularity.

Friendship changes differentially predict neural correlates of decision-making for friends across adolescence

Adolescents' peer world is highly dynamic with constant dissolution of old friendships and formation of new ones. Though many of adolescents' risky decisions involve their peers, little is known about how adolescents' ever-changing friendships shape their ability to make these peer-involving risky decisions, particularly adaptive ones, and whether this association shifts over time. In a 5-wave longitudinal fMRI study, 173 adolescents (at wave 1: Mage = 12.8, SDage = 0.52; range = 11.9-14.5) made risky choices to win money for their best friend. We assessed whether participants nominated the same or different best friend as their previous participation year (a total of 340 data points of friendship maintenance / change). In early adolescence, adolescents with the same best friend took more adaptive risks for that best friend than those with a different best friend. In late adolescence, however, adolescents with a different best friend took more adaptive risks for the new best friend than those with the same best friend. Further, the amygdala was differentially sensitive to friendship maintenance / change during these peer-involving adaptive risks across time. This study has implications for how stable and flexible peer landscapes differentially modulate social motivation and social decision-making over the course of adolescence.

Adolescents' neural sensitivity to high and low popularity: Longitudinal links to risk-taking and prosocial behavior

Adolescents are particularly attuned to popularity within peer groups, which impacts behaviors such as risk-taking and prosocial behavior. Neurodevelopmental changes orient adolescents toward salient social cues in their environment. We examined whether neural regions that track popularity are associated with longitudinal changes in risk-taking and prosocial behavior. During an fMRI scan, adolescents (n = 109, Mage=13.59, SD=0.59) viewed pictures of their popular and unpopular classmates based on sociometric nominations from their social networks. Neural tracking of high popularity in the dorsomedial prefrontal cortex was associated with increases in risk-taking behavior, whereas tracking of low popularity in the right insula was associated with increases in prosocial behavior. Results suggest that individual differences in neural tracking of popularity relate to longitudinal changes in adolescents' social behaviors.

Detection of autism spectrum disorder using graph representation learning algorithms and deep neural network, based on fMRI signals

Introduction

Can we apply graph representation learning algorithms to identify autism spectrum disorder (ASD) patients within a large brain imaging dataset? ASD is mainly identified by brain functional connectivity patterns. Attempts to unveil the common neural patterns emerged in ASD are the essence of ASD classification. We claim that graph representation learning methods can appropriately extract the connectivity patterns of the brain, in such a way that the method can be generalized to every recording condition, and phenotypical information of subjects. These methods can capture the whole structure of the brain, both local and global properties.

Methods

The investigation is done for the worldwide brain imaging multi-site database known as ABIDE I and II (Autism Brain Imaging Data Exchange). Among different graph representation techniques, we used AWE, Node2vec, Struct2vec, multi node2vec, and Graph2Img. The best approach was Graph2Img, in which after extracting the feature vectors representative of the brain nodes, the PCA algorithm is applied to the matrix of feature vectors. The classifier adapted to the features embedded in graphs is an LeNet deep neural network.

Results and discussion

Although we could not outperform the previous accuracy of 10-fold cross-validation in the identification of ASD versus control patients in this dataset, for leave-one-site-out cross-validation, we could obtain better results (our accuracy: 80%). The result is that graph embedding methods can prepare the connectivity matrix more suitable for applying to a deep network.

Positive risk taking and neural sensitivity to risky decision making in adolescence

This study examines associations between adolescents' positive risk taking and neural activation during risky decision-making. Participants included 144 adolescents ages 13-16 years (Mage = 14.23; SDage = 0.7) from diverse racial and ethnic groups. Participants self-reported their engagement in positive and negative risk taking. Additionally, participants played the Cups task during fMRI, where they chose between a safe choice (guaranteed earning of 15 cents) and a risky choice (varying probabilities of earning more than 15 cents). Using a risk-return framework, we examined adolescents' sensitivity to both risks (safe versus risky) and returns (expected value, or potential reward as a function of its probability of occurring) at the behavioral and neural levels. All participants took more risks when the expected value of the choice was high. However, high positive risk taking was uniquely associated with dampened dmPFC tracking of expected value. Together, results show that adolescents' positive risk taking is associated with neural activity during risky decision-making. Findings are among the first to identify brain-behavior correlations associated with positive risk taking during adolescence.

Classification-guided Neural Network-based Correction of Magnetic Resonance-related Gradient Artifact Residuals in Simultaneously Recorded Surface Electromyography

Spontaneous muscular activities can be studied by simultaneous recordings of surface electromyography (sEMG) and diffusion-weighted magnetic resonance imaging (DW-MRI). For reliable assessment of the spontaneous activity rate in sEMG data during active MR imaging, it is necessary to have a decent gradient artifact (GA) correction algorithm enabling the detection of small spontaneous activities with an amplitude of few microvolts. In this work, a neural network with weak label annotations during the training process is utilized for enhanced correction of GA residuals in the sEMG recordings. Based on sEMG signal decomposition and class-activation maps from the neural network classification, the amount of GA residuals is iteratively decreased in the sEMG signal. This leads to a reduction of the false-positive rate in automated spontaneous activity detection. Quality of GA residual correction is therefore estimated by using a specialized second neural network model. Clinical relevance- This work establishes an improved GA residual correction for simultaneously recorded sEMG data during MRI to enhance the ability for small spontaneous activity detection.

Neural connectivity underlying adolescent social learning in sibling dyads

Social learning theory posits that adolescents learn to adopt social norms by observing the behaviors of others and internalizing the associated outcomes. However, the underlying neural processes by which social learning occurs is less well-understood, despite extensive neurobiological reorganization and a peak in social influence sensitivity during adolescence. Forty-four adolescents (Mage = 12.2 years) completed an fMRI scan while observing their older sibling within four years of age (Mage = 14.3 years) of age complete a risky decision-making task. Group iterative multiple model estimation (GIMME) was used to examine patterns of directional brain region connectivity supporting social learning. We identified group-level neural pathways underlying social observation including the anterior insula to the anterior cingulate cortex and mentalizing regions to social cognition regions. We also found neural states based on adolescent sensitivity to social learning via age, gender, modeling, differentiation, and behavior. Adolescents who were more likely to be influenced elicited neurological up-regulation whereas adolescents who were less likely to be socially influenced elicited neurological down-regulation during risk-taking. These findings highlight patterns of how adolescents process information while a salient influencer takes risks, as well as salient neural pathways that are dependent on similarity factors associated with social learning theory.

A comprehensive investigation of physiologic noise modeling in resting state fMRI; time shifted cardiac noise in EPI and its removal without external physiologic signal measures

Hemodynamic cardiac and respiratory-cycle fluctuations are a source of unwanted non-neuronal signal components, often called physiologic noise, in resting state (rs-) fMRI studies. Here, we use image-based retrospective correction of physiological motion (RETROICOR) with externally measured physiologic signals to investigate cardiac and respiratory hemodynamic phase functions reflected in rs-fMRI data. We find that the cardiac phase function is time shifted locally, while the respiratory phase function is described as single, fixed phase form across the brain. In light of these findings, we propose an update to Physiologic EStimation by Temporal ICA (PESTICA), our publically available software package that estimates physiologic signals when external physiologic measures are not available. This update incorporates: 1) auto-selection of slicewise physiologic regressors and generation of physiologic fixed phase regressors with total slices/TR sampling rate, 2) Fourier series expansion of the cardiac fixed phase regressor to account for time delayed cardiac noise 3) removal of cardiac and respiratory noise in imaging data. We compare the efficacy of the updated method to RETROICOR.

Deep Attentive Spatio-Temporal Feature Learning for Automatic Resting-State fMRI Denoising

Resting-state functional magnetic resonance imaging (rs-fMRI) is a non-invasive functional neuroimaging modality that has been widely used to investigate functional connectomes in the brain. Since noise and artifacts generated by non-neuronal physiological activities are predominant in raw rs-fMRI data, effective noise removal is one of the most important preprocessing steps prior to any subsequent analysis. For rs-fMRI denoising, a common trend is to decompose rs-fMRI data into multiple components and then regress out noise-related components. Therefore, various machine learning techniques have been used in such analyses with predefined procedures and manually engineered features. However, the lack of a universal definition of a noise-related source or artifact complicates manual feature engineering. Manual feature selection can result in the failure to capture unknown types of noise. Furthermore, the possibility that the hand-crafted features will only work for the broader population (e.g., healthy adults) but not for "outliers" (e.g., infants or subjects that belong to a disease cohort) is quite high. In practice, we have limited knowledge of which features should be extracted; thus, multi-classifier assembly must be implemented to improve performance, although this process is quite time-consuming. However, in real rs-fMRI applications, fast and accurate automatic identification of noise-related components on different datasets is critical. To solve this problem, we propose a novel, automatic, and end-to-end deep learning framework dedicated to noise-related component identification via a faster and more effective multi-layer feature extraction strategy that learns deeply embedded spatio-temporal features of the components. In this study, we achieved remarkable performance on various rs-fMRI datasets, including multiple adult rs-fMRI datasets from different rs-fMRI studies and an infant rs-fMRI dataset, which is quite heterogeneous and differs from that of adults. Our proposed framework also dramatically increases the noise detection speed owing to its inherent ability for deep learning (< 1s for single-component classification). It can be easily integrated into any preprocessing pipeline, even those that do not use standard procedures but depend on alternative toolboxes.

Intranasal Oxytocin Modulates the Salience Network in Aging

Growing evidence supports a role of the neuropeptide oxytocin in promoting social cognition and prosocial behavior, possibly via modulation of the salience of social information. The effect of intranasal oxytocin administration on the salience network, however, is not well understood, including in the aging brain. To address this research gap, 42 young (22.52 ± 3.02 years; 24 in the oxytocin group) and 43 older (71.12 ± 5.25 years; 21 in the oxytocin group) participants were randomized to either self-administer intranasal oxytocin or placebo prior to resting-state functional imaging. The salience network was identified using independent component analysis (ICA). Independent t-tests showed that individuals in the oxytocin compared to the placebo group had lower within-network resting-state functional connectivity, both for left amygdala (MNI coordinates: x = −18, y = 0, z = −15; corrected p < 0.05) within a more ventral salience network and for right insula (MNI coordinates: x = 39, y = 6, z = −6; corrected p < 0.05) within a more dorsal salience network. Age moderation analysis furthermore demonstrated that the oxytocin-reduced functional connectivity between the ventral salience network and the left amygdala was only present in older participants. These findings suggest a modulatory role of exogenous oxytocin on resting-state functional connectivity within the salience network and support age-differential effects of acute intranasal oxytocin administration on this network.

An Approach to Automatically Label and Order Brain Activity/Component Maps

Background: Functional magnetic resonance imaging (fMRI) is a brain imaging technique that provides detailed insights into brain function and its disruption in various brain disorders. The data-driven analysis of fMRI brain activity maps involves several postprocessing steps, the first of which is identifying whether the estimated brain network maps capture signals of interest, for example, intrinsic connectivity networks (ICNs), or artifacts. This is followed by linking the ICNs to standardized anatomical and functional parcellations. Optionally, as in the study of functional network connectivity (FNC), rearranging the connectivity graph is also necessary to facilitate interpretation. Methods: Here we develop a novel and efficient method (Autolabeler) for implementing and integrating all of these processes in a fully automated manner. The Autolabeler method is pretrained on a cross-validated elastic-net regularized general linear model from the noisecloud toolbox to separate neuroscientifically meaningful ICNs from artifacts. It is capable of automatically labeling activity maps with labels from several well-known anatomical and functional parcellations. Subsequently, this method also maximizes the modularity within functional domains to generate a more systematically structured FNC matrix for post hoc network analyses. Results: Results show that our pretrained model achieves 86% accuracy at classifying ICNs from artifacts in an independent validation data set. The automatic anatomical and functional labels also have a high degree of similarity with manual labels selected by human raters. Discussion: At a time of ever-increasing rates of generating brain imaging data and analyzing brain activity, the proposed Autolabeler method is intended to automate such analyses for faster and more reproducible research. Impact statement Our proposed method is capable of implementing and integrating some of the crucial tasks in functional magnetic resonance imaging (fMRI) studies. It is the first to incorporate such tasks without the need for expert intervention. We develop an open-source toolbox for the proposed method that can function as stand-alone software and additionally provides seamless integration with the widely used group independent component analysis for fMRI toolbox (GIFT). This integration can aid investigators to conduct fMRI studies in an end-to-end automated manner.

Toddler-Mother Attachment Moderates Adolescents' Behavioral and Neural Evaluation of Trustworthiness

This longitudinal study examined the prospective association between toddler–mother attachment to adolescents’ (n = 52; 34 boys; M_age = 13.22 years; 90% White) behavioral and neural responses during the evaluation of trustworthiness from unfamiliar, emotionally neutral faces. At 33 months, toddler–mother attachment status (secure vs insecure classification) was assessed using a modified Strange Situation procedure. Results revealed that attachment moderated the processing of trustworthiness facial cues. As faces became less trustworthy, adolescents with a secure (vs insecure) attachment history rated the faces as correspondingly less trustworthy and showed increasing (vs overall blunted) activation in brain regions involved in trustworthiness perception (i.e. bilateral amygdala, bilateral fusiform, right anterior insula and right posterior superior temporal sulcus). Findings suggest that a secure compared with insecure child–mother attachment in toddlerhood may be associated with greater capacity for, or openness to, processing potentially negative social information at both the behavioral and neural levels during adolescence.

The role of early attachment and parental presence in adolescent behavioral and neurobiological regulation

Early attachment shapes brain development underlying emotion regulation. Given that sensitivity to affective cues is heightened during adolescence and effective emotion regulation strategies continue to develop, it is imperative to examine the role of early attachment and parental influence on adolescent regulation. Fifty-one children (M age=32.61 months) participated in a modified Strange Situation with their mother and approximately 10 years later (M age =13.2 years) completed an fMRI scan during which they were presented with appetitive and aversive affective cues (images of adolescent interactions) during a Go-Nogo task. They completed the task alone and in the presence of a parent. Behavioral multilevel models and whole-brain analyses showed attachment-related patterns, such that affective cues elicited greater behavioral and neural dysregulation in insecure (versus secure) adolescents.Furthermore, parental presence buffered behavioral and neural dysregulation toward socially aversive cues for adolescents with early insecure attachment, underscoring the salience of caregivers across development in promoting regulation in their offspring.

Automated pipeline for EEG artifact reduction (APPEAR) recorded during fMRI

Objective.Simultaneous electroencephalography-functional magnetic resonance imaging (EEG-fMRI) recordings offer a high spatiotemporal resolution approach to study human brain and understand the underlying mechanisms mediating cognitive and behavioral processes. However, the high susceptibility of EEG to MRI-induced artifacts hinders a broad adaptation of this approach. More specifically, EEG data collected during fMRI acquisition are contaminated with MRI gradients and ballistocardiogram artifacts, in addition to artifacts of physiological origin. There have been several attempts for reducing these artifacts with manual and time-consuming pre-processing, which may result in biasing EEG data due to variations in selecting steps order, parameters, and classification of artifactual independent components. Thus, there is a strong urge to develop a fully automatic and comprehensive pipeline for reducing all major EEG artifacts. In this work, we introduced an open-access toolbox with a fully automatic pipeline for reducing artifacts from EEG data collected simultaneously with fMRI (refer to APPEAR).Approach.The pipeline integrates average template subtraction and independent component analysis to suppress both MRI-related and physiological artifacts. To validate our results, we tested APPEAR on EEG data recorded from healthy control subjects during resting-state (n= 48) and task-based (i.e. event-related-potentials (ERPs);n= 8) paradigms. The chosen gold standard is an expert manual review of the EEG database.Main results.We compared manually and automated corrected EEG data during resting-state using frequency analysis and continuous wavelet transformation and found no significant differences between the two corrections. A comparison between ERP data recorded during a so-called stop-signal task (e.g. amplitude measures and signal-to-noise ratio) also showed no differences between the manually and fully automatic fMRI-EEG-corrected data.Significance.APPEAR offers the first comprehensive open-source toolbox that can speed up advancement of EEG analysis and enhance replication by avoiding experimenters' preferences while allowing for processing large EEG-fMRI cohorts composed of hundreds of subjects with manageable researcher time and effort.

Social neural sensitivity as a susceptibility marker to family context in predicting adolescent externalizing behavior

Adolescence represents a period of risk for developing patterns of risk-taking and conduct problems, and the quality of the family environment is one robust predictor of such externalizing behavior. However, family factors may not affect all youth uniformly, and individual differences in neurobiological susceptibility to the family context may moderate its influence. The current study investigated brain-based individual differences in social motivational processing as a susceptibility marker to family conflict in predicting externalizing behavior in early adolescent youth. 163 adolescents (M_age = 12.87 years) completed an fMRI scan during which they anticipated social rewards and social punishments. For adolescents with heightened ventral striatum and amygdala blood oxygen-level dependent (BOLD) response during the anticipation of social rewards and heightened ventral striatum BOLD response during the anticipation of social punishments, higher levels of family conflict were associated with greater externalizing behavior. BOLD response when anticipating both social rewards and punishments suggested increased susceptibility to maladaptive family contexts, highlighting the importance of considering adolescent social motivation in positive and negatively valenced contexts.

Self-Oriented Neural Circuitry Predicts Other-Oriented Adaptive Risks in Adolescence: A Longitudinal Study

Adolescence is marked by changes in decision-making and perspective-taking abilities. Although adolescents make more adaptive decisions with age, little is understood about how adolescents take adaptive risks that impact others and how this behavior changes developmentally. Functional coupling between reward [e.g., ventral striatum (VS)] and ‘social brain’ [e.g. temporal parietal junction (TPJ)/ posterior superior temporal sulcus (pSTS), medial prefrontal cortex (mPFC)] systems may be differentially shape adaptive risks for the self and other. A total of 173 participants completed between one and three sessions across three waves [a total of 433 behavioral and 403 functional magnetic resonance imaging (fMRI) data points]. During an fMRI scan, adolescents completed a risky decision-making task where they made risky decisions to win money for themselves and their parent. The risky decisions varied in their expected value (EV) of potential reward. Results show that from the 6th through 9th grades, adolescents took increasingly more adaptive risks for themselves than for their parent. Additionally, greater VS–TPJ/pSTS and VS–mPFC connectivity that tracks EV when making risky decisions for themselves in 6th grade, but a lower VS–mPFC connectivity in 9th grade, predicted greater adaptive risk-taking for their parent. This study contributes to our understanding of the self as a neural proxy for promoting adaptive social behaviors in youth.

4D Modeling of fMRI Data via Spatio-Temporal Convolutional Neural Networks (ST-CNN)

Since the human brain functional mechanism has been enabled for investigation by the functional Magnetic Resonance Imaging (fMRI) technology, simultaneous modeling of both the spatial and temporal patterns of brain functional networks from 4D fMRI data has been a fundamental but still challenging research topic for neuroimaging and medical image analysis fields. Currently, general linear model (GLM), independent component analysis (ICA), sparse dictionary learning, and recently deep learning models, are major methods for fMRI data analysis in either spatial or temporal domains, but there are few joint spatial-temporal methods proposed, as far as we know. As a result, the 4D nature of fMRI data has not been effectively investigated due to this methodological gap. The recent success of deep learning applications for functional brain decoding and encoding greatly inspired us in this work to propose a novel framework called spatio-temporal convolutional neural network (ST-CNN) to extract both spatial and temporal characteristics from targeted networks jointly and automatically identify of functional networks. The identification of Default Mode Network (DMN) from fMRI data was used for evaluation of the proposed framework. Results show that only training the framework on one fMRI dataset is sufficiently generalizable to identify the DMN from different datasets of different cognitive tasks and resting state. Further investigation of the results shows that the joint-learning scheme can capture the intrinsic relationship between the spatial and temporal characteristics of DMN and thus it ensures the accurate identification of DMN from independent datasets. The ST-CNN model brings new tools and insights for fMRI analysis in cognitive and clinical neuroscience studies.

Integrated 3D motion analysis with functional magnetic resonance neuroimaging to identify neural correlates of lower extremity movement

BACKGROUND

To better understand the neural drivers of aberrant motor control, methods are needed to identify whole brain neural correlates of isolated joints during multi-joint lower-extremity coordinated movements. This investigation aimed to identify the neural correlates of knee kinematics during a unilateral leg press task.

NEW METHOD

The current study utilized an MRI-compatible motion capture system in conjunction with a lower extremity unilateral leg press task during fMRI. Knee joint kinematics and brain activity were collected concurrently and averaged range of motion were modeled as covariates to determine the neural substrates of knee out-of-plane (frontal) and in-plane (sagittal) range of motion.

RESULTS

Increased out-of-plane (frontal) range of motion was associated with altered brain activity in regions important for attention, sensorimotor control, and sensorimotor integration (z >3.1, p < .05), but no such correlates were found with in-plane (sagittal) range of motion (z >3.1, p > .05). Comparison with Existing Method(s): Previous studies have either presented overall brain activation only, or utilized biomechanical data collected outside MRI in a standard biomechanics lab for identifying single-joint neural correlates.

CONCLUSIONS

The study shows promise for the MRI-compatible system to capture lower-extremity biomechanical data collected concurrently during fMRI, and the present data identified potentially unique neural drivers of aberrant biomechanics. Future research can adopt these methods for patient populations with CNS-related movement disorders to identify single-joint kinematic neural correlates that may adjunctively supplement brain-body therapeutic approaches.

Neural Correlates of Conflicting Social Influence on Adolescent Risk Taking

Adolescence is often characterized by heightened risk-taking behaviors, which are shaped by social influence from parents and peers. However, little is understood about how adolescents make risky decisions under conflicting influence. The valuation system in the brain may elucidate how adolescents differentially integrate conflicting social information. Twenty-eight adolescents (M_age  = 12.7 years) completed a social influence task during a functional magnetic resonance imaging scan. Behaviorally, adolescents took more risks only when their parent endorsed risky decisions but not when their peers endorsed risky decisions. At the neural level, adolescents showed enhanced vmPFC-striatum functional connectivity when they made risky decisions that followed their parents' risky decisions. Results suggest that parents' decisions may guide youths' risk-taking behavior under conflicting influence.

Hormonal and neural correlates of prosocial conformity in adolescents

The dual hormone hypothesis, which centers on the interaction between testosterone and cortisol on social behavior, offers a compelling framework for examining the role of hormones on the neural correlates of adolescent peer conformity. Expanding on this hypothesis, the present study explored the interaction between testosterone and cortisol via hair concentrations on adolescents' conformity to peers. During fMRI, 136 adolescents (51 % female) ages 11-14 years (M = 12.32; SD = 0.6) completed a prosocial decision-making task. Participants chose how much of their time to donate to charity before and after observing a low- or high-prosocial peer. Conformity was measured as change in behavior pre- to post-observation. High testosterone with low cortisol was associated with greater conformity to high-prosocial peers but not low prosocial peers. Focusing on high prosocial peers, whole-brain analyses indicated greater activation post- vs. pre-observation as a function of high testosterone and low cortisol in regions implicated in social cognition, salience detection, and reward processing: pSTS/TPJ, insula, OFC, and caudate nucleus. Results highlight the relevance of hormones for understanding the neural correlates of adolescents' conformity to prosocial peers.

Acute exercise, memory, and neural activation in young adults

Acute exercise benefits memory, and the temporal placement of exercise relative to exposure can affect the magnitude of benefits observed. Although the temporal placement appears to be important, there is a limited understanding as to how cognitive benefits in response to acute exercise are achieved. Hence, we conducted a two-part study including a behavioral study and a follow-up functional magnetic resonance imaging (fMRI) study to advance our understanding of the potential role of the effects of exercise on memory and neural activation. For Study One, we assessed the effect of acute exercise on memory in young adults. Participants were randomized to exercise before exposure for 20 min (before only, BO), after exposure for 20 min (After Only, AO), before and after exposure for 10 min at each time (before and after, BA), or to receive no exercise (No-exercise Control, NC). Similar to previous findings, any exercise prior to exposure (BO, BA) benefited some aspects of memory performance. Interestingly, the more consistent and larger benefits were seen with a shorter duration of exercise both before and after exposure (BA). Study Two replicated the methods of Study One comparing the BA condition (which had the most robust benefits) to the NC condition while collecting fMRI data during the memory task. Analyses assessed condition differences of activation during encoding and recall. There were no condition differences during memory encoding, however there was a condition effect on activation in occipito-temporal regions during the memory recall trials. Consistent with previous research, exercise appears to benefit memory with some exercise prior to exposure being important for the benefits achieved. Further, exercise affects neural activation and the results appear complementary to the behavior findings. Future research should use a within-subjects design to control for heterogeneity in behavior and neural activation.

Neurobiological Sensitivity to Social Rewards and Punishments Moderates Link Between Peer Norms and Adolescent Risk Taking

Although peer influence is a strong predictor of adolescents' risk-taking behaviors, not all adolescents are susceptible to their peer group. One hundred and thirty-six adolescents (M_age  = 12.79 years) completed an fMRI scan, measures of perceived peer group norms, and engagement in risky behavior. Ventral striatum (VS) sensitivity when anticipating social rewards and avoiding social punishments significantly moderated the association between perceived peer norms and adolescents' own risk behaviors. Perceptions of more deviant peer norms were associated with increased risky behavior, but only for adolescents with high VS sensitivity; adolescents with low VS sensitivity were resilient to deviant peer norms, showing low risk taking regardless of peer context. Findings provide a novel contribution to the study of peer influence susceptibility.

A novel spatiotemporal tool for the automatic classification of fMRI noise based on Independent Component Analysis

In this study, a semi-automatic, easy-to-use classification method for the identification and removal of fMRI noise is proposed and tested. The method relies on subject-level spatial independent component analysis (ICA) of fMRI data. Starting from a reference set of labeled independent components (ICs), novel ICs are classified as physiological/artefactual by combining a spatial correlation (SC) analysis with the reference ICs and relative power spectral (PS) analysis. Here, ICs from a task-based fMRI dataset were used as reference. SC and SP thresholds were set using a test dataset (5 subjects, same fMRI protocol) based on Receiving Operating Characteristic curves. The tool performance and versatility were measured on a resting-state fMRI dataset (5 subjects). Our results show that the method can automatically identify noise-related ICs with accuracy, specificity and sensitivity higher than 80% across different fMRI protocols. These findings also suggest that the reference set provided in the present study might be used to mark ICs coming from independent taskrelated or resting-state fMRI datasets.Clinical relevance- The new method will be included in a userfriendly, open-source tool for removal of noisy contributions from fMRI datasets to be used in clinical and research practices.

Differential Behavioral and Neural Profiles in Youth With Conduct Problems During Risky Decision-Making

Neuroimaging work has examined neural processes underlying risk taking in adolescence, yet predominantly in low-risk youth. To determine whether we can extrapolate from current neurobiological models, this functional magnetic resonance imaging study investigated risk taking and peer effects in youth with conduct problems (CP; N = 19) and typically developing youth (TD; N = 25). Results revealed higher real-life risk taking, lower risky decisions, and no peer effects on a risk-taking task in CP youth. CP youth showed greater ventral striatum (VS) activity during safe than risky decisions, whereas TD youth showed greater VS activation during risky decisions. Differential VS activity explained higher real-life risk taking in CP youth. Findings provide preliminary evidence that risk-taking behavior in youth with CD problems is characterized by differential neural patterns.

Neural sensitivity to conflicting attitudes supports greater conformity toward positive over negative influence in early adolescence

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Early adolescents show overall low rates of conformity to conflicting attitudes.

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Adolescents conform more to peers’ attitudes towards constructive than unconstructive behaviors.

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Adolescents conform more when parents and peers endorsed positive than negative influence.

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vmPFC, dACC, and TPJ activity may underlie context-dependent conformity differences.

Adolescents often need to reconcile discrepancies between their own attitudes and those of their parents and peers, but the social contexts under which adolescents conform to the attitudes of others, or the neurocognitive processes underlying decisions to conform, remain unexplored. This fMRI study assessed the extent to which early adolescents (n = 39, ages 12–14) conform to their parents’ and peers’ conflicting attitudes toward different types of behavior (unconstructive and constructive) and in response to different types of influence (negative and positive). Overall, adolescents exhibited low rates of conformity, sticking with their pre-existing attitudes 65 % of the time. When they did conform, adolescents were more likely to conform to their peers’ attitudes towards constructive than unconstructive behaviors, exhibiting decreased activation in the ventromedial prefrontal cortex, dorsal anterior cingulate cortex, insula, and inferior frontal gyrus during peer conformity toward constructive over unconstructive behaviors. Adolescents were also more likely to conform when their parents and peers endorsed relatively more positive influence than negative influence, exhibiting increased activation in the temporoparietal junction when considering conforming to negative over positive influence. These results highlight early adolescents’ ability to stick with their own opinions when confronted with opposing attitudes and conform selectively based on the social context.

Dynamic brain connectivity attuned to the complexity of relative clause sentences revealed by a single-trial analysis

To explore the issue of how the human brain processes sentences with different levels of complexity, we sought to compare the neural substrates underlying the processing of Chinese subject-extracted relative clause (SRC) and object-extracted relative clause (ORC) sentences in a trial-by-trial fashion. Previous neuroimaging studies have demonstrated that the involvement of the left inferior frontal gyrus (LIFG) and the left superior temporal gyrus (LSTG) is critical for the processing of relative clause (RC) sentences. In this study, we employed independent component analysis (ICA) to decompose brain activity into a set of independent components. Then, the independent component maps were spatially normalized using a surface-based approach in order to further spatially correlate and match the equivalent components from individual participants. The selected equivalent components indicated that the LIFG and the LSTG were consistently engaged in sentence processing among the participants. Subsequently, we observed alterations in the functional coupling between the LIFG and the LSTG in response to SRCs and ORCs using a Granger causality analysis. Specifically, comprehending Chinese ORCs with a canonical word order only involved a unidirectional connection from the LIFG to the LSTG for the integration of lexical-syntactic information. On the other hand, comprehending Chinese SRCs required bi-directional connectivity between the LIFG and the LSTG to fulfill increased integration demands in reconstructing the argument hierarchy due to a non-canonical word order. Furthermore, through a single-trial analysis, the strength of the connectivity from the LIFG to the LSTG was found to be significantly correlated with the complexity of the SRC sentences as quantified by eye-tracking measures. These findings indicated that the effective connectivity from the LIFG to the LSTG played an important role in the comprehension of complex sentences and that enhanced strength of this connectivity might reflect increased integration demands and restructuring attempts during sentence processing. Taken together, the results of the present study reveal that interregional interaction in the brain network for sentence processing can be dynamically engaged in response to different levels of complexity and also shed some light on the interpretation of neuroimaging and behavioral evidence when accounting for the nature of sentence complexity during reading.

Functional Dissociations of the Left Anterior and Posterior Occipitotemporal Cortex for Semantic and Non-semantic Phonological Access

Previous studies have identified the ventral and dorsal brain regions that respectively support semantic and non-semantic phonological access. Nevertheless, the specific role of the left occipitotemporal cortex (lOTC) in the two pathways of phonological access is ambiguous. To address that question, the present study compared word reading in Chinese (presumably relying on the semantic pathway) with that in English (presumably relying on the non-semantic pathway). Results revealed a clear dissociation in the involvement of the anterior and posterior lOTC in semantic and non-semantic phonological access. Specifically, the anterior lOTC showed greater activation for Chinese than for English, whereas the posterior lOTC showed greater activation for English than for Chinese. More importantly, both psychophysiological interaction analysis and resting-state functional connectivity analysis showed that the anterior lOTC was functionally connected to the ventral brain regions (e.g., left anterior fusiform gyrus, anterior temporal lobe, and ventral inferior frontal gyrus), whereas the posterior lOTC was functionally connected to the dorsal brain regions (e.g., left posterior superior temporal gyrus, supramarginal gyrus, and dorsal inferior frontal gyrus). These results suggest that the anterior and posterior lOTC are involved in semantic and non-semantic phonological access, respectively.

Neural Representation of Parental Monitoring and Links to Adolescent Risk Taking

Decades of developmental research have demonstrated the positive role of parental monitoring during adolescence, a time during which youth seek exploration and show heightened risk taking. The present study employed a novel neural pattern similarity approach to identify neural patterns underpinning parental monitoring, with attention to implications for adolescent risk taking. Mothers (N = 23) underwent an fMRI scan during which they completed a risk-taking task and viewed the risk-taking behavior of their adolescent child. Using a representational similarity analysis, we examined the neural pattern similarity between mothers’ anticipation of their child’s risk taking and their own decisions. Higher parental monitoring was reflected in greater similarity between neural pattern of anticipating their adolescents’ risk taking and experiencing their own safe outcomes. Moreover, greater neural pattern similarity between mothers’ anticipation and their own safe outcomes was associated with lower risk-taking propensity in adolescents. Taken together, the present study provides preliminary evidence for the neural patterns underpinning parental monitoring, highlighting the importance of incorporating parents’ brain as a window to understand parenting practices and adolescent risk taking.

Reshaping cortical activity with subthalamic stimulation in Parkinson's disease during finger tapping and gait mapped by near infrared spectroscopy

Exploration of motor cortex activity is essential to understanding the pathophysiology in Parkinson's Disease (PD), but only simple motor tasks can be investigated using a fMRI or PET. We aim to investigate the cortical activity of PD patients during a complex motor task (gait) to verify the impact of deep brain stimulation in the subthalamic nucleus (DBS-STN) by using Near-Infrared-Spectroscopy (NIRS). NIRS is a neuroimaging method of brain cortical activity using low-energy optical radiation to detect local changes in (de)oxyhemoglobin concentration. We used a multichannel portable NIRS during finger tapping (FT) and gait. To determine the signal activity, our methodology consisted of a pre-processing phase for the raw signal, followed by statistical analysis based on a general linear model. Processed recordings from 9 patients were statistically compared between the on and off states of DBS-STN. DBS-STN led to an increased activity in the contralateral motor cortex areas during FT. During gait, we observed a concentration of activity towards the cortex central area in the "stimulation-on" state. Our study shows how NIRS can be used to detect functional changes in the cortex of patients with PD with DBS-STN and indicates its future use for applications unsuited for PET and a fMRI.

Resting State fMRI: Going Through the Motions

Resting state functional magnetic resonance imaging (rs-fMRI) has become an indispensable tool in neuroscience research. Despite this, rs-fMRI signals are easily contaminated by artifacts arising from movement of the head during data collection. The artifacts can be problematic even for motions on the millimeter scale, with complex spatiotemporal properties that can lead to substantial errors in functional connectivity estimates. Effective correction methods must be employed, therefore, to distinguish true functional networks from motion-related noise. Research over the last three decades has produced numerous correction methods, many of which must be applied in combination to achieve satisfactory data quality. Subject instruction, training, and mild restraints are helpful at the outset, but usually insufficient. Improvements come from applying multiple motion correction algorithms retrospectively after rs-fMRI data are collected, although residual artifacts can still remain in cases of elevated motion, which are especially prevalent in patient populations. Although not commonly adopted at present, “real-time” correction methods are emerging that can be combined with retrospective methods and that promise better correction and increased rs-fMRI signal sensitivity. While the search for the ideal motion correction protocol continues, rs-fMRI research will benefit from good disclosure practices, such as: (1) reporting motion-related quality control metrics to provide better comparison between studies; and (2) including motion covariates in group-level analyses to limit the extent of motion-related confounds when studying group differences.

Heart rate variability as a biomarker in health and affective disorders: A perspective on neuroimaging studies

The dynamic embodiment of psychological processes is evident in the association of health outcomes, behavioural traits and psychological functioning with Heart Rate Variability (HRV). The dominant high-frequency component of HRV is an index of the central neural control of heart rhythm, mediated via the parasympathetic vagus nerve. HRV provides a potential objective measure of action policies for the adaptive and predictive allostatic regulation of homeostasis within the cardiovascular system. In its support, a network of brain regions (referred to as the 'central autonomic network') maps internal state, and controls autonomic responses. This network includes regions of prefrontal cortex, anterior cingulate cortex, insula, amygdala, periaqueductal grey, pons and medulla. Human neuroimaging studies of neural activation and functional connectivity broadly endorse this architecture, and its link with cardiac regulation at rest and dysregulation in clinical states that include affective disorders. In this review, we appraise neuroimaging research and related evidence for HRV as an informative marker of autonomic integration with affect and cognition, taking a perspective on function and organisation. We consider evidence for the utility of HRV as a metric to inform targeted interventions to improve autonomic and affective dysregulation, and suggest research questions for further investigation.

Behavioral and Neural Dysregulation to Social Rewards and Links to Internalizing Symptoms in Adolescents

Adolescence is a time of unique sensitivity to socially salient stimuli such as social rewards. This period overlaps with the onset of psychopathology such as internalizing and externalizing symptoms. In the current studies, we examined behavioral and neural patterns of dysregulation to social rewards and threats, and links to internalizing and externalizing symptoms in youths. In study 1, we used a social Go/NoGo cognitive control task using peer faces to test for age-related behavioral differences in inhibitory failures in adolescents (N = 53, Mage = 13.37 years), and adults (N = 51, Mage = 43.71 years). In study 2, an independent adolescent sample (N = 51, Mage = 13.98 years) completed a similar social Go/NoGo cognitive control task during fMRI. Results show that adolescents had greater inhibitory failures - as measured by false alarm rate - to both social reward and threat cues than adults, and more so to social reward than threat cues. Greater inhibitory failures to social reward than threat cues were associated with greater internalizing symptoms, but were not significantly related to externalizing symptoms. At the neural level, greater inhibitory failures to social reward than threat cues as well as greater internalizing symptoms were both associated with heightened amygdala-ventral striatum connectivity. Our findings indicate that subcortico-subcortical connectivity, which is deemed to occur chronologically earlier and thus necessary for subcortico-cortical circuits, may serve as an early biomarker for emotion dysregulation and a risk factor for internalizing symptoms.

Alterations in adolescent dopaminergic systems as a function of early mother-toddler attachment: A prospective longitudinal examination

Early experiences have the potential for outsized influence on neural development across a wide number of domains. In humans, many of the most important such experiences take place in the context of the mother-child attachment relationship. Work from animal models has highlighted neural changes in dopaminergic systems as a function of early care experiences, but translational research in humans has been limited. Our goal was to fill this gap by examining the longitudinal associations between early attachment experiences (assessed at 2.5 years) and neural responses to risk and rewards during adolescence (assessed at 13 years). Adolescence is a developmental period where sensitivity to rewards has important implications for behavior and long-term outcomes, providing an important window to study potential influences of early attachment experiences on reward processing. In order to address this question, 50 adolescents completed a risk and reward task during an fMRI scan, allowing us to assess differences in neural sensitivity to changes in risk level and reward amount as a function of early attachment experiences. Adolescents with insecure attachment histories showed blunted sensitivity to increasing risk levels in regions of the dorsal striatum, while also showing heightened sensitivity to increasing reward levels in the same region. These results highlight the importance of early attachment experiences for long-term neural development. Specifically, early exposure to more maladaptive relationships with caregivers may confer dual risks prospectively for adolescents, sensitizing them to rewarding outcomes while de-sensitizing them to potential risks associated with those behaviors, perhaps due to stress-related dopaminergic changes early in development.

Culture Modulates the Neural Correlates Underlying Risky Exploration

Most research on cultural neuroscience focuses on one dimension of culture: group membership or individual orientation. However, it is especially important to examine the intersection between the two to better understand the acculturation process. To examine the role of culture in the neural correlates of risky exploration, the current study recruited 22 American and 24 Chinese international students. Participants reported on their independent self-construal, a measure defining the self in terms of emphasizing unique attributes, and underwent an functional magnetic resonance imaging (fMRI) scan while completing a risk-taking task. At the group level, American (vs. Chinese) participants showed greater risky exploration on the task. Moreover, while independent self-construal was not related to American individuals' behavioral performance and neural correlates of risky exploration, Chinese participants who reported greater independent self-construal recruited greater activation in regions of the cognitive control system [e.g., dorsolateral prefrontal cortex (DLPFC)] and affective system [e.g., anterior insula (AI)], which was related to greater risky exploration. Taken together, our findings suggest that culture as group membership and individual orientation may interact with each other and relate to neural systems underlying risky exploration. This study highlights the importance of studying the role of culture at both group and individual level, which is particularly critical to understand individuals as they acculturate to a new environment.

A comparison of denoising pipelines in high temporal resolution task-based functional magnetic resonance imaging data

It has been known for decades that head motion/other artifacts affect the blood oxygen level-dependent signal. Recent recommendations predominantly focus on denoising resting state data, which may not apply to task data due to the different statistical relationships that exist between signal and noise sources. Several blind-source denoising strategies (FIX and AROMA) and more standard motion parameter (MP) regression (0, 12, or 24 parameters) analyses were therefore compared across four sets of event-related functional magnetic resonance imaging (erfMRI) and block-design (bdfMRI) datasets collected with multiband 32- (repetition time [TR] = 460 ms) or older 12-channel (TR = 2,000 ms) head coils. The amount of motion varied across coil designs and task types. Quality control plots indicated small to moderate relationships between head motion estimates and percent signal change in both signal and noise regions. Blind-source denoising strategies eliminated signal as well as noise relative to MP24 regression; however, the undesired effects on signal depended both on algorithm (FIX > AROMA) and design (bdfMRI > erfMRI). Moreover, in contrast to previous results, there were minimal differences between MP12/24 and MP0 pipelines in both erfMRI and bdfMRI designs. MP12/24 pipelines were detrimental for a task with both longer block length (30 ± 5 s) and higher correlations between head MPs and design matrix. In summary, current results suggest that there does not appear to be a single denoising approach that is appropriate for all fMRI designs. However, even nonaggressive blind-source denoising approaches appear to remove signal as well as noise from task-related data at individual subject and group levels.

Motion artifact in studies of functional connectivity: Characteristics and mitigation strategies

Motion artifacts are now recognized as a major methodological challenge for studies of functional connectivity. As in-scanner motion is frequently correlated with variables of interest such as age, clinical status, cognitive ability, and symptom severity, in-scanner motion has the potential to introduce systematic bias. In this article, we describe how motion-related artifacts influence measures of functional connectivity and discuss the relative strengths and weaknesses of commonly used denoising strategies. Furthermore, we illustrate how motion can bias inference, using a study of brain development as an example. Finally, we highlight directions of ongoing and future research, and provide recommendations for investigators in the field. Hum Brain Mapp, 40:2033-2051, 2019. © 2017 Wiley Periodicals, Inc.

Sorted Golden-step phase encoding: an improved Golden-step imaging technique for cardiac and respiratory self-gated cine cardiovascular magnetic resonance imaging

BACKGROUND

Numerous self-gated cardiac imaging techniques have been reported in the literature. Most can track either cardiac or respiratory motion, and many incur some overhead to imaging data acquisition. We previously described a Cartesian cine imaging technique, pseudo-projection motion tracking with golden-step phase encoding, capable of tracking both cardiac and respiratory motion at no cost to imaging data acquisition. In this work, we describe improvements to the technique by dramatically reducing its vulnerability to eddy current and flow artifacts and demonstrating its effectiveness in expanded cardiovascular applications.

METHODS

As with our previous golden-step technique, the Cartesian phase encodes over time were arranged based on the integer golden step, and readouts near ky = 0 (pseudo-projections) were used to derive motion. In this work, however, the readouts were divided into equal and consecutive temporal segments, within which the readouts were sorted according to ky. The sorting reduces the phase encode jump between consecutive readouts while maintaining the pseudo-randomness of ky to sample both cardiac and respiratory motion without comprising the ability to retrospectively set the temporal resolution of the original technique. On human volunteers, free-breathing, electrocardiographic (ECG)-free cine scans were acquired for all slices of the short axis stack and the 4-chamber view of the long axis. Retrospectively, cardiac motion and respiratory motion were automatically extracted from the pseudo-projections to guide cine reconstruction. The resultant image quality in terms of sharpness and cardiac functional metrics was compared against breath-hold ECG-gated reference cines.

RESULTS

With sorting, motion tracking of both cardiac and respiratory motion was effective for all slices orientations imaged, and artifact occurrence due to eddy current and flow was efficiently eliminated. The image sharpness derived from the self-gated cines was found to be comparable to the reference cines (mean difference less than 0.05 mm- 1 for short-axis images and 0.075 mm- 1 for long-axis images), and the functional metrics (mean difference < 4 ml) were found not to be statistically different from those from the reference.

CONCLUSIONS

This technique dramatically reduced the eddy current and flow artifacts while preserving the ability of cost-free motion tracking and the flexibility of choosing arbitrary navigator zone width, number of cardiac phases, and duration of scanning. With the restriction of the artifacts removed, the Cartesian golden-step cine imaging can now be applied to cardiac imaging slices of more diverse orientation and anatomy at greater reliability.

Differential effects of parent and peer presence on neural correlates of risk taking in adolescence

Adolescence is a developmental period associated with increased health-risk behaviors and unique sensitivity to the input from the social context, paralleled by major changes in the developing brain. Peer presence increases adolescent risk taking, associated with greater reward-related activity, while parental presence decreases risk taking, associated with decreased reward-related activity and increased cognitive control. Yet the effects specific to peers and parents are still unknown. The current functional magnetic resonance imaging (fMRI) study compared within-person peer and parent influences on risky decision-making during adolescence (ages 12–15 years; N = 56). Participants completed the Yellow Light Game (YLG), a computerized driving task, during which they could make safe or risky decisions, in the presence of a peer and their parent. Behavioral findings revealed no effects of social context on risk taking. At the neural level, a collection of affective, social and cognitive regions [ventral striatum (VS), temporo-parietal junction (TPJ), and dorsolateral prefrontal cortex (dlPFC)] was more active during decision-making with peers than parents. Additionally, functional connectivity analyses showed greater coupling between affective, social and cognitive control regions (VS-insula, VS-TPJ) during decision-making with parents than peers. These findings highlight the complex nature of social influence processes in peer and parent contexts, and contribute to our understanding of the opportunities and vulnerabilities associated with adolescent social sensitivity.

Model-based network discovery of developmental and performance-related differences during risky decision-making

Theories of adolescent neurodevelopment have largely focused on group-level descriptions of neural changes that help explain increases in risk behavior that are stereotypical of the teen years. However, because these models are concerned with describing the "average" individual, they can fail to account for important individual or within-group variability. New methodological developments now offer the possibility of accounting for both group trends and individual differences within the same modeling framework. Here we apply GIMME, a model-based approach which uses both group and individual-level information to construct functional connectivity maps, to investigate risky behavior and neural changes across development. Adolescents (N = 30, Mage = 13.22), young adults (N = 23, Mage = 19.19), and adults (N = 31, Mage = 43.93) completed a risky decision-making task during an fMRI scan, and functional networks were constructed for each individual. We took two subgrouping approaches: 1) a confirmatory approach where we searched for functional connections that distinguished between our a priori age categories, and 2) an exploratory approach where we allowed an unsupervised algorithm to sort individuals freely. Contrary to expectations, we show that age is not the most influence contributing to network configurations. The implications for developmental theories and methodologies are discussed.

Contributions of default mode network stability and deactivation to adolescent task engagement

Out of the several intrinsic brain networks discovered through resting-state functional analyses in the past decade, the default mode network (DMN) has been the subject of intense interest and study. In particular, the DMN shows marked suppression during task engagement, and has led to hypothesized roles in internally-directed cognition that need to be down-regulated in order to perform goal-directed behaviors. Previous work has largely focused on univariate deactivation as the mechanism of DMN suppression. However, given the transient nature of DMN down-regulation during task, an important question arises: Does the DMN need to be strongly, or more stably suppressed to promote successful task learning? In order to explore this question, 65 adolescents (M_age = 13.32; 21 females) completed a risky decision-making task during an fMRI scan. We tested our primary question by examining individual differences in absolute level of deactivation against the stability of activation across time in predicting levels of feedback learning on the task. To measure stability, we utilized a model-based functional connectivity approach that estimates the stability of activation across time within a region. In line with our hypothesis, the stability of activation in default mode regions predicted task engagement over and above the absolute level of DMN deactivation, revealing a new mechanism by which the brain can suppress the influence of brain networks on behavior. These results also highlight the importance of adopting model-based network approaches to understand the functional dynamics of the brain.

Interaction of Developmental Venous Anomalies with Resting-State Functional MRI Measures

BACKGROUND AND PURPOSE

Functional MR imaging of the brain, used for both clinical and neuroscientific applications, relies on measuring fluctuations in blood oxygenation. Such measurements are susceptible to noise of vascular origin. The purpose of this study was to assess whether developmental venous anomalies, which are frequently observed normal variants, can bias fMRI measures by appearing as true neural signal.

MATERIALS AND METHODS

Large developmental venous anomalies (1 in each of 14 participants) were identified from a large neuroimaging cohort (n = 814). Resting-state fMRI data were decomposed using independent component analysis, a data-driven technique that creates distinct component maps representing aspects of either structured noise or true neural activity. We searched all independent components for maps that exhibited a spatial distribution of their signals following the topography of developmental venous anomalies.

RESULTS

Of the 14 developmental venous anomalies identified, 10 were clearly present in 17 fMRI independent components in total. While 9 (52.9%) of these 17 independent components were dominated by venous contributions and 2 (11.8%) by motion artifacts, 2 independent components (11.8%) showed partial neural signal contributions and 5 independent components (29.4%) unambiguously exhibited typical neural signal patterns.

CONCLUSIONS

Developmental venous anomalies can strongly resemble neural signal as measured by fMRI. They are thus a potential source of bias in fMRI analyses, especially when present in the cortex. This could impede interpretation of local activity in patients, such as in presurgical mapping. In scientific studies with large samples, developmental venous anomaly confounds could be mainly addressed using independent component analysis-based denoising.

Intergroup social influence on emotion processing in the brain

Emotions usually occur in a social context; yet little is known about how similar and dissimilar others influence our emotions. In the current study, we examined whether ingroup and outgroup members have differential influence on emotion processing at the behavioral and neural levels. To this end, we recruited 45 participants to rate a series of images displaying people engaged in different emotional contexts. Participants then underwent an fMRI scan where they viewed the same images along with information on how ingroup and outgroup members rated them, and they were asked to rate the images again. We found that participants shifted their emotions to be more in alignment with the ingroup over the outgroup, and that neural regions implicated in positive valuation [ventral striatum (VS) and ventromedial prefrontal cortex (vmPFC)], mentalizing [dorsomedial prefrontal cortex (dmPFC), medial prefrontal cortex (mPFC), posterior superior temporal sulcus (pSTS), and temporal pole], as well as emotion processing and salience detection (amygdala and insula), linearly tracked this behavior such that the extent of neural activity in these regions paralleled changes in participants' emotions. Results illustrate the powerful impact that ingroup members have on our emotions.

Differential effects of parent and peer presence on neural correlates of risk taking in adolescence

Adolescence is a developmental period associated with increased health-risk behaviors and unique sensitivity to the input from the social context, paralleled by major changes in the developing brain. Peer presence increases adolescent risk taking, associated with greater reward-related activity, while parental presence decreases risk taking, associated with decreased reward-related activity and increased cognitive control. Yet the effects specific to peers and parents are still unknown. The current functional magnetic resonance imaging (fMRI) study compared within-person peer and parent influences on risky decision-making during adolescence (ages 12-15 years; N = 56). Participants completed the Yellow Light Game (YLG), a computerized driving task, during which they could make safe or risky decisions, in the presence of a peer and their parent. Behavioral findings revealed no effects of social context on risk taking. At the neural level, a collection of affective, social and cognitive regions [ventral striatum (VS), temporo-parietal junction (TPJ), and dorsolateral prefrontal cortex (dlPFC)] was more active during decision-making with peers than parents. Additionally, functional connectivity analyses showed greater coupling between affective, social and cognitive control regions (VS-insula, VS-TPJ) during decision-making with parents than peers. These findings highlight the complex nature of social influence processes in peer and parent contexts, and contribute to our understanding of the opportunities and vulnerabilities associated with adolescent social sensitivity.

Neural correlates of sibling closeness and association with externalizing behavior in adolescence

Sibling relationships have been linked to adolescent externalizing behaviors, but the neurobiological factors that underlie this association have not been identified. This study investigated sibling closeness and birth order as a predictor of adolescent externalizing behavior via differences in neural processes during safe decision-making. A total of 77 adolescents (range = 12–15 years, M_age = 13.45 years, 40 females) completed a computerized driving task during a functional MRI scan. Results showed that adolescents’ perceptions of sibling closeness were associated with greater neural activation in the anterior insula, ventral striatum and left ventrolateral prefrontal cortex when making safe decisions, suggesting that the quality of sibling relationships modulates adolescent neurocognition even without being present. Furthermore, moderated mediation analyses revealed that higher sibling closeness was associated with lower externalizing behavior via left anterior insula activation during safe decision-making, but only for adolescents without older siblings (i.e. eldest children) compared to adolescents who had multiple older siblings. Importantly, these findings persisted above and beyond parental and peer closeness and sibling characteristics (i.e. sex, relatedness, birth order), highlighting the significant influence of sibling relationships on adolescent externalizing behavior through the brain.

Functional connectivity in the social brain across childhood and adolescence

Previous research has characterized a collection of neural regions which support social-cognitive processes. While this 'social brain' is often described as a cohesive unit, it has been largely assessed with univariate methodologies, which cannot account for functional relationships 'between' brain regions, and therefore cannot test the idea of the social brain as a network. In the present work, we utilized a multi-method approach to empirically assess the functional architecture of the social brain. Fifty participants (ages 8-16) completed a social evaluation task during an functional imaging scan. Results from three unique functional connectivity methodologies demonstrated that social brain regions show strong functional relationships, while also interfacing with non-social regions, suggesting that future work should consider network relationships between social brain regions in addition to traditional univariate approaches. We probed, but did not find age-related differences in social brain network organization, demonstrating that this functional architecture is in place by late childhood.