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This data descriptor outlines a shared neuroimaging dataset from the UCLA Consortium for Neuropsychiatric Phenomics, which focused on understanding the dimensional structure of memory and cognitive control (response inhibition) functions in both healthy individuals (130 subjects) and individuals with neuropsychiatric disorders including schizophrenia (50 subjects), bipolar disorder (49 subjects), and attention deficit/hyperactivity disorder (43 subjects). The dataset includes an extensive set of task-based fMRI assessments, resting fMRI, structural MRI, and high angular resolution diffusion MRI. The dataset is shared through the OpenfMRI project, and is formatted according to the Brain Imaging Data Structure (BIDS) standard.

Rationale: Early diagnosis of bronchiolitis obliterans syndrome (BOS) is critical in understanding pathogenesis and devising therapeutic trials. Although potential-BOS stage (BOS 0-p), encompassing early changes in FEV(1) and forced expiratory flow, midexpiratory phase (FEF(25-75%)), has been proposed, there is a paucity of data validating its utility in single-lung transplantation.Objective: The aim of this study was to define the predictive ability of BOS 0-p in single-lung transplantation.Methods: We retrospectively analyzed spirometric data for 197 single-lung recipients. Sensitivity, specificity, and positive predictive value of BOS 0-p were examined over time using Kaplan-Meier methodology.Results: BOS 0-p FEV(1) was associated with higher sensitivity, specificity, and positive predictive value than the FEF(25-75%) criterion over different time periods investigated. The probability of testing positive for BOS 0-p FEV(1) in patients with BOS (sensitivity) was 71% at 2 years before the onset of BOS. The probability of being free from development of BOS 0-p FEV(1) in patients free of BOS at follow-up (specificity) was 93% within the last year. Of patients who met the BOS 0-p FEV(1) criterion, 81% developed BOS or died within 3 years. The specificity and positive predictive value curves for the BOS 0-p FEV(1) were significantly different between patients with underlying restrictive versus obstructive physiology (p = 0.05 and 0.01, respectively).Conclusion: The FEV(1) criterion for BOS 0-p provides useful predictive information regarding the risk of development of BOS or death in single-lung recipients. The predictive value of this criterion is higher in patients with underlying restriction and is superior to the FEF(25-75%) criterion. [ABSTRACT FROM AUTHOR]

Abstract Background This is the first investigation of its kind to explore the views of people affected by pancreatic cancer with regard to research priorities. Pancreatic cancer has an extremely poor outlook in terms of early diagnosis, effective treatment and survival. Those affected by the disease generally lack opportunities to voice their needs or concerns in an organised manner, link with others affected by the condition and take part in research. Methods This qualitative study adopts a self-selected telephone focussed discussion group approach. Information was obtained from distinct carer and patient groups after adequate controls such as the 'safe space' technique (repeatedly enquiring on and respecting the emotional needs) were implemented to protect participants from undue physical and psychological distress. Results Five themes emerged overall, with three themes being common between the patients and carers groups. Early detection, clinician communication and public awareness were areas of recurring discussion and consensus for both groups. The fourth theme to emerge for the patient group centred on quality of care, while the fourth theme of the carer group focused on the need for more and improved treatment options. Conclusion Research priorities for pancreatic cancer consumers have been identified via an investigation that was tailored to meet exceptional needs. This research gives us a primary understanding of the role that pancreatic cancer patients can play in identifying areas of research that are responsive to their needs and priorities when suitably planned. Importantly it also provides a much greater understanding of the grim realities of the disease for those affected. This work is likely to be of value to anyone planning to work with those with a time limited, challenging condition.

Despite the widespread use of the Research Domain Criteria (RDoC) framework in psychiatry and neuroscience, recent studies suggest that the RDoC is insufficiently specific or excessively broad relative to the underlying brain circuitry it seeks to elucidate. To address these concerns, we employed a latent variable approach using bifactor analysis. We examined 84 whole-brain task-based fMRI (tfMRI) activation maps from 19 studies with 6,192 participants. A curated subset of 37 maps with a balanced representation of RDoC domains constituted the training set, and the remaining held-out maps formed the internal validation set. External validation was conducted using 36 peak coordinate activation maps from Neurosynth, using terms of RDoC constructs as seeds for topic meta-analysis. Here, we show that a bifactor model incorporating a task-general domain and splitting the cognitive systems domain better fits the examined corpus of tfMRI data than the current RDoC framework. We also identify the domain of arousal and regulatory systems as underrepresented. Our data-driven validation supports revising the RDoC framework to reflect underlying brain circuitry more accurately., Competing Interests: Competing interests The authors declare no competing interests.

In a perfect world, scientists would develop analyses that are guaranteed to reveal the ground truth of a research question. In reality, there are countless viable workflows that produce distinct, often conflicting, results. Although reproducibility places a necessary bound on the validity of results, it is not sufficient for claiming underlying validity, eventual utility, or generalizability. In this work we focus on how embracing variability in data analysis can improve the generalizability of results. We contextualize how design decisions in brain imaging can be made to capture variation, highlight examples, and discuss how variability capture may improve the quality of results., (© 2024. The Author(s).)

Recent work has shown that deep learning is a powerful tool for predicting brain activation patterns evoked through various tasks using resting state features. We replicate and improve upon this recent work to introduce two models, BrainSERF and BrainSurfGCN, that perform at least as well as the state-of-the-art while greatly reducing memory and computational footprints. Our performance analysis observed that low predictability was associated with a possible lack of task engagement derived from behavioral performance. Furthermore, a deficiency in model performance was also observed for closely matched task contrasts, likely due to high individual variability confirmed by low test-retest reliability. Overall, we successfully replicate recently developed deep learning architecture and provide scalable models for further research., Competing Interests: Declaration of Competing Interests No competing interests are present among the authors of this work.

We describe the following shared data from N = 103 healthy adults who completed a broad set of cognitive tasks, surveys, and neuroimaging measurements to examine the construct of self-regulation. The neuroimaging acquisition involved task-based fMRI, resting state fMRI, and structural MRI. Each subject completed the following ten tasks in the scanner across two 90-minute scanning sessions: attention network test (ANT), cued task switching, Columbia card task, dot pattern expectancy (DPX), delay discounting, simple and motor selective stop signal, Stroop, a towers task, and a set of survey questions. The dataset is shared openly through the OpenNeuro project, and the dataset is formatted according to the Brain Imaging Data Structure (BIDS) standard., (© 2024. The Author(s).)

Empirical studies reporting low test-retest reliability of individual blood oxygen-level dependent (BOLD) signal estimates in functional magnetic resonance imaging (fMRI) data have resurrected interest among cognitive neuroscientists in methods that may improve reliability in fMRI. Over the last decade, several individual studies have reported that modeling decisions, such as smoothing, motion correction and contrast selection, may improve estimates of test-retest reliability of BOLD signal estimates. However, it remains an empirical question whether certain analytic decisions consistently improve individual and group level reliability estimates in an fMRI task across multiple large, independent samples. This study used three independent samples ( N s: 60, 81, 119) that collected the same task (Monetary Incentive Delay task) across two runs and two sessions to evaluate the effects of analytic decisions on the individual (intraclass correlation coefficient [ICC(3,1)]) and group (Jaccard/Spearman rho ) reliability estimates of BOLD activity of task fMRI data. The analytic decisions in this study vary across four categories: smoothing kernel (five options), motion correction (four options), task parameterizing (three options) and task contrasts (four options), totaling 240 different pipeline permutations. Across all 240 pipelines, the median ICC estimates are consistently low, with a maximum median ICC estimate of .43 - .55 across the three samples. The analytic decisions with the greatest impact on the median ICC and group similarity estimates are the Implicit Baseline contrast, Cue Model parameterization and a larger smoothing kernel. Using an Implicit Baseline in a contrast condition meaningfully increased group similarity and ICC estimates as compared to using the Neutral cue. This effect was largest for the Cue Model parameterization; however, improvements in reliability came at the cost of interpretability. This study illustrates that estimates of reliability in the MID task are consistently low and variable at small samples, and a higher test-retest reliability may not always improve interpretability of the estimated BOLD signal., Competing Interests: Conflicts of Interest The authors declare that they have no conflicts of interest.

Interpreting the neural response elicited during task functional magnetic resonance imaging (fMRI) remains a challenge in neurodevelopmental research. The monetary incentive delay (MID) task is an fMRI reward processing task that is extensively used in the literature. However, modern psychometric tools have not been used to evaluate measurement properties of the MID task fMRI data. The current study uses data for a similar task design across three adolescent samples (N = 346 [Age mean 12.0; 44 % Female]; N = 97 [19.3; 58 %]; N = 112 [20.2; 38 %]) to evaluate multiple measurement properties of fMRI responses on the MID task. Confirmatory factor analysis (CFA) is used to evaluate an a priori theoretical model for the task and its measurement invariance across three samples. Exploratory factor analysis (EFA) is used to identify the data-driven measurement structure across the samples. CFA results suggest that the a priori model is a poor representation of these MID task fMRI data. Across the samples, the data-driven EFA models consistently identify a six-to-seven factor structure with run and bilateral brain region factors. This factor structure is moderately-to-highly congruent across the samples. Altogether, these findings demonstrate a need to evaluate theoretical frameworks for popular fMRI task designs to improve our understanding and interpretation of brain-behavior associations., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflicts of interest., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Response times (RTs) are often the main signal of interest in cognitive psychology but are often ignored in functional MRI (fMRI) analyses. In fMRI analysis the intensity of the signal serves as a proxy for the intensity of local neuronal activity, but changes in either the intensity or the duration of neuronal activity can yield identical fMRI signals. Therefore, if RTs are ignored and pair with neuronal durations, fMRI results claiming intensity differences may be confounded by RTs. We show how ignoring RTs goes beyond this confound, where longer RTs are paired with larger activation estimates, to lesser-known issues where RTs become confounds in group-level analyses and, surprisingly, how the RT confound can induce other artificial group-level associations with variables that are not related to the condition contrast or RTs. We propose a new time-series model to address these issues and encourage increasing focus on what the widespread RT-based signal represents., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Response inhibition is key to controlled behavior and is commonly investigated with the stop-signal paradigm. The authors investigated how response inhibition is situated within a taxonomy of control processes by combining multiple forms of control within dual tasks. Response inhibition, as measured by stop-signal reaction time (SSRT), was impaired when combined with shape matching, but not the flanker task, and when combined with cued task switching, but not predictable task switching, suggesting that response inhibition may be weakly or variably impaired when combined with selective attention and set shifting demands, respectively. Response inhibition was also consistently impaired when combined with the N-back or directed forgetting tasks, putative measures of working memory. Impairments of response inhibition by other control demands appeared to be primarily driven by task context, as SSRT slowing was similar for trials where control demands were either high (e.g., task switch) or low (e.g., task stay). These results demonstrate that response inhibition processes are often impaired in the context of other control demands, even on trials where direct engagement of those other control processes is not required. This suggests a taxonomy of control in which response inhibition overlaps with related control processes, especially working memory. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Objective: Mindfulness-based interventions are widely used to target pain, yet their neural mechanisms of action are insufficiently understood. The authors studied neural and subjective pain response in a randomized active-control trial of mindfulness-based stress reduction (MBSR) alongside long-term meditation practitioners., Methods: Healthy participants (N=115) underwent functional neuroimaging during a thermal acute pain task before and after random assignment to MBSR (N=28), an active control condition (health enhancement program [HEP]) (N=32), or a waiting list control condition (N=31). Long-term meditators (N=30) completed the same neuroimaging paradigm. Pain response was measured via self-reported intensity and unpleasantness, and neurally via two multivoxel machine-learning-derived signatures: the neurologic pain signature (NPS), emphasizing nociceptive pain processing, and the stimulus intensity independent pain signature-1 (SIIPS1), emphasizing stimulus-independent neuromodulatory processes., Results: The MBSR group showed a significant decrease in NPS response relative to the HEP group (Cohen's d=-0.43) and from pre- to postintervention assessment (d=-0.47). The MBSR group showed small, marginal decreases in NPS relative to the waiting list group (d=-0.36), and in SIIPS1 relative to both groups (HEP group, d=-0.37; waiting list group, d=-0.37). In subjective unpleasantness, the MBSR and HEP groups also showed modest significant reductions compared with the waiting list group (d=-0.45 and d=-0.55). Long-term meditators reported significantly lower pain than nonmeditators but did not differ in neural response. Within the long-term meditator group, cumulative practice during intensive retreat was significantly associated with reduced SIIPS1 (r=-0.65), whereas daily practice was not., Conclusions: Mindfulness training showed associations with pain reduction that implicate differing neural pathways depending on extent and context of practice. Use of neural pain signatures in randomized trials offers promise for guiding the application of mindfulness interventions to pain treatment.

Disruptions of self-regulation are a hallmark of numerous psychiatric disorders. Here, we examine the relationship between transdiagnostic dimensions of psychopathology and changes in self-regulation in the early phase of the COVID-19 pandemic. We used a data-driven approach on a large number of cognitive tasks and self-reported surveys in training datasets. Then, we derived measures of self-regulation and psychiatric functioning in an independent population sample (N = 102) tested both before and after the onset of the COVID-19 pandemic, when the restrictions in place represented a threat to mental health and forced people to flexibly adjust to modifications of daily routines. We found independent relationships between transdiagnostic dimensions of psychopathology and longitudinal alterations in specific domains of self-regulation defined using a diffusion decision model. Compared to the period preceding the onset of the pandemic, a symptom dimension related to anxiety and depression was characterized by a more cautious behavior, indexed by the need to accumulate more evidence before making a decision. Instead, social withdrawal related to faster non-decision processes. Self-reported measures of self-regulation predicted variance in psychiatric symptoms both concurrently and prospectively, revealing the psychological dimensions relevant for separate transdiagnostic dimensions of psychiatry, but tasks did not. Taken together, our results are suggestive of potential cognitive vulnerabilities in the domain of self-regulation in people with underlying psychiatric difficulties in face of real-life stressors. More generally, they also suggest that the study of cognition needs to take into account the dynamic nature of real-world events as well as within-subject variability over time., (© 2022. The Author(s).)

Emodiversity, or the variety and relative abundance of emotions experienced, provides a metric that can be used to understand emotional experience and its relation to well-being above and beyond average levels of positive and negative affect. Past research has found that more diverse emotional experiences, both positive and negative, are related to better mental and physical health outcomes. The present research aimed to test the relationship between positive and negative emodiversity across the span of 8 days with measures of health and well-being using 2 samples of the Midlife in the United States study (http://midus.wisc.edu/). Participants ( N = 2,788) reported emotional states (14 negative, 13 positive) once each day for 8 days. Emodiversity scores were computed for each day using an adaptation of Shannon's biodiversity index and averaged across the days. All models included average affect and demographic covariates. Greater positive emodiversity was associated with fewer symptoms of depression and anxiety and fewer physical health symptoms but was not related to eudaimonic well-being nor cognitive functioning. In contrast to previous research, greater negative emodiversity was related to more symptoms of depression and anxiety and more physical health symptoms. Greater negative emodiversity was only associated with one positive outcome: better executive functioning. These findings illustrate inconsistencies across studies in whether negative emodiversity is associated with better or worse outcomes and raise further questions about how the construct of emodiversity can be better refined. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The uncinate fasciculus is a white matter tract that may facilitate emotion regulation by carrying connections from the prefrontal cortex to regions of the temporal lobe, including the amygdala. Depression and anxiety are associated with reduced uncinate fasciculus fractional anisotropy (FA)-a diffusion tensor imaging measure related to white matter integrity. In the current study, we tested whether FA in the uncinate fasciculus is associated with individual differences in emotional recovery measured with corrugator supercilii electromyography in response to negative, neutral, and positive images in 108 participants from the Midlife in the US (MIDUS; http://midus.wisc.edu) Refresher study. Corrugator activity is linearly associated with changes in affect, and differentiated negative, neutral, and positive emotional responses. Higher uncinate fasciculus FA was associated with lower corrugator activity 4-8 seconds after negative image offset, indicative of better recovery from negative provocation. In an exploratory analysis, we found a similar association for the inferior fronto-occipital, inferior longitudinal and superior longitudinal fasciculi. These results suggest that the microstructural features of the uncinate fasciculus, and these other association white matter fibers, may support emotion regulatory processes with greater white matter integrity facilitating healthier affective functioning. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Unaddressed occupational stress and trauma contribute to elevated rates of mental illness and suicide in policing, and to violent and aggressive behavior that disproportionately impacts communities of color. Emerging evidence suggests mindfulness training with police may reduce stress and aggression and improve mental health, but there is limited evidence for changes in biological outcomes or the lasting benefits of mindfulness training. We conducted a randomized controlled trial (RCT) of 114 police officers from three Midwestern U.S. law enforcement agencies. We assessed stress-related physical and mental health symptoms, blood-based inflammatory markers, and hair and salivary cortisol. Participants were then randomized to an 8-week mindfulness intervention or waitlist control (WLC), and the same assessments were repeated post-intervention and at 3-month follow-up. Relative to waitlist control, the mindfulness group had greater improvements in psychological distress, mental health symptoms, and sleep quality post-training, gains that were maintained at 3-month follow-up. Intervention participants also had a significantly lower cortisol awakening response (CAR) at 3-month follow-up relative to waitlist control. Contrary to hypotheses, there were no intervention effects on hair cortisol, diurnal cortisol slope, or inflammatory markers. In summary, an 8-week mindfulness intervention for police officers led to self-reported improvements in distress, mental health, and sleep, and a lower CAR. These benefits persisted (or emerged) at 3-month follow-up, suggesting that this training may buffer against the long-term consequences of chronic stress. Future research should assess the persistence of these benefits over a longer period while expanding the scope of outcomes to consider the broader community of mindfulness training for police. Clinical Trial Registration: ClinicalTrials.gov#NCT03488875., Competing Interests: RD is the founder, president, and serves on the board of directors for the non-profit organization, Healthy Minds Innovations, Inc. CS was employed by The Academy for Mindfulness, Glendale WI, at the time of this work. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Grupe, Stoller, Alonso, McGehee, Smith, Mumford, Rosenkranz and Davidson.)

Law enforcement officers are regularly exposed directly and indirectly to a wide variety of traumatic stressors, which take place against a backdrop of high levels of organizational stressors. Consequently, this group is at elevated risk for posttraumatic stress disorder (PTSD) and other negative physical and mental health outcomes, yet there are few empirically supported interventions to proactively mitigate the effects of occupational stress for this population. Recent studies suggest that training in mindfulness meditation may reduce perceived stress and improve related physical and mental health outcomes in this group. We sought to demonstrate feasibility, acceptability, and adherence for an 8-week mindfulness training program in 30 officers from a mid-sized, Midwestern U.S. police department, replicate findings of improved stress-related health outcomes, and provide novel evidence for reduced PTSD symptoms. All 30 officers completed the training, with high rates of class attendance, substantial out-of-class practice time, and good acceptability of the training and teachers. We replicated findings of reduced post-training perceived stress, sleep disturbances, anxiety, and burnout. We also identified novel evidence for reduced PTSD symptoms that persisted at a 5-month follow-up assessment. These results indicate key targets for future investigation in larger, mechanistic, randomized controlled trials of mindfulness training in police officers., Competing Interests: Conflict of Interest Dr. Richard J. Davidson is the founder and president of, and serves on the board of directors for, the non-profit organization, Healthy Minds Innovations, Inc. The other authors report no conflicts of interest.

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses 1 . The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset 2-5 . Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

The bed nucleus of the stria terminalis (BNST) and central nucleus of the amygdala (CeA) are hypothesized to be the output nodes of the extended amygdala threat response, integrating multiple signals to coordinate the threat response via outputs to the hypothalamus and brainstem. The BNST and CeA are structurally and functionally connected, suggesting interactions between these regions may regulate how the response to provocation unfolds. However, the relationship between human BNST-CeA connectivity and the behavioral response to affective stimuli is little understood. To investigate whether individual differences in BNST-CeA connectivity are related to the affective response to negatively valenced stimuli, we tested relations between resting-state BNST-CeA connectivity and both facial electromyographic (EMG) activity of the corrugator supercilii muscle and eyeblink startle magnitude during affective image presentation within the Refresher sample of the Midlife in the United States (MIDUS) study. We found that higher right BNST-CeA connectivity was associated with greater corrugator activity to negative, but not positive, images. There was a trend-level association between right BNST-CeA connectivity and trait negative affect. Eyeblink startle magnitude was not significantly related to BNST-CeA connectivity. These results suggest that functional interactions between BNST and CeA contribute to the behavioral response to negative emotional events., Competing Interests: Declaration of competing interest R.J.D. serves on the board of directors for the non-profit organization Healthy Minds Innovations. The other authors report no perceived or real conflicts of interest., (Copyright © 2019. Published by Elsevier Inc.)

While rodent research suggests that the bed nucleus of the stria terminalis (BNST) and centromedial amygdala (CM) coordinate the hormonal stress response, little is known about the BNST's role in the human stress response. The human BNST responds to negatively valenced stimuli, which likely subserves its role in responding to threat. Thus, variation in BNST reactivity to negatively valenced stimuli may relate to differences in the stress response. We measured participants' blood oxygenated level-dependent response to affective images and salivary cortisol and α-amylase (AA) levels in response to a subsequent Trier social stress test (TSST). Greater BNST activation to emotionally evocative images was associated with a larger TSST-evoked AA, but not cortisol response. This association remained after controlling for CM activation, which was not related to the cortisol or AA response. These results suggest that the BNST response to negatively valenced images subserves its role in coordinating the stress response, a BNST role in the stress response independent from the CM, and highlight the need for investigation of the conditions under which BNST activation predicts the cortisol response. Our findings are critical for the future study of mood and anxiety disorders, as dysregulation of the stress system plays a key role in their pathogenesis., (© The Author(s) 2020. Published by Oxford University Press.)

Mindfulness meditation training has been shown to increase resting-state functional connectivity between nodes of the frontoparietal executive control network (dorsolateral prefrontal cortex [DLPFC]) and the default mode network (posterior cingulate cortex [PCC]). We investigated whether these effects generalized to a Mindfulness-Based Stress Reduction (MBSR) course and tested for structural and behaviorally relevant consequences of change in connectivity. Healthy, meditation-naïve adults were randomized to either MBSR (N = 48), an active (N = 47) or waitlist (N = 45) control group. Participants completed behavioral testing, resting-state fMRI scans and diffusion tensor scans at pre-randomization (T1), post-intervention (T2) and ~5.5 months later (T3). We found increased T2-T1 PCC-DLPFC resting connectivity for MBSR relative to control groups. Although these effects did not persist through long-term follow-up (T3-T1), MBSR participants showed a significantly stronger relationship between days of practice (T1 to T3) and increased PCC-DLPFC resting connectivity than participants in the active control group. Increased PCC-DLPFC resting connectivity in MBSR participants was associated with increased microstructural connectivity of a white matter tract connecting these regions and increased self-reported attention. These data show that MBSR increases PCC-DLPFC resting connectivity, which is related to increased practice time, attention and structural connectivity., (© The Author(s) 2019. Published by Oxford University Press.)

Background: Prior studies of pediatric posttraumatic stress disorder (PTSD) have reported cross-sectional and age-related structural and functional brain abnormalities in networks associated with cognitive, affective, and self-referential processing. However, no reported studies have comprehensively examined longitudinal gray matter development and its intrinsic functional correlates in pediatric PTSD., Methods: Twenty-seven youths with PTSD and 21 nontraumatized typically developing (TD) youths were assessed at baseline and 1-year follow-up. At each visit, youths underwent structural magnetic resonance imaging and resting-state functional magnetic resonance imaging. Regions with volumetric abnormalities in whole-brain structural analyses were identified and used as seeds in exploratory intrinsic connectivity analyses., Results: Youths with PTSD exhibited sustained reductions in gray matter volume (GMV) in right ventromedial prefrontal cortex (PFC) and bilateral ventrolateral PFC. Group-by-time analyses revealed aberrant longitudinal development in dorsolateral PFC, where typically developing youths exhibited normative decreases in GMV between baseline and follow-up, and youths with PTSD showed increases in GMV. Using these regions as seeds, patients with PTSD exhibited atypical longitudinal decreases in intrinsic PFC-amygdala and PFC-hippocampus connectivity, in contrast to increases in typically developing youths. Specifically, youths with PTSD showed decreasing ventromedial PFC-amygdala connectivity as well as decreasing ventrolateral PFC-hippocampus connectivity over time. Notably, volumetric abnormalities in ventromedial PFC and ventrolateral PFC were predictive of symptom severity., Conclusions: These findings represent novel longitudinal volumetric and connectivity changes in pediatric PTSD. Atypical prefrontal GMV and prefrontal-amygdala/hippocampus development may underlie persistence of PTSD in youths and could serve as future therapeutic targets., (Copyright © 2018 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Meditation training can improve mood and emotion regulation, yet the neural mechanisms of these affective changes have yet to be fully elucidated. We evaluated the impact of long- and short-term mindfulness meditation training on the amygdala response to emotional pictures in a healthy, non-clinical population of adults using blood-oxygen level dependent functional magnetic resonance imaging. Long-term meditators (N = 30, 16 female) had 9081 h of lifetime practice on average, primarily in mindfulness meditation. Short-term training consisted of an 8-week Mindfulness- Based Stress Reduction course (N = 32, 22 female), which was compared to an active control condition (N = 35, 19 female) in a randomized controlled trial. Meditation training was associated with less amygdala reactivity to positive pictures relative to controls, but there were no group differences in response to negative pictures. Reductions in reactivity to negative stimuli may require more practice experience or concentrated practice, as hours of retreat practice in long-term meditators was associated with lower amygdala reactivity to negative pictures - yet we did not see this relationship for practice time with MBSR. Short-term training, compared to the control intervention, also led to increased functional connectivity between the amygdala and a region implicated in emotion regulation - ventromedial prefrontal cortex (VMPFC) - during affective pictures. Thus, meditation training may improve affective responding through reduced amygdala reactivity, and heightened amygdala-VMPFC connectivity during affective stimuli may reflect a potential mechanism by which MBSR exerts salutary effects on emotion regulation ability., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Recent reading research implicates executive control regions as sites of difference in struggling readers. However, as studies often employ only reading or language tasks, the extent of deviation in control engagement in children with reading difficulties is not known. The current study investigated activation in reading and executive control brain regions during both a sentence comprehension task and a nonlexical inhibitory control task in third-fifth grade children with and without reading difficulties. We employed both categorical (group-based) and individual difference approaches to relate reading ability to brain activity. During sentence comprehension, struggling readers had less activation in the left posterior temporal cortex, previously implicated in language, semantic, and reading research. Greater negative activity (relative to fixation) during sentence comprehension in a left inferior parietal region from the executive control literature correlated with poorer reading ability. Greater comprehension scores were associated with less dorsal anterior cingulate activity during the sentence comprehension task. Unlike the sentence task, there were no significant differences between struggling and nonstruggling readers for the nonlexical inhibitory control task. Thus, differences in executive control engagement were largely specific to reading, rather than a general control deficit across tasks in children with reading difficulties, informing future intervention research.

The ability to understand emotional experiences of others, empathy, is a valuable skill for effective social interactions. Various types of training increase empathy in adolescents, but their impact on brain circuits underlying empathy has not been examined. Video games provide a unique medium familiar and engaging to adolescents and can be used to deliver training at scale. We developed an empathy training video game, Crystals of Kaydor (Crystals), and investigated whether playing Crystals increases empathic accuracy (EA) and related brain activation in adolescents ( N  = 74; 27 female; mean age(sd) = 12.8(0.7) years; age range 11-14 years). Participants completed a resting state functional MRI (rs-fMRI) scan and an EA task during an fMRI scan before and after 2 weeks of daily gameplay with either the empathy training game, Crystals ( N  = 34), or the commercial video game Bastion ( N  = 40), an active control condition. There were no group differences in EA improvement following gameplay, however, engagement with training aspects of Crystals was associated with a higher increase in EA-related activation in right temporoparietal junction following gameplay. Moreover, rs-fMRI connectivity in empathy-related brain circuits (posterior cingulate-medial prefrontal cortex; MPFC) was stronger after Crystals gameplay compared to Bastion. The more individuals' EA increased following Crystals versus Bastion, the stronger their rs-fMRI connectivity in brain circuits relevant for emotion regulation (amygdala-MPFC). These findings suggest that a video game designed to increase empathic accuracy produces behaviorally-relevant, functional neural changes in fewer than 6 h of gameplay in adolescents., Competing Interests: Dr. Richard J. Davidson is the founder, president, and serves on the board of directors for the non-profit organization, Healthy Minds Innovations, Inc. No donors, either anonymous or identified, have participated in the design, conduct, or reporting of research results in this manuscript. The remaining authors declare no competing interests.

Prior research indicates that cognitive vulnerabilities can render individuals more susceptible to psychopathology in the wake of stressful events. However, little work has directly targeted the neural mechanisms involved. In this study, we examined functional magnetic resonance imaging (fMRI) activity as a function of negative cognitive style, a well-studied cognitive vulnerability for depression. We adapted a robust paradigm in which undergraduate students completed fMRI testing after a known ecologically valid stressor (a midterm exam). Negative cognitive style correlated with brain activity in response to both negative and exam-related information in dorsolateral prefrontal cortex and/or angular gyrus, both regions involved in abstract, self-referential thought. There were commonalities and differences in patterns of activity, suggesting that these individuals may process domain-general and domain-specific negative information in different ways but drawing upon a common frontoparietal network. This study, thus, identifies a potential brain network associated with negative cognitive style, and enhances our understanding of neural mechanisms of cognitive vulnerability to psychopathology. (PsycINFO Database Record, ((c) 2018 APA, all rights reserved).)

Emotional processing often continues beyond the presentation of emotionally evocative stimuli, which can result in affective biasing or coloring of subsequently encountered events. Here, we describe neural correlates of affective coloring and examine how individual differences in affective style impact the magnitude of affective coloring. We conducted functional magnetic resonance imaging in 117 adults who passively viewed negative, neutral and positive pictures presented 2 s prior to neutral faces. Brain responses to neutral faces were modulated by the valence of preceding pictures, with greater activation for faces following negative (vs positive) pictures in the amygdala, dorsomedial and lateral prefrontal cortex, ventral visual cortices, posterior superior temporal sulcus, and angular gyrus. Three days after the magnetic resonance imaging scan, participants rated their memory and liking of previously encountered neutral faces. Individuals higher in trait positive affect and emotional reappraisal rated faces as more likable when preceded by emotionally arousing (negative or positive) pictures. In addition, greater amygdala responses to neutral faces preceded by positively valenced pictures were associated with greater memory for these faces 3 days later. Collectively, these results reveal individual differences in how emotions spill over onto the processing of unrelated social stimuli, resulting in persistent and affectively biased evaluations of such stimuli.

We cannot see the minds of others, yet people often spontaneously interpret how they are viewed by other people (i.e., meta-perceptions) and often in a self-flattering manner. Very little is known about the neural associations of meta-perceptions, but a likely candidate is the ventromedial pFC (VMPFC). VMPFC has been associated with both self- and other-perception as well as motivated self-perception. Does this function extend to meta-perceptions? The current study examined neural activity while participants made meta-perceptive interpretations in various social scenarios. A drift-diffusion model was used to test whether the VMPFC is associated with two processes involved in interpreting meta-perceptions in a self-flattering manner: the extent to which the interpretation process involves the preferential accumulation of evidence in favor of a self-flattering interpretation versus the extent to which the interpretation process begins with an expectation that favors a self-flattering outcome. Increased VMPFC activity was associated with the extent to which people preferentially accumulate information when interpreting meta-perceptions under ambiguous conditions and marginally associated with self-flattering meta-perceptions. Together, the present findings illuminate the neural underpinnings of a social cognitive process that has received little attention to date: how we make meaning of others' minds when we think those minds are pointed at us.

Empathy, the ability to understand others' emotions, can occur through perspective taking and experience sharing. Neural systems active when adults empathize include regions underlying perspective taking (e.g. medial prefrontal cortex; MPFC) and experience sharing (e.g. inferior parietal lobule; IPL). It is unknown whether adolescents utilize networks implicated in both experience sharing and perspective taking when accurately empathizing. This question is critical given the importance of accurately understanding others' emotions for developing and maintaining adaptive peer relationships during adolescence. We extend the literature on empathy in adolescence by determining the neural basis of empathic accuracy, a behavioral assay of empathy that does not bias participants toward the exclusive use of perspective taking or experience sharing. Participants (N = 155, aged 11.1-15.5 years) watched videos of 'targets' describing emotional events and continuously rated the targets' emotions during functional magnetic resonance imaging scanning. Empathic accuracy related to activation in regions underlying perspective taking (MPFC, temporoparietal junction and superior temporal sulcus), while activation in regions underlying experience sharing (IPL, anterior cingulate cortex and anterior insula) related to lower empathic accuracy. These results provide novel insight into the neural basis of empathic accuracy in adolescence and suggest that perspective taking processes may be effective for increasing empathy., (© The Author (2017). Published by Oxford University Press.)

Even after thorough preprocessing and a careful time series analysis of functional magnetic resonance imaging (fMRI) data, artifact and other issues can lead to violations of the assumption that the variance is constant across subjects in the group level model. This is especially concerning when modeling a continuous covariate at the group level, as the slope is easily biased by outliers. Various models have been proposed to deal with outliers including models that use the first level variance or that use the group level residual magnitude to differentially weight subjects. The most typically used robust regression, implementing a robust estimator of the regression slope, has been previously studied in the context of fMRI studies and was found to perform well in some scenarios, but a loss of Type I error control can occur for some outlier settings. A second type of robust regression using a heteroscedastic autocorrelation consistent (HAC) estimator, which produces robust slope and variance estimates has been shown to perform well, with better Type I error control, but with large sample sizes (500-1000 subjects). The Type I error control with smaller sample sizes has not been studied in this model and has not been compared to other modeling approaches that handle outliers such as FSL's Flame 1 and FSL's outlier de-weighting. Focusing on group level inference with a continuous covariate over a range of sample sizes and degree of heteroscedasticity, which can be driven either by the within- or between-subject variability, both styles of robust regression are compared to ordinary least squares (OLS), FSL's Flame 1, Flame 1 with outlier de-weighting algorithm and Kendall's Tau. Additionally, subject omission using the Cook's Distance measure with OLS and nonparametric inference with the OLS statistic are studied. Pros and cons of these models as well as general strategies for detecting outliers in data and taking precaution to avoid inflated Type I error rates are discussed., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Even after thorough preprocessing and a careful time series analysis of functional magnetic resonance imaging (fMRI) data, artifact and other issues can lead to violations of the assumption that the variance is constant across subjects in the group level model. This is especially concerning when modeling a continuous covariate at the group level, as the slope is easily biased by outliers. Various models have been proposed to deal with outliers including models that use the first level variance or that use the group level residual magnitude to differentially weight subjects. The most typically used robust regression, implementing a robust estimator of the regression slope, has been previously studied in the context of fMRI studies and was found to perform well in some scenarios, but a loss of Type I error control can occur for some outlier settings. A second type of robust regression using a heteroscedastic autocorrelation consistent (HAC) estimator, which produces robust slope and variance estimates has been shown to perform well, with better Type I error control, but with large sample sizes (500-1000 subjects). The Type I error control with smaller sample sizes has not been studied in this model and has not been compared to other modeling approaches that handle outliers such as FSL's Flame 1 and FSL's outlier de-weighting. Focusing on group level inference with a continuous covariate over a range of sample sizes and degree of heteroscedasticity, which can be driven either by the within- or between-subject variability, both styles of robust regression are compared to ordinary least squares (OLS), FSL's Flame 1, Flame 1 with outlier de-weighting algorithm and Kendall's Tau. Additionally, subject omission using the Cook's Distance measure with OLS and nonparametric inference with the OLS statistic are studied. Pros and cons of these models as well as general strategies for detecting outliers in data and taking precaution to avoid inflated Type I error rates are discussed., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Older and younger adults performed a state-based decision-making task while undergoing functional MRI (fMRI). We proposed that younger adults would be more prone to base their decisions on expected value comparisons, but that older adults would be more reactive decision-makers who would act in response to recent changes in rewards or states, rather than on a comparison of expected values. To test this we regressed BOLD activation on two measures from a sophisticated reinforcement learning (RL) model. A value-based regressor was computed by subtracting the immediate value of the selected alternative from its long-term value. The other regressor was a state-change uncertainty signal that served as a proxy for whether the participant's state improved or declined, relative to the previous trial. Younger adults' activation was modulated by the value-based regressor in ventral striatal and medial PFC regions implicated in reinforcement learning. Older adults' activation was modulated by state-change uncertainty signals in right dorsolateral PFC, and activation in this region was associated with improved performance in the task. This suggests that older adults may depart from standard expected-value based strategies and recruit lateral PFC regions to engage in reactive decision-making strategies., (Copyright © 2016 Elsevier Inc. All rights reserved.)

One of the most difficult category learning problems for humans is learning nonnative speech categories. While feedback-based category training can enhance speech learning, the mechanisms underlying these benefits are unclear. In this functional magnetic resonance imaging study, we investigated neural and computational mechanisms underlying feedback-dependent speech category learning in adults. Positive feedback activated a large corticostriatal network including the dorsolateral prefrontal cortex, inferior parietal lobule, middle temporal gyrus, caudate, putamen, and the ventral striatum. Successful learning was contingent upon the activity of domain-general category learning systems: the fast-learning reflective system, involving the dorsolateral prefrontal cortex that develops and tests explicit rules based on the feedback content, and the slow-learning reflexive system, involving the putamen in which the stimuli are implicitly associated with category responses based on the reward value in feedback. Computational modeling of response strategies revealed significant use of reflective strategies early in training and greater use of reflexive strategies later in training. Reflexive strategy use was associated with increased activation in the putamen. Our results demonstrate a critical role for the reflexive corticostriatal learning system as a function of response strategy and proficiency during speech category learning., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Psychiatric disorders are characterized by major fluctuations in psychological function over the course of weeks and months, but the dynamic characteristics of brain function over this timescale in healthy individuals are unknown. Here, as a proof of concept to address this question, we present the MyConnectome project. An intensive phenome-wide assessment of a single human was performed over a period of 18 months, including functional and structural brain connectivity using magnetic resonance imaging, psychological function and physical health, gene expression and metabolomics. A reproducible analysis workflow is provided, along with open access to the data and an online browser for results. We demonstrate dynamic changes in brain connectivity over the timescales of days to months, and relations between brain connectivity, gene expression and metabolites. This resource can serve as a testbed to study the joint dynamics of human brain and metabolic function over time, an approach that is critical for the development of precision medicine strategies for brain disorders.

The episodic memory system enables accurate retrieval while maintaining flexibility by representing both specific episodes and generalizations across events. Although theories suggest that the hippocampus (HPC) is dedicated to represent specific episodes while the medial prefrontal cortex (MPFC) generalizes, other accounts posit that HPC can also integrate related memories. Here we use high-resolution functional magnetic resonance imaging in humans to examine how representations of memory elements change to either differentiate or generalize across related events. We show that while posterior HPC and anterior MPFC maintain distinct memories for individual events, anterior HPC and posterior MPFC integrate across memories. Integration is particularly likely for established memories versus those encoded simultaneously, highlighting the greater impact of prior knowledge on new encoding. We also show dissociable coding signatures in ventrolateral PFC, a region previously implicated in interference resolution. These data highlight how memory elements are represented to simultaneously promote generalization across memories and protect from interference.

Resting state functional MRI (fMRI) has enabled description of group-level functional brain organization at multiple spatial scales. However, cross-subject averaging may obscure patterns of brain organization specific to each individual. Here, we characterized the brain organization of a single individual repeatedly measured over more than a year. We report a reproducible and internally valid subject-specific areal-level parcellation that corresponds with subject-specific task activations. Highly convergent correlation network estimates can be derived from this parcellation if sufficient data are collected-considerably more than typically acquired. Notably, within-subject correlation variability across sessions exhibited a heterogeneous distribution across the cortex concentrated in visual and somato-motor regions, distinct from the pattern of intersubject variability. Further, although the individual's systems-level organization is broadly similar to the group, it demonstrates distinct topological features. These results provide a foundation for studies of individual differences in cortical organization and function, especially for special or rare individuals. VIDEO ABSTRACT., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Older adults experience parallel changes in sleep, circadian rhythms, and episodic memory. These processes appear to be linked such that disruptions in sleep contribute to deficits in memory. Although more variability in circadian patterns is a common feature of aging and predicts pathology, little is known about how alterations in circadian activity rhythms within older adults influence new episodic learning. Following 10 days of recording sleep-wake patterns using actigraphy, healthy older adults underwent fMRI while performing an associative memory task. The results revealed better associative memory was related to more consistent circadian activity rhythms, independent of total sleep time, sleep efficiency, and level of physical activity. Moreover, hippocampal activity during successful memory retrieval events was positively correlated with associative memory accuracy and circadian activity rhythm (CAR) consistency. We demonstrated that the link between consistent rhythms and associative memory performance was mediated by hippocampal activity. These findings provide novel insight into how the circadian rhythm of sleep-wake cycles are associated with memory in older adults and encourage further examination of circadian activity rhythms as a biomarker of cognitive functioning., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

The occurrence of collinearity in fMRI-based GLMs (general linear models) may reduce power or produce unreliable parameter estimates. It is commonly believed that orthogonalizing collinear regressors in the model will solve this problem, and some software packages apply automatic orthogonalization. However, the effects of orthogonalization on the interpretation of the resulting parameter estimates is widely unappreciated or misunderstood. Here we discuss the nature and causes of collinearity in fMRI models, with a focus on the appropriate uses of orthogonalization. Special attention is given to how the two popular fMRI data analysis software packages, SPM and FSL, handle orthogonalization, and pitfalls that may be encountered in their usage. Strategies are discussed for reducing collinearity in fMRI designs and addressing their effects when they occur.

There is a large gap between the types of risky behavior we recommend to others and those we engage in ourselves. In this study, we hypothesized that a source of this gap is greater reliance on information about others' behavior when deciding whether to take a risk oneself than when deciding whether to recommend it to others. To test this hypothesis, we asked participants either to report their willingness to engage in a series of risky behaviors themselves; their willingness to recommend those behaviors to a loved one; or, how good of an idea it would be for either them or a loved one to engage in the behaviors. We then asked them to evaluate those behaviors on criteria related to the expected utility of the risk (benefits, costs, and likelihood of costs), and on engagement in the activity by people they knew. We found that, after accounting for effects of perceived benefit, cost, and likelihood of cost, perceptions of others' behavior had a dramatically larger impact on participants' willingness to engage in a risk than on their willingness to recommend the risk or their prescriptive evaluation of the risk. These findings indicate that the influence of others' choices on risk-taking behavior is large, direct, cannot be explained by an economic utility model of risky decision-making, and goes against one's own better judgment.

A prerequisite for a pattern analysis using functional magnetic resonance imaging (fMRI) data is estimating the patterns from time series data, which then are input into the pattern analysis. Here we focus on how the combination of study design (order and spacing of trials) with pattern estimator impacts the Type I error rate of the subsequent pattern analysis. When Type I errors are inflated, the results are no longer valid, so this work serves as a guide for designing and analyzing MVPA studies with controlled false positive rates. The MVPA strategies examined are pattern classification and similarity, utilizing single trial activation patterns from the same functional run. Primarily focusing on the Least Squares Single and Least Square All pattern estimators, we show that collinearities in the models, along with temporal autocorrelation, can cause false positive correlations between activation pattern estimates that adversely impact the false positive rates of pattern similarity and classification analyses. It may seem intuitive that increasing the interstimulus interval (ISI) would alleviate this issue, but remaining weak correlations between activation patterns persist and have a strong influence in pattern similarity analyses. Pattern similarity analyses using only activation patterns estimated from the same functional run of data are susceptible to inflated false positives unless trials are randomly ordered, with a different randomization for each subject. In other cases, where there is any structure to trial order, valid pattern similarity analysis results can only be obtained if similarity computations are restricted to pairs of activation patterns from independent runs. Likewise, for pattern classification, false positives are minimized when the testing and training sets in cross validation do not contain patterns estimated from the same run., (Copyright © 2014 Elsevier Inc. All rights reserved.)

Multi-voxel pattern analysis (MVPA) has led to major changes in how fMRI data are analyzed and interpreted. Many studies now report both MVPA results and results from standard univariate voxel-wise analysis, often with the goal of drawing different conclusions from each. Because MVPA results can be sensitive to latent multidimensional representations and processes whereas univariate voxel-wise analysis cannot, one conclusion that is often drawn when MVPA and univariate results differ is that the activation patterns underlying MVPA results contain a multidimensional code. In the current study, we conducted simulations to formally test this assumption. Our findings reveal that MVPA tests are sensitive to the magnitude of voxel-level variability in the effect of a condition within subjects, even when the same linear relationship is coded in all voxels. We also find that MVPA is insensitive to subject-level variability in mean activation across an ROI, which is the primary variance component of interest in many standard univariate tests. Together, these results illustrate that differences between MVPA and univariate tests do not afford conclusions about the nature or dimensionality of the neural code. Instead, targeted tests of the informational content and/or dimensionality of activation patterns are critical for drawing strong conclusions about the representational codes that are indicated by significant MVPA results., (Copyright © 2014 Elsevier Inc. All rights reserved.)

The stop-signal task, in which participants must inhibit prepotent responses, has been used to identify neural systems that vary with individual differences in inhibitory control. To explore how these differences relate to other aspects of decision making, a drift-diffusion model of simple decisions was fitted to stop-signal task data from go trials to extract measures of caution, motor execution time, and stimulus processing speed for each of 123 participants. These values were used to probe fMRI data to explore individual differences in neural activation. Faster processing of the go stimulus correlated with greater activation in the right frontal pole for both go and stop trials. On stop trials, stimulus processing speed also correlated with regions implicated in inhibitory control, including the right inferior frontal gyrus, medial frontal gyrus, and BG. Individual differences in motor execution time correlated with activation of the right parietal cortex. These findings suggest a robust relationship between the speed of stimulus processing and inhibitory processing at the neural level. This model-based approach provides novel insight into the interrelationships among decision components involved in inhibitory control and raises interesting questions about strategic adjustments in performance and inhibitory deficits associated with psychopathology.