Lessons learned: A neuroimaging research center's transition to open and reproducible science.

Human functional neuroimaging has evolved dramatically in recent years, driven by increased technical complexity and emerging evidence that functional neuroimaging findings are not generally reproducible. In response to these trends, neuroimaging scientists have developed principles, practices, and tools to both manage this complexity as well as to enhance the rigor and reproducibility of neuroimaging science. We group these best practices under four categories: experiment pre-registration, FAIR data principles, reproducible neuroimaging analyses, and open science. While there is growing recognition of the need to implement these best practices there exists little practical guidance of how to accomplish this goal. In this work, we describe lessons learned from efforts to adopt these best practices within the Brain Imaging Research Center at the University of Arkansas for Medical Sciences over 4 years (July 2018-May 2022). We provide a brief summary of the four categories of best practices. We then describe our center's scientific workflow (from hypothesis formulation to result reporting) and detail how each element of this workflow maps onto these four categories. We also provide specific examples of practices or tools that support this mapping process. Finally, we offer a roadmap for the stepwise adoption of these practices, providing recommendations of why and what to do as well as a summary of cost-benefit tradeoffs for each step of the transition.

Action-value processing underlies the role of the dorsal anterior cingulate cortex in performance monitoring during self-regulation of affect.

In this study, we merged methods from engineering control theory, machine learning, and human neuroimaging to critically test the putative role of the dorsal anterior cingulate cortex (dACC) in goal-directed performance monitoring during an emotion regulation task. Healthy adult participants (n = 94) underwent cued-recall and re-experiencing of their responses to affective image stimuli with concurrent functional magnetic resonance imaging and psychophysiological response recording. During cued-recall/re-experiencing trials, participants engaged in explicit self-regulation of their momentary affective state to match a pre-defined affective goal state. Within these trials, neural decoding methods measured affect processing from fMRI BOLD signals across the orthogonal affective dimensions of valence and arousal. Participants' affective brain states were independently validated via facial electromyography (valence) and electrodermal activity (arousal) responses. The decoded affective states were then used to contrast four computational models of performance monitoring (i.e., error, predicted response outcome, action-value, and conflict) by their relative abilities to explain emotion regulation task-related dACC activation. We found that the dACC most plausibly encodes action-value for both valence and arousal processing. We also confirmed that dACC activation directly encodes affective arousal and also likely encodes recruitment of attention and regulation resources. Beyond its contribution to improving our understanding of the roles that the dACC plays in emotion regulation, this study introduced a novel analytical framework through which affect processing and regulation may be functionally dissociated, thereby permitting mechanistic analysis of real-world emotion regulation strategies, e.g., distraction and reappraisal, which are widely employed in cognitive behavioral therapy to address clinical deficits in emotion regulation.

A test of affect processing bias in response to affect regulation.

In this study we merged methods from machine learning and human neuroimaging to test the role of self-induced affect processing states in biasing the affect processing of subsequent image stimuli. To test this relationship we developed a novel paradigm in which (n = 40) healthy adult participants observed affective neural decodings of their real-time functional magnetic resonance image (rtfMRI) responses as feedback to guide explicit regulation of their brain (and corollary affect processing) state towards a positive valence goal state. By this method individual differences in affect regulation ability were controlled. Attaining this brain-affect goal state triggered the presentation of pseudo-randomly selected affectively congruent (positive valence) or incongruent (negative valence) image stimuli drawn from the International Affective Picture Set. Separately, subjects passively viewed randomly triggered positively and negatively valent image stimuli during fMRI acquisition. Multivariate neural decodings of the affect processing induced by these stimuli were modeled using the task trial type (state- versus randomly-triggered) as the fixed-effect of a general linear mixed-effects model. Random effects were modeled subject-wise. We found that self-induction of a positive valence brain state significantly positively biased valence processing of subsequent stimuli. As a manipulation check, we validated affect processing state induction achieved by the image stimuli using independent psychophysiological response measures of hedonic valence and autonomic arousal. We also validated the predictive fidelity of the trained neural decoding models using brain states induced by an out-of-sample set of image stimuli. Beyond its contribution to our understanding of the neural mechanisms that bias affect processing, this work demonstrated the viability of novel experimental paradigms triggered by pre-defined cognitive states. This line of individual differences research potentially provides neuroimaging scientists with a valuable tool for exploring the roles and identities of intrinsic cognitive processing mechanisms that shape our perceptual processing of sensory stimuli.

L-DOPA and consolidation of fear extinction learning among women with posttraumatic stress disorder.

This study tested whether L-DOPA delivered during the consolidation window following fear extinction learning reduces subsequent fear responding among women with PTSD. Adult women diagnosed with PTSD completed a contextual fear acquisition and extinction task during fMRI and then immediately received either placebo (n = 34), 100/25 mg L-DOPA/carbidopa (n = 28), or 200/50 mg L-DOPA/carbidopa (n = 29). Participants completed a resting-state scan before the task and again 45 min following drug ingestion to characterize effects of L-DOPA on extinction memory neural reactivation patterns during consolidation. Twenty-four hours later, participants returned for tests of context renewal, extinction recall, and reinstatement during fMRI with concurrent skin conductance responding (SCR) assessment. Both active drug groups demonstrated increased reactivation of extinction encoding in the amygdala during the post-task resting-state scan. For SCR data, both drug groups exhibited decreased Day 2 reinstatement across all stimuli compared to placebo, and there was some evidence for decreased context renewal to the fear stimulus in the 100 mg group compared to placebo. For imaging data, both drug groups demonstrated decreased Day 2 reinstatement across stimuli in a bilateral insula network compared to placebo. There was no evidence in SCR or neural activity that L-DOPA improved extinction recall. Reactivation of extinction encodings in the amygdala during consolidation on Day 1 predicted Day 2 activation of the insula network. These results support a role for dopamine during the consolidation window in boosting reactivation of amygdala extinction encodings and reducing reinstatement, but not improving extinction recall, in women with PTSD.

Intertemporal decision-making-related brain states predict adolescent drug abuse intervention responses.

Adolescent drug misuse represents a major risk factor for long-term drug use disorders. However, wide individual differences in responses to first-line behavioral therapies targeting adolescent drug misuse limit critical early intervention. Identifying the neural signatures of those adolescents most likely to respond to an intervention would potentially guide personalized strategies for reducing drug misuse. Prior to a 14-week evidence-based intervention involving combinations of contingency management, motivational enhancement, and cognitive behavioral therapy, thirty adolescent alcohol and/or cannabis users underwent fMRI while performing a reward delay discounting (DD) task tapping an addiction-related cognition. Intervention responses were longitudinally characterized by both urinalysis and self-report measures of the percentage of days used during treatment and in post-treatment follow-up. Group independent component analysis (ICA) of task fMRI data identified neural processing networks related to DD task performance. Separate measures of wholesale recruitment during immediate reward choices and within-network functional connectivity among selective networks significantly predicted intervention-related changes in drug misuse frequency. Specifically, heightened pre-intervention engagement of a temporal lobe "reward motivation" network for impulsive choices on the DD task predicted poorer intervention outcomes, while modes of functional connectivity within the reward motivation network, a prospection network, and a posterior insula network demonstrated robust associations with intervention outcomes. Finally, the pre-intervention functional organization of the prospection network also predicted post-intervention drug use behaviors for up to 6 months of follow-up. Multiple functional variations in the neural processing networks supporting preference for immediate and future rewards signal individual differences in readiness to benefit from an effective behavioral therapy for reducing adolescent drug misuse. The implications for efforts to boost therapy responses are discussed.

Differential Roles of the Salience Network During Prediction Error Encoding and Facial Emotion Processing Among Female Adolescent Assault Victims.

BACKGROUND: Early-life assaultive violence exposure is a potent risk factor for posttraumatic stress disorder (PTSD) and other mood and anxiety disorders. Neurocircuitry models posit that increased risk is mediated by heightened emotion processing in a salience network including the dorsal anterior cingulate cortex, anterior insula, and amygdala. However, the processes of reinforcement learning (RL) also engage the salience network and are implicated in responses to early-life trauma and PTSD. To define their relative roles in response to early-life trauma and PTSD symptoms, the current study compared engagement of the salience network during emotion processing and RL as a function of early-life assault exposure. METHODS: Adolescent girls (n = 30 girls who had previously been physically or sexually assaulted; n = 30 healthy girls for comparison) 11 to 17 years of age completed two types of tasks during functional magnetic resonance imaging: a facial emotion processing task and an RL task using either social or nonsocial stimuli. Independent component analysis was used to identify a salience network and characterize its engagement in response to emotion processing and prediction error encoding during the RL tasks. RESULTS: Assault was related to greater reactivity of the salience network during emotion processing. By contrast, we found lesser encoding of negative prediction errors in the salience network, particularly during the social RL task, in girls who had been assaulted. The dysfunction of salience network activity during emotion processing and prediction error encoding was not associated with PTSD symptoms. CONCLUSIONS: These results suggest that hyper- versus hypoactivity of the salience network among trauma-exposed youths depends on the cognitive-affective domain.

Common Functional Brain States Encode both Perceived Emotion and the Psychophysiological Response to Affective Stimuli.

Multivariate pattern analysis (MVPA) of functional magnetic resonance imaging (fMRI) data has critically advanced the neuroanatomical understanding of affect processing in the human brain. Central to these advancements is the brain state, a temporally-succinct fMRI-derived pattern of neural activation, which serves as a processing unit. Establishing the brain state's central role in affect processing, however, requires that it predicts multiple independent measures of affect. We employed MVPA-based regression to predict the valence and arousal properties of visual stimuli sampled from the International Affective Picture System (IAPS) along with the corollary skin conductance response (SCR) for demographically diverse healthy human participants (n = 19). We found that brain states significantly predicted the normative valence and arousal scores of the stimuli as well as the attendant individual SCRs. In contrast, SCRs significantly predicted arousal only. The prediction effect size of the brain state was more than three times greater than that of SCR. Moreover, neuroanatomical analysis of the regression parameters found remarkable agreement with regions long-established by fMRI univariate analyses in the emotion processing literature. Finally, geometric analysis of these parameters also found that the neuroanatomical encodings of valence and arousal are orthogonal as originally posited by the circumplex model of dimensional emotion.

The neural representation of the association between comorbid drug use disorders and childhood maltreatment.

BACKGROUND: Comorbidity of drug use disorders (DUD) with other psychopathology is associated with worse functional and treatment outcomes than DUD alone. The present study sought to identify altered functional neural circuitry underlying DUD comorbidity with other psychiatric disorders, and model the relationship of these alterations to childhood trauma (Childhood Trauma Questionnaire) and negative self-beliefs (Beck Depression Inventory). METHODS: A sample of adult men and women (mean = 36.8 years) with childhood maltreatment histories (n = 81) was allocated into the following groups based on psychiatric diagnoses and drug use history: no current or past psychiatric disorders (trauma control sample, n = 20), DUD only (n = 22), psychopathology only (n = 20), and DUD comorbid with other psychiatric illness (DCoP, n = 25). RESULTS: Multiple regression of seed-based resting-state fMRI, controlling for age and sex, identified a functional connection between the right rostral anterior cingulate cortex (rACC) and left temporoparietal junction (TPJ) that was significantly increased in DCoP females, relative to the other clinical and control groups. Within the DCoP female sample, mediation analysis demonstrated that strength of connectivity between the subgenual cingulate cortex and both the right anterior insula and rostral lateral prefrontal cortex significantly mediated the relationship between increasing physical abuse and self-criticism with age as a moderator. CONCLUSIONS: This study related sex-dependent alterations in functional organization of the prefrontal cortex with DCoP that are, in turn, related to magnitude of negative self-beliefs to childhood trauma exposure. Additionally, DCoP-selective alterations in rACC connectivity suggest that the neural correlates of DCoP do not represent linear additive contributions from two independent disorders.

Does development moderate the effect of early life assaultive violence on resting-state networks? An exploratory study.

Current neurocircuitry models of PTSD do not account for developmental effects, despite that early life assaultive violence is a potent risk factor for PTSD. Here, we preliminarily evaluated developmental stage as a moderator of the effect of early life assaultive violence on resting-state connectivity amongst regions associated with emotion generation and regulation using fMRI. Participants were adult women (n = 25) and adolescent girls (n = 36) who had or had not experienced early life assaultive violence. We found significant interactions between developmental stage and trauma exposure on resting-state functional connectivity (FC). Left amygdala connectivity with the left ventral anterior cingulate gyrus (BA 32) was reduced among trauma-exposed compared to control adolescents, but increased among trauma-exposed compared to control adults. A corresponding pattern of results was identified for FC between rostral anterior cingulate gyrus seed region and a similar right ventral anterior superior frontal gyrus cluster. Increased FC in both regions for assaulted adult women scaled positively with self-reported emotion regulation difficulties. Our results should be viewed tentatively due to sample limitations, but provide impetus to examine whether neurocircuitry models of PTSD may be strengthened by accounting for developmental stage.

Personality variables modify the relationship between childhood maltreatment history and poor functional outcomes.

Childhood maltreatment history is a prevalent risk factor for substance use disorder and has lifelong adverse consequences on psychiatric wellbeing. The role of personality variations in determining childhood maltreatment-associated outcomes is poorly understood. This study sought to test neuroticism and agreeableness as mediator and moderator, respectively, of functional outcomes associated with having a history of childhood maltreatment and presence/absence of cocaine dependence. Ninety-four participants completed the Structured Clinical Interview for DSM-IV (SCID-IV), Childhood Trauma Questionnaire (CTQ), NEO-Five Factor Inventory (NEO-FFI), and the Addiction Severity Index (ASI). The distribution-of-the-product strategy tested if neuroticism mediated the relationship between CTQ and ASI scores. Agreeableness was tested as a moderator using bootstrapped multiple regression analyses with agreeableness*CTQ interaction terms as predictors of ASI scores. Analyses covaried for cocaine dependence to determine its influence. Neuroticism mediated the relationship between severity of childhood maltreatment history and family (ASI-Family) and psychiatric (ASI-Psychiatric) dysfunction in adulthood, independent of cocaine dependence. Agreeableness negatively moderated the effect of childhood maltreatment severity on family dysfunction. Exposure to emotional neglect and abuse selectively drove the mediation and moderation effects. Personality-directed interventions that reduce neuroticism or increase agreeableness may be promising approaches to uncouple childhood maltreatment history from lifelong social and psychiatric dysfunction.

Brain States That Encode Perceived Emotion Are Reproducible but Their Classification Accuracy Is Stimulus-Dependent.

The brain state hypothesis of image-induced affect processing, which posits that a one-to-one mapping exists between each image stimulus and its induced functional magnetic resonance imaging (fMRI)-derived neural activation pattern (i.e., brain state), has recently received support from several multivariate pattern analysis (MVPA) studies. Critically, however, classification accuracy differences across these studies, which largely share experimental designs and analyses, suggest that there exist one or more unaccounted sources of variance within MVPA studies of affect processing. To explore this possibility, we directly demonstrated strong inter-study correlations between image-induced affective brain states acquired 4 years apart on the same MRI scanner using near-identical methodology with studies differing only by the specific image stimuli and subjects. We subsequently developed a plausible explanation for inter-study differences in affective valence and arousal classification accuracies based on the spatial distribution of the perceived affective properties of the stimuli. Controlling for this distribution improved valence classification accuracy from 56% to 85% and arousal classification accuracy from 61% to 78%, which mirrored the full range of classification accuracy across studies within the existing literature. Finally, we validated the predictive fidelity of our image-related brain states according to an independent measurement, autonomic arousal, captured via skin conductance response (SCR). Brain states significantly but weakly (r = 0.08) predicted the SCRs that accompanied individual image stimulations. More importantly, the effect size of brain state predictions of SCR increased more than threefold (r = 0.25) when the stimulus set was restricted to those images having group-level significantly classifiable arousal properties.

Altered neural encoding of prediction errors in assault-related posttraumatic stress disorder.

Posttraumatic stress disorder (PTSD) is widely associated with deficits in extinguishing learned fear responses, which relies on mechanisms of reinforcement learning (e.g., updating expectations based on prediction errors). However, the degree to which PTSD is associated with impairments in general reinforcement learning (i.e., outside of the context of fear stimuli) remains poorly understood. Here, we investigate brain and behavioral differences in general reinforcement learning between adult women with and without a current diagnosis of PTSD. 29 adult females (15 PTSD with exposure to assaultive violence, 14 controls) underwent a neutral reinforcement-learning task (i.e., two arm bandit task) during fMRI. We modeled participant behavior using different adaptations of the Rescorla-Wagner (RW) model and used Independent Component Analysis to identify timecourses for large-scale a priori brain networks. We found that an anticorrelated and risk sensitive RW model best fit participant behavior, with no differences in computational parameters between groups. Women in the PTSD group demonstrated significantly less neural encoding of prediction errors in both a ventral striatum/mPFC and anterior insula network compared to healthy controls. Weakened encoding of prediction errors in the ventral striatum/mPFC and anterior insula during a general reinforcement learning task, outside of the context of fear stimuli, suggests the possibility of a broader conceptualization of learning differences in PTSD than currently proposed in current neurocircuitry models of PTSD.

Large-scale brain organization during facial emotion processing as a function of early life trauma among adolescent girls.

Background: A wealth of research has investigated the impact of early life trauma exposure on functional brain activation during facial emotion processing and has often demonstrated amygdala hyperactivity and weakened connectivity between amygdala and medial PFC (mPFC). There have been notably limited investigations linking these previous node-specific findings into larger-scale network models of brain organization. Method: To address these gaps, we applied graph theoretical analyses to fMRI data collected during a facial emotion processing task among 88 adolescent girls (n = 59 exposed to direct physical or sexual assault; n = 29 healthy controls), aged 11-17, during fMRI. Large-scale organization indices of modularity, assortativity, and global efficiency were calculated for stimulus-specific functional connectivity using an 883 region-of-interest parcellation. Results: Among the entire sample, more severe early life trauma was associated with more modular and assortative, but less globally efficient, network organization across all stimulus categories. Among the assaulted girls, severity of early life trauma and PTSD diagnoses were both simultaneously related to increased modular brain organization. We also found that more modularized network organization was related both to amygdala hyperactivation and weakened connectivity between amygdala and medial PFC. Conclusions: These results demonstrate that early life trauma is associated with enhanced brain organization during facial emotion processing and that this pattern of brain organization might explain the commonly observed association between childhood trauma and amygdala hyperactivity and weakened connectivity with mPFC. Implications of these results for neurocircuitry models are discussed.

Distributed Neural Processing Predictors of Multi-dimensional Properties of Affect.

Recent evidence suggests that emotions have a distributed neural representation, which has significant implications for our understanding of the mechanisms underlying emotion regulation and dysregulation as well as the potential targets available for neuromodulation-based emotion therapeutics. This work adds to this evidence by testing the distribution of neural representations underlying the affective dimensions of valence and arousal using representational models that vary in both the degree and the nature of their distribution. We used multi-voxel pattern classification (MVPC) to identify whole-brain patterns of functional magnetic resonance imaging (fMRI)-derived neural activations that reliably predicted dimensional properties of affect (valence and arousal) for visual stimuli viewed by a normative sample (n = 32) of demographically diverse, healthy adults. Inter-subject leave-one-out cross-validation showed whole-brain MVPC significantly predicted (p < 0.001) binarized normative ratings of valence (positive vs. negative, 59% accuracy) and arousal (high vs. low, 56% accuracy). We also conducted group-level univariate general linear modeling (GLM) analyses to identify brain regions whose response significantly differed for the contrasts of positive versus negative valence or high versus low arousal. Multivoxel pattern classifiers using voxels drawn from all identified regions of interest (all-ROIs) exhibited mixed performance; arousal was predicted significantly better than chance but worse than the whole-brain classifier, whereas valence was not predicted significantly better than chance. Multivoxel classifiers derived using individual ROIs generally performed no better than chance. Although performance of the all-ROI classifier improved with larger ROIs (generated by relaxing the clustering threshold), performance was still poorer than the whole-brain classifier. These findings support a highly distributed model of neural processing for the affective dimensions of valence and arousal. Finally, joint error analyses of the MVPC hyperplanes encoding valence and arousal identified regions within the dimensional affect space where multivoxel classifiers exhibited the greatest difficulty encoding brain states - specifically, stimuli of moderate arousal and high or low valence. In conclusion, we highlight new directions for characterizing affective processing for mechanistic and therapeutic applications in affective neuroscience.

Modes of Large-Scale Brain Network Organization during Threat Processing and Posttraumatic Stress Disorder Symptom Reduction during TF-CBT among Adolescent Girls.

Posttraumatic stress disorder (PTSD) is often chronic and disabling across the lifespan. The gold standard treatment for adolescent PTSD is Trauma-Focused Cognitive-Behavioral Therapy (TF-CBT), though treatment response is variable and mediating neural mechanisms are not well understood. Here, we test whether PTSD symptom reduction during TF-CBT is associated with individual differences in large-scale brain network organization during emotion processing. Twenty adolescent girls, aged 11-16, with PTSD related to assaultive violence completed a 12-session protocol of TF-CBT. Participants completed an emotion processing task, in which neutral and fearful facial expressions were presented either overtly or covertly during 3T fMRI, before and after treatment. Analyses focused on characterizing network properties of modularity, assortativity, and global efficiency within an 824 region-of-interest brain parcellation separately during each of the task blocks using weighted functional connectivity matrices. We similarly analyzed an existing dataset of healthy adolescent girls undergoing an identical emotion processing task to characterize normative network organization. Pre-treatment individual differences in modularity, assortativity, and global efficiency during covert fear vs neutral blocks predicted PTSD symptom reduction. Patients who responded better to treatment had greater network modularity and assortativity but lesser efficiency, a pattern that closely resembled the control participants. At a group level, greater symptom reduction was associated with greater pre-to-post-treatment increases in network assortativity and modularity, but this was more pronounced among participants with less symptom improvement. The results support the hypothesis that modularized and resilient brain organization during emotion processing operate as mechanisms enabling symptom reduction during TF-CBT.

Functional independence in resting-state connectivity facilitates higher-order cognition.

Growing evidence suggests that intrinsic functional connectivity (i.e. highly structured patterns of communication between brain regions during wakeful rest) may encode cognitive ability. However, the generalizability of these findings is limited by between-study differences in statistical methodology and cognitive domains evaluated. To address this barrier, we evaluated resting-state neural representations of multiple cognitive domains within a relatively large normative adult sample. Forty-four participants (mean(sd) age=31(10) years; 18 male and 26 female) completed a resting-state functional MRI scan and neuropsychological assessments spanning motor, visuospatial, language, learning, memory, attention, working memory, and executive function performance. Robust linear regression related cognitive performance to resting-state connectivity among 200 a priori determined functional regions of interest (ROIs). Only higher-order cognitions (such as learning and executive function) demonstrated significant relationships between brain function and behavior. Additionally, all significant relationships were negative - characterized by moderately positive correlations among low performers and weak to moderately negative correlations among high performers. These findings suggest that functional independence among brain regions at rest facilitates cognitive performance. Our interpretation is consistent with graph theoretic analyses which represent the brain as independent functional nodes that undergo dynamic reorganization with task demand. Future work will build upon these findings by evaluating domain-specific variance in resting-state neural representations of cognitive impairment among patient populations.

Amygdala response predicts trajectory of symptom reduction during Trauma-Focused Cognitive-Behavioral Therapy among adolescent girls with PTSD.

Trauma-Focused Cognitive-Behavioral Therapy (TF-CBT) is the gold standard treatment for pediatric PTSD. Nonetheless, clinical outcomes in TF-CBT are highly variable, indicating a need to identify reliable predictors that allow forecasting treatment response. Here, we test the hypothesis that functional neuroimaging correlates of emotion processing predict PTSD symptom reduction during Trauma-Focused Cognitive-Behavioral Therapy (TF-CBT) among adolescent girls with PTSD. Thirty-four adolescent girls with PTSD related to physical or sexual assault were enrolled in TF-CBT, delivered in an approximately 12 session format, in an open trial. Prior to treatment, they were engaged in an implicit threat processing task during 3T fMRI, during which they viewed faces depicting fearful or neutral expressions. Among adolescent girls completing TF-CBT (n = 23), slopes of PTSD symptom trajectories during TF-CBT were significantly related to pre-treatment degree of bilateral amygdala activation while viewing fearful vs neutral images. Adolescents with less symptom reduction were characterized by greater amygdala activation to both threat and neutral images (i.e., less threat-safety discrimination), whereas adolescents with greater symptom reduction were characterized by amygdala activation only to threat images. These clinical outcome relationships with pre-treatment bilateral amygdala activation remained when controlling for possible confounding demographic or clinical variables (e.g., concurrent psychotropic medication, comorbid diagnoses). While limited by a lack of a control group, these preliminary results suggest that pre-treatment amygdala reactivity to fear stimuli, a component of neurocircuitry models of PTSD, positively predicts symptom reduction during TF-CBT among assaulted adolescent girls, providing support for an objective measure for forecasting treatment response in this vulnerable population.

Synthesis, binding affinity, radiolabeling, and microPET evaluation of 4-(2-substituted-4-substituted)-8-(dialkylamino)-6-methyl-1-substituted-3,4-dihydropyrido[2,3-b]pyrazin-2(1H)-ones as ligands for brain corticotropin-releasing factor type-1 (CRF1) receptors.

Compounds 1-14 were synthesized in a search for high-affinity CRF1 receptor ligands that could be radiolabeled with (11)C or (18)F for use as positron emission tomography (PET) radiotracers. Derivatives of 2 were developed which contained amide N-fluoroalkyl substituents. Compounds [(18)F]24 and [(18)F]25 were found to have appropriate lipophilicities of logP7.4=2.2 but microPET imaging with [(18)F]25 demonstrated limited brain uptake.

Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback.

Posttraumatic Stress Disorder (PTSD) is characterized by intrusive recall of the traumatic memory. While numerous studies have investigated the neural processing mechanisms engaged during trauma memory recall in PTSD, these analyses have only focused on group-level contrasts that reveal little about the predictive validity of the identified brain regions. By contrast, a multivariate pattern analysis (MVPA) approach towards identifying the neural mechanisms engaged during trauma memory recall would entail testing whether a multivariate set of brain regions is reliably predictive of (i.e., discriminates) whether an individual is engaging in trauma or non-trauma memory recall. Here, we use a MVPA approach to test 1) whether trauma memory vs neutral memory recall can be predicted reliably using a multivariate set of brain regions among women with PTSD related to assaultive violence exposure (N=16), 2) the methodological parameters (e.g., spatial smoothing, number of memory recall repetitions, etc.) that optimize classification accuracy and reproducibility of the feature weight spatial maps, and 3) the correspondence between brain regions that discriminate trauma memory recall and the brain regions predicted by neurocircuitry models of PTSD. Cross-validation classification accuracy was significantly above chance for all methodological permutations tested; mean accuracy across participants was 76% for the methodological parameters selected as optimal for both efficiency and accuracy. Classification accuracy was significantly better for a voxel-wise approach relative to voxels within restricted regions-of-interest (ROIs); classification accuracy did not differ when using PTSD-related ROIs compared to randomly generated ROIs. ROI-based analyses suggested the reliable involvement of the left hippocampus in discriminating memory recall across participants and that the contribution of the left amygdala to the decision function was dependent upon PTSD symptom severity. These results have methodological implications for real-time fMRI neurofeedback of the trauma memory in PTSD and conceptual implications for neurocircuitry models of PTSD that attempt to explain core neural processing mechanisms mediating PTSD.