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ACNP 59Th Annual Meeting: Poster Session II www.nature.com/npp ABSTRACTS COLLECTION ACNP 59th Annual Meeting: Poster Session II Neuropsychopharmacology (2020) 45:170–277; https://doi.org/10.1038/s41386-020-00891-6 Sponsorship Statement: Publication of this supplement is sponsored by the ACNP. Presenting author disclosures may be found within the abstracts. Asterisks in the author lists indicate presenter of the abstract at the annual meeting. T1. Structural Covariance Network Stability Over Time After between unidimensional posttraumatic syndromes (e.g., PTSD, Trauma Exposure: Preliminary Assessment of Longitudinal depression, and anxiety) and component loadings. Analyses of the Multimodal MRI Data From the Aurora Study relationships between changes in component loadings and changes in unidimensional outcome data are planned pending Nathaniel Harnett*, Timothy Ely, Sanne van Rooij, Katherine the release of 6-month psychometric data. Finegold, Lauren LeBois, Vishnu Murty, Tanja Jovanovic, Kerry Results: ICCs across the components were generally high with Ressler, Jennifer Stevens 59 of the components demonstrating ICCs of 0.99, but another 44 components showed relatively low ICCs (<0.5). The most reliable Harvard Medical School/McLean Hospital, Belmont, Massachusetts, component (ICC = 0.999, p < 0.001) was a multimodal component United States of predominantly GMV (26%), PSA (21%), MO (18%) and FA (16%) 1234567890();,: and was reflective of increased gray matter of the insula, Background: The structure of human neural circuits is critical for dorsolateral prefrontal cortex (PFC), and ventromedial PFC, and neurocognitive processes that maintain healthy emotional func- altered white matter of the cingulum, uncinate fasciculus, and tion. Prior human and animal model research suggests that inferior longitudinal fasciculus. Interestingly, LICA also separated trauma/stress exposure can trigger maladaptive processes that “noise” from “signal” components, with some of the noise may lead to brain structure changes that contribute to posttrau- components demonstrating high ICC values (0.95–0.99, p < matic dysfunction. However, limited work to date has investigated 0.001). These high ICC components reflected participant-specific how changes in brain structure over time relate to changes in idiosyncrasies (e.g., distinct patterns of spatial variability) across posttraumatic symptoms. Further, prior research has largely used the modalities. Independent samples t-tests of high and low unimodal approaches which do not take into account shared posttraumatic stress severity at 2-weeks post-trauma also revealed variability between brain measures (i.e., noting that brain gray differences in two components, with one representing greater and white matter likely covary). Therefore, the present study GMV (39%) and PSA (53%) of the temporal gyrus and posterior utilized longitudinal multimodal magnetic resonance imaging hippocampus [t(45) = 2.18, p = 0.04; ICC = 0.01, p = 0.455] and (MRI) to investigate potential changes in structural covariance the other representing greater GMV (49%) and PSA (17%) of the networks. anterior temporal lobe and visual cortex [t(45) = 2.43, p = 0.02, Methods: Participants were recruited from emergency depart- ICC = −0.22, p = 0.949]. High posttraumatic stress severity was ments following trauma exposure (primarily motor vehicle associated with lower loadings for both components and the low collisions) as part of the AURORA Study, a multisite longitudinal ICCs suggest these components are highly variable between fl investigation of posttraumatic syndromes. In the current analysis, timepoints, potentially re ecting changes with the process of an initial dataset of 363 participants completed MRI scans within recovery (to be tested with the release of 6 month data). a) ~2-weeks, b) ~6-months, or c) both ~2-weeks and ~6-months Conclusions: Multimodal structural covariance networks post-trauma. Following quality control and removal of participants assessed in recently traumatized individuals are generally stable = between 2-weeks and 6-months following trauma exposure. missing scan modalities, n 248 participants were included in a fi fi multimodal data fusion analysis with n = 54 scanned at both Participant-speci c variance related to time was also identi ed through LICA and demonstrated high stability. These results timepoints. Structural MRI processing through a combination of suggest participant-specific variance can be readily separated FMRIPPREP and FSLVBM was completed to obtain measures of from group-level SCNs that may be related to later posttraumatic gray-matter volume (GMV), cortical thickness (CT), and pial surface outcomes. Preliminary analyses also revealed two SCNs that varied area (PSA) to index gray matter properties. Diffusion tensor with acute posttraumatic stress symptoms and these networks imaging was completed to obtain measures of fractional reflected variability in gray matter properties within regions of the anisotropy (FA), mean diffusivity (MD), and mode of the diffusion ventral visual stream. Interestingly, our prior work showed an tensor (MO) of the white matter skeleton. Data fusion was inverse relationship to the one observed here such that greater completed using linked independent components analysis (LICA) gray matter properties of the ventral visual stream were of the above brain structure features. A high dimensionality was associated with greater posttraumatic stress symptoms. These estimated (d = 119) to better separate participant-specific noise findings may be related to differences in when MRI data was from signal data. LICA returns a participant-specific value for the assessed given the low stability of loadings from these loading of each component, with each component representing components over time. Longitudinal assessment of multimodal shared variance across the feature modalities. For the 54 structural covariance networks may provide important informa- participants with longitudinal data, intraclass correlation coeffi- tion on structural changes relevant to assessing susceptibility to cients (ICC) were obtained to evaluate the stability of the observed posttraumatic stress and identifying brain changes associated with components. Preliminary analyses also assessed the relationship changes in symptoms over time. © The Author(s), under exclusive licence to American College of Neuropsychopharmacology 2020 ACNP 59th Annual Meeting: Poster Session II 171 Keywords: Multimodal Neuroimaging, Trauma Exposure, MRI, configural group showed comparable responses (p > 0.25). DTI, Data Fusion Furthermore, responses across days in the elemental group revealed Disclosure: Nothing to disclose. that tone extinction diminished responses to the tone but not the square CS+ (Day x Cue: F1,141 = 4.59, p = 0.034). These findings fi indicate that extinction generalized between cues following T2. Elemental and Con gural Threat Learning Bias Extinction configural but not elemental threat learning. Generalization Next, we examined whether extinction would generalize from component cues to the full compound. After extinction of the Elizabeth Goldfarb*, Tahj Blow, Joseph Dunsmoor, Elizabeth tone on Day 2, on Day 3 we extinguished both tone and square Phelps cues. We then tested responses to the tone+square compound in both groups. Examining all CS+ trials revealed substantial Yale Medical School, New Haven, Connecticut, United States differences in how threat learning influenced responses to the cues and the compound (Group x CS+: F2,187 = 8.08, p = 0.0004). Background: Aversive experiences are complex, containing many Unlike the elemental group, the configural group responded more cues that can be remembered in different ways. How these events strongly to the compound than either cue (both p < 0.012). The are remembered may have important consequences for later configural group continued to respond strongly to the compound threat and safety responses. For example, different cues can be CS+ than CS− throughout Day 3 (F1,420 = 41.37, p < 0.001), individually associated with an aversive outcome (elemental) or showing that compound threat responses were not extinguished. integrated into a holistic context (configural). A bias toward However, the elemental group did not significantly differentiate elemental rather than configural representations has been the compound CS+ and CS− (F1,429 = 2.03, p = 0.15; Group x proposed as an etiology for posttraumatic stress disorder (PTSD). Compound: F1,849 = 13.43, p = 0.0003). Thus, unlike extinction However, it remains unclear how these different representations generalization between cues, extinction of component cues influence later extinction of these threat memories. As extinction generalized to the compound following elemental but not is a crucial feature of exposure therapy for PTSD and other anxiety configural threat learning. disorders, understanding how different forms of threat learning Conclusions: These findings demonstrate that configural and modulate extinction has significant clinical implications. elemental learning for an aversive event had opposite effects on Research in rodents has shown that configural threat learning the success of later extinction generalization. Whereas learning a (e.g., tone + light = shock) facilitated extinction generalization – configural association enabled extinction of one component cue that is, learning the tone was safe (extinction) diminished to extend to the other component cue, extinguishing both responses to the light. However, elemental threat learning (tone = component cues separately
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