Abstract Fear overgeneralization is a potential pathogenic mechanism of anxiety-related disorders. A dominant model posits that overgeneralization occurs when the hippocampus fails to distinctly encode benign stimuli with insufficient similarity to previously encountered fear cues, triggering excessive retrieval of stored fear representations. This model has cross-species support but has not been causally tested in humans. A developing literature demonstrates that hippocampal network targeted transcranial magnetic stimulation (HNT-TMS) can strengthen hippocampal-dependent memory encoding. Building on this literature, we hypothesized that HNT-TMS would strengthen encoding of perceptually similar stimuli and thereby reduce retrieval errors (i.e., sharpen discrimination) in participants with post-traumatic stress symptoms. We predicted that this effect would emerge for fear stimuli as measured by the Farmer Task and neutral stimuli as measured by the Mnemonic Similarity Task. Continuous theta-burst stimulation (cTBS) was delivered to individualized left posterior-parietal targets derived via precision functional mapping, seed-based connectivity, and electric-field modeling methods. A vertex control target was also stimulated in a within-subject design (final N = 25). Multilevel models did not reveal significant interactions between stimulation target and fear or neutral stimulus discrimination. However, HNT-TMS strengthened fear discrimination in participants with lower sensitization, indexed by responsivity to a control stimulus perceptually unrelated to the CS+. Sensitization reflects indiscriminate fear responding unrelated to CS + similarity and is not expected to engage the hippocampal CS + matching function. Our findings therefore indicate that HNT-TMS may selectively sharpen fear discrimination when the hippocampal CS + matching function is more strongly engaged.

Heightened generalization of conditioned fear and avoidance to safe stimuli resembling threat is a key feature of pathological anxiety and might contribute to the increased prevalence of anxiety-related disorders among women. Though animal studies have documented over-generalized fear in female versus male rodents, analogous work in humans is sparse, and no studies to date have examined gender differences in generalized avoidance. We addressed this gap by testing 170 self-identified women (n = 85) and men (n = 85) using a video game-based task assessing generalized Pavlovian fear (perceived threat, fear-potentiated startle) and generalized instrumental avoidance. Instrumental measures of generalization reflected maladaptive avoidance by virtue of being unnecessary to secure safety and incurring a cost of losing the game in which the task is embedded. Women displayed increases in both Pavlovian generalization of perceived threat and maladaptive generalized avoidance. Additionally, decreased motivation to win the game among women mediated the effect of gender on generalized avoidance, and generalized perceived risk and tendencies toward experiential avoidance positively predicted generalized avoidance in women but not men. Overall, findings implicate the undue spread of fear and avoidance to safe stimuli resembling danger among women as a candidate mechanism for differential rates of clinical anxiety across the genders.

Although symptoms of obsessive compulsive disorder (OCD) may vary markedly, they often involve a fear of consequences that are both catastrophic and highly improbable (e.g., contracting HIV from a doorknob). Accordingly, a heightened sensitivity to what we refer to as improbable catastrophes may represent an underlying feature of OCD, yet this possibility awaits experimental validation. To fill this gap, 78 undergraduates with wide-ranging levels of OCD symptom severity completed a fear-conditioning paradigm designed to elicit varying degrees of perceived threat probability/aversiveness to test whether OCD symptoms predict heightened reactivity to unlikely, high-aversion threats. Consistent with predictions, participants with higher OCD symptoms were more avoidant of low-probability, high-aversion threats and also exhibited greater threat expectancy and physiological reactivity to more improbable threats in general. These findings implicate excessive avoidance of improbable catastrophes and heightened reactivity to unlikely threats more generally as underlying features of OCD.

Intolerance of uncertainty (IU) has been conceptualized as a transdiagnostic vulnerability for emotional psychopathology, but few studies have tested whether it prospectively predicts emotional psychopathology, and none have utilized transdiagnostic and clinician-rated outcomes. To fill this gap, the present study tested whether IU prospectively predicted the clinician-rated severity of transdiagnostic emotional psychopathology six months later in a treatment-seeking Veteran sample. Participants completed the Intolerance of Uncertainty 12-item scale (IUS-12) and the Structured Clinical Interview for the DSM-5 (SCID-5) at Time 1 and again six-months later (Time 2); assessed emotional disorders included both anxiety-related disorders (i.e., post-traumatic stress disorder, generalized anxiety disorder, panic disorder, social anxiety disorder, obsessive compulsive disorder, specific phobia) and depressive conditions (i.e., major depressive disorder and persistent depressive disorder). Linear regression analyses revealed a bidirectional prospective relation between IU and emotional psychopathology, wherein higher Time 1 IUS-12 predicted greater Time 2 emotional disorder severity and greater Time 1 emotional disorder severity predicted higher Time 2 IUS-12. Follow-up analyses revealed that IU prospectively predicted the maintenance (but not the development) of anxiety-related issues, whereas prediction of Time 2 depression was nullified when controlling for Time 1 anxiety pathology. These findings implicate IU as a transdiagnostic vulnerability for emotional psychopathology and suggest the construct can be particularly useful as a treatment target and prognostic indicator for anxiety-related conditions.

Lab-based fear-conditioning studies have repeatedly implicated exaggerated threat reactivity to benign (unreinforced) stimuli as concurrent markers of clinical anxiety, but little work has examined the strength of false alarms as a longitudinal predictor of anxiety problems. As such, we tested whether heightened false alarms of conditioned threat assessed in participants' first semester of college predicted second-semester symptoms of generalized anxiety disorder (GAD) and social anxiety disorder (SAD) - two anxiety conditions that are common in college students, have been associated with excessive false alarms, and have yet to be assessed with longitudinal conditioning designs. Here, we focused on the predictive effects of behavioral threat responses (threat expectancy, subjective anxiety, avoidance) given their greater potential for translation to the clinic. Results implicate conditioning-related increases in anxiety to safe stimuli resembling the danger-cue as prospective predictors of GAD. In contrast, SAD was predicted by non-specific elevations in anxiety to a broad set of safe stimuli, as well as by increased threat expectancy toward cues least resembling the conditioned danger cue. These findings suggest that risk for GAD and SAD are captured by distinct, behavioral indicators of false-alarms that may be more feasibly collected in clinical settings compared to alternative experimental anxiety measures like psychophysiological responses.

Background and Objectives Fear conditioning represents the prevailing model by which organisms acquire novel threat contingencies. However, little work has been devoted to linking laboratory measures of fear conditioning to the development of real-world threat responses. To fill this gap, the present study explored whether individual differences in a laboratory-based fear conditioning measure could predict levels of COVID-19-related anxiety and avoidance assessed during the first month of the pandemic.Design and Method Forty-eight undergraduate students who had previously participated in two fear conditioning experiments prior to COVID-19 completed a survey assessing COVID-19 anxiety and avoidance. The fear conditioning experiment involved learning to discriminate between a shape contingently associated with mild electric shock (CS+) and two other shapes that were not (CS-).Results Increased subjective anxiety to our laboratory CS+ prior to the pandemic predicted heightened COVID-19 anxiety. Follow-up analyses revealed that participants with high COVID-19 anxiety exhibited increased anxiety to CS+ during the final experimental block relative to participants with low COVID-19 anxiety.Conclusions Findings from this exploratory study tentatively implicate fear conditioning in the development of real-world fear responses and underscore the importance of investigating laboratory fear conditioning as a predictor of anxiety responses to real-world threats.

Background: Recent evidence implicates intensive panic control treatment (IPCT) - a full panic control treatment protocol compressed into a single weekend - as a viable alternative for Veterans with panic disorder who are unable or unwilling to commit to standard weekly cognitive behavioral therapy (CBT). However, no studies to date have examined pretreatment predictors of response to IPCT. Knowledge of such predictors may be important for understanding which Veterans are best suited for IPCT relative to standard CBT. Methods: Participants were military Veterans with a primary diagnosis of panic disorder (N = 26) who participated in three open trials of IPCT. Pretreatment predictors were tested within linear regression models used to predict panic disorder severity at 2-week and 6-month follow-up assessments. Pretreatment predictors included: Panic disorder severity, agoraphobic avoidance, PTSD symptoms, anxiety sensitivity, and age. Results: Pretreatment symptoms of PTSD predicted reduced treatment response at 2-week but not 6-month follow-up, whereas pretreatment anxiety sensitivity predicted reduced response at 6-month but not 2-week follow-up. Limitations: Current findings are tempered by the exploratory nature of the analyses and a small sample. Conclusions: Our study offers tentative evidence that success in IPCT may be linked to a distinct pretreatment profile relative to that of standard weekly therapy. These preliminary findings should be confirmed in larger studies that directly compare pretreatment predictors of intensive versus standard weekly CBT for panic disorder.

Beginning in 2015, the United States Environmental Protection Agency’s (EPA’s) National Estuary Program (NEP) started a collaboration with partners in seven estuaries along the East Coast (Barnegat Bay; Casco Bay), West Coast (Santa Monica Bay; San Francisco Bay; Tillamook Bay), and the Gulf of Mexico (GOM) Coast (Tampa Bay; Mission-Aransas Estuary) of the United States to expand the use of autonomous monitoring of partial pressure of carbon dioxide (pCO2) and pH. Analysis of high-frequency (hourly to sub-hourly) coastal acidification data including pCO2, pH, temperature, salinity, and dissolved oxygen (DO) indicate that the sensors effectively captured key parameter measurements under challenging environmental conditions, allowing for an initial characterization of daily to seasonal trends in carbonate chemistry across a range of estuarine settings. Multi-year monitoring showed that across all water bodies temperature and pCO2 covaried, suggesting that pCO2 variability was governed, in part, by seasonal temperature changes with average pCO2 being lower in cooler, winter months and higher in warmer, summer months. Furthermore, the timing of seasonal shifts towards increasing (or decreasing) pCO2 varied by location and appears to be related to regional climate conditions. Specifically, pCO2 increases began earlier in the year in warmer water, lower latitude water bodies in the GOM (Tampa Bay; Mission-Aransas Estuary) as compared with cooler water, higher latitude water bodies in the northeast (Barnegat Bay; Casco Bay), and upwelling-influenced West Coast water bodies (Tillamook Bay; Santa Monica Bay; San Francisco Bay). Results suggest that both thermal and non-thermal influences are important drivers of pCO2 in Tampa Bay and Mission-Aransas Estuary. Conversely, non-thermal processes, most notably the biogeochemical structure of coastal upwelling, appear to be largely responsible for the observed pCO2 values in West Coast water bodies. The co-occurrence of high salinity, high pCO2, low DO, and low temperature water in Santa Monica Bay and San Francisco Bay characterize the coastal upwelling paradigm that is also evident in Tillamook Bay when upwelling dominates freshwater runoff and local processes. These data demonstrate that high-quality carbonate chemistry observations can be recorded from estuarine environments using autonomous sensors originally designed for open-ocean settings.

Though overgeneralization of Pavlovian fear to safe stimuli resembling conditioned danger-cues is a known feature of clinical anxiety, its role in maladaptive avoidance has been understudied. The current work investigates neural substrates of Pavlovian generalization as predictors of maladaptive, generalized avoidance decisions as well as diagnostic and personality variables that moderate this relationship.

Dimensional models of obsessive-compulsive (OC) symptoms, as seen in obsessive-compulsive disorder (OCD), are instrumental in explaining the heterogeneity observed in this condition and have received considerable empirical support. Normative models of personality partially align with OC symptoms; however, maladaptive personality models present a more compelling approach because of their direct relevance to pathological behavior. Prior efforts to map OC symptoms to maladaptive personality space, as operationalized by the DSM-5 Alternative Model of Personality Disorder (AMPD), find these symptoms cross-load under both Negative Affectivity and Psychoticism traits. However, tests of OC symptoms in conjunction with the full AMPD structure, and its 25 lower-level facets, are lacking. We applied joint exploratory factor analysis to an AMPD instrument, the Personality Inventory for DSM-5 (PID-5), and OC symptom data from two separate samples (total N=1506) to locate OC symptoms within AMPD space. As expected, OC symptoms cross-loaded on Negative Affectivity, Psychoticism and on the low-end of Disinhibition. OC symptoms more strongly loaded on Psychoticism across samples, suggesting structural relations between OCD and psychotic experiences are stronger than DSM models imply. Facet loadings largely resembled the canonical PID-5 structure. A notable exception was that two Psychoticism facets (Perceptual Dysregulation and Unusual Beliefs/Experiences) more closely tracked OC symptom loadings. We also report exploratory analyses of OC symptom subscales (e.g., obsessing, ordering, checking) with PID-5 variables. Results are discussed in the context of the placement of OC symptoms/OCD in PID-5 space and within the Hierarchical Taxonomy of Psychopathology, an ongoing effort to improve psychopathology classification.

Ocean and coastal acidification (OCA) present a unique set of sustainability challenges at the human-ecological interface. Extensive biogeochemical monitoring that can assess local acidification conditions, distinguish multiple drivers of changing carbonate chemistry, and ultimately inform local and regional response strategies is necessary for successful adaptation to OCA. However, the sampling frequency and cost-prohibitive scientific equipment needed to monitor OCA are barriers to implementing the widespread monitoring of dynamic coastal conditions. Here, we demonstrate through a case study that existing community-based water monitoring initiatives can help address these challenges and contribute to OCA science. We document how iterative, sequential outreach, workshop-based training, and coordinated monitoring activities through the Northeast Coastal Acidification Network (a) assessed the capacity of northeastern United States community science programs and (b) engaged community science programs productively with OCA monitoring efforts. Our results (along with the companion manuscript) indicate that community science programs are capable of collecting robust scientific information pertinent to OCA and are positioned to monitor in locations that would critically expand the coverage of current OCA research. Furthermore, engaging community stakeholders in OCA science and outreach enabled a platform for dialogue about OCA among other interrelated environmental concerns and fostered a series of co-benefits relating to public participation in resource and risk management. Activities in support of community science monitoring have an impact not only by increasing local understanding of OCA but also by promoting public education and community participation in potential adaptation measures.

Clinical anxiety is characterized by unnecessary avoidance of false-alarms of threat. This abnormality often arises from undue generalized avoidance to safe stimuli resembling a conditioned danger-cue (CS+). The present fMRI work examines the extent to which behavioral approach tendencies may protect against maladaptive generalized avoidance and identifies associated neural processes.

Overgeneralization of conditioned fear to safe stimuli that resemble a previously-learned threat-cue is a well-studied correlate of clinical anxiety, yet whether conditioned disgust generalizes remains unknown, as does the extent to which such generalization is associated with disgust-related traits and maladaptive outcomes. The present study addresses this gap by adapting a validated fear-generalization paradigm to assess conditioned disgust and behavioral avoidance to a disgust-cue (CS+) paired with a disgusting video clip, and safe generalization stimuli parametrically varying in perceptual similarity to CS+. For comparison, levels of fear generalization were also assessed using the original fear-generalization paradigm. In both paradigms, costly and unnecessary avoidance to safe threat-cue approximations analogues maladaptive outcomes of generalization. In the disgust paradigm only, disgust-proneness was associated with elevated perceived risk to safe stimuli and increases in the extent to which such elevations were accompanied by maladaptive avoidance. Comparable levels of generalization, and positive associations between generalization and maladaptive avoidance, were found across disgust and fear paradigms. Results confirm that conditioned disgust is subject to generalization, implicate generalized disgust as a source of maladaptive avoidance particularly among those prone to disgust, and suggest a potential role for these processes in the etiology and maintenance of disgust-related disorders.

Generalization of Pavlovian fear to safe stimuli resembling conditioned-danger cues (CS+) is a widely accepted conditioning correlate of clinical anxiety. Though much of the pathogenic influence of such generalization may lie in the associated avoidance, few studies have assessed maladaptive avoidance decisions associated with Pavlovian generalization. Lab-based assessments of this process, here referred to as aversive Pavlovian-instrumental covariation during generalization (APIC-G), have recently begun. The current study represents a next step in this line of work by conducting the first examination of anxiety-related dimensions of personality that may exacerbate APIC-G. Specifically, we test anxiety sensitivity (AS) and intolerance of uncertainty (IU) as moderators of relations between Pavlovian generalization and maladaptive avoidance decisions in 102 undergraduate students with wide-ranging levels of IU and AS. Results indicate a facilitative effect of AS on this APIC-G process, with AS strengthening relations between Pavlovian generalization and maladaptive generalized avoidance whether operationalizing Pavlovian generalization with psychophysiological (fear-potentiated startle) or behavioral measures. Additionally, IU was found to facilitate APIC-G when indexing Pavlovian generalization with behavioral but not fear-potentiated startle measures. Moderating effects of AS were most pronounced for stimulus classes bearing the highest resemblance to CS+, whereas effects of IU were most pronounced for the stimulus class with the highest level of threat ambiguity. Results implicate AS and IU as risk factors for the maladaptive decisional correlates of Pavlovian generalization and suggest that established associations between these traits and clinical anxiety may derive, in part, from their enhancement of maladaptive APIC-G.

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the global carbon budget – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), EFF was 9.4 ± 0.5 GtC yr−1, ELUC 1.3 ± 0.7 GtC yr−1, GATM 4.7 ± 0.1 GtC yr−1, SOCEAN 2.4 ± 0.5 GtC yr−1, and SLAND 3.0 ± 0.8 GtC yr−1, with a budget imbalance BIM of 0.6 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1. Also for 2016, ELUC was 1.3 ± 0.7 GtC yr−1, GATM was 6.1 ± 0.2 GtC yr−1, SOCEAN was 2.6 ± 0.5 GtC yr−1, and SLAND was 2.7 ± 1.0 GtC yr−1, with a small BIM of −0.3 GtC. GATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the high fossil emissions and the small SLAND consistent with El Niño conditions. The global atmospheric CO2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6–9 months indicate a renewed growth in EFF of +2.0 % (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).

Efforts to estimate air-water carbon dioxide (CO2) exchange on regional or global scales are constrained by a lack of direct, continuous surface water CO2 observations. Sensor technology for the in situ measurement of the partial pressure of carbon dioxide (pCO(2)) has progressed, but still poses limitations including expense and bio-fouling concerns. We describe a simple, inexpensive, in situ pCO(2) method (SIPCO2) in which a non-dispersive infrared (NDIR) detector is paired with an air pump in an enclosed housing to produce air-sea equilibration. We first evaluated this approach in a laboratory setting, then in an estuarine-coastal ocean laboratory for several months to continuously monitor aquatic pCO(2). An accepted, accurate NDIR-based CO2 measurement technique was employed alongside SIPCO2 to provide an assessment of sensor performance. SIPCO2 allows for low-cost, relatively accurate measurements of pCO(2) (mean difference of 2565 latm from validation system after laboratory calibration) without reagents or membranes, and can be assembled and operated with a minimal amount of technical skill. While not suitable for some exacting applications, this SIPCO2 approach could rapidly and effectively increase the number of quality CO2 observations in a range of aquatic environments. We also provide detailed instructions for the assembly of SIPCO2 from commercially available components.