Observing the suppression of individual aversive memories from conscious awareness.

When reminded of an unpleasant experience, people often try to exclude the unwanted memory from awareness, a process known as retrieval suppression. Here we used multivariate decoding (MVPA) and representational similarity analyses on EEG data to track how suppression unfolds in time and to reveal its impact on item-specific cortical patterns. We presented reminders to aversive scenes and asked people to either suppress or to retrieve the scene. During suppression, mid-frontal theta power within the first 500 ms distinguished suppression from passive viewing of the reminder, indicating that suppression rapidly recruited control. During retrieval, we could discern EEG cortical patterns relating to individual memories-initially, based on theta-driven visual perception of the reminders (0 to 500 ms) and later, based on alpha-driven reinstatement of the aversive scene (500 to 3000 ms). Critically, suppressing retrieval weakened (during 360 to 600 ms) and eventually abolished item-specific cortical patterns, a robust effect that persisted until the reminder disappeared (780 to 3000 ms). Representational similarity analyses provided converging evidence that retrieval suppression weakened the representation of target scenes during the 500 to 3000 ms reinstatement window. Together, rapid top-down control during retrieval suppression abolished cortical patterns of individual memories, and precipitated later forgetting. These findings reveal a precise chronometry on the voluntary suppression of individual memories.

Altered brain activity related to inhibitory processing in youth with insomnia.

Insomnia has been shown to negatively affect one's cognitive functioning. While there has been some evidence suggesting sleep disruption in relation to impaired inhibitory control, a major component of executive function, little is known about the underlying neural processing in insomnia. The current study aimed to examine the differences in the behavioral responses and electroencephalography (EEG) correlates of inhibitory control between youths with insomnia and healthy sleepers. Twenty-eight participants with insomnia disorder and 31 healthy sleeper controls aged between 15 and 25 completed the study. Electroencephalographic activity was recorded during the Cued Go/NoGo (CGNG) task, a task assessing inhibitory control. Although insomnia group exhibited comparable behavioral performance to the healthy sleeper group, they showed impaired attention preparation, as displayed by a smaller contingent negative variation (CNV) component (F = 4.10, p = 0.048) after cue onset; and demonstrated impaired inhibitory control, as evidenced by smaller N2 and theta power on 200-350 ms (MANCOVA multivariate Group effect, F = 5.85, p < 0.001). The results suggested that youths with insomnia demonstrated altered brain activity during inhibitory control, despite their comparable behavioral performance. Given that impaired inhibitory control is often implicated in psychopathology, future studies with a longitudinal design are needed to further explore the long-term impacts and trajectory of altered inhibitory control in youths with insomnia.

Discovering Metamorphic Relations for Scientific Software From User Forums.

Scientific software can be used for decades and is constantly evolving. Recently, metamorphic testing, a property-based testing technique, has shown to be effective in testing scientific software, and the necessary properties are expressed as metamorphic relations. However, the development of metamorphic relations is difficult: it requires considerable practical expertise for the software tester. In this article, we report our experience of uncovering metamorphic relations from a user forum's questions of the United States Environmental Protection Agency's Storm Water Management Model (SWMM). Our study not only illustrates a wealth of end users' expertise in interpreting software results, but also demonstrates the usefulness of classifying the user-oriented metamorphic relations into a nominal, ordinal, and functional hierarchy mainly from the software output perspective.

Scientific Software Testing Goes Serverless: Creating and Invoking Metamorphic Functions.

Our function-as-a-service (FaaS) framework transformed end users' questions into automated tests for scientific software. Our case study illustrates the FaaSification of scientific software testing and the importance of value-driven evaluations by focusing on real-world defect detection.

Exploratory Metamorphic Testing for Scientific Software.

Scientific model developers are able to verify and validate their software via metamorphic testing, even when the expected output of a given test case is not readily available. The tenet is to check whether certain relations hold among the expected outputs of multiple related inputs. Contemporary approaches require the relations to be defined before tests. Our experience shows that it is often straightforward to first define the multiple iterations of tests for performing continuous simulations, and then keep multiple and even competing metamorphic relations open for investigating the testing-result patterns. We call this new approach exploratory metamorphic testing, and report our experience of applying it to detect bugs, mismatches, and constraints in automatically calibrating parameters for the United States Environmental Protection Agency's Storm Water Management Model (SWMM).

Reactivating cue approached positive personality traits during sleep promotes positive self-referential processing.

People preferentially endorse positive personality traits as more self-descriptive than negative ones, a positivity self-referential bias. Here, we investigated how to enhance positive self-referential processing, integrating wakeful cue-approach training task (CAT) and sleep-based targeted memory reactivation (TMR). In the CAT, participants gave speeded motor responses to cued positive personality traits. In a subsequent nap, we unobtrusively re-played half of the trained positive traits during slow-wave sleep (TMR). Upon awakening, CAT+TMR facilitated participants' speed in endorsing positive traits in immediate tests, and rendered participants endorse more positive traits as self-descriptive after one week. Notably, these enhancements were associated with the directionality of cue-related 1-4 Hz slow traveling waves (STW) that propagate across brain regions. Specifically, anterior-to-posterior backward STW was positively associated with these benefits, whereas forward STW showed negative associations. These findings demonstrate the potential benefits of integrated wakeful cue-approach training and sleep-based memory reactivation in strengthening positive self-referential processing.

Organic electrochemical transistors as on-site signal amplifiers for electrochemical aptamer-based sensing.

Electrochemical aptamer-based sensors are typically deployed as individual, passive, surface-functionalized electrodes, but they exhibit limited sensitivity especially when the area of the electrode is reduced for miniaturization purposes. We demonstrate that organic electrochemical transistors (electrolyte gated transistors with volumetric gating) can serve as on-site amplifiers to improve the sensitivity of electrochemical aptamer-based sensors. By monolithically integrating an Au working/sensing electrode, on-chip Ag/AgCl reference electrode, and Poly(3,4-ethylenedioxythiophene)-poly(styrenesulfonate) counter electrode - also serving as the channel of an organic electrochemical transistor- we can simultaneously perform testing of organic electrochemical transistors and traditional electroanalytical measurement on electrochemical aptamer-based sensors including cyclic voltammetry and square-wave voltammetry. This device can directly amplify the current from the electrochemical aptamer-based sensor via the in-plane current modulation in the counter electrode/transistor channel. The integrated sensor can sense transforming growth factor beta 1 with 3 to 4 orders of magnitude enhancement in sensitivity compared to that in an electrochemical aptamer-based sensor (292 µA/dec vs. 85 nA/dec). This approach is believed to be universal, and can be applied to a wide range of tethered electrochemical reporter-based sensors to enhance sensitivity, aiding in sensor miniaturization and easing the burden on backend signal processing.

Prosocial behavior promotes positive emotion during the COVID-19 pandemic.

The COVID-19 pandemic has raised concerns about humans' physical and mental well-being. In response, there has been an urgent "call to action" for psychological interventions that enhance positive emotion and psychological resilience. Prosocial behavior has been shown to effectively promote well-being, but is this strategy effective during a pandemic when ongoing apprehension for personal safety could acutely heighten self-focused concern? In two online preregistered experiments (N = 1,623) conducted during the early stage of pandemic (April 2020), we examined this question by randomly assigning participants to engage in other- or self-beneficial action. For the first time, we manipulated whether prosocial behavior was related to the source of stress (coronavirus disease 2019 [COVID-19]): Participants purchased COVID-19-related (personal protective equipment, PPE) or COVID-19-unrelated items (food/writing supplies) for themselves or someone else. Consistent with preregistered hypotheses, prosocial (vs. non-pro-social or proself) behavior led to higher levels of self-reported positive affect, empathy, and social connectedness. Notably, we also found that psychological benefits were larger when generous acts were unrelated to COVID-19 (vs. related to COVID-19). When prosocial and proself spending involved identical COVID-19 PPEs items, prosocial behavior's benefits were detectable only on empathy and social connectedness, but not on posttask positive affect. These findings suggest that while there are boundary conditions to be considered, generous action offers one strategy to bolster well-being during the pandemic. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Neural response to rewards in youths with insomnia.

STUDY OBJECTIVES: Insomnia and depression are common comorbid conditions in youths. Emerging evidence suggests that disrupted reward processing may be implicated in the association between insomnia and the increased risk for depression. Reduced reward positivity (RewP) as measured by event-related potential (ERP) has been linked to depression, but has not been tested in youths with insomnia. METHODS: Twenty-eight participants with insomnia disorder and without any comorbid psychiatric disorders and 29 healthy sleepers aged between 15-24 completed a monetary reward task, the Cued Door task, while electroencephalographic activity was recorded. RewP (reward minus non-reward difference waves) was calculated as the mean amplitudes within 200-300 ms time window at FCz. Two analyses of covariance (ANCOVAs) were conducted with age as a covariate on RewP amplitude and latency, respectively. RESULTS: Participants with insomnia had a significantly lower RewP amplitude regardless of cue types (Gain, Control, and Loss) than healthy sleepers, F(1, 51) = 4.95, p = 0.031, indicating blunted reward processing. On the behavioral level, healthy sleepers were more prudential (slower reaction time) in decision making towards Loss/Gain cues than their insomnia counterparts. Trial-by-trial behavioral adjustment analyses showed that, compared with healthy sleepers, participants with insomnia were less likely to dynamically change their choices in response to Loss cues. CONCLUSIONS: Dysfunctional reward processing, coupled with inflexibility of behavioral adjustment in decision-making, is associated with insomnia disorder among youth, independent of mood disorders. Future studies with long-term follow-up are needed to further delineate the developmental trajectory of insomnia-related reward dysfunctions in youth.

Optimistic amnesia: how online and offline processing shape belief updating and memory biases in immediate and long-term optimism biases.

When people are confronted with feedback that counters their prior beliefs, they preferentially rely on desirable rather than undesirable feedback in belief updating, i.e. an optimism bias. In two pre-registered EEG studies employing an adverse life event probability estimation task, we investigated the neurocognitive processes that support the formation and the change of optimism biases in immediate and 24 h delayed tests. We found that optimistic belief updating biases not only emerged immediately but also became significantly larger after 24 h, suggesting an active role of valence-dependent offline consolidation processes in the change of optimism biases. Participants also showed optimistic memory biases: they were less accurate in remembering undesirable than desirable feedback probabilities, with inferior memories of undesirable feedback associated with lower belief updating in the delayed test. Examining event-related brain potentials (ERPs) revealed that desirability of feedback biased initial encoding: desirable feedback elicited larger P300s than undesirable feedback, with larger P300 amplitudes predicting both higher belief updating and memory accuracies. These results suggest that desirability of feedback could bias both online and offline memory-related processes such as encoding and consolidation, with both processes contributing to the formation and change of optimism biases.

Sleep's short-term memory preservation and long-term affect depotentiation effect in emotional memory consolidation: behavioral and EEG evidence.

STUDY OBJECTIVES: Sleep plays a pivotal role in the off-line processing of emotional memory. However, much remains unknown for its immediate vs. long-term influences. We employed behavioral and electrophysiological measures to investigate the short- and long-term impacts of sleep vs. sleep deprivation on emotional memory. METHODS: Fifty-nine participants incidentally learned 60 negative and 60 neutral pictures in the evening and were randomly assigned to either sleep or sleep deprivation conditions. We measured memory recognition and subjective affective ratings in 12- and 60-h post-encoding tests, with EEGs in the delayed test. RESULTS: In a 12-h post-encoding test, compared to sleep deprivation, sleep equally preserved both negative and neutral memory, and their affective tones. In the 60-h post-encoding test, negative and neutral memories declined significantly in the sleep group, with attenuated emotional responses to negative memories over time. Furthermore, two groups showed spatial-temporally distinguishable ERPs at the delayed test: while both groups showed the old-new frontal negativity (300-500 ms, FN400), sleep-deprived participants additionally showed an old-new parietal, Late Positive Component effect (600-1000 ms, LPC). Multivariate whole-brain ERPs analyses further suggested that sleep prioritized neural representation of emotion over memory processing, while they were less distinguishable in the sleep deprivation group. CONCLUSIONS: These data suggested that sleep's impact on emotional memory and affective responses is time-dependent: sleep preserved memories and affective tones in the short term, while ameliorating affective tones in the long term. Univariate and multivariate EEG analyses revealed different neurocognitive processing of remote, emotional memories between sleep and sleep deprivation groups.

Unit and regression tests of scientific software: A study on SWMM.

Testing helps assure software quality by executing a program and uncovering bugs. Scientific software developers often find it challenging to carry out systematic and automated testing due to reasons like inherent model uncertainties and complex floating-point computations. Extending the recent work on analyzing the unit tests written by the developers of the Storm Water Management Model (SWMM) [32], we report in this paper the investigation of both unit and regression tests of SWMM. The results show that the 2953 unit tests of SWMM have a 39.7% statement-level code coverage and a 82.4% user manual coverage. Meanwhile, an examination of 58 regression tests of SWMM shows a 44.9% statement-level code coverage and a near 100% user manual coverage. We also observe a "getter-setter-getter" testing pattern from the SWMM unit tests, and suggest a diversified way of executing regression tests.