Self-deception: Distorted metacognitive process in ambiguous contexts.

As one of the commonly used folk psychological concepts, self-deception has been intensively discussed yet is short of solid ground from cognitive neuroscience. Self-deception is a biased cognitive process of information to obtain or maintain a false belief that could be both self-enhancing or self-diminishing. Study 1 (N = 152) captured self-deception by adopting a modified numerical discrimination task that provided cheating opportunities, quantifying errors in predicting future performance (via item-response theory model), and measuring the belief of how good they are at solving the task (i.e., self-efficacy belief). By examining whether self-efficacy belief is based upon actual ability (true belief) or prediction errors (false belief), Study 1 showed that self-deception occurred in the effortless (easier access to answer cues) rather than effortful (harder access to answer cues) cheating opportunity conditions, suggesting high ambiguity in attributions facilitates self-deception. Studies 2 and 3 probed the neural source of self-deception, linking self-deception with the metacognitive process. Both studies replicated behavioral results from Study 1. Study 2 (ERP study; N = 55) found that the amplitude of frontal slow wave significantly differed between participants with positive/self-enhancing and negative/self-diminishing self-deceiving tendencies in incorrect predictions while remaining similar in correct predictions. Study 3 (functional magnetic resonance imaging study; N = 33) identified self-deceiving associated activity in the anterior medial prefrontal cortex and showed that effortless cheating context increased cheating behaviors that further facilitated self-deception. Our findings suggest self-deception is a false belief associated with a distorted metacognitive mental process that requires ambiguity in attributions of behaviors.

Bootstrap-Based Between-Study Heterogeneity Tests in Meta-Analysis.

Meta-analysis combines pertinent information from existing studies to provide an overall estimate of population parameters/effect sizes, as well as to quantify and explain the differences between studies. However, testing between-study heterogeneity is one of the most challenging tasks in meta-analysis research. Existing methods for testing heterogeneity, such as the Q test and likelihood ratio (LR) test, have been criticized for their failure to control Type I error rate and/or failure to attain enough statistical power. Although better reference distribution approximations have been proposed in the literature, their application is limited. Additionally, when the interest is to test whether the size of the heterogeneity is larger than a specific level, existing methods are far from mature. To address these issues, we propose new heterogeneity tests. Specifically, we combine bootstrap methods with existing heterogeneity tests (i.e., the maximum LR test, the restricted maximum LR test, and the Q test) to overcome the reference distribution issue and denote them as B-ML-LRT, B-REML-LRT, and B-Q, respectively. Simulation studies were conducted to examine and compare the performance of the proposed methods with the regular LR test, the regular Q test, and the Kulinskaya's improved Q test in both random- and mixed-effects meta-analyses. Based on the results of Type I error rates and statistical power, B-REML-LRT is recommended. Additionally, the improved Q test is also recommended when it is applicable. An R package boot.heterogeneity is provided to facilitate the implementation of the proposed tests.

Predicting visual working memory with multimodal magnetic resonance imaging.

The indispensability of visual working memory (VWM) in human daily life suggests its importance in higher cognitive functions and neurological diseases. However, despite the extensive research efforts, most findings on the neural basis of VWM are limited to a unimodal context (either structure or function) and have low generalization. To address the above issues, this study proposed the usage of multimodal neuroimaging in combination with machine learning to reveal the neural mechanism of VWM across a large cohort (N = 547). Specifically, multimodal magnetic resonance imaging features extracted from voxel-wise amplitude of low-frequency fluctuations, gray matter volume, and fractional anisotropy were used to build an individual VWM capacity prediction model through a machine learning pipeline, including the steps of feature selection, relevance vector regression, cross-validation, and model fusion. The resulting model exhibited promising predictive performance on VWM (r = .402, p < .001), and identified features within the subcortical-cerebellum network, default mode network, motor network, corpus callosum, anterior corona radiata, and external capsule as significant predictors. The main results were then compared with those obtained on emotional regulation and fluid intelligence using the same pipeline, confirming the specificity of our findings. Moreover, the main results maintained well under different cross-validation regimes and preprocess strategies. These findings, while providing richer evidence for the importance of multimodality in understanding cognitive functions, offer a solid and general foundation for comprehensively understanding the VWM process from the top down.

Correcting for the multiplicative and additive effects of measurement unreliability in meta-analysis of correlations.

As a powerful tool for synthesizing information from multiple studies, meta-analysis has gained high popularity in many disciplines. Conclusions stemming from meta-analyses are often used to direct theory development, calibrate sample size planning, and guide critical decision-making and policymaking. However, meta-analyses can be conflicted, misleading, and irreproducible. One of the reasons for meta-analyses to be misleading is the improper handling of measurement unreliability. We show that even when there is no publication bias, the current meta-analysis procedures would frequently detect nonexistent effects, and provide severely biased estimates and intervals with coverage rates far below the intended level. In this study, an effective approach to correcting for unreliability is proposed and evaluated via simulation studies. Its sensitivity to the violation of the homogeneous reliability and residual correlation assumption is also tested. The proposed method is illustrated using a real meta-analysis on the relationship between extroversion and subjective well-being. Substantial differences in meta-analytic results are observed between the proposed method and existing methods. Further, although not specifically designed for aggregating effect sizes with various measures, the proposed method can be used to fulfill the purpose. The study ends with discussions on the limitations and guidelines for implementing the proposed approach. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The speed and temporal frequency of visual apparent motion modulate auditory duration perception.

In the present study, we investigated how the perception of auditory duration could be modulated by a task-irrelevant, concurrent visual apparent motion, induced by visual bars alternating between left and right sides. Moreover, we examined the influence of the speed and temporal frequency of visual apparent motion on the perception of auditory duration. In each trial, the standard visual stimuli (two vertical bars) were presented sequentially, except that visual apparent motion was included in the fourth stimulus. A tone was presented simultaneously with each visual stimulus, while the fourth tone was presented with varied duration. Participants judged whether the fourth tone lasted longer than the other four tones. In Experiment 1, the speed of visual apparent motion (Fast vs. Slow) was manipulated by changing the interval between two bars. The mean point of subjective equality (PSE) in the Slow apparent motion condition was larger than that in the Static condition. Moreover, participants tended to overestimate the duration only in the Static condition, i.e., time dilation effect, which disappeared under apparent motion conditions. In Experiment 2, in addition to speed, we controlled the temporal frequency of apparent motion by manipulating the number of bars, generating four conditions of visual apparent motion (Physical-fast, Perceived-fast, Perceived-slow, vs. Static). The mean PSE was significantly smaller in the Physical-fast condition than in the Static and Perceived-slow conditions. Moreover, we found a time compression effect in both the Perceived-slow and Static conditions but not in the Perceived-fast and Physical-fast conditions. These results suggest that the auditory duration could be modulated by the concurrent, contextual visual apparent motion, and both the speed and temporal frequency of the task-irrelevant visual apparent motion contribute to the bias in perceiving the auditory duration.

Assessing the Impact of Precision Parameter Prior in Bayesian Non-parametric Growth Curve Modeling.

Bayesian non-parametric (BNP) modeling has been developed and proven to be a powerful tool to analyze messy data with complex structures. Despite the increasing popularity of BNP modeling, it also faces challenges. One challenge is the estimation of the precision parameter in the Dirichlet process mixtures. In this study, we focus on a BNP growth curve model and investigate how non-informative prior, weakly informative prior, accurate informative prior, and inaccurate informative prior affect the model convergence, parameter estimation, and computation time. A simulation study has been conducted. We conclude that the non-informative prior for the precision parameter is less preferred because it yields a much lower convergence rate, and growth curve parameter estimates are not sensitive to informative priors.

Charity Misconduct on Public Health Issues Impairs Willingness to Offer Help.

Charity organizations positively impact our societies but charity misconduct impairs people's willingness to contribute to charity and functional health systems on public health issues. This study investigates the impact of charity misconduct on people's willingness to offer help on public health issues and possible ways of reducing the negative impact brought by charity misconduct news through four studies (Ntotal = 1269). Results showed that charity misconduct on public health issues significantly reduced individuals' willingness to offer help via both the charity involved with the misconduct and any charity they prefer (Study 1 and 2). Furthermore, news on charity misconduct reduced people's general willingness to help in contexts that did not involve charity (Study 3). Finally, presenting charity nonmisconduct news after charity misconduct news increases individuals' willingness to offer help via the nonmisconduct charity (Study 4), suggesting a potential way to nudge people to provide help in the fight against the negative impact brought by charity misconduct news. The findings show the backfire of reporting charity misconduct news and have important implications for potential ways to facilitate people to offer help.

Cognitive Enhancement of Repetitive Transcranial Magnetic Stimulation in Patients With Mild Cognitive Impairment and Early Alzheimer's Disease: A Systematic Review and Meta-Analysis.

Repetitive transcranial magnetic stimulation (rTMS), a non-invasive brain stimulation technique, has been considered as a potentially effective treatment for the cognitive impairment in patients with mild cognitive impairment (MCI) and Alzheimer's Disease (AD). However, the effectiveness of this therapy is still under debate due to the variety of rTMS parameters and individual differences including distinctive stages of AD in the previous studies. The current meta-analysis is aiming to assess the cognitive enhancement of rTMS treatment on patients of MCI and early AD. Three datasets (PubMed, Web of Science and CKNI) were searched with relative terms and finally twelve studies with 438 participants (231 in the rTMS group and 207 in the control group) in thirteen randomized, double-blind and controlled trials were included. Random effects analysis revealed that rTMS stimulation significantly introduced cognitive benefits in patients of MCI and early AD compared with the control group (mean effect size, 1.17; 95% CI, 0.76 - 1.57). Most settings of rTMS parameters (frequency, session number, stimulation site number) significantly enhanced global cognitive function, and the results revealed that protocols with 10 Hz repetition frequency and DLPFC as the stimulation site for 20 sessions can already be able to produce cognitive improvement. The cognitive enhancement of rTMS could last for one month after the end of treatment and patients with MCI were likely to benefit more from the rTMS stimulation. Our meta-analysis added important evidence to the cognitive enhancement of rTMS in patients with MCI and early AD and discussed potential underlying mechanisms about the effect induced by rTMS.

Dispositional mindfulness and mental health in Chinese emerging adults: A multilevel model with emotion dysregulation as a mediator.

Using a multilevel model, this study examined emotion dysregulation as a mediator between dispositional mindfulness and mental health among Chinese emerging adults. Participants were 191 Chinese emerging adults (female = 172) between 18 and 27 years old (M = 21.06 years, SD = 2.01 years), who completed a questionnaire that assessed their dispositional mindfulness, emotion dysregulation, and mental health outcomes for three times over 12 months, with a three-month lag between each time point. Within-person analysis revealed that emotion dysregulation mediated between dispositional mindfulness and mental health outcomes, including subjective well-being and symptoms of depression and anxiety. Time was positively associated with emotion dysregulation and negatively associated with symptoms of depression and anxiety. Between-person analysis revealed that emotion dysregulation negatively mediated between dispositional mindfulness and symptoms of depression and anxiety, but not subjective well-being. These findings call attention to within-person versus between-person effects of emotion dysregulation as a mediator between dispositional mindfulness and psychological outcomes, particularly of symptoms of depression and anxiety. Attesting to the relations established in western societies, the relations are also applicable to emerging adults in the Chinese context. Evidence was thus advanced to inform translational research efforts that promote mindfulness and emotion regulation as assets of mental health.

Impaired early visual categorization of fear in social anxiety.

Social anxiety is associated with biased social perception, especially of ambiguous cues. While aberrations in high-level processes (e.g., cognitive appraisal and interpretation) have been implicated in such biases, contributions of early, low-level stimulus processing remain unclear. Categorical perception represents an efficient process to resolve signal ambiguity, and categorical emotion perception can swiftly classify sensory input, "tagging" biologically important stimuli at early stages of processing to facilitate ecological response. However, early threat categorization could be disrupted by exaggerated (or disinhibited) threat processing in anxiety, resulting in biased perception of ambiguous signals. We tested this hypothesis among individuals with low and high trait social anxiety (LSA/HSA; defined relative to the current sample), who performed a two-alternative forced-choice (fear or neutral) task on facial expressions parametrically varied along a neutral-fear continuum. The groups diverged in the reaction time (RT) profile along the neutral-fear continuum, which was characteristic of categorical perception in the LSA (vs. HSA) group with drastically increased RT from neutral to intermediate (boundary) fear intensities, contrasting monotonic, nonsignificant RT changes in the HSA group. Neurometric analysis along the continuum identified an early neutral-fear categorization operation (arising in the P1, an early visual ERP at 100 ms), which was nonetheless impaired in the HSA group (due to disinhibited response at the neutral-fear boundary). Absent group differences in higher-level cognitive operations (identified by later ERPs), current findings highlight a dispositional cognitive vulnerability in early visual categorization of social threat, which could precipitate further cognitive aberrations and, eventually, the onset of social anxiety disorder.

Residential Mobility Decreases Neural Responses to Social Norm Violation.

Social norms are essential, but they vary across cultures and societies. With the internationalization of human society, population mobility has greatly increased, especially in developing countries, which can have an impact on people's psychological states and behaviors and result in sociocultural change. The current research used three studies to examine the hypothesis that residential mobility plays a crucial role in the perception of social norm violations. Study 1 used an association test and found that residential mobility was correlated with the perception of both weak and strong social norm violations in females. Study 2 combined electroencephalography and found a negative differential N400 between weak social norm violations and appropriate behavior between residentially mobile and stable mindsets, suggesting that residential mobility modulates individuals' detection of social norm-violating behavior. Study 3 revealed that residential mobility does not have a similar effect on semantic violations, which indicates that the effect of residential mobility does not occur in non-social norm violations. Our findings provide insight into how and why individuals' detection of social norm-violating behaviors varies according to the dynamic development of society. As residential mobility continues to increase worldwide, especially in developing countries, more attention should be paid to the concomitant impact during the course of sociocultural change to build a better strategy for cultural specific social governance.

Testing autocorrelation and partial autocorrelation: Asymptotic methods versus resampling techniques.

Autocorrelation and partial autocorrelation, which provide a mathematical tool to understand repeating patterns in time series data, are often used to facilitate the identification of model orders of time series models (e.g., moving average and autoregressive models). Asymptotic methods for testing autocorrelation and partial autocorrelation such as the 1/T approximation method and the Bartlett's formula method may fail in finite samples and are vulnerable to non-normality. Resampling techniques such as the moving block bootstrap and the surrogate data method are competitive alternatives. In this study, we use a Monte Carlo simulation study and a real data example to compare asymptotic methods with the aforementioned resampling techniques. For each resampling technique, we consider both the percentile method and the bias-corrected and accelerated method for interval construction. Simulation results show that the surrogate data method with percentile intervals yields better performance than the other methods. An R package pautocorr is used to carry out tests evaluated in this study.

Decomposing fear perception: A combination of psychophysics and neurometric modeling of fear perception.

Emotion perception is known to involve multiple operations and waves of analysis, but specific nature of these processes remains poorly understood. Combining psychophysical testing and neurometric analysis of event-related potentials (ERPs) in a fear detection task with parametrically varied fear intensities (N=45), we sought to elucidate key processes in fear perception. Building on psychophysics marking fear perception thresholds, our neurometric model fitting identified several putative operations and stages: four key processes arose in sequence following face presentation - fear-neutral categorization (P1 at 100ms), fear detection (P300 at 320ms), valuation (early subcomponent of the late positive potential/LPP at 400-500ms) and conscious awareness (late subcomponent LPP at 500-600ms). Furthermore, within-subject brain-behavior association suggests that initial emotion categorization was mandatory and detached from behavior whereas valuation and conscious awareness directly impacted behavioral outcome (explaining 17% and 31% of the total variance, respectively). The current study thus reveals the chronometry of fear perception, ascribing psychological meaning to distinct underlying processes. The combination of early categorization and late valuation of fear reconciles conflicting (categorical versus dimensional) emotion accounts, lending support to a hybrid model. Importantly, future research could specifically interrogate these psychological processes in various behaviors and psychopathologies (e.g., anxiety and depression).