Mengfan Zhang

Anxiety disorders involve maladaptive responses to fear, yet the underlying mental representations remain poorly understood. Traditional approaches have typically relied on predetermined psychological dimensions, limiting the characterization of underlying representations. Focusing on arachnophobia as a model condition, we used a similarity-based approach to reveal mental representations of spider-related images. From 705 individuals, we analyzed 49,141 pairwise similarity judgments among 314 spider-related images, constituting the largest dataset of its kind. Multidimensional Scaling identified a 5-dimensional representational space, with four dimensions strongly predicting fear ratings, and capturing a substantial amount of variance relevant to spider-related fear. These findings indicate that fear-related representations are structured along specific dimensions with complex information that cannot be reduced to conventional predetermined dimensions, such as fear and disgust. Our approach provides a scalable and flexible framework for studying fear-related representations, offering potential applications for refining exposure therapy and anxiety treatment strategies.

Semantic priming has been studied for nearly 50 years across various experimental manipulations and theoretical frameworks. Although previous studies provide insight into the cognitive underpinnings of semantic representations, they have suffered from small sample sizes and a lack of linguistic and cultural diversity. In this Registered Report, we measured the size and the variability of the semantic priming effect across 19 languages (n = 25,163 participants analysed) by creating the largest available database of semantic priming values using an adaptive sampling procedure. We found evidence for semantic priming in terms of differences in response latencies between related word-pair conditions and unrelated word-pair conditions. Model comparisons showed that the inclusion of a random intercept for language improved model fit, providing support for variability in semantic priming across languages. This study highlights the robustness and variability of semantic priming across languages and provides a rich, linguistically diverse dataset for further analysis. The Stage 1 protocol for this Registered Report was accepted in principle on 15 July 2022. The protocol, as accepted by the journal, can be found at https://osf.io/u5bp6 (registration) or https://osf.io/q4fjy (preprint version 6, 31 May 2022).

Semantic priming has been studied for nearly 50 years across various experimental manipulations and theoretical frameworks. Although previous studies provide insight into the cognitive underpinnings of semantic representations, they have suffered from small sample sizes and a lack of linguistic and cultural diversity. In this Registered Report, we measured the size and the variability of the semantic priming effect across 19 languages (N = 25,163 participants analyzed) by creating the largest available database of semantic priming values based on an adaptive sampling procedure. We found evidence for semantic priming in terms of differences in response latencies between related word-pair conditions and unrelated word-pair conditions. Model comparisons showed that inclusion of a random intercept for language improved model fit, providing support for variability in semantic priming across languages. This study highlights the robustness and variability of semantic priming across languages and provides a rich, linguistically diverse dataset for further analysis.

Neuroimaging has greatly improved our understanding of phobic mechanisms. To expand on these advancements, we present data on the heterogeneity of neural patterns in spider phobia combined with various psychological dimensions of spider phobia, using spider-relevant stimuli of various intensities. Specifically, we have created a database in which 49 spider-fearful individuals viewed 225 spider-relevant images in the fMRI scanner and performed behavioral avoidance tasks before and after the fMRI scan. For each participant, the database consists of the neuroimaging part, which includes an anatomical scan, five passive-viewing, and two resting-state functional runs in both raw and pre-processed form along with associated quality control reports. Additionally, the behavioral section includes self-report questionnaires and avoidance tasks collected in pre- and post-sessions. The dataset is well suited for investigating neural mechanisms of phobias, brain-behavior correlations, and also contributes to the existing phobic neuroimaging datasets with spider-fearful samples.

Spider phobia is one of the most common specific phobias and can be highly detrimental to one’s quality of life. To evaluate the efficacy of treatments, reliable pre- and post-treatment assessments are needed. Behavioral avoidance tests (BATs), where one is asked to approach a spider, are commonly used as such measures. With the increasing popularity of computerized interventions, there is a demand for quick assessments for fear of spiders, that can be completed using computers or smartphones. Here, we tested the validity of a novel computerized BAT (cBAT) that we introduced in our previous work. In this cBAT, participants unblurred three images of spiders up until a point where they still felt comfortable viewing them. We expected that the cBAT would be moderately to strongly correlated with established measures for fear of spiders. Our analysis revealed that the cBAT showed moderate convergent and concurrent validity through correlations with self-report questionnaires indicating spider fear, and with a real-life BAT, respectively. However, the latter was no longer observed in a follow-up. While the cBAT facilitates ease of application and has a quick, straightforward participant task, we conclude that the cBAT is a limited measure for fear of spiders and might not fully capture the complexity of spider-related avoidance behavior compared to tasks that simulate real-life scenarios more closely. We propose the development of a refined cBAT that maintains an easily applicable participant task.

Spiders are among the most diverse and evolutionarily successful taxa in the animal kingdom. Nevertheless, their popularity with humans is low, and arachnophobia, which is characterized by an intense and irrational fear of spiders, is one of the most common specific phobias. While it is clear that spiders generally evoke aversive responses in humans, it is a highly understudied question which visual attributes of spiders trigger these emotions. Here, we categorized a set of 313 images showing spiders and spider-related content according to a variety of visual attributes, and performed a machine learning analysis to investigate which attributes were associated with the mean fear, disgust, and approach-avoidance ratings of 152 spider-fearful adults. Predictive models were able to account for approximately 70%, 67%, and 60% of the variance in mean fear, disgust, and approach-avoidance ratings, respectively. Visual attributes indicating the subjective size, texture, prominence of the legs, subjective distance, and the overall presence of a spider were significant predictors of aversive responses. Our results shed light on the visual features that contribute to spider-related aversiveness. This knowledge may help in the selection and creation of stimuli that are particularly effective in improving classical exposure therapy, as well as novel computerized exposure-based treatments.

Neuroimaging has greatly improved our understanding of phobic mechanisms. To expand on these advancements, we present data on the heterogeneity of neural patterns in spider phobia combined with various psychological dimensions of spider phobia, using spider-relevant stimuli of various intensities. Specifically, we have created a database in which 49 spider-fearful individuals viewed 225 spider-relevant images in the fMRI scanner and performed behavioral avoidance tasks before and after the fMRI scan. For each participant, the database consists of the neuroimaging part, which includes an anatomical scan, 5 passive-viewing and 2 resting-state functional runs in both raw and preprocessed form, along with associated quality control reports. Additionally, a behavioral section includes self-report questionnaires and avoidance tasks collected in pre- and post-sessions. The dataset is well suited for investigating neural mechanisms of phobias, brain-behavior correlations, and also contributes to the existing phobic neuroimaging datasets with spider-fearful samples.

Background The Incentive-Sensitization Theory postulates that addiction is primarily driven by the sensitization of the brain’s reward system to addictive substances, such as nicotine. According to this theory, exposure to such substances leads to an increase in ‘wanting’, while ‘liking’ the experience remains relatively unchanged. Although this candidate mechanism has been well substantiated through animal brain research, its translational validity for humans has only been partially demonstrated so far, with evidence from human neuroscience data being very limited. Methods From fMRI data of N=31 individuals with Nicotine Use Disorder, we created multivoxel patterns capable of capturing wanting and liking-related dimensions from a smoking cue-reactivity task. Using these patterns, we then designed a novel resting-state ‘reading’ method to evaluate how much wanting or liking still persist as a neural trace after watching the cues. Results We found that the persistence of wanting-related brain patterns at rest increases with longer smoking history but this was not the case for liking-related patterns. Interestingly, such behavior has not been observed for non-temporal measures of smoking intensity. Conclusion This study provides basic human neuroscience evidence that the dissociation between liking and wanting escalates over time, further substantiating the Incentive-Sensitization Theory, at least for Nicotine Use Disorder. These results suggest that treatment approaches could be personalized to account for the variability in individuals’ neural adaptation to addiction by considering how individuals differ in the extent to which their incentive salience system is sensitized.

Exposure therapy is an established treatment for anxiety disorders but the mechanisms underpinning its effectiveness remain unclear. Two theories offer contrasting perspectives: the traditional habituation model posits that a form of stimulus desensitization is required during exposure, while the inhibitory learning model emphasizes the formation of new non-fearful associations. Crucially, while the former may manifest as amygdala habituation, the latter may not. To distinguish between the two models, this study uses functional magnetic resonance imaging to examine the amygdala responses of spider-fearful participants during fear exposure. We hypothesized that intervention success might align with stable or even increased amygdala activation – an indicator of active engagement and re-learning as proposed by the inhibitory learning model. Conversely, decreasing amygdala activity might not be a sign of reduced fear memory as proposed by the habituation model, but could signal mental detachment, leading to suboptimal treatment outcomes. Our results corroborated our hypotheses: individuals with escalating amygdala responses during exposure exhibited better clinical progress, while those showing amygdala ‘habituation’ benefited less. Our results strengthen the case for the inhibitory learning model and highlight that therapy may not aim to diminish fear per se but rather to engage patients in active processing and association formation.

Tobacco smoking is associated with deleterious health outcomes. Most smokers want to quit smoking, yet relapse rates are high. Understanding neural differences associated with tobacco use may help generate novel treatment options. Several animal studies have recently highlighted the central role of the thalamus in substance use disorders, but this research focus has been understudied in human smokers. Here, we investigated associations between structural and functional magnetic resonance imaging measures of the thalamus and its subnuclei to distinct smoking characteristics. We acquired anatomical scans of 32 smokers as well as functional resting‐state scans before and after a cue‐reactivity task. Thalamic functional connectivity was associated with craving and dependence severity, whereas the volume of the thalamus was associated with dependence severity only. Craving, which fluctuates rapidly, was best characterized by differences in brain function, whereas the rather persistent syndrome of dependence severity was associated with both brain structural differences and function. Our study supports the notion that functional versus structural measures tend to be associated with behavioural measures that evolve at faster versus slower temporal scales, respectively. It confirms the importance of the thalamus to understand mechanisms of addiction and highlights it as a potential target for brain‐based interventions to support smoking cessation, such as brain stimulation and neurofeedback.