Does compulsion explain addiction?

One of the leading drug addiction theories states that habits and the underlying neural process of a ventral to dorsal striatal shift are the building blocks of compulsive drug-seeking behaviour and that compulsion is the maladaptive persistence of responding despite adverse consequences. Here we discuss that compulsive behaviour as defined primarily from the perspective of animal experimentation falls short of the clinical phenomena and their neurobiological correlates. Thus for the human condition, the concept of compulsive habbits should be critically addressed and potentially revised.

Analysis of post-market adverse events of istradefylline: a real-world study base on FAERS database.

Analyze the adverse event (AE) signals of istradefylline based on the FAERS database. By extracting large-scale data from the FAERS database, this study used various signal quantification techniques such as ROR, PRR, BCPNN, and MGPS to calculate and evaluate the ratio and association between istradefylline and specific AEs. In the FAERS database, this study extracted data from the third quarter of 2019 to the first quarter of 2023, totaling 6,749,750 AE reports. After data cleansing and drug screening, a total of 3633 AE reports related to istradefylline were included for analysis. Based on four calculation methods, this study unearthed 25 System Organ Class (SOC) AE signals and 82 potential preferred terms (PTs) related to istradefylline. The analysis revealed new AEs during istradefylline treatment, including reports of Parkinsonism hyperpyrexia syndrome (n = 3, ROR 178.70, PRR 178.63, IC 1.97, EBGM 165.63), Compulsions (n = 5, ROR 130.12, PRR 130.04, IC 2.53, EBGM 123.02), Deep brain stimulation (n = 10, ROR 114.42, PRR 114.27, IC 3.33, EBGM 108.83), and Freezing phenomenon (n = 60, ROR 97.52, PRR 96.76, IC 5.21, EBGM 92.83). This study provides new risk signals and important insights into the use of istradefylline, but further research and validation are needed, especially for those AE that may occur in actual usage scenarios but are not yet explicitly described in the instructions.

Developing feasible and acceptable strategies for integrating the use of patient-reported outcome measures (PROMs) in gender-affirming care: An implementation study.

OBJECTIVE: Use CFIR guidance to create comprehensive, evidence-based, feasible, and acceptable gender-affirming care PROM implementation strategies. DESIGN, SETTING, PARTICIPANTS: A 3-Phase participatory process was followed to design feasible and acceptable strategies for integrating PROMs in gender-affirming care. In Phase 1, barriers and enablers to PROM implementation for gender-affirming care were identified from a previous systematic review and our prior qualitative study. We used the CFIR-ERIC tool to match previously identified barriers and enablers with expert-endorsed implementation strategies. In Phase 2, implementation strategy outputs from CFIR-ERIC were organised according to cumulative percentage value. In Phase 3, gender-affirming care PROM implementation strategies underwent iterative refinement based on rounds of stakeholder feedback with seven patient and public partners and a gender-affirming healthcare professional. RESULTS: The systematic review and qualitative study identified barriers and enablers to PROM implementation spanning all five CFIR domains, and 30 CFIR constructs. The top healthcare professional-relevant strategies to PROM implementation from the CFIR-ERIC output include: identifying and preparing implementation champions, collecting feedback on PROM implementation, and capturing and sharing local knowledge between clinics on implementation. Top patient-relevant strategies include: having educational material on PROMs, ensuring adaptability of PROMs, and collaborating with key local organisations who may be able to support patients. CONCLUSIONS: This study developed evidence-based, feasible, and acceptable strategies for integrating PROMs in gender-affirming care, representing evidence from a systematic review of 286 international articles, a qualitative study of 24 gender-affirming care patients and healthcare professionals, and iteration from 7 patient and public partners and a gender-affirming healthcare professional. The finalised strategies include patient- and healthcare professional-relevant strategies for implementing PROMs in gender-affirming care. Clinicians and researchers can select and tailor implementation strategies best applying to their gender-affirming care setting.

From compulsivity to compulsion: the neural basis of compulsive disorders.

Compulsive behaviour, an apparently irrational perseveration in often maladaptive acts, is a potential transdiagnostic symptom of several neuropsychiatric disorders, including obsessive-compulsive disorder and addiction, and may reflect the severe manifestation of a dimensional trait termed compulsivity. In this Review, we examine the psychological basis of compulsions and compulsivity and their underlying neural circuitry using evidence from human neuroimaging and animal models. Several main elements of this circuitry are identified, focused on fronto-striatal systems implicated in goal-directed behaviour and habits. These systems include the orbitofrontal, prefrontal, anterior cingulate and insular cortices and their connections with the basal ganglia as well as sensoriomotor and parietal cortices and cerebellum. We also consider the implications for future classification of impulsive-compulsive disorders and their treatment.

The role of psychosis and clozapine load in excessive checking in treatment-resistant schizophrenia: longitudinal observational study.

BACKGROUND: A significant proportion of people with clozapine-treated schizophrenia develop 'checking' compulsions, a phenomenon yet to be understood. AIMS: To use habit formation models developed in cognitive neuroscience to investigate the dynamic interplay between psychosis, clozapine dose and obsessive-compulsive symptoms (OCS). METHOD: Using the anonymised electronic records of a cohort of clozapine-treated patients, including longitudinal assessments of OCS and psychosis, we performed longitudinal multi-level mediation and multi-level moderation analyses to explore associations of psychosis with obsessiveness and excessive checking. Classic bivariate correlation tests were used to assess clozapine load and checking compulsions. The influence of specific genetic variants was tested in a subsample. RESULTS: A total of 196 clozapine-treated individuals and 459 face-to-face assessments were included. We found significant OCS to be common (37.9%), with checking being the most prevalent symptom. In mediation models, psychosis severity mediated checking behaviour indirectly by inducing obsessions (r = 0.07, 95% CI 0.04-0.09; P < 0.001). No direct effect of psychosis on checking was identified (r = -0.28, 95% CI -0.09 to 0.03; P = 0.340). After psychosis remission (n = 65), checking compulsions correlated with both clozapine plasma levels (r = 0.35; P = 0.004) and dose (r = 0.38; P = 0.002). None of the glutamatergic and serotonergic genetic variants were found to moderate the effect of psychosis on obsession and compulsion (SLC6A4, SLC1A1 and HTR2C) survived the multiple comparisons correction. CONCLUSIONS: We elucidated different phases of the complex interplay of psychosis and compulsions, which may inform clinicians' therapeutic decisions.

Spatio-Temporal Image-Based Encoded Atlases for EEG Emotion Recognition.

Emotion recognition plays an essential role in human-human interaction since it is a key to understanding the emotional states and reactions of human beings when they are subject to events and engagements in everyday life. Moving towards human-computer interaction, the study of emotions becomes fundamental because it is at the basis of the design of advanced systems to support a broad spectrum of application areas, including forensic, rehabilitative, educational, and many others. An effective method for discriminating emotions is based on ElectroEncephaloGraphy (EEG) data analysis, which is used as input for classification systems. Collecting brain signals on several channels and for a wide range of emotions produces cumbersome datasets that are hard to manage, transmit, and use in varied applications. In this context, the paper introduces the Empátheia system, which explores a different EEG representation by encoding EEG signals into images prior to their classification. In particular, the proposed system extracts spatio-temporal image encodings, or atlases, from EEG data through the Processing and transfeR of Interaction States and Mappings through Image-based eNcoding (PRISMIN) framework, thus obtaining a compact representation of the input signals. The atlases are then classified through the Empátheia architecture, which comprises branches based on convolutional, recurrent, and transformer models designed and tuned to capture the spatial and temporal aspects of emotions. Extensive experiments were conducted on the Shanghai Jiao Tong University (SJTU) Emotion EEG Dataset (SEED) public dataset, where the proposed system significantly reduced its size while retaining high performance. The results obtained highlight the effectiveness of the proposed approach and suggest new avenues for data representation in emotion recognition from EEG signals.

Multiple serous cavity effusion screening based on smear images using vision transformer.

Serous cavity effusion is a prevalent pathological condition encountered in clinical settings. Fluid samples obtained from these effusions are vital for diagnostic and therapeutic purposes. Traditionally, cytological examination of smears is a common method for diagnosing serous cavity effusion, renowned for its convenience. However, this technique presents limitations that can compromise its efficiency and diagnostic accuracy. This study aims to overcome these challenges and introduce an improved method for the precise detection of malignant cells in serous cavity effusions. We have developed a transformer-based classification framework, specifically employing the vision transformer (ViT) model, to fulfill this objective. Our research involved collecting smear images and corresponding cytological reports from 161 patients who underwent serous cavity drainage. We meticulously annotated 4836 patches from these images, identifying regions with and without malignant cells, thus creating a unique dataset for smear image classification. The findings of our study reveal that deep learning models, particularly the ViT model, exhibit remarkable accuracy in classifying patches as malignant or non-malignant. The ViT model achieved an impressive area under the receiver operating characteristic curve (AUROC) of 0.99, surpassing the performance of the convolutional neural network (CNN) model, which recorded an AUROC of 0.86. Additionally, we validated our models using an external cohort of 127 patients. The ViT model sustained its high-level screening performance, achieving an AUROC of 0.98 at the patient level, compared to the CNN model's AUROC of 0.84. The visualization of our ViT models confirmed their capability to precisely identify regions containing malignant cells in multiple serous cavity effusion smear images. In summary, our study demonstrates the potential of deep learning models, particularly the ViT model, in automating the screening process for serous cavity effusions. These models offer significant assistance to cytologists in enhancing diagnostic accuracy and efficiency. The ViT model stands out for its advanced self-attention mechanism, making it exceptionally suitable for tasks that necessitate detailed analysis of small, sparsely distributed targets like cellular clusters in serous cavity effusions.

Pathological buying on the rise? Compensative and compulsive buying in Poland in the pre- and (Post-)pandemic times.

The study concerns the development of compensative and compulsive buying in Poland comparing the results of three waves of a cross-sectional study conducted before and at the end of the COVID-19 pandemic. Six predictors of susceptibility to compensative and compulsive buying are in focus: materialism, self-esteem, gender, age, frequency of online shopping, and experience of the COVID-19 pandemic. However, the importance of the first four predictors in explaining compensative and compulsive buying is already very well described in the literature, while the novelty consists in the predictive model including the variables that describe frequency of online shopping and negative experiences related to the COVID-19 pandemic, such as coronavirus infection, hospitalization or death of a loved one. On the one hand, a stronger susceptibility to compensative and compulsive buying could be a reaction to these negative experiences of the pandemic; on the other hand, the increased frequency of online shopping as a result of the pandemic may be an important factor in the development of compensative and compulsive buying due to the easy implementation of purchase acts and weaker social control. To achieve the above research objectives, the German Compulsive Buying Indicator (GCBI) was used to measure susceptibility to compensative and compulsive buying. The data were obtained within three waves of the study (2010, 2019, 2022) based on a random sample of about 1,000 respondents representing statistically the general adult population. Drawing on this study, the prevalence of compensative and compulsive buying is observed at 12-19% and 2-4%. The predictors of GCBI are materialism, self-esteem, gender in all examined models and additionally age, frequency of online shopping, and experience of the COVID-19 pandemic in selected models. Although the findings related to the role of materialism, self-esteem, and gender in the prediction of GCBI reflect the results reported in the literature, the analogous conclusions about age, online shopping, and experiences with the COVID-19 pandemic are different from the established opinions. The commonly reported effect of age becomes statistically significant when the examined population is limited to Gens Y and Z. Although extensive online shopping co-exists with compensative and compulsive buying in the total population, the obtained data lead to reverse conclusions in the case of women's subpopulation representing Gens Y and Z. The negative experience with the COVID-19 pandemic operationalised as hospitalization of a close friend predicts GCBI, but again only in the case of representatives of Gens Y and Z, especially among women. The findings show how important the creation of appropriate intervention strategies is within the consumer policy directed to representatives of the younger generations who may develop pathological buying as a response to negative experiences such as COVID-19 pandemic. The findings can inform of the goals behind therapeutic support for compulsive buyers, and implications for social work. People affected by excessive compensative or compulsive buying need to be given opportunities to build up their strengths and growth of their psychological resources towards healthy self-esteem, which seems to be the best protection against excessive compensative and compulsive buying.

A network analysis of mechanisms of change during exposures over the course of intensive OCD treatment.

Exposure and response prevention (ERP) is an evidence-based treatment for obsessive-compulsive disorder (OCD). Theories for how it works vary in their emphasis on active mechanisms of change. The current study aimed to clarify mechanisms of change in ERP for OCD using network analysis, comparing ERP networks at the start and end of intensive treatment (partial hospital and residential). In our sample of 182 patients, the most central node in both networks was engagement with exposure, which was consistently related to greater understanding of ERP rationale, higher willingness, and less ritualization, accounting for all other variables in the network. There were no significant differences in networks between the start and end of treatment. These results suggest that nonspecific parameters like facilitating engagement in exposures without ritualizing and providing a clear rationale to clients may be key to effective treatment. As such, it may be useful for clinicians to spend adequate time underscoring the need to eliminate rituals to fully engage in exposure tasks and explaining the rationale for ERP prior to doing exposures, regardless of theoretical orientation. Nonetheless, findings represent group-level statistics and more fine-grained idiographic analyses may reveal individual-level differences with respect to central mechanisms of change. Other limitations include demographic homogeneity of our sample.

Current Understanding of Compulsive Sexual Behavior Disorder and Co-occurring Conditions: What Clinicians Should Know about Pharmacological Options.

Compulsive sexual behavior disorder (CSBD) has recently been recognized as a psychiatric disorder. Pharmacological treatments for CSBD have received little study and thus have limited empirical support. The main objective of the present work is to review existing literature on the efficacy of different drugs on the symptomatology of CSBD, including the subtype of problematic pornography use (PPU). The main pharmacological approaches to treating CSBD have included opioid antagonists (naltrexone and nalmefene), selective serotonin reuptake inhibitors (paroxetine, citalopram, fluoxetine, and sertraline), mood stabilizers (topiramate), tricyclic antidepressants (clomipramine), serotonin antagonist and reuptake inhibitors (nefazodone), and N-acetylcysteine. Since people with CSBD may experience different co-occurring disorders, these should be considered when choosing the best pharmacological treatment. Pharmacological therapy for CSBD/PPU has been suggested as an adjunct to psychological therapies, which, for the moment, have the most empirical evidence. However, to evaluate the efficacy of most of the drugs presented in this narrative review, data to date have only been available from case studies. Thus, empirical support is scant and generalizability of results is limited, highlighting the need for more research in this area.

Dance for the dead: The role of top-down beliefs for social cohesion and anxiety management in naturally occurring collective rituals.

Collective rituals, particularly those characterized by synchrony and pain, have been shown to yield positive social and emotional outcomes. The question arises as to whether these findings extend to low-arousal, family-centered rituals and how spiritual beliefs factor into these communal practices. This study set out to examine the interplay between belief, ritual participation, and their effects on anxiety, social cohesion, and prosocial behavior during a low-arousal collective ritual in Mikasa, Japan. Drawing upon a sample of 183 festival participants, we measured belief in ancestors using a novel scale, identifying significant and consistent associations between these beliefs and measures of social cohesion across multiple targets. Moreover, active participation as a festival dancer displayed a positive relationship with feelings of social cohesion, particularly towards other festival attendees and at the national level. On measures of prosocial behavior, ancestral beliefs were positively associated with generosity shown within the festival setting, whereas observers were less generous towards community members than a non-attending control group. Anxiety outcomes displayed a negative relationship with ancestral beliefs and ritual observation but not participation as seen in previous research, suggesting a complex interplay between rituals, emotions, and individual states. These findings provide novel insights into the importance of belief systems and active participation in shaping social bonds and behaviors in the context of collective rituals.

Maximizing translational value in models of compulsive behavior: A commentary on Pickenhan et al. (2024).

In this issue of Cognitive, Affective, and Behavioral Neuroscience, Pickenhan et al. (2024) discuss the need for translational studies to understand features underlying obsessive-compulsive disorder (OCD). They highlight the translational value of the observing-response task (ORT) for modeling functional and maladaptive checking behaviors, a common symptom of OCD.

Plectronoceratids (Cephalopoda) from the latest Cambrian at Black Mountain, Queensland, reveal complex three-dimensional siphuncle morphology, with major taxonomic implications.

The Plectronoceratida includes the earliest known cephalopod fossils and is thus fundamental to a better understanding of the origin and early evolution of this group of molluscs. The bulk of described material comes from the late Cambrian Fengshan Formation in North China with isolated occurrences in South China, Laurentia, Kazakhstan and Siberia. Knowledge of their morphology and taxonomy is limited in that most specimens were only studied as longitudinal sections, which are prone to misinterpretations due to variations in the plane of section. We describe more than 200 new specimens, which exceeds the entire hitherto published record of plectronoceratids. The material was collected by Mary Wade and colleagues during the 1970s and 1980s, from the lower Ninmaroo Formation at Black Mountain (Mount Unbunmaroo), Queensland, Australia. Despite the collecting effort, diverse notes and early incomplete drafts, Mary Wade never published this material before her death in 2005. The specimens provide novel insights into the three-dimensional morphology of the siphuncle based on abundant material, prompting a general revision of the order Plectronoceratida. We describe Sinoeremoceras marywadeae sp. nov. from numerous, well-preserved specimens, allowing investigation of ontogenetic trajectories and intraspecific variability, which in turn enables improved interpretations of the three-dimensional siphuncle morphology. The siphuncle of S. marywadeae sp. nov. and other plectronoceratids is characterised by highly oblique segments, an elongated middorsal portion of the septal neck (= septal flap) and laterally expanded segments that extend dorsally relative to the septal flap (= siphuncular bulbs). We show that this complex siphuncular structure has caused problems of interpretation because it was studied mainly from longitudinal sections, leading to the impression that there were large differences between specimens and supposed species. We revise the order Protactinoceratida and the families Protactinoceratidae and Balkoceratidae as junior synonyms of the Plectronoceratida and Plectronoceratidae, respectively. We reduce the number of valid genera from eighteen (including one genus formerly classified as an ellesmeroceratid) to three: Palaeoceras Flower, 1954, Plectronoceras Kobayashi, 1935 and Sinoeremoceras Kobayashi, 1933. We accept 10 valid species to which the 68 previously established species may be assigned. Sinoeremoceras contains 8 of the 10 plus the new species. Two species, previously referred to ellesmeroceratid genera, are transferred to Sinoeremoceras. This revised scheme groups plectronoceratids into distinct geographically and stratigraphically separated species, which better reflects biological realities and removes bias caused by preparation techniques. North China remains important containing the highest known diversity and was likely a centre of cephalopod diversification.

Conducting head-mounted eye-tracking research with young children with autism and children with increased likelihood of later autism diagnosis.

BACKGROUND: Over the past years, researchers have been using head-mounted eye-tracking systems to study young children's gaze behaviors in everyday activities through which children learn about the world. This method has great potential to further our understanding of how millisecond-level gaze behaviors create multisensory experiences and fluctuate around social environments. While this line of work can yield insight into early perceptual experiences and potential learning mechanisms, the majority of the work is exclusively conducted with typically-developing children. Sensory sensitivities, social-communication difficulties, and challenging behaviors (e.g., disruption, elopement) are common among children with developmental disorders, and they may represent potential methodological challenges for collecting high-quality data. RESULTS: In this paper, we describe our research practices of using head-mounted eye trackers with 41 autistic children and 17 children with increased likelihood of later autism diagnosis without auditory or visual impairments, including those who are minimally or nonspeaking and/or have intellectual disabilities. The success rate in gathering data among children with autism was 92.68%. 3 of 41 children failed to complete the play-session, resulting in an 86.36% success rate among 1-4-year-olds and a 100.00% success rate among 5-8-year-olds. 1 of 17 children with increased likelihood of later autism diagnosis failed to complete the play-session, resulting in a success rate of 94.11%. There were numerous "challenging" behaviors relevant to the method. The most common challenging behaviors included taking the eye-tracking device off, elopement, and becoming distressed. Overall, among children with autism, 88.8% of 1-4-year-olds and 29.4% of 5-8-year-olds exhibited at least one challenging behavior. CONCLUSIONS: Research capitalizing on this methodology has the potential to reveal early, socially-mediated gaze behaviors that are relevant for autism screening, diagnosis, and intervention purposes. We hope that our efforts in documenting our study methodology will help researchers and clinicians effectively study early naturally-occuring gaze behaviors of children during non-experimental contexts across the spectrum and other developmental disabilities using head-mounted eye-tracking. Ultimately, such applications may increase the generalizability of results, better reflect the diversity of individual characteristics, and offer new ways in which this method can contribute to the field.

The segmentation and intelligent recognition of structural surfaces in borehole images based on the U2-Net network.

Structural planes decrease the strength and stability of rock masses, severely affecting their mechanical properties and deformation and failure characteristics. Therefore, investigation and analysis of structural planes are crucial tasks in mining rock mechanics. The drilling camera obtains image information of deep structural planes of rock masses through high-definition camera methods, providing important data sources for the analysis of deep structural planes of rock masses. This paper addresses the problems of high workload, low efficiency, high subjectivity, and poor accuracy brought about by manual processing based on current borehole image analysis and conducts an intelligent segmentation study of borehole image structural planes based on the U2-Net network. By collecting data from 20 different borehole images in different lithological regions, a dataset consisting of 1,013 borehole images with structural plane type, lithology, and color was established. Data augmentation methods such as image flipping, color jittering, blurring, and mixup were applied to expand the dataset to 12,421 images, meeting the requirements for deep network training data. Based on the PyTorch deep learning framework, the initial U2-Net network weights were set, the learning rate was set to 0.001, the training batch was 4, and the Adam optimizer adaptively adjusted the learning rate during the training process. A dedicated network model for segmenting structural planes was obtained, and the model achieved a maximum F-measure value of 0.749 when the confidence threshold was set to 0.7, with an accuracy rate of up to 0.85 within the range of recall rate greater than 0.5. Overall, the model has high accuracy for segmenting structural planes and very low mean absolute error, indicating good segmentation accuracy and certain generalization of the network. The research method in this paper can serve as a reference for the study of intelligent identification of structural planes in borehole images.

Collecting behavioral evidence from a highly mobile and seasonal population: A protocol for a survey on quad bike injuries.

BACKGROUND: Quad bikes are popular recreational, four-wheeled bikes in the Middle East. Injury prevention programs targeting quad bike crashes in the United Arab Emirates (UAE) need evidence about the risk factors and behaviours associated with these crashes in the target population. This is a protocol for a study aiming to investigate quad bike rider behaviours and to assess the risk factors associated with related injuries in the UAE. METHODS: This is a cross-sectional observational study aiming to describe a seasonal sport in a desert environment. With an estimated sample size of 451, the survey will follow a three-stage, location-based sampling strategy using the line-transect method. A sampling frame of desert locations with high injury incidences was developed, using Dubai ambulance injury records. Further expansion of the sampling frame was participatory, involving police, enthusiasts, emergency responders and gas station employees. The data collection will be limited to the winter months in fifteen high-injury desert locations across three major Emirates in the UAE. Trained researchers will observe the riders directly in the desert to note their riding habits, followed by a researcher-administered interview on riding and injury history. The interviews will be administered in Arabic and English using Qualtrics software on handheld tablets with offline and online entry mode. In addition, paper-based entry with the same format will be used as a contingency in busy quad bike locations. CONCLUSION: The objective of this study protocol is to develop a comprehensive survey that will furnish substantial evidence for the formulation of effective injury prevention strategies. To enhance the credibility of the recorded riding behaviors, field observations will be employed. The uniqueness of this study lies in its innovative sampling strategy, custom-tailored to accommodate the highly mobile and transient population of desert bikers in the UAE.