Serotonergic Neurons in the Chick Brainstem Express Various Serotonin Receptor Subfamily Genes

Serotonin (5-hydroxytryptamine, 5-HT) is a phylogenetically conserved modulatory neurotransmitter. In mammals, 5-HT plays an important role in the regulation of many mental states and the processing of emotions in the central nervous system. Serotonergic neurons in the central nervous system, including the dorsal raphe (DR) and median raphe (MR) nuclei, are spatially clustered in the brainstem and provide ascending innervation to the entire forebrain and midbrain. Both between and within the DR and MR, these serotonergic neurons have different cellular characteristics, developmental origin, connectivity, physiology, and related behavioral functions. Recently, an understanding of the heterogeneity of the DR and MR serotonergic neurons has been developed at the molecular level. In birds, emotion-related behavior is suggested to be modulated by the 5-HT system. However, correspondence between the raphe nuclei of birds and mammals, as well as the cellular heterogeneity in the serotonergic neurons of birds are poorly understood. To further understand the heterogeneity of serotonergic neurons in birds, we performed a molecular dissection of the chick brainstem using in situ hybridization. In this study, we prepared RNA probes for chick orthologs of the following serotonin receptor genes: 5-HTR1A, 5-HTR1B, 5-HTR1D, 5-HTR1E, 5-HTR1F, 5-HTR2A, 5-HTR2B, 5-HTR2C, 5-HTR3A, 5-HTR4, 5-HTR5A, and 5-HTR7. We showed that the expression pattern of 5-HT receptors in the serotonin neurons of chick DR and MR may vary, suggesting heterogeneity among and within the serotonin neurons of the DR and MR in the chick brainstem. Our findings regarding the molecular properties of serotonergic neurons in the bird raphe system will facilitate a good understanding of the correspondence between bird and mammalian raphes.

The Pervasive Impact of Ignorance

Norm violations have been demonstrated to impact a wide range of seemingly non-normative judgments. Among other things, when agents' actions violate prescriptive norms they tend to be seen as having done those actions more freely, as having acted more intentionally, as being more of a cause of subsequent outcomes, and even as being less happy. The explanation of this effect continues to be debated, with some researchers appealing to features of actions that violate norms, and other researchers emphasising the importance of agents' mental states when acting. Here, we report the results of two large-scale experiments that replicate and extend twelve of the studies that originally demonstrated the pervasive impact of norm violations. In each case, we build on the pre-existing experimental paradigms to additionally manipulate whether the agents knew that they were violating a norm while holding fixed the action done. We find evidence for a pervasive impact of ignorance: the impact of norm violations on non-normative judgments depends largely on the agent knowing that they were violating a norm when acting. Moreover, we find evidence that the reduction in the impact of normality is underpinned by people's counterfactual reasoning: people are less likely to consider an alternative to the agent’s action if the agent is ignorant. We situate our findings in the wider debate around the role of normality in people's reasoning.

Recognition of Emotions for People with Autism: An Approach to Improve Skills

Autism spectrum disorder refers to a neurodevelopmental disorders characterized by repetitive behavior patterns, impaired social interaction, and impaired verbal and nonverbal communication. The ability to recognize mental states from facial expressions plays an important role in both social interaction and interpersonal communication. Thus, in recent years, several proposals have been presented, aiming to contribute to the improvement of emotional skills in order to improve social interaction. In this paper, a game is presented to support the development of emotional skills in people with autism spectrum disorder. The software used helps to develop the ability to recognize and express six basic emotions: joy, sadness, anger, disgust, surprise, and fear. Based on the theory of facial action coding systems and digital image processing techniques, it is possible to detect facial expressions and classify them into one of the six basic emotions. Experiments were performed using four public domain image databases (CK+, FER2013, RAF-DB, and MMI) and a group of children with autism spectrum disorder for evaluating the existing emotional skills. The results showed that the proposed software contributed to improvement of the skills of detection and recognition of the basic emotions in individuals with autism spectrum disorder.

Parental Mentalizing During a Pandemic: Use of Mental-State Language on Parenting Social Media Before and During the COVID-19 Pandemic

The COVID-19 pandemic has been a demanding caregiving context for parents, particularly during lockdowns. In this study, we examined parental mentalization, parents’ proclivity to consider their own and their child’s mental states, during the pandemic, as manifested in mental-state language (MSL) on parenting social media. Parenting-related posts on Reddit from two time periods in the pandemic in 2020, March to April (lockdown) and July to August (postlockdown), were compared with time-matched control periods in 2019. MSL and self–other references were measured using text-analysis methods. Parental mentalization content decreased during the pandemic: Posts referred less to mental activities and to other people during the COVID-19 pandemic and showed decreased affective MSL, cognitive MSL, and self-references specifically during lockdown. Father-specific subreddits exhibited strongest declines in mentalization content, whereas mother-specific subreddits exhibited smaller changes. Implications on understanding associations between caregiving contexts and parental mentalization, gender differences, and the value of using social-media data to study parenting and mentalizing are discussed.

Simultaneous Classification of Both Mental Workload and Stress Level Suitable for an Online Passive Brain–Computer Interface

Research studies on EEG-based mental workload detection for a passive BCI generally focus on classifying cognitive states associated with the performance of tasks at different levels of difficulty, with no other aspects of the user’s mental state considered. However, in real-life situations, different aspects of the user’s state such as their cognitive (e.g., level of mental workload) and affective (e.g., level of stress/anxiety) states will often change simultaneously, and performance of a BCI system designed considering just one state may be unreliable. Moreover, multiple mental states may be relevant to the purposes of the BCI—for example both mental workload and stress level might be related to an aircraft pilot’s risk of error—and the simultaneous prediction of states may be critical in maximizing the practical effectiveness of real-life online BCI systems. In this study we investigated the feasibility of performing simultaneous classification of mental workload and stress level in an online passive BCI. We investigated both subject-specific and cross-subject classification approaches, the latter with and without the application of a transfer learning technique to align the distributions of data from the training and test subjects. Using cross-subject classification with transfer learning in a simulated online analysis, we obtained accuracies of 77.5 ± 6.9% and 84.1 ± 5.9%, across 18 participants for mental workload and stress level detection, respectively.

COVID-19 Changed Prevalence, Disease Spectrum and Management Strategies of Ocular Trauma

The coronavirus disease 2019 (COVID-19) pandemic has significantly impacted the health of people around the world and has reshaped social behaviors and clinical practice. The purpose of this perspective is to provide epidemiologists and clinicians with information about how the spectrum of ocular trauma diseases changed, as well as to optimize management for improving patient prognosis during this crisis. Analysis of current studies revealed that the prevalence of eye trauma decreased overall, with a trend of delayed medical treatment during the COVID-19 era. Irregular epidemic prevention and control measures, unprotected home activities, and unusual mental states are the main causes of ocular trauma. Strategies for reducing morbidity are also discussed, including popularizing the use norms of prevention and control supplies, taking heed to the safety of family activities, highlighting the special status of child protection, and paying attention to previous case data to implement region-specific precautions. The procedure of ophthalmological emergency and outpatient management should also be optimized, and mental health should be emphasized during this pandemic.

IS MENTAL HEALTH RESPONSIBLE FOR ANGER OUTBURSTS AND ULTIMATELY HYPERTENSION?

Objectives: To explore the relationship of depression, anxiety, and stress (mental health) with anger dimensions and to study that if these mental states predict hypertension disease? Methodology: Cross-sectional research design was used in the current research. Data was collected from 3 public sector hospitals of Lahore from May 15, 2019 to September 30, 2019. Sample of (N = 240) consecutive hypertensive patients with Mage 43.0707 ± 7.99 were recruited. Depression, Anxiety and Stress Scale (Lovibond & Lovibond, 1995), and State Trait Anger Expression Inventory (Spielberger, 1988) were used for data collection. Descriptive statistics, logistic regression, and independent samples t-test were carried on for data analyses. Results: Significant positive correlation of depression, anxiety, and stress with anger dimensions was explore. Depression appeared as predictors of state anger, trait anger, anger in, anger control, and total anger (p<0.05). Anxiety emerged as predictor of state anger, trait anger, anger in, anger control, and total anger and stress as predictor of state anger, trait anger, anger in, anger control, and total anger. Significant gender differences appeared in depression, anxiety, stress, state anger, trait anger, anger in, anger control, and total anger (p<0.05). Conclusion: Depression, anxiety, and stress have a significant relationship with anger and hypertension disease.

Sportsman’s Mental State Evaluation and Early Warning Method Using Decision Tree

Aiming at the intelligent needs of psychological state assessment of university students, the text information-based psychological problem identification approach is investigated in the paper. This approach uses the text of student forums within universities as the database and introduces the convolutional neural network (CNN) model in deep learning, which contains a convolutional layer, a pooling layer, and a fully connected layer. After the convolution is completed, the convolution result is de-linearized by the activation function, and then pooling is performed to improve the fitting ability of the network for nonlinearities. For data processing, behavioral features attribute features, content features, and social relationship features are extracted from text information as the input of the CNN by using the decision tree. The psychological lexicon of expertise (LIWC) is used to enhance the efficiency of text word frequency statistics when performing text content extraction. To evaluate the performance of the proposed method, simulations are performed in the open dataset of CLPsyh2017 ReachOut Forum, and the FastText method is used as a comparison. The results show that the CNN model achieves an accuracy of 0.71 in the full-sample domain, which is significantly higher than that of the FastText model at 0.64. In the early warning evaluation of mental states, the CNN performance is better than that of FastText.

The Energy Homeostasis Principle: A Naturalistic Approach to Explain the Emergence of Behavior

It is still elusive to explain the emergence of behavior and understanding based on its neural mechanisms. One renowned proposal is the Free Energy Principle (FEP), which uses an information-theoretic framework derived from thermodynamic considerations to describe how behavior and understanding emerge. FEP starts from a whole-organism approach, based on mental states and phenomena, mapping them into the neuronal substrate. An alternative approach, the Energy Homeostasis Principle (EHP), initiates a similar explanatory effort but starts from single-neuron phenomena and builds up to whole-organism behavior and understanding. In this work, we further develop the EHP as a distinct but complementary vision to FEP and try to explain how behavior and understanding would emerge from the local requirements of the neurons. Based on EHP and a strict naturalist approach that sees living beings as physical and deterministic systems, we explain scenarios where learning would emerge without the need for volition or goals. Given these starting points, we state several considerations of how we see the nervous system, particularly the role of the function, purpose, and conception of goal-oriented behavior. We problematize these conceptions, giving an alternative teleology-free framework in which behavior and, ultimately, understanding would still emerge. We reinterpret neural processing by explaining basic learning scenarios up to simple anticipatory behavior. Finally, we end the article with an evolutionary perspective of how this non-goal-oriented behavior appeared. We acknowledge that our proposal, in its current form, is still far from explaining the emergence of understanding. Nonetheless, we set the ground for an alternative neuron-based framework to ultimately explain understanding.