Search Results (54)

Objectives. Identity disturbance and instability in Borderline Personality Disorder (BPD) are associated with impairments in the integration of emotional autobiographical memory (EAM). At the neurophysiological level, it has been suggested that EAM dysfunction may be linked with functional connectivity (FC) alterations of the salience network (SN). Despite this, evidence in adolescents with BPD remains scarce, especially under task-related conditions. Therefore, we investigated SN electroencephalography (EEG) FC in adolescents with BPD during the resting-state condition (RS) and during two EAM tasks (i.e., happiness- and fear-related). Methods. A total of 24 female adolescents with BPD and 15 healthy controls underwent RS and task-related EEG recording. All participants were also assessed for BPD and related clinical dimensions. EEG FC analyses in the SN were performed using exact Low-Resolution Brain Electromagnetic Tomography (eLORETA) software. Results. Compared to controls, BPD patients exhibited reduced theta SN connectivity during RS. This hypo-connectivity pattern was positively correlated with all BPD-related dimensions (i.e., emotional dysregulation, impulsiveness, dissociative symptoms, and childhood trauma). Furthermore, compared to the RS, during the listening of fear-related memories, BPD patients showed an increase in delta SN connectivity. This hyper-connectivity pattern was negatively correlated with the self-reported vividness of recall. Conclusions. While decreased SN theta connectivity may be a common neural marker of traumatic disintegration, increased SN delta connectivity may indicate a neural correlate of suppression/avoidance of negative memories. Full article

Emotion alters the way humans walk, yet most prior studies have relied on laboratory-based 3D motion capture systems. While accurate, these approaches limit translation to real-world settings and have largely focused on spatiotemporal parameters and joint motions. This study evaluated the feasibility of using inertial measurement units (IMUs) to detect emotion-related changes in gait variability as well as spatiotemporal gait parameters. Fourteen healthy young adults completed overground gait trials while wearing two ankle-mounted IMUs. Five target emotions, anger, sadness, neutral emotion, joy, and fear, were elicited using an autobiographical memory paradigm. The IMUs measured stride length, stride time, stride velocity, cadence, and gait variability. The results showed that stride length, stride time, stride velocity, and cadence significantly differed across emotions. Anger and joy were associated with longer strides and faster velocities, while sadness produced slower walking with longer stride times and reduced cadence. Interestingly, gait variability did not differ significantly across emotional states. These findings demonstrate that IMUs can capture emotion specific gait changes previously documented with motion capture, supporting their feasibility for use in natural and clinical contexts. This work advances understanding of how emotions shape gait and highlights the potential of wearable technology for unobtrusive emotion and mobility research. Full article

Background/Objectives: Emotional fear memories are increasingly recognized as contributors to the development of specific fears and phobias. Despite this, relatively little dental fear research has specifically focused on patient memories or their potential role in the etiology of dental fear. Methods: This two-study paper employs qualitative thematic analysis of memories for dental visits among traumatized patients (study 1) and the general patient population (ranging from endorsing no dental fear to severe fear). Recollections were evaluated based on the characteristics (i.e., sensory descriptors, affectively laden, intrusive) of emotional fear memories (studies 1 and 2) and according to a modified cognitive vulnerability model of dental fear (study 2). Results: Characteristics of emotional fear memories were ubiquitous across recollections of individuals who endorsed traumatic dental visits in childhood. Among the general patient population, these characteristics and cognitive vulnerability themes (particularly perceptions of the visit and dentist as dangerous and untrustworthy) were more prevalent in the earliest remembered visits for fearful individuals. When individuals were asked to recall their worst dental visits, emotional fear memory characteristics and vulnerability perceptions were evident across the spectrum of current fear (none to severe). Conclusions: This study contributes to nascent work examining memory in specific fears and phobias and suggests that worst recollections across a general sample share many of the characteristics that might otherwise imply vulnerability for anxiety. We recommend that dental practices universally screen patients for fear, inquire about past negative experiences, partner with patients to minimize evoking their specific vulnerabilities, and diligently implement these personalized care plans. Full article

Post-traumatic stress disorder (PTSD) has traditionally been viewed as a psychiatric disorder of fear, memory, and emotional regulation. However, growing evidence implicates systemic and neuroinflammation as key contributors. Individuals with PTSD often exhibit elevated blood levels of pro-inflammatory cytokines such as IL-1β, IL-6, TNF-α, and C-reactive protein, indicating immune dysregulation. Dysfunctions in the hypothalamic–pituitary–adrenal (HPA) axis marked by reduced cortisol levels impair the body’s ability to regulate inflammation, allowing persistent immune activation. Circulating cytokines cross a weakened blood–brain barrier and activate microglia, which release additional inflammatory mediators. This neuroinflammatory loop can damage brain circuits critical to emotion processing including the hippocampus, amygdala, and prefrontal cortex, and disrupt neurotransmitter systems like serotonin and glutamate, potentially explaining PTSD symptoms such as hyperarousal and persistent fear memories. Rodent models of PTSD show similar inflammatory profiles, reinforcing the role of neuroinflammation in disease pathology. Bromo-epi-androsterone (BEA), a synthetic analog of dehydroepiandrosterone (DHEA), has shown potent anti-inflammatory effects in clinical trials, significantly reducing IL-1β, IL-6, and TNF-α. By modulating immune activity, BEA represents a promising candidate for mitigating neuroinflammation and its downstream effects in PTSD. These findings support the rationale for initiating clinical trials of BEA as a novel therapeutic intervention for PTSD. Full article

The aim of this article is to critically and reliably assess the potential of current emotion recognition technologies for practical applications in human–computer interaction (HCI) systems. The study made use of two databases: one in English (RAVDESS) and another in Polish (EMO-BAJKA), both containing speech recordings expressing various emotions. The effectiveness of recognizing seven and eight different emotions was analyzed. A range of acoustic features, including energy features, mel-cepstral features, zero-crossing rate, fundamental frequency, and spectral features, were utilized to analyze the emotions in speech. Machine learning techniques such as convolutional neural networks (CNNs), long short-term memory (LSTM) networks, and support vector machines with a cubic kernel (cubic SVMs) were employed in the emotion classification task. The research findings indicated that the effective recognition of a broad spectrum of emotions in a subject-independent approach is limited. However, significantly better results were obtained in the classification of paired emotions, suggesting that emotion recognition technologies could be effectively used in specific applications where distinguishing between two particular emotional states is essential. To ensure a reliable and accurate assessment of the emotion recognition system, care was taken to divide the dataset in such a way that the training and testing data contained recordings of completely different individuals. The highest classification accuracies for pairs of emotions were achieved for Angry–Fearful (0.8), Angry–Happy (0.86), Angry–Neutral (1.0), Angry–Sad (1.0), Angry–Surprise (0.89), Disgust–Neutral (0.91), and Disgust–Sad (0.96) in the RAVDESS. In the EMO-BAJKA database, the highest classification accuracies for pairs of emotions were for Joy–Neutral (0.91), Surprise–Neutral (0.80), Surprise–Fear (0.91), and Neutral–Fear (0.91). Full article

This study arises from the growing need to train professionals capable of confronting and analyzing the overabundance of information in an increasingly complex world, where critical thinking is seen as an indispensable skill for informed decision making and problem solving. To this end, a systematic narrative review methodology was applied to the scientific literature, compiling data from various international databases. The results reveal that physiological factors (memory, attention, nutrition and physical activity), psychological factors (cognitive biases, fear of ambiguity, and metacognition), sociocultural factors (diversity, inequality, and cultural norms), technological factors (digitalization, use of AI, and digital literacy), and educational factors (active pedagogical strategies and collaborative work) play a determining role in the development of critical thinking in higher education. The discussion emphasizes the complex interaction between these factors and underscores the need for holistic approaches that strengthen both cognitive competencies and emotional well-being. In conclusion, we recommend designing comprehensive training interventions that consider the identified factors, promoting inclusive and reflective environments, aimed at developing critical, autonomous graduates capable of facing contemporary challenges. Full article

Recognizing widespread emotional and mental health issues among students during the COVID-19 pandemic, it is crucial to investigate whether recovery and resilience have emerged in the post-pandemic era. A retrospective survey was conducted with high school students in Da Nang, a Vietnamese tourist city that endured multiple waves of COVID-19 from 2020 to 2022. The survey was conducted 18 months after Da Nang was locked down and had only recently entered the ‘new normal’ phase in early 2023. Results revealed that even though the pandemic had subsided, negative emotional experiences remained vivid in students’ memories, even when the pandemic was internationally declared to have ended. Fears of illness, death, isolation, losing social connections, and disruptions in academic paths still lingered. Nevertheless, a significant rebound from predominantly negative to positive emotions was observed among the young people. Understanding which negative emotions affected students the most will allow us to devise more targeted policies and provide more effective social services in response to similar public health crises in the future. Full article

Background: The fimbria-fornix is a nerve fiber bundle that connects various structures of the limbic system in the brain and plays a key role in cognition. It has become a major target of deep brain stimulation (DBS) to treat memory impairment in both dementia patients and animal models of neurological diseases. Previously, we have reported the beneficial memory effects of chronic forniceal DBS in mouse models of intellectual disability disorders. In Rett syndrome and CDKL5 deficiency disorder models, DBS strengthens hippocampal synaptic plasticity, reduces dentate inhibitory transmission or increases adult hippocampal neurogenesis that aids memory. However, the underlying neuronal circuitry mechanisms remain unknown. This study we explored the neural network circuits involved in forniceal DBS treatment. Methods: We used acute forniceal DBS-induced expression of c-Fos, an activity-dependent neuronal marker, to map the brain structures functionally connected to the fornix. We also evaluated the mouse behavior of locomotion, anxiety, and fear memory after acute forniceal DBS treatment. Results: Acute forniceal DBS induces robust activation of multiple structures in the limbic system. DBS-induced neuronal activation extends beyond hippocampal formation and includes brain structures not directly innervated by the fornix. Conclusions: Acute forniceal DBS activates multiple limbic structures associated with emotion and memory. The neural circuits revealed here help elucidate the neural network effect and pave the way for further research on the mechanism by which forniceal DBS induces benefits on cognitive impairments. Full article

Background/Objectives: Recent studies have investigated the effects of ketamine on fear memory in animals. However, it is unclear if ketamine might affect avoidance memory and emotional behaviors concomitantly. In this study, we compared the effects of (R,S)- and (S)-ketamine in modulating avoidance responses, depression- and anxiety-related behaviors in stressed mice. Methods: Mice were previously exposed to inescapable footshock stress, and 24 h later, they were trained in the active avoidance task. (R,S)-ketamine or (S)-isomer was administered 1 h prior to re-exposition to the active avoidance task. Three hours after drug administration, mice were tested in the tail suspension, followed by the open field test. Results: Neither form of ketamine affected avoidance memory retrieval, while (S)-ketamine, and tangentially, (R,S) reduced avoidance responses during re-exposition to aversive stimulus. In the tail suspension test, (R,S)- and (S)-ketamine equally evoked antidepressant effects. In the open field test, the racemic mixture, but not (S)-ketamine, induced anxiolytic actions. Conclusions: These findings reinforce the therapeutic potential of ketamine for the treatment of stress-related disorders, with (R,S)-ketamine being more effective in simultaneously inducing antidepressant and anxiolytic responses and reducing avoidance responses in stressed mice. Full article

Presidential elections are an important political event that often trigger intense debate. With more than 139 million users, YouTube serves as a significant platform for understanding public opinion through sentiment analysis. This study aimed to implement deep learning techniques for a multi-label sentiment analysis of comments on YouTube videos related to the 2024 Indonesian presidential election. Offering a fresh perspective compared to previous research that primarily employed traditional classification methods, this study classifies comments into eight emotional labels: anger, anticipation, disgust, joy, fear, sadness, surprise, and trust. By focusing on the emotional spectrum, this study provides a more nuanced understanding of public sentiment towards presidential candidates. The CRISP-DM method is applied, encompassing stages of business understanding, data understanding, data preparation, modeling, evaluation, and deployment, ensuring a systematic and comprehensive approach. This study employs a dataset comprising 32,000 comments, obtained via YouTube Data API, from the KPU and Najwa Shihab channels. The analysis is specifically centered on comments related to presidential candidate debates. Three deep learning models—Convolutional Neural Network (CNN), Bidirectional Long Short-Term Memory (Bi-LSTM), and a hybrid model combining CNN and Bi-LSTM—are assessed using confusion matrix, Area Under the Curve (AUC), and Hamming loss metrics. The evaluation results demonstrate that the Bi-LSTM model achieved the highest accuracy with an AUC value of 0.91 and a Hamming loss of 0.08, indicating an excellent ability to classify sentiment with high precision and a low error rate. This innovative approach to multi-label sentiment analysis in the context of the 2024 Indonesian presidential election expands the insights into public sentiment towards candidates, offering valuable implications for political campaign strategies. Additionally, this research contributes to the fields of natural language processing and data mining by addressing the challenges associated with multi-label sentiment analysis. Full article

Glutamate is the main excitatory neurotransmitter in the brain wherein it controls cognitive functional domains and mood. Indeed, brain areas involved in memory formation and consolidation as well as in fear and emotional processing, such as the hippocampus, prefrontal cortex, and amygdala, are predominantly glutamatergic. To ensure the physiological activity of the brain, glutamatergic transmission is finely tuned at synaptic sites. Disruption of the mechanisms responsible for glutamate homeostasis may result in the accumulation of excessive glutamate levels, which in turn leads to increased calcium levels, mitochondrial abnormalities, oxidative stress, and eventually cell atrophy and death. This condition is known as glutamate-induced excitotoxicity and is considered as a pathogenic mechanism in several diseases of the central nervous system, including neurodevelopmental, substance abuse, and psychiatric disorders. On the other hand, these disorders share neuroplasticity impairments in glutamatergic brain areas, which are accompanied by structural remodeling of glutamatergic neurons. In the current narrative review, we will summarize the role of glutamate-induced excitotoxicity in both the pathophysiology and therapeutic interventions of neurodevelopmental and adult mental diseases with a focus on autism spectrum disorders, substance abuse, and psychiatric disorders. Indeed, glutamatergic drugs are under preclinical and clinical development for the treatment of different mental diseases that share glutamatergic neuroplasticity dysfunctions. Although clinical evidence is still limited and more studies are required, the regulation of glutamate homeostasis is attracting attention as a potential crucial target for the control of brain diseases. Full article

In the so-called West, feminist activists and scholars have long been traumatised by the erasure of their histories via dominant patriarchal narratives, which has served as an impediment to the intergenerational transmission of feminist knowledge. Recently, while acknowledging the very real and ongoing impact of this historical omission, some feminists have issued a call to turn away from a narrative of women’s history as ‘serial forgetting’ and towards an acknowledgement of the affirmative capacity of feminist remembering. At the same time, memory theorist Ann Rigney has advocated for a ‘positive turn’ in memory studies, away from what she perceives to be the field’s gravitation towards trauma and instead towards an analysis of life’s positive legacies. In this article, I combine both approaches to investigate one feminist memory-keeper’s archive, analysing what it reveals about ‘the mechanisms by which positive attachments are transmitted across space and time’. Throughout her life, little-known ‘between-the-waves’ Australian feminist Ruby Rich (1888–1988) performed multiple intersecting activist activities. While she created feminist memories through her work for various political organisations, she also collected, stored and transmitted feminist memories through her campaign for a dedicated space for women’s collections in the National Library of Australia. Propelled by fear of loss and inspired by hope for remembering, Rich constructed a brand of archival activism that was both educational and emotional. In this paper, I examine the strategies Rich employed to try to realise her dream of effecting intellectual and affective bonds between future feminists and their predecessors. Full article

Fear extinction is a phenomenon that involves a gradual reduction in conditioned fear responses through repeated exposure to fear-inducing cues. Functional brain connectivity assessments, such as functional magnetic resonance imaging (fMRI), provide valuable insights into how brain regions communicate during these processes. Stress, a ubiquitous aspect of life, influences fear learning and extinction by changing the activity of the amygdala, prefrontal cortex, and hippocampus, leading to enhanced fear responses and/or impaired extinction. Glucocorticoid receptors (GRs) are key to the stress response and show a dual function in fear regulation: while they enhance the consolidation of fear memories, they also facilitate extinction. Accordingly, GR dysregulation is associated with anxiety and mood disorders. Recent advancements in cognitive neuroscience underscore the need for a comprehensive understanding that integrates perspectives from the molecular, cellular, and systems levels. In particular, neuropharmacology provides valuable insights into neurotransmitter and receptor systems, aiding the investigation of mechanisms underlying fear regulation and potential therapeutic targets. A notable player in this context is cortisol, a key stress hormone, which significantly influences both fear memory reconsolidation and extinction processes. Gaining a thorough understanding of these intricate interactions has implications in terms of addressing psychiatric disorders related to stress. This review sheds light on the complex interactions between cognitive processes, emotions, and their neural bases. In this endeavor, our aim is to reshape the comprehension of fear, stress, and their implications for emotional well-being, ultimately aiding in the development of therapeutic interventions. Full article

Fear is characterized by distinct behavioral and physiological responses that are essential for the survival of the human species. Fear conditioning (FC) serves as a valuable model for studying the acquisition, extinction, and expression of fear. The serotonin (5-hydroxytryptamine, 5-HT) system is known to play a significant role in emotional and motivational aspects of human behavior, including fear learning and expression. Accumulating evidence from both animal and human studies suggests that brain regions involved in FC, such as the amygdala, hippocampus, and prefrontal cortex, possess a high density of 5-HT receptors, implicating the crucial involvement of serotonin in aversive learning. Additionally, studies exploring serotonin gene polymorphisms have indicated their potential influence on FC. Therefore, the objective of this work was to review the existing evidence linking 5-HT with fear learning and memory in humans. Through a comprehensive screening of the PubMed and Web of Science databases, 29 relevant studies were included in the final review. These studies investigated the relationship between serotonin and fear learning using drug manipulations or by studying 5-HT-related gene polymorphisms. The results suggest that elevated levels of 5-HT enhance aversive learning, indicating that the modulation of serotonin 5-HT2A receptors regulates the expression of fear responses in humans. Understanding the role of this neurochemical messenger in associative aversive learning can provide insights into psychiatric disorders such as anxiety and post-traumatic stress disorder (PTSD), among others. Full article

In the billions of faces that are shaped by thousands of different cultures and ethnicities, one thing remains universal: the way emotions are expressed. To take the next step in human–machine interactions, a machine (e.g., a humanoid robot) must be able to clarify facial emotions. Allowing systems to recognize micro-expressions affords the machine a deeper dive into a person’s true feelings, which will take human emotion into account while making optimal decisions. For instance, these machines will be able to detect dangerous situations, alert caregivers to challenges, and provide appropriate responses. Micro-expressions are involuntary and transient facial expressions capable of revealing genuine emotions. We propose a new hybrid neural network (NN) model capable of micro-expression recognition in real-time applications. Several NN models are first compared in this study. Then, a hybrid NN model is created by combining a convolutional neural network (CNN), a recurrent neural network (RNN, e.g., long short-term memory (LSTM)), and a vision transformer. The CNN can extract spatial features (within a neighborhood of an image), whereas the LSTM can summarize temporal features. In addition, a transformer with an attention mechanism can capture sparse spatial relations residing in an image or between frames in a video clip. The inputs of the model are short facial videos, while the outputs are the micro-expressions recognized from the videos. The NN models are trained and tested with publicly available facial micro-expression datasets to recognize different micro-expressions (e.g., happiness, fear, anger, surprise, disgust, sadness). Score fusion and improvement metrics are also presented in our experiments. The results of our proposed models are compared with that of literature-reported methods tested on the same datasets. The proposed hybrid model performs the best, where score fusion can dramatically increase recognition performance. Full article