While generally reliable, human memory is susceptible to distortions such as false memories. This study investigates the relationships among the emotional valence of events, mood states, and the formation of false autobiographical memories, applying the blind implantation method. We examine the impact of positive and negative moods, combined with the emotional valence of events (negative vs. positive), on false belief and recollection ratings. We conducted two preliminary studies to develop an online mood induction and select critical and noncritical autobiographical events. In the main experiment, 715 adults completed a list of 20 autobiographical events. The participants who had not experienced certain critical events were invited to a second phase, resulting in a final sample of 242 participants (130 female, 108 male, and four others), aged 19-81 years (M = 40.35, SD = 12.64). After experiencing the mood induction, they were presented with a survey suggesting that they had previously reported experiencing a critical event. False beliefs and memories were implanted in 6% (n = 15) to 34% (n = 83) of the cases. While mood did not affect false belief and recollection ratings, negative events led to greater false belief and recollection than positive events did, aligning with the associative activation model and fuzzy-trace theory. These findings highlight the need for caution in settings (e.g., therapy), where possible suggestive techniques could inadvertently implant false traumatic memories.
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http://dx.doi.org/10.3758/s13421-025-01697-x | DOI Listing |
Schizophr Bull Open
January 2025
Neuropsychology and Applied Cognitive Neuroscience Laboratory, CAS Key Laboratory of Mental Health, Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China.
Background And Hypothesis: Affective forecasting (AF), the ability to forecast emotional responses for future events, is critical for optimal decision-making and mental health. Most previous AF studies were conducted using laboratory-based tasks but overlooked the impacts of real-life situations and social interactions. This study used the experience sampling method to examine real-life AF in young healthy adults and individuals with high social anhedonia.
View Article and Find Full Text PDFFront Physiol
February 2025
College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
Objective: This study aims to employ physiological model simulation to systematically analyze the frequency-domain components of PPG signals and extract their key features. The efficacy of these frequency-domain features in effectively distinguishing emotional states will also be investigated.
Methods: A dual windkessel model was employed to analyze PPG signal frequency components and extract distinctive features.
Clin Rehabil
March 2025
Hearing Sciences (Scottish Section), Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Glasgow, UK.
ObjectiveTo address the extent to which the emotional experience of everyday listening situations is impacted by hearing loss and hearing aid use.DesignAn exploratory prospective study with an observation arm and an intervention arm utilising smartphone-based ecological momentary assessment over 10 days. A hearing loss group was asked to wear and not wear their hearing aids on alternate days.
View Article and Find Full Text PDFSci Rep
March 2025
Key Laboratory of Cognition and Personality (SWU), Ministry of Education, Chongqing, 400715, China.
Anxiety is an interactive disorder of the mind and body, characterized by excessive worry about uncertain future events and a dysfunction of the autonomic nervous system. Previous studies have shown that slow, deep breathing can reduce physical tension, and anxiety. Although we know that slow and deep breathing techniques can effectively regulate anxiety and other emotions, the psychological and neurophysiological mechanisms of slow breathing on anxiety have not been systematically explored.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
March 2025
Steady state visually evoked potential (SSVEP)-based brain-computer interfaces (BCIs), which are widely used in rehabilitation and disability assistance, can benefit from real-time emotion recognition to enhance human-machine interaction. However, the learned discriminative latent representations in SSVEP-BCIs may generalize in an unintended direction, which can lead to reduced accuracy in detecting emotional states. In this paper, we introduce a Valence-Arousal Disentangled Representation Learning (VADL) method, drawing inspiration from the classical two-dimensional emotional model, to enhance the performance and generalization of emotion recognition within SSVEP-BCIs.
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