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Auditory verbal hallucinations (AVHs)-or hearing voices-occur in clinical and non-clinical populations, but their mechanisms remain unclear. Predictive processing models of psychosis have proposed that hallucinations arise from an over-weighting of prior expectations in perception. It is unknown, however, whether this reflects (i) a sensitivity to explicit modulation of prior knowledge or (ii) a pre-existing tendency to spontaneously use such knowledge in ambiguous contexts. Four experiments were conducted to examine this question in healthy participants listening to ambiguous speech stimuli. In experiments 1a ( = 60) and 1b ( = 60), participants discriminated intelligible and unintelligible sine-wave speech before and after exposure to the original language templates (i.e. a modulation of expectation). No relationship was observed between top-down modulation and two common measures of hallucination-proneness. Experiment 2 ( = 99) confirmed this pattern with a different stimulus-sine-vocoded speech (SVS)-that was designed to minimize ceiling effects in discrimination and more closely model previous top-down effects reported in psychosis. In Experiment 3 ( = 134), participants were exposed to SVS without prior knowledge that it contained speech (i.e. naïve listening). AVH-proneness significantly predicted both pre-exposure identification of speech and successful recall for words hidden in SVS, indicating that participants could actually decode the hidden signal spontaneously. Altogether, these findings support a pre-existing tendency to spontaneously draw upon prior knowledge in healthy people prone to AVH, rather than a sensitivity to temporary modulations of expectation. We propose a model of clinical and non-clinical hallucinations, across auditory and visual modalities, with testable predictions for future research.
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http://dx.doi.org/10.1093/nc/niac002 | DOI Listing |
Sci Robot
September 2025
College of Computer Science and Technology, Zhejiang University, Hangzhou, China.
According to productive failure (PF) theory, experiencing failure during problem-solving can enhance students' knowledge acquisition in subsequent instruction. However, challenging students with problems beyond their current capabilities may strain their skills, prior knowledge, and emotional well-being. To address this, we designed a social robot-assisted teaching activity in which students observed a robot's unsuccessful problem-solving attempts, offering a PF-like preparatory effect without requiring direct failure.
View Article and Find Full Text PDFAdv Physiol Educ
September 2025
Division of Epidemiology and Biostatistics, St. John's Medical College, Bangalore, Karnataka, India.
The amphibian dissection for medical students was halted by the restrictions imposed by the National regulatory guidelines, prompting medical curricula to revise and innovate instructional methods. Hence there is a critical need for potential innovative solutions to enhance students' understanding of physiological concepts. Therefore, this study aimed (a) to evaluate the gain in knowledge and retention with computer assisted simulation (CAS) vs traditional (TT) teaching learning strategies in first year medical and paramedical students, and (b) to obtain students' and faculty feedback about strengths and limitations of both strategies.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
September 2025
The tumor microenvironment is a dynamic eco system where cellular interactions drive cancer progression. However, inferring cell-cell communication from non-spatial scRNA-seq data remains challenging due to incomplete li gand-receptor databases and noisy cell type annotations. H ere, we propose scGraphDap, a graph neural network frame work that integrates functional state pseudo-labels and graph structure learning to improve both cell type annotation an d CCC inference.
View Article and Find Full Text PDFIEEE J Biomed Health Inform
September 2025
In recent years, deep learning on protein structures has attracted widespread attention, as structures determine proteins' function. A series of structure-based protein property prediction methods have been proposed, achieving remarkable performance. However, these methods often neglect the importance of the protein size and fail to fully leverage it, leading to biases toward certain sizes and suboptimal overall performance.
View Article and Find Full Text PDFMemory
September 2025
The Psychology Research Institute (INPSY), Masaryk University, Brno, Czech Republic.
This study explores the relationship between cultural life scripts and actual life stories of Czechs and Slovaks, building on prior research by Štěpánková et al. (2020. Czech and Slovak life scripts: The rare case of two countries that used to be one.
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