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Psychotic disorders as well as psychosis proneness in the general population have been associated with perceptual instability, suggesting weakened predictive processing. Sleep disturbances play a prominent role in psychosis and schizophrenia, but it is unclear whether perceptual stability diminishes with sleep deprivation, and whether the effects of sleep deprivation differ as a function of psychosis proneness. In the current study, we aimed to clarify this matter. In this preregistered study, 146 participants successfully completed an intermittent version of the random dot kinematogram (RDK) task and the 21-item Peters Delusion Inventory (PDI-21) to assess perceptual stability and psychosis proneness, respectively. Participants were randomized to sleep either as normal (8 to 9 h in bed) ( = 72; = 24.7, = 6.2, 41 women) or to stay awake through the night ( = 74; = 24.8, = 5.1, 44 women). Sleep deprivation resulted in diminished perceptual stability, as well as in decreases in perceptual stability over the course of the task. However, we did not observe any association between perceptual stability and PDI-21 scores, nor a tendency for individuals with higher PDI-21 scores to be more vulnerable to sleep-deprivation-induced decreases in perceptual stability. The present study suggests a compromised predictive processing system in the brain after sleep deprivation, but variation in psychosis trait is not related to greater vulnerability to sleep deprivation in our dataset. Further studies in risk groups and patients with psychosis are needed to evaluate whether sleep loss plays a role in the occurrence of objectively measured perceptual-related clinical symptoms.
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http://dx.doi.org/10.3390/brainsci12101338 | DOI Listing |
Curr Biol
August 2025
Department of Cognitive, Linguistic, and Psychological Sciences, Brown University, 190 Thayer Street, Providence, RI 02912, USA.
Across various types of learning and memory, when a new training session follows a previous one after a certain temporal interval, the previously acquired learning can be disrupted-an effect known as retrograde interference (RI) or catastrophic forgetting. This disruption is thought to result from disrupting interactions between the learning of the first-trained task and the learning of the second-trained task while the former has not yet stabilized. Such destructive interactions have been considered characteristic not only of RI but also of related phenomena.
View Article and Find Full Text PDFCognition
August 2025
School of Psychological Sciences, Birkbeck, University of London, United Kingdom. Electronic address:
To perceive speech listeners must decide how to prioritize information from multiple acoustic dimensions. Over the course of language learning, individuals form stable perceptual strategies which reflect the strength of the statistical relationship between values along particular acoustic dimensions and linguistic categories. Despite this underlying stability, listeners will change their strategies in response to evidence about shifts in the reliability of acoustic dimensions as cues to categorization.
View Article and Find Full Text PDFNPJ Parkinsons Dis
August 2025
School of Mathematical Sciences, the Clinical Hospital of Chengdu Brain Science Institute, University of Electronic Science and Technology of China, Chengdu, PR China.
Parkinson's disease (PD) is the second most common neurodegenerative disease with progressive structural alterations throughout the brain, resulting in motor symptoms that seriously affect patients' daily life. The present study then aimed to explore the progressive co-changes in gray matter patterns in PD and identify the longitudinal neuroimaging biomarkers that could predict the progressive motor symptoms of PD. Non-negative Matrix Factorization (NMF) was first used to decompose gray matter images into 7 latent factors from healthy samples, and then the latent factors were validated on an independent dataset to verify the stability of the structural factors.
View Article and Find Full Text PDFBull Math Biol
August 2025
Applied Mathematical Sciences, Korea University, 2511, Sejong-Ro, 30019, Sejong, Republic of Korea.
This study examines a competition model featuring nonuniform dispersal, referred to as starvation-driven-type diffusion (SDTD). This model incorporates the motility of species that adhere to a starvation-driven diffusion (SDTD). paradigm while also factoring in perceptual constraints within a spatially heterogeneous region.
View Article and Find Full Text PDFFront Syst Neurosci
July 2025
Departments of Mathematics and Statistics, Psychological and Brain Sciences, and Biomedical Engineering, Boston University, Boston, MA, United States.
This article describes a biological neural network model that explains how humans learn to understand large language models and their meanings. This kind of learning typically occurs when a student learns from a teacher about events that they experience together. Multiple types of self-organizing brain processes are involved, including content-addressable memory; conscious visual perception; joint attention; object learning, categorization, and cognition; conscious recognition; cognitive working memory; cognitive planning; neural-symbolic computing; emotion; cognitive-emotional interactions and reinforcement learning; volition; and goal-oriented actions.
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