Language comprehension occurs when the left-hemisphere (LH) and the right-hemisphere (RH) share information derived from discourse [Beeman, M. J., Bowden, E. M., & Gernsbacher, M. A. (2000). Right and left hemisphere cooperation for drawing predictive and coherence inferences during normal story comprehension. Brain and Language, 71, 310-336]. This study investigates the role of knowledge domain across hemispheres, hypothesizing that the RH demonstrates inference processes for planning knowledge while the LH demonstrates inference processes for knowledge of physical cause and effect. In experiment 1, sixty-eight participants completed divided-visual-field reading tasks with 2-sentence stimuli that relied on these knowledge areas. Results showed that readers made more planning inferences from the RH and more physical inferences from the LH, indicating inference processes occur from each hemisphere dependent upon the knowledge domain required to support it. In experiment 2, sixty-four participants completed the same reading task with longer, story-length stimuli to demonstrate the effect in a more realistic setting. Experiment 2 results replicated the findings from experiment 1, extending previous findings, specifying that hemispheric differences for inferences rely on knowledge domains.
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http://dx.doi.org/10.1016/j.neuropsychologia.2008.03.023 | DOI Listing |
Trends Cogn Sci
January 2025
Department of Psychology, Biological Psychology, University of Cologne, Cologne, Germany. Electronic address:
Multi-line electronic gambling machines (EGMs) are strongly associated with problem gambling. Dopamine (DA) plays a central role in substance-use disorders, which share clinical and behavioral features with disordered gambling. The structural design features of multi-line EGMs likely lead to the elicitation of various dopaminergic effects within their nested anticipation-outcome structure.
View Article and Find Full Text PDFVet Res Forum
December 2024
Department of Theriogenology, Faculty of Veterinary Medicine, Urmia University, Urmia, Iran.
The cooling procedure markedly diminishes the quality of guinea pig () sperms, primarily because their membranes are highly susceptible to this process. This susceptibility triggers the generation of reactive oxygen species and free radicals, ultimately leading to lipid peroxidation in the sperm membrane. Surprisingly, there has been a lack of research on the use of Tris-based extenders to safeguard guinea pig sperm under refrigeration conditions.
View Article and Find Full Text PDFCogn Neurodyn
December 2025
Department of Electronics and Communication Engineering, Karpagam College of Engineering, Coimbatore, Tamil Nadu 641032 India.
Cross subject Electroencephalogram (EEG) emotion recognition refers to the process of utilizing electroencephalogram signals to recognize and classify emotions across different individuals. It tracks neural electrical patterns, and by analyzing these signals, it's possible to infer a person's emotional state. The objective of cross-subject recognition is to create models or algorithms that can reliably detect emotions in both the same person and several other people.
View Article and Find Full Text PDFCogn Neurodyn
December 2025
School of Mechatronical Engineering, Beijing Institute of Technology, No. 5 Zhongguancun South Street, Haidian District, Beijing, 100081 China.
Enhancing the accuracy of emotion recognition models through multimodal learning is a common approach. However, challenges such as insufficient modal feature learning in multimodal inference and scarcity of sample data continue to pose obstacles that need to be overcome. Therefore, we propose a novel adaptive lightweight multimodal efficient feature inference network (ALME-FIN).
View Article and Find Full Text PDFPhilos Trans A Math Phys Eng Sci
January 2025
Microsystems Group, School of Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.
The increasing demand for processing large volumes of data for machine learning (ML) models has pushed data bandwidth requirements beyond the capability of traditional von Neumann architecture. In-memory computing (IMC) has recently emerged as a promising solution to address this gap by enabling distributed data storage and processing at the micro-architectural level, significantly reducing both latency and energy. In this article, we present In-Memory comPuting architecture based on Y-FlAsh technology for Coalesced Tsetlin machine inference (IMPACT), underpinned on a cutting-edge memory device, Y-Flash, fabricated on a 180 nm complementary metal oxide semiconductor (CMOS) process.
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