Temporal context models (TCMs) have been influential in understanding episodic memory and its neural underpinnings. Recently, TCMs have been extended to explain emotional memory effects, one of the most clinically important findings in the field of memory research. This review covers recent advances in hypotheses for the neural representation of spatiotemporal context through the lens of TCMs, including their ability to explain the influence of emotion on episodic and temporal memory. In recent years, simplifying assumptions of "classical" TCMs - with exponential trace decay and the mechanism by which temporal context is recovered - have become increasingly clear. The review also outlines how recent advances could be incorporated into a future TCM, beyond classical assumptions, to integrate emotional modulation.
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http://dx.doi.org/10.1080/02699931.2024.2371075 | DOI Listing |
Hum Brain Mapp
December 2024
Research Group Cognition and Plasticity, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
The ability to integrate semantic information into the context of a sentence is essential for human communication. Several studies have shown that the predictability of a final keyword based on the sentence context influences semantic integration on the behavioral, neurophysiological, and neural level. However, the architecture of the underlying network interactions for semantic integration across the lifespan remains unclear.
View Article and Find Full Text PDFAddict Behav Rep
June 2025
Department of Psychiatry and Behavioural Neurosciences, McMaster University, 100 West 5th St., Hamilton, ON L8N 3K7, Canada.
Background: The substance use crisis continues to progress. Medication for Opioid Use Disorder (MOUD) are prescribed to reduce opioid use and related harms; however, many individuals continue to use substances while on treatment. The objective of this study was to describe the temporal and demographic trends of the agreement between self-reported and urine tested substances.
View Article and Find Full Text PDFJ Morphol
January 2025
Macroevolution Unit, Okinawa Institute of Science of Technology, Onna-son, Okinawa, Japan.
Dental impressions, developed for accurate capture of oral characteristics in human clinical settings, are seldom used in research on nonlivestock, nonprimate, and especially nonmammalian vertebrates due to a lack of appropriate tools. Studies of dentitions in most vertebrate species usually require euthanasia and specimen dissection, microCT and other scans with size and resolution tradeoffs, and/or ad-hoc individual impressions or removal of single teeth. These approaches prevent in-vivo studies that factor in growth and other chronological changes and separate teeth from the context of the whole mouth.
View Article and Find Full Text PDFInfect Dis Poverty
December 2024
Ecosystem Change and Population Health Research Group, Centre for Immunology and Infection Control, School of Public Health and Social Work, Queensland University of Technology, Kelvin Grove, Brisbane, QLD, 4059, Australia.
Background: Rapid human movement plays a crucial role in the spatial dissemination of the dengue virus. Nevertheless, robust quantification of this relationship using both spatial and temporal models remains necessary. This study aims to explore the spatial and temporal patterns of dengue transmission under various human movement contexts.
View Article and Find Full Text PDFJ Environ Manage
December 2024
Department of Economics and Management Science, Xinhua College of Ningxia University, Yinchuan, 750021, China; Graduate School of Business, Universiti Sains Malaysia, George Town, 11800, Malaysia. Electronic address:
Global warming caused by carbon emissions has become a significant concern for countries worldwide. This study thoroughly examines the spatiotemporal patterns and spatial spillover effects of carbon emissions in China. This research employs kernel density estimation, Moran's index, and the standard deviation ellipse model to analyse the spatiotemporal evolution of carbon emissions in China while utilizing the spatial Durbin model to explore the spatial spillover effects of the digital economy on carbon emissions.
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