Multiple object tracking (MOT) is generally regarded as a pure attention-consuming task that draws heavily on attention resources. In the present study, we adopted a cross-channel visual-audio dual-task paradigm, i.e., the MOT task combined with the concurrent auditory N-back working memory task, to test whether working memory indeed plays a necessary role in the process of multiple tracking, as well as to further identify the specific types of working memory components involved in this process. Experiments 1a and 1b examined the relationship between the MOT task and nonspatial object working memory (OWM) processing by manipulating the tracking load and working memory load, respectively. Results in both experiments indicated that the concurrent nonspatial OWM task did not have a significant effect on the tracking capacity of the MOT task. In contrast, Experiments 2a and 2b examined the relationship between the MOT task and spatial working memory (SWM) processing by a similar approach. Results in both experiments indicated that the concurrent SWM task significantly impaired the tracking capacity of the MOT task, showing a gradual decrease with increasing SWM load. Overall, our study provides empirical evidence that multiple object tracking does involve working memory, primarily related to spatial working memory rather than nonspatial object working memory, which sheds more light on the mechanisms of multiple object tracking.
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http://dx.doi.org/10.1111/sjop.12901 | DOI Listing |
Sleep
January 2025
UR2NF-Neuropsychology and Functional Neuroimaging Research Unit affiliated at CRCN - Centre for Research in Cognition and Neurosciences and UNI - ULB Neuroscience Institute, Université Libre de Bruxelles (ULB), Brussels, Belgium.
Enhancing the retention of recent memory traces through sleep reactivation is possible via Targeted Memory Reactivation (TMR), involving cueing learned material during post-training sleep. Evidence indicates detectable short-term microstructural changes in the brain within an hour after motor sequence learning, and post-training sleep is believed to contribute to the consolidation of these motor memories, potentially leading to enduring microstructural changes. In this study, we explored how TMR during post-training sleep affects performance gains and delayed microstructural remodeling, using both standard Diffusion Tensor Imaging (DTI) and advanced Neurite Orientation Dispersion & Density Imaging (NODDI).
View Article and Find Full Text PDFJ Gerontol B Psychol Sci Soc Sci
January 2025
Linguistics and English as a Second Language, Faculty of Arts, University of Groningen, Groningen, the Netherlands.
Objectives: The complex life experience of speaking two or more languages has been suggested to preserve cognition in older adulthood. This study aimed to investigate this further by examining the relationship between multilingual experience variables and cognitive functioning in a large cohort of older adults in the diversely multilingual north of the Netherlands.
Method: 11,332 older individuals participating in the Lifelines Cohort Study completed a language experience questionnaire.
Sensors (Basel)
January 2025
Development Adaptation Handicap (DevAH) Research Unit, Université de Lorraine, 54000 Nancy, France.
Analyzing performance in rowing, e.g., analyzing force and power output profiles produced either on ergometer or on boat, is a priority for trainers and athletes.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Key Laboratory of Concrete and Pre-Stressed Concrete Structures of the Ministry of Education, Southeast University, Nanjing 210096, China.
Monitoring existing cracks is a critical component of structural health monitoring in bridges, as temperature fluctuations significantly influence crack development. The study of the Huai'an Bridge indicated that concrete cracks predominantly occur near the central tower, primarily due to temperature variations between the inner and outer surfaces. This research aims to develop a deep learning model utilizing Long Short-Term Memory (LSTM) neural networks to predict crack depth based on the thermal variations experienced by the main tower.
View Article and Find Full Text PDFSensors (Basel)
December 2024
College of Information Science and Engineering, Hunan Normal University, Changsha 410081, China.
Early detection of autism spectrum disorder (ASD) is particularly important given its insidious qualities and the high cost of the diagnostic process. Currently, static functional connectivity studies have achieved significant results in the field of ASD detection. However, with the deepening of clinical research, more and more evidence suggests that dynamic functional connectivity analysis can more comprehensively reveal the complex and variable characteristics of brain networks and their underlying mechanisms, thus providing more solid scientific support for computer-aided diagnosis of ASD.
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