Although visuospatial short-term memory tasks have been found to engage more executive resources than do their phonological counterparts, it remains unclear whether this is due to intrinsic differences between the tasks or differences in participants' experience with them. The authors found 11-year-olds' performances on both visual short-term and working memory tasks to be more greatly impaired by an executive suppression task (random number generation) than were those of 8-year-olds. Similar findings with adults (e.g., Kane & Engle, 2000) suggest that the imposition of a suppression task may have overloaded the older children's executive resources, which would otherwise be used for deploying strategies for performing the primary tasks. Conversely, the younger children, who probably never had the capacity or know-how to engage these facilitative strategies in the first place, performed more poorly in the single task condition but were less affected in the dual task condition. These findings suggest that differences in the children's ability to deploy task-relevant strategy are likely to account for at least part of the executive resource requirements of visual memory tasks.
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http://dx.doi.org/10.1037/a0017554 | DOI Listing |
Biosci Trends
January 2025
Department of Rehabilitation, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Cognitive impairment refers to the impairment of higher brain functions such as perception, thinking or memory that affects the individual's ability to perform daily or social activities. Studies have found that changes in neuronal activity during tasks in patients with cognitive impairment are closely related to changes in cerebral cortical hemodynamics. Functional near-infrared spectroscopy is an indirect method to measure neural activity based on changes in blood oxygen concentration in the cerebral cortex.
View Article and Find Full Text PDFFront Biosci (Landmark Ed)
January 2025
Department of Zoology, College of Science, King Saud University, 11451 Riyadh, Saudi Arabia.
Background: We investigated chitosan's protective effects against tertiary butylhydroquinone (TBHQ)-induced toxicity in adult male rats, focusing on cognitive functions and oxidative stress in the brain, liver, and kidneys.
Methods: Rats were divided into four groups (n = 8/group): (1) Control, (2) Chitosan only, (3) TBHQ only, and (4) Chitosan + TBHQ.
Results: TBHQ exposure led to significant cognitive impairments and increased oxidative stress, marked by elevated malondialdehyde (MDA) and decreased superoxide dismutase (SOD) and glutathione (GSH) levels.
J Integr Neurosci
January 2025
Sports, Exercise and Brain Sciences Laboratory, Sports Coaching College, Beijing Sport University, 100084 Beijing, China.
Background: Sports fatigue in soccer athletes has been shown to decrease neural activity, impairing cognitive function and negatively affecting motor performance. Transcranial direct current stimulation (tDCS) can alter cortical excitability, augment synaptic plasticity, and enhance cognitive function. However, its potential to ameliorate cognitive impairment during sports fatigue remains largely unexplored.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Graduate School of National Science and Technology, Kanazawa University, Kanazawa 920-1192, Japan.
The development of deep learning has led to the proposal of various models for human activity recognition (HAR). Convolutional neural networks (CNNs), initially proposed for computer vision tasks, are examples of models applied to sensor data. Recently, high-performing models based on Transformers and multi-layer perceptrons (MLPs) have also been proposed.
View Article and Find Full Text PDFMicromachines (Basel)
December 2024
Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China.
Reconfigurable processor-based acceleration of deep convolutional neural network (DCNN) algorithms has emerged as a widely adopted technique, with particular attention on sparse neural network acceleration as an active research area. However, many computing devices that claim high computational power still struggle to execute neural network algorithms with optimal efficiency, low latency, and minimal power consumption. Consequently, there remains significant potential for further exploration into improving the efficiency, latency, and power consumption of neural network accelerators across diverse computational scenarios.
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