The purpose of the present study is to compare the effect of aging on direct and indirect measures of temporal order memory, derived from the Rey Auditory Verbal Learning Test (AVLT). The spontaneous order in which the list was recalled in Trial 5 served as the indirect measure, and the explicit reordering of the words into their original order of presentation (i.e., Trial 10) served as the direct measure. Based on previously reported norms (n = 528) on the Rey AVLT, the effects of age (20-91 years) on the two measures of temporal order were analyzed. The results demonstrated that the direct measure was much more sensitive to the effect of age than the indirect measure. Furthermore, the direct measure was more significantly correlated with other verbal memory measures derived from the Rey AVLT. These results are consistent with studies that have documented that the frontal lobes, implicated in temporal memory, show the most significant degenerative changes over the years. As a result, the effortful and direct cognitive tasks in general and particularly in memory are more vulnerable to the effects of aging. These results lend further support to the dissociation between direct and indirect measures of memory in older adults. These temporal order measures, which are not usually assessed in standard batteries, could now be derived from a standard, frequently used test (i.e., Rey AVLT) and increase its diagnostic value.
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http://dx.doi.org/10.1080/13803395.2011.625352 | DOI Listing |
Ophthalmic Physiol Opt
January 2025
Northeastern University College of Science, Boston, Massachusetts, USA.
Purpose: To assess longitudinal changes in optical quality across the periphery (horizontal meridian, 60°) in young children who are at high (HR) or low risk (LR) of developing myopia, as well as a small subgroup of children who developed myopia over a 3-year time frame.
Methods: Aberrations were measured every 6 months in 92 children with functional emmetropia at baseline. Children were classified into HR or LR based on baseline refractive error and parental myopia.
Pflugers Arch
January 2025
Division of Neurophysiology, Department of Physiology, Hyogo Medical University, Hyogo, 663 8501, Japan.
The nucleus tractus solitarius (NTS) contains neurons that relay sensory swallowing commands information from the oropharyngeal cavity and swallowing premotor neurons of the dorsal swallowing group (DSG). However, the spatio-temporal dynamics of the interplay between the sensory relay and the DSG is not well understood. Here, we employed fluorescence imaging after microinjection of the calcium indicator into the NTS in an arterially perfused brainstem preparation of rat (n = 8) to investigate neuronal population activity in the NTS in response to superior laryngeal nerve (SLN) stimulation.
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January 2025
Department of Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 2N2, Canada.
Goal: Current methodologies for assessing cerebral compliance using pressure sensor technologies are prone to errors and issues with inter- and intra-observer consistency. RAP, a metric for measuring intracranial compensatory reserve (and therefore compliance), holds promise. It is derived using the moving correlation between intracranial pressure (ICP) and the pulse amplitude of ICP (AMP).
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January 2025
Department of Electrical Engineering, Faculty of Engineering, Universitas Indonesia, Depok 16424, Indonesia.
The Internet of Things (IoT) has emerged as a crucial element in everyday life. The IoT environment is currently facing significant security concerns due to the numerous problems related to its architecture and supporting technology. In order to guarantee the complete security of the IoT, it is important to deal with these challenges.
View Article and Find Full Text PDFSensors (Basel)
January 2025
College of Geology Engineering and Geomatics, Chang'an University, Xi'an 710054, China.
Precipitable water vapor (PWV) is an important indicator to characterize the spatial and temporal variability of water vapor. A high spatial and temporal resolution of atmospheric precipitable water can be obtained using ground-based GNSS, but its inversion accuracy is usually limited by the weighted mean temperature, Tm. For this reason, based on the data of 17 ground-based GNSS stations and water vapor reanalysis products over 2 years in the Hong Kong region, a new model for water vapor inversion without the Tm parameter is established by deep learning in this paper, the research results showed that, compared with the PWV information calculated by the traditional model using Tm parameter, the accuracy of the PWV retrieved by the new model proposed in this paper is higher, and its accuracy index parameters BIAS, MAE, and RMSE are improved by 38% on average.
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