Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Unlabelled: Artificial Memory Systems (AMSs) are tools that allow for the storage and retrieval of coded information beyond the physical body, ranging from computers and writing systems to tallying sticks. Current scientific knowledge suggests humans are the only species to manufacture and use these tools. While a number of artifacts dating back to the Middle Paleolithic have been considered to be early instances of AMS, conclusive and systematic evidence of this function is absent. Here we contrast the spatial distribution of markings on these potential early AMSs to other Paleolithic artifacts displaying butchery and ornamental marks, as well as ethnographically recorded cases of AMS. We find that both ethnographic and Upper Paleolithic AMSs are endowed with systematically different signatures that distinguish them from the other artifacts. These findings suggest that modern humans in at least Africa and Europe had sophisticated cognitive capabilities for information storage and retrieval, providing insights into the possible development of quantity-related cognition.
Supplementary Information: The online version contains supplementary material available at 10.1007/s12520-025-02286-4.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12287167 | PMC |
| http://dx.doi.org/10.1007/s12520-025-02286-4 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Maximizing theoretical and practical storage capacity in single-layer feedforward neural networks.
Front Comput Neurosci
August 2025
Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, United States.
Artificial neural networks are limited in the number of patterns that they can store and accurately recall, with capacity constraints arising from factors such as network size, architectural structure, pattern sparsity, and pattern dissimilarity. Exceeding these limits leads to recall errors, eventually leading to catastrophic forgetting, which is a major challenge in continual learning. In this study, we characterize the theoretical maximum memory capacity of single-layer feedforward networks as a function of these parameters.
View Article and Find Full Text PDFSmart load balancing in cloud computing: Integrating feature selection with advanced deep learning models.
PLoS One
September 2025
College of Business Administration, Northern Border University (NBU), Arar, Kingdom of Saudi Arabia.
The increasing dependence on cloud computing as a cornerstone of modern technological infrastructures has introduced significant challenges in resource management. Traditional load-balancing techniques often prove inadequate in addressing cloud environments' dynamic and complex nature, resulting in suboptimal resource utilization and heightened operational costs. This paper presents a novel smart load-balancing strategy incorporating advanced techniques to mitigate these limitations.
View Article and Find Full Text PDFCognitive load suppresses explicit learning while sparing implicit learning in visuomotor adaptation.
J Neurophysiol
September 2025
School of Psychological and Cognitive Sciences, Peking University, Beijing, China.
Limiting cognitive resources negatively impacts motor learning, but its cognitive mechanism is still unclear. Previous studies failed to differentiate its effect on explicit (or cognitive) and implicit (or procedural) aspects of motor learning. Here, we designed a dual-task paradigm requiring participants to simultaneously perform a visual working memory task and a visuomotor rotation adaptation task to investigate how cognitive load differentially impacted explicit and implicit motor learning.
View Article and Find Full Text PDFLow Frequency of Dementia with Lewy Bodies Diagnosis in a Colombian Memory Clinic.
Mov Disord Clin Pract
September 2025
Centre for Age-Related Medicine (SESAM), Stavanger University Hospital, Stavanger, Norway.
Background: The global burden of dementia is increasing, particularly in low- and middle-income countries. Dementia with Lewy bodies (DLB) is the second most common neurodegenerative dementia but remains underreported and frequently misdiagnosed. Its prevalence in Latin America is largely unknown.
View Article and Find Full Text PDFEnhanced Giant Ferroelectric Tunneling Electroresistance in 2D Ruddlesden-Popper Oxides.
ACS Nano
September 2025
Key Laboratory of Artificial Micro- and Nano-Structures of Ministry of Education, and School of Physics and Technology, Wuhan University, Wuhan 430072, China.
Ferroelectric tunnel junctions (FTJs) based on ferroelectric switching and quantum tunneling effects with thickness down to a few unit cells have been explored for applications of two-dimensional (2D) electronic devices in data storage and neural networks. As a key performance indicator, the enhanced tunneling electrosistance (TER) ratio provides a broader dynamic range for precise modulation of synaptic weights, improving the stability and accuracy of neural networks. Herein, we report an observation of pronounced enhancement in the TER ratio by over 4 orders of magnitude through the fabrication of large-scale heterostructures combining bismuth ferrite with two-dimensional Ruddlesden-Popper oxide BiFeO.
View Article and Find Full Text PDF