The ability to maintain information for a short period of time (i.e. working memory, WM) tends to decrease across the life span with large inter-individual variability; the underlying neuronal bases, however, remain unclear. To address this issue, we used a multimodal imaging approach (voxel-based morphometry, diffusion-tensor imaging, electroencephalography) to test the contribution of brain structures and neural oscillations in an elderly population. Thirty-one healthy elderly participants performed a change-detection task with different load conditions. As expected, accuracy decreased with increasing WM load, reflected by power modulations in the theta-alpha band (5-12 Hz). Importantly, these power changes were directly related to the tract strength between parahippocampus and parietal cortex. Furthermore, between-subject variance in gray matter volume of the parahippocampus and dorsal striatum predicted WM accuracy. Together, our findings provide new evidence that WM performance critically depends on parahippocampal and striatal integrity, while theta-alpha oscillations may provide a mechanism to bind the nodes within the WM network.
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http://dx.doi.org/10.1038/s41598-018-36793-3 | DOI Listing |
JMIR Form Res
January 2025
Department of Computer Science, University of California, Irvine, Irvine, CA, United States.
Background: Acute pain management is critical in postoperative care, especially in vulnerable patient populations that may be unable to self-report pain levels effectively. Current methods of pain assessment often rely on subjective patient reports or behavioral pain observation tools, which can lead to inconsistencies in pain management. Multimodal pain assessment, integrating physiological and behavioral data, presents an opportunity to create more objective and accurate pain measurement systems.
View Article and Find Full Text PDFJ Exp Psychol Gen
January 2025
Institute for Mind and Biology, University of Chicago.
Individual differences in working memory predict a wide range of cognitive abilities. However, little research has been done on whether working memory continues to predict task performance after repetitive learning. Here, we tested whether working memory ability continued to predict long-term memory (LTM) performance for picture sequences even after participants showed massive learning.
View Article and Find Full Text PDFPLoS Biol
January 2025
Department of Biochemistry and Molecular Biology, Dalhousie University, Halifax, Canada.
The role of epigenetics and chromatin in the maintenance of postmitotic neuronal cell identities is not well understood. Here, we show that the histone methyltransferase Trithorax (Trx) is required in postmitotic memory neurons of the Drosophila mushroom body (MB) to enable their capacity for long-term memory (LTM), but not short-term memory (STM). Using MB-specific RNA-, ChIP-, and ATAC-sequencing, we find that Trx maintains homeostatic expression of several non-canonical MB-enriched transcripts, including the orphan nuclear receptor Hr51, and the metabolic enzyme lactate dehydrogenase (Ldh).
View Article and Find Full Text PDFPLoS One
January 2025
Departamento de Psicología Evolutiva y Comunicación, Campus Universitario de Vigo, University of Vigo, Vigo, Spain.
The main purpose of this study was to examine the age-related changes in inhibitory control of 450 children at the ages of 7-8, 11-12, and 14-16 when controlling for working memory capacity (WMC) and processing speed to determine whether inhibition is an independent factor far beyond its possible reliance on the other two factors. This examination is important for several reasons. First, empirical evidence about age-related changes of inhibitory control is controversial.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Electrical Engineering, College of Engineering, Taif University, Taif, Saudi Arabia.
Modernizing power systems into smart grids has introduced numerous benefits, including enhanced efficiency, reliability, and integration of renewable energy sources. However, this advancement has also increased vulnerability to cyber threats, particularly False Data Injection Attacks (FDIAs). Traditional Intrusion Detection Systems (IDS) often fall short in identifying sophisticated FDIAs due to their reliance on predefined rules and signatures.
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