Source memory is considered to be the cornerstone of episodic memory that enables us to discriminate similar but different events. In the present fMRI study, we investigated whether neural correlates of source retrieval differed by stimulus content in the medial temporal lobe (MTL) when the item and context had been integrated as a perceptually unitized entity. Participants were presented with a list of items either in verbal or pictorial form overlaid on a colored square and instructed to integrate both the item and context into a single image. At test, participants judged the study status of test items and the color in which studied items were presented. Source recognition invariant of stimulus content elicited retrieval activity in both the left anterior hippocampus extending to the perirhinal cortex and the right posterior hippocampus. Word-selective source recognition was related to activity in the left perirhinal cortex, whereas picture-selective source recognition was identified in the left posterior hippocampus. Neural activity sensitive to novelty detection common to both words and pictures was found in the left anterior and right posterior hippocampus. Novelty detection selective to words was associated with the left perirhinal cortex, while activity sensitive to new pictures was identified in the bilateral hippocampus and adjacent MTL cortices, including the parahippocampal, entorhinal, and perirhinal cortices. These findings provide further support for the integral role of the hippocampus both in source recognition and in detection of new stimuli across stimulus content. Additionally, novelty effects in the MTL reveal the integral role of the MTL cortex as the interface for processing new information. Collectively, the present findings demonstrate the importance of the MTL for both previously experienced and novel events.
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http://dx.doi.org/10.1016/j.brainres.2014.01.029 | DOI Listing |
J Insect Sci
January 2025
School of Biological Sciences, University of Aberdeen, King's College, Aberdeen, UK.
Radio frequency identification (RFID) technology and marker recognition algorithms can offer an efficient and non-intrusive means of tracking animal positions. As such, they have become important tools for invertebrate behavioral research. Both approaches require fixing a tag or marker to the study organism, and so it is useful to quantify the effects such procedures have on behavior before proceeding with further research.
View Article and Find Full Text PDFPharmaceutics
January 2025
Department of Pharmaceutical Bioscience, Translational Drug Discovery and Development, Uppsala University, SE-75124 Uppsala, Sweden.
: N-acetyl-galactosamine small interfering RNAs (GalNAc-siRNA) are an emerging class of drugs due to their durable knockdown of disease-related proteins. Direct conjugation of GalNAc onto the siRNA enables targeted uptake into hepatocytes via GalNAc recognition of the Asialoglycoprotein Receptor (ASGPR). With a transient plasma exposure combined with a prolonged liver half-life, GalNAc-siRNA exhibits distinct disposition characteristics.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Architectural Engineering, Dankook University, 152 Jukjeon-ro, Yongin-si 16890, Republic of Korea.
In the construction industry, ensuring the proper installation, retention, and dismantling of temporary structures, such as jack supports, is critical to maintaining safety and project timelines. However, inconsistencies between on-site data and construction documentation remain a significant challenge. To address this, this study proposes an integrated monitoring framework that combines computer vision-based object detection and document recognition techniques.
View Article and Find Full Text PDFMed Biol Eng Comput
January 2025
State Key Laboratory of Power Transmission Equipment Technology, School of Electrical Engineering, Chongqing, University, Chongqing, 400044, People's Republic of China.
Selecting channels for motor imagery (MI)-based brain-computer interface (BCI) systems can not only enhance the portability of the systems, but also improve the decoding performance. Hence, we propose a cross-domain-based channel selection (CDCS) approach, which effectively minimizes the number of EEG channels used while maintaining high accuracy in MI recognition. The EEG source imaging (ESI) technique is employed to map scalp EEG into the cortical source domain.
View Article and Find Full Text PDFSci Rep
January 2025
School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan, 430081, P.R. China.
Foam ceramics are widely used in industrial applications due to their unique properties, including high porosity, lightweight, and high-temperature resistance. However, their complex microstructure presents significant challenges for image analysis. Traditional machine learning methods often fall short in capturing both global feature dependencies and detailed representations.
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