We report the acquisition and recall of novel facts by Jon, a young adult with early onset developmental amnesia whose episodic memory is gravely impaired due to selective bilateral hippocampal damage. Jon succeeded in learning some novel facts but compared with a control group his intertrial retention was impaired during acquisition and, except for the most frequently repeated facts, he was also less accurate in correctly sourcing these facts to the experiment. The results further support the hypothesis that despite a severely compromised episodic memory and hippocampal system, there is nevertheless the capacity to accrue semantic knowledge available to recall.
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http://dx.doi.org/10.1016/j.neuropsychologia.2008.05.021 | DOI Listing |
Can J Exp Psychol
January 2025
Department of Psychology, University of Western Ontario.
Episodic future thinking is the ability to project the self forward in time to preexperience a potential future event. It has been hypothesized that two components enhance simulations of future events: personal likelihood and event familiarity. Personal likelihood varies depending on the dynamics of personal goals throughout an individual's lifetime.
View Article and Find Full Text PDFJ Biomed Inform
January 2025
Harvard Medical School, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA; Harvard T.H. Chan School of Public Health, Boston, MA, USA. Electronic address:
Motivation: The increasing availability of electronic health record (EHR) systems has created enormous potential for translational research. Recent developments in representation learning techniques have led to effective large-scale representations of EHR concepts along with knowledge graphs that empower downstream EHR studies. However, most existing methods require training with patient-level data, limiting their abilities to expand the training with multi-institutional EHR data.
View Article and Find Full Text PDFNeural Netw
December 2024
Department of Mechanical Engineering, National University of Singapore, 9 Engineering Drive 1, Singapore 117575, Singapore. Electronic address:
Manual annotation of ultrasound images relies on expert knowledge and requires significant time and financial resources. Semi-supervised learning (SSL) exploits large amounts of unlabeled data to improve model performance under limited labeled data. However, it faces two challenges: fusion of contextual information at multiple scales and bias of spatial information between multiple objects.
View Article and Find Full Text PDFBehav Res Methods
January 2025
Department of Psychology, Sapienza, University of Rome, Rome, Italy.
The complex interplay between low- and high-level mechanisms governing our visual system can only be fully understood within ecologically valid naturalistic contexts. For this reason, in recent years, substantial efforts have been devoted to equipping the scientific community with datasets of realistic images normed on semantic or spatial features. Here, we introduce VISIONS, an extensive database of 1136 naturalistic scenes normed on a wide range of perceptual and conceptual norms by 185 English speakers across three levels of granularity: isolated object, whole scene, and object-in-scene.
View Article and Find Full Text PDFSci Rep
January 2025
Robotics Group, Department of Mechanic Engineering, Computer and Aerospace Sciences, University of León, 24006, León, Spain.
Symbolic anchoring is an important topic in robotics, as it enables robots to obtain symbolic knowledge from the perceptual information acquired through their sensors and maintain the link between that knowledge and the sensory data. In cognitive-based robots, this process of transforming sub-symbolic data generated by sensors to obtain and maintain symbolic knowledge is still an open problem. To address this issue, this paper presents SAILOR, a framework for symbolic anchoring integrated into ROS 2.
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