The hippocampus is essential for consolidation of declarative information and spatial navigation. Alzheimer's disease (AD) diagnosis tends to be preceded by a long prodromal period and mild cognitive impairment (MCI). Our goal was to test whether amnestic MCI comprises two different subgroups, with hippocampal and non-hippocampal memory impairment, that vary with respect to spatial navigation ability. A total of 52 patients were classified into two subgroups: non-amnestic MCI (naMCI) (n=10) and amnestic MCI (aMCI) (n=42). The aMCI subgroup was further stratified into memory impairment of hippocampal type-hippocampal aMCI (HaMCI) (n=10) (potential preclinical AD) and isolated retrieval impairment-non-hippocampal (NHaMCI) (n=32). Results were compared to control (n=28) and AD (n=21) groups. We used the Hidden Goal Task, a human analogue of the Morris Water Maze, to examine spatial navigation either dependent (egocentric) or independent of individual's position (allocentric). Overall, the HaMCI group performed poorer on spatial navigation than the NHaMCI group, especially in the latter trials when the HaMCI group exhibited limited capacity to learn and the NHaMCI group exhibited a learning effect. Finally, the HaMCI group performed almost identically as the AD group. Spatial navigation deficit is particularly pronounced in individuals with hippocampus-related memory impairment and may signal preclinical AD.
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http://dx.doi.org/10.1016/j.bbr.2009.03.041 | DOI Listing |
Proc Natl Acad Sci U S A
January 2025
Institute of Behavioural Neuroscience, Department of Experimental Psychology, University College London, London WC1H 0AP, United Kingdom.
Efficient planning is a distinctive hallmark of intelligence in humans, who routinely make rapid inferences over complex world contexts. However, studies investigating how humans accomplish this tend to focus on naive participants engaged in simplistic tasks with small state spaces, which do not reflect the intricacy, ecological validity, and human specialization in real-world planning. In this study, we examine the street-by-street route planning of London taxi drivers navigating across more than 26,000 streets in London (United Kingdom).
View Article and Find Full Text PDFElife
January 2025
Department of Psychology, University of York, North Yorkshire, United Kingdom.
Processing pathways between sensory and default mode network (DMN) regions support recognition, navigation, and memory but their organisation is not well understood. We show that functional subdivisions of visual cortex and DMN sit at opposing ends of parallel streams of information processing that support visually mediated semantic and spatial cognition, providing convergent evidence from univariate and multivariate task responses, intrinsic functional and structural connectivity. Participants learned virtual environments consisting of buildings populated with objects, drawn from either a single semantic category or multiple categories.
View Article and Find Full Text PDFFront Plant Sci
January 2025
Institute of Agricultural Facilities and Equipment, Jiangsu Academy of Agricultural Sciences, Nanjing, Jiangsu, China.
Three-dimensional (3D) LiDAR is crucial for the autonomous navigation of orchard mobile robots, offering comprehensive and accurate environmental perception. However, the increased richness of information provided by 3D LiDAR also leads to a higher computational burden for point cloud data processing, posing challenges to real-time navigation. To address these issues, this paper proposes a 3D point cloud optimization method based on the octree data structure for autonomous navigation of orchard mobile robots.
View Article and Find Full Text PDFJ R Soc Interface
January 2025
School of Computing and Mathematical Sciences, University of Leicester, Leicester, UK.
Achieving a comprehensive understanding of animal intelligence demands an integrative approach that acknowledges the interplay between an organism's brain, body and environment. Insects, despite their limited computational resources, demonstrate remarkable abilities in navigation. Existing computational models often fall short in faithfully replicating the morphology of real insects and their interactions with the environment, hindering validation and practical application in robotics.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Thoracic Surgery, The Second Xiangya Hospital of Central South University, 139 Renmin Road, Changsha, 410011, Hunan, China.
Percutaneous transthoracic puncture of small pulmonary nodules is technically challenging. We developed a novel electromagnetic navigation puncture system for the puncture of sub-centimeter lung nodules by combining multiple deep learning models with electromagnetic and spatial localization technologies. We compared the performance of DL-EMNS and conventional CT-guided methods in percutaneous lung punctures using phantom and animal models.
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