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The hippocampus is a key region for forming mental maps of our environment. These maps represent spatial information such as distances between landmarks. A cognitive map can allow for flexible inference of spatial relationships that have never been directly experienced before. Previous work has shown that the human hippocampus encodes distances between locations, but it is unclear how Euclidean and path distances are distinguished. In this study, participants performed an object-location task in a virtual environment. We combined functional magnetic resonance imaging with representational similarity analysis to test how Euclidean and path distances are represented in the hippocampus. We observe that hippocampal neural pattern similarity for objects scales with distance between object locations, and suggest that the hippocampus integrates Euclidean and path distances. One key characteristic of cognitive maps is their adaptive and flexible nature. We therefore subsequently modified path distances between objects using roadblocks in the environment. We found that hippocampal pattern similarity between objects adapted as a function of these changes in path distance, selectively in route learners but not in map learners. Taken together, our study supports the idea that the hippocampus creates integrative and flexible cognitive maps.
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http://dx.doi.org/10.1038/s41598-025-90504-3 | DOI Listing |
ISA Trans
September 2025
School of Mechatronic Engineering, Jiangsu Normal University, Xuzhou 221116, China. Electronic address:
Multi-arm rock drilling robots frequently encounter challenges in extreme environments, such as tunnels, where they are subjected to high-frequency impact loads, multi-degree-of-freedom motion coupling, and large-range motion control vibrations. First, we propose a collision-free path planning method that combines an improved genetic algorithm (IGA) and an improved artificial potential field method. This method is based on the kinematic model of the rock drilling robot.
View Article and Find Full Text PDFJ Chem Phys
September 2025
Department of Applied Chemistry, University of Seoul, Seoul 02504, Republic of Korea.
Nonequilibrium thermodynamics plays a crucial role in understanding a wide range of physical and chemical processes. While significant advances have been made through frameworks, such as the fluctuation theorem, it remains challenging to define thermodynamic quantities, such as energy, entropy, and free energy, at the local level during nonequilibrium processes. Recently, Jinwoo and Tanaka [Sci.
View Article and Find Full Text PDFAlzheimers Dement
September 2025
Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Introduction: In observational studies of preclinical AD, an arbitrary "baseline" can obscure where an individual is located along a theoretical continuum. Optimizing longitudinal trajectories can distill multiple, non-linearly distributed observations into a single metric and inform where an individual may be along the disease course.
Methods: We developed a cognitive time (c-time) metric based on longitudinal cognitive data (mean = 7.
Neuro Oncol
August 2025
Department of Oncology, Cross Cancer Institute, University of Alberta.
Background: Glioblastoma (GBM) is a deadly brain cancer with a dismal prognosis. There is evidence that infiltration and therapy resistance in GBM are driven by tumor microtubes (TMs), ultra-long membrane-enclosed protrusions that serve as intercellular communication channels. The aims of this study were to investigate the role of TMs and identify the molecular drivers involved in TM formation.
View Article and Find Full Text PDFIEEE Trans Image Process
January 2025
CNNs have demonstrated superior performance in medical image segmentation. To overcome the limitation of only using local receptive field, previous work has attempted to integrate Transformers into convolutional network components such as encoders, decoders, or skip connections. However, these methods can only establish long-distance dependencies for some specific patterns and usually neglect the loss of fine-grained details during downsampling in multi-scale feature extraction.
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