Spatial integration refers to the superimposition of two separate spatial relationships between cues (C1-C2 and C2-C3) by a common linking element (C2). This linkage creates a new spatial relationship between cues that were never paired together (C1-C3). Several authors obtained conflicting results on spatial integration in both humans and animals. Using a dynamic 3D virtual environment, we provide the first clear evidence that humans can integrate two spatial relationships into a new spatial relationship that guides spatial navigation. This research is discussed in light of a spatial version of the temporal coding hypothesis (Savastano and Miller, 1998).
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.beproc.2011.08.013 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
3D CT to 2D X-ray image registration for improved visualization of tibial vessels in endovascular procedures.
Int J Comput Assist Radiol Surg
January 2025
Department of Medical Biophysics, University of Toronto, Toronto, Canada.
Purpose: During endovascular revascularization interventions for peripheral arterial disease, the standard modality of X-ray fluoroscopy (XRF) used for image guidance is limited in visualizing distal segments of infrapopliteal vessels. To enhance visualization of arteries, an image registration technique was developed to align pre-acquired computed tomography (CT) angiography images and to create fusion images highlighting arteries of interest.
Methods: X-ray image metadata capturing the position of the X-ray gantry initializes a multiscale iterative optimization process, which uses a local-variance masked normalized cross-correlation loss to rigidly align a digitally reconstructed radiograph (DRR) of the CT dataset with the target X-ray, using the edges of the fibula and tibia as the basis for alignment.
Integrating ecological and recreational functions to optimize ecological security pattern in Fuzhou City.
Sci Rep
January 2025
College of Landscape Architecture and Art, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
The scientific establishment of the Ecological Security Pattern (ESP) is crucial for fostering the synergistic development of ecological and recreational functions, thereby enhancing urban ecological protection, recreational development, and sustainable growth. This study aimed to propose a novel method of constructing ESP considering both ecological and recreational functions, and to reconstruct ESP by weighing the relationship between ecological protection and recreational development. Utilizing Fuzhou City as a case study, a comprehensive application of methodologies including Morphological Spatial Pattern Analysis (MSPA), landscape connectivity analysis, ArcGIS spatial analysis, social network analysis (SNA), and circuit theory is employed to develop both the ESP and the Recreational Spatial Pattern (RSP).
View Article and Find Full Text PDFLeveraging U-Net and selective feature extraction for land cover classification using remote sensing imagery.
Sci Rep
January 2025
Computer Vision Center, Universitat Autònoma de Barcelona, Barcelona, 08193, Spain.
In this study, we explore an enhancement to the U-Net architecture by integrating SK-ResNeXt as the encoder for Land Cover Classification (LCC) tasks using Multispectral Imaging (MSI). SK-ResNeXt introduces cardinality and adaptive kernel sizes, allowing U-Net to better capture multi-scale features and adjust more effectively to variations in spatial resolution, thereby enhancing the model's ability to segment complex land cover types. We evaluate this approach using the Five-Billion-Pixels dataset, composed of 150 large-scale RGB-NIR images and over 5 billion labeled pixels across 24 categories.
View Article and Find Full Text PDFInferring Multi-slice Spatially Resolved Gene Expression from H&E-stained Histology Images with STMCL.
Methods
January 2025
School of Information Science and Engineering, Yunnan University, Kunming, 650500, Yunnan, China. Electronic address:
Spatial transcriptomics has significantly advanced the measurement of spatial gene expression in the field of biology. However, the high cost of ST limits its application in large-scale studies. Using deep learning to predict spatial gene expression from H&E-stained histology images offers a more cost-effective alternative, but existing methods fail to fully leverage the multimodal information provided by Spatial transcriptomics and pathology images.
View Article and Find Full Text PDFNumber of subfields of the rat dorsal subiculum defined by the NOS and PCP4 immunoreactivities changes according to the different levels of observation.
Neuroscience
January 2025
Department of Molecular Anatomy, School of Medicine University of the Ryukyus, Uehara, 207, Nishihara, Okinawa 903-0213, Japan.
The subiculum is a main output part of the hippocampal formation and important for learning and memory. According to connection studies, the distal and proximal regions of the subiculum project to the brain regions related to the spatial and emotional memories, respectively. Our previous morphological studies indicated that the ventral subiculum (vSub) consists of two regions, the distal subiculum (Sub1) and the proximal subiculum (Sub2), while the dorsal subiculum (dSub) seemed to comprise only one region (Sub1).
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!