Representation of auditory and visual spatial information in the intraparietal sulcus of rhesus macaques.

2005 ◽  
Author(s):  
O'Dhaniel Alexander Mullette-Gillman
Keyword(s):  
Spatial Information ◽  
Rhesus Macaques ◽  
Intraparietal Sulcus ◽  
Visual Spatial

scholarly journals Non-communicable disease surveillance in India using Geographical Information System-An experience from Punjab

2021 ◽  
Vol 33 (3) ◽  
pp. 506-511
Author(s):  
Sheikh Mohd Saleem ◽  
Chaitnya Aggarwal ◽  
Om Prakash Bera ◽  
Radhika Rana ◽  
Gurmandeep Singh ◽  
...  
Keyword(s):  
Information System ◽  
Spatial Information ◽  
Communicable Diseases ◽  
Project Planning ◽  
Geographical Information ◽  
Non Communicable Diseases ◽  
Visual Spatial ◽  
Catchment Areas ◽  
Health Related ◽  
Space Data

"Geographic information system (GIS) collects various kinds of data based on the geographic relationship across space." Data in GIS is stored to visualize, analyze, and interpret geographic data to learn about an area, an ongoing project, site planning, business, health economics and health-related surveys and information. GIS has evolved from ancient disease maps to 3D digital maps and continues to grow even today. The visual-spatial mapping of the data has given us an insight into different diseases ranging from diarrhea, pneumonia to non-communicable diseases like diabetes mellitus, hypertension, cardiovascular diseases, or risk factors like obesity, being overweight, etc. All in a while, this information has highlighted health-related issues and knowledge about these in a contemporary manner worldwide. Researchers, scientists, and administrators use GIS for research project planning, execution, and disease management. Cases of diseases in a specific area or region, the number of hospitals, roads, waterways, and health catchment areas are examples of spatially referenced data that can be captured and easily presented using GIS. Currently, we are facing an epidemic of non-communicable diseases, and a powerful tool like GIS can be used efficiently in such a situation. GIS can provide a powerful and robust framework for effectively monitoring and identifying the leading cause behind such diseases.  GIS, which provides a spatial viewpoint regarding the disease spectrum, pattern, and distribution, is of particular importance in this area and helps better understand disease transmission dynamics and spatial determinants. The use of GIS in public health will be a practical approach for surveillance, monitoring, planning, optimization, and service delivery of health resources to the people at large. The GIS platform can link environmental and spatial information with the disease itself, which makes it an asset in disease control progression all over the globe.

Adaptation in the Auditory Space Map of the Barn Owl

2006 ◽  
Vol 96 (2) ◽  
pp. 813-825 ◽  
Author(s):  
Yoram Gutfreund ◽  
Eric I. Knudsen
Keyword(s):  
Inferior Colliculus ◽  
Spatial Information ◽  
Short Term Memory ◽  
Threshold Level ◽  
Central Nucleus ◽  
Visually Guided ◽  
Auditory Space ◽  
Visual Spatial ◽  
Stimulus Offset ◽  
A Site

Auditory neurons in the owl’s external nucleus of the inferior colliculus (ICX) integrate information across frequency channels to create a map of auditory space. This study describes a powerful, sound-driven adaptation of unit responsiveness in the ICX and explores the implications of this adaptation for sensory processing. Adaptation in the ICX was analyzed by presenting lightly anesthetized owls with sequential pairs of dichotic noise bursts. Adaptation occurred in response even to weak, threshold-level sounds and remained strong for more than 100 ms after stimulus offset. Stimulation by one range of sound frequencies caused adaptation that generalized across the entire broad range of frequencies to which these units responded. Identical stimuli were used to test adaptation in the lateral shell of the central nucleus of the inferior colliculus (ICCls), which provides input directly to the ICX. Compared with ICX adaptation, adaptation in the ICCls was substantially weaker, shorter lasting, and far more frequency specific, suggesting that part of the adaptation observed in the ICX was attributable to processes resident to the ICX. The sharp tuning of ICX neurons to space, along with their broad tuning to frequency, allows ICX adaptation to preserve a representation of stimulus location, regardless of the frequency content of the sound. The ICX is known to be a site of visually guided auditory map plasticity. ICX adaptation could play a role in this cross-modal plasticity by providing a short-term memory of the representation of auditory localization cues that could be compared with later-arriving, visual–spatial information from bimodal stimuli.

Egocentric Action in Early Infancy: Spatial Frames of Reference for Saccades

1997 ◽  
Vol 8 (3) ◽  
pp. 224-230 ◽  
Author(s):  
Rick O. Gilmore ◽  
Mark H. Johnson
Keyword(s):  
Spatial Information ◽  
Visual Space ◽  
Frames Of Reference ◽  
Saccade Target ◽  
Visually Guided ◽  
Retinal Position ◽  
Position Information ◽  
Visual Spatial ◽  
Visually Guided Action ◽  
Spatial Frames Of Reference

The extent to which infants combine visual (i e, retinal position) and nonvisual (eye or head position) spatial information in planning saccades relates to the issue of what spatial frame or frames of reference influence early visually guided action We explored this question by testing infants from 4 to 6 months of age on the double-step saccade paradigm, which has shown that adults combine visual and eye position information into an egocentric (head- or trunk-centered) representation of saccade target locations In contrast, our results imply that infants depend on a simple retinocentric representation at age 4 months, but by 6 months use egocentric representations more often to control saccade planning Shifts in the representation of visual space for this simple sensorimotor behavior may index maturation in cortical circuitry devoted to visual spatial processing in general

Common coding of auditory and visual spatial information in working memory

2008 ◽  
Vol 1230 ◽  
pp. 158-167 ◽  
Author(s):  
Günther Lehnert ◽  
Hubert D. Zimmer
Keyword(s):  
Working Memory ◽  
Spatial Information ◽  
Common Coding ◽  
Visual Spatial

scholarly journals Long-Term Loop Closure Detection through Visual-Spatial Information Preserving Multi-Order Graph Matching

2020 ◽  
Vol 34 (06) ◽  
pp. 10369-10376
Author(s):  
Peng Gao ◽  
Hao Zhang
Keyword(s):  
Spatial Information ◽  
Graph Matching ◽  
Fundamental Problem ◽  
Graph Representation ◽  
Spatial Relationships ◽  
Matching Problem ◽  
Loop Closure ◽  
Loop Closure Detection ◽  
Visual Spatial

Loop closure detection is a fundamental problem for simultaneous localization and mapping (SLAM) in robotics. Most of the previous methods only consider one type of information, based on either visual appearances or spatial relationships of landmarks. In this paper, we introduce a novel visual-spatial information preserving multi-order graph matching approach for long-term loop closure detection. Our approach constructs a graph representation of a place from an input image to integrate visual-spatial information, including visual appearances of the landmarks and the background environment, as well as the second and third-order spatial relationships between two and three landmarks, respectively. Furthermore, we introduce a new formulation that formulates loop closure detection as a multi-order graph matching problem to compute a similarity score directly from the graph representations of the query and template images, instead of performing conventional vector-based image matching. We evaluate the proposed multi-order graph matching approach based on two public long-term loop closure detection benchmark datasets, including the St. Lucia and CMU-VL datasets. Experimental results have shown that our approach is effective for long-term loop closure detection and it outperforms the previous state-of-the-art methods.

Spatial recoding of sound: Pitch-varying auditory cues modulate up/down visual spatial attention

2012 ◽  
Vol 25 (0) ◽  
pp. 150-151 ◽  
Author(s):  
Irune Fernández-Prieto ◽  
Fátima Vera-Constán ◽  
Joel García-Morera ◽  
Jordi Navarra
Keyword(s):  
Spatial Attention ◽  
Visual Target ◽  
Reaction Times ◽  
Detection Task ◽  
Spatial Processing ◽  
Intraparietal Sulcus ◽  
Auditory Cues ◽  
Visual Spatial Attention ◽  
Visual Spatial ◽  
Pitch Direction

Previous studies suggest the existence of facilitatory effects between, for example, responding upwards/downwards while hearing a high/low-pitched tone, respectively (e.g., Occeli et al., 2009; Rusconi et al., 2006). Neuroimaging research has started to reveal the activation of parietal areas (e.g., the intraparietal sulcus, IPS) during the performance of various pitch-based musical tasks (see Foster and Zatorre, 2010a, 2010b). Since several areas in the parietal cortex (e.g., the IPS; see Chica et al., 2011) are strongly involved in orienting visual attention towards external events, we investigated the possible effects of perceiving pitch-varying stimuli (i.e., ‘ascending’ or ‘descending’ flutter sounds) on the spatial processing of visual stimuli. In a variation of the Posner cueing paradigm (Posner, 1980), participants performed a speeded detection task of a visual target that could appear at one of four different spatial positions (two above and two below the fixation point). Irrelevant ascending (200–700 Hz) or descending (700–200 Hz) flutter sounds were randomly presented 550 ms before the onset of the visual target. According to our results, faster reaction times were observed when the visual target appeared in a position (up/down) that was compatible with the ‘pitch direction’ (ascending or descending) of the previously-presented auditory ‘cuing’ stimulus. Our findings suggest that pitch-varying sounds are recoded spatially, thus modulating visual spatial attention.

scholarly journals Designing information fusion for the encoding of visual–spatial information

Ergonomics ◽  
2008 ◽  
Vol 51 (6) ◽  
pp. 775-797 ◽  
Author(s):  
Samuel M. Waldron ◽  
John Patrick ◽  
Geoffrey B. Duggan ◽  
Simon Banbury ◽  
Andrew Howes
Keyword(s):  
Information Fusion ◽  
Spatial Information ◽  
Visual Spatial
Sign in / Sign up

Export Citation Format

Share Document