Mechanism(s) for Apprehending Numerosity Based On Several Visual Properties

2011 ◽  
Author(s):  
Charles Chubb ◽  
Charles E. Wright ◽  
Elhum Shamshiri ◽  
Megan Wang
Keyword(s):  
Visual Properties

Spatio-temporal visual properties in the ascending tectofugal system

2010 ◽  
Vol 5 (1) ◽  
pp. 21-30 ◽  
Author(s):  
Alice Rokszin ◽  
Zita Márkus ◽  
Gábor Braunitzer ◽  
Antal Berényi ◽  
Marek Wypych ◽  
...  
Keyword(s):  
Visual Information ◽  
Frequency Tuning ◽  
Temporal Frequency ◽  
Neuronal Population ◽  
Neuronal Responses ◽  
Temporal Properties ◽  
Visual Receptive Field ◽  
Detailed Statistical Analysis ◽  
Spatio Temporal ◽  
Visual Properties

AbstractOur study compares the spatio-temporal visual receptive field properties of different subcortical stages of the ascending tectofugal visual system. Extracellular single-cell recordings were performed in the superficial (SCs) and intermediate (SCi) layers of the superior colliculus (SC), the suprageniculate nucleus (Sg) of the posterior thalamus and the caudate nucleus (CN) of halothane-anesthetized cats. Neuronal responses to drifting gratings of various spatial and temporal frequencies were recorded. The neurons of each structure responded optimally to low spatial and high temporal frequencies and displayed narrow spatial and temporal frequency tuning. The detailed statistical analysis revealed that according to its stimulus preferences the SCs has markedly different spatio-temporal properties from the homogeneous group formed by the SCi, Sg and CN. The SCs neurons preferred higher spatial and lower temporal frequencies and had broader spatial tuning than the other structures. In contrast to the SCs the visually active SCi, as well as the Sg and the CN neurons possessed consequently similar spatio-temporal preferences. These data support our hypothesis that the visually active SCi, Sg and CN neurons form a homogeneous neuronal population given a similar spatio-temporal frequency preference and a common function in processing of dynamic visual information.

Spatial and temporal visual properties of the neurons in the intermediate layers of the superior colliculus

2009 ◽  
Vol 454 (1) ◽  
pp. 76-80 ◽  
Author(s):  
Zita Márkus ◽  
Antal Berényi ◽  
Zsuzsanna Paróczy ◽  
Marek Wypych ◽  
Wioletta J. Waleszczyk ◽  
...  
Keyword(s):  
Superior Colliculus ◽  
Intermediate Layers ◽  
Visual Properties

Synthetic and Comparative Hydrology of Earth, Mars, and Titan

2021 ◽  
Author(s):  
Vojtěch Cuřín ◽  
Johanna Blöcher ◽  
Petr Brož ◽  
Yannis Markonis ◽  
Jan Masner ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Atmospheric Precipitation ◽  
Morphological Characteristics ◽  
Remote Sensing Data ◽  
Machine Learning Techniques ◽  
Carbon Sphere ◽  
Spatial Homogeneity ◽  
Planetary Bodies ◽  
Network Properties ◽  
Visual Properties

<p>Earth, Mars, and Titan are the only known planetary bodies in our solar system where flowing liquids have shaped surface topography and formed extensive river networks. Fed by atmospheric precipitation and carved by fluvial erosion, these channels are observable in remote sensing data. They carry information about the interactions between the atmosphere, the hydro(carbon)sphere, and the lithosphere and allow for investigation of the conditions that had prevailed during their formation. Comparison of drainage basins, which developed in these profoundly different environments, could yield insights into the past and ongoing hydrological processes in addition to climatic, chemical, and topographic conditions of the planetary bodies. Increased computing capacities allow for building and utilization of a vast database of hydrological, climatological, and geological data as well as algorithmic evaluation of remote sensing products. Here, we propose a classification of basins from Earth, Mars, and Titan using several machine learning techniques based on their morphological characteristics, network properties, spatial homogeneity, cross-scale self-similarity, and visual properties. Constraints on climatic and geologic properties of the terrestrial basin classes will be identified, and the results of their morphology-climatic relationship extrapolated to Mars and Titan. To find out more, visit our project’s website https://www.schemata-project.com/.</p>

scholarly journals Solving the "right" problems for effective machine learning driven in vitro fertilization

2021 ◽  
Author(s):  
Itay Erlich ◽  
Assaf Ben-Meir ◽  
Iris Har-Vardi ◽  
James A Grifo ◽  
Assaf Zaritsky
Keyword(s):  
Machine Learning ◽  
In Vitro Fertilization ◽  
Clinical Factors ◽  
Vitro Fertilization ◽  
Data Intensive ◽  
Live Embryo ◽  
The Right ◽  
Visual Properties ◽  
Selection Of

Automated live embryo imaging has transformed in-vitro fertilization (IVF) into a data-intensive field. Unlike clinicians who rank embryos from the same IVF cycle cohort based on the embryos visual quality and determine how many embryos to transfer based on clinical factors, machine learning solutions usually combine these steps by optimizing for implantation prediction and using the same model for ranking the embryos within a cohort. Here we establish that this strategy can lead to sub-optimal selection of embryos. We reveal that despite enhancing implantation prediction, inclusion of clinical properties hampers ranking. Moreover, we find that ambiguous labels of failed implantations, due to either low quality embryos or poor clinical factors, confound both the optimal ranking and even implantation prediction. To overcome these limitations, we propose conceptual and practical steps to enhance machine-learning driven IVF solutions. These consist of separating the optimizing of implantation from ranking by focusing on visual properties for ranking, and reducing label ambiguity.

scholarly journals The limited contribution of early visual cortex in visual working memory for surface roughness

2020 ◽  
Author(s):  
Munendo Fujimichi ◽  
Hiroki Yamamoto ◽  
Jun Saiki
Keyword(s):  
Working Memory ◽  
Visual Cortex ◽  
Visual Working Memory ◽  
Brain Activity ◽  
Visual Representations ◽  
Brain Regions ◽  
Daily Lives ◽  
Early Visual Cortex ◽  
Roughness Discrimination ◽  
Visual Properties

Are visual representations in the human early visual cortex necessary for visual working memory (VWM)? Previous studies suggest that VWM is underpinned by distributed representations across several brain regions, including the early visual cortex. Notably, in these studies, participants had to memorize images under consistent visual conditions. However, in our daily lives, we must retain the essential visual properties of objects despite changes in illumination or viewpoint. The role of brain regions—particularly the early visual cortices—in these situations remains unclear. The present study investigated whether the early visual cortex was essential for achieving stable VWM. Focusing on VWM for object surface properties, we conducted fMRI experiments while male and female participants performed a delayed roughness discrimination task in which sample and probe spheres were presented under varying illumination. By applying multi-voxel pattern analysis to brain activity in regions of interest, we found that the ventral visual cortex and intraparietal sulcus were involved in roughness VWM under changing illumination conditions. In contrast, VWM was not supported as robustly by the early visual cortex. These findings show that visual representations in the early visual cortex alone are insufficient for the robust roughness VWM representation required during changes in illumination.

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