Title :
New trends in computational modeling: A Neuroid-based retina model
Author :
Arguello, E. ; Silva, R. ; Huerta, Milagros ; Castillo, Claris
Author_Institution :
Lab. C, Simon Bolivar Univ., Caracas, Venezuela
Abstract :
It is thought that using detailed neuron-models could lead to a better understanding of how the nervous system works. However, neural networks preserve their collective computational properties, regardless of the level of description used for modeling the main building block. In this paper, we built a Neuroid-based retina model. As a result of the implementation, the Neuroid was able to reproduce the essential features of the photoreceptor response to light. Likewise, the retina model responded to specific visual effects such as simultaneous contrast, Mach bands and Hermann grid. All of these suggest that the Neuroid comprises enough functional characteristics, such that we could focus not only on the most relevant computational aspects of nerve cells, but also in the collective capabilities of large-scale neural networks.
Keywords :
cellular biophysics; eye; medical computing; neural nets; neurophysiology; physiological models; visual perception; Hermann grid; Mach bands; collective computational property; computational modeling; description level; large-scale neural network; light photoreceptor response; main building block modeling; nerve cell; nervous system; neuroid-based retina model; simultaneous contrast; visual effect; Biological neural networks; Computational modeling; Lighting; Market research; Photoreceptors; Retina;
Conference_Titel :
Engineering in Medicine and Biology Society (EMBC), 2013 35th Annual International Conference of the IEEE
Conference_Location :
Osaka
DOI :
10.1109/EMBC.2013.6610562