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Espinoza, G.

Publications and source records attributed to Espinoza, G..

2 recordsLinked to original sources

Visual Perception of 3D Space and Shape in Time - Part III: 2D Shape Recognition by Log-Scaling

Human vision has a remarkable ability to recognize complex 3D objects such as faces that appear with any size and 3D orientations at any 3D location. If we initially memorize a face only with a normalized size and viewed from directly head on, the direct comparison between the one-sized memory and a new incoming image would demand tremendous mental frame translations in 7D. How can we perform such a demanding task so promptly and reliably as we experience the objects in the world around us? Intriguingly, our primary visual cortex exhibits a 2D retinotopy with a log-polar coordinate system, where scaling up/down of shape is converted to linear frame translation. As a result, mental scaling can be performed by linearly translating the memory or the perceptual image until they overlap with each other. According to our new model of NHT (Neural Holography Tomography), alpha brainwaves traveling at a constant speed can conduct this linear translation. With this scheme, every scaling up/down by a factor of two should take the same amount of extra mental time to recognize a smaller/larger face. To test this hypothesis, we designed a reaction time (RT) experiment, where participants were first asked to memorize sets of unfamiliar faces with a given specific size (4{degrees} or 8{degrees}). Following the memorization phase, similar stimuli with a wide range of sizes (from 1{degrees} to 32{degrees}) were presented, and RTs were recorded. As predicted, the increase in RT was proportional to the scaling factor in the log scale. Furthermore, we observed that RTs were fastest for 8{degrees} faces even if the memorized face was 4{degrees}. This supports our hypothesis that we always memorize faces at the exact size of ~8 {degrees}. To our surprise, the increases in RT were also consistent with the mentally-estimated depth sensation, which indicates that the apparent size of the recognized face can create a proper depth sensation.

neuroscience↗

On the proportional abundance of species: Integrating population genetics and community ecology

The frequency of genes in interconnected populations and of species in interconnected communities are affected by similar processes, such as birth, death and immigration. The equilibrium distribution of gene frequencies in structured populations is known since the 1930s, under Wrights metapopulation model known as the island model. The equivalent distribution for the species frequency (i.e. the species proportional abundance distribution (SPAD), at the metacommunity level, however, is unknown. In this contribution, we develop a stochastic model to analytically account for this distribution (SPAD). We show that the same as for genes SPAD follows a beta distribution, which provides a good description of empirical data and applies across a continuum of scales. This stochastic model, based upon a diffusion approximation, provides an alternative to neutral models for the species abundance distribution (SAD), which focus on number of individuals instead of proportions, and demonstrate that the relative frequency of genes in local populations and of species within communities follow the same probability law. We hope our contribution will help stimulate the mathematical and conceptual integration of theories in genetics and ecology.

ecology↗