A cell model in the ventral visual pathway for the detection of circles of curvature constituting figures

التفاصيل البيبلوغرافية
العنوان: A cell model in the ventral visual pathway for the detection of circles of curvature constituting figures
المؤلفون: Makoto Hashimoto, Yoshinari Makino, Susumu Kawakami, Takehiro Ito, Masafumi Yano
المصدر: Heliyon
Heliyon, Vol 6, Iss 11, Pp e05397-(2020)
بيانات النشر: Elsevier BV, 2020.
سنة النشر: 2020
مصطلحات موضوعية: Nervous system, 0301 basic medicine, Consciousness, Column, Simple cell, Curvature, Lateral geniculate nucleus, Hough transform, law.invention, Combinatorics, 03 medical and health sciences, Cognition, 0302 clinical medicine, Intersection, law, Curvature-circle detection, medicine, Information systems, Mathematical biosciences, lcsh:Social sciences (General), lcsh:Science (General), 3D normal-line transform, Emotion, Physics, Multidisciplinary, Behavioral neuroscience, Systems neuroscience, Tangent, Coarse-to-fine extraction, 030104 developmental biology, Transformation (function), medicine.anatomical_structure, Cell-array conversion, Cell model, lcsh:H1-99, Shape recognition, Normal, 030217 neurology & neurosurgery, lcsh:Q1-390, Research Article
الوصف: The contour of an arbitrary figure can be represented as a group of circles of curvature in contact with it, with each curvature circle represented by its center OC and radius r. We propose a series of cell models for detecting this circle, which is composed of a lateral geniculate nucleus (LGN) cell, nondirectionally selective (NDS) simple cell, and curvature-circle detection cell (CDC). The LGN and NDS simple cells were previously modeled. The CDC has been modeled as follows. Each tangent in contact with this circle is detected by an NDS simple cell that performs the Hough transformation of LGN cell responses, and then this tangent is transformed to a three-dimensional (3D) normal line in a CDC column. This transformation has been named a 3D normal-line transform. Performing this transformation for all tangents causes a CDC at the intersection of these normal lines to fire most intensively, and thus the OC and r of the circle is detected as the coordinates of this intersection. Therefore, the CDC has been modeled as this 3D normal-line transform. Based on this CDC, we model two types of constancy CDC: a position-invariant CDC and a curvature-invariant CDC. These three types of CDC reflect the response to various stimuli in actual area V4 cells. In order to validate these CDC types neurophysiologically, we propose an experimental method using microelectrodes. Cell models previously reported correspond to this hierarchy: the S1, S2, and C2 cells correspond to the NDS simple cell, CDC, and position-invariant CDC, respectively.
Cell model, Curvature-circle detection, 3D normal-line transform, Column, Coarse-to-fine extraction, Cell-array conversion, Shape recognition, Information systems, Behavioral neuroscience, Nervous system, Cognition, Consciousness, Emotion, Systems neuroscience, Mathematical biosciences.
تدمد: 2405-8440
الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e33cf342d4f6e5cc552ec7c456b43b70Test
https://doi.org/10.1016/j.heliyon.2020.e05397Test
حقوق: OPEN
رقم الانضمام: edsair.doi.dedup.....e33cf342d4f6e5cc552ec7c456b43b70
قاعدة البيانات: OpenAIRE