The physical architecture of neural circuits is thought to underlie the computations that give rise to higher order feature sensitivity in the neocortex. Recent technological breakthroughs have allowed the structural and functional investigation of the basic computational units of neural circuits; individual synaptic connections. However, it remains unclear how cortical neurons sample and integrate the thousands of synaptic inputs, supplied by different brain structures, to achieve feature selectivity. Here, I first describe how visual cortical circuits transform the elementary inputs supplied by the periphery into highly diverse, but well-organized, feature representations. By combining and optimizing newly developed techniques to map the functional synaptic connections with defined sources of inputs, I show that the intersection between columnar architecture and dendritic sampling strategies can lead to the selectivity properties of individual neurons: First, in the canonical feedforward circuit, the basal dendrites of a pyramidal neuron utilize unique strategies to sample ON (light increment) and OFF (light decrement) inputs in orientation columns to create the distinctive receptive field structure that is responsible for basic sensitivity to visual spatial location, orientation, spatial frequency, and phase. Second, for long-range horizontal connections, apical dendrites unbiasedly integrate functionally specialized and spatially targeted inputs in different orientation columns, which generates specific axial surround modulation of the receptive field. / Includes bibliography. / Dissertation (Ph.D.)--Florida Atlantic University, 2019. / FAU Electronic Theses and Dissertations Collection
| Identifer | oai:union.ndltd.org:fau.edu/oai:fau.digital.flvc.org:fau_41947 |
| Contributors | Lee, Kuo-Sheng (author), Fitzpatrick, David (Thesis advisor), Florida Atlantic University (Degree grantor), Charles E. Schmidt College of Science, Department of Biological Sciences |
| Publisher | Florida Atlantic University |
| Source Sets | Florida Atlantic University |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation, Text |
| Format | 160 p., application/pdf |
| Rights | Copyright © is held by the author with permission granted to Florida Atlantic University to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder., http://rightsstatements.org/vocab/InC/1.0/ |
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