All ETDs from UAB

Advisory Committee Chair

Kristina M Visscher

Advisory Committee Members

Lawrence Sincich

David Knight

Document Type

Thesis

Date of Award

2019

Degree Name by School

Master of Arts (MA) College of Arts and Sciences

Abstract

Vision is important for our everyday life, but we use our central vision differently than our peripheral vision. For example, we use central vision to read and peripheral vision when getting the gist of a scene. Different functions of central and peripheral vision suggest that information from central vision may be processed differently from that in peripheral vision. A previous functional magnetic resonance imaging (MRI) connectivity study suggested reliable differences in connections between centrally- and peripherally-representing visual cortex, and those differences follow well-established networks. Central-representing cortex was preferentially connected to regions belonging to the fronto-parietal (FP) net-work, mid-peripheral was generally more connected to the cingulo-opercular (CO) net-work, and far-peripheral was more connected to the default mode network (DMN). This led to the question of whether these connections reflect differing structural tracts. In this study, we used diffusion MRI of 786 subjects from the Human Connectome Project. We performed probabilistic tractography on anatomically defined target regions of interest in V1, corresponding to central, mid-peripheral, and far-peripheral visual eccentricities and seed regions of the FP network, CO network, and DMN. Differences in cortical termination track probabilities were then analyzed on the surface. Difference maps comparing tract probability for far-peripheral vs. central V1 regions showed the FP network was more connected to central V1 and the DMN was more connected to far-peripheral V1. The CO network was more connected to mid than central V1 and far V1. These results suggest eccentricity-based regions are differentially structural-ly connected to cortical, functional networks. In the comparison of eccentricity-based regions we found resemblance of structural connectivity to functional connectivity network patterns. Results imply that some of the differences in functional connectivity previously ob-served and currently replicated derive from direct connections observable through diffusion imaging, but some of these connections cannot be observed through diffusion imaging and may derive from multisynaptic connections. Studying the differential structural connections of portions of V1 contributes to our understanding of the way the human brain processes visual information and forms a base-line for understanding any modifications in processing that might occur with training or experience.

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