Macromolecular tissue volume mapping of lateral geniculate nucleus subdivisions in living human brains

Hiroki Oishi; Hiromasa Takemura; Kaoru Amano

NeuroImage (Jan 2023)

Macromolecular tissue volume mapping of lateral geniculate nucleus subdivisions in living human brains

Hiroki Oishi,
Hiromasa Takemura,
Kaoru Amano

Affiliations

Hiroki Oishi: Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita 565-0871, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita 565-0871, Japan; Department of Psychology, University of California, Berkeley, Berkeley, CA 94704, United States; Corresponding author at: Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita 565-0871, Japan.
Hiromasa Takemura: Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita 565-0871, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita 565-0871, Japan; Division of Sensory and Cognitive Brain Mapping, Department of System Neuroscience, National Institute for Physiological Sciences, Okazaki 444-8585, Japan; Department of Physiological Sciences, School of Life Science, SOKENDAI (The Graduate University for Advanced Studies), Hayama 240-0193, Japan; Corresponding author at: Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita 565-0871, Japan.
Kaoru Amano: Center for Information and Neural Networks (CiNet), Advanced ICT Research Institute, National Institute of Information and Communications Technology, Suita 565-0871, Japan; Graduate School of Frontier Biosciences, Osaka University, Suita 565-0871, Japan; Graduate School of Information Science and Technology, The University of Tokyo, Tokyo 113-8656, Japan

Journal volume & issue: Vol. 265
p. 119777

Abstract

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The lateral geniculate nucleus (LGN) is a key thalamic nucleus in the visual system, which has an important function in relaying retinal visual input to the visual cortex. The human LGN is composed mainly of magnocellular (M) and parvocellular (P) subdivisions, each of which has different stimulus selectivity in neural response properties. Previous studies have discussed the potential relationship between LGN subdivisions and visual disorders based on psychophysical data on specific types of visual stimuli. However, these relationships remain speculative because non-invasive measurements of these subdivisions are difficult due to the small size of the LGN. Here we propose a method to identify these subdivisions by combining two structural MR measures: high-resolution proton-density weighted images and macromolecular tissue volume (MTV) maps. We defined the M and P subdivisions based on MTV fraction data and tested the validity of the definition by (1) comparing the data with that from human histological studies, (2) comparing the data with functional magnetic resonance imaging measurements on stimulus selectivity, and (3) analyzing the test-retest reliability. The findings demonstrated that the spatial organization of the M and P subdivisions was consistent across subjects and in line with LGN subdivisions observed in human histological data. Moreover, the difference in stimulus selectivity between the subdivisions identified using MTV was consistent with previous physiology literature. The definition of the subdivisions based on MTV was shown to be robust over measurements taken on different days. These results suggest that MTV mapping is a promising approach for evaluating the tissue properties of LGN subdivisions in living humans. This method potentially will enable neuroscientific and clinical hypotheses about the human LGN subdivisions to be tested.

Published in NeuroImage

ISSN: 1053-8119 (Print); 1095-9572 (Online)
Publisher: Elsevier
Country of publisher: United States
LCC subjects: Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry
Website: https://www.journals.elsevier.com/neuroimage

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