PT  - JOURNAL ARTICLE
AU  - Irem Yildirim
AU  - Khan Hekmatyar
AU  - Keith A. Schneider
TI  - Evaluating Quantitative and Functional MRI As Potential Techniques to Identify the Subdivisions in the Human Lateral Geniculate Nucleus
AID  - 10.1101/2022.11.16.516765
DP  - 2022 Jan 01
TA  - bioRxiv
PG  - 2022.11.16.516765
4099  - http://biorxiv.org/content/early/2022/11/16/2022.11.16.516765.short
4100  - http://biorxiv.org/content/early/2022/11/16/2022.11.16.516765.full
AB  - Segmenting the magnocellular (M) and parvocellular (P) divisions of the human lateral geniculate nucleus (LGN) has been challenging yet remains an important goal because the LGN is the only place in the brain where these two information streams are spatially disjoint and can be studied independently. Previous research used the amplitude of responses to different types of stimuli to separate M and P regions (Denison et al., 2014; Zhang et al., 2015). However, this method is confounded because the hilum region of the LGN exhibits greater response amplitudes to all stimuli and can be mistaken for the M subdivision (DeSimone & Schneider, 2019). Therefore, we have employed two independent methodologies that do not rely upon the functional response properties of the M and P neurons to segment the M and P regions: 1) structural quantitative MRI (qMRI) at 3T to measure the T1 relaxation time, and 2) monocular and dichoptic functional MRI (fMRI) procedures to measure eye-specific responses. Our qMRI results agreed with the anatomical expectations, identifying M regions on the ventromedial surface of the LGN. The monocular fMRI procedure was better than the dichoptic condition to identify the eye-dominance signals. Both procedures revealed significant right eye bias, and neither could reliably identify the first M layer of the LGN. These findings indicated that the qMRI methods are promising whereas the functional identification of contralateral layers requires further refinement.HighlightsT1 parameter in qMRI segregates M and P regions of LGN in individual subjects at 3T.Eye-specific voxels in LGN respond more strongly to monocular than dichoptic viewing.Clusters of eye-specific regions but not layers can be separated at 1.5 mm resolution.Competing Interest StatementThe authors have declared no competing interest.