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Larissa McKetton, Keith A. Schneider; Discriminating the eye-specific layers of the human lateral geniculate nucleus using high-resolution fMRI. Journal of Vision 2012;12(9):212. doi: 10.1167/12.9.212.
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© ARVO (1962-2015); The Authors (2016-present)
The lateral geniculate nucleus (LGN) is a small thalamic nucleus receiving binocular input from the contralateral visual field. The LGN is organized into six interleaved monocular layers. The dorsal four main layers receive parvocellular (P) input and the dorsal two layers magnocellular (M). Our experimental objective was to directly image and discriminate these eye-specific layers of the LGN in human participants.
Participants were scanned using a Siemens Trio 3T MRI scanner and 32-channel head coil. Anatomical regions of interest (ROIs) were created for the LGN by manually tracing 1 h of registered and averaged proton density weighted images. Functional MRI scanning utilized an EPI sequence with a 256 matrix and 192 mm field of view, resulting in an in-plane resolution of 0.75 × 0.75 mm2. Stimuli were presented using an Avotec 7021 goggle system that allowed independent high-contrast stimulation of each eye. The stimuli consisted of a field of moving dots, a variable fraction of which moved coherently. The dots in the left and right visual fields periodically switched between the eyes. Subjects were required to detect changes in the direction of coherence. The coherence fraction was manipulated such that subjects were approximately 75% correct, maintaining the attentional demands of the stimulus.
We were able to reliably activate the LGN using the high-resolution EPI sequence, and we compared these activations to the anatomically defined ROIs as well as to previous results acquired at lower resolutions. Using the high-resolution imaging, we were able to reliably assign voxels as being dominated by one eye or the other and discriminate the monocular layers.
We have demonstrated that it is possible to discriminate the eye-specific layers of the LGN by directly imaging their functional activation using high-resolution fMRI.
Meeting abstract presented at VSS 2012
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