4.7 Article

Reliable identification of the auditory thalamus using multi-modal structural analyses

Journal

NEUROIMAGE
Volume 30, Issue 4, Pages 1112-1120

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2005.11.025

Keywords

medial geniculate body; lateral geniculate nucleus; proton density; diffusion-weighted imaging; tractography

Funding

  1. MRC [MC_U135079236, G0501316, MC_U135079238] Funding Source: UKRI
  2. Medical Research Council [MC_U135079236, G0501316, MC_U135079238] Funding Source: researchfish
  3. Medical Research Council [MC_U135079238, MC_U135079236, G0501316] Funding Source: Medline
  4. Wellcome Trust [075481, 078204] Funding Source: Medline

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The medial geniculate body (MGB) of the thalamus is a key component of the auditory system. It is involved in relaying and transforming auditory information to the cortex and in top-down modulation of processing in the midbrain, brainstem, and ear. Functional imaging investigations of this region in humans, however, have been limited by the difficulty of distinguishing MGB from other thalamic nuclei. Here, we introduce two methods for reliably delineating MGB anatomically in individuals based on conventional and diffusion MRI data. The first uses high-resolution proton density weighted scanning optimized for subcortical grey-white contrast. The second uses diffusion-weighted imaging and probabilistic tractography to automatically segment the medial and lateral geniculate nuclei from surrounding structures based on their distinctive patterns of connectivity to the rest of the brain. Both methods produce highly replicable results that are consistent with published atlases. Importantly, both methods rely on commonly available imaging sequences and standard hardware, a significant advantage over previously described approaches. In addition to providing useful approaches for identifying the MGB and LGN in vivo, our study offers further validation of diffusion tractography for the parcellation of grey matter regions on the basis of their connectivity patterns. (c) 2005 Elsevier Inc. All rights reserved.

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