Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging

Abstract

Evidence concerning anatomical connectivities in the human brain is sparse and based largely on limited post-mortem observations. Diffusion tensor imaging has previously been used to define large white-matter tracts in the living human brain, but this technique has had limited success in tracing pathways into gray matter. Here we identified specific connections between human thalamus and cortex using a novel probabilistic tractography algorithm with diffusion imaging data. Classification of thalamic gray matter based on cortical connectivity patterns revealed distinct subregions whose locations correspond to nuclei described previously in histological studies. The connections that we found between thalamus and cortex were similar to those reported for non-human primates and were reproducible between individuals. Our results provide the first quantitative demonstration of reliable inference of anatomical connectivity between human gray matter structures using diffusion data and the first connectivity-based segmentation of gray matter.

Thalamic functional connectivity and its association with behavioral performance in older age

“…(2003)). The probabilistic masks from this atlas, thresholded at a probability of 25% as applied previously (Serra et al., 2014), comprise seven bilateral subregions that have been identified to structurally connect predominantly to the following: primary motor cortex (MT), premotor cortex (pMT), somatosensory cortex (ST), occipital cortex (OT), frontal cortex (FT), posterior parietal cortex (PT), and temporal cortex (TT) (see Figure 2).…”

“…However, the majority of studies in humans have investigated the thalamus as a whole, despite the differential connectivity and function of its subregions. Segmentation of the thalamus has been performed with diffusion tensor imaging (DTI) data (Behrens et al., 2003; Duan, Heckenberg, Xi, & Hao, 2006; Jang & Yeo, 2014; Kumar, Mang, & Grodd, 2014; Ye, Bogovic, Ying, & Prince, 2013) as well as using FC of resting‐state fMRI data (Hale et al., 2015; Kim, Park, & Park, 2013; Zhang et al., 2008). Despite some discrepancies in thalamic connectivity results between these different methodologies, the general principles identified are similar and reasonably consistent with histological and anatomical studies.…”

PREP2: A biomarker‐based algorithm for predicting upper limb function after stroke

“…In preparation, template tracts were constructed using probabilistic fiber tracking in the contralesional hemispheres of 85 patients. Diffusion‐weighted images were preprocessed with motion and eddy current correction, skull stripping, estimation and fitting of diffusion parameters, and modeling of crossing fibers 18. Seed masks were placed at the pyramid and the primary motor cortex (M1), with a way point at the posterior limb of the internal capsule, for the corticospinal tract template.…”

Connectivity‐based segmentation of the periaqueductal gray matter in human with brainstem optimized diffusion MRI

“…Successful clustering was defined as identification of a distinct cluster that had a spatial representation as predicted by the animal model of the PAG, that is, a cluster that was parallel to the aqueduct in the dorsomedial, dorsolateral, lateral, or ventrolateral aspect of the PAG. Previous tractography segmentation studies [Behrens et al, 2003a] have identified that results were reproducible in approximately 70% of subjects due to the performance of tractography. K means clustering is a hard clustering technique that will identify a predetermined number of clusters.…”