Neural connectivity underlying core language functions.

Abstract

Introduction: Although many white matter tracts underlying language functions have been identified, even in aggregate they do not provide a sufficiently detailed and expansive picture to enable us to fully understand the computational processes that might underly language production and comprehension. We employed diffusion tensor tractography (DTT) with a tensor distribution model to more extensively explore the white matter tracts supporting core language functions. Our study was guided by hypotheses stemming largely from the aphasia literature.

Methods: We employed high angular resolution diffusion imaging (HARDI) with a dual region of interest tractography approach. Our diffusion tensor distribution model uses a mixture of Wishart distributions to estimate the water molecule displacement probability functions on a voxel-by-voxel basis and to model crossing/branching fibers using a multicompartmental approach.

Results: We replicated the results of previously published studies of tracts underlying language function. Our study also yielded a number of novel findings: 1) extensive connectivity between Broca's region and the entirety of the middle and superior frontal gyri; 2) extensive interconnectivity between the four subcomponents of Broca's region, pars orbitalis, pars triangularis, pars opercularis, and the inferior precentral gyrus; 3) connectivity between the mid-superior temporal gyrus and the transverse gyrus; 4) connectivity between the mid-superior temporal gyrus, the transverse gyrus, and the planum temporale and the inferior and middle temporal gyri; and 5) connectivity between mid- and anterior superior temporal gyrus and all components of Broca's region.

Discussion: These results, which replicate the results of prior DTT studies, also considerably extend them and thereby provide a fuller picture of the structural basis of language function and the basis for a novel model of the neural network architecture of language function. This new model is entirely consistent with discoveries from the aphasia literature and with parallel distributed processing conceptualizations of language function.