Local field potential signal transmission is correlated with the fractional anisotropy measured by diffusion tractography.

Abstract

In this paper we aim to examine the correlation between diffusion tensor imaging parameters of anatomical connectivity and characteristics of signal transmission obtained from patient-specific transfer function models. Here, we focused on elucidating the correlation between structural and functional neural connectivity within a cohort of pediatric patients diagnosed with dystonia. Diffusion tractography images were obtained from 12 patients with dystonia prior to the deep brain stimulation surgery. For each patient, we processed the imaging data to estimate anatomical measures including fractional anisotropy, axial diffusivity, number of fibre tracts per unit area, and fibre tract length. After the implantation of temporary depth leads for each patient as part of their treatment plan, intracranial signals were recorded. Transfer function models of local field potential recordings and the corresponding measures of functional connectivity were computed for each patient. Linear mixed effect analysis was then employed to determine the relationship between transfer function measures and diffusion tractography parameters. Our results illustrate a positive correlation between fractional anisotropy, AD, and intrinsic neural transmission measures, representing amplification and spread of intrinsic neural oscillations, obtained from the transfer functions models. However, no significant correlation was found between the functional connectivity and number of fibre tracts or fibre lengths. Our findings suggest that white matter integrity, as measured by fractional anisotropy and AD, can potentially reflect the amplification and spread of intrinsic brain signals throughout the network. This study underscores the significant relationship between structural and functional connectivity, offering valuable insights into propagation of neural activity in the brain network and potential implications for optimizing non-invasive treatments and planning for neurological disorders.