Topography of Hippocampal Connectivity with Sensorimotor Cortex Revealed by Optimizing Smoothing Kernel and Voxel Size

Abstract

Evaluating hippocampal connectivity across task conditions can be challenging, especially in the absence of activation to select the size and location of seeds; furthermore, optimal analysis parameters are unknown. Hippocampal task-specific connectivity with sensorimotor cortex was identified from psychophysiological interactions (PPI) during volitional movements; connectivity from a structural seed represented the mean of connectivity maps from all voxels in a hippocampal region, whereas connectivity from a functional seed represented maximal connectivity from an individual voxel. Motor activation and hippocampal connectivity were both evaluated across different processing parameters (3mm vs. 4mm isovoxels, smoothing kernels of 6-10mm). Topography in hippocampal connectivity was apparent along both its longitudinal axis and mediolateral axis, but only with optimal processing. Larger voxels improved signal-to-noise during individual and group analyses, lowering the statistical threshold and increasing the area of activation. The 10mm smoothing kernel was optimal for detecting connectivity from structural seeds, whereas the size of the smoothing kernel had little effect on connectivity from functional seeds. Unlike other approaches, structural seeds in this study allowed task-related connectivity to be examined throughout the hippocampus. By optimizing processing parameters, topography in hippocampal connectivity became demonstrable from both structural seeds and individual voxels. Larger voxels and smoothing kernels improved sensitivity for detecting activation and hippocampal connectivity, with the use of structural / functional seeds uncovering details about the topography of its functional connections.