Peripheral Nerve Activation Evokes Machine-Learnable Signals in the Dorsal Column Nuclei.

ABSTRACT: The brainstem dorsal column nuclei (DCN) are essential to inform the brain of tactile and proprioceptive events experienced by the body. However, little is known about how ascending somatosensory information is represented in the DCN. Our objective was to investigate the usefulness of high-frequency (HF) and low-frequency (LF) DCN signal features (SFs) in predicting the nerve from which signals were evoked. We also aimed to explore the robustness of DCN SFs and map their relative information content across the brainstem surface. DCN surface potentials were recorded from urethane-anesthetized Wistar rats during sural and peroneal nerve electrical stimulation. Five salient SFs were extracted from each recording electrode of a seven-electrode array. We used a machine learning approach to quan

SUBMITTER: Loutit AJ 

PROVIDER: S-EPMC6448039 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature