Replication Data For: Spiking patterns in the globus pallidus highlight convergent neural dynamics across diverse genetic dystonia syndromes

Human Globus Pallidum Single-Unit Activity Dataset in Genetic Dystonia Patients

This dataset consists of tabular data encompassing diverse neural features extracted from spiking trains of stable single-unit activity. These units were isolated from raw microelectrode recordings obtained from the globus pallidum of genetic dystonia patients who underwent globus pallidus internal (GPi) deep brain stimulation (DBS) surgery. The dataset includes anonymized patient IDs, details about the patient's genetic dystonia mutation, as well as information on the hemisphere and depth of microelectrode recordings (MER). Additionally, it features neural properties such as firing rate, spiking regularity, neural bursts, oscillations, and pause characteristics of isolated single-unit activities (SUAs).

To process the raw MER, we applied a semi-parametric offline spike sorting algorithm to isolate SUAs. The SUAs were analyzed both in the temporal and frequency domains to derive a comprehensive set of features related to spiking patterns.

For those interested in replicating or understanding the feature extraction process, the MATLAB source code is available in the Github repository.