English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Deep Brain Stimulation (DBS) has been successfully used to treat patients with Parkinson’s Disease. DBS employs an electrode that regulates the oscillatory activity of the basal ganglia, such as the subthalamic nucleus (STN). A critical point during the surgical implantation of such electrode is the precise localization of the target. This is done using presurgical images, stereotactic frames, and microelectrode recordings (MER). The latter allows neurophysiologists to visualize the electrical activity of different structures along the surgical track, each of them with well-defined variations in the frequency pattern; however, this is far from an automatic or semi-automatic method to help these specialists make decisions concerning the surgical target. To pave the way to automation, we analyzed three frequency bands in MER signals acquired from 11 patients undergoing DBS: beta (13-40 Hz), gamma (40-200 Hz), and high-frequency oscillations (HFO – 201-400 Hz). In this study, we propose and assess five indexes in order to detect the STN: variations in autoregressive parameters and their derivative along the surgical track, the energy of each band calculated using the Yule-Walker power spectral density, the high-to-low (H/L) ratio, and its derivative. We found that the derivative of one parameter of the beta band and the H/L ratio of the HFO/gamma bands produced errors in STN targeting like those reported in the literature produced by image-based methods (&lt;2 mm). Although the indexes introduced here are simple to compute and could be applied in real time, further studies must be conducted to be able to generalize their results.

Beta, gamma and High-Frequency Oscillation characterization for targeting in Deep Brain Stimulation procedures