| Autor: |
Kumbhare D; Department of Neurosurgery, Virginia Commonwealth University Health System, Richmond, VA, United States.; McGuire Research Institute, Hunter Holmes McGuire VA Medical Center, Richmond, VA, United States., Palys V; Department of Neurosurgery, Virginia Commonwealth University Health System, Richmond, VA, United States.; Department of Neurosurgery, University of Arkansas for Medical Sciences, Little Rock, AR, United States., Toms J; Department of Neurosurgery, Virginia Commonwealth University Health System, Richmond, VA, United States.; Southeast PD Research, Education and Clinical Center, Hunter Holmes McGuire VA Medical Center, Richmond, VA, United States., Wickramasinghe CS; Department of Computer Science, Virginia Commonwealth University, Richmond, VA, United States., Amarasinghe K; Department of Computer Science, Virginia Commonwealth University, Richmond, VA, United States., Manic M; Department of Computer Science, Virginia Commonwealth University, Richmond, VA, United States., Hughes E; School of Medicine, Virginia Commonwealth University, Richmond, VA, United States., Holloway KL; Department of Neurosurgery, Virginia Commonwealth University Health System, Richmond, VA, United States.; Southeast PD Research, Education and Clinical Center, Hunter Holmes McGuire VA Medical Center, Richmond, VA, United States. |
| Abstrakt: |
Deep brain stimulation (DBS) of nucleus basalis of Meynert (NBM) is currently being evaluated as a potential therapy to improve memory and overall cognitive function in dementia. Although, the animal literature has demonstrated robust improvement in cognitive functions, phase 1 trial results in humans have not been as clear-cut. We hypothesize that this may reflect differences in electrode location within the NBM, type and timing of stimulation, and the lack of a biomarker for determining the stimulation's effectiveness in real time. In this article, we propose a methodology to address these issues in an effort to effectively interface with this powerful cognitive nucleus for the treatment of dementia. Specifically, we propose the use of diffusion tensor imaging to identify the nucleus and its tracts, quantitative electroencephalography (QEEG) to identify the physiologic response to stimulation during programming, and investigation of stimulation parameters that incorporate the phase locking and cross frequency coupling of gamma and slower oscillations characteristic of the NBM's innate physiology. We propose that modulating the baseline gamma burst stimulation frequency, specifically with a slower rhythm such as theta or delta will pose more effective coupling between NBM and different cortical regions involved in many learning processes. |
