Logo image
Adaptive deep brain stimulation (aDBS) controlled by local field potential oscillations
Journal article   Peer reviewed

Adaptive deep brain stimulation (aDBS) controlled by local field potential oscillations

Alberto Priori, Guglielmo Foffani, Lorenzo Rossi and Sara Marceglia
Experimental neurology, v 245
01 Jul 2013
PMID: 23022916

Abstract

Life Sciences & Biomedicine Neurosciences Neurosciences & Neurology Science & Technology
Despite their proven efficacy in treating neurological disorders, especially Parkinson's disease, deep brain stimulation COBS) systems could be further optimized to maximize treatment benefits. In particular, because current open-loop DBS strategies based on fixed stimulation settings leave the typical parkinsonian motor fluctuations and rapid symptom variations partly uncontrolled, research has for several years focused on developing novel "closed-loop" or "adaptive" DBS (aDBS) systems. aDBS consists of a simple closed-loop model designed to measure and analyze a control variable reflecting the patient's clinical condition to elaborate new stimulation settings and send them to an "intelligent" implanted stimulator. The major problem in developing an aDBS system is choosing the ideal control variable for feedback. Here we review current evidence on the advantages of neurosignal-controlled aDBS that uses local field potentials (LFPs) as a control variable, and describe the technology already available to create new aDBS systems, and the potential benefits of aDBS for patients with Parkinson's disease. (C) 2012 Published by Elsevier Inc.

Metrics

14 Record Views
267 citations in Scopus

Details

UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

InCites Highlights

Data related to this publication, from InCites Benchmarking & Analytics tool:

Collaboration types
Domestic collaboration
International collaboration
Web of Science research areas
Neurosciences
Logo image