PMID- 33052884
OWN - NLM
STAT- MEDLINE
DCOM- 20210623
LR  - 20220112
IS  - 1741-2552 (Electronic)
IS  - 1741-2552 (Linking)
VI  - 17
IP  - 5
DP  - 2020 Oct 14
TI  - Deep brain stimulation: a review of the open neural engineering challenges.
PG  - 051002
LID - 10.1088/1741-2552/abb581 [doi]
AB  - OBJECTIVE: Deep brain stimulation (DBS) is an established and valid therapy for a 
      variety of pathological conditions ranging from motor to cognitive disorders. 
      Still, much of the DBS-related mechanism of action is far from being understood, 
      and there are several side effects of DBS whose origin is unclear. In the last 
      years DBS limitations have been tackled by a variety of approaches, including 
      adaptive deep brain stimulation (aDBS), a technique that relies on using 
      chronically implanted electrodes on 'sensing mode' to detect the neural markers 
      of specific motor symptoms and to deliver on-demand or modulate the stimulation 
      parameters accordingly. Here we will review the state of the art of the several 
      approaches to improve DBS and summarize the main challenges toward the 
      development of an effective aDBS therapy. APPROACH: We discuss models of basal 
      ganglia disorders pathogenesis, hardware and software improvements for 
      conventional DBS, and candidate neural and non-neural features and related 
      control strategies for aDBS. MAIN RESULTS: We identify then the main operative 
      challenges toward optimal DBS such as (i) accurate target localization, (ii) 
      increased spatial resolution of stimulation, (iii) development of in silico tests 
      for DBS, (iv) identification of specific motor symptoms biomarkers, in particular 
      (v) assessing how LFP oscillations relate to behavioral disfunctions, and (vi) 
      clarify how stimulation affects the cortico-basal-ganglia-thalamic network to 
      (vii) design optimal stimulation patterns. SIGNIFICANCE: This roadmap will lead 
      neural engineers novel to the field toward the most relevant open issues of DBS, 
      while the in-depth readers might find a careful comparison of advantages and 
      drawbacks of the most recent attempts to improve DBS-related neuromodulatory 
      strategies.
FAU - Vissani, Matteo
AU  - Vissani M
AD  - The BioRobotics Institute, Scuola Superiore Sant'Anna, 56025 Pisa, Italy.
AD  - Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56025 
      Pisa, Italy.
FAU - Isaias, Ioannis U
AU  - Isaias IU
AD  - Department of Neurology, University Hospital Wurzburg, Wurzburg, Germany.
FAU - Mazzoni, Alberto
AU  - Mazzoni A
AUID- ORCID: 0000-0002-9632-1831
AD  - The BioRobotics Institute, Scuola Superiore Sant'Anna, 56025 Pisa, Italy.
AD  - Department of Excellence in Robotics and AI, Scuola Superiore Sant'Anna, 56025 
      Pisa, Italy.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PT  - Review
DEP - 20201014
PL  - England
TA  - J Neural Eng
JT  - Journal of neural engineering
JID - 101217933
SB  - IM
MH  - *Basal Ganglia
MH  - *Deep Brain Stimulation
MH  - Electrodes, Implanted
MH  - Thalamus
EDAT- 2020/10/15 06:00
MHDA- 2021/06/24 06:00
CRDT- 2020/10/14 17:59
PHST- 2020/10/14 17:59 [entrez]
PHST- 2020/10/15 06:00 [pubmed]
PHST- 2021/06/24 06:00 [medline]
AID - 10.1088/1741-2552/abb581 [doi]
PST - epublish
SO  - J Neural Eng. 2020 Oct 14;17(5):051002. doi: 10.1088/1741-2552/abb581.