Evidence map›Paper›PMID 25009455›Full record

ArticleFrontiers in neuroscience2014

A neurochemical closed-loop controller for deep brain stimulation: toward individualized smart neuromodulation therapies.

Peter J Grahn, Grant W Mallory, Obaid U Khurram, B Michael Berry, Jan T Hachmann, Allan J Bieber, Kevin E Bennet, Hoon-Ki Min, Su-Youne Chang, Kendall H Lee and 1 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing papers in PubMed
10.1field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

52 citing papers in PubMed, 158 citations in OpenAlex.

  1. Review
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  9. Flexible and Stretchable Bioelectronics.Materials (Basel, Switzerland) · 2022
    Review
  10. Review
  11. Article
  12. Deep brain stimulation in Huntington's disease: a literature review.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2021
    Review
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  14. Article
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  16. Article
  17. Evaluation of electrochemical methods for tonic dopamine detectionTrends in analytical chemistry : TRAC · 2020
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 1 country.

Peter J GrahnMayo Clinic College of Medicine, Mayo Clinic Rochester, MN, USA.
Grant W MalloryDepartment of Neurologic Surgery, Mayo Clinic Rochester, MN, USA.
Obaid U KhurramMayo Clinic College of Medicine, Mayo Clinic Rochester, MN, USA.
B Michael BerryMayo Clinic College of Medicine, Mayo Clinic Rochester, MN, USA.
Jan T HachmannDepartment of Neurologic Surgery, Mayo Clinic Rochester, MN, USA.
Allan J BieberDepartment of Neurologic Surgery, Mayo Clinic Rochester, MN, USA ; Department of Neurology, Mayo Clinic Rochester, MN, USA.
Kevin E BennetDepartment of Neurologic Surgery, Mayo Clinic Rochester, MN, USA ; Division of Engineering, Mayo Clinic Rochester, MN, USA.
Hoon-Ki MinDepartment of Neurologic Surgery, Mayo Clinic Rochester, MN, USA ; Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, MN, USA.
Su-Youne ChangDepartment of Neurologic Surgery, Mayo Clinic Rochester, MN, USA.
Kendall H LeeDepartment of Neurologic Surgery, Mayo Clinic Rochester, MN, USA ; Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, MN, USA.
J L LujanDepartment of Neurologic Surgery, Mayo Clinic Rochester, MN, USA ; Department of Physiology and Biomedical Engineering, Mayo Clinic Rochester, MN, USA.
Mayo Clinic · USMayo Clinic in Arizona · USWinnMed · US

Funding

TRAINING IN TRANSLATIONAL RESEARCH: BENCH TO BEDSIDER25GM055252 · NIGMS · MAYO CLINIC ROCHESTER · PI LUJAN, LUIS, MAHER, LOUIS JAMES · 1996 to 2022
$8.3M
Neurochemical closed-loop controller for smart DBSR01NS084975 · NINDS · MAYO CLINIC ROCHESTER · PI LUJAN, LUIS · 2014 to 2018
$2.0M
WINCS and DBSR01NS070872 · NINDS · MAYO CLINIC ROCHESTER · PI LEE, KENDALL H. · 2011 to 2015
$1.7M
NIGMS NIH HHS R25 GM055252NINDS NIH HHS R01 NS070872NINDS NIH HHS R01 NS084975
6 · The paper itself

Abstract

Current strategies for optimizing deep brain stimulation (DBS) therapy involve multiple postoperative visits. During each visit, stimulation parameters are adjusted until desired therapeutic effects are achieved and adverse effects are minimized. However, the efficacy of these therapeutic parameters may decline with time due at least in part to disease progression, interactions between the host environment and the electrode, and lead migration. As such, development of closed-loop control systems that can respond to changing neurochemical environments, tailoring DBS therapy to individual patients, is paramount for improving the therapeutic efficacy of DBS. Evidence obtained using electrophysiology and imaging techniques in both animals and humans suggests that DBS works by modulating neural network activity. Recently, animal studies have shown that stimulation-evoked changes in neurotransmitter release that mirror normal physiology are associated with the therapeutic benefits of DBS. Therefore, to fully understand the neurophysiology of DBS and optimize its efficacy, it may be necessary to look beyond conventional electrophysiological analyses and characterize the neurochemical effects of therapeutic and non-therapeutic stimulation. By combining electrochemical monitoring and mathematical modeling techniques, we can potentially replace the trial-and-error process used in clinical programming with deterministic approaches that help attain optimal and stable neurochemical profiles. In this manuscript, we summarize the current understanding of electrophysiological and electrochemical processing for control of neuromodulation therapies. Additionally, we describe a proof-of-principle closed-loop controller that characterizes DBS-evoked dopamine changes to adjust stimulation parameters in a rodent model of DBS. The work described herein represents the initial steps toward achieving a "smart" neuroprosthetic system for treatment of neurologic and psychiatric disorders.

Indexed as

deep brain stimulation (DBS)fast scan cyclic voltammetry (FSCV)feedback control systemsindividualized medicinelocal field potentials (LFP)machine learning

Identifiers

PMID25009455
PMCPMC4070176
OpenAlexW2078098979

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.