Literature DB >> 21867795

Deep brain stimulation: BCI at large, where are we going to?

Alim Louis Benabid1, Thomas Costecalde, Napoleon Torres, Cecile Moro, Tetiana Aksenova, Andrey Eliseyev, Guillaume Charvet, Fabien Sauter, David Ratel, Corinne Mestais, Pierre Pollak, Stephan Chabardes.   

Abstract

UNLABELLED: Brain-computer interfaces (BCIs) include stimulators, infusion devices, and neuroprostheses. They all belong to functional neurosurgery. Deep brain stimulators (DBS) are widely used for therapy and are in need of innovative evolutions. Robotized exoskeletons require BCIs able to drive up to 26 degrees of freedom (DoF). We report the nanomicrotechnology development of prototypes for new 3D DBS and for motor neuroprostheses. For this complex project, all compounds have been designed and are being tested. Experiments were performed in rats and primates for proof of concepts and development of the electroencephalogram (EEG) recognition algorithm.
METHODS: Various devices have been designed. (A) In human, a programmable multiplexer connecting five tetrapolar (20 contacts) electrodes to one DBS channel has been designed and implanted bilaterally into STN in two Parkinsonian patients. (B) A 50-mm diameter titanium implant, telepowered, including a radioset, emitting ECoG data recorded by a 64-electrode array using an application-specific integrated circuit, is being designed to be implanted in a 50-mm trephine opening. Data received by the radioreceiver are processed through an original wavelet-based Iterative N-way Partial Least Square algorithm (INPLS, CEA patent). Animals, implanted with ECoG recording electrodes, had to press a lever to obtain a reward. The brain signature associated to the lever press (LP) was detected online by ECoG processing using INPLS. This detection allowed triggering the food dispenser.
RESULTS: (A) The 3D multiplexer allowed tailoring the electrical field to the STN. The multiplication of the contacts affected the battery life and suggested different implantation schemes. (B) The components of the human implantable cortical BCI are being tested for reliability and toxicology to meet criteria for chronicle implantation in 2012. (C) In rats, the algorithm INPLS could detect the cortical signature with an accuracy of about 80% of LPs on the electrodes with the best correlation coefficient (located over the cerebellar cortex), 1% of the algorithm decisions were false positives. We aim to pilot effectors with DoF up to 3 in monkeys.
CONCLUSION: We have designed multielectrodes wireless implants to open the way for BCI ECoG-driven effectors. These technologies are also used to develop new generations of brain stimulators, either cortical or for deep targets. This chapter is aimed at illustrating that BCIs are actually the daily background of DBS, that the evolution of the method involves a growing multiplicity of targets and indications, that new technologies make possible and simpler than before to design innovative solutions to improve DBS methodology, and that the coming out of BCI-driven neuroprostheses for compensation of motor and sensory deficits is a natural evolution of functional neurosurgery.
Copyright © 2011 Elsevier B.V. All rights reserved.

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Year:  2011        PMID: 21867795     DOI: 10.1016/B978-0-444-53815-4.00016-9

Source DB:  PubMed          Journal:  Prog Brain Res        ISSN: 0079-6123            Impact factor:   2.453


  4 in total

Review 1.  Deep brain stimulation (DBS) at the interface of neurology and psychiatry.

Authors:  Nolan R Williams; Michael S Okun
Journal:  J Clin Invest       Date:  2013-11-01       Impact factor: 14.808

2.  Neurosurgery and the dawning age of Brain-Machine Interfaces.

Authors:  Nathan C Rowland; Jonathan Breshears; Edward F Chang
Journal:  Surg Neurol Int       Date:  2013-03-19

3.  Recursive Exponentially Weighted N-way Partial Least Squares Regression with Recursive-Validation of Hyper-Parameters in Brain-Computer Interface Applications.

Authors:  Andrey Eliseyev; Vincent Auboiroux; Thomas Costecalde; Lilia Langar; Guillaume Charvet; Corinne Mestais; Tetiana Aksenova; Alim-Louis Benabid
Journal:  Sci Rep       Date:  2017-11-24       Impact factor: 4.379

4.  Penalized Multi-Way Partial Least Squares for Smooth Trajectory Decoding from Electrocorticographic (ECoG) Recording.

Authors:  Andrey Eliseyev; Tetiana Aksenova
Journal:  PLoS One       Date:  2016-05-19       Impact factor: 3.240

  4 in total

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