Literature DB >> 17234696

Brain-computer interfaces: communication and restoration of movement in paralysis.

Niels Birbaumer1, Leonardo G Cohen.   

Abstract

The review describes the status of brain-computer or brain-machine interface research. We focus on non-invasive brain-computer interfaces (BCIs) and their clinical utility for direct brain communication in paralysis and motor restoration in stroke. A large gap between the promises of invasive animal and human BCI preparations and the clinical reality characterizes the literature: while intact monkeys learn to execute more or less complex upper limb movements with spike patterns from motor brain regions alone without concomitant peripheral motor activity usually after extensive training, clinical applications in human diseases such as amyotrophic lateral sclerosis and paralysis from stroke or spinal cord lesions show only limited success, with the exception of verbal communication in paralysed and locked-in patients. BCIs based on electroencephalographic potentials or oscillations are ready to undergo large clinical studies and commercial production as an adjunct or a major assisted communication device for paralysed and locked-in patients. However, attempts to train completely locked-in patients with BCI communication after entering the complete locked-in state with no remaining eye movement failed. We propose that a lack of contingencies between goal directed thoughts and intentions may be at the heart of this problem. Experiments with chronically curarized rats support our hypothesis; operant conditioning and voluntary control of autonomic physiological functions turned out to be impossible in this preparation. In addition to assisted communication, BCIs consisting of operant learning of EEG slow cortical potentials and sensorimotor rhythm were demonstrated to be successful in drug resistant focal epilepsy and attention deficit disorder. First studies of non-invasive BCIs using sensorimotor rhythm of the EEG and MEG in restoration of paralysed hand movements in chronic stroke and single cases of high spinal cord lesions show some promise, but need extensive evaluation in well-controlled experiments. Invasive BMIs based on neuronal spike patterns, local field potentials or electrocorticogram may constitute the strategy of choice in severe cases of stroke and spinal cord paralysis. Future directions of BCI research should include the regulation of brain metabolism and blood flow and electrical and magnetic stimulation of the human brain (invasive and non-invasive). A series of studies using BOLD response regulation with functional magnetic resonance imaging (fMRI) and near infrared spectroscopy demonstrated a tight correlation between voluntary changes in brain metabolism and behaviour.

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Mesh:

Year:  2007        PMID: 17234696      PMCID: PMC2151357          DOI: 10.1113/jphysiol.2006.125633

Source DB:  PubMed          Journal:  J Physiol        ISSN: 0022-3751            Impact factor:   5.182


  61 in total

1.  A spelling device for the paralysed.

Authors:  N Birbaumer; N Ghanayim; T Hinterberger; I Iversen; B Kotchoubey; A Kübler; J Perelmouter; E Taub; H Flor
Journal:  Nature       Date:  1999-03-25       Impact factor: 49.962

2.  Forebrain inhibitory mechanisms: cortical synchronization induced by basal forebrain stimulation.

Authors:  M B STERMAN; C D CLEMENTE
Journal:  Exp Neurol       Date:  1962-08       Impact factor: 5.330

Review 3.  Slow potentials of the cerebral cortex and behavior.

Authors:  N Birbaumer; T Elbert; A G Canavan; B Rockstroh
Journal:  Physiol Rev       Date:  1990-01       Impact factor: 37.312

4.  Memory performance and area-specific self-regulation of slow cortical potentials: dual-task interference.

Authors:  W Lutzenberger; L E Roberts; N Birbaumer
Journal:  Int J Psychophysiol       Date:  1993-11       Impact factor: 2.997

5.  Failure to replicate visceral learning in the acute curarized rat preparation.

Authors:  B R Dworkin; N E Miller
Journal:  Behav Neurosci       Date:  1986-06       Impact factor: 1.912

6.  Cortical self-regulation in patients with epilepsies.

Authors:  B Rockstroh; T Elbert; N Birbaumer; P Wolf; A Düchting-Röth; M Reker; I Daum; W Lutzenberger; J Dichgans
Journal:  Epilepsy Res       Date:  1993-01       Impact factor: 3.045

7.  Behavioral treatment of scoliosis and kyphosis.

Authors:  N Birbaumer; H Flor; B Cevey; B Dworkin; N E Miller
Journal:  J Psychosom Res       Date:  1994-08       Impact factor: 3.006

8.  Self-regulation of slow cortical potentials in psychiatric patients: schizophrenia.

Authors:  F Schneider; B Rockstroh; H Heimann; W Lutzenberger; R Mattes; T Elbert; N Birbaumer; M Bartels
Journal:  Biofeedback Self Regul       Date:  1992-12

9.  Area-specific self-regulation of slow cortical potentials on the sagittal midline and its effects on behavior.

Authors:  N Birbaumer; L E Roberts; W Lutzenberger; B Rockstroh; T Elbert
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1992 Jul-Aug

10.  Comparison of the efficacy of electromyographic biofeedback, cognitive-behavioral therapy, and conservative medical interventions in the treatment of chronic musculoskeletal pain.

Authors:  H Flor; N Birbaumer
Journal:  J Consult Clin Psychol       Date:  1993-08
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  143 in total

Review 1.  A brief history of the resting state: the Washington University perspective.

Authors:  Abraham Z Snyder; Marcus E Raichle
Journal:  Neuroimage       Date:  2012-01-12       Impact factor: 6.556

2.  Does the 'P300' speller depend on eye gaze?

Authors:  P Brunner; S Joshi; S Briskin; J R Wolpaw; H Bischof; G Schalk
Journal:  J Neural Eng       Date:  2010-09-21       Impact factor: 5.379

3.  Decoding and cortical source localization for intended movement direction with MEG.

Authors:  Wei Wang; Gustavo P Sudre; Yang Xu; Robert E Kass; Jennifer L Collinger; Alan D Degenhart; Anto I Bagic; Douglas J Weber
Journal:  J Neurophysiol       Date:  2010-08-25       Impact factor: 2.714

Review 4.  Volitional control of neural activity: implications for brain-computer interfaces.

Authors:  Eberhard E Fetz
Journal:  J Physiol       Date:  2007-01-18       Impact factor: 5.182

5.  Information Theoretic Feature Transformation Learning for Brain Interfaces.

Authors:  Ozan Ozdenizci; Deniz Erdogmus
Journal:  IEEE Trans Biomed Eng       Date:  2019-03-28       Impact factor: 4.538

Review 6.  The development of brain-machine interface neuroprosthetic devices.

Authors:  Parag G Patil; Dennis A Turner
Journal:  Neurotherapeutics       Date:  2008-01       Impact factor: 7.620

7.  Automated classification of fMRI data employing trial-based imagery tasks.

Authors:  Jong-Hwan Lee; Matthew Marzelli; Ferenc A Jolesz; Seung-Schik Yoo
Journal:  Med Image Anal       Date:  2009-01-16       Impact factor: 8.545

8.  Brain-machine interfaces and transcranial stimulation: future implications for directing functional movement and improving function after spinal injury in humans.

Authors:  Jose M Carmena; Leonardo G Cohen
Journal:  Handb Clin Neurol       Date:  2012

9.  Brain-machine interface in chronic stroke rehabilitation: a controlled study.

Authors:  Ander Ramos-Murguialday; Doris Broetz; Massimiliano Rea; Leonhard Läer; Ozge Yilmaz; Fabricio L Brasil; Giulia Liberati; Marco R Curado; Eliana Garcia-Cossio; Alexandros Vyziotis; Woosang Cho; Manuel Agostini; Ernesto Soares; Surjo Soekadar; Andrea Caria; Leonardo G Cohen; Niels Birbaumer
Journal:  Ann Neurol       Date:  2013-08-07       Impact factor: 10.422

Review 10.  Neural interface technology for rehabilitation: exploiting and promoting neuroplasticity.

Authors:  Wei Wang; Jennifer L Collinger; Monica A Perez; Elizabeth C Tyler-Kabara; Leonardo G Cohen; Niels Birbaumer; Steven W Brose; Andrew B Schwartz; Michael L Boninger; Douglas J Weber
Journal:  Phys Med Rehabil Clin N Am       Date:  2010-02       Impact factor: 1.784

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