Literature DB >> 16189972

Visual spatial attention control in an independent brain-computer interface.

Simon P Kelly1, Edmund C Lalor, Ciarán Finucane, Gary McDarby, Richard B Reilly.   

Abstract

This paper presents a novel brain computer interface (BCI) design employing visual evoked potential (VEP) modulations in a paradigm involving no dependency on peripheral muscles or nerves. The system utilizes electrophysiological correlates of visual spatial attention mechanisms, the self-regulation of which is naturally developed through continuous application in everyday life. An interface involving real-time biofeedback is described, demonstrating reduced training time in comparison to existing BCIs based on self-regulation paradigms. Subjects were cued to covertly attend to a sequence of letters superimposed on a flicker stimulus in one visual field while ignoring a similar stimulus of a different flicker frequency in the opposite visual field. Classification of left/right spatial attention is achieved by extracting steady-state visual evoked potentials (SSVEPs) elicited by the stimuli. Six out of eleven physically and neurologically healthy subjects demonstrate reliable control in binary decision-making, achieving at least 75% correct selections in at least one of only five sessions, each of approximately 12-min duration. The highest-performing subject achieved over 90% correct selections in each of four sessions. This independent BCI may provide a new method of real-time interaction for those with little or no peripheral control, with the added advantage of requiring only brief training.

Mesh:

Year:  2005        PMID: 16189972     DOI: 10.1109/TBME.2005.851510

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  23 in total

Review 1.  Brain-computer interfaces in medicine.

Authors:  Jerry J Shih; Dean J Krusienski; Jonathan R Wolpaw
Journal:  Mayo Clin Proc       Date:  2012-02-10       Impact factor: 7.616

2.  High-speed spelling with a noninvasive brain-computer interface.

Authors:  Xiaogang Chen; Yijun Wang; Masaki Nakanishi; Xiaorong Gao; Tzyy-Ping Jung; Shangkai Gao
Journal:  Proc Natl Acad Sci U S A       Date:  2015-10-19       Impact factor: 11.205

3.  Towards an independent brain-computer interface using steady state visual evoked potentials.

Authors:  Brendan Z Allison; Dennis J McFarland; Gerwin Schalk; Shi Dong Zheng; Melody Moore Jackson; Jonathan R Wolpaw
Journal:  Clin Neurophysiol       Date:  2008-02       Impact factor: 3.708

Review 4.  Guidelines for Feature Matching Assessment of Brain-Computer Interfaces for Augmentative and Alternative Communication.

Authors:  Kevin M Pitt; Jonathan S Brumberg
Journal:  Am J Speech Lang Pathol       Date:  2018-08-06       Impact factor: 2.408

5.  Oscillatory alpha-band mechanisms and the deployment of spatial attention to anticipated auditory and visual target locations: supramodal or sensory-specific control mechanisms?

Authors:  Snigdha Banerjee; Adam C Snyder; Sophie Molholm; John J Foxe
Journal:  J Neurosci       Date:  2011-07-06       Impact factor: 6.167

6.  Clinical Applications of Brain-Computer Interfaces: Current State and Future Prospects.

Authors:  Joseph N Mak; Jonathan R Wolpaw
Journal:  IEEE Rev Biomed Eng       Date:  2009

7.  Neurofeedback training of gamma band oscillations improves perceptual processing.

Authors:  Neda Salari; Christian Büchel; Michael Rose
Journal:  Exp Brain Res       Date:  2014-07-04       Impact factor: 1.972

8.  Brain state-triggered stimulus delivery: An efficient tool for probing ongoing brain activity.

Authors:  M L Andermann; J Kauramäki; T Palomäki; C I Moore; R Hari; I P Jääskeläinen; M Sams
Journal:  Open J Neurosci       Date:  2012-09-29

9.  Exploiting individual primary visual cortex geometry to boost steady state visual evoked potentials.

Authors:  M Isabel Vanegas; Annabelle Blangero; Simon P Kelly
Journal:  J Neural Eng       Date:  2013-04-03       Impact factor: 5.379

Review 10.  A survey of stimulation methods used in SSVEP-based BCIs.

Authors:  Danhua Zhu; Jordi Bieger; Gary Garcia Molina; Ronald M Aarts
Journal:  Comput Intell Neurosci       Date:  2010-03-07
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.