Associative Plasticity Induced by a Brain-Computer Interface Based on Movement-Related Cortical Potentials

Natalie Mrachacz Kersting; Ning Jiang; Kim Dremstrup; Dario Farina

doi:10.1201/9781351231954-35

Associative Plasticity Induced by a Brain-Computer Interface Based on Movement-Related Cortical Potentials

Natalie Mrachacz Kersting, Ning Jiang, Kim Dremstrup, Dario Farina

Research output: Contribution to book/anthology/report/conference proceeding › Book chapter › Research › peer-review

2 Citations (Scopus)

Abstract

This chapter presents the basic concepts of a brain-computer-interface (BCI) designed for neuromodulation that is based on known theories of memory storage and learning. Initially, an overview is provided of the control signal, the movement-related cortical potential (MRCP), its advantages over other signal modalities, and its neural generators. This is followed by a detailed account of factors that affect the MRCP morphology such as task parameters, shifts in user attention and plasticity, and insights into algorithm design for both detection and classification in an online self-paced BCI. Finally, the applications of this type of associative BCI to more complex tasks such as human gait and in the clinical environment with patients are presented.

Original language	English
Title of host publication	Brain-Computer Interfaces Handbook : Technological and Theoretical Advances
Number of pages	16
Publisher	CRC Press
Publication date	1 Jan 2018
Pages	669-684
ISBN (Print)	9780367375454
ISBN (Electronic)	9781351231947
DOIs	https://doi.org/10.1201/9781351231954-35
Publication status	Published - 1 Jan 2018

Bibliographical note

Publisher Copyright:
© 2018 by Taylor & Francis Group, LLC.

Access to Document

10.1201/9781351231954-35

AUB Link

Search for the material in Aalborg University Library's search engine

Cite this

@inbook{6d446d5815b7441aa59fc5fbd9988479,

title = "Associative Plasticity Induced by a Brain-Computer Interface Based on Movement-Related Cortical Potentials",

abstract = "This chapter presents the basic concepts of a brain-computer-interface (BCI) designed for neuromodulation that is based on known theories of memory storage and learning. Initially, an overview is provided of the control signal, the movement-related cortical potential (MRCP), its advantages over other signal modalities, and its neural generators. This is followed by a detailed account of factors that affect the MRCP morphology such as task parameters, shifts in user attention and plasticity, and insights into algorithm design for both detection and classification in an online self-paced BCI. Finally, the applications of this type of associative BCI to more complex tasks such as human gait and in the clinical environment with patients are presented.",

author = "Kersting, {Natalie Mrachacz} and Ning Jiang and Kim Dremstrup and Dario Farina",

note = "Publisher Copyright: {\textcopyright} 2018 by Taylor & Francis Group, LLC.",

year = "2018",

month = jan,

day = "1",

doi = "10.1201/9781351231954-35",

language = "English",

isbn = "9780367375454",

pages = "669--684",

booktitle = "Brain-Computer Interfaces Handbook",

publisher = "CRC Press",

}

Associative Plasticity Induced by a Brain-Computer Interface Based on Movement-Related Cortical Potentials. / Kersting, Natalie Mrachacz; Jiang, Ning; Dremstrup, Kim et al.
Brain-Computer Interfaces Handbook: Technological and Theoretical Advances. CRC Press, 2018. p. 669-684.

Research output: Contribution to book/anthology/report/conference proceeding › Book chapter › Research › peer-review

TY - CHAP

T1 - Associative Plasticity Induced by a Brain-Computer Interface Based on Movement-Related Cortical Potentials

AU - Kersting, Natalie Mrachacz

AU - Jiang, Ning

AU - Dremstrup, Kim

AU - Farina, Dario

PY - 2018/1/1

Y1 - 2018/1/1

N2 - This chapter presents the basic concepts of a brain-computer-interface (BCI) designed for neuromodulation that is based on known theories of memory storage and learning. Initially, an overview is provided of the control signal, the movement-related cortical potential (MRCP), its advantages over other signal modalities, and its neural generators. This is followed by a detailed account of factors that affect the MRCP morphology such as task parameters, shifts in user attention and plasticity, and insights into algorithm design for both detection and classification in an online self-paced BCI. Finally, the applications of this type of associative BCI to more complex tasks such as human gait and in the clinical environment with patients are presented.

AB - This chapter presents the basic concepts of a brain-computer-interface (BCI) designed for neuromodulation that is based on known theories of memory storage and learning. Initially, an overview is provided of the control signal, the movement-related cortical potential (MRCP), its advantages over other signal modalities, and its neural generators. This is followed by a detailed account of factors that affect the MRCP morphology such as task parameters, shifts in user attention and plasticity, and insights into algorithm design for both detection and classification in an online self-paced BCI. Finally, the applications of this type of associative BCI to more complex tasks such as human gait and in the clinical environment with patients are presented.

UR - http://www.scopus.com/inward/record.url?scp=85093744954&partnerID=8YFLogxK

U2 - 10.1201/9781351231954-35

DO - 10.1201/9781351231954-35

M3 - Book chapter

AN - SCOPUS:85093744954

SN - 9780367375454

SP - 669

EP - 684

BT - Brain-Computer Interfaces Handbook

PB - CRC Press

ER -

Associative Plasticity Induced by a Brain-Computer Interface Based on Movement-Related Cortical Potentials

Abstract

Bibliographical note

Access to Document

AUB Link

Other files and links

Fingerprint

Cite this