Functional Mapping of the Brain for Brain–Computer Interfacing: A Review

Author:

Singh Satya P.1,Mishra Sachin23,Gupta Sukrit4,Padmanabhan Parasuraman23ORCID,Jia Lu35,Colin Teo Kok Ann36,Tsai Yeo Tseng6,Kejia Teo6,Sankarapillai Pramod7,Mohan Anand3,Gulyás Balázs238

Affiliation:

1. Centre of Excellence in Artificial Intelligence and Department of ECE, Netaji Subhas University of Technology, New Delhi 110078, India

2. Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore 636921, Singapore

3. Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 636921, Singapore

4. School of Computer Science & Engineering, Nanyang Technological University, Singapore 636921, Singapore

5. DSO National Laboratories (Kent Ridge), 27 Medical Drive, Singapore 117510, Singapore

6. Division of Neurosurgery, Department of Surgery, National University Hospital, National University Health System, 1E Kent Ridge Road, Level 11, Singapore 119228, Singapore

7. Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India

8. Department of Clinical Neuroscience, Karolinska Institute, 17176 Stockholm, Sweden

Abstract

Brain–computer interfacing has been applied in a range of domains including rehabilitation, neuro-prosthetics, and neurofeedback. Neuroimaging techniques provide insight into the structural and functional aspects of the brain. There is a need to identify, map and understand the various structural areas of the brain together with their functionally active roles for the accurate and efficient design of a brain–computer interface. In this review, the functionally active areas of the brain are reviewed by analyzing the research available in the literature on brain–computer interfacing in conjunction with neuroimaging experiments. This review first provides an overview of various approaches of brain–computer interfacing and basic components in the BCI system and then discuss active functional areas of the brain being utilized in non-invasive brain–computer interfacing performed with hemodynamic signals and electrophysiological recording-based signals. This paper also discusses various challenges and limitations in BCI becoming accessible to a novice user, including security issues in the BCI system, effective ways to overcome those issues, and design implementations.

Funder

Lee Kong Chian School of Medicine and Data Science and AI Research (DSAIR) center of Nanyang Technological University Singapore

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

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