2020 – Issue 1

Book Review – Neural Engineering, 3rd Edition (Bin He, Editor)

BOOK REVIEW

May 2020

Bruce Wheeler, PhD

Dr. Bin He is to be congratulated on pulling together an even stronger set of contributors and topics to make the third edition of Neural Engineering (Bin He, editor; Springer) a significant enhancement over the second edition. Easiest to note are the inclusion of 22 chapters (an increase of 3), with nine new topics, and three previous topics presented by new authors with fresh perspectives. Perhaps over half the material is new. A quick additional look shows that the new topics are quite timely.

Transfer Learning for Brain-Computer Interfaces: Euclidean Alignment and Label Alignment

RESEARCH

May 2020

Dongrui Wu and He He

Ministry of Education Key Laboratory of Image Processing and Intelligent Control, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China.
Email: drwu@hust.edu.cn, hehe91@hust.edu.cn.

A brain-computer interface (BCI) system [1], [2] acquires the brain signal, decodes it, and then translates it into control commands for external devices, so that a user can interact with his/her surroundings using thoughts directly.

Re-designing the Wheel: The High Relevance of EEG in Studying Brain Networks

RESEARCH

May 2020

Abbas Sohrabpour and Bin He

There seem to be two major principles that govern brain function; functional segregation and functional integration [1]. The brain is a highly specialized, and at the same time, a highly integrated organ. Spatially segregated regions are tuned to perform special functions optimally (functional segregation), and at a higher level, multiple regions need to pull resources together, and integrate functions, to perform complex tasks (functional integration).

Overview of the IEEE Standards Roadmap on Neurotechnologies for Brain-Machine Interfacing

OPINION

May 2020

Ricardo Chavarriaga, Sumit Soman, Zach McKinney, Jose L Contreras-Vidal, Stephen F Bush

Introduction

Brain-machine interfacing (BMI) systems are a product of multiple integrated technologies, including sensing modules for biosignal acquisition and processing, computational systems for signal decoding and system control, and actuation modules for providing sensory, mechanical, or electrical feedback to the user, and/or for effecting desired physical actions.

About BrainInsight

BrainInsight, the IEEE Brain Initiative eNewsletter, is a quarterly online publication, featuring practical and timely information and forward-looking commentary on neurotechnologies. BrainInsight describes recent breakthroughs in research, primers on methods of interests, or report recent events such as conferences or workshops.


Managing Editor

Ricardo Chavarriaga
Zurich University of Applied Science(ZHAW)
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