Newsletter

Message from the Editor

OPINION

September 2020

Ricardo Chavarriaga

The COVID19 pandemic has brought upon us an unprecedented situation. The current events have had a profound impact at a global scale and have once more shown the important role that science and technology play in providing solutions to societal challenges.

Temporary Tattoo Electrodes for brain recordings in clinical settings

RESEARCH

September 2020

Laura M. Ferrari1*, E. Ismailova3*, F.Greco2*

Temporary Tattoo Electrodes (TTEs) are dry and conformable electrodes that are able to capture weak surface electrophysiological signals while being imperceptible for the user. We demonstrated the use and characterised TTEs in a clinical electroencephalography (EEG) monitoring set-up, proving for the first time the compatibility of a dry electrode with magnetoencephalography (MEG) sensors (Figure 1) (1).

Bayesian optimization for automated neurostimulation: future directions and challenges

RESEARCH

September 2020

Samuel Laferrière1,2, Marco Bonizzato3, Numa Dancause3, & Guillaume Lajoie1,4

The stimulation optimization problem & the rapid evolution of electrode technology:
The development of neurostimulation techniques for targeted biomarker control is an active area of research. New implantable devices are microfabricated with hundreds or thousands of electrodes, holding great potential for precise spatiotemporal stimulation. These interfaces not only serve as a crucial experimental tool to probe computation in neural circuits [7,8,9], but also have applications in neuroprostheses used to aid recovery of motor, sensory and cognitive modalities affected by injury or disease [14-19]. Yet, existing electrical neuromodulation interventions do not fully take advantage of the rich stimulation repertoire advanced electrode technologies offer, instead relying mostly on incomplete and manual input-output mapping, and often on single electrode stimulation [1,6].

What large-scale analysis tells us about EEG pre-processing

RESEARCH

September 2020

Kay Robbins1 Senior Member, IEEE and Tim Mullen2, Member IEEE

Although electroencephalography (EEG) is an important high time-resolution brain imaging technology used in laboratory, clinical, and even consumer applications, consistent handling of signal artifacts continues to be an important challenge. In a recent series of papers [1] [2] [3], we and collaborators compared EEG analysis results across multiple studies, EEG headset types, and preprocessing methods. We considered channel and source signal characteristics and explored time-locked event analysis. The work produced several insights of general interest to EEG researchers, as outlined below.

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.

Creating a neuroprosthesis for active tactile exploration of textures

RESEARCH

December 2019

Original paper: J. E. O’Doherty*, S. Shokur *, L. E. Medina, M. A. Lebedev, M. A. L. Nicolelis. Creating a neuroprosthesis for active tactile exploration of textures (2019). Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1908008116
Solaiman Shokur

Sensory neuroprostheses offer the promise of restoring perceptual function to people with impaired sensation [1], [2]. In such devices, diminished sensory modalities (e.g., hearing [3], vision [4], [5], or cutaneous touch [6]–[8]) are reenacted through streams of artificial input to the nervous system, typically using electrical stimulation of nerve fibers in the periphery [9] or neurons in the central nervous system [10]. Restored cutaneous touch, in particular, would be of great benefit for the users of upper-limb prostheses, who place a high priority on the ability to perform functions without the necessity to constantly engage visual attention [11]. This could be achieved through the addition of artificial somatosensory channels to the prosthetic device [1].

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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