The IEEE Brain Initiative eNewsletter is a quarterly online publication launched in January 2017. It features practical and timely information and forward-looking commentary on neurotechnologies and neuroengineering. eNewsletter articles can describe recent breakthroughs in research, primers on methods of interests, or report recent events such as conferences or workshops. You can contact the eNewsletter editor with any questions concerning the topic or content of your article.

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Wireless Miniature Freely-Floating Optogenetic Stimulation Implant

Communicated by Dr. Jun Wang

RESEARCH

December 2021

Linran Zhao, Wen Li, Maysam Ghovanloo, Yaoyao Jia

There is an increasing realization that the majority of brain functions relate to a large distributed network of neurons that are spread over different interconnected regions of the brain. Thus, neural recording and modulation of the future will require the ability to simultaneously interface with multiple neural sites distributed over a large brain area. Traditional methods for modulating neuronal function have relied on direct stimulation by tiny electrodes, which effectiveness is undermined by the limited spatial and temporal precision with which individual cells can be selectively targeted. The emergence of optogenetic stimulation provides distinct advantages over electrical stimulation, such as cell-type specificity, sub-millisecond temporal precision, and rapid reversibility. Optogenetic neuromodulation has the potential to revolutionize the study of how neurons operate as members of larger networks and may ultimately help patients suffering from neurological disorders. Hence, we aspire to design a distributed wireless neural interface framework to stimulate large-scale neuronal ensembles over large brain areas. The distributed framework includes an array of tiny, wireless, and highly efficient implants, each of which operates autonomously to stimulate neural activities.

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Spherical Biomimetic Eyes with Nanowire Arrays: From design to application

Communicated by Dr. Yiwen Wang

RESEARCH

December 2021

Leilei Gu, Yucheng Ding, Zhiyong Fan

“To see is to believe”. High-performance imaging devices are essential in society, particularly in the current age of Artificial Intelligence (AI) +. The biological eyes have been polished by natural selection for millions of years and their function has been verified by the diverse environment. Learning from the masterpiece of nature is therefore a shortcut to improve our manmade systems. As one of the wisest creatures in nature, human eyes are advanced image sensing systems with superiorities such as high resolution, wide field-of-view (FoV), high energy efficiency, and strong accommodations. Their high performance originates from the combined effect of a vastly flexible optical system, high-density and sensitive photoreceptor arrays, and powerful neural networks from both retina and cortex. The human eyes have a spherical shape with a hemispherical retina. A hemispherical shape matches well with the Petzval surface, which is the theoretical focal plane of the spherical lens, leading to clear and sharp imaging. In regular cameras, to mitigate the mismatching in planar structure, a delicate lens array has to be inserted to gradually bend the focal plane into quasi-flat. In our cell phones, there are 10-16 lens. With a well-designed hemispherical image sensor, high-quality imaging with a simple structure can be achieved.

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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].

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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.

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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.

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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.

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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).

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