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.
An affective computing aspect on similarities and differences in emotion recognition with EEG and eye movements among Chinese, German, and French people
Wei Liu, Bao-Liang Lu
Emotions, especially facial expressions, used to be thought of as universal all around the world: we would cry when we are sad, and we would smile when we are happy. However, you might have experienced that you do not laugh after hearing a foreign joke realizing that the joke has distinct cultural backgrounds. Emotions, therefore, seem to have both universal and culturally variable components. Understanding the relationship between cultures and emotions can help us know whether emotions affect physical health in the same way across various cultures and inform us about the effectiveness of mental health interventions for patients with different cultural backgrounds. In addition, from the aspect of affective computing, a deep comprehension of cultural influences on emotions can help us build emotion recognition models for generalizing to people around the world.
Self-stretchable Christmas-tree-shaped Ultraflexible Neural Probes
Ye Tian, Cunkai Zhou, Kuikui Zhang, Huiran Yang, Zhaohan Chen, Zhitao Zhou, Xiaoling Wei, Tiger H. Tao, Liuyang Sun
Implantable flexible neural probes have been demonstrated bridging the mechanical mismatch between invasive probes and brain tissues, minimizing footprint in brain, and chronic biocompatibility . However, conventional needle-shaped flexible neural probes reported before have recording sites distributed vertically along a relatively narrow shank , which limits the lateral range in which the probes may record neural signals. Although designs with more probe shanks expand the lateral detectable range, the high implantation density reflects in increased tissue damage and surgery complexity. In this work, we developed a flexible neural probe by novel Christmas-tree structure, which has branches that are foldable along the shank by temporary encapsulation before implantation and self-stretchable after the encapsulation dissolves after implantation. The probe we developed affords increased lateral sensing range without causing extra brain tissue damage.
Next Generation Neural Interfaces: Research on Emerging Technologies at Imperial College London
D. Y. Barsakcioglu, S. Luan, L. Grand, T. G. Constandinou
The era of bioelectronic healthcare is dawning upon us. As electronic systems shrink in size and improve in functionality, we see more and more emerging devices that can track vital signs, such as heart rate and blood pressure, realising the grand vision of highly connected sensor nodes monitoring patients’ health beyond the hospital doors. The real revolution in digital healthcare, however, lies in bringing not only the diagnostics but also the therapy to the patient which requires interfacing the world of electronics with biology.
Network Data on the Statistical Testbench
A New Method for Generating Realistic Null Data Exploiting Underlying Graph Structure with Application to EEG
E. Pirondini, A. Vybornova, M. Coscia, and D. Van De Ville
Technological and computational advances are making available large amounts of high-dimensional and rich-structured biomedical data, including brain images and signals. Acknowledging the network structure in our analyses opens a multitude of avenues in investigating “systems level” properties. For instance, computational neuroscience has boosted the interest in modeling and analyzing large datasets using concepts normally applied in networks and graph theories.
On the Need of Standards for Brain-Machine Interface Systems
R. Chavarriaga, C. Carey, C. Tom, B. Ash
The field of Brain-Machine Interfacing (BMI) is going through a very exciting period where the state-of- the-art in research is currently being tested on its intended end-users. Evidently, this translation from laboratory proof-of concepts to viable clinical and assistive solutions entails a large set of challenges. Furthermore, the possibility of deploying and commercializing BMI-based solutions requires researchers, manufacturers, and regulatory agencies to ensure these devices comply with well-defined criteria on their safety and effectiveness. In consequence, there is an increased interest on development of appropriate standards for BMI systems.