scholarly journals Bayesian clustering and tracking of neuronal signals for autonomous neural interfaces

2008 ◽  
Author(s):  
Michael T. Wolf ◽  
Joel W. Burdick
Keyword(s):  
Neural Interfaces ◽  
Bayesian Clustering

Implantable Neural Interfaces for Sharks

2007 ◽  
Author(s):  
Daryl R. Kipke ◽  
Jeffrey Carrier ◽  
David J. Anderson
Keyword(s):  
Neural Interfaces

scholarly journals Progress and challenges of implantable neural interfaces based on nature-derived materials

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Eugenio Redolfi Riva ◽  
Silvestro Micera
Keyword(s):  
Interface Design ◽  
Specific Area ◽  
Building Blocks ◽  
Matrix Proteins ◽  
Neural Interface ◽  
Neural Interfaces ◽  
Biomedical Science ◽  
Chronic Inflammatory Response ◽  
The Impact

AbstractNeural interfaces are bioelectronic devices capable of stimulating a population of neurons or nerve fascicles and recording electrical signals in a specific area. Despite their success in restoring sensory-motor functions in people with disabilities, their long-term exploitation is still limited by poor biocompatibility, mechanical mismatch between the device and neural tissue and the risk of a chronic inflammatory response upon implantation.In this context, the use of nature-derived materials can help address these issues. Examples of these materials, such as extracellular matrix proteins, peptides, lipids and polysaccharides, have been employed for decades in biomedical science. Their excellent biocompatibility, biodegradability in the absence of toxic compound release, physiochemical properties that are similar to those of human tissues and reduced immunogenicity make them outstanding candidates to improve neural interface biocompatibility and long-term implantation safety. The objective of this review is to highlight progress and challenges concerning the impact of nature-derived materials on neural interface design. The use of these materials as biocompatible coatings and as building blocks of insulation materials for use in implantable neural interfaces is discussed. Moreover, future perspectives are presented to show the increasingly important uses of these materials for neural interface fabrication and their possible use for other applications in the framework of neural engineering.

Multivariate Bayesian clustering using covariate‐informed components with application to boreal vegetation sensitivity

Biometrics ◽  
2021 ◽  
Author(s):  
Henry R. Scharf ◽  
Ann M. Raiho ◽  
Sierra Pugh ◽  
Carl A. Roland ◽  
David K. Swanson ◽  
...  
Keyword(s):  
Bayesian Clustering

Bayesian clustering with AutoClass explicitly recognises uncertainties in landscape classification

Ecography ◽  
2007 ◽  
Vol 30 (4) ◽  
pp. 526-536 ◽  
Author(s):  
J. Angus Webb ◽  
Nicholas R. Bond ◽  
Stephen R. Wealands ◽  
Ralph Mac Nally ◽  
Gerry P. Quinn ◽  
...  
Keyword(s):  
Bayesian Clustering ◽  
Landscape Classification

Vertically Aligned Carbon Nanofiber Arrays: An Advance toward Electrical-Neural Interfaces

Small ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 89-94 ◽  
Author(s):  
T. D. Barbara Nguyen-Vu ◽  
Hua Chen ◽  
Alan M. Cassell ◽  
Russell Andrews ◽  
Meyya Meyyappan ◽  
...  
Keyword(s):  
Carbon Nanofiber ◽  
Neural Interfaces ◽  
Vertically Aligned ◽  
Vertically Aligned Carbon Nanofiber

GaN-on-silicon MicroLEDs for neural interfaces

2021 ◽  
Author(s):  
Kanghwan Kim ◽  
Fan Wu ◽  
Kensall D. Wise ◽  
Euisik Yoon
Keyword(s):  
Neural Interfaces
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