Soft bioelectronic materials for brain computer interface

Abstract. Traditional rigid electronic materials for brain-computer interface cannot work stably and will cause rejection reactions and inflammation of the brain. In response, scientists have tried new strategies to develop flexible bioelectronic materials that can stably recognize and control neural activity in the tissue interface environment to monitor and modulate brain function, and meet desired level of effect to provide safe treatment to neural and muscle diseases such as Hence, in this comprehensive review, the paramount significance of optimal electronic materials tailored for Brain-Computer Interface (BCI) applications is underscored. The virtues of biocompatible materials are highlighted, delving into their fabrication methodologies, distinctive material attributes, and deployment in secure therapeutic interventions for a spectrum of neurological disorders including paralysis, dementia, and depression. Current investigations in this domain are presented, outlining the pivotal evaluation criteria for these materials. Recent advancements are introduced and synthesized, considering the prevailing influential factors that shape the field's trajectory. Additionally, the review acknowledges lingering hurdles and outlines prospective avenues for future exploration, ensuring a holistic perspective. Ultimately, the entire discourse culminates in a synthesis that validates the substantial applicability and potential of soft bioelectronic materials within the realm of interfacing computer science with biology, heralding a promising future in neurotechnology.

Authors

Institutions

Publication Details

Journal
Theoretical and Natural Science
Published
2024-11-22
DOI
https://doi.org/10.54254/2753-8818/62/20241536
Primary Topic
Neuroscience and Neural Engineering
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Soft bioelectronic materials for brain computer interface

MX Tang
Theoretical and Natural Science
Neuroscience and Neural Engineering
article

Soft bioelectronic materials for brain computer interface

MX Tang
article en

Abstract

Abstract. Traditional rigid electronic materials for brain-computer interface cannot work stably and will cause rejection reactions and inflammation of the brain. In response, scientists have tried new strategies to develop flexible bioelectronic materials that can stably recognize and control neural activity in the tissue interface environment to monitor and modulate brain function, and meet desired level of effect to provide safe treatment to neural and muscle diseases such as Hence, in this comprehensive review, the paramount significance of optimal electronic materials tailored for Brain-Computer Interface (BCI) applications is underscored. The virtues of biocompatible materials are highlighted, delving into their fabrication methodologies, distinctive material attributes, and deployment in secure therapeutic interventions for a spectrum of neurological disorders including paralysis, dementia, and depression. Current investigations in this domain are presented, outlining the pivotal evaluation criteria for these materials. Recent advancements are introduced and synthesized, considering the prevailing influential factors that shape the field's trajectory. Additionally, the review acknowledges lingering hurdles and outlines prospective avenues for future exploration, ensuring a holistic perspective. Ultimately, the entire discourse culminates in a synthesis that validates the substantial applicability and potential of soft bioelectronic materials within the realm of interfacing computer science with biology, heralding a promising future in neurotechnology.

Theoretical and Natural ScienceVol. 62(1)
Beijing University of Chemical Technology (CN)
Openalex Percentile: Top 78%
Neuroscience and Neural Engineering
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.