.png){kind=icon}
返回
Sensitive and robust chemical detection using an olfactory brain-computer interface
.png){kind=icon}
OA
AI
DOI：10.1016/j.bios.2021.113664.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
When it comes to detecting volatile chemicals, biological olfactory systems far outperform all artificial chemical detection devices in their versatility, speed, and specificity. Consequently, the use of trained animals for chemical detection in security, defense, healthcare, agriculture, and other applications has grown astronomically. However, the use of animals in this capacity requires extensive training and behavior-based communication. Here we propose an alternative strategy, a bio-electronic nose, that capitalizes on the superior capability of the mammalian olfactory system, but bypasses behavioral output by reading olfactory information directly from the brain. We engineered a brain-computer interface that captures neuronal signals from an early stage of olfactory processing in awake mice combined with machine learning techniques to form a sensitive and selective chemical detector. We chronically implanted a grid electrode array on the surface of the mouse olfactory bulb and systematically recorded responses to a large battery of odorants and odorant mixtures across a wide range of concentrations. The bio-electronic nose has a comparable sensitivity to the trained animal and can detect odors on a variable background. We also introduce a novel genetic engineering approach that modifies the relative abundance of particular olfactory receptors in order to improve the sensitivity of our bio-electronic nose for specific chemical targets. Our recordings were stable over months, providing evidence for robust and stable decoding over time. The system also works in freely moving animals, allowing chemical detection to occur in real-world environments. Our bio-electronic nose outperforms current methods in terms of its stability, specificity, and versatility, setting a new standard for chemical detection.
Keyword:
Mouse olfaction
Brain-computer interface (BMIs)
Chemical sensing
Neural engineering
Neural signals
Pattern recognition
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
10.5
论文数:
1.8W
被引数:
7.7W
机构
引用论文
Diagnosis and Classification of 17 Diseases from 1404 Subjects via Pattern Analysis of Exhaled Molecules通过呼出分子的模式分析对1404名受试者的17种疾病进行诊断和分类.png)
ACS NANOOAAI
ACS NANOIF16
OAAI分享收藏分享收藏Effects of concentric and eccentric contractions on phosphorylation of MAPKerk1/2 and MAPKp38 in isolated rat skeletal muscle同心收缩和偏心收缩对大鼠离体骨骼肌MAPKerk1/2 和MAPKp38 磷酸化的影响OAAI
OAAI分享收藏分享收藏Dynamic ensemble odor coding in the mammalian olfactory bulb: Sensory information at different timescalesNEURON
OAAI
NEURONIF15
OAAI分享收藏
查看更多内容