Towards High-Resolution Brain-Chip Interface and Automated Analysis of Multichannel Neuronal Signals

被引:0
|
作者
Mahmud, Mufti [1 ]
Cecchetto, Claudia [1 ]
Maschietto, Marta [1 ]
Thewes, Roland [2 ]
Vassanelli, Stefano [1 ]
机构
[1] Univ Padua, Dept Biomed Sci, NeuroChip Lab, I-35131 Padua, Italy
[2] Tech Univ Berlin, Fac EECS, Chair Sensor & Actuator Syst, D-10587 Berlin, Germany
关键词
Brain-machine interface; extracellular signal; somatosensory cortex; neuronal big data; intelligent analysis; artifact removal; noise characterization; FIELD POTENTIALS; LARGE-SCALE; BIG DATA; SIGMATE;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
To understand brain functions and diagnose brain disorders, scientists have developed various probing tools and techniques. This development has been facilitated by the rapid growth of micro-and nano-technology over the last two decades and allowed the scientists to record neuronal signals at multiple scales and simultaneously from hundreds of channels. However, this huge amount of data poses a big challenge and requires proper interpretation before any meaning can be derived. As a response, various automated and intelligent methods and tools have been proposed for the mining of such data. Here we overview some of the high-resolution neuronal probes available at present, the neuronal signals recorded through them, and a few possible automated methods to analyze the acquired signals. Towards the end we indicate few research challenges and outlook.
引用
收藏
页码:868 / 872
页数:5
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