An adaptive neural spike detector with threshold-lock loop

2009 IEEE International Symposium on Circuits and Systems ◽

10.1109/iscas.2009.5118217 ◽

2009 ◽

Author(s):

Chung-Ching Peng ◽

Pawan Sabharwal ◽

Rizwan Bashirullah

Keyword(s):

Neural Spike ◽

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An area/power efficient electrode-matched neural-spike detector embedded in implantable 256-channel MEA

2017 IEEE Biomedical Circuits and Systems Conference (BioCAS) ◽

10.1109/biocas.2017.8325057 ◽

2017 ◽

Author(s):

Myungjin Han ◽

Go Eun Ha ◽

Eunji Cheong ◽

Gunhee Han ◽

Youngcheol Chae

Keyword(s):

Power Efficient ◽

Neural Spike ◽

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A 1 V, compact, current-mode neural spike detector with detection probability estimator in 65 nm CMOS

2015 IEEE International Symposium on Circuits and Systems (ISCAS) ◽

10.1109/iscas.2015.7168743 ◽

2015 ◽

Author(s):

Enyi Yao ◽

Arindam Basu

Keyword(s):

Detection Probability ◽

Current Mode ◽

Probability Estimator ◽

Neural Spike ◽

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A 0.7 V, 40 nW Compact, Current-Mode Neural Spike Detector in 65 nm CMOS

IEEE Transactions on Biomedical Circuits and Systems ◽

10.1109/tbcas.2015.2432834 ◽

2016 ◽

Vol 10 (2) ◽

pp. 309-318 ◽

Author(s):

Enyi Yao ◽

Yi Chen ◽

Arindam Basu

Keyword(s):

Current Mode ◽

Neural Spike ◽

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Sub-threshold-based ultra-low-power neural spike detector

Electronics Letters ◽

10.1049/el.2010.3711 ◽

2011 ◽

Vol 47 (6) ◽

pp. 367 ◽

Author(s):

H. Li ◽

Q. Xu

Keyword(s):

Low Power ◽

Ultra Low Power ◽

Neural Spike ◽

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A micro-power neural spike detector and feature extractor in .13μm CMOS

2008 IEEE Custom Integrated Circuits Conference ◽

10.1109/cicc.2008.4672089 ◽

2008 ◽

Author(s):

Jeremy Holleman ◽

Apurva Mishra ◽

Chris Diorio ◽

Brian Otis

Keyword(s):

Neural Spike ◽

Feature Extractor ◽

Micro Power ◽

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Adaptive Threshold Neural Spike Detector Using Stationary Wavelet Transform in CMOS

IEEE Transactions on Neural Systems and Rehabilitation Engineering ◽

10.1109/tnsre.2015.2425736 ◽

2015 ◽

Vol 23 (6) ◽

pp. 946-955 ◽

Author(s):

Yuning Yang ◽

C. Sam Boling ◽

Awais M. Kamboh ◽

Andrew J. Mason

Keyword(s):

Wavelet Transform ◽

Adaptive Threshold ◽

Stationary Wavelet Transform ◽

Neural Spike ◽

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Low-power MicroVrms noise neural spike detector for implantable interface microsystem device

Microelectronics Reliability ◽

10.1016/j.microrel.2015.02.001 ◽

2015 ◽

Vol 55 (5) ◽

pp. 807-814 ◽

Author(s):

Hongge Li ◽

Huixin Bai ◽

Qicheng Xu ◽

Tongsheng Xia

Keyword(s):

Low Power ◽

Neural Spike ◽

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Multi-Pattern Recognition Through Maximization of Signal-to-Peak-Interference Ratio With Application to Neural Spike Sorting

IEEE Transactions on Signal Processing ◽

10.1109/tsp.2020.3033973 ◽

2020 ◽

Vol 68 ◽

pp. 6240-6254

Author(s):

Jasper Wouters ◽

Panagiotis Patrinos ◽

Fabian Kloosterman ◽

Alexander Bertrand

Keyword(s):

Pattern Recognition ◽

Spike Sorting ◽

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PtNPt/MWCNT-PEDOT:PSS-Modified Microelectrode Arrays for the Synchronous Dopamine and Neural Spike Detection in Rat Models of Sleep Deprivation

ACS Applied Bio Materials ◽

10.1021/acsabm.1c00172 ◽

2021 ◽

Author(s):

Zeying Lu ◽

Shengwei Xu ◽

Hao Wang ◽

Enhui He ◽

Juntao Liu ◽

...

Keyword(s):

Sleep Deprivation ◽

Microelectrode Arrays ◽

Spike Detection ◽

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An uncertainty principle for neural coding: Conjugate representations of position and velocity are mapped onto firing rates and co‐firing rates of neural spike trains

Hippocampus ◽

10.1002/hipo.23197 ◽

2020 ◽

Vol 30 (4) ◽

pp. 396-421 ◽

Author(s):

Ryan Grgurich ◽

Hugh T. Blair

Keyword(s):

Uncertainty Principle ◽

Neural Coding ◽

Spike Trains ◽

Firing Rates ◽

Neural Spike ◽

Neural Spike Trains

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