This paper presents a Real-Time Neural Spikes (RT-Neu) Imaging system on FPGA that processes and detects the electrical activity of a neurons population taken from rat hippocampi on an Electrolyte-Oxide-Semiconductor (EOS) Multi Electrode Array (MEA) local matrix of 32×32 pixels. RT-Neu has been implemented on Xilinx Zynq-7000 ARM/FPGA SoC. It receives the neural signals coming from a 9.375 kSample/(sec·pixel) 32×32 pixels EOS Biosensor, filters the single-pixel low-frequency offset/noise components and finally performs a multi-pixel signal processing (using a PCA-based correlation algorithm) to provide a final spatial map of the neural culture electrical activity. The correlation algorithm has been implemented to operate on multiplexed signals allowing to identify single neural Action Potentials (AP) with amplitudes as low as 215 μV0-PEAK. A dedicated GUI has been developed to monitor in real-time the neuron population electrical activity and whose demo video can be found at [1].

Tambaro, M., Vallicelli, E., Tomasella, D., Baschirotto, A., Vassanelli, S., Maschietto, M., et al. (2019). Real-Time Neural (RT-Neu) Spikes Imaging by a 9375 sample/(sec pixel) 32×32 pixels Electrolyte-Oxide-Semiconductor Biosensor. In PRIME 2019 - 15th Conference on Ph.D. Research in Microelectronics and Electronics, Proceedings (pp.233-236). Institute of Electrical and Electronics Engineers Inc. [10.1109/PRIME.2019.8787817].

Real-Time Neural (RT-Neu) Spikes Imaging by a 9375 sample/(sec pixel) 32×32 pixels Electrolyte-Oxide-Semiconductor Biosensor

EA Vallicelli;A Baschirotto;M De Matteis
2019

Abstract

This paper presents a Real-Time Neural Spikes (RT-Neu) Imaging system on FPGA that processes and detects the electrical activity of a neurons population taken from rat hippocampi on an Electrolyte-Oxide-Semiconductor (EOS) Multi Electrode Array (MEA) local matrix of 32×32 pixels. RT-Neu has been implemented on Xilinx Zynq-7000 ARM/FPGA SoC. It receives the neural signals coming from a 9.375 kSample/(sec·pixel) 32×32 pixels EOS Biosensor, filters the single-pixel low-frequency offset/noise components and finally performs a multi-pixel signal processing (using a PCA-based correlation algorithm) to provide a final spatial map of the neural culture electrical activity. The correlation algorithm has been implemented to operate on multiplexed signals allowing to identify single neural Action Potentials (AP) with amplitudes as low as 215 μV0-PEAK. A dedicated GUI has been developed to monitor in real-time the neuron population electrical activity and whose demo video can be found at [1].
No
slide + paper
Scientifica
Principal Component Analysis, Real-Time, Field Programmable Gate Array, Neuronal Activity, Neural Network
English
2019 15th Conference on Ph. D Research in Microelectronics and Electronics (PRIME)
9781728135496
Tambaro, M., Vallicelli, E., Tomasella, D., Baschirotto, A., Vassanelli, S., Maschietto, M., et al. (2019). Real-Time Neural (RT-Neu) Spikes Imaging by a 9375 sample/(sec pixel) 32×32 pixels Electrolyte-Oxide-Semiconductor Biosensor. In PRIME 2019 - 15th Conference on Ph.D. Research in Microelectronics and Electronics, Proceedings (pp.233-236). Institute of Electrical and Electronics Engineers Inc. [10.1109/PRIME.2019.8787817].
Tambaro, M; Vallicelli, E; Tomasella, D; Baschirotto, A; Vassanelli, S; Maschietto, M; DE MATTEIS, M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/240388
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