TY - GEN
T1 - An active micro-electrode array with spike detection and asynchronous readout
AU - Datta-Chaudhuri, Timir
AU - Senevirathna, Bathiya
AU - Castro, Alexander
AU - Smela, Elisabeth
AU - Abshire, Pamela
N1 - Publisher Copyright: © 2014 IEEE.
PY - 2014/12/9
Y1 - 2014/12/9
N2 - We present an active micro-electrode array for neural recording with integrated spike detection and an asynchronous readout architecture. Neural amplifier arrays generate voluminous data because of the necessary per-channel sampling rates and number of channels in a dense array. Most of the time, neural cells produce well below 100 spikes per second, with action potential durations generally on the order of 1 ms, and accordingly much of the recorded data from a neural amplifier is not of interest. In the case of dense arrays recording from single units, only the timing of action potentials is relevant and spike sorting is not required. In such a case, the bandwidth requirement of the neural array can be reduced by employing an event-driven data communication protocol such as address event representation (AER). In our array, these events are generated by the spike detection circuits and then relayed to AER modules that send the address of the spiking neuron off-chip using a digital encoding scheme. Based on simulation data, the system implemented here reduces bandwidth requirements by a factor of 1600 in comparison to traditional synchronous sampling.
AB - We present an active micro-electrode array for neural recording with integrated spike detection and an asynchronous readout architecture. Neural amplifier arrays generate voluminous data because of the necessary per-channel sampling rates and number of channels in a dense array. Most of the time, neural cells produce well below 100 spikes per second, with action potential durations generally on the order of 1 ms, and accordingly much of the recorded data from a neural amplifier is not of interest. In the case of dense arrays recording from single units, only the timing of action potentials is relevant and spike sorting is not required. In such a case, the bandwidth requirement of the neural array can be reduced by employing an event-driven data communication protocol such as address event representation (AER). In our array, these events are generated by the spike detection circuits and then relayed to AER modules that send the address of the spiking neuron off-chip using a digital encoding scheme. Based on simulation data, the system implemented here reduces bandwidth requirements by a factor of 1600 in comparison to traditional synchronous sampling.
KW - AER
KW - NEO
KW - bio-potential
KW - neural amplifier
KW - spike detection
UR - https://www.scopus.com/pages/publications/84920520527
U2 - 10.1109/BioCAS.2014.6981794
DO - 10.1109/BioCAS.2014.6981794
M3 - Conference contribution
T3 - IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings
SP - 588
EP - 591
BT - IEEE 2014 Biomedical Circuits and Systems Conference, BioCAS 2014 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE Biomedical Circuits and Systems Conference, BioCAS 2014
Y2 - 22 October 2014 through 24 October 2014
ER -