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64 channel neural recording amplifier with tunable bandwidth in 180 nm CMOS technology

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Języki publikacji
EN
Abstrakty
EN
This paper presents the design and measurements of low-noise multichannel front-end electronics for recording extra-cellular neuronal signals using microelectrode arrays. The integrated circuit contains 64 readout channels and is fabricated in CMOS 180 nm technology. A single readout channel is built of an AC coupling circuit at the input, a low-noise preamplifier, a band-pass filter and a second amplifier. In order to reduce the number of output lines, the 64 analog signals from readout channels are multiplexed to a single output by an analog multiplexer. The chip is optimized for low noise and good matching performance and has the possibility of passband tuning. The low cut-off frequency can be tuned in the 1 Hz - 60 Hz range while the high cut-off frequency can be tuned in the 3.5 kHz - 15 kHz range. For the nominal gain setting at 44 dB and power dissipation per single channel of 220 žW, the equivalent input noise is in the range from 6 žV - 11 žV rms depending on the band-pass filter settings. The chip has good uniformity concerning the spread of its electrical parameters from channel to channel. The spread of the gain calculated as standard deviation to mean value is about 4.4% and the spread of the low cut-off frequency set at 1.6 Hz is only 0.07 Hz. The chip occupies 5×2.3 mm⊃2 of silicon area. To our knowledge, our solution is the first reported multichannel recording system which allows to set in each recording channel the low cut-off frequency within a single Hz with a small spread of this parameter from channel to channel. The first recordings of action potentials from the thalamus of the rat under urethane anesthesia are presented.
Rocznik
Strony
631--643
Opis fizyczny
Bibliogr. 21 poz., rys., tab., wykr.
Twórcy
autor
autor
autor
autor
  • AGH Univeristy of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of Measurement and Instrumentation, al. A. Mickiewicza 30, 30-059 Krakow, Poland, pgrybos@agh.edu.pl
Bibliografia
  • [1] Ahuja, A. K. et al. (2008). An In Vitro Model of a Retinal Prosthesis. IEEE Transactions on Biomedical Engineering, 55 (6), 1744-1753.
  • [2] Piedade, M. et al. (2005). Visual Neuroprosthesis: A Non Invasive System for Stimulating the Cortex. IEEE Transactions on Circuits and Systems, 52 (12).
  • [3] Nurmikko, A. V. et al. (2010). Listening to Brain Microcircuits for Interfacing With External World-Progress in Wireless Implantable Microelectronic Neuroengineering Devices. Proceedings of the IEEE, 98(3), 375-388.
  • [4] Litke, A. M. et al. (2002). Large scale imaging of retinal output activity. Nucl. Instr. and Meth., 501, 298-307.
  • [5] Johnstone, A. F. M. (2010). Microelectrode arrays: A physiologically based neurotoxicity testing platform for the 21st century. NeuroToxiciology, 31(4), 331-350.
  • [6] Collins, F. S. et al. (2008). Transforming environmental health protection. Science, 319, 906-907.
  • [7] Genov, R. et al. (2006). 16-Channel Integrated Potentiostat for Distributed Neurochemical Sensing. IEEE Transactions on Circuits and Systems, 53(11).
  • [8] Jochum, T. et al. (2009). Integrated circuit amplifiers for multi-electrode intracortical recording. Journal of Neural Engineering, 6(1).
  • [9] Blum, R. A. et al. (2007). An Integrated System for Simultaneous, Multichannel Neuronal Stimulation and Recording. IEEE Transactions on Circuits and Systems, 54(12).
  • [10] Harrison, R. R. et al. (2007). A low-power integrated circuit for a wireless 100-electrode neural recording system. IEEE Journal of Solid-State Circuits, 42, 123-133.
  • [11] Frey, U. et al. (2010). Switch-Matrix-Based High-Density Microelectrode Array in CMOS Technology. IEEE Journal of Solid-State Circuits, 45, 467-482.
  • [12] Roham, M. et al. (2008). A reconfigurable IC for wireless monitoring of chemical or electrical neural activity. International Symposium on Circuits and Systems, 1978-1981.
  • [13] Dąbrowski, W. et al. (2004). A low noise multichannel integrated circuit for recording neuronal signals using microelectrode arrays. Biosensors and Bioelectronics, 19, 749-761.
  • [14] Grybos, P. et al. (2004). Low noise multichannel front-end electronics for recording signals from alive neuronal cells. Mixed Design of Integrated Circuits and Systems, 214-219.
  • [15] Litke, A. et al. (2004). What does the eye tell the brain?: Development of system for the large-scale recording of retinal output activity. IEEE Transactions on Nuclear Science, 51, 1434-1440.
  • [16] Kmon, P. et al. (2009). Design and measurements of 64-channel ASIC for neural signal recording. International Conference of the IEEE Engineering in Medicine and Biology Society. EMBC, Minneapolis, USA, 528-531.
  • [17] Zoladz, M. et al. (2011). A Bidirectional 64-channel Neurochip for Recording and Stimulation Neural Network Activity. The 5th International IEEE EMBS Neural Engineering, Cancun, Mexico, 380-383.
  • [18] Szczygiel, R. et al. (2011). FPDR90-A Low Noise, Fast Pixel Readout Chip in 90 nm CMOS Technology. IEEE Transactions on Nuclear Science, 58(3), 1361-1369.
  • [19] Gryboś, P. (2002). Low Noise Multichannel Integrated Circuits in CMOS Technology for Physics and Biology Applications. Monography 117, AGH Institutional University of Science and Learning Publishers, Kraków, available at: www.kmet.agh.edu.pl/www/asics.
  • [20] Lewandowski, M. H. et al. (2000). Ultradian rhythmic neuronal oscillation in the intergeniculate leaflet. Neuroreport, 11, 317-321.
  • [21] Brown, E. A. et al. (2008). Stimulus-artifact elimination in a multi-electrode system. IEEE Transactions on Biomedical Circuits and Systems, 2(1).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSW1-0087-0010
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