This paper reports a multi-channel neural spike recording system-on-chip with digital data compression and wireless telemetry. The circuit consists of 16 amplifiers, an analog time-division multiplexer, a single 8 bit analog-to-digital converter, a digital signal compression unit and a wireless transmitter. Although only 16 amplifiers are integrated in our current die version, the whole system is designed to work with 64, demonstrating the feasibility of a digital processing and narrowband wireless transmission of 64 neural recording channels. Compression of the raw data is achieved by detecting the action potentials (APs) and storing 20 samples for each spike waveform. This compression method retains sufficiently high data quality to allow for single neuron identification (spike sorting). The 400 MHz transmitter employs a Manchester-Coded Frequency Shift Keying (MC-FSK) modulator with low modulation index. In this way, a 1:25 Mbit/s data rate is delivered within a limited band of about 3 MHz. The chip is realized in a 0:35 μm AMS CMOS process featuring a 3 V power supply with an area of 3:1 x 2:7 mm2. The achieved transmission range is over 10 m with an overall power consumption for 64 channels of 17:2 mW. This figure translates into a power budget of 269 μW per channel, in line with published results but allowing a larger transmission distance and more efficient bandwidth occupation of the wireless link. The integrated circuit was mounted on a small and light board to be used during neuroscience experiments with freely-behaving rats. Powered by 2 AAA batteries, the system can continuously work for more than 100 hours allowing for long-lasting neural spike recordings.
Seese, T.; Harasaki, H.; Saidel, G.; Davies, C. Characterization of tissue morphology, angiogenesi, and temperature in the adaptive response of muscle tissue to chronic heating. Labs Invest. 1998, 78, 1553–1562.
[3]
Harrison, R.R.; Watkins, P.T.; Lovejoy, R.O.; Kier, R.J.; Black, D.J.; Greger, B.; Solzbacher, F. A low-power integrated circuit for a wireless 100-electrode neural recording system. IEEE J. Solid State Circuits 2007, 1, 123–133.
[4]
Sodagar, A.M.; Perlin, G.E.; Yao, Y.; Najafi, K.; Wise, K.D. An implantable 64-channel wireless microsystem for single-unit recording. IEEE J. Solid State Circuits 2009, 9, 2591–2604.
[5]
Hochberg, L.R.; Serruya, M.D.; Friehs, G.M.; Mukand, J.A.; Saleh, M.; Caplan, A.H.; Branner, A.; Chen, D.; Penn, R.D.; Donoghue, J.P. Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 2006, 442, 164–171, doi:10.1038/nature04970.
[6]
Chae, M.S.; Liu, W.; Yang, Z.; Chen, T.; Kim, J.; Sivaprakasam, M.; Yuce, M.A. 128-Channel 6 mW Wireless Neural Recording IC with On-the-Fly Spike Sorting and UWB Transmitter. In Proceedings of the IEEE International Solid-State Circuits Conference (ISSCC 2008)Digest of Technical Papers, San Francisco, CA, USA, 3–7 February 2008; pp. 146–148.
[7]
Lee, S.B.; Lee, H.M.; Kiani, M.; Jow, U.M.; Ghovanloo, M. An inductively powered scalable 32-channel wireless neural recording system-on-a-chip for neuroscience applications. IEEE Trans. Biomed. Circuits Syst. 2010, 4, 360–371, doi:10.1109/TBCAS.2010.2078814.
[8]
Liu, Y.-H.; Li, C.-H.; Lin, T.-H. A 200-pJ/b MUX-Based RF transmitter for implantable multichannel neural recording. IEEE Trans. Microw. Theory Tech. 2009, 57, 2533–2541, doi:10.1109/TMTT.2009.2029955.
[9]
Bonfanti, A.; Ceravolo, M.; Zambra, G.; Gusmeroli, R.; Borghi, T.; Spinelli, A.S.; Lacaita, A.L. A multi-channel low-power IC for neural spike recording with data compression and narrowband 400-MHz MC-FSK wireless transmission. In Proceedings of the 2010 European Solid-State Device Research Conference (ESSCIRC), Seville, Spain, 14–16 September 2010; pp. 330–333.
[10]
Harrison, R.R.; Charles, C. An implantable 64-channel wireless microsystem for single-unit recording. IEEE J. Solid State Circuits 2003, 6, 958–965, doi:10.1109/JSSC.2003.811979.
[11]
Cp is not drawn in Figure 3. It can be easily verified that these strays do not affect, in principle, the differential gain of the first stage. Only their mismatch causes a pole-zero doublet which, however, has no practical impact since it lays at very low frequency, below the band of interest.
[12]
Vittoz, E.; Fellrath, J. CMOS analog integrated circuits based on weak inversion operations. IEEE J. Solid State Circuits 2003, 3, 224–231.
[13]
Enz, C.C.; Krummenacher, F.; Vittoz, E.A. An analytical MOS transistor model valid in all region of operation and dedicated to low-voltage and low-current applications. Analog Integr. Circuits Signal Process. 1995, 8, 83–114, doi:10.1007/BF01239381.
[14]
Steyaert, M.S.J.; Sansen, W.M.C. A micropower low-noise monolithic instrumentation amplifier for medical purposes. IEEE J. Solid State Circuits 1987, 22, 1163–1168, doi:10.1109/JSSC.1987.1052869.
[15]
This limit can be overwhelmed adopting a current-reuse input stage that makes use of both NMOS and PMOS transistors [6,36]. However, in this case, the impact of flicker noise and of the input capacitance [see Equation (1)] may be detrimental.
[16]
Chae, M.S.; Liu, W.; Sivaprakasam, M. Design Optimization for Integrated Neural Recording Systems. IEEE J. Solid State Circuits 2008, 49, 1931–1939.
[17]
Mollazadeh, M.; Murari, K.; Cauwenberghs, G.; Thakor, N. From Spikes to EEG: Integrated Multichannel and Selective Acquisition of Neuropotentials. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2008), Vancouver, Canada, 20–25 August 2008; pp. 2741–2744.
[18]
Joye, N.; Schmid, A.; Leblebici, Y. An electrical model of the cell-electrode interface for high-density microelectrode arrays. In Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBS 2008), Vancouver, Canada, 20–25 August 2008; pp. 559–562.
[19]
Agnes, A. Very low power Successive Approximation A/D Converter for Instrumentation Applications. Ph.D. Dissertation, Universitá di Pavia, Pavia, Italy, 2009.
[20]
Razavi, B.; Wooley, B.A.; Leblebici, Y. Design techniques for high-speed, high-resolution comparators. IEEE J. Solid State Circuits 1992, 27, 1916–1926, doi:10.1109/4.173122.
Vibert, J.F.; Costa, J. Spike separation in multiunit records: a multivariate analysis of spike descriptive parameters. Electroenceophal. Clin. Neurophys. 1979, 47, 172–182, doi:10.1016/0013-4694(79)90219-0.
[23]
Oweiss, K. A Systems Approach for Data Compression and Latency Reduction in Cortically Controlled Brain Machine Interfaces. IEEE Trans. Biomed. Eng. 2006, 53, 1364–1377, doi:10.1109/TBME.2006.873749.
[24]
Lewicki, M.S. A review of methods for spike sorting: The detection and classification of neural action potentials. Comput. Meth. Prog. Biomed. 1998, 9, 53–78.
[25]
Zouridakis, G.; Tam, D.C. Identification of reliable spike templates in multi-unit extracellular recordings using fuzzy clustering. Comput. Meth. Prog. Biomed. 2000, 61, 91–98, doi:10.1016/S0169-2607(99)00032-2.
[26]
The public database is available at Professor Rodrigo Quiroga’s website, http://www2.le.ac.uk/departments/engineering/research/bioengineering/neuroengineering-lab/spike-sorting/ [37]. The file adopted to validate the compression algorithm is C-difficult1-noise01.mat.
[27]
Bonfanti, A.; Borghi, T.; Gusmeroli, R.; Zambra, G.; Oliyink, A.; Fadiga, L.; Spinelli, A.S.; Baranauskas, G. A low-power integrated circuit for analog spike detection and sorting in neural prosthesis systems. In Proceedings of the IEEE Biomedical Circuits and Systems Conference (BioCAS 2008), Baltimore, MD, USA, 20–22 November 2008; pp. 257–260.
[28]
Andreani, P.; Fard, A. More on the Phase Noise Performance of CMOS Differential-Pair LC-Tank Oscillators. IEEE J. Solid State Circuits 2006, 41, 2703–2712, doi:10.1109/JSSC.2006.884188.
[29]
Bonfanti, A.; Pepe, F.; Samori, C.; Lacaita, A.L. Flicker noise up-conversion due to harmonic distortion in Van der Pol oscillators. IEEE Trans. Circuit Syst. I 2012, 59, 1418–1430, doi:10.1109/TCSI.2011.2177132.
[30]
The quality factor of the tank is approximately determined by the inductor loss at 400 MHz frequency, giving .
[31]
Samori, C.; Lacaita, A.L.; Villa, F.; Zappa, F. Spectrum folding and phase noise in LC tuned oscillators. IEEE Trans. Circuit Syst. I 1998, 45, 781–790, doi:10.1109/82.700925.
[32]
Carson, J.R. Notes on the theory of modulation. Proc. Inst. Radio Eng. 1922, 10, 57–64, doi:10.1109/JRPROC.1922.219793.
[33]
Tan, C.; Tjhung, T.; Singh, H. Performance of Narrow-Band Manchester Coded FSK with Discriminator Detection. IEEE Trans. Commun. 1983, 31, 659–667, doi:10.1109/TCOM.1983.1095858.
[34]
Lacaita, A.; Levantino, S.; Samori, C. Integrated Frequency Synthesizers for Wireless Systems; Cambridge University Press: Cambridge, UK, 2007.
[35]
Abdhelhalim, K.; Genov, R. 915-MHz Wireless 64-Channel Neural Recording SoC with Programmable Mixed-Signal FIR Filters. In Proceedings of the 2011 European Solid-State Device Research Conference (ESSCIRC), Helsinki, Finland, 12–16 September 2011; pp. 223–226.
[36]
Liew, W.-S.; Zou, X.; Lian, Y. A 0.5-V 1.13-μW/channel neural recording interface with digital multiplexing scheme. In Proceedings of the 2011 European Solid-State Device Research Conference (ESSCIRC), Helsinki, Finland, 12–16 September 2011; pp. 219–222.
[37]
Martinez, J.; Pedreira, C.; Ison, M.J.; Quiroga, R.Q. Realistic simulation of extracellular recordings. J. Neurosci. Meth. 2009, 184, 285–293, doi:10.1016/j.jneumeth.2009.08.017.
