Abstract
Microelectronic technologies have been exploited to make possible interfacing with a large number of neurons electronically and simultaneously. This advance not only accelerates brain research but also opens the era of “bioelectronic medicine,” in which a variety of neural disorders could be treated by implantable microsystems. To interact with neurons bidirectionally and chronically, the microsystem needs to incorporate not only neural recording and stimulation circuits but also wireless power and data transmission circuits. The latter is particularly important for medical devices to avoid the need for battery replacement. Therefore, this chapter introduces the design considerations for the key component circuits in an implantable microsystem. Moreover, microsystems integrating optical interfaces to achieve better flexibility and specificity in neuromodulation will also be reviewed.
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Abbreviations
- AAC:
-
Automatic Amplitude Control
- ADC:
-
Analog-to-Digital Converter
- AP:
-
Action Potential
- ASK:
-
Amplitude-Shift Keying
- CCS:
-
Constant-Current Stimulation
- COOK:
-
Cyclic On-Off Keying
- ECoG:
-
Electrocorticography
- EEG:
-
Electroencephalography
- FSK:
-
Frequency-Shift Keying
- HFSC:
-
High-Frequency, Switched Capacitor
- LFP:
-
Local Field Potential
- LNA:
-
Low-Noise Amplifier
- L-RSK:
-
Load-Induced Resonance-Shift Keying
- LSK:
-
Load-Shift Keying
- NEF:
-
Noise Efficiency Factor
- PP:
-
Parallel-Parallel
- PS:
-
Parallel-Series
- SCS:
-
Switched-Capacitor Stimulation
- SoC:
-
System on a Chip
- SP:
-
Series-Parallel
- SS:
-
Series-Series
- VCO:
-
Voltage-Controlled Oscillator
- VMS:
-
Voltage-Mode Stimulation
- WPT:
-
Wireless Power Transfer
References
Sodagar, A.M., et al.: An implantable 64-channel wireless microsystem for single-unit neural recording. IEEE J. Solid State Circuits. 44(9), 2591–2604 (2009)
Lambacher, A., et al.: Electrical imaging of neuronal activity by multi-transistor-array (MTA) recording at 7.8 mu m resolution. Appl. Phys. A-Mater. Sci. Process. 79(7), 1607–1611 (2004)
Lebedev, M.A., Nicolelis, M.A.L.: Brain-machine interfaces: past, present and future. Trends Neurosci. 29(9), 536–546 (2006)
Bhatti, P.T., Wise, K.D.: A 32-site 4-channel high-density electrode array for a cochlear prosthesis. IEEE J. Solid State Circuits. 41(12), 2965–2973 (2006)
Shire, D.B., et al.: Development and implantation of a minimally invasive wireless subretinal neurostimulator. IEEE Trans. Biomed. Eng. 56(10), 2502–2511 (2009)
Nicolelis, M.A.L.: Brain-machine interfaces to restore motor function and probe neural circuits. Nat. Rev. Neurosci. 4(5), 417–422 (2003)
Nicolelis, M.A.L.: Actions from thoughts. Nature. 409(6818), 403–407 (2001)
Velliste, M., et al.: Cortical control of a prosthetic arm for self-feeding. Nature. 453(7198), 1098–1101 (2008)
Hochberg, L.R., et al.: Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature. 485(7398), 372–U121 (2012)
Miocinovic, S., et al.: History, applications, and mechanisms of deep brain stimulation. JAMA Neurol. 70(2), 163–171 (2013)
Benabid, A.L., Benazzous, A., Pollak, P.: Mechanisms of deep brain stimulation. Mov. Disord. 17, S73–S74 (2002)
Cagnan, H., et al.: The nature of tremor circuits in parkinsonian and essential tremor. Brain. 137, 3223–3234 (2014)
Hamani, C., et al.: Effects of different stimulation parameters on the antidepressant-like response of medial prefrontal cortex deep brain stimulation in rats. J. Psychiatr. Res. 44(11), 683–687 (2010)
Rouaud, T., et al.: Reducing the desire for cocaine with subthalamic nucleus deep brain stimulation. Proc. Natl. Acad. Sci. U. S. A. 107(3), 1196–1200 (2010)
Chen, C.C., et al.: Neuronal activity in globus pallidus interna can be synchronized to local field potential activity over 3-12 Hz in patients with dystonia. Exp. Neurol. 202(2), 480–486 (2006)
Norlin, P., et al.: A 32-site neural recording probe fabricated by DRIE of SOI substrates. J. Micromech. Microeng. 12(4), 414–419 (2002)
Hara, S.A., Kim, B.J., Kuo, J.T., Lee, C.D., Meng, E., Pikov, V.: Long-term stability of intracortical recordings using perforated and arrayed Parylene sheath electrodes. J. Neural Eng. 13(6):066020 (2016)
Schalk, G.: Can electrocorticography (ECoG) support robust and powerful brain-computer interfaces? Front. Neuroeng. 3, 9–9 (2010)
Tatum, W.O.: Handbook of EEG interpretation, 2nd edn. New York, Demos Medical (2014)
Millan, J.D., et al.: Noninvasive brain-actuated control of a mobile robot by human EEG. IEEE Trans. Biomed. Eng. 51(6), 1026–1033 (2004)
Casson, A.J., et al.: Wearable electroencephalography what is it, why is it needed, and what does it entail? IEEE Eng. Med. Biol. Mag. 29(3), 44–56 (2010)
Muller, R., et al.: A minimally invasive 64-channel wireless mu ECoG implant. IEEE J. Solid State Circuits. 50(1), 344–359 (2015)
Benazzouz, A., et al.: Effect of high-frequency stimulation of the subthalamic nucleus on the neuronal activities of the substantia nigra pars reticulata and ventrolateral nucleus of the thalamus in the rat. Neuroscience. 99(2), 289–295 (2000)
Priori, A., et al.: Adaptive deep brain stimulation (aDBS) controlled by local field potential oscillations. Exp. Neurol. 245, 77–86 (2013)
Guo, J., Yuan, J., Chan, M.: Modeling of the cell-electrode interface noise for microelectrode arrays. IEEE Trans. Biomed. Circuits Syst. 6(6), 605–613 (2012)
Mohan, R., et al.: A 0.6-V, 0.015-mm(2), time-based ECG readout for ambulatory applications in 40-nm CMOS. IEEE J. Solid State Circuits. 52(1), 298–308 (2017)
Harrison, R.R., Charles, C.: A low-power low-noise CMOS amplifier for neural recording applications. IEEE J. Solid State Circuits. 38(6), 958–965 (2003)
Wang, S., et al.: Leakage compensation scheme for ultra-high-resistance pseudo-resistors in neural amplifiers. Electron. Lett. 54(5) (2018)
Denison, T., et al.: A 2 mu W 100 nV/rtHz chopper-stabilized instrumentation amplifier for chronic measurement of neural field potentials. IEEE J. Solid State Circuits. 42(12), 2934–2945 (2007)
Jiang, W.L., et al.: A +/− 50-mV linear-input-range VCO-based neural-recording front-end with digital nonlinearity correction. IEEE J. Solid State Circuits. 52(1), 173–184 (2017)
Ng, K.A., Xu, Y.P.: A low-power, high CMRR neural amplifier system employing CMOS inverter-based OTAs with CMFB through supply rails. IEEE J. Solid State Circuits. 51(3), 724–737 (2016)
Chandrakumar, H., Markovic, D.: A 15.2-ENOB 5-kHz BW 4.5-mu W chopped CT delta sigma-ADC for artifact-tolerant neural recording front ends. IEEE J. Solid State Circuits. 53(12), 3470–3483 (2018)
Johnson, B.C., et al.: An implantable 700 mu W 64-channel neuromodulation IC for simultaneous recording and stimulation with rapid artifact recovery. In: 2017 Symposium on Vlsi Circuits, pp. C48–C49 (2017)
Steyaert, M.S.J., Sansen, W.M.C., Chang, Z.Y.: A micropower low-noise monolithic instrumentation amplifier for medical purposes. IEEE J. Solid State Circuits. 22(6), 1163–1168 (1987)
Enz, C.C., Temes, G.C.: Circuit techniques for reducing the effects of op-amp imperfections: autozeroing, correlated double sampling, and chopper stabilization. Proc. IEEE. 84(11), 1584–1614 (1996)
Lin, Y.P., et al.: A battery-less, implantable neuro-electronic interface for studying the mechanisms of deep brain stimulation in rat models. IEEE Trans. Biomed. Circuits Syst. 10(1), 98–112 (2016)
Verma, N., et al.: A micro-power EEG acquisition SoC with integrated feature extraction processor for a chronic seizure detection system. IEEE J. Solid State Circuits. 45(4), 804–816 (2010)
Bin Altaf, M.A., Zhang, C., Yoo, J.: A 16-channel patient-specific seizure onset and termination detection SoC with impedance-adaptive transcranial electrical stimulator. IEEE J. Solid State Circuits. 50(11), 2728–2740 (2015)
Fan, Q., et al.: A 1.8μW 1μV-offset capacitively-coupled chopper instrumentation amplifier in 65nm CMOS. In: 2010 Proceedings of ESSCIRC (2010)
Hong, G., Lieber, C.M.: Novel electrode technologies for neural recordings. Nat. Rev. Neurosci. 6, 330–345 (2019)
Seymour, J.P., et al.: State-of-the-art MEMS and microsystem tools for brain research. Microsyst. Nanoeng. 3:16066 (2017)
Lopez, C.M., et al.: An implantable 455-active-electrode 52-channel CMOS neural probe. IEEE J. Solid State Circuits. 49(1), 248–261 (2014)
Ballini, M., et al.: A 1024-channel CMOS microelectrode array with 26,400 electrodes for recording and stimulation of electrogenic cells in vitro. IEEE J. Solid State Circuits. 49(11), 2705–2719 (2014)
Eversmann, B., et al.: A neural tissue interfacing chip for in-vitro applications with 32k recording / stimulation channels on an active area of 2.6 mm2. In: 2011 Proceedings of the ESSCIRC (ESSCIRC) (2011)
Harrison, R.R., et al.: A low-power integrated circuit for a wireless 100-electrode neural recording system. IEEE J. Solid State Circuits. 42(1), 123–133 (2007)
Olsson, R.H., Wise, K.D.: A three-dimensional neural recording microsystem with implantable data compression circuitry. IEEE J. Solid State Circuits. 40(12), 2796–2804 (2005)
Aziz, J.N.Y., et al.: 256-channel neural recording and delta compression microsystem with 3D electrodes. IEEE J. Solid State Circuits. 44(3), 995–1005 (2009)
Wikipedia. Rheobase (2019). Available from: https://en.wikipedia.org/wiki/Rheobase
Cogan, S.F.: Neural stimulation and recording electrodes. Annu. Rev. Biomed. Eng. 10(1), 275–309 (2008)
Hsu, W.Y., Schmid, A.: Compact, energy-efficient high-frequency switched capacitor neural stimulator with active charge balancing. IEEE Trans. Biomed. Circuits Syst. 11(4), 878–888 (2017)
Lee, H.M., Park, H., Ghovanloo, M.: A power-efficient switched-capacitor stimulating system for electrical/optical deep brain stimulation. IEEE J. Solid State Circuits. 50(1), 360–374 (2013)
Noorsal, E., et al.: A neural stimulator frontend with high-voltage compliance and programmable pulse shape for epiretinal implants. IEEE J. Solid State Circuits. 47(1), 244–256 (2012)
Williams, I., Constandinou, T.G.: An energy-efficient, dynamic voltage scaling neural stimulator for a proprioceptive prosthesis. IEEE Trans. Biomed. Circuits Syst. 7(2), 129–139 (2013)
Arfin, S.K., Sarpeshkar, R.: An energy-efficient, adiabatic electrode stimulator with inductive energy recycling and feedback current regulation. IEEE Trans. Biomed. Circuits Syst. 6(1), 1–14 (2012)
van Dongen, M.N., Serdijn, W.A.: A power-efficient multichannel neural stimulator using high-frequency pulsed excitation from an unfiltered dynamic supply. IEEE Trans. Biomed. Circuits Syst. 10(1), 61–71 (2016)
Hsu, W.Y.: System Design and Advanced Circuit Techniques for Bi-Directional Brain-Machine Interfaces. Lausanne, EPFL (2018)
Soltani, N., et al.: Cellular inductive powering system for weakly-linked resonant rodent implants. In: 2013 IEEE Biomedical Circuits and Systems Conference. pp. 350–353 (2013)
Kassiri, H., et al.: Battery-less tri-band-radio neuro-monitor and responsive neurostimulator for diagnostics and treatment of neurological disorders. IEEE J. Solid State Circuits. 51(5), 1274–1289 (2016)
Wang, C.S., Covic, G.A., Stielau, O.H.: Power transfer capability and bifurcation phenomena of loosely coupled inductive power transfer systems. IEEE Trans. Ind. Electron. 51(1), 148–157 (2004)
Baker, M.W., Sarpeshkar, R.: Feedback analysis and design of RF power links for low-power bionic systems. IEEE Trans. Biomed. Circuits Syst. 1(1), 28–38 (2007)
Pan, J., et al.: Self-regulated wireless power and simultaneous 5MB/S reverse data over one pair of coils. In: 2018 IEEE Symposium on VLSI Circuits (2018)
Ahn, D., Hong, S.: Wireless power transmission with self-regulated output voltage for biomedical implant. IEEE Trans. Ind. Electron. 61(5), 2225–2235 (2014)
Ha, S., et al.: Energy recycling telemetry IC with simultaneous 11.5 mW power and 6.78 Mb/s backward data delivery over a single 13.56 MHz inductive link. IEEE J. Solid State Circuits. 51(11), 2664–2678 (2016)
Mandal, S., Sarpeshkar, R.: Power-efficient impedance-modulation wireless data links for biomedical implants. IEEE Trans. Biomed. Circuits Syst. 2(4), 301–315 (2008)
Lee, H.M., Ghovanloo, M.: An integrated power-efficient active rectifier with offset-controlled high speed comparators for inductively powered applications. IEEE Trans. Circuits Syst. I Regul. Pap. 58(8), 1749–1760 (2011)
Yizhar, O., et al.: Optogenetics in neural systems. Neuron. 71(1), 9–34 (2011)
Thompson, A.C., Stoddart, P.R., Jansen, E.D.: Optical stimulation of neurons. Curr. Mol. Imaging. 3(2), 162–177 (2014)
Tye, K.M., Deisseroth, K.: Optogenetic investigation of neural circuits underlying brain disease in animal models. Nat. Rev. Neurosci. 13(4), 251–266 (2012)
Alt, M.T., et al.: Let there be light-optoprobes for neural implants. Proc. IEEE. 105(1), 101–138 (2017)
Izzo, A.D., et al.: Laser stimulation of auditory neurons: effect of shorter pulse duration and penetration depth. Biophys. J. 94(8), 3159–3166 (2008)
Izzo, A.D., et al.: Laser stimulation of the auditory nerve. Lasers Surg. Med. 38(8), 745–753 (2006)
Jenkins, M.W., et al.: Optical pacing of the adult rabbit heart. Biomed. Opt. Express. 4(9), 1626–1635 (2013)
Wells, J., Kao, C., Jansen, E.D., Konrad, P., Mahadevan-Jansen, A.: Application of infrared light for in vivo neural stimulation. J. Biomed. Opt. 10(6):064003 (2005)
Liljemalm, R., Nyberg, T.: Quantification of a thermal damage threshold for astrocytes using infrared laser generated heat gradients. Ann. Biomed. Eng. 42(4), 822–832 (2014)
Han, X.: In vivo application of optogenetics for neural circuit analysis. ACS Chem. Neurosci. 3(8), 577–584 (2012)
Boyden, E.S., et al.: Millisecond-timescale, genetically targeted optical control of neural activity. Nat. Neurosci. 8(9), 1263–1268 (2005)
Schwaerzle, M., et al.: Ultracompact optrode with integrated laser diode chips and SU-8 waveguides for optogenetic applications. In: 26th IEEE International Conference on Micro Electro Mechanical Systems. pp. 1029–1032 (2013)
Son, Y., et al.: In vivo optical modulation of neural signals using monolithically integrated two-dimensional neural probe arrays. Sci. Rep. 5 (2015)
Zorzos, A.N., et al.: Three-dimensional multiwaveguide probe array for light delivery to distributed brain circuits. Opt. Lett. 37(23), 4841–4843 (2012)
Zorzos, A.N., Boyden, E.S., Fonstad, C.G.: Multiwaveguide implantable probe for light delivery to sets of distributed brain targets. Opt. Lett. 35(24), 4133–4135 (2010)
Kampasi, K., et al.: Dual color optogenetic control of neural populations using low-noise, multishank optoelectrodes. Microsyst. Nanoeng. 4(1), 10 (2018)
Park, H., et al.: The first neural probe integrated with light source (blue laser diode) for optical stimulation and electrical recording. In: 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. pp. 2961–2964 (2011)
Li, B., et al.: A nanofabricated optoelectronic probe for manipulating and recording neural dynamics. J. Neural Eng. 15(4), 046008 (2018)
Shin, G., et al.: Flexible near-field wireless optoelectronics as subdermal implants for broad applications in optogenetics. Neuron. 93(3), 509 (2017)
McCall, J.G., et al.: Preparation and implementation of optofluidic neural probes for in vivo wireless pharmacology and optogenetics. Nat. Protoc. 12(2), 219–237 (2017)
Samineni, V.K., et al.: Fully implantable, battery-free wireless optoelectronic devices for spinal optogenetics. Pain. 158(11), 2108–2116 (2017)
Noh, K.N., Park, S.I., Qazi, R., Zou, Z., Mickle, A.D., Grajales-Reyes, J.G., Jang, K.I., Gereau, RW 4th., Xiao, J., Rogers, J.A., Jeong, J.W.: Miniaturized, battery-free optofluidic systems with potential for wireless pharmacology and optogenetics. Small. 14(4):10.1002/smll.201702479 (2018)
Jia, Y., Khan, W., Lee, B., Fan, B., Madi, F., Weber, A., Li, W., Ghovanloo, M.: Wireless opto-electro neural interface for experiments with small freely behaving animals. J. Neural Eng. 15(4):046032 (2018)
Gagnon-Turcotte, G., et al.: A 0.13-mu m CMOS SoC for simultaneous multichannel optogenetics and neural recording. IEEE J. Solid State Circuits. 53(11), 3087–3100 (2018)
Wu, F., et al.: Monolithically integrated mu LEDs on silicon neural probes for high-resolution optogenetic studies in behaving animals. Neuron. 88(6), 1136–1148 (2015)
Yamakawa, T., et al.: Development of an implantable flexible probe for simultaneous near-infrared spectroscopy and electrocorticography. IEEE Trans. Biomed. Eng. 61(2), 388–395 (2014)
Kwon, K.Y., et al.: Opto-mu ECoG array: a hybrid neural interface with transparent mu ECoG electrode array and integrated LEDs for optogenetics. IEEE Trans. Biomed. Circuits Syst. 7(5), 593–600 (2013)
Kim, T.-I., et al.: Injectable, cellular-scale optoelectronics with applications for wireless optogenetics. Science. 340(6129), 211–216 (2013)
Mickle, A.D., et al.: A wireless closed-loop system for optogenetic peripheral neuromodulation. Nature. 565(7739), 361–365 (2019)
Stark, E., Koos, T., Buzsaki, G.: Diode probes for spatiotemporal optical control of multiple neurons in freely moving animals. J. Neurophysiol. 108(1), 349–363 (2012)
Wang, J., Wagner, F., Borton, D.A., Zhang, J., Ozden, I., Burwell, R.D., Nurmikko, A.V., van Wagenen, R., Diester, I., Deisseroth, K.: Integrated device for combined optical neuromodulation and electrical recording for chronic in vivo applications. J. Neural Eng. 9(1):016001 (2012)
Kilias, A., et al.: Optogenetic entrainment of neural oscillations with hybrid fiber probes. J. Neural Eng. 15(5), 056006 (2018)
Park, S., et al.: One-step optogenetics with multifunctional flexible polymer fibers. Nat. Neurosci. 20, 612 (2017)
Pisanello, F., et al.: Multipoint-emitting optical fibers for spatially addressable in vivo optogenetics. Neuron. 82(6), 1245–1254 (2014)
Maghsoudloo, E., et al.: A smart neuroscience platform with wireless power transmission for simultaneous optogenetics and electrophysiological recording. In: 2018 IEEE International Symposium on Circuits and Systems (2018)
Kassiri, H., et al.: Arbitrary-waveform electro-optical intracranial neurostimulator with load-adaptive high-voltage compliance. IEEE Trans. Neural Syst. Rehabil. Eng. 27(4), 582–593 (2019)
Ameli, R., et al.: A wireless and batteryless neural headstage with optical stimulation and electrophysiological recording. In: 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (2013)
Wentz, C.T., et al.: A wirelessly powered and controlled device for optical neural control of freely-behaving animals. J. Neural Eng. 8(4), 046021 (2011)
Kassiri, H., et al.: Rail-to-rail-input dual-radio 64-channel closed-loop neurostimulator. IEEE J. Solid State Circuits. 52(11), 2793–2810 (2017)
Li, C., et al.: Overview of recent development on wireless sensing circuits and systems for healthcare and biomedical applications. IEEE J. Emerg. Sel. Top. Circuits Syst. 8(2), 165–177 (2018)
Ibrahim, A., Meng, M., Kiani, M.: A comprehensive comparative study on inductive and ultrasonic wireless power transmission to biomedical implants. IEEE Sensors J. 18(9), 3813–3826 (2018)
Wirdatmadja, S.A., et al.: Wireless optogenetic neural dust for deep brain stimulation. In: 2016 IEEE 18th International Conference on E-Health Networking, Applications and Services. pp. 640–645 (2016)
Charthad, J., et al.: A mm-sized wireless implantable device for electrical stimulation of peripheral nerves. IEEE Trans. Biomed. Circuits Syst. 12(2), 257–270 (2018)
Lee, S., et al.: A 250 mu m x 57 mu m microscale opto-electronically transduced electrodes (MOTEs) for neural recording. IEEE Trans. Biomed. Circuits Syst. 12(6), 1256–1266 (2018)
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Hsu, WY., Hsieh, PH., Chen, H. (2021). Design Considerations for Implantable Neural Circuits and Systems. In: Thakor, N.V. (eds) Handbook of Neuroengineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-2848-4_19-1
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