Skip to main content
SpringerLink
Log in

Future of Neural Interfaces

  • Chapter
  • First Online:
Book cover Neural Interface: Frontiers and Applications

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1101))

Abstract

The technological ability to capture electrophysiological activity of populations of cortical neurons through chronic implantable devices has led to significant advancements in the field of brain-computer interfaces. Recent progress in the field has been driven by developments in integrated microelectronics, wireless communications, materials science, and computational neuroscience. Here, we review major device development landmarks in the arena of neural interfaces from FDA-approved clinical systems to prototype head-mounted and fully implantable wireless systems for multi-channel neural recording. Additionally, we provide an outlook toward next-generation, highly miniaturized technologies for minimally invasive, vastly parallel neural interfaces for naturalistic, closed-loop neuroprostheses.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Afshar P, Khambhati A, Stanslaski S, Carlson D, Jensen R, Dani S, …, Denison T (2013) A translational platform for prototyping closed-loop neuromodulation systems. Front Neural Circuits 6:117

    Google Scholar 

  2. Ando H, Takizawa K, Yoshida T, Matsushita K, Hirata M, Suzuki T (2016) Wireless multichannel neural recording with a 128-mbps UWB transmitter for an implantable brain-machine interfaces. IEEE Trans Biomed Circuits Syst 10(6):1068–1078

    Article  CAS  PubMed  Google Scholar 

  3. Aflalo T, Kellis S, Klaes C, Lee B, Shi Y, Pejsa K, …, Liu C (2015) Decoding motor imagery from the posterior parietal cortex of a tetraplegic human. Science 348(6237):906–910

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Biederman W, Yeager DJ, Narevsky N, Leverett J, Neely R, Carmena JM, …, Rabaey JM (2015) A 4.78 mm 2 fully-integrated neuromodulation SoC combining 64 acquisition channels with digital compression and simultaneous dual stimulation. IEEE J Solid State Circuits 50(4):1038–1047

    Article  Google Scholar 

  5. Bonfanti A, Ceravolo M, Zambra G, Gusmeroli R, Borghi T, Spinelli AS, Lacaita AL (2010) A multi-channel low-power IC for neural spike recording with data compression and narrowband 400-MHz MC-FSK wireless transmission. In: 2010 Proceedings of ESSCIRC, September. IEEE, pp 330–333

    Google Scholar 

  6. Borton DA, Yin M, Aceros J, Nurmikko A (2013) An implantable wireless neural interface for recording cortical circuit dynamics in moving primates. J Neural Eng 10(2):026010

    Article  PubMed  PubMed Central  Google Scholar 

  7. Bozorgzadeh B, Schuweiler DR, Bobak MJ, Garris PA, Mohseni P (2016) Neurochemostat: a neural interface SoC with integrated chemometrics for closed-loop regulation of brain dopamine. IEEE Trans Biomed Circuits Syst 10(3):654–667

    Article  PubMed  Google Scholar 

  8. Brenna S, Padovan F, Neviani A, Bevilacqua A, Bonfanti A, Lacaita AL (2016) A 64-channel 965-$\mu\text {W} $ neural recording SoC with UWB wireless transmission in 130-nm CMOS. IEEE Trans Circuits Syst Express Briefs 63(6):528–532

    Article  Google Scholar 

  9. Carmena JM, Lebedev MA, Crist RE, O’Doherty JE, Santucci DM, Dimitrov DF, …, Nicolelis MA (2003) Learning to control a brain–machine interface for reaching and grasping by primates. PLoS Biol 1(2):e42

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Castagnola E, Maiolo L, Maggiolini E, Minotti A, Marrani M, Maita F, …, Fadiga L (2015a) PEDOT-CNT-coated low-impedance, ultra-flexible, and brain-conformable micro-ECoG arrays. IEEE Trans Neural Syst Rehabil Eng 23(3):342–350

    Article  PubMed  Google Scholar 

  11. Castagnola V, Descamps E, Lecestre A, Dahan L, Remaud J, Nowak LG, Bergaud C (2015b) Parylene-based flexible neural probes with PEDOT coated surface for brain stimulation and recording. Biosens Bioelectron 67:450–457

    Article  CAS  PubMed  Google Scholar 

  12. Chen G, Dodson B, Hedges DM, Steffensen SC, Harb JN, Puleo C, …, Davis RC (2018) Fabrication of high aspect ratio millimeter-tall free-standing carbon nanotube-based microelectrode arrays. ACS Biomater Sci Eng 4(5):1900–1907

    Google Scholar 

  13. Collinger JL, Wodlinger B, Downey JE, Wang W, Tyler-Kabara EC, Weber DJ, …, Schwartz AB (2013) High-performance neuroprosthetic control by an individual with tetraplegia. Lancet 381(9866):557–564

    Article  Google Scholar 

  14. Dadarlat MC, O’doherty JE, Sabes PN (2015) A learning-based approach to artificial sensory feedback leads to optimal integration. Nat Neurosci 18(1):138

    Article  CAS  PubMed  Google Scholar 

  15. Deku F, Cohen Y, Joshi-Imre A, Kanneganti A, Gardner TJ, Cogan SF (2018) Amorphous silicon carbide ultramicroelectrode arrays for neural stimulation and recording. J Neural Eng 15(1):016007

    Article  PubMed  PubMed Central  Google Scholar 

  16. Diaz-Botia CA, Luna LE, Neely RM, Chamanzar M, Carraro C, Carmena JM, …, Maharbiz MM (2017) A silicon carbide array for electrocorticography and peripheral nerve recording. J Neural Eng 14(5):056006

    Article  CAS  PubMed  Google Scholar 

  17. Gao H, Walker RM, Nuyujukian P, Makinwa KA, Shenoy KV, Murmann B, Meng TH (2012) HermesE: a 96-channel full data rate direct neural Interface in 0.13μm CMOS. IEEE J Solid State Circuits 47(4):1043–1055

    Article  Google Scholar 

  18. Gao P, Trautmann E, Byron MY, Santhanam G, Ryu S, Shenoy K, Ganguli S (2017) A theory of multineuronal dimensionality, dynamics and measurement. bioRxiv 1:214262

    Google Scholar 

  19. Heelan C, Komar J, Vargas-Irwin CE, Simeral JD, Nurmikko AV (2015) A mobile embedded platform for high performance neural signal computation and communication. In: 2015 IEEE biomedical circuits and systems conference (BioCAS), October. IEEE, pp 1–4

    Google Scholar 

  20. Heelan C, Nurmikko AV, Truccolo W (2018) FPGA implementation of deep-learning recurrent neural networks with sub-millisecond real-time latency for BCI-decoding of large-scale neural sensors (104 nodes). In: 2018 40th annual international conference of the ieee engineering in medicine and biology society (EMBC), July. IEEE, pp 1070–1073

    Google Scholar 

  21. Hochberg LR, Serruya MD, Friehs GM, Mukand JA, Saleh M, Caplan AH, …, Donoghue JP (2006) Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 442(7099):164

    Article  CAS  PubMed  Google Scholar 

  22. Hochberg LR, Bacher D, Jarosiewicz B, Masse NY, Simeral JD, Vogel J, …, Donoghue JP (2012) Reach and grasp by people with tetraplegia using a neurally controlled robotic arm. Nature 485(7398):372

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Jarosiewicz B, Sarma AA, Bacher D, Masse NY, Simeral JD, Sorice B, …, Cash SS (2015) Virtual typing by people with tetraplegia using a self-calibrating intracortical brain-computer interface. Sci Trans Med 7(313):313ra179

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Jeong J, Laiwalla F, Lee J, Ritasalo R, Pudas M, Larson L, …, Nurmikko A (2019) Conformal hermetic sealing of wireless microelectronic implantable Chiplets by multilayered atomic layer deposition (ALD). Adv Funct Mater 29(5):1806440

    Google Scholar 

  25. Jun JJ, Steinmetz NA, Siegle JH, Denman DJ, Bauza M, Barbarits B et al (2017) Fully integrated silicon probes for high-density recording of neural activity. Nature 551(7679):232

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Khodagholy D, Gelinas JN, Thesen T, Doyle W, Devinsky O, Malliaras GG, Buzsáki G (2015) NeuroGrid: recording action potentials from the surface of the brain. Nat Neurosci 18(2):310

    Article  CAS  PubMed  Google Scholar 

  27. Kozai TD, Catt K, Du Z, Na K, Srivannavit O, Razi-ul MH, …, Cui XT (2016) Chronic in vivo evaluation of PEDOT/CNT for stable neural recordings. IEEE Trans Biomed Eng 63(1):111–119

    Article  PubMed  Google Scholar 

  28. Kwon KY, Lee HM, Ghovanloo M, Weber A, Li W (2015) Design, fabrication, and packaging of an integrated, wirelessly-powered optrode array for optogenetics application. Front Syst Neurosci 9:69

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. Lee J, Mok E, Huang J, Cui L, Lee AH, Leung VW, Mercier P, Shellhammer S, Larson L, Asbeck A, Song YK, Nurmikko A, Laiwalla F (2019) An implantable wireless network of distributed microscale sensors for neural applications. IEEE EMBS conference on neural engineering 2019

    Google Scholar 

  30. Leuthardt EC, Schalk G, Wolpaw JR, Ojemann JG, Moran DW (2004) A brain–computer interface using electrocorticographic signals in humans. J Neural Eng 1(2):63

    Article  PubMed  Google Scholar 

  31. Liu X, Zhang M, Xiong T, Richardson AG, Lucas TH, Chin PS, …, Van der Spiegel J (2016) A fully integrated wireless compressed sensing neural signal acquisition system for chronic recording and brain machine interface. IEEE Trans Biomed Circuits Syst 10(4):874–883

    Article  PubMed  Google Scholar 

  32. Luan L, Wei X, Zhao Z, Siegel JJ, Potnis O, Tuppen CA, …, Dunn AK (2017) Ultraflexible nanoelectronic probes form reliable, glial scar–free neural integration. Sci Adv 3(2):e1601966

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  33. McDermott H (2016) Neurobionics: treatments for disorders of the central nervous system. In: Neurobionics: the biomedical engineering of neural prostheses. Wiley, Hoboken, pp 213–230

    Chapter  Google Scholar 

  34. Mestais CS, Charvet G, Sauter-Starace F, Foerster M, Ratel D, Benabid AL (2015) WIMAGINE: wireless 64-channel ECoG recording implant for long term clinical applications. IEEE Trans Neural Syst Rehabil Eng 23(1):10–21

    Article  PubMed  Google Scholar 

  35. Mirbozorgi SA, Bahrami H, Sawan M, Rusch LA, Gosselin B (2016) A single-chip full-duplex high speed transceiver for multi-site stimulating and recording neural implants. IEEE Trans Biomed Circuits Syst 10(3):643–653

    Article  PubMed  Google Scholar 

  36. Müller-Putz GR, Schwarz A, Pereira J, Ofner P (2016) From classic motor imagery to complex movement intention decoding: the noninvasive Graz-BCI approach. In: Progress in brain research, vol 228. Elsevier, pp 39–70

    Google Scholar 

  37. Oxley TJ, Opie NL, John SE, Rind GS, Ronayne SM, Wheeler TL, …, Steward C (2016) Minimally invasive endovascular stent-electrode array for high-fidelity, chronic recordings of cortical neural activity. Nat Biotechnol 34(3):320

    Google Scholar 

  38. Park YS, Hochberg LR, Eskandar EN, Cash SS, Truccolo W (2013) Early detection of human epileptic seizures based on intracortical local field potentials. In: 2013 6th international IEEE/EMBS conference on neural engineering (NER), November. IEEE, pp 323–326

    Google Scholar 

  39. Raducanu BC, Yazicioglu RF, Lopez CM, Ballini M, Putzeys J, Wang S et al (2016) Time multiplexed active neural probe with 678 parallel recording sites. In: 2016 46th European solid-state device research conference (ESSDERC). IEEE, pp 385–388

    Google Scholar 

  40. Rios G, Lubenov EV, Chi D, Roukes ML, Siapas AG (2016) Nanofabricated neural probes for dense 3-D recordings of brain activity. Nano Lett 16(11):6857–6862

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Santhanam G, Linderman MD, Gilja V, Afshar A, Ryu SI, Meng TH, Shenoy KV (2007) HermesB: a continuous neural recording system for freely behaving primates. IEEE Trans Biomed Eng 54(11):2037–2050

    Article  PubMed  Google Scholar 

  42. Schwarz DA, Lebedev MA, Hanson TL, Dimitrov DF, Lehew G, Meloy J, …, Ramakrishnan A (2014) Chronic, wireless recordings of large-scale brain activity in freely moving rhesus monkeys. Nat Methods 11(6):670

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Seo D, Carmena JM, Rabaey JM, Alon E, Maharbiz MM (2013) Neural dust: an ultrasonic, low power solution for chronic brain-machine interfaces. arXiv preprint arXiv:1307.2196

    Google Scholar 

  44. Seo D, Neely RM, Shen K, Singhal U, Alon E, Rabaey JM, …, Maharbiz MM (2016) Wireless recording in the peripheral nervous system with ultrasonic neural dust. Neuron 91(3):529–539

    Article  CAS  PubMed  Google Scholar 

  45. Seymour EÇ, Freedman DS, Gökkavas M, Özbay E, Sahin M, Ünlü MS (2014) Improved selectivity from a wavelength addressable device for wireless stimulation of neural tissue. Front Neuroeng 7:5

    Article  PubMed  PubMed Central  Google Scholar 

  46. Simeral JD, Kim SP, Black MJ, Donoghue JP, Hochberg LR (2011) Neural control of cursor trajectory and click by a human with tetraplegia 1000 days after implant of an intracortical microelectrode array. J Neural Eng 8(2):025027

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Tabot GA, Dammann JF, Berg JA, Tenore FV, Boback JL, Vogelstein RJ, Bensmaia SJ (2013) Restoring the sense of touch with a prosthetic hand through a brain interface. Proc Natl Acad Sci 110(45):18279–18284

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Tsai D, Sawyer D, Bradd A, Yuste R, Shepard KL (2017) A very large-scale microelectrode array for cellular-resolution electrophysiology. Nat Commun 8(1):1802

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Viventi J, Kim DH, Vigeland L, Frechette ES, Blanco JA, Kim YS, …, Wulsin DF (2011) Flexible, foldable, actively multiplexed, high-density electrode array for mapping brain activity in vivo. Nat Neurosci 14(12):1599

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Wang W, Collinger JL, Degenhart AD, Tyler-Kabara EC, Schwartz AB, Moran DW, …, Kelly JW (2013) An electrocorticographic brain interface in an individual with tetraplegia. PLoS One 8(2):e55344

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Wessberg J, Stambaugh CR, Kralik JD, Beck PD, Laubach M, Chapin JK, …, Nicolelis MA (2000) Real-time prediction of hand trajectory by ensembles of cortical neurons in primates. Nature 408(6810):361

    Article  CAS  PubMed  Google Scholar 

  52. Wodlinger B, Downey JE, Tyler-Kabara EC, Schwartz AB, Boninger ML, Collinger JL (2014) Ten-dimensional anthropomorphic arm control in a human brain− machine interface: difficulties, solutions, and limitations. J Neural Eng 12(1):016011

    Article  PubMed  Google Scholar 

  53. Yeon P, Mirbozorgi S, Ash B, Eckhardt H, Ghovanloo M (2016) Fabrication and microassembly of a mm-sized floating probe for a distributed wireless neural interface. Micromachines 7(9):154

    Article  PubMed Central  Google Scholar 

  54. Yeon P, Gonzalez JL, Zia M, Rajan SK, May GS, Bakir MS, Ghovanloo M (2017) Microfabrication, assembly, and hermetic packaging of mm-sized free-floating neural probes. In 2017 IEEE biomedical circuits and systems conference (BioCAS), October. IEEE, pp 1–4

    Google Scholar 

  55. Yin M, Borton DA, Komar J, Agha N, Lu Y, Li H, …, Larson L (2014) Wireless neurosensor for full-spectrum electrophysiology recordings during free behavior. Neuron 84(6):1170–1182

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

The authors are very grateful to many members, past and present, in their laboratory. These include Jihun Lee, Joonsoo Jeong, David Borton, Ming Yin, Y.-K. Song, William R. Patterson III, Naubahar Agha, and Chris Heelan, among others. At Brown University, the authors are part of a synergistic brain science and neurotechnology effort with many colleagues including John Donoghue, Leigh Hochberg, David Rosler, John Simeral, and Carlos Vargas-Irwin whom we thank for their continuing input and expertise. Special thanks are also extended to Krishna Shenoy and his colleagues at Stanford for providing early leadership in the field.

All animal procedures referred in this chapter were conducted according to protocols approved by Institutional Animal Care and Use Committee (IACUC) at each institution. Research in the authors’ laboratory was supported by US National Institutes of Health, Defense Advanced Projects Agency and the National Science Foundation.

Author information

Authors and Affiliations

  1. School of Engineering, Brown University, Providence, RI, USA

    Farah Laiwalla & Arto Nurmikko

Authors
  1. Farah Laiwalla
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Arto Nurmikko
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Arto Nurmikko .

Editor information

Editors and Affiliations

  1. Qiushi Academy for Advanced Studies, Zhejiang University, Hangzhou, Zhejiang, China

    Xiaoxiang Zheng

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Laiwalla, F., Nurmikko, A. (2019). Future of Neural Interfaces. In: Zheng, X. (eds) Neural Interface: Frontiers and Applications. Advances in Experimental Medicine and Biology, vol 1101. Springer, Singapore. https://doi.org/10.1007/978-981-13-2050-7_9

Download citation

Publish with us

Policies and ethics

Search

Navigation