Skip to main content
SpringerLink
Log in

A Concurrent Brain-Machine Interface for Enhanced Sequential Motor Function

  • Chapter
  • First Online:
Brain-Computer Interface Research

Part of the book series: SpringerBriefs in Electrical and Computer Engineering ((BRIEFSELECTRIC))

Abstract

Brain-machine interfaces (BMIs) have largely been designed for performing single-targeted movements. However, many tasks involve planning a sequence of such targeted movements before execution. Hence a BMI that can concurrently decode the complete planned sequence before its execution can enable subjects to also perform these sequential movements. Moreover, such concurrent decoding may allow the BMI to consider the higher-level goal of the task to reformulate the motor plan and perform it more effectively. Here, we demonstrate that concurrent BMI decoding is possible. Using population-wide modeling, we discovered two distinct subpopulations of neurons in the rhesus monkey premotor cortex that allowed two planned targets of a sequential movement to be simultaneously held in working memory without degradation. Interestingly, this simultaneous representation occurred because each subpopulation encoded either only currently held or only newly added target information regardless of the exact sequence. Capitalizing on this stable representation, we developed a BMI that concurrently decodes a full motor sequence in advance of movement and can then accurately execute it as desired.

This work was published in part in Nature Neuroscience (Shanechi et al. 2012a).

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 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

  • Averbeck BB, Chafee MV, Crowe DA, Georgopoulos AP (2002) Parallel processing of serial movements in prefrontal cortex. Proc Natl Acad Sci USA 99:13172–13177

    Article  Google Scholar 

  • Averbeck BB, Sohn J-W, Lee D (2006) Activity in prefrontal cortex during dynamic selection of action sequences. Nat Neurosci 9:276–282

    Article  Google Scholar 

  • Baldauf D, Cui H, Andersen RA (2008) The posterior parietal cortex encodes in parallel both goals for double-reach sequences. J Neurosci 28:10081–10089

    Article  Google Scholar 

  • Batista AP, Andersen RA (2001) The parietal reach region codes the next planned movement in a sequential reach task. J Neurophysiol 85:539–544

    Google Scholar 

  • Boussaoud D, Bremmer F (1999) Gaze effects in the cerebral cortex: reference frames for space coding and action. Exp Brain Res 128:170–180

    Article  Google Scholar 

  • Brown EN, Frank LM, Tang D, Quirk MC, Wilson MA (1998) A statistical paradigm for neural spike train decoding applied to position prediction from ensemble firing patterns of rat hippocampal place cells. J Neurosci 18:7411–7425

    Google Scholar 

  • Carmena JM et al (2003) Learning to control a brain-machine interface for reaching and grasping by primates. PLoS Biol 1:193–208

    Article  Google Scholar 

  • Chapin JK, Moxon KA, Markowitz RS, Nicolelis MAL (1999) Real-time control of a robot arm using simultaneously recorded neurons in the motor cortex. Nat Neurosci 2:664–670

    Article  Google Scholar 

  • Chase SM, Schwartz AB, Kass RE (2009) Bias, optimal linear estimation, and the differences between open-loop simulation and closed-loop performance of spiking-based brain-computer interface algorithms. Neural Netw 22:1203–1213

    Article  Google Scholar 

  • Crammond DJ, Kalaska JF (1994) Modulation of preparatory neuronal activity in dorsal premotor cortex due to stimulus-response compatibility. J Neurophysiol 71:1281–1284

    Google Scholar 

  • Crammond DJ, Kalaska JF (1996) Differential relation of discharge in primary motor cortex and premotor cortex to movements versus actively maintained postures during a reaching task. Exp Brain Res 108:45–61

    Article  Google Scholar 

  • Crammond DJ, Kalaska JF (2000) Prior information in motor and premotor cortex: activity during the delay period and effect on pre-movement activity. J Neurophysiol 84:986–1005

    Google Scholar 

  • Crutcher MD, Russo GS, Ye S, Backus DA (2004) Target-, limb-, and context-dependent neural activity in the cingulate and supplementary motor areas of the monkey. Exp Brain Res 158:278–288

    Article  Google Scholar 

  • Dempster AP, Laird NM, Rubin DB (1977) Maximum likelihood from incomplete data via the EM algorithm. J Roy Statist Soc B 39:1–38

    MathSciNet  MATH  Google Scholar 

  • Eden UT, Frank LM, Barbieri R, Solo V, Brown EN (2004) Dynamic analysis of neural encoding by point process adaptive filtering. Neural Comput 16:971–998

    Article  MATH  Google Scholar 

  • Ganguly K, Carmena JM (2009) Emergence of a stable cortical map for neuroprosthetic control. PLoS Biol 7:1–13

    Article  Google Scholar 

  • Hochberg LR et al (2006) Neuronal ensemble control of prosthetic devices by a human with tetraplegia. Nature 442:164–171

    Article  Google Scholar 

  • Hocherman S, Wise SP (1991) Effects of hand movement path on motor cortical activity in awake, behaving rhesus monkeys. Exp Brain Res 83:285–302

    Article  Google Scholar 

  • Jong PD, Mackinnon MJ (1988) Covariances for smoothed estimates in state space models. Biometrika 75:601–602

    Article  MathSciNet  MATH  Google Scholar 

  • Kettner RE, Marcario JK, Port NL (1996) Control of remembered reaching sequences in monkey. II. Storage and preparation before movement in motor and premotor cortex. Exp Brain Res 112:347–358

    Article  Google Scholar 

  • Kim S-P, Simeral JD, Hochberg LR, Donoghue JP, Black MJ (2008) Neural control of computer cursor velocity by decoding motor cortical spiking activity in humans with tetraplegia. J Neural Eng 5:455–476

    Article  Google Scholar 

  • Kurata K (1993) Premotor cortex of monkeys: Set- and movement-related activity reflecting amplitude and direction of wrist movements. J Neurophysiol 69:187–200

    Google Scholar 

  • Li Z et al (2009) Unscented Kalman filter for brain-machine interfaces. PLoS ONE 4:1–18

    Article  Google Scholar 

  • Lu X, Ashe J (2005) Anticipatory activity in primary motor cortex codes memorized movement sequences. Neuron 45:967–973

    Article  Google Scholar 

  • Messier J, Kalaska JF (2000) Covariation of primate dorsal premotor cell activity with direction and amplitude during a memorized-delay reaching task. J Neurophysiol 84:152–165

    Google Scholar 

  • Moritz CT, Perlmutter SI, Fetz EE (2008) Direct control of paralysed muscles by cortical neurons. Nature 456:639–643

    Article  Google Scholar 

  • Mulliken GH, Musallam S, Andersen RA (2008) Decoding trajectories from posterior parietal cortex ensembles. J Neurosci 28:12913–12926

    Article  Google Scholar 

  • Musallam S, Corneil BD, Greger B, Scherberger H, Andersen RA (2004) Cognitive control signals for neural prosthetics. Science 305:258–262

    Article  Google Scholar 

  • Mushiake H, Inase M, Tanji J (1990) Selective coding of motor sequence in the supplementary motor area of the monkey cerebral cortex. Exp Brain Res 82:208–210

    Article  Google Scholar 

  • Mushiake H, Saito N, Sakamoto K, Itoyama Y, Tanji J (2006) Activity in the lateral prefrontal cortex reflects multiple steps of future events in action plans. Neuron 50:631–641

    Article  Google Scholar 

  • Nakajima T, Hosaka R, Mushiake H, Tanji J (2009) Covert representation of second-next movement in the pre-supplementary motor area of monkeys. J Neurophysiol 101:1883–1889

    Article  Google Scholar 

  • Ninokura Y, Mushiake H, Tanji J (2003) Representation of the temporal order of visual objects in the primate lateral prefrontal cortex. J Neurophysiol 89:2868–2873

    Article  Google Scholar 

  • Ohbayashi M, Ohki K, Miyashita Y (2003) Conversion of working memory to motor sequence in the monkey premotor cortex. Science 301:233–236

    Article  Google Scholar 

  • Saito N, Mushiake H, Sakamoto K, Itoyama Y, Tanji J (2005) Representation of immediate and final behavioral goals in the monkey prefrontal cortex during an instructed delay period. Cereb Cortex 15:1535–1546

    Article  Google Scholar 

  • Santhanam G, Ryu SI, Yu BM, Afshar A, Shenoy KV (2006) A high-performance brain-computer interface. Nature 442:195–198

    Article  Google Scholar 

  • Serruya MD, Hatsopoulos NG, Paninski L, Fellows MR, Donoghue JP (2002) Instant neural control of a movement signal. Nature 416:141–142

    Article  Google Scholar 

  • Shanechi MM, Hu RC, Powers M, Wornell GW, Brown EN, Williams ZM (2012a) Neural population partitioning and a concurrent brain-machine interface for sequential motor function. Nat Neurosci 15:1715–1722

    Google Scholar 

  • Shanechi MM, Wornell GW, Williams ZM, Brown EN (2012b) Feedback-controlled parallel point process filter for estimation of goal-directed movements from neural signals. IEEE Trans Neural Syst Rehabil Eng. doi:10.1109/TNSRE.2012.2221743

  • Shanechi MM, Williams ZM, Wornell GW, Hu RC, Powers M, Brown EN (2013) A Real-time brain-machine interface combining motor target and trajectory intent using an optimal feedback control design. PLoS ONE 8:e59049.

    Google Scholar 

  • Shanechi MM, Hu RC, Williams ZM (2014) A cortical–spinal prosthesis for targeted limb movement in paralysed primate avatars. Nat Commun 5:3237. doi:10.1038/ncomms4237.

  • Shima K, Tanji J (2000) Neuronal activity in the supplementary and presupplementary motor areas for temporal organization of multiple movements. J Neurophysiol 84:2148–2160

    Google Scholar 

  • Shima K, Isoda M, Mushiake H, Tanji J (2007) Categorization of behavioural sequences in the prefrontal cortex. Nature 445:315–318

    Article  Google Scholar 

  • Smith AC, Brown EN (2003) Estimating a state-space model from point process observations. Neural Comput 15:965–991

    Article  MATH  Google Scholar 

  • Smith AC et al (2010) State-space algorithms for estimating spike rate functions. Comput Intell Neurosci 2010

    Google Scholar 

  • Tanji J, Shima K (1994) Role for supplementary motor area cells in planning several movements ahead. Nature 371:413–416

    Article  Google Scholar 

  • Taylor DM, Tillery SIH, Schwartz AB (2002) Direct cortical control of 3D neuroprosthetic devices. Science 296:1829–1832

    Article  Google Scholar 

  • Truccolo W, Eden UT, Fellows MR, Donoghue JP, Brown EN (2005) A point process framework for relating neural spiking activity to spiking history, neural ensemble, and extrinsic covariate effects. J Neurophysiol 93:1074–1089

    Article  Google Scholar 

  • Velliste M, Perel S, Spalding MC, Whitford AS, Schwartz AB (2008) Cortical control of a prosthetic arm for self-feeding. Nature 453:1098–1101

    Article  Google Scholar 

  • Wessberg J et al (2000) Real-time prediction of hand trajectory by ensembles of cortical neurons in primates. Nature 408:361–365

    Article  Google Scholar 

  • Wolpaw JR, McFarland DJ (2004) Control of a two-dimensional movement signal by a noninvasive brain-computer interface in humans. Proc Natl Acad Sci USA 101:17849–17854

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, CA, USA

    Maryam M. Shanechi

  2. Massachusetts General Hospital, Boston, MA, USA

    Rollin C. Hu, Marissa Powers, Emery N. Brown & Ziv M. Williams

  3. Harvard Medical School, Boston, MA, USA

    Rollin C. Hu, Emery N. Brown & Ziv M. Williams

  4. Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA

    Gregory W. Wornell

  5. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

    Emery N. Brown

Authors
  1. Maryam M. Shanechi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rollin C. Hu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marissa Powers
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gregory W. Wornell
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Emery N. Brown
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ziv M. Williams
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Maryam M. Shanechi .

Editor information

Editors and Affiliations

  1. Schiedlberg, Austria

    Christoph Guger

  2. Albany, New York, USA

    Theresa Vaughan

  3. Cognitive Science Dept., UC San Diego, La Jolla, California, USA

    Brendan Allison

Rights and permissions

Reprints and permissions

Copyright information

© 2014 The Author(s)

About this chapter

Cite this chapter

Shanechi, M.M., Hu, R.C., Powers, M., Wornell, G.W., Brown, E.N., Williams, Z.M. (2014). A Concurrent Brain-Machine Interface for Enhanced Sequential Motor Function. In: Guger, C., Vaughan, T., Allison, B. (eds) Brain-Computer Interface Research. SpringerBriefs in Electrical and Computer Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-09979-8_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-09979-8_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-09978-1

  • Online ISBN: 978-3-319-09979-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation