Decoding neural activity to predict rat locomotion using intracortical and epidural arrays

Filipe O. Barroso, Bryan Yoder, David Tentler, Josephine J. Wallner, Amina A. Kinkhabwala, Maria K. Jantz, Robert Davisson Flint, Pablo M. Tostado, Evonne Pei, Ambika D.R. Satish, Sarah K. Brodnick, Aaron J. Suminski, Justin C. Williams, Lee E Miller, Matthew C Tresch*

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

Objective. Recovery of voluntary gait after spinal cord injury (SCI) requires the restoration of effective motor cortical commands, either by means of a mechanical connection to the limbs, or by restored functional connections to muscles. The latter approach might use functional electrical stimulation (FES), driven by cortical activity, to restore voluntary movements. Moreover, there is evidence that this peripheral stimulation, synchronized with patients' voluntary effort, can strengthen descending projections and recovery. As a step towards establishing such a cortically-controlled FES system for restoring function after SCI, we evaluate here the type and quantity of neural information needed to drive such a brain machine interface (BMI) in rats. We compared the accuracy of the predictions of hindlimb electromyograms (EMG) and kinematics using neural data from an intracortical array and a less-invasive epidural array. Approach. Seven rats were trained to walk on a treadmill with a stable pattern. One group of rats (n = 4) was implanted with intracortical arrays spanning the hindlimb sensorimotor cortex and EMG electrodes in the contralateral hindlimb. Another group (n = 3) was implanted with epidural arrays implanted on the dura overlying hindlimb sensorimotor cortex. EMG, kinematics and neural data were simultaneously recorded during locomotion. EMGs and kinematics were decoded using linear and nonlinear methods from multiunit activity and field potentials. Main results. Predictions of both kinematics and EMGs were effective when using either multiunit spiking or local field potentials (LFPs) recorded from intracortical arrays. Surprisingly, the signals from epidural arrays were essentially uninformative. Results from somatosensory evoked potentials (SSEPs) confirmed that these arrays recorded neural activity, corroborating our finding that this type of array is unlikely to provide useful information to guide an FES-BMI for rat walking. Significance. We believe that the accuracy of our decoders in predicting EMGs from multiunit spiking activity is sufficient to drive an FES-BMI. Our future goal is to use this rat model to evaluate the potential for cortically-controlled FES to be used to restore locomotion after SCI, as well as its further potential as a rehabilitative technology for improving general motor function.

Original languageEnglish (US)
Article number036005
JournalJournal of Neural Engineering
Volume16
Issue number3
DOIs
StatePublished - Jan 1 2019

Fingerprint

Locomotion
Decoding
Rats
Hindlimb
Brain-Computer Interfaces
Biomechanical Phenomena
Kinematics
Electromyography
Spinal Cord Injuries
Electric Stimulation
Brain
Deep Brain Stimulation
Recovery
Exercise equipment
Somatosensory Evoked Potentials
Bioelectric potentials
Gait
Restoration
Walking
Muscle

Keywords

  • Brain machine interface
  • Epidural
  • Functional electrical stimulation
  • Intracortical
  • Local field potential
  • Sensorimotor cortex
  • Spinal cord injury

ASJC Scopus subject areas

  • Biomedical Engineering
  • Cellular and Molecular Neuroscience

Cite this

Barroso, Filipe O. ; Yoder, Bryan ; Tentler, David ; Wallner, Josephine J. ; Kinkhabwala, Amina A. ; Jantz, Maria K. ; Flint, Robert Davisson ; Tostado, Pablo M. ; Pei, Evonne ; Satish, Ambika D.R. ; Brodnick, Sarah K. ; Suminski, Aaron J. ; Williams, Justin C. ; Miller, Lee E ; Tresch, Matthew C. / Decoding neural activity to predict rat locomotion using intracortical and epidural arrays. In: Journal of Neural Engineering. 2019 ; Vol. 16, No. 3.
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abstract = "Objective. Recovery of voluntary gait after spinal cord injury (SCI) requires the restoration of effective motor cortical commands, either by means of a mechanical connection to the limbs, or by restored functional connections to muscles. The latter approach might use functional electrical stimulation (FES), driven by cortical activity, to restore voluntary movements. Moreover, there is evidence that this peripheral stimulation, synchronized with patients' voluntary effort, can strengthen descending projections and recovery. As a step towards establishing such a cortically-controlled FES system for restoring function after SCI, we evaluate here the type and quantity of neural information needed to drive such a brain machine interface (BMI) in rats. We compared the accuracy of the predictions of hindlimb electromyograms (EMG) and kinematics using neural data from an intracortical array and a less-invasive epidural array. Approach. Seven rats were trained to walk on a treadmill with a stable pattern. One group of rats (n = 4) was implanted with intracortical arrays spanning the hindlimb sensorimotor cortex and EMG electrodes in the contralateral hindlimb. Another group (n = 3) was implanted with epidural arrays implanted on the dura overlying hindlimb sensorimotor cortex. EMG, kinematics and neural data were simultaneously recorded during locomotion. EMGs and kinematics were decoded using linear and nonlinear methods from multiunit activity and field potentials. Main results. Predictions of both kinematics and EMGs were effective when using either multiunit spiking or local field potentials (LFPs) recorded from intracortical arrays. Surprisingly, the signals from epidural arrays were essentially uninformative. Results from somatosensory evoked potentials (SSEPs) confirmed that these arrays recorded neural activity, corroborating our finding that this type of array is unlikely to provide useful information to guide an FES-BMI for rat walking. Significance. We believe that the accuracy of our decoders in predicting EMGs from multiunit spiking activity is sufficient to drive an FES-BMI. Our future goal is to use this rat model to evaluate the potential for cortically-controlled FES to be used to restore locomotion after SCI, as well as its further potential as a rehabilitative technology for improving general motor function.",
keywords = "Brain machine interface, Epidural, Functional electrical stimulation, Intracortical, Local field potential, Sensorimotor cortex, Spinal cord injury",
author = "Barroso, {Filipe O.} and Bryan Yoder and David Tentler and Wallner, {Josephine J.} and Kinkhabwala, {Amina A.} and Jantz, {Maria K.} and Flint, {Robert Davisson} and Tostado, {Pablo M.} and Evonne Pei and Satish, {Ambika D.R.} and Brodnick, {Sarah K.} and Suminski, {Aaron J.} and Williams, {Justin C.} and Miller, {Lee E} and Tresch, {Matthew C}",
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Barroso, FO, Yoder, B, Tentler, D, Wallner, JJ, Kinkhabwala, AA, Jantz, MK, Flint, RD, Tostado, PM, Pei, E, Satish, ADR, Brodnick, SK, Suminski, AJ, Williams, JC, Miller, LE & Tresch, MC 2019, 'Decoding neural activity to predict rat locomotion using intracortical and epidural arrays', Journal of Neural Engineering, vol. 16, no. 3, 036005. https://doi.org/10.1088/1741-2552/ab0698

Decoding neural activity to predict rat locomotion using intracortical and epidural arrays. / Barroso, Filipe O.; Yoder, Bryan; Tentler, David; Wallner, Josephine J.; Kinkhabwala, Amina A.; Jantz, Maria K.; Flint, Robert Davisson; Tostado, Pablo M.; Pei, Evonne; Satish, Ambika D.R.; Brodnick, Sarah K.; Suminski, Aaron J.; Williams, Justin C.; Miller, Lee E; Tresch, Matthew C.

In: Journal of Neural Engineering, Vol. 16, No. 3, 036005, 01.01.2019.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Decoding neural activity to predict rat locomotion using intracortical and epidural arrays

AU - Barroso, Filipe O.

AU - Yoder, Bryan

AU - Tentler, David

AU - Wallner, Josephine J.

AU - Kinkhabwala, Amina A.

AU - Jantz, Maria K.

AU - Flint, Robert Davisson

AU - Tostado, Pablo M.

AU - Pei, Evonne

AU - Satish, Ambika D.R.

AU - Brodnick, Sarah K.

AU - Suminski, Aaron J.

AU - Williams, Justin C.

AU - Miller, Lee E

AU - Tresch, Matthew C

PY - 2019/1/1

Y1 - 2019/1/1

N2 - Objective. Recovery of voluntary gait after spinal cord injury (SCI) requires the restoration of effective motor cortical commands, either by means of a mechanical connection to the limbs, or by restored functional connections to muscles. The latter approach might use functional electrical stimulation (FES), driven by cortical activity, to restore voluntary movements. Moreover, there is evidence that this peripheral stimulation, synchronized with patients' voluntary effort, can strengthen descending projections and recovery. As a step towards establishing such a cortically-controlled FES system for restoring function after SCI, we evaluate here the type and quantity of neural information needed to drive such a brain machine interface (BMI) in rats. We compared the accuracy of the predictions of hindlimb electromyograms (EMG) and kinematics using neural data from an intracortical array and a less-invasive epidural array. Approach. Seven rats were trained to walk on a treadmill with a stable pattern. One group of rats (n = 4) was implanted with intracortical arrays spanning the hindlimb sensorimotor cortex and EMG electrodes in the contralateral hindlimb. Another group (n = 3) was implanted with epidural arrays implanted on the dura overlying hindlimb sensorimotor cortex. EMG, kinematics and neural data were simultaneously recorded during locomotion. EMGs and kinematics were decoded using linear and nonlinear methods from multiunit activity and field potentials. Main results. Predictions of both kinematics and EMGs were effective when using either multiunit spiking or local field potentials (LFPs) recorded from intracortical arrays. Surprisingly, the signals from epidural arrays were essentially uninformative. Results from somatosensory evoked potentials (SSEPs) confirmed that these arrays recorded neural activity, corroborating our finding that this type of array is unlikely to provide useful information to guide an FES-BMI for rat walking. Significance. We believe that the accuracy of our decoders in predicting EMGs from multiunit spiking activity is sufficient to drive an FES-BMI. Our future goal is to use this rat model to evaluate the potential for cortically-controlled FES to be used to restore locomotion after SCI, as well as its further potential as a rehabilitative technology for improving general motor function.

AB - Objective. Recovery of voluntary gait after spinal cord injury (SCI) requires the restoration of effective motor cortical commands, either by means of a mechanical connection to the limbs, or by restored functional connections to muscles. The latter approach might use functional electrical stimulation (FES), driven by cortical activity, to restore voluntary movements. Moreover, there is evidence that this peripheral stimulation, synchronized with patients' voluntary effort, can strengthen descending projections and recovery. As a step towards establishing such a cortically-controlled FES system for restoring function after SCI, we evaluate here the type and quantity of neural information needed to drive such a brain machine interface (BMI) in rats. We compared the accuracy of the predictions of hindlimb electromyograms (EMG) and kinematics using neural data from an intracortical array and a less-invasive epidural array. Approach. Seven rats were trained to walk on a treadmill with a stable pattern. One group of rats (n = 4) was implanted with intracortical arrays spanning the hindlimb sensorimotor cortex and EMG electrodes in the contralateral hindlimb. Another group (n = 3) was implanted with epidural arrays implanted on the dura overlying hindlimb sensorimotor cortex. EMG, kinematics and neural data were simultaneously recorded during locomotion. EMGs and kinematics were decoded using linear and nonlinear methods from multiunit activity and field potentials. Main results. Predictions of both kinematics and EMGs were effective when using either multiunit spiking or local field potentials (LFPs) recorded from intracortical arrays. Surprisingly, the signals from epidural arrays were essentially uninformative. Results from somatosensory evoked potentials (SSEPs) confirmed that these arrays recorded neural activity, corroborating our finding that this type of array is unlikely to provide useful information to guide an FES-BMI for rat walking. Significance. We believe that the accuracy of our decoders in predicting EMGs from multiunit spiking activity is sufficient to drive an FES-BMI. Our future goal is to use this rat model to evaluate the potential for cortically-controlled FES to be used to restore locomotion after SCI, as well as its further potential as a rehabilitative technology for improving general motor function.

KW - Brain machine interface

KW - Epidural

KW - Functional electrical stimulation

KW - Intracortical

KW - Local field potential

KW - Sensorimotor cortex

KW - Spinal cord injury

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Barroso FO, Yoder B, Tentler D, Wallner JJ, Kinkhabwala AA, Jantz MK et al. Decoding neural activity to predict rat locomotion using intracortical and epidural arrays. Journal of Neural Engineering. 2019 Jan 1;16(3). 036005. https://doi.org/10.1088/1741-2552/ab0698