Restoring sensorimotor function through intracortical interfaces: progress and looming challenges

Bensmaia, Sliman J.; Miller, Lee E.

doi:10.1038/nrn3724

Cited by 368Neuroscience and Neural EngineeringEEG and Brain-Computer InterfacesMuscle activation and electromyography studies

Restoring sensorimotor function through intracortical interfaces: progress and looming challenges

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Bensmaia, Sliman J., Miller, Lee E.·2014·Nature Reviews Neuroscience

DOI 10.1038/nrn3724PMC PMC12278825

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Abstract

The loss of a limb or paralysis resulting from spinal cord injury has devastating consequences on quality of life. One approach to restoring lost sensory and motor abilities in amputees and patients with tetraplegia is to supply them with implants that provide a direct interface with the CNS. Such brain–machine interfaces might enable a patient to exert voluntary control over a prosthetic or robotic limb or over the electrically induced contractions of paralysed muscles. A parallel interface could convey sensory information about the consequences of these movements back to the patient. Recent developments in the algorithms that decode motor intention from neuronal activity and in approaches to convey sensory feedback by electrically stimulating neurons, using biomimetic and adaptation-based approaches, have shown the promise of invasive interfaces with sensorimotor cortices, although substantial challenges remain.

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These flexible stimulators function by releasing electrical and optical signals into the brain, spinal cord, and periphery nerves to achieve neural modulation for sensory perception and motor rehabilitation.
“These flexible stimulators function by releasing (electrical and optical) signals into the brain,[272] spinal cord,[522] and periphery nerves[529] to achieve neural modulation for associated sensory perception and motor rehabilitation.”
From Flexible Electronics and Devices as Human–Machine Interfaces for Medical Robotics (2022) · cites this paper as [272]
The section on eliciting somatosensory percepts through cortical stimulation describes electrical stimulation of the brain to evoke sensations and discusses optogenetic stimulation as a possible approach. It does not establish that flexible stimulators deliver both electrical and optical signals to the brain for sensory perception and motor rehabilitation; the optical approach is presented as prospective. In the printed sentence, this citation is attached to the brain, not the spinal-cord or peripheral-nerve claims. (LLM, conf=0.84)
Experimental — accuracy not yet measured
ICMS pulse trains transferred through implanted electrodes (UEAs) in a monkey can restore sensory feedback.
“In other studies, ICMS pulse trains have been transferred through implanted electrodes (UEAs) in a monkey for restoration of sensory feedback (Bensmaia and Miller, 2014; Chen et al., 2014; Kim et al., 2015).”
From Selectivity and Longevity of Peripheral-Nerve and Machine Interfaces: A Review. (2017) · cites this paper as Bensmaia and Miller, 2014
In “Adaptation in sensory BMIs” (page unavailable), the review reports that a monkey used somatosensory ICMS delivered across eight electrodes to guide a cursor. In “Elicitation of somatosensory percepts through cortical stimulation” (page unavailable), it describes monkey experiments with ICMS pulse trains, but frames restoring lost touch and proprioception as a future goal. The passages do not identify the electrodes as UEAs or establish that sensory feedback was restored in the monkey. (LLM, conf=0.87)
Experimental — accuracy not yet measured
Subcutaneous invasive electrophysiological signals can be obtained through brain interfaces, ECoG on the cortical surface, and LFPs from electrodes inserted into the cortex.
“Subcutaneous invasive electrophysiological signals can be derived through brain interfaces,[270–272] using electrocorticography (ECoG)[273,274] on the cortical surface as well as local field potentials (LFP)[275,276] extracted from electrodes inserted into the cortex.”
From Flexible Electronics and Devices as Human–Machine Interfaces for Medical Robotics (2022) · cites this paper as [272]
Sophisticated approaches have been developed to control prosthetic hands intuitively.
“Major strides have been made in the development of approaches to control these hands either by decoding motor intent from myoelectric signals (Fougner et al., 2012;Schultz and Kuiken, 2011) or from the activation of neurons in motor cortex (Bensmaia and Miller, 2014;Wodlinger et al., 2015).”
From Biomimetic approaches to bionic touch through a peripheral nerve interface (2015) · cites this paper as Bensmaia and Miller, 2014

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Electrically controlled release of the nerve growth factor from a collagen–carbon nanotube composite for supporting neuronal growth
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Laying the Ghost of ‘Muscles Versus Movements’
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Towards a Naturalistic Brain-Machine Interface: Hybrid Torque and Position Control Allows Generalization to Novel Dynamics
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Lack of Adaptation to Random Conflicting Force Fields of Variable Magnitude
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A Fully Implantable, Programmable and Multimodal Neuroprocessor for Wireless, Cortically Controlled Brain-Machine Interface Applications
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Neural Decoding of Movements: From Linear to Nonlinear Trajectory Models
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Continuous decoding of grasping tasks for a prospective implantable cortical neuroprosthesis
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Decoding Dexterous Finger Movements in a Neural Prosthesis Model Approaching Real-World Conditions
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2 of the 197 references couldn’t be matched to a known paper.

Research works printed but not linked: 2

[144]Yu B, Cunningham J, Shenoy K & Sahani M in Neural Information Processing; Lecture Notes in Computer Science Vol. 4984 (eds Ishikawa M, Doya K, Miyamoto H & Yamakawa T) 586– 595 (Springer, 2008).
[192]Malarkey E & Parpura V in Brain Edema XIV Vol. 106 Acta Neurochirurgica Supplementum (eds Czernicki Z) 337– 341 (Springer, 2010).

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Pursuing prosthetic electronic skin
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Flexible Electronics and Devices as Human–Machine Interfaces for Medical Robotics
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Long-term stability of cortical population dynamics underlying consistent behavior
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Clinical translation of a high-performance neural prosthesis
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Proprioceptive and cutaneous sensations in humans elicited by intracortical microstimulation
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High‐Aspect‐Ratio Nanostructured Surfaces as Biological Metamaterials
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Graphene-Based Interfaces Do Not Alter Target Nerve Cells
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Non-Invasive Activation of Cervical Spinal Networks after Severe Paralysis
Gad, P. N., Lee, S., Terrafranca, N., Zhong, H., Turner, A. E., Gerasimenko, Y., & Edgerton, V. R. (2018) · Journal of Neurotrauma · doi:10.1089/neu.2017.5461 · Cited by 210 · see citing works
Biomimetic approaches to bionic touch through a peripheral nerve interface
Saal, H. P., & Bensmaia, S. J. (2015) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2015.06.010 · Cited by 179 · see citing works
“Major strides have been made in the development of approaches to control these hands either by decoding motor intent from myoelectric signals (Fougner et al., 2012; Schultz and Kuiken, 2011) or from the activation of neurons in motor cortex (Bensmaia and Miller, 2014; Wodlinger et al., 2015).”
Influential
Combining Decoder Design and Neural Adaptation in Brain-Machine Interfaces
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Brain–computer interfaces: the innovative key to unlocking neurological conditions
Zhang, H., Jiao, L., Yang, S., Li, H., Jiang, X., Feng, J., Zou, S., Xu, Q., Gu, J., Wang, X., et al. (2024) · International Journal of Surgery · doi:10.1097/js9.0000000000002022 · Cited by 173 · see citing works
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Triboelectric bending sensor based smart glove towards intuitive multi-dimensional human-machine interfaces
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Mesh electronics: a new paradigm for tissue-like brain probes
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Restoring the Sense of Touch Using a Sensorimotor Demultiplexing Neural Interface
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Implantable microcoils for intracortical magnetic stimulation
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Should I stay or should I go? Conceptual underpinnings of goal-directed actions
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A review of critical challenges in MI-BCI: From conventional to deep learning methods
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Perspectives on classical controversies about the motor cortex
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Human perception of electrical stimulation on the surface of somatosensory cortex
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Behavioral assessment of sensitivity to intracortical microstimulation of primate somatosensory cortex
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Recent Progress on Microelectrodes in Neural Interfaces
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The Potential of Stereotactic-EEG for Brain-Computer Interfaces: Current Progress and Future Directions
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A Low-Noise Chopper Amplifier Designed for Multi-Channel Neural Signal Acquisition
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Decoding Movement From Electrocorticographic Activity: A Review
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Compliant intracortical implants reduce strains and strain rates in brain tissuein vivo
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Design of a Closed-Loop, Bidirectional Brain Machine Interface System With Energy Efficient Neural Feature Extraction and PID Control
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Real-time brain-machine interface in non-human primates achieves high-velocity prosthetic finger movements using a shallow feedforward neural network decoder
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Somatosensory Cortex Efficiently Processes Touch Located Beyond the Body
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Review: Human Intracortical Recording and Neural Decoding for Brain–Computer Interfaces
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Upper limb cortical maps in amputees with targeted muscle and sensory reinnervation
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Biomimetic encoding model for restoring touch in bionic hands through a nerve interface
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Selectivity and Longevity of Peripheral-Nerve and Machine Interfaces: A Review.
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“Preclinical works on the approaches related to the brain (Bensmaia and Miller, 2014), dorsal root ganglion (Weber et al., 2006, 2011; Bruns et al., 2013), and intra-spinal microstimulation (Gaunt et al., 2006; Capogrosso et al., 2016) are progressing.”
An Artificial Peripheral Neural System Based on Highly Stretchable and Integrated Multifunctional Sensors
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Rapid Integration of Artificial Sensory Feedback during Operant Conditioning of Motor Cortex Neurons
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Brain-Machine Interfaces: Powerful Tools for Clinical Treatment and Neuroscientific Investigations
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Neural Decoding for Intracortical Brain–Computer Interfaces
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Neuroprosthetic-enabled control of graded arm muscle contraction in a paralyzed human
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Decoding Local Field Potentials for Neural Interfaces
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Evoked haptic sensations in the hand via non-invasive proximal nerve stimulation
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The effects of chronic intracortical microstimulation on neural tissue and fine motor behavior
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Bioinspired Prosthetic Interfaces
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Feel-Good Robotics: Requirements on Touch for Embodiment in Assistive Robotics
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Going beyond primary motor cortex to improve brain–computer interfaces
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Sensory threshold neuromuscular electrical stimulation fosters motor imagery performance
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Challenges for Large-Scale Cortical Interfaces
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Task-Specific somatosensory feedback via cortical stimulation in humans
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Brain-machine interface facilitated neurorehabilitation via spinal stimulation after spinal cord injury: Recent progress and future perspectives
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Biomimetic computer-to-brain communication enhancing naturalistic touch sensations via peripheral nerve stimulation
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Biological and bionic hands: natural neural coding and artificial perception
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Syringe-injectable electronics with a plug-and-play input/output interface.
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The frequency of cortical microstimulation shapes artificial touch
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Enhanced Control of Cortical Pyramidal Neurons With Micromagnetic Stimulation
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Design and demonstration of an intracortical probe technology with tunable modulus
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A 128-Channel FPGA-Based Real-Time Spike-Sorting Bidirectional Closed-Loop Neural Interface System
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Regaining the senses of touch and movement
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Prostheses as extensions of the body: Progress and challenges
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Implantable Neural Interfaces and Wearable Tactile Systems for Bidirectional Neuroprosthetics Systems
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Bidirectional brain-computer interfaces
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Authors: Bensmaia, S. J., & Miller, L. E.
Affiliations: Northwestern University (US)
Corresponding author: Miller, Lee E.
ORCID: Miller, Lee E.
Venue: Nature Reviews Neuroscience
Publisher: Springer Science and Business Media LLC
Published: 2014-04-17
Volume: 15
Issue: 5
Pages: 313-325
ISSN: 1471-003X (ISSN-L)
1471-0048
DOI: 10.1038/nrn3724
PMC: PMC12278825
OpenAlex: W2074613775
Semantic Scholar: 8ef38d89080f639fcb493ec37ca04ea6b6c7f6dc
Cited by: 368
References: 197
Citations by year: 2026: 18 · 2025: 24 · 2024: 24 · 2023: 19 · 2022: 32 · 2021: 34 · 2020: 35 · 2019: 30 · 2018: 32 · 2017: 43 · 2016: 43 · 2015: 24 · 2014: 9 · 2013: 1
FWCI: 4.48
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: www.springer.com/tdm (tdm)
Locations: Nature reviews. Neuroscience (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Funders: National Institutes of Health (5r01ns048845-09)
U.S. Public Health Service (082865)
National Institute of Neurological Disorders and Stroke (NS-048845, R01-NS-048845, R01NS082865, R01NS053603, #NS053603)
Topics: Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
Keywords: sensorimotor cortex, prosthetic control, tetraplegia, spinal cord injury, amputation, motor intention decoding, sensory feedback, electrical stimulation of neurons
MeSH terms: Cerebral Cortex, Electric Stimulation, Humans, Movement, Paralysis, User-Computer Interface, Prostheses and Implants, Recovery of Function

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