Cited by 1,875EEG and Brain-Computer InterfacesNeuroscience and Neural EngineeringMuscle activation and electromyography studies

Brain–machine interfaces: past, present and future

Lebedev, Mikhail A., Nicolelis, Miguel A.L.·2006·Trends in Neurosciences

Abstract

Since the original demonstration that electrical activity generated by ensembles of cortical neurons can be employed directly to control a robotic manipulator, research on brain-machine interfaces (BMIs) has experienced an impressive growth. Today BMIs designed for both experimental and clinical studies can translate raw neuronal signals into motor commands that reproduce arm reaching and hand grasping movements in artificial actuators. Clearly, these developments hold promise for the restoration of limb mobility in paralyzed subjects. However, as we review here, before this goal can be reached several bottlenecks have to be passed. These include designing a fully implantable biocompatible recording device, further developing real-time computational algorithms, introducing a method for providing the brain with sensory feedback from the actuators, and designing and building artificial prostheses that can be controlled directly by brain-derived signals. By reaching these milestones, future BMIs will be able to drive and control revolutionary prostheses that feel and act like the human arm.

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Crossref · 10.1016/j.tins.2006.07.004

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151 of 151 references verified0 citation errors · 0 not checkable

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  • After animals started to control the actuator directly using their neuronal activity, their limbs eventually stopped moving, while the animals continued to control the actuator by generating proper modulations of their cortical neurons.

    “Remarkably, after these animals started to control the actuator directly using their neuronal activity, their limbs eventually stopped moving, while the animals continued to control the actuator by generating proper modulations of their cortical neurons.”
  • The brain was capable of undergoing a gradual assimilation of the actuator within the same maps that represented the body.

    “The most parsimonious interpretation of this finding is that the brain was capable of undergoing a gradual assimilation of the actuator within the same maps that represented the body.”
  • Stimulation in different layers of the cerebral cortex induces various activations of neuronal subtypes and their complex connection to subcortical regions, which leads to diverse cognition, sensory perception and motor control.

    “Stimulation in different layers of the cerebral cortex induces various activations of neuronal subtypes and their complex connection to subcortical regions, which leads to diverse cognition, sensory perception and motor control26.”

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Authors
Lebedev, M. A., & Nicolelis, M. A. L.
Affiliations
Duke University (US)
Corresponding author
Nicolelis, Miguel A.L.
Venue
Trends in Neurosciences
Publisher
Elsevier BV
Published
2006-09
Volume
29
Issue
9
Pages
536-546
ISSN
0166-2236 (ISSN-L)
OpenAlex
W2169866873
Cited by
1,875
References
151
Citations by year
2026: 73 · 2025: 120 · 2024: 114 · 2023: 66 · 2022: 51 · 2021: 97 · 2020: 75 · 2019: 95 · 2018: 96 · 2017: 97 · 2016: 110 · 2015: 129 · 2014: 126 · 2013: 105 · 2012: 107
FWCI
5.82
Type
journal article
Language
en
Open access
closed
Locations
  • Trends in Neurosciences (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neural Engineering
  • Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
Keywords
brain-computer interface, neural decoding, motor control, robotic arm control, biocompatible electrodes, real-time signal processing, sensory feedback, neural prostheses, paralysis
MeSH terms
Animals, Biofeedback, Psychology, Brain, Brain Diseases, Computer Systems, Electrodes, Implanted, Electroencephalography, Humans, Microelectrodes, Self-Help Devices, User-Computer Interface, Prostheses and Implants

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