Brain–machine interfaces: past, present and future
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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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.”
From Empirical perspectives from the self-model theory of subjectivity: a brief summary with examples (2007) · cites this paper as Lebedev and Nicolelis, 2006
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.”
From Empirical perspectives from the self-model theory of subjectivity: a brief summary with examples (2007) · cites this paper as Lebedev and Nicolelis, 2006
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.”
From A flexible three-dimensional electrode mesh: An enabling technology for wireless brain–computer interface prostheses (2016) · cites this paper as [26]
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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
- Semantic Scholar
- eb06f203a0b21f8d7e23efed26bdeb9fc7def49a
- 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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