Direct control of paralyzed muscles by cortical neurons

By C. Moritz, S. Perlmutter, E. Fetz. Nature, 2008

627 citations recorded by the source corpus.

A potential treatment for paralysis resulting from spinal cord injury is to route control signals from the brain around the injury by artificial connections. Such signals could then control electrical stimulation of muscles, thereby restoring volitional movement to paralysed limbs. In previously separate experiments, activity of motor cortex neurons related to actual or imagined movements has been used to control computer cursors and robotic arms, and paralysed muscles have been activated by functional electrical stimulation. Here we show that Macaca nemestrina monkeys can directly control stimulation of muscles using the activity of neurons in the motor cortex, thereby restoring goal-directed movements to a transiently paralysed arm. Moreover, neurons could control functional stimulation equally well regardless of any previous association to movement, a finding that considerably expands the source of control signals for brain-machine interfaces. Monkeys learned to use these artificial connections from cortical cells to muscles to generate bidirectional wrist torques, and controlled multiple neuron–muscle pairs simultaneously. Such direct transforms from cortical activity to muscle stimulation could be implemented by autonomous electronic circuitry, creating a relatively natural neuroprosthesis. These results are the first demonstration that direct artificial connections between cortical cells and muscles can compensate for interrupted physiological pathways and restore volitional control of movement to paralysed limbs.

Subfields: Biomedical Engineering, Cellular and Molecular Neuroscience, Cognitive Neuroscience

View Paper: https://www.semanticscholar.org/paper/810f0636677582f22617b054dc899a23f42978e1

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Citations in the corpus

Real-time fMRI neurofeedback: Progress and challenges (2013, background): “These research lines continue into the present time (Jackson et al., 2006; Moritz et al., 2008; Schafer and Moore, 2011).”
Intention, action planning, and decision making in parietal-frontal circuits. (2009, background): “Most efforts have concentrated on the motor cortex for obtaining movement intention signals (Donoghue, 2002; Schwartz, 2004; Nicolelis, 2003; Kennedy and Bakay, 2000; Moritz et al., 2008).”
Brain-Machine Interfaces: From Basic Science to Neuroprostheses and Neurorehabilitation. (2017, methodology): “Eberhard Fetz’ group temporarily paralyzed monkeys’ hands with an anesthetic blockade (556) and then employed the firing rate of neurons located in the primary motor cortex (M1) to control an FES device that evoked wrist torques.”
Combining Brain–Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges (2010, methodology): “It’s worth noting that Fetz’s group [124] has recently described an invasive approach to brain-controlled orthosis conceptually similar to previous attempts based on non-invasive BCI mentioned above.”
Brain-Computer Interfaces Using Sensorimotor Rhythms: Current State and Future Perspectives (2014, positive): “Many studies have shown that training for and using BCIs can lead to changes in neural activity that facilitate use of prosthetic devices, especially when combined with functional electric stimulation (FES) [95], [96].”
Emergence of a Stable Cortical Map for Neuroprosthetic Control (2009, result): “). In each animal, we could record approximately 75–100 well-isolated units during each daily session. However, consistent with reports in the literature”
Reach and grasp by people with tetraplegia using a neurally controlled robotic arm (2012, neutral): “In addition to the robotic assistive device shown here, MI signals might also be used by people with paralysis to reanimate paralyzed muscles using functional electrical stimulation (FES) 27–29 or by people with limb loss to control prosthetic limbs.”
Brain-machine interfaces in neurorehabilitation of stroke. (2015, positive): “…cortico-spinal pathways to allow for continuous and permanent control of robotic devices (Collinger et al., 2013) or functional electric stimulation (FES) of paralyzed muscles (Moritz et al., 2008; Pohlmeyer et al., 2009; Ethier et al., 2012; McGie et al., in press; Pfurtscheller et al., 2003).”