.
\nProducing accurate and stable, long-term readings of neuronal activity using a brain\u2013machine
\ninterface (BMI) is now possible thanks to work by Naotaka Fujii and his colleagues at the RIKEN
\nBrain Science Institute, Wako1. Their results could help researchers to develop durable and versatile
\nneural prostheses for rehabilitation patients.
\n.
\nBMIs read neural activity associated with planning and executing movements and decode it into
\ncommands that are relayed to an external device such as a computer cursor or robotic arm.
\nThis normally involves recording simultaneously from multiple, single neurons, so the
\necordings are unstable and the decoding model needs re-calibration on a daily basis.
\nFujii and colleagues used an alternative technique called electrocorticography, in which an
\n array of electrodes is used to record the population activity of cortical neurons.
\n.
\nElectrocorticography is often used to evaluate epileptic patients before neurosurgery but is not normally
\nused for longer than two weeks. It was thought to provide a low fidelity signal for BMIs, because
\n the electrodes record neural activity from the cortical surface, rather than within the cortex.
\nTo overcome this, the researchers designed an electrode array for long-term recording, and developed
\n a novel decoding algorithm that samples neural activity from multiple brain regions.
\nAfter implanting the electrodes into the brains of monkeys, so that they spanned multiple brain
\nregions, Fujii and colleagues trained the animals to spontaneously reach out and grasp food presented to
\n them. The monkeys wore custom-made jackets fitted with reflective markers at the shoulders, elbows
\n and wrists. The researchers then recorded the monkeys\u2019 arm movements using a motion capture system,
\n and correlated them with the neuronal activity recorded by the electrodes.
\n.
\nBy decoding the signals, they could predict the trajectory and orientation of the monkeys\u2019 arms in three
\ndimensions. The accuracy of the decoding was comparable to that of existing BMIs which record activity
\n from single cells. Furthermore, the recordings were highly stable, and could be decoded for several months
\nwithout recalibration.
\n.
\nThe new recording technique should prove to be useful for researchers investigating movement control
\nand higher cognitive functions. It could also lead to versatile devices that can be implanted for long
\nperiods of time, to aid patients with brain damage, spinal cord injury, and neurodegenerative conditions
\nsuch as amyotrophic lateral sclerosis, notes Fujii.
\n.
\n\u201cOur electrode array is still not ready for long-term use in patients, because of the risk of infection,\u201d says
\nFujii, \u201cbut we are now developing a fully implantable wireless device to prevent this.\u201d<\/p>\n","protected":false},"excerpt":{"rendered":"
. Producing accurate and stable, long-term readings of neuronal activity using a brain\u2013machine interface (BMI) is now possible thanks to work by Naotaka Fujii and his colleagues at the RIKEN Brain Science Institute, Wako1. Their results could help researchers to develop durable and versatile neural prostheses for rehabilitation patients. . BMIs read neural activity associated … <\/p>\n