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Symposia and Mini-SymposiaM

Biomimetic Brain Machine Interfaces for the Control of Movement

Andrew H. Fagg, Nicholas G. Hatsopoulos, Victor de Lafuente, Karen A. Moxon, Shamim Nemati, James M. Rebesco, Ranulfo Romo, Sara A. Solla, Jake Reimer, Dennis Tkach, Eric A. Pohlmeyer and Lee E. Miller
Journal of Neuroscience 31 October 2007, 27 (44) 11842-11846; DOI: https://doi.org/10.1523/JNEUROSCI.3516-07.2007
Andrew H. Fagg
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Nicholas G. Hatsopoulos
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Victor de Lafuente
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Karen A. Moxon
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Shamim Nemati
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James M. Rebesco
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Ranulfo Romo
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Sara A. Solla
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Jake Reimer
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Dennis Tkach
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Eric A. Pohlmeyer
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Lee E. Miller
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    Figure 1.

    Experimental setup for motor BMI experiments. A, Recordings from chronically implanted electrode array are decoded to provide real-time control signals. B, In the Hatsopoulos laboratory, these signals can be used to control cursor position (gray circle at monkey's hand) either directly or indirectly through joint torque predictions acting on a forward dynamic limb model. In some experiments, the commands are also used to control the position of the monkey's own limb via the KINARM exoskeleton and thereby supply proprioceptive feedback to the monkey. Botox injections are being investigated as a means to reduce the monkey's ability to resist these imposed movements. C, An analogous system in Miller's laboratory involves a monkey trained to perform a wrist flexion task whose forearm flexor muscles can be temporarily paralyzed by injecting Lidocaine into cuffs surrounding the median and ulnar nerves. EMG predictions are sent to a stimulator and a set of intramuscular electrodes implanted in the paralyzed muscles. This allows the monkey to generate voluntarily controlled muscle contractions despite the paralysis.

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    Figure 2.

    Movement-related signals predicted using neural discharge recorded from multielectrode arrays chronically implanted in the primary motor cortex. A, X-component of actual (red) and predicted (blue) Cartesian hand position during a sequence of movements between randomly positioned targets. Dashed lines indicate breaks between sets of movements. B, Shoulder torque predicted during the same movements. Torque prediction accuracy increased further with the addition of limb state (angular position and velocity; black lines) inputs. C, EMG signals predicted during a sequence of unconstrained reach and grasp movements. Flx Dig, Flexor digitorum; Ext Dig, extensor digitorum.

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    Figure 3.

    Flow of somatic information from the sensory cortices of the parietal lobe to the premotor and motor cortices of the frontal lobe. Color scale indicates the latency to activation of each cortical area after a 20 Hz vibratory stimulus applied to a fingertip. 1, 2, 3b, 5, Brodmann areas 1, 2, 3b, and 5; S2, secondary somatosensory cortex; PMd, PMv, dorsal and ventral premotor cortices; SMA, supplementary motor area.

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The Journal of Neuroscience: 27 (44)
Journal of Neuroscience
Vol. 27, Issue 44
31 Oct 2007
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Biomimetic Brain Machine Interfaces for the Control of Movement
Andrew H. Fagg, Nicholas G. Hatsopoulos, Victor de Lafuente, Karen A. Moxon, Shamim Nemati, James M. Rebesco, Ranulfo Romo, Sara A. Solla, Jake Reimer, Dennis Tkach, Eric A. Pohlmeyer, Lee E. Miller
Journal of Neuroscience 31 October 2007, 27 (44) 11842-11846; DOI: 10.1523/JNEUROSCI.3516-07.2007

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Biomimetic Brain Machine Interfaces for the Control of Movement
Andrew H. Fagg, Nicholas G. Hatsopoulos, Victor de Lafuente, Karen A. Moxon, Shamim Nemati, James M. Rebesco, Ranulfo Romo, Sara A. Solla, Jake Reimer, Dennis Tkach, Eric A. Pohlmeyer, Lee E. Miller
Journal of Neuroscience 31 October 2007, 27 (44) 11842-11846; DOI: 10.1523/JNEUROSCI.3516-07.2007
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