Cortical Representation of Ipsilateral Arm Movements in Monkey and Man

Ganguly, Karunesh; Secundo, Lavi; Ranade, Gireeja; Orsborn, Amy L.; Chang, Edward F.; Dimitrov, D; Wallis, Jonathan D.; Barbaro, Nicholas M.; Knight, Robert T.; Carmena, Jose M.

doi:10.1523/jneurosci.2471-09.2009

Cited by 144 publications

(154 citation statements)

References 44 publications

(99 reference statements)

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“…Interestingly, movement of the ipsilateral arm also modifies the activity of neurons in these motor areas (Donchin et al, 1998;Cisek et al, 2003;Ganguly et al, 2009). Therefore, when the left arm is adapted to a force field while the right arm is being moved in a particular direction, the representation of the force field is constructed specifically for the right-arm movement direction.…”

Section: Encoding Of Opposite-arm Kinematics In the Primitivesmentioning

confidence: 99%

Gain Field Encoding of the Kinematics of Both Arms in the Internal Model Enables Flexible Bimanual Action

Yokoi¹,

Hirashima²,

Nozaki³

2011

J. Neurosci.

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Bimanual action requires the neural controller (internal model) for each arm to predictively compensate for mechanical interactions resulting from movement of both that arm and its counterpart on the opposite side of the body. Here, we demonstrate that the brain may accomplish this by constructing the internal model with primitives multiplicatively encoding information from the kinematics of both arms. We had human participants adapt to a novel force field imposed on one arm while both arms were moving in particular directions and examined the generalization pattern of motor learning when changing the movement directions of both arms. The generalization pattern was consistent with the pattern predicted from the multiplicative encoding scheme. As proposed by previous theoretical studies, the strength of multiplicative encoding was manifested in the observation that participants could adapt reaching movements to complicated force fields depending nonlinearly on the movement directions of both arms. These results indicate that multiplicative neuronal influence of the kinematics of the opposing arm on the internal models enables the brain to control bimanual movement by providing great flexible ability to handle arbitrary dynamical environments resulting from the interactions of both arms.

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Section: Encoding Of Opposite-arm Kinematics In the Primitivesmentioning

confidence: 99%

Gain Field Encoding of the Kinematics of Both Arms in the Internal Model Enables Flexible Bimanual Action

Yokoi¹,

Hirashima²,

Nozaki³

2011

J. Neurosci.

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“…In the 1980s, Georgopoulos et al [34,35] constructed a standard center-out task, in which monkeys were trained to move a lightweight, frictionless joystick to capture one in eight randomly lighted targets to obtain a liquid reward. This paradigm has been improved and employed in many BMI studies to research forelimb movement in later 30 years [36,37]. Some other paradigms are also developed for decoding the movement trajectory of monkey arm, hand or finger [38].…”

mentioning

confidence: 99%

Development of an invasive brain-machine interface with a monkey model

Zhang

Hao

et al. 2012

Chin. Sci. Bull.

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Brain-machine interfaces (BMIs) translate neural activities of the brain into specific instructions that can be carried out by external devices. BMIs have the potential to restore or augment motor functions of paralyzed patients suffering from spinal cord damage. The neural activities have been used to predict the 2D or 3D movement trajectory of monkey's arm or hand in many studies. However, there are few studies on decoding the wrist movement from neural activities in center-out paradigm. The present study developed an invasive BMI system with a monkey model using a 10×10-microelectrode array in the primary motor cortex. The monkey was trained to perform a two-dimensional forelimb wrist movement paradigm where neural activities and movement signals were simultaneous recorded. Results showed that neuronal firing rates highly correlated with forelimb wrist movement; > 70% (105/149) neurons exhibited specific firing changes during movement and > 36% (54/149) neurons were used to discriminate directional pairs. The neuronal firing rates were also used to predict the wrist moving directions and continuous trajectories of the forelimb wrist. The four directions could be classified with 96% accuracy using a support vector machine, and the correlation coefficients of trajectory prediction using a general regression neural network were above 0.8 for both horizontal and vertical directions. Results showed that this BMI system could predict monkey wrist movements in high accuracy through the use of neuronal firing information.

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“…We also tested and did not find any evidence for significant correlation with other frequency bands (i.e. δ = 1–4 Hz, θ = 4–8 Hz, α = 8–12 Hz, β = 18–26 Hz, low γ = 30–50 Hz11, 12, 13). …”

Section: Resultsmentioning

confidence: 89%

Muscle synergies after stroke are correlated with perilesional high gamma

Godlove

Gulati

Dichter

et al. 2016

Ann Clin Transl Neurol

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Movements can be factored into modules termed “muscle synergies”. After stroke, abnormal synergies are linked to impaired movements; however, their neural basis is not understood. In a single subject, we examined how electrocorticography signals from the perilesional cortex were associated with synergies. The measured synergies contained a mix of both normal and abnormal patterns and were remarkably similar to those described in past work. Interestingly, we found that both normal and abnormal synergies were correlated with perilesional high gamma. Given the link between high gamma and cortical spiking, our results suggest that perilesional spiking may organize synergies after stroke.

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Cortical Representation of Ipsilateral Arm Movements in Monkey and Man

Cited by 144 publications

References 44 publications

Gain Field Encoding of the Kinematics of Both Arms in the Internal Model Enables Flexible Bimanual Action

Gain Field Encoding of the Kinematics of Both Arms in the Internal Model Enables Flexible Bimanual Action

Development of an invasive brain-machine interface with a monkey model

Muscle synergies after stroke are correlated with perilesional high gamma

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