The human primary somatosensory cortex encodes imagined movement in the absence of sensory information

Jafari, Matiar; Aflalo, Tyson; Chivukula, Srinivas; Kellis, Spencer; Salas, Manuel; Norman, Sumner L.; Pejsa, Kelsie; Liu, Charles Yu; Andersen, Richard A.

doi:10.1038/s42003-020-01484-1

Cited by 34 publications

(27 citation statements)

References 40 publications

(64 reference statements)

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“…These results suggest that neural signals could also be present during imagined movement (Zhang et al, 2017). Furthermore, modulation of S1 neurons during motor imagery of reaching has been demonstrated for the same participant whose data underlies this work (Jafari et al, 2020). If grasping motor imagery can be robustly decoded, a single implant in S1 could allow for a bidirectional BMI, able to decode grasp intentions and utilize electrical stimulation to evoke somatosensations (Armenta Salas et al, 2018).…”

Section: Introductionsupporting

confidence: 63%

“…Secondly, the task design might have only weakly engaged the neural populations we recorded from, as the electrode implant mostly covered the contralateral arm area (Armenta Salas et al, 2018). A different task, that involved the arm by reaching to grasp an object, could have elicited stronger neuronal activity (Jafari et al, 2020). Thirdly, units in S1 showed mostly grasp independent increase in activity compared to baseline (Figure 2C,E), opening up the possibility that the grasps were not different enough to evoke stronger decoding abilities in S1.…”

Section: S1 Encodes Imagined Grasps Significantly But Does Not Improve With Population Sizementioning

confidence: 99%

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Decoding grasp and speech signals from the cortical grasp circuit in a tetraplegic human

Kellis

et al. 2021

Preprint

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Tetraplegia from spinal cord injury leaves many patients paralyzed below the neck, leaving them unable to perform most activities of daily living. Brain-machine interfaces (BMIs) could give tetraplegic patients more independence by directly utilizing brain signals to control external devices such as robotic arms or hands. The cortical grasp network has been of particular interest because of its potential to facilitate the restoration of dexterous object manipulation. However, a network that involves such high-level cortical areas may also provide additional information, such as the encoding of speech. Towards understanding the role of different brain areas in the human cortical grasp network, neural activity related to motor intentions for grasping and performing speech was recorded in a tetraplegic patient in the supramarginal gyrus (SMG), the ventral premotor cortex (PMv), and the somatosensory cortex (S1). We found that in high-level brain areas SMG and PMv, grasps were well represented by firing rates of neuronal populations already at visual cue presentation. During motor imagery, grasps could be significantly decoded from all brain areas. At identical neuronal population sizes, SMG and PMv achieved similar highly-significant decoding abilities, demonstrating their potential for grasp BMIs. During speech, SMG encoded both spoken grasps and colors, in contrast to PMv and S1, which were not able to significantly decode speech.These findings suggest that grasp signals can robustly be decoded at a single unit level from the cortical grasping circuit in human. Data from PMv suggests a specialized role in grasping, while SMG’s role is broader and extends to speech. Together, these results indicate that brain signals from high-level areas of the human cortex can be exploited for a variety of different BMI applications.

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Section: Introductionsupporting

confidence: 63%

Section: S1 Encodes Imagined Grasps Significantly But Does Not Improve With Population Sizementioning

confidence: 99%

Decoding grasp and speech signals from the cortical grasp circuit in a tetraplegic human

Kellis

et al. 2021

Preprint

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“…When all the fastest ring (9, 10, 17, 20, 21, 22 and 23) are removed the accuracy drops dramatically to 22.2% (FAST). Most importantly, when slow ring are removed as a group (2,3,4,5,11,18,25,26) the accuracy drops to 37.9% (SLOW). Data indicating the total rings for each of the 26 single units over 4.5 seconds are illustrated in gure 5b.…”

Section: Phone Classi Cation In Locked-in Participant 5 Speaking Silentlymentioning

confidence: 99%

“…Most recently, Willett et al [1] have recorded from human arm motor cortex and provided a writing facility, easily convertible to speech, using Utah arrays and recording multi-units. Other researchers [2,3,4] have used micro-electrode arrays to control paralyzed limbs and robotic limbs, also recording multi-units. ECoG electrodes placed on the cortical surface have been used by Chang and his group [5] to develop a speech prosthesis using the frequency domain to interpret and produce the intended speech.…”

Section: Introductionmentioning

confidence: 99%

Slow Firing Single Units Are Essential for Optimal Decoding of Silent Speech

Kennedy

Ganesh

Cervantes

2022

Preprint

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Summary The motivation of someone who is locked-in, that is, paralyzed and mute, is to find relief for their loss of function. The data presented in this report is part of an attempt to restore one of those lost functions, namely, speech. An essential feature of the development of a speech prosthetic is optimal decoding of patterns of recorded neural signals during silent or covert speech, that is, speaking ‘inside the head’ with no audible output due to the paralysis of the articulators. The aim of this paper is to illustrate the importance of both fast and slow single unit firings recorded from an individual with locked-in syndrome and from an intact participant speaking silently. Long duration electrodes were implanted in the motor speech cortex for up to 13 years in the locked-in participant. The data herein provide evidence that slow firing single units are essential for optimal decoding accuracy. Additional evidence indicates that slow firing single units can be conditioned in the locked-in participant five years after implantation, further supporting their role in decoding.

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“…In sum, the combination of inappropriately high forces when manipulating objects with the possible underestimate of the duration of the resulting object motion may be detrimental for in-flight mission operations. However, since mental imagery engages brain regions partially distinct from those involved in motor interaction with real objects 44 – 46 , we hypothesize that visual imagery might overcome the limitations of perceptual-motor interactions with weightless objects. If so, mental imagery might be useful to train people to deal with weightless objects in preparation for a space mission, as well as during the mission to facilitate space adaptation.…”

Section: Introductionmentioning

confidence: 99%

Mental imagery of object motion in weightlessness

2021

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Mental imagery represents a potential countermeasure for sensorimotor and cognitive dysfunctions due to spaceflight. It might help train people to deal with conditions unique to spaceflight. Thus, dynamic interactions with the inertial motion of weightless objects are only experienced in weightlessness but can be simulated on Earth using mental imagery. Such training might overcome the problem of calibrating fine-grained hand forces and estimating the spatiotemporal parameters of the resulting object motion. Here, a group of astronauts grasped an imaginary ball, threw it against the ceiling or the front wall, and caught it after the bounce, during pre-flight, in-flight, and post-flight experiments. They varied the throwing speed across trials and imagined that the ball moved under Earth’s gravity or weightlessness. We found that the astronauts were able to reproduce qualitative differences between inertial and gravitational motion already on ground, and further adapted their behavior during spaceflight. Thus, they adjusted the throwing speed and the catching time, equivalent to the duration of virtual ball motion, as a function of the imaginary 0 g condition versus the imaginary 1 g condition. Arm kinematics of the frontal throws further revealed a differential processing of imagined gravity level in terms of the spatial features of the arm and virtual ball trajectories. We suggest that protocols of this kind may facilitate sensorimotor adaptation and help tuning vestibular plasticity in-flight, since mental imagery of gravitational motion is known to engage the vestibular cortex.

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The human primary somatosensory cortex encodes imagined movement in the absence of sensory information

Cited by 34 publications

References 40 publications

Decoding grasp and speech signals from the cortical grasp circuit in a tetraplegic human

Decoding grasp and speech signals from the cortical grasp circuit in a tetraplegic human

Slow Firing Single Units Are Essential for Optimal Decoding of Silent Speech

Mental imagery of object motion in weightlessness

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