Delivering the Sense of Touch to the Human Brain

Darie, Radu; Powell, Marc; Borton, David A.

doi:10.1016/j.neuron.2017.02.008

Cited by 7 publications

(7 citation statements)

References 12 publications

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“…Therefore, rapid closed-loop sensory feedback not only augments sensory function but also augments motor function. Furthermore, these results provide substantial evidence that sensory feedback during movement can enhance the sense of agency and other correlates of enhanced sensorimotor integration in patients with upper-limb dysfunction (Collinger et al, 2018;Darie et al, 2017;Bensmaia and Miller, 2014;Ackerley and Kavounoudias, 2015;Marasco et al, 2018;Flesher et al, 2016Flesher et al, , 2017Flesher et al, , 2019. Overall, successful sensorimotor demultiplexing occurred on 100% of task trials (198 total trials).…”

Section: Sensory and Motor Events In M1 Can Be Simultaneouslymentioning

confidence: 73%

“…This study uses closed-loop vibrotactile feedback during BCI operation. There are alternative ways to provide sensory feedback following SCI, including intracortical microstimulation (Flesher et al, 2016(Flesher et al, , 2017(Flesher et al, , and 2019Armenta Salas et al, 2018;Collinger et al, 2018;Darie et al, 2017;Bensmaia and Miller, 2014;Godlove et al, 2014) or extracortical microstimulation in S1 (Caldwell et al, 2019;Johnson et al, 2013). Compared to stimulation in S1, previous studies demonstrate that tactilebased feedback enables rapid sensory perception at a significantly faster latency (Caldwell et al, 2019;Godlove et al, 2014).…”

Section: Types Of Sensory Feedback and Implications For Bci Implant Locationsmentioning

confidence: 99%

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Restoring the Sense of Touch Using a Sensorimotor Demultiplexing Neural Interface

Ganzer

Schwemmer

et al. 2020

Cell

105

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Section: Sensory and Motor Events In M1 Can Be Simultaneouslymentioning

confidence: 73%

Section: Types Of Sensory Feedback and Implications For Bci Implant Locationsmentioning

confidence: 99%

Restoring the Sense of Touch Using a Sensorimotor Demultiplexing Neural Interface

Ganzer

Schwemmer

et al. 2020

Cell

105

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“…Single-word descriptors have the advantage that they can be compared across large data sets or subjects. However, as experimental advances continue to push the capabilities of ICMS, responses could become more complex and future studies might benefit from more structured descriptors, which take into consideration the complexity of these sensory experiences ( Darie et al, 2017 ).…”

Section: Resultsmentioning

confidence: 99%

Proprioceptive and cutaneous sensations in humans elicited by intracortical microstimulation

Salas

Bashford

Kellis

et al. 2018

eLife

202

177

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Pioneering work with nonhuman primates and recent human studies established intracortical microstimulation (ICMS) in primary somatosensory cortex (S1) as a method of inducing discriminable artificial sensation. However, these artificial sensations do not yet provide the breadth of cutaneous and proprioceptive percepts available through natural stimulation. In a tetraplegic human with two microelectrode arrays implanted in S1, we report replicable elicitations of sensations in both the cutaneous and proprioceptive modalities localized to the contralateral arm, dependent on both amplitude and frequency of stimulation. Furthermore, we found a subset of electrodes that exhibited multimodal properties, and that proprioceptive percepts on these electrodes were associated with higher amplitudes, irrespective of the frequency. These novel results demonstrate the ability to provide naturalistic percepts through ICMS that can more closely mimic the body’s natural physiological capabilities. Furthermore, delivering both cutaneous and proprioceptive sensations through artificial somatosensory feedback could improve performance and embodiment in brain-machine interfaces.

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“…Intended movement is then relayed to an external agent like a prosthetic arm. The prosthetic arm's movement then has to be conveyed to the brain regions (e.g., the sensorimotor cortex) responsible for sensing the individual's environment using neural stimulation patterns [60,61].…”

Section: B Neural Processing Applications and Algorithmic Kernelsmentioning

confidence: 99%

A Multi-Site Accelerator-Rich Processing Fabric for Scalable Brain-Computer Interfacing

Sriram¹,

Pothukuchi²,

Michał³

et al. 2023

Preprint

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Hull 1 is an accelerator-rich distributed implantable brain-computer interface (BCI) that reads biological neurons at data rates that are 2-3 orders of magnitude higher than the prior art, while supporting many neuroscientific applications. Prior approaches have restricted brain interfacing to tens of megabits per second in order to meet two constraints necessary for effective operation and safe long-term implantation-power dissipation under tens of milliwatts and response latencies in the tens of milliseconds. Hull also adheres to these constraints, but is able to interface with the brain at much higher data rates, thereby enabling, for the first time, BCI-driven research on and clinical treatment of brain-wide behaviors and diseases that require reading and stimulating many brain locations. Central to Hull's power efficiency is its realization as a distributed system of BCI nodes with accelerator-rich compute. Hull balances modular system layering with aggressive cross-layer hardware-software co-design to integrate compute, networking, and storage. The result is a lesson in designing networked distributed systems with hardware accelerators from the ground up.

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Delivering the Sense of Touch to the Human Brain

Cited by 7 publications

References 12 publications

Restoring the Sense of Touch Using a Sensorimotor Demultiplexing Neural Interface

Restoring the Sense of Touch Using a Sensorimotor Demultiplexing Neural Interface

Proprioceptive and cutaneous sensations in humans elicited by intracortical microstimulation

A Multi-Site Accelerator-Rich Processing Fabric for Scalable Brain-Computer Interfacing

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