A computational model that predicts behavioral sensitivity to intracortical microstimulation

Kim, Sung Shin; Callier, Thierri; Bensmaı̈a, Sliman J.

doi:10.1088/1741-2552/14/1/016012

Cited by 20 publications

(15 citation statements)

References 51 publications

(108 reference statements)

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“…S7 and Validation of catch trials). Increased perceived magnitude at higher frequencies has also been reported for peripheral nerve stimulation (19)(20)(21) and is consistent with the hypothesis that intensity is determined by the spike rate evoked in the neuronal population (17,18).…”

Section: Discussionsupporting

confidence: 87%

“…Spatial Pattern of Recruitment. Computational modeling suggests that the perceived magnitude of a stimulus can be predicted from the population spike count (17,18). To the extent that animals were not solely relying on differences in sensory magnitude to discriminate frequency, however, this neural code is unlikely to exclusively mediate their behavioral performance.…”

Section: Dependence Of the Sensory Correlates Of Icms Frequency On Thementioning

confidence: 99%

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The frequency of cortical microstimulation shapes artificial touch

Callier

Brantly

Caravelli

et al. 2019

Proc. Natl. Acad. Sci. U.S.A.

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Intracortical microstimulation (ICMS) of the somatosensory cortex evokes vivid tactile sensations and can be used to convey sensory feedback from brain-controlled bionic hands. Changes in ICMS frequency lead to changes in the resulting sensation, but the discriminability of frequency has only been investigated over a narrow range of low frequencies. Furthermore, the sensory correlates of changes in ICMS frequency remain poorly understood. Specifically, it remains to be elucidated whether changes in frequency only modulate sensation magnitude—as do changes in amplitude—or whether they also modulate the quality of the sensation. To fill these gaps, we trained monkeys to discriminate the frequency of ICMS pulse trains over a wide range of frequencies (from 10 to 400 Hz). ICMS amplitude also varied across stimuli to dissociate sensation magnitude from ICMS frequency and ensure that animals could not make frequency judgments based on magnitude. We found that animals could consistently discriminate ICMS frequency up to ∼200 Hz but that the sensory correlates of frequency were highly electrode dependent: On some electrodes, changes in frequency were perceptually distinguishable from changes in amplitude—seemingly giving rise to a change in sensory quality; on others, they were not. We discuss the implications of our findings for neural coding and for brain-controlled bionic hands.

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Section: Discussionsupporting

confidence: 87%

Section: Dependence Of the Sensory Correlates Of Icms Frequency On Thementioning

confidence: 99%

The frequency of cortical microstimulation shapes artificial touch

Callier

Brantly

Caravelli

et al. 2019

Proc. Natl. Acad. Sci. U.S.A.

Self Cite

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“…Note that systematic selection biases on catch trials disappeared to the extent that animals judged frequency independently of amplitude (Figure 4, see below). Increased perceived magnitude at higher frequencies has also been reported for peripheral nerve stimulation (D'Anna et al, 2017;Graczyk et al, 2016) and is consistent with the hypothesis that intensity is determined by the spike rate evoked in the neuronal population (Kim et al, 2017).…”

Section: Increased Icms Frequency Leads To Increased Perceived Magnitudesupporting

confidence: 88%

“…from simulations suggest that the perceived magnitude of a stimulus can be predicted from the population spike count (Kim et al, 2017). To the extent that animals were not solely relying on intensity differences, however, this neural code is unlikely to exclusively mediate their behavioral performance.…”

Section: Resultsmentioning

confidence: 99%

The frequency of cortical microstimulation shapes artificial touch

Callier

Brantly

Caravelli

et al. 2019

Preprint

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Intracortical microstimulation (ICMS) of somatosensory cortex evokes vivid tactile sensations and can be used to convey sensory feedback in brain-controlled bionic hands. Changes in ICMS frequency result in discriminable percepts, but the effects of frequency have only been investigated over a narrow range of low frequencies, spanning only a small fraction of that relevant for neuroprosthetics. Furthermore, the sensory correlates of changes in ICMS frequency remain to be elucidated. To fill these gaps, we trained monkeys to discriminate the frequency of ICMS pulse trains over a wide range of frequencies (from 10 to 400 Hz). ICMS amplitude also varied across stimuli to reduce the animals' reliance on magnitude in making frequency judgments. We found that animals could discriminate ICMS frequency up to about 200 Hz but that the sensory correlates of frequency were highly electrode dependent. We discuss the implications of our findings for neural coding and brain-machine interfaces.

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“…However, the optimal design of this signal is the topic of much debate [40]. Biomimetic signal designers have delivered electrical stimulation patterns similar to the neural signals expected by the sensory cortex [11], [41]. By recording neural activation patterns of a sensation elicited via mechanical stimuli, electrical stimulation mimicking those recorded patterns can evoke similar sensations, which at times may be indistinguishable from natural sensation [18], [42].…”

mentioning

confidence: 99%

A Robust Encoding Scheme for Delivering Artificial Sensory Information via Direct Brain Stimulation

Bjånes

Moritz

2019

IEEE Trans. Neural Syst. Rehabil. Eng.

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Innovations for creating somatosensation via direct electrical stimulation of the brain will be required for the next generation of bi-directional cortical neuroprostheses. The current lack of tactile perception and proprioceptive input likely imposes a fundamental limit on speed and accuracy of brain-controlled prostheses or re-animated limbs. This study addresses the unique challenge of identifying a robust, high bandwidth sensory encoding scheme in a high-dimensional parameter space. Previous studies demonstrated single dimensional encoding schemes delivering low bandwidth sensory information, but no comparison has been performed across parameters, nor with update rates suitable for real-time operation of a neuroprosthesis. Here, we report the first comprehensive measurement of the resolution of key stimulation parameters such as pulse amplitude, pulse width, frequency, train interval and number of pulses. Surprisingly, modulation of stimulation frequency was largely undetectable. While we initially expected high frequency content to be an ideal candidate for passing high throughput sensory signals to the brain, we found only modulation of very low frequencies were detectable. Instead, the charge-per-phase of each pulse yields the highest resolution sensory signal, and is the key parameter modulating perceived intensity. The stimulation encoding patterns were designed for high-bandwidth information transfer that will be required for bi-directional brain interfaces. Our discovery of the stimulation features which best encode perceived intensity have significant implications for design of any neural interface seeking to convey information directly to the brain via electrical stimulation.

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A computational model that predicts behavioral sensitivity to intracortical microstimulation

Cited by 20 publications

References 51 publications

The frequency of cortical microstimulation shapes artificial touch

The frequency of cortical microstimulation shapes artificial touch

The frequency of cortical microstimulation shapes artificial touch

A Robust Encoding Scheme for Delivering Artificial Sensory Information via Direct Brain Stimulation

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