A method to establish functional vagus nerve topography from electro-neurographic spontaneous activity

Pitzus, Andrea; Romeni, Simone; Vallone, Fabio; Micera, Silvestro

doi:10.1016/j.patter.2022.100615

Cited by 4 publications

(5 citation statements)

References 36 publications

(73 reference statements)

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“…The variability encountered in sensation localization could also be investigated in a larger sample size study to identify possible clusters in sensations distribution. Such a study should be accompanied by an investigation on the propagation of electrical signals generated by the different waveform in the nerve using finite element methods to associate the projection in the hand to the portion of nerve stimulated 43 , 44 .…”

Section: Discussionmentioning

confidence: 99%

Non-rectangular neurostimulation waveforms elicit varied sensation quality and perceptive fields on the hand

Collu

Earley

Barbaro

et al. 2023

Sci Rep

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Electrical stimulation of the nerves is known to elicit distinct sensations perceived in distal parts of the body. The stimulation is typically modulated in current with charge-balanced rectangular shapes that, although easily generated by stimulators available on the market, are not able to cover the entire range of somatosensory experiences from daily life. In this regard, we have investigated the effect of electrical neurostimulation with four non-rectangular waveforms in an experiment involving 11 healthy able-bodied subjects. Weiss curves were estimated and rheobase and chronaxie values were obtained showing increases in stimulation time required to elicit sensations for some waveforms. The localization of the sensations reported in the hand also appeared to differ between waveforms, although the total area did not vary significantly. Finally, the possibility of distinguishing different charge- and amplitude-matched stimuli was demonstrated through a two-alternative-forced-choice (2AFC) match-to-sample task, showing the ability of participants to successfully distinguish between waveforms with similar electrical characteristics but different shapes and charge transfer rates. This study provides evidence that, by using different waveforms to stimulate nerves, it is possible to affect not only the required charge to elicit sensations but also the sensation quality and its localization.

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Section: Discussionmentioning

confidence: 99%

Non-rectangular neurostimulation waveforms elicit varied sensation quality and perceptive fields on the hand

Collu

Earley

Barbaro

et al. 2023

Sci Rep

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show abstract

“…When optimizing the stimulation protocols, we assumed to know the functional topography of the implanted nerve section. Intuitively, the approximate location of functional groups can be determined by applying stimuli from single sites located at different positions in the implanted electrodes and using triangulation (similarly to what is done using neural recordings in [28]- [30]). However, to the best of our knowledge, rigorous methods have not been developed yet.…”

Section: Assumptions On Nerve Functional Topographymentioning

confidence: 99%

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

Romeni

Losanno

Koert

et al. 2023

Preprint

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Objective: Peripheral nerve interfaces have the potential to restore sensory, motor, and visceral functions. In particular, intraneural interfaces allow targeting deep neural structures with high selectivity, even if their performance strongly depends upon the implantation procedure and the subject's anatomy. Currently, few alternatives exist for the determination of the target subject structural and functional anatomy, and statistical characterizations from cadaveric samples are limited because of their high cost. We propose an optimization workflow that can guide both the pre-surgical planning and the determination of maximally selective multisite stimulation protocols for implants consisting of several intraneural electrodes, and we characterize its performance in silico. We show that the availability of structural and functional information leads to very high performances and allows taking informed decisions on neuroprosthetic design. Approach: We employ hybrid models (HMs) of neuromodulation in conjunction with a machine learning-based surrogate model to determine fiber activation under electrical stimulation, and two steps of optimization through particle swarm optimization (PSO) to optimize in silico implant geometry, implantation and stimulation protocols using morphological data from the human median nerve at a reduced computational cost. Main results: Our method allows establishing the optimal geometry of multi-electrode transverse intra-fascicular multichannel electrode (TIME) implants, the optimal number of electrodes to implant, their optimal insertion, and a set of multipolar stimulation protocols that lead in silico to selective activation of all the muscles innervated by the human median nerve. Significance: We show how to use effectively HMs for optimizing personalized neuroprostheses for motor function restoration. We provide in-silico evidences about the potential of multipolar stimulation to increase greatly selectivity. We also show that the knowledge of structural and functional anatomies of the target subject leads to very high selectivity and motivate the development of methods for their in vivo characterization.

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“…While such methods are investigated, one possibility to perform optimizations without knowledge of the precise fascicular topography of the target nerve could be to employ 'generic' nerve models which do not contain any fascicle structure, like what has been proposed in [11,27,28]. Indeed, methods to determine functional topography can be run even without knowledge of the fascicular topography [27,28], giving in such cases not the exact location of the target functional groups, but a reconstruction in an abstract space where the distance between two points is proportional to the electrical impedance between them, which could be used as a basis for the proposed optimizations. Further analyses should be performed to confirm whether this is indeed the case.…”

Section: Assumptions On Nerve Structural Topographymentioning

confidence: 99%

“…When optimizing the stimulation protocols, we assumed to know the functional topography of the implanted nerve section. Intuitively, the approximate location of functional groups can be determined by applying stimuli from single sites located at different positions in the implanted electrodes and using triangulation (similarly to what is done using neural recordings in [27,28,30,31]). However, to the best of our knowledge, rigorous methods have not been developed yet.…”

Section: Assumptions On Nerve Functional Topographymentioning

confidence: 99%

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

Romeni,

Losanno,

Koert

et al. 2023

J. Neural Eng.

Self Cite

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Objective. Peripheral nerve interfaces have the potential to restore sensory, motor, and visceral functions. In particular, intraneural interfaces allow targeting deep neural structures with high selectivity, even if their performance strongly depends upon the implantation procedure and the subject’s anatomy. Here, we propose an optimization workflow that can guide both the pre-surgical planning and the determination of maximally selective multisite stimulation protocols for implants consisting of several intraneural electrodes, and we characterize its performance in silico. Approach. We use hybrid models (HMs) of neuromodulation in conjunction with machine learning and evolutionary optimization to perform for the first time a true in silico optimization of implant geometry, implantation and stimulation protocols using morphological data from the human median nerve at a reduced computational cost.Main results. Our method allows establishing the optimal geometry of multi-electrode intraneural implants, the optimal number of electrodes to implant, their optimal insertion, and a set of multipolar stimulation protocols that lead in silico to selective activation of all the muscles innervated by the human median nerve. Significance. Our work consists of a set of methods and guidelines to use effectively HMs for optimizing personalized neuroprostheses for sensory and motor function restoration, and for bioelectronic medicine.

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A method to establish functional vagus nerve topography from electro-neurographic spontaneous activity

Cited by 4 publications

References 36 publications

Non-rectangular neurostimulation waveforms elicit varied sensation quality and perceptive fields on the hand

Non-rectangular neurostimulation waveforms elicit varied sensation quality and perceptive fields on the hand

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

Combining biophysical models and machine learning to optimize implant geometry and stimulation protocol for intraneural electrodes

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