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

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 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 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 theirin vivocharacterization.

Small dendritic synapses enhance temporal coding in a model of cochlear nucleus bushy cells.

Spherical bushy cells (SBCs) in the anteroventral cochlear nucleus receive a single or very few powerful axosomatic inputs from the auditory nerve. However, SBCs are also contacted by small regular bouton synapses of the auditory nerve, located in their dendritic tree. The function of these small inputs is unknown. It was speculated that the interaction of axosomatic inputs with small dendritic inputs improved temporal precision, but direct evidence for this is missing. In a compartment model of spherical bushy cells with a stylized or realistic three-dimensional (3-D) representation of the bushy dendrite, we explored this hypothesis. Phase-locked dendritic inputs caused both tonic depolarization and a modulation of the model SBC membrane potential at the frequency of the stimulus. For plausible model parameters, dendritic inputs were subthreshold. Instead, the tonic depolarization increased the excitability of the SBC model and the modulation of the membrane potential caused a phase-dependent increase in the efficacy of the main axosomatic input. This improved response rate and entrainment for low-input frequencies and temporal precision of output at and above the characteristic frequency. A careful exploration of morphological and biophysical parameters of the bushy dendrite suggested a functional explanation for the peculiar shape of the bushy dendrite. Our model for the first time directly implied a role for the small excitatory dendritic inputs in auditory processing: they modulate the efficacy of the main input and are thus a plausible mechanism for the improvement of temporal precision and fidelity in these central auditory neurons.NEW & NOTEWORTHY We modeled dendritic inputs from the auditory nerve that spherical bushy cells of the cochlear nucleus receive. Dendritic inputs caused both tonic depolarization and modulation of the membrane potential at the input frequency. This improved the rate, entrainment, and temporal precision of output action potentials. Our simulations suggest a role for small dendritic inputs in auditory processing: they modulate the efficacy of the main input supporting temporal precision and fidelity in these central auditory neurons.