• peripheral neural fascicles
• nerve-on-a-chip platform
• ex vivo
• spinal dorsal roots
• ultrasound neuromodulation
• electrophysiology
• ultrasound stimulation

Ultrasound stimulation (US) has recently emerged as a promising technology to achieve reliable, selective and noninvasive neuromodulation of various targets in which low-intensity ultrasound is delivered to nervous system tissue, resulting in transient modulation of neural activity. A myriad of applications can therefore be envisaged in which US would replace the standard and invasive electrical stimulation.
However, despite the growing emergence of this scientific field, to date, the fundamental mechanism(s) by which ultrasonic waves can modulate neural activity are still unknown.
This work includes the development of various branches of a computational modeling framework aimed to decipher the mechanisms of US-neuron interactions and formulate predictions of US neuromodulatory effects for different targets in the central and peripheral nervous systems, as well as its validation against experimental data.
The goal of this thesis is to extend a computational framework that simulate peripheral neural response and implement a more realistic model accounting for the specificities of this ex vivo experimental setting, to formulate predictions that can be directly compared to experimental data.
The work combines various modeling, experimental and analysis tasks, including:
-modeling of the experimental platform
-acoustic and electromagnetic simulations
-validation of the results against experimental data collected during experiments.
A nerve-on-a-chip platform was exploited for ex-vivo study: it is an efficient design tool for neuroprosthetic research focusing on implants for nerve regeneration and peripheral nerve cuffs. Indeed, regenerative micro-channel implants offer a fascicular-like design with tens of parallel micro-conduits that support peripheral nerve regeneration and embed microelectrodes that communicate with the regenerated axons, whereas the microchannel design amplifies the extracellular neural signal amplitude.
The recorded signals acquired using this platform were preprocessed: amplified, delayed against each other with variable delay times, added and band-pass filtered. Finally, the resulting amplitudes, conduction velocity and latencies were measured to perform a fiber-specific and fiber nonspecific analysis.