13:00: Opening by the Moderator Thomas Gomes Nørgaard dos Santos Nielsen
13:05: PhD lecture by Felipe Rettore Andreis
14:00: Questions and comments from the Committee
15:30: Questions and comments from the audience at the Moderator’s discretion
16:00: Conclusion of the session by the Moderator
The Faculty Council has appointed the following adjudication committee to evaluate the thesis and the associated lecture:
Paul Yoo, University of Toronto
Peter Veltink, University of Twente
Associate Professor Jacob Melgaard, Department of Health Science and Technology, Aalborg University
Associate Professor Thomas Gomes Nørgaard dos Santos Nielsen, Department of Health Science and Technology, Aalborg University
HOW TO PARTICIPATE
The Ph.D. Defense is organized as a hybrid event you can participate digitally via Zoom or physical presence.
Please click here to participate via Zoom.
Meeting ID: 680 4742 4173
Implantable neural interfaces have been used for several decades in research and clinical applications to modulate the autonomic nervous system and restore amputees' motor and sensory function. Several electrode designs exist to achieve such a goal. Still, to date, the most widely adopted interface is the extraneural cuff electrode, with its main advantages of simple surgical implantation and extended chronic viability. However, given the intrinsic noisy environment and the small selectivity of extraneural cuffs, its recording capabilities are limited, resulting in most of its applications as "open-loop" systems. To improve the recording selectivity of extraneural cuffs, a method using multi-electrode configurations, which, combined with a simple delay-and-add operator, make it possible to infer fibre type and direction of propagation, has been suggested. In addition, the simplicity of the system enables its use for "closed-loop" applications.
Another factor limiting the improvement of peripheral nerve interfaces is the gap between the peripheral nerve structure of small animal models and humans. To name a few of the differences, the smaller nerves and simpler fascicular structures can create significant differences in stimulation thresholds when moving from research to clinical applications. There is a growing body of literature suggesting that the peripheral nervous system of pigs may provide a better translational model than the commonly used rodents. However, our knowledge of the peripheral nervous system of pigs, especially the somatic nervous system, is still limited.
Therefore, this thesis aimed to advance peripheral nerve interfaces in a large animal model (i.e., the pig). Three studies were designed to achieve this goal. Study I aimed at characterising the excitability properties of the ulnar nerve in pigs through a wide range of electrical stimulation parameters while, at the same time, recording the neural activity with a multiple-electrode cuff. In Study II, the morphological features of the ulnar nerve were explored with a histological assessment. This study aimed at answering the following question: is the neuroanatomy of the ulnar nerve in pigs more comparable to humans than rodents? Finally, Study III investigated several algorithms for extracting information from linear electrode arrays. While the delay-and-add operator has been traditionally used in electroneurography, different approaches have been adopted for similar problems in other research areas, which led us to assess and compare the performance of each suitable algorithm with simulated and in vivo data.
In summary, the results from study I show the feasibility of using a multiple-electrode cuff to distinguish fibre population and provide data for researchers aiming to use the ulnar nerve in pigs as a model for probing the neural circuitry. Study II provides a detailed analysis of the ulnar nerve morphology in pigs. It shows how the pig can be a suitable translational model for peripheral nervous system studies. Finally, study III evaluates several algorithms for extracting information from multiple-electrode cuffs and discusses the advantages and drawbacks of each. This work contributes to the advancement of peripheral nerve interfaces by exploring an ulnar nerve model in a porcine, representing a step forward into using large animal models for peripheral nerve interface research.