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Recchia, F. A.

Publications and source records attributed to Recchia, F. A..

2 recordsLinked to original sources

Neural stimulation hardware for the selective intrafascicular modulation of the vagus nerve

The neural stimulation of the vagus nerve is able to modulate various functions of the parasympathetic response in different organs. The stimulation of the vagus nerve is a promising approach to treating inflammatory diseases, obesity, diabetes, heart failure, and hypertension. The complexity of the vagus nerve requires highly selective stimulation, allowing the modulation of target-specific organs without side effects. Here, we address this issue by adapting a neural stimulator and developing an intraneural electrode for the particular modulation of the vagus nerve. The neurostimulator parameters such as amplitude, pulse width, and pulse shape were modulated. Single-, and multi-channel stimulation was performed at different amplitudes. For the first time, I polyimide thin-film neural electrode was designed for the specific stimulation of the vagus nerve. In vivo experiments were performed in the adult minipig to validate to elicit electrically evoked action potentials and to modulate physiological functions selectively, validating the selectivity of intraneural stimulation. Electrochemical tests of the electrode and the neurostimulator showed that the stimulation hardware was working correctly. Stimulating the porcine vagus nerve resulted in selective modulation of the vagus nerve. Alpha, beta, and theta waves could be distinguished during single- and multi-channel stimulation. We have shown that the here presented system is able to activate the vagus nerve selectively and can therefore modulate the heart rate, diastolic pressure, and systolic pressure. The here presented system may be used to restore the cardiac loop after denervation by implementing biomimetic stimulation patterns. Presented methods may be used to develop intraneural electrodes adapted for various applications.

bioengineering↗

Simultaneous decoding of cardiovascular and respiratory functional changes from pig intraneural vagus nerve signals

Bioelectronic medicine is opening new perspectives for the treatment of some major chronic diseases through the physical modulation of autonomic nervous system activity. Being the main peripheral route for electrical signals between central nervous system and visceral organs, the vagus nerve (VN) is one of the most promising targets. Closed-loop neuromodulation would be crucial to increase effectiveness and reduce side effects, but it depends on the possibility of extracting useful physiological information from VN electrical activity, which is currently very limited. Here, we present a new decoding algorithm properly detecting different functional changes from VN signals. They were recorded using intraneural electrodes in anaesthetized pigs during cardiovascular and respiratory challenges mimicking increases in arterial blood pressure, tidal volume and respiratory rate. A novel decoding algorithm was developed combining discrete wavelet transformation, principal component analysis, and ensemble learning made of classification trees. It robustly achieved high accuracy levels in identifying different functional changes and discriminating among them. We also introduced a new index for the characterization of recording and decoding performance of neural interfaces. Finally, by combining an anatomically validated hybrid neural model and discrimination analysis, we provided new evidence suggesting a functional topographical organization of VN fascicles. This study represents an important step towards the comprehension of VN signaling, paving the way to the development of effective closed-loop bioelectronic systems.

neuroscience↗