The goal of this experimental study is to investigate the somatosensory system through intraneural recording and stimulation of the median nerve in healthy volunteers and participants with upper-limb amputation. The main questions it aims to answer are:
* How does median nerve activity encode tactile perception during different types of mechanical tactile stimulation in healthy subjects? * How can tactile information be artificially encoded and restored through intraneural microstimulation in both healthy subjects and upper-limb amputee participants? How rich and functionally meaningful is the restored sensory information? * What are the neurophysiological mechanisms underlying tactile stimulus processing and the associated patterns of brain activation during tactile stimulation?
Participants will undergo median nerve recordings using microneurography during controlled mechanical tactile stimulation, as well as intraneural microstimulation with specific patterns to evoke near-natural tactile sensations. They will perform perceptual reporting tasks related to stimulus type, intensity, and localization, as well as psychophysical tests under different stimulation conditions. When possible, they will also undergo non-invasive recordings of brain activity using electroencephalography during sensory stimulation.
Age between 18-60 years, of any sex
Signed informed consent
No neurological diseases
Presence of both intact upper limbs
Conditions affecting perceptual abilities
Inability to provide informed consent
Pregnancy or breastfeeding (self-reported)
Clinical conditions that, in the judgment of the investigator responsible for recruitment, may interfere with microneurography, microstimulation, and EEG procedures
Parallel
Microneurography
Procedure/SurgeryMicroneurography is a minimally invasive neurophysiological technique that allows direct recording of the electrical activity of single peripheral nerve fibers using specific microelectrodes inserted into the nerve.
Intraneural Microstimulation
Procedure/SurgeryIntraneural microstimulation is a minimally invasive neurophysiological technique in which small electrical currents are delivered through a microelectrode inserted into a peripheral nerve to selectively activate nerve fibers and evoke sensory perceptions.
Mechanoreceptor identification success rate
The proportion of experimental sessions in which a single mechanoreceptive afferent is successfully isolated and identified using MNG during controlled mechanical tactile stimulation, expressed as the percentage of successful recordings (%).
Mechanoreceptor classification accuracy
The accuracy of mechanoreceptor type classification (e.g., SA1, SA2, RA, PC) based on MNG recordings during mechanical tactile stimulation, expressed as the percentage of correctly classified receptors (%).
Peripheral afferent firing rate during tactile stimulation
The mean firing rate (spikes/s) of mechanoreceptive afferents recorded by MNG during controlled mechanical tactile stimulation.
Tactile mechanical detection threshold
The minimum stimulus intensity (expressed in grams of calibrated Von Frey Hairs) required to evoke a consistent neural response during mechanical tactile stimulation.
Event-related potential amplitude during intraneural microstimulation
Event-related potentials (ERPs) elicited by intraneural microstimulation and recorded using 128-channel EEG will be quantified by peak amplitude (µV) of stimulus-locked cortical responses.
Event-related potential latency during intraneural microstimulation
Event-related potentials (ERPs) elicited by intraneural microstimulation and recorded using 128-channel EEG will be quantified by peak latency (ms) of stimulus-locked cortical responses.
EEG spectral power modulation during intraneural microstimulation
Changes in EEG spectral power recorded using 128-channel EEG during intraneural microstimulation expressed as spectral power (µV²) or percentage change from baseline (%)
Decoding accuracy of tactile stimulation conditions from EEG signals
Machine learning-based classification of tactile stimulation conditions using EEG-derived features (classification accuracy %)
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Azienda Ospedaliero, Universitaria Pisana
Lead sponsor
Scuola Superiore di Studi Universitari e di Perfezionamento Sant'Anna
Collaborator
