Biology subjects

Agnesi, F.

Publications and source records attributed to Agnesi, F..

3 recordsLinked to original sources

bioRxiv2026

Decoding peripheral stimulation from cortical and spinal recordings reveals complementary sensorimotor information

The somatosensory system encodes peripheral inputs through a sequence of ascending neural relays spanning spinal, subcortical and cortical levels. While multivariate decoding of electroencephalography (EEG) signals has demonstrated that cortical activity contains fine-grained information about somatosensory stimuli, the extent to which earlier processing stages contribute additional, non-redundant information remains unclear. To address this gap, we investigated a dataset comprising peripheral sensory stimulation and mixed stimulation (i.e., stimulation engaging both sensory and motor fibers). We assessed whether stimulation characteristics can be decoded from spinal recordings using high-density electrospinography (ESG), and whether combining ESG with EEG enhances decoding performance. Decoding accuracy varied systematically with both stimulation type and signal modality. ESG was the most informative signal for mixed and mixed vs sensory discrimination, reaching an average accuracy of [~]98%, while EEG provided a relative advantage for purely sensory tasks, though absolute accuracy remained more modest for both modalities. Critically, combining the two modalities together consistently matched or outperformed either one, used alone, across all conditions, with gains most pronounced for mixed vs sensory discrimination. Multi-subject generalization improved progressively with training-set size, rising to [~]88% with 15 training subjects for mixed classification, suggesting that subject-independent decoding of motor intent may be achievable when models are trained on a larger number of subjects. Taken together, these results establish that spinal ESG signals carry decodable information about peripheral stimulation that is complementary to and not redundant with cortical EEG. This finding supports a multilevel framework for decoding sensorimotor processing in humans and motivates the development of dual-modality brain-machine interfaces that leverage both cortical and spinal signals to improve the control of neurostimulation and assistive devices.

bioengineering↗

bioRxiv2024

Simulation Insights on the Compound Action Potential in Multifascicular Nerves

ObjectiveDevelop an efficient method for simulating evoked compound action potential (eCAP) signals from complex nerves to help optimize and interpret eCAP recordings; validate it through comparison with measured vagus nerve eCAP recordings; elucidate the subtle interplay giving rise to specific eCAP signal shapes and magnitudes. ApproachWe developed an extended reciprocity theorem approach to model neuron signals in heterogeneous environments, and use it to study analytically the single fibre action potential. We then established a semi-analytic model that also uses hybrid electromagnetic-electrophysiological simulations to model eCAP signals from complex nerves populated with heterogeneous fiber populations of fibers. A cuff electrode was used to measure activity induced by vagus nerve stimulation in in vivo porcine experiments; these measurements were compared with signals produced by the model. Main ResultsThe semi-analytic model produces signals that approximate the shape and amplitude of in vivo measurements. Partially activated fascicles contribute substantially to the signal, as eCAP contributions from smoothly varying fiber calibers in fully activated ones partially cancel. As a result, eCAP magnitude does not depend monotonically on the stimulation current and recruitment level. Because the eCAP is sensitive to the degree of activation in individual fascicles, and to the location of the recording electrodes with respect to individual fascicles, the contributions of different fascicles to the recorded eCAP signals vary significantly with changes in the shape and placement of the stimulus and the recording electrodes. SignificanceOur method can be used to rapidly assess new stimulation and recording setups involving complex nerves and neurovascular bundles, e.g., to maximize signal information content, for closed-loop control in bioelectronic medicine applications, and potentially to non-destructively reconstruct structural and functional nerve topologies through inverse problem solving.

neuroscience↗

bioRxiv2023

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↗