 |
FEDERICO LEVA
Dottorando
Dipartimento di Ingegneria "Enzo Ferrari"
|
Home |
Pubblicazioni
2023
- From Finite Element Simulations to Equivalent Circuit Models of Extracellular Neuronal Recording Systems based on Planar and Mushroom Electrodes
[Articolo su rivista]
Leva, Federico; Verardo, Claudio; Palestri, Pierpaolo; Selmi, Luca
abstract
2023
- Identification of Axon Bendings in Neurons by Multiphysics FEM Simulations of High-Density MEA Extracellular Recordings
[Relazione in Atti di Convegno]
Leva, Federico; Corna, Andrea; Werginz, Paul; Palestri, Pierpaolo; Zeck, Guenter; Selmi, Luca
abstract
2023
- Mitigation of Electrical/Ionic Interference in Iontronic Neurostimulation/Neurosensing Platforms: A Simulation Study
[Relazione in Atti di Convegno]
Nicolini, Jacopo; Leva, Federico; Palestri, Pierpaolo; Selmi, Luca
abstract
2022
- A simulation study of FET-based nanoelectrodes for active intracellular neural recordings
[Relazione in Atti di Convegno]
Leva, Federico; Palestri, Pierpaolo; Selmi, Luca
abstract
2022
- Multiphysics Finite-Element Modeling of the Neuron/Electrode Electrodiffusive Interaction
[Relazione in Atti di Convegno]
Leva, Federico; Verardo, Claudio; Mele, Leandro Julian; Palestri, Pierpaolo; Selmi, Luca
abstract
2022
- Multiscale simulation analysis of passive and active micro/nano-electrodes for CMOS-based in-vitro neural sensing devices
[Articolo su rivista]
Leva, Federico; Selmi, Luca; Palestri, Pierpaolo
abstract
Neuron and neural network studies are remarkably fostered by novel stimulation and recording systems, which often make use of biochips fabricated with advanced electronic technologies and, notably, micro and nanoscale CMOS. Models of the transduction mechanisms involved in the sensor and recording of the neuron activity are useful to optimize the sensing device architecture and its coupling to the readout circuits, as well as to interpret the measured data. Starting with an overview of recently published integrated active and passive micro/nano-electrode sensing devices for in-vitro studies fabricated with modern (CMOS based) micro-nano technology, this paper presents a mixed-mode device-circuit numerical analytical multiscale and multiphysics simulation methodology to describe the neuron-sensor coupling, suitable to derive useful design guidelines. A few representative structures and coupling conditions are analyzed in more detail in terms of the most relevant electrical figures of merit including signal-to-noise ratio.
2020
- Modelling of vertical nano-needles as sensing devices for neuronal signal recordings
[Relazione in Atti di Convegno]
Selmi, Luca; Palestri, Pierpaolo; Leva, Federico
abstract
This paper reports a design-oriented numerical study of vertical Si-nanowires to be used as sensing elements for the detection of the intracellular electrical activity of neurons. An equivalent lumped-element circuit model is derived and validated by comparison with physics-based numerical simulations. Most of the component values can be identified individually by geometrical and physical considerations. The transfer function and the SNR of the sensor in presence of thermal noise are derived, and the impact of the device geometry is shown.