Alberto Mazzoni

About

Alberto Mazzoni is a leading researcher at the intersection of neuroscience, robotics, and neural engineering, whose work is fundamentally reshaping our understanding of tactile perception and its application in prosthetics. His research focuses on three key areas: biomimetic tactile sensing, neuroprosthetic feedback, and computational neuroscience. Mazzoni’s major contributions include pioneering the use of spiking neural networks to model the cuneate nucleus—the brain’s first tactile processing station—demonstrating how these networks can learn and generalize naturalistic textures under varying conditions. His highly cited 2018 study (118 citations) provided a critical comparison of amplitude versus frequency modulation for intraneural sensory feedback in bidirectional hand prostheses, directly informing the design of more intuitive artificial limbs. Additionally, his 2021 survey of transfemoral amputee priorities (38 citations) has become a cornerstone for user-centered prosthetic design. Mazzoni’s work bridges the gap between biological neural dynamics and artificial systems, with notable achievements in developing neuromorphic touch sensors that can detect slippage and edge orientation. His research, accumulating hundreds of citations, is not only advancing fundamental neuroscience but also delivering tangible solutions for restoring sensory feedback and motor function in amputees and stroke patients.

Research Focus

Key Achievements

Top Papers

1. 1
   Comparison of linear frequency and amplitude modulation for intraneural sensory feedback in bidirectional hand prostheses

   118 citations · 2018
2. 2
   Survey of transfemoral amputee experience and priorities for the user-centered design of powered robotic transfemoral prostheses

   38 citations · 2021
3. 3
   Intracellular Dynamics in Cuneate Nucleus Neurons Support Self-Stabilizing Learning of Generalizable Tactile Representations

   36 citations · 2018
4. 4
   Cuneate spiking neural network learning to classify naturalistic texture stimuli under varying sensing conditions

   23 citations · 2019
5. 5
   Identification of Slippage on Naturalistic Surfaces via Wavelet Transform of Tactile Signals

   20 citations · 2018
6. 6
   Neuromorphic Artificial Sense of Touch: Bridging Robotics and Neuroscience

   15 citations · 2017
7. 7
   Tactile Decoding of Edge Orientation With Artificial Cuneate Neurons in Dynamic Conditions

   15 citations · 2019
8. 8
   Convergence of regular spiking and intrinsically bursting Izhikevich neuron models as a function of discretization time with Euler method

   12 citations · 2019
9. 9
   Biomimetic tactile sensing

   12 citations · 2015
10. 10
    Neurophysiological underpinnings of an intensive protocol for upper limb motor recovery in subacute and chronic stroke patients

    7 citations · 2023

Key Collaborators

Contact & Links