Representative Publications

Books and Book Chapters

• Semprini M., Boi F. and Vato A. (2016) Bidirectional Brain-Machine Interfaces. In: Closed Loop
  Neuroscience, edited by El Hady, Academic Press, San Diego (U.S.), pp. 201-212.
• Vato A. (2015) The cyborgs are coming: neuroscience and bioengineering meet - Arrivano i cyborg.
  Dove neuroscienze e bioingengeria si incontrano, Italian language, Hoepli Press, Milan (Italy).
• Bonzano L., Vato A., Chiappalone M. and Martinoia S. (2007) Modulation of electrophysiological
  activity in neural networks: towards a bioartificial living system. In: Handbook of Neural Engineering,
  edited by Matin Akay, Wiley/IEEE Press, New York (U.S.), pp. 29-40.
• Martinoia S., Chiappalone M. and Vato A. (2004) Bioartificial neuronal networks: coupling networks of
  biological neuron to microtransducer arrays. In: Smart adaptive system on silicon, edited by Valle M.,
  Kluwer Academic Publisher, Boston (U.S.), pp. 285-302.

 

Journal Articles

• Xie, T., Wu, Z., Schalk, G., Tong, Y., Vato, A., Raviv, N., Guo, Q., Ye, H., Sheng, X., Zhu, X., Brunner,
  P. & Chen, L. (2022). Automated intraoperative central sulcus localization and somatotopic mapping
  using median nerve stimulation. Journal of Neural Engineering, 19(4), 046020.
• Putzolu, M., Samogin J., Cosentino C., Mezzarobba S., Bonassi G., Lagravinese G., Vato A., Mantini
  D., Avanzino L., and Pelosin E. (2022) Neural oscillations during motor imagery of complex gait: an
  HdEEG study. Scientific Reports 12, 4314.
• De Feo, V., Boi, F., Safaai, H., Onken, A., Panzeri, S., and Vato, A. (2017) State-dependent decoding
  algorithms improve the performance of a bidirectional BMI in anesthetized rats. Frontiers in
  Neuroscience, 11, 269.
• Boi F., Moratis T., De Feo V., Diotalevi F., Bartolozzi C., Indiveri G., and Vato A. (2016) A bidirectional
  brain-machine interface featuring a neuromorphic hardware decoder. Frontiers in Neuroscience, 10,
  563.
• Panzeri S., Safaai H., De Feo V., and Vato A. (2016) Implications of the dependence of neuronal
  activity on neural network states for the design of brain-machine interfaces. Frontiers in Neuroscience,
  10, 165.
• Angotzi G.N., Baranauskas G., Vato A., Bonfanti A., Zambra G., Maggiolini E., Semprini M., Ricci D.,
  Ansaldo A, Castagnola E., Ius T., Skrap M., and Fadiga L. (2015) A Compact and Autoclavable System
  for Acute Extracellular Neural Recording and Brain Pressure Monitoring for Humans. IEEE
  Transactions on Biomedical Circuits and Systems 9(1), 50-59.
• Angotzi G.N., Boi F., Zordan S., Bonfanti A., and Vato A. (2014) A programmable closed-loop recording
  and stimulating wireless system for behaving small laboratory animals. Scientific Reports 4, 5963.
• Vato A., Szymanski F.D., Semprini M., Mussa-Ivaldi F.A., and Panzeri S. (2014) A bidirectional brain-machine interface algorithm that approximates arbitrary force fields. PLoS One 9(3), e91677.