Neural Computer Interaction

Research activities

The Neural Computer Interaction Laboratory aims to investigate the dynamics of the brain processes toward the development of adaptive neuromodualtion medical devices.

A major goal of the NCILab is to develop a theoretical framework to analyze and decode Electrocorticographic signals (ECoGs) recorded form human subjects in order to increase our knowledge about the dynamics of the brain processes toward clinical applications of such knowledge. We are also interested in developing new algorithms to increase the amount of information that a bidirectional brain-machine interfaces exchange with the brain by exploring how neural responses depend on ongoing spontaneous activity.

Projects

EcoG

Analysis of ECoG grid recordings from human subject to understand dynamic communication across neural populations

Collaborations

• Neural Computation Lab in IIT (S. Panzeri)
• National Center for Adaptive Neurotechnologies at Wadsworth Center of Albany (G. Schalk)
• Albany Medical Center (A. Ritaccio)

Bidirectional BMI

Development of bidirectional brain-machine interfaces to explore new decoding and encoding strategies to increase the amount of information exchanged between the brain and the external environment.

Collaborations

• Neural Computation Lab in IIT (S. Panzeri)

Selected Publications

• A bidirectional brain-machine interface featuring a neuromorphic hardware decoder.

  Boi F, Moratis T, De Feo V, Diotalevi F, Bartolozzi C, Indiveri G, Vato A Frontiers in Neuroscience 10:563 (2016)

• Implications of the Dependence of Neuronal Activity on Neural Network States for the Design of Brain-Machine Interfaces

  Panzeri S, Safaai H, De Feo V, Vato A. Frontiers in Neuroscience (2016)

• A programmable closed-loop recording and stimulating wireless system for behaving small laboratory animals.

  Angotzi GN, Boi F, Zordan S, Bonfanti A, Vato A. Scientific Reports (2014)

• A bidirectional brain-machine interface algorithm that approximates arbitrary force-fields

  Vato A, Szymanski FD, Semprini M, Mussa Ivaldi FA, Panzeri S. PloS One, 9,3 (2014)

• Shaping the Dynamics of a Bidirectional Neural Interface.

  Vato A, Semprini M, Maggiolini E, Szymanski FD, Fadiga L, Panzeri S, Mussa Ivaldi FA. PLoS Computational Biology, vol. 8, no. 7 (2012)

Members

Principal investigator

Alessandro Vato received the M.Eng. degree in electronics engineering and the Ph.D. degree in Bioengineering and Bioelectronics both from the University of Genova, Genova, Italy in 2000 and 2004, respectively. From 2005 to 2008 he has been a Postdoctoral Fellow at the Department of Physiology at the Northwestern University of Chicago, IL. In 2008 he joined the Brain Machine Interface Laboratory at the Fondazione Istituto Italiano di Tecnologia as researcher. His research interests include the development of brain-machine interfaces for neuroprosthetic applications, closed-loop systems, cortical neurophysiology and intracortical microstimulation as artificial sensory channel.