Brain-machine interfaces (BMIs) are mostly investigated as a means to provide paralyzed people with new communication channels with the external world. However, the communication between brain and artificial devices also offers a unique opportunity to study the dynamical properties of neural systems.
I focused on bidirectional interfaces, which operate in two ways by translating neural signals into input commands for the device and the output of the device into neural stimuli. Bidirectional BMIs help investigating neural information processing and how neural dynamics may participate in the control of external devices. In this respect, a bidirectional BMI can be regarded as a fancy combination of neural recording and stimulation apparatus, connected via an artificial body. The artificial body can be designed in virtually infinite ways in order to observe different aspects of neural dynamics and to approximate desired control policies.
- 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.
- 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.
- Vato A., Semprini M., Maggiolini E., Szymanski F.D., Fadiga L., Panzeri S. and Mussa-Ivaldi F.A. (2012). Shaping the dynamics of a bidirectional neural interface. PLoS Computational Biology 8(7), e1002578.
- Mussa-Ivaldi F.A., Alford S.T., Chiappalone M., Fadiga L., Karniel A., Kositsky M., Maggiolini E., Panzeri S., Sanguineti V., Semprini M. and Vato A. (2010). New perspectives on the dialogue between brains and machines. Frontiers in Neuroscience