Dynamic Brain-Machine Interface
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Dynamic Brain-Machine Interface : a novel paradigm for bidirectional interaction between brains and dynamical systems. / Szymanski, Francois D; Semprini, Marianna; Mussa-Ivaldi, Ferdinando A; Fadiga, Luciano; Panzeri, Stefano; Vato, Alessandro.
In: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference, Vol. 2011, 2011, p. 4592-5.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Dynamic Brain-Machine Interface
T2 - a novel paradigm for bidirectional interaction between brains and dynamical systems
AU - Szymanski, Francois D
AU - Semprini, Marianna
AU - Mussa-Ivaldi, Ferdinando A
AU - Fadiga, Luciano
AU - Panzeri, Stefano
AU - Vato, Alessandro
PY - 2011
Y1 - 2011
N2 - Brain-Machine Interfaces (BMIs) are systems which mediate communication between brains and artificial devices. Their long term goal is to restore motor functions, and this ultimately demands the development of a new generation of bidirectional brain-machine interfaces establishing a two-way brain-world communication channel, by both decoding motor commands from neural activity and providing feedback to the brain by electrical stimulation. Taking inspiration from how the spinal cord of vertebrates mediates communication between the brain and the limbs, here we present a model of a bidirectional brain-machine interface that interacts with a dynamical system by generating a control policy in the form of a force field. In our model, bidirectional communication takes place via two elements: (a) a motor interface decoding activities recorded from a motor cortical area, and (b) a sensory interface encoding the state of the controlled device into electrical stimuli delivered to a somatosensory area. We propose a specific mathematical model of the sensory and motor interfaces guiding a point mass moving in a viscous medium, and we demonstrate its performance by testing it on realistically simulated neural responses.
AB - Brain-Machine Interfaces (BMIs) are systems which mediate communication between brains and artificial devices. Their long term goal is to restore motor functions, and this ultimately demands the development of a new generation of bidirectional brain-machine interfaces establishing a two-way brain-world communication channel, by both decoding motor commands from neural activity and providing feedback to the brain by electrical stimulation. Taking inspiration from how the spinal cord of vertebrates mediates communication between the brain and the limbs, here we present a model of a bidirectional brain-machine interface that interacts with a dynamical system by generating a control policy in the form of a force field. In our model, bidirectional communication takes place via two elements: (a) a motor interface decoding activities recorded from a motor cortical area, and (b) a sensory interface encoding the state of the controlled device into electrical stimuli delivered to a somatosensory area. We propose a specific mathematical model of the sensory and motor interfaces guiding a point mass moving in a viscous medium, and we demonstrate its performance by testing it on realistically simulated neural responses.
KW - Brain/physiology
KW - Humans
KW - Man-Machine Systems
U2 - 10.1109/IEMBS.2011.6091137
DO - 10.1109/IEMBS.2011.6091137
M3 - SCORING: Journal article
C2 - 22255360
VL - 2011
SP - 4592
EP - 4595
JO - Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
JF - Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
SN - 2375-7477
ER -