title: RatCar system for estimating locomotion states using neural signals with parameter monitoring: Vehicle-formed brain-machine interfaces for rat.
abstract: An online brain-machine interface (BMI) in the form of a small vehicle, the 'RatCar,' has been developed. A rat had neural electrodes implanted in its primary motor cortex and basal ganglia regions to continuously record neural signals. Then, a linear state space model represents a correlation between the recorded neural signals and locomotion states (i.e., moving velocity and azimuthal variances) of the rat. The model parameters were set so as to minimize estimation errors, and the locomotion states were estimated from neural firing rates using a Kalman filter algorithm. The results showed a small oscillation to achieve smooth control of the vehicle in spite of fluctuating firing rates with noises applied to the model. Major variation of the model variables converged in a first 30 seconds of the experiments and lasted for the entire one hour session.
authors.affiliation: Department of Information Physics and Computing, Graduate School of Information Science and Technology, The University of Tokyo, 7-3-1 Hongo, Bunkyo, Japan. of@ratcar.org
authors.forename: Osamu
authors.initials: O
authors.lastname: Fukayama
authors.forename: Noriyuki
authors.initials: N
authors.lastname: Taniguchi
authors.forename: Takafumi
authors.initials: T
authors.lastname: Suzuki
authors.forename: Kunihiko
authors.initials: K
authors.lastname: Mabuchi
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000502:physiology*; D004562:Electrocardiography / Q000379:methods*; D005071:Evoked Potentials / Q000502:physiology*; D008124:Locomotion / Q000502:physiology*; D008328:Man-Machine Systems; D010363:Pattern Recognition, Automated / Q000379:methods*; D051381:Rats; D014584:User-Computer Interface