Non-linear analysis of the rhythmic activity in rodent brains.
This paper discusses the employment of non-parametric non-linear prediction algorithms to investigate non-linear dynamics in the rhythmic brain activity of rats. Three algorithms (Sugihara-May Simplex, K-neighbour and Casdagli's) were tested yielding similar prediction results which--when subject to a suitable bootstrap based t-tests--revealed that the theta waves recorded in rat brains cannot have their intrinsic non-linearity dismissed at a significance of 0.05.
Alvarenga
M Y
MY
Graduate Program, IMECC, State University of Campinas, Brazil.
Sameshima
K
K
Baccalá
L A
LA
Yang
H M
HM
D000465:Algorithms; D000818:Animals; D005544:Forecasting; D006624:Hippocampus / Q000502:physiology*; D017711:Nonlinear Dynamics; D009716:Numerical Analysis, Computer-Assisted; D051381:Rats / Q000502:physiology*; D018709:Statistics, Nonparametric; D013826:Theta Rhythm / Q000662:veterinary*