NONLINEAR PREDICTION AS A TOOL FOR TRACKING THE DYNAMICS OF SINGLE-TRIAL READINESS POTENTIALS

The performance of a voluntary act is preceded by an intrinsic process of intention and preparation accompanied by specific patterns of scal p-recorded EEG. The baseline shift to negativity and the decrease of a lpha and beta oscillations prior to movement performance are considere d to reflect the motor preparation and are observable even in single-t rial EEG records during repetitive voluntary movements. The single-tri al features of these patterns are of importance since they would refle ct the dynamics of EEG activity during movement performance throughout the experimental session. Since this process is very complex and its dynamics is unclear, we applied a more general approach, i.e. the meth od of nonlinear prediction (NP) recommended for detection of chaos in the behavior of nonlinear dynamical systems. The NP is based on a libr ary of past patterns of the time series used to compute the prediction of future pattern. If the time series is chaotic, the correlation coe fficient between predicted and actual values would decrease as a funct ion of the prediction step. The NP was applied to EEG records containi ng readiness potentials (RPs) at Fz, Cz, Pz, C3 and C4 during repetiti ve voluntary finger flexion. Because of nonstationarity, the predictio n and the library spanned the same time period. As a result (1) chaoti c segments in EEG records were detected; and (2) the sharp jumps of th e absolute error between predicted and actual values indicated instanc es of poor prediction, which were interpreted as indicating new stages of EEG activity related to the preparatory process of motor activity.