Parameterized estimation of long-range correlation and variance components in human serial interval production.
Repetitive movements lead to isochronous serial interval production which exhibit inherent variability. The Wing-Kristofferson model offers a decomposition of the interresponse intervals in tapping tasks based on a cognitive component and on a motor component. We suggest a new theoretical and fully parametric approach to this model in which the cognitive component is modeled as a long-memory process and the motor component is treated as a white noise process, mutually independent. Under these assumptions, we obtained the autocorrelation function and the spectral density function. Furthermore, we propose an estimator based on the maximization of the frequency-domain representation of the likelihood function. Finally, we conducted a simulation study to assess the properties of this estimator and performed an experimental study involving tapping tasks with two target frequencies (1.250 Hz and 0.625 Hz).
Diniz
Ana
A
CIPER, Faculty of Human Kinetics, Technical University of Lisbon, Lisbon, Portugal.
Barreiros
João
J
Crato
Nuno
N
D000161:Acoustic Stimulation; D001288:Attention / Q000502:physiology; D001307:Auditory Perception; D003071:Cognition / Q000502:physiology*; D003198:Computer Simulation; D005260:Female; D006801:Humans; D008297:Male; D008959:Models, Neurological; D009043:Motor Activity / Q000502:physiology*; D009068:Movement / Q000502:physiology*; D011597:Psychomotor Performance / Q000502:physiology*; D011930:Reaction Time / Q000502:physiology; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors; D013998:Time Perception / Q000502:physiology; D055815:Young Adult