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).
CIPER, Faculty of Human Kinetics, Technical University of Lisbon, Lisbon, Portugal.
Ana
A
Diniz
João
J
Barreiros
Nuno
N
Crato
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