TY - JOUR
T1 - Using 1/f noise to examine planning and control in a discrete aiming task
AU - Valdez, André B.
AU - Amazeen, Eric
N1 - Funding Information:
Acknowledgments The authors gratefully acknowledge the contributions of Peter Killeen, Stephen Goldinger, and Didier Delignieres. This research was supported by National Science Foundation grant BCS-0518013.
PY - 2008/5
Y1 - 2008/5
N2 - The present study used 1/f noise to examine how spatial, physical, and timing constraints affect planning and control processes in aiming. Participants moved objects of different masses to different distances at preferred speed (Experiment 1) and as quickly as possible (Experiment 2). Power spectral density, standardized dispersion, rescaled range, and an autoregressive fractionally integrated moving average (ARFIMA) model selection procedure were used to quantify 1/f noise. Measures from all four analyses were in reasonable agreement, with more ARFIMA (long-range) models selected at peak velocity in Experiment 1 and fewer selected at peak velocity in Experiment 2. There also was a nonsignificant trend where, at preferred speed, of those participants who showed 1/f noise, more tended to show 1/f noise at peak velocity, when planning and control would overlap most. This trend disappeared for fast movements, where planning and control would have less time to overlap. Summing short-range processes at different timescales can produce 1/f-like noise. As planning is a slower-moving process and control faster, present results suggest that, with enough time for both planning and control, 1/f noise in aiming may arise from a similar summation of processes. Potential limitations of time series length in the present task are discussed.
AB - The present study used 1/f noise to examine how spatial, physical, and timing constraints affect planning and control processes in aiming. Participants moved objects of different masses to different distances at preferred speed (Experiment 1) and as quickly as possible (Experiment 2). Power spectral density, standardized dispersion, rescaled range, and an autoregressive fractionally integrated moving average (ARFIMA) model selection procedure were used to quantify 1/f noise. Measures from all four analyses were in reasonable agreement, with more ARFIMA (long-range) models selected at peak velocity in Experiment 1 and fewer selected at peak velocity in Experiment 2. There also was a nonsignificant trend where, at preferred speed, of those participants who showed 1/f noise, more tended to show 1/f noise at peak velocity, when planning and control would overlap most. This trend disappeared for fast movements, where planning and control would have less time to overlap. Summing short-range processes at different timescales can produce 1/f-like noise. As planning is a slower-moving process and control faster, present results suggest that, with enough time for both planning and control, 1/f noise in aiming may arise from a similar summation of processes. Potential limitations of time series length in the present task are discussed.
KW - 1/f Noise
KW - Control
KW - Fractal
KW - Long-range correlation
KW - Planning
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U2 - 10.1007/s00221-008-1305-0
DO - 10.1007/s00221-008-1305-0
M3 - Article
C2 - 18283444
AN - SCOPUS:42649120663
SN - 0014-4819
VL - 187
SP - 303
EP - 319
JO - Experimental Brain Research
JF - Experimental Brain Research
IS - 2
ER -