The Library
System identification in priming of pop-out
Tools
Martini, Paolo. (2010) System identification in priming of pop-out. Vision Research, Vol.50 (No.21). pp. 2110-2115. ISSN 0042-6989
|
PDF
WRAP_Martini_281011-kernel3.pdf - Accepted Version - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader Download (603Kb) |
Official URL: http://dx.doi.org/10.1016/j.visres.2010.07.024
Abstract
Inter-trial repetitions of a target's features in a visual search task reduce the time needed to find the target. Here I examine these sequential dependencies in the Priming of Pop-Out task (PoP) by means of system identification techniques. The results are as follows. Response time facilitation due to repetition of the target's features increases linearly with difficulty in segmenting the target from the distracters. However, z-scoring the reaction times normalizes responses by equating facilitation across levels of difficulty. Memory kernels, representing the influence of the current trial on any future trial, can then be calculated from data normalized and averaged across conditions and observers. The average target-defining feature kernel and the target position kernel are well fit by a sum of two exponentials model, comprised of a high-gain, fast-decay component and a low-gain, slow-decay component. In contrast, the average response-defining feature kernel is well fit by a single exponential model with very low-gain and decay similar to the slow component of the target-defining feature kernel. Analysis of single participant's data reveals that a fast-decay component is often also present for the response-defining feature, but can be either facilitatory or inhibitory and thus tends to cancel out in pooled data. Overall, the results are similar to integration functions of reward history recently observed in primates during frequency-matching experiments. I speculate that sequential dependencies in POP result from learning mechanisms that bias the attentional weighting of certain aspects of the stimulus in an effort to minimize a prediction error signal.
| Item Type: | Journal Article |
|---|---|
| Subjects: | B Philosophy. Psychology. Religion > BF Psychology |
| Divisions: | Faculty of Science > Psychology |
| Library of Congress Subject Headings (LCSH): | Visual perception, Recognition (Psychology) |
| Journal or Publication Title: | Vision Research |
| Publisher: | Pergamon-Elsevier Science Ltd. |
| ISSN: | 0042-6989 |
| Date: | 12 October 2010 |
| Volume: | Vol.50 |
| Number: | No.21 |
| Number of Pages: | 6 |
| Page Range: | pp. 2110-2115 |
| Identification Number: | 10.1016/j.visres.2010.07.024 |
| Status: | Peer Reviewed |
| Publication Status: | Published |
| Access rights to Published version: | Restricted or Subscription Access |
| Funder: | Research Councils UK (RCUK) |
| References: | Baddeley, R.J., Ingram, H.A., & Miall, R.C. (2003). System identification applied to a visuomotor task: Near-optimal human performance in a noisy changing task. Journal of Neuroscience, 23 (7), 3066-3075. Bertelson, P. (1965). Serial choice reaction-time as a function of response versus signal-and-response repetition. Nature, 206 (980), 217-218. Corrado, G.S., Sugrue, L.P., Seung, H.S., & Newsome, W.T. (2005). Linear-nonlinear-Poisson models of primate choice dynamics. Journal of the Experimental Analysis of Behavior, 84 (3), 581-617. DeCarlo, L.T., & Cross, D.V. (1990). Sequential effects in magnitude scaling: Models and theory. Journal of Experimental Psychology: General, 119 (4), 375-396. Goodfellow, L.D. (1938). A psychological interpretation of the results of the Zenith radio experiments in telepathy. Journal of Experimental Psychology, 23 (6), 601-632. Goolsby, B.A., & Suzuki, S. (2001). Understanding priming of color-singleton search: Roles of attention at encoding and "retrieval." Perception & Psychophysics, 63 (6), 929-944. Hagelbarger, D.W. (1956). SEER, A SEquence Extrapolating Robot. IRE Transactions on Electronic Computers, EC-5 (1), 1-7. Hunter, I., & Davison, M. (1985). Determination of a behavioral transfer function: White-noise analysis of session-to-session response-ratio dynamics on concurrent VI VI schedules. Journal of the Experimental Analysis of Behavior, 43 (1), 43-59. Hurst, H.E., Black, R.P., & Simaika, Y.M. (1965). Long-term storage, an experimental study. (pp. xiv, 145 p.). London,: Constable. Kristjansson, A. (2008). "I know what you did on the last trial"--a selective review of research on priming in visual search. Front Biosci, 13, 1171-1181. Laming, D.R. (1969). Subjective probability in choice-reaction experiments. Journal of Mathematical Psychology, 6 (1), 81-120. Lau, B., & Glimcher, P.W. (2005). Dynamic response-by-response models of matching behavior in rhesus monkeys. Journal of the Experimental Analysis of Behavior, 84 (3), 555-579. Maljkovic, V., & Martini, P. (2005). Implicit short-term memory and event frequency effects in visual search. Vision Research, 45 (21), 2831-2846. Maljkovic, V., & Nakayama, K. (1994). Priming of pop-out: I. Role of features. Memory & Cognition, 22 (6), 657-672. Maljkovic, V., & Nakayama, K. (1996). Priming of pop-out: II. The role of position. 1996. Perception & Psychophysics, 58 (7), 977-991. Maljkovic, V., & Nakayama, K. (2000). Priming of pop-out: III. A short-term implicit memory system beneficial for rapid target selection. Visual Cognition, 7 (5), 571-595. Marmarelis, P.Z., & Marmarelis, V.Z. (1978). Analysis of physiological systems : the white-noise approach. (pp. xvi, 487). New York: Plenum Press. Marmarelis, V.Z., & Berger, T.W. (2005). General methodology for nonlinear modeling of neural systems with Poisson point-process inputs. Math Biosci, 196 (1), 1-13. Maunsell, J.H. (2004). Neuronal representations of cognitive state: reward or attention? Trends Cogn Sci, 8 (6), 261-265. McClure, S.M., Ericson, K.M., Laibson, D.I., Loewenstein, G., & Cohen, J.D. (2007). Time discounting for primary rewards. J Neurosci, 27 (21), 5796-5804. Rustichini, A. (2008). Dual or unitary system? Two alternative models of decision making. Cogn Affect Behav Neurosci, 8 (4), 355-362. Senders, V.L., & Sowards, A. (1952). Analysis of response sequences in the setting of a psychophysical experiment. 1952. American Journal of Psychology, 65, 358-374. Skinner, B.F. (1942). The processes involved in the repeated guessing of alternatives. Journal of Experimental Psychology, 30 (6), 495-503. Stewart, N., Brown, G.D.A., & Chater, N. (2002). Sequence effects in categorization of simple perceptual stimuli. 2002. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28 (1), 3-11. Sugrue, L.P., Corrado, G.S., & Newsome, W.T. (2005). Choosing the greater of two goods: Neural currencies for valuation and decision making. Nature Reviews Neuroscience, 6 (5), 363-375. Sutton, R.S., & Barto, A.G. (1998). Reinforcement learning : an introduction. (pp. xviii, 322 p.). Cambridge, Mass.: MIT Press. Taylor, L.R., Woiwod, I.P., & Perry, J.N. (1978). Density-Dependence of Spatial Behavior and Rarity of Randomness. Journal of Animal Ecology, 47 (2), 383-406. Treisman, M., & Faulkner, A. (1984). The setting and maintenance of criteria representing levels of confidence. Journal of Experimental Psychology: Human Perception and Performance, 10 (1), 119-139. Verplanck, W.S., Collier, G.H., & Cotton, J.W. (1952). Nonindependence of successive responses in measurements of the visual threshold. Journal of Experimental Psychology, 44 (4), 273-282. Wagenmakers, E.-J., & Brown, S. (2007). On the linear relation between the mean and the standard deviation of a response time distribution. Psychological Review, 114 (3), 830-841. |
| URI: | http://wrap.warwick.ac.uk/id/eprint/5047 |
Data sourced from Thomson Reuters' Web of Knowledge
Actions (login required)
![]() |
View Item |
Tools
Tools

