How different spatial-frequency components contribute to visual information acquisition.

We test 3 theories of global and local scene information acquisition, defining global and local in terms of spatial frequencies. By independence theories, high- and low-spatial-frequency information are acquired over the same time course and combine additively. By global-precedence theories, global information acquisition precedes local information acquisition, but they combine additively. By interactive theories, global information also affects local-information acquisition rate. We report 2 digit-recall experiments. In the 1st, we confirmed independence theories. In the 2nd, we disconfirmed both independence theories and interactive theories, leaving global-precedence theories as the remaining alternative. We show that a specific global-precedence theory quantitatively accounted for Experiments 1-2 data as well as for past data. We discuss how their spatial-frequency definition of spatial scale comports with definitions used by others, and we consider the suggestion by P. G. Schyns and colleagues (e.g., D. J. Morrison & Schyns, 2001) that the visual system may act flexibly rather than rigidly in its use of spatial scales.

[1]  Denis G. Pelli,et al.  The visual filter mediating letter identification , 1994, Nature.

[2]  A. Oliva,et al.  Dr. Angry and Mr. Smile: when categorization flexibly modifies the perception of faces in rapid visual presentations , 1999, Cognition.

[3]  A. Oliva,et al.  Coarse Blobs or Fine Edges? Evidence That Information Diagnosticity Changes the Perception of Complex Visual Stimuli , 1997, Cognitive Psychology.

[4]  J. Robson,et al.  Application of fourier analysis to the visibility of gratings , 1968, The Journal of physiology.

[5]  R. Watt.  Scanning from coarse to fine spatial scales in the human visual system after the onset of a stimulus. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[6]  Stephen A. Engel,et al.  Linearity across spatial frequency in object recognition , 1998, Vision Research.

[7]  J. Duncan,et al.  On the time course of perceptual information that results from a brief visual presentation. , 1992, Journal of experimental psychology. Human perception and performance.

[8]  G R Loftus,et al.  How much is an icon worth? , 1985, Journal of experimental psychology. Human perception and performance.

[9]  J R Lishman,et al.  Role of coarse and fine spatial information in face and object processing. , 1996, Journal of experimental psychology. Human perception and performance.

[10]  E. Wright,et al.  Effects of semantic priming on visual encoding of pictures. , 1989, Journal of experimental psychology. General.

[11]  H Pashler,et al.  How persuasive is a good fit? A comment on theory testing. , 2000, Psychological review.

[12]  G R Loftus,et al.  A theory of visual information acquisition and visual memory with special application to intensity-duration trade-offs. , 1994, Journal of experimental psychology. Human perception and performance.

[13]  G. Loftus,et al.  A front end to a theory of picture recognition , 1999, Psychonomic bulletin & review.

[14]  L. Kaufman,et al.  Handbook of perception and human performance , 1986 .

[15]  Nicholas Costen,et al.  One extreme or the other or perhaps the golden mean? Issues of spatial resolution in face processing , 1999 .

[16]  G. Loftus,et al.  Binocular information acquisition and visual memory. , 1998, Journal of experimental psychology. Human perception and performance.

[17]  G. Loftus,et al.  Differential Acquisition Rates for Different Types of Information from Pictures , 1983, The Quarterly journal of experimental psychology. A, Human experimental psychology.

[18]  H. Hughes,et al.  Global Precedence, Spatial Frequency Channels, and the Statistics of Natural Images , 1996, Journal of Cognitive Neuroscience.

[19]  Erin M. Harley,et al.  Why is it difficult to see in the fog? How stimulus contrast affects visual perception and visual memory , 2004, Psychonomic bulletin & review.

[20]  T. Sanocki.  Interaction of scale and time during object identification. , 2001, Journal of experimental psychology. Human perception and performance.

[21]  D G Pelli,et al.  The VideoToolbox software for visual psychophysics: transforming numbers into movies. , 1997, Spatial vision.

[22]  D H Brainard,et al.  The Psychophysics Toolbox. , 1997, Spatial vision.

[23]  T. Sanocki.  Time course of object identification: evidence for a global-to-local contingency. , 1993, Journal of experimental psychology. Human perception and performance.

[24]  D. Pelli,et al.  The role of spatial frequency channels in letter identification , 2002, Vision Research.

[25]  T. Sanocki,et al.  Effects of early common features on form perception , 1991, Perception & psychophysics.

[26]  N. Graham.  Visual Pattern Analyzers , 1989 .

[27]  Frédéric Gosselin,et al.  Bubbles: a technique to reveal the use of information in recognition tasks , 2001, Vision Research.

[28]  C Blakemore,et al.  On the existence of neurones in the human visual system selectively sensitive to the orientation and size of retinal images , 1969, The Journal of physiology.

[29]  D. Navon.  Forest before trees: The precedence of global features in visual perception , 1977, Cognitive Psychology.

[30]  T A Busey,et al.  Providing a sensory basis for models of visual information acquisition , 1993, Perception & psychophysics.

[31]  K. D. De Valois,et al.  Spatial vision. , 1980, Annual review of psychology.

[32]  P. Schyns,et al.  Usage of spatial scales for the categorization of faces, objects, and scenes , 2001, Psychonomic bulletin & review.

[33]  A. Oliva,et al.  From Blobs to Boundary Edges: Evidence for Time- and Spatial-Scale-Dependent Scene Recognition , 1994 .

[34]  G. Loftus,et al.  Sensory and cognitive components of visual information acquisition. , 1994, Psychological review.