Interference in character processing reflects common perceptual expertise across writing systems.

Perceptual expertise, even within the visual domain, can take many forms, depending on the goals of the practiced task and the visual information available to support performance. Given the same goals, expertise for different categories can recruit common perceptual resources, which could lead to interference during concurrent processing. We measured whether irrelevant characters of one writing system produce interference during visual search for characters of another writing system, as a function of expertise. Chinese-English bilinguals and English readers searched for target Roman letters among other distractors in a rapid serial visual presentation (RSVP) sequence. Chinese character distractors interfered with Roman letter search more than pseudoletter distractors, only for bilingual readers, suggesting a common perceptual bottleneck for Roman and Chinese processing in experts with both domains. We ruled out an explanation at the level of phonetic codes, by showing that concurrent verbal rehearsal has no effect on the magnitude of such interference. These findings converge with results showing competition between faces and cars in car experts to suggest that different domains of expertise that overlap in their cortical representations also possess a common perceptual bottleneck.

[1]  Isabel Gauthier,et al.  What constrains the organization of the ventral temporal cortex? , 2000, Trends in Cognitive Sciences.

[2]  Talma Hendler,et al.  Eccentricity Bias as an Organizing Principle for Human High-Order Object Areas , 2002, Neuron.

[3]  W. Schneider,et al.  Cross‐cultural effect on the brain revisited: Universal structures plus writing system variation , 2005, Human brain mapping.

[4]  M. Tarr,et al.  Visual expertise with nonface objects leads to competition with the early perceptual processing of faces in the human occipitotemporal cortex. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[5]  G. Jobard,et al.  The Case for Letter Expertise , 2009 .

[6]  I. Gauthier,et al.  Perceptual interference supports a non-modular account of face processing , 2003, Nature Neuroscience.

[7]  Isabel Gauthier,et al.  Letter processing in the visual system: Different activation patterns for single letters and strings , 2005, Cognitive, affective & behavioral neuroscience.

[8]  T. Busey,et al.  Behavioral and electrophysiological evidence for configural processing in fingerprint experts , 2005, Vision Research.

[9]  N. Kanwisher,et al.  Visual word processing and experiential origins of functional selectivity in human extrastriate cortex , 2007, Proceedings of the National Academy of Sciences.

[10]  K. James,et al.  Letter processing automatically recruits a sensory–motor brain network , 2006, Neuropsychologia.

[11]  C. Eriksen,et al.  Effects of noise letters upon the identification of a target letter in a nonsearch task , 1974 .

[12]  A. Watson,et al.  Quest: A Bayesian adaptive psychometric method , 1983, Perception & psychophysics.

[13]  I. Gauthier,et al.  Conditions for Facelike Expertise with Objects Becoming a Ziggerin Expert—but Which Type? , 2022 .

[14]  M. Posner Chronometric explorations of mind : the third Paul M. Fitts lectures, delivered at the University of Michigan, September 1976 , 1978 .

[15]  Yetta Kwailing Wong,et al.  A Multimodal Neural Network Recruited by Expertise with Musical Notation , 2010, Journal of Cognitive Neuroscience.

[16]  J. Tanaka The entry point of face recognition: evidence for face expertise. , 2001, Journal of experimental psychology. General.

[17]  Isabel Gauthier,et al.  Expertise with characters in alphabetic and nonalphabetic writing systems engage overlapping occipito-temporal areas , 2009, Cognitive neuropsychology.

[18]  David L. Sheinberg,et al.  The Training and Transfer of Real-World Perceptual Expertise , 2005, Psychological science.

[19]  James W. Tanaka,et al.  A Reevaluation of the Electrophysiological Correlates of Expert Object Processing , 2006, Journal of Cognitive Neuroscience.

[20]  A. Treisman,et al.  A feature-integration theory of attention , 1980, Cognitive Psychology.

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

[22]  M. Tarr,et al.  Unraveling mechanisms for expert object recognition: bridging brain activity and behavior. , 2002, Journal of experimental psychology. Human perception and performance.

[23]  Isabel Gauthier,et al.  An early electrophysiological response associated with expertise in letter perception , 2005, Cognitive, affective & behavioral neuroscience.

[24]  Bruno Rossion,et al.  Long-term Expertise with Artificial Objects Increases Visual Competition with Early Face Categorization Processes , 2007, Journal of Cognitive Neuroscience.

[25]  Urs Maurer,et al.  Left-lateralized N170 Effects of Visual Expertise in Reading: Evidence from Japanese Syllabic and Logographic Scripts , 2008, Journal of Cognitive Neuroscience.

[26]  I. Gauthier,et al.  An analysis of letter expertise in a levels-of-categorization framework , 2007 .

[27]  I. Gauthier,et al.  Expertise for cars and birds recruits brain areas involved in face recognition , 2000, Nature Neuroscience.

[28]  Rankin W. McGugin,et al.  Expertise increases the functional overlap between face and object perception , 2010, Cognition.

[29]  Glyn W. Humphreys,et al.  A Search Asymmetry Reversed by Figure-Ground Assignment , 2000, Psychological science.

[30]  Cindy M. Bukach,et al.  Beyond faces and modularity: the power of an expertise framework , 2006, Trends in Cognitive Sciences.

[31]  Edward Awh,et al.  Evidence against a central bottleneck during the attentional blink: Multiple channels for configural and featural processing , 2004, Cognitive Psychology.

[32]  G. Cottrell,et al.  Seeing Blobs as Faces or Letters: Modeling Effects on Discrimination , 2004 .

[33]  G. E. MacKinnon,et al.  Reading Research Advances in Theory and Practice , 1985 .

[34]  Xueting Li,et al.  The Role of Top-Down Task Context in Learning to Perceive Objects , 2010, The Journal of Neuroscience.

[35]  I. Gauthier,et al.  Beyond Shape: How You Learn about Objects Affects How They Are Represented in Visual Cortex , 2009, PloS one.

[36]  Isabel Gauthier,et al.  Font Tuning Associated with Expertise in Letter Perception , 2006, Perception.

[37]  A. Treisman Perceptual grouping and attention in visual search for features and for objects. , 1982, Journal of experimental psychology. Human perception and performance.

[38]  K. James,et al.  The role of sensorimotor learning in the perception of letter-like forms: Tracking the causes of neural specialization for letters , 2009, Cognitive neuropsychology.

[39]  Rankin W. McGugin,et al.  Irrelevant objects of expertise compete with faces during visual search , 2011, Attention, perception & psychophysics.

[40]  J. Tanaka,et al.  Object categories and expertise: Is the basic level in the eye of the beholder? , 1991, Cognitive Psychology.

[41]  N. Lavie Perceptual load as a necessary condition for selective attention. , 1995, Journal of experimental psychology. Human perception and performance.

[42]  M. Posner,et al.  Retention of visual and name codes of single letters. , 1969, Journal of experimental psychology.