Extremely selective attention: eye-tracking studies of the dynamic allocation of attention to stimulus features in categorization.

Humans have an extremely flexible ability to categorize regularities in their environment, in part because of attentional systems that allow them to focus on important perceptual information. In formal theories of categorization, attention is typically modeled with weights that selectively bias the processing of stimulus features. These theories make differing predictions about the degree of flexibility with which attention can be deployed in response to stimulus properties. Results from 2 eye-tracking studies show that humans can rapidly learn to differently allocate attention to members of different categories. These results provide the first unequivocal demonstration of stimulus-responsive attention in a categorization task. Furthermore, the authors found clear temporal patterns in the shifting of attention within trials that follow from the informativeness of particular stimulus features. These data provide new insights into the attention processes involved in categorization.

[1]  M. A. Erickson,et al.  Executive attention and task switching in category learning: Evidence for stimulus-dependent representation , 2008, Memory & cognition.

[2]  S. Lewandowsky,et al.  Context-gated knowledge partitioning in categorization. , 2003, Journal of experimental psychology. Learning, memory, and cognition.

[3]  Eric I. Knudsen,et al.  Top-down gain control of the auditory space map by gaze control circuitry in the barn owl , 2006, Nature.

[4]  Allen W Ingling,et al.  Separating perceptual and decisional attention processes in the identification and categorization of integral-dimension stimuli. , 2003, Journal of experimental psychology. Learning, memory, and cognition.

[5]  S. Liversedge,et al.  Saccadic eye movements and cognition , 2000, Trends in Cognitive Sciences.

[6]  T. Trabasso,et al.  Storage and verification stages in processing concepts. , 1971 .

[7]  Joseph H. Goldberg,et al.  Identifying fixations and saccades in eye-tracking protocols , 2000, ETRA.

[8]  John K. Kruschke,et al.  Dimensional Relevance Shifts in Category Learning , 1996, Connect. Sci..

[9]  D. Medin,et al.  SUSTAIN: a network model of category learning. , 2004, Psychological review.

[10]  E. Knudsen Fundamental components of attention. , 2007, Annual review of neuroscience.

[11]  E. Rolls,et al.  Attention, short-term memory, and action selection: A unifying theory , 2005, Progress in Neurobiology.

[12]  John R. Anderson,et al.  Eye Movements Do Not Reflect Retrieval Processes , 2004, Psychological science.

[13]  Thomas Serre,et al.  A feedforward architecture accounts for rapid categorization , 2007, Proceedings of the National Academy of Sciences.

[14]  John K. Kruschke,et al.  Associative learning in baboons (Papio papio) and humans (Homo sapiens): species differences in learned attention to visual features , 1998, Animal Cognition.

[15]  Aaron B. Hoffman,et al.  Thirty-something categorization results explained: selective attention, eyetracking, and models of category learning. , 2005, Journal of experimental psychology. Learning, memory, and cognition.

[16]  Wolfgang M. Pauli,et al.  Attentional control of associative learning—A possible role of the central cholinergic system , 2008, Brain Research.

[17]  J. Kruschke,et al.  Rules and exemplars in category learning. , 1998, Journal of experimental psychology. General.

[18]  N. Stanietsky,et al.  The interaction of TIGIT with PVR and PVRL2 inhibits human NK cell cytotoxicity , 2009, Proceedings of the National Academy of Sciences.

[19]  A. L. Yarbus,et al.  Eye Movements and Vision , 1967, Springer US.

[20]  James T. Townsend,et al.  Mathematical Psychology , 2020, Psychology.

[21]  I. J. Myung,et al.  Toward a method of selecting among computational models of cognition. , 2002, Psychological review.

[22]  J. Kruschke Toward a unified model of attention in associative learning , 2001 .

[23]  Aaron B. Hoffman,et al.  Eyetracking and selective attention in category learning , 2005, Cognitive Psychology.

[24]  J. Kruschke,et al.  Eye gaze and individual differences consistent with learned attention in associative blocking and highlighting. , 2005, Journal of experimental psychology. Learning, memory, and cognition.

[25]  R. Nosofsky Attention, similarity, and the identification-categorization relationship. , 1986, Journal of experimental psychology. General.

[26]  R. Desimone,et al.  Neural mechanisms of selective visual attention. , 1995, Annual review of neuroscience.

[27]  J. Kruschke,et al.  ALCOVE: an exemplar-based connectionist model of category learning. , 1992, Psychological review.

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

[29]  K. Rayner Eye movements in reading and information processing: 20 years of research. , 1998, Psychological bulletin.

[30]  J. D. Smith,et al.  Category learning in rhesus monkeys: a study of the Shepard, Hovland, and Jenkins (1961) tasks. , 2004, Journal of experimental psychology. General.

[31]  J. Kruschke,et al.  Rule-based extrapolation in perceptual categorization , 2002, Psychonomic bulletin & review.

[32]  J. Murre,et al.  Selective attention along arbitrary axes , 2007 .

[33]  Douglas L. Medin,et al.  Context theory of classification learning. , 1978 .

[34]  M. Corbetta,et al.  Control of goal-directed and stimulus-driven attention in the brain , 2002, Nature Reviews Neuroscience.

[35]  J. Findlay,et al.  The Relationship between Eye Movements and Spatial Attention , 1986, The Quarterly journal of experimental psychology. A, Human experimental psychology.

[36]  J. D. Smith,et al.  Comparing prototype-based and exemplar-based accounts of category learning and attentional allocation. , 2002, Journal of experimental psychology. Learning, memory, and cognition.

[37]  R. Paul,et al.  Phototaxis in water fleas (Daphnia magna) is differently influenced by visible and UV light , 1998, Journal of Comparative Physiology A.

[38]  Mark R. Blair,et al.  Errors, efficiency, and the interplay between attention and category learning , 2009, Cognition.

[39]  K. Lamberts Information-accumulation theory of speeded categorization. , 2000, Psychological review.

[40]  S. Lewandowsky,et al.  Knowledge partitioning in categorization: constraints on exemplar models. , 2004, Journal of experimental psychology. Learning, memory, and cognition.

[41]  Michael W. Spratling,et al.  A feedback model of perceptual learning and categorization , 2006, Visual Cognition.

[42]  A. L. Yarbus Eye Movements During Perception of Complex Objects , 1967 .

[43]  M. Segraves,et al.  Muscimol-induced inactivation of monkey frontal eye field: effects on visually and memory-guided saccades. , 1999, Journal of neurophysiology.

[44]  Garrison W. Cottrell,et al.  A probabilistic model of eye movements in concept formation , 2007, Neurocomputing.

[45]  J. Stevenson The cultural origins of human cognition , 2001 .

[46]  B. Love,et al.  The Emergence of Multiple Learning Systems , 2006 .

[47]  S. Edgell,et al.  Delayed exposure to additional relevant information in nonmetric multiple-cue probability learning , 1987 .