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• W2767410147 abstract "Feature-Semantic Gradients in Lexical Categorization Revealed by Graded Manual Responses Rick Dale (rad28@cornell.edu) Nicholas C. Hindy (nch24@cornell.edu) Michael J. Spivey (spivey@cornell.edu) Department of Psychology, Cornell University, Ithaca, NY, 14853 Abstract research over the past 10 years has shown that eye movements offer a semi-continuous measure of ongoing cognitive processing (Ballard, Hayhoe, & Pelz, 1995; Tanenhaus, Spivey-Knowlton, Eberhard, & Sedivy, 1995; Underwood, 2005). Aggregate data from eye movements often indicate a graded nature inherent to cognition in general. Similar findings demonstrate that manual motor output can reveal graded representations. The force and velocity of manual responses vary concomitantly with frequency in a lexical decision task (Abrams & Balota, 1991; Balota & Abrams, 1995), and response and stimulus probability in simple reaction-time tasks (Mattes, Ulrich, & Miller, 2002; Ulrich, Mattes, & Miller, 1999; see also Osman, Kornblum, & Meyer, 1986; Balota, Boland, & Shields, 1989). And in experimental work similar to the saccade trajectory experiments described above, Tipper, Howard, and Jackson (1997) have shown that arm trajectories can curve depending on the visual distractor context in which reaching motions are made (see also Tipper et al., 1992; Sheliga et al., 1997). More recently, Spivey, Grosjean, and Knoblich (2005) and Dale, Kehoe, and Spivey (in press) used computer-mouse trajectories to show that graded manual output reveals temporal continuity in the underlying cognitive processes in spoken word recognition and categorization. In the latter two studies, manual trajectories were measured through streaming x-y coordinates of computer- mouse movement, and revealed attraction to other response choices in the visual display. For example, in Dale et al. (in press), mouse trajectories were recorded during lexical and pictorial categorization of animal exemplars. Participants categorized an animal by clicking the mouse on one of two category choices. Mouse-movement trajectories consisted of a movement from the bottom center of the screen, to the correct target on the upper left- or right-hand corner of the screen (beside which was a competing category label). Target trials used atypical animals (e.g., whale) with an incorrect competitor category that had considerable overlap in terms of semantic and visual features (e.g., fish). Though participants responded by clicking the appropriate category (e.g., mammal), mouse-movement trajectories exhibited substantial attraction toward the competitor category. Competing activation of the incorrect category in these trials was evident even in the properties of the resultant motor Participants performed a categorization task in which basic- level animal names (e.g., cat) were assigned to their superordinate categories (e.g., mammal). Manual motor output was measured by sampling computer-mouse movement while participants clicked on the correct superordinate category label, and not on a simultaneously presented incorrect category. Animal names were selected from the concept-name set of McRae, de Sa, & Seidenberg (1997), in which each concept is associated with a sparse semantic feature vector. If the competing category label draws motor attraction during the categorization task, this attraction should be predicted by feature-semantic measures based on animals’ proximity to the incorrect category. This proximity was computed by comparing each animal’s feature vector to the mean vector of alternative category choices (e.g., cat’s vector to the central tendency of all reptile vectors). Dependent measures were computed from mouse-movement trajectories. Degree of trajectory curvature correlated with the proximity of an animal’s vector to the mean vector of alternative categories, but only in a particular feature- semantic space. Results suggest that continuous motor output may systematically reflect underlying cognitive processing. Keywords: Categorization, representation, motor output typicality, semantics, Introduction An increasing amount of research reveals that dynamic characteristics of motor output reflect underlying cognitive processing, rather than simply reflecting the discrete decision resulting from that processing. For example, when the cognitive system directs manual output amidst an array of graspable objects, the arm’s movement does not always proceed in ballistic fashion toward a single selected object, but may vary continuously depending on the nature of underlying processing. Both manual output and oculomotor responses demonstrate these dynamic characteristics intrinsic to the temporal extent of a response, not just the final outcome of the response. For example, Doyle and Walker (2001) demonstrate that saccadic eye movements reflect attentional processing of visual cues in a simple fixation experiment. Saccade trajectories to the same location exhibit very subtle differential curvature depending on the position of distractor or cue stimuli (see also Sheliga, Riggio, & Rizzolatti, 1995). Additionally, considerable" @default.
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• W2767410147 title "Feature-Semantic Gradients in Lexical Categorization Revealed by Graded Manual Responses" @default.
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