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C R Sears

Publications and source records attributed to C R Sears.

4 recordsLinked to original sources
PubMed2000

Multiple object tracking and attentional processing.

How are attentional priorities set when multiple stimuli compete for access to the limited-capacity visual attention system? According to Pylyshyn (1989) and Yantis and Johnson (1990), a small number of visual objects can be preattentively indexed or tagged and thereby accessed more rapidly by a subsequent attentional process (e.g., the traditional "spotlight of attention"). In the present study, we used the multiple object tracking methodology of Pylyshyn and Storm (1988) to investigate the relation between what we call "visual indexing" and attentional processing. Participants visually tracked a subset of a set of identical, independently randomly moving objects in a display (the targets), and made a speeded identification response when they noticed a target or a nontarget (distractor) object undergo a subtle form transformation. We found that target form changes were identified more rapidly than nontarget form changes, and that the speed of responding to target form changes was unaffected by the number of nontargets in the display when the form-changing targets were successfully tracked. We also found that this enhanced processing only applied to the targets themselves and not to nearby nontarget distractors, showing that the allocation of a broadened region of visual attention (as in the zoom-lens model of attentional allocation) could not account for these findings. These results confirm that visual indexing bestows a processing priority to a number of objects in the visual field.

Attention↗
PubMed1999

Diversity of odourant binding proteins revealed by an expressed sequence tag project on male Manduca sexta moth antennae.

A small expressed sequence tag (EST) project generating 506 ESTs from 375 cDNAs was undertaken on the antennae of male Manduca sexta moths in an effort to discover olfactory receptor proteins. We encountered several clones that encode apparent transmembrane proteins; however, none is a clear candidate for an olfactory receptor. Instead we found a greater diversity of odourant binding proteins (OBPs) than previously known in moth antennae, raising the number known for M. sexta from three to seven. Together with evidence of seventeen members of the family from the Drosophila melanogaster genome project, our results suggest that insects may have many tens of OBPs expressed in subsets of the chemosensory sensilla on their antennae. These results support a model for insect olfaction in which OBPs selectively transport and present odourants to transmembrane olfactory receptors. We also found five members of a family of shorter proteins, named sensory appendage proteins (SAPs), that might also be involved in odourant transport. This small EST project also revealed several candidate odourant degrading enzymes including three P450 cytochromes, a glutathione S-transferase and a uridine diphosphate (UDP) glucosyltransferase. Several first insect homologues of proteins known from vertebrates, the nematode Caenorhabditis elegans, yeast and bacteria were encountered, and most have now also been detected by the large D. melanogaster EST project. Only thriteen entirely novel proteins were encountered, some of which are likely to be cuticle proteins.

Amino Acid Sequence↗
PubMed1999

Orthographic neighborhood effects in perceptual identification and semantic categorization tasks: a test of the multiple read-out model.

How should a word's orthographic neighborhood affect perceptual identification and semantic categorization, both of which require a word to be uniquely identified? According to the multiple read-out model (Grainger & Jacobs, 1996), inhibitory neighborhood frequency effects should be observed in these types of tasks, and facilitatory neighborhood size effects should not be. In Experiments 1 and 2 (perceptual identification), these effects were examined as a function of stimulus visibility (i.e., high vs. low visibility) to provide as full a test as possible of the model's predictions. In the high-visibility conditions, words with large neighborhoods were reported less accurately than words with small neighborhoods, but there was no effect of neighborhood frequency (i.e., whether the word had a higher frequency neighbor). In the low-visibility conditions, low-frequency words with large neighborhoods and low-frequency words with higher frequency neighbors showed superior identification performance. In the semantic categorization task (Experiment 3), words with large neighborhoods were responded to more rapidly than words with small neighborhoods, but there was no effect of neighborhood frequency. These results are inconsistent with two of the basic premises of the multiple read-out model--namely, that facilitatory neighborhood size effects are due to a variable response criterion (the sigma criterion), rather than to lexical selection processes, and that the lexical selection processes themselves produce an inhibitory neighborhood frequency effect (via the M criterion). Instead, the present results, in conjunction with previous findings, suggest that large neighborhoods (and perhaps higher frequency neighbors) do aid lexical selection.

Adult↗