
doi: 10.3758/bf03202772
pmid: 7162943
In four experiments, right-handed subjects were asked to identify uppercase letters presented tachistoscopically in the right (R) or left (L) visual field or in both visual fields simultaneously (RL). When R, L, and RL trials were randomized together and RL trials consisted of the same letter in each visual field (Experiments 1 and 2), 11 of 21 male subjects (Experiment 1) and 9 of 18 female subjects (Experiment 2) showed a strong left-visual-field advantage, and the remainder in each experiment showed an equivalently strong right-visual-field advantage. When the RL trials consisted of a different letter in the two visual fields (Experiment 3), a consistent right-visual-field advantage was observed. It is argued that these results reflect predominantly analytical (left-hemisphere) processing of “different” pairs and relatively holistic processing of “same” pairs, which induces a shift toward a right-hemisphere advantage in some subjects. The main purpose of three of the four experiments was to test five probability models of hemispheric integration: (1) statistical summation, which assumes that the hemispheres operate independently; (2) redundancy, which assumes that RL decisions reflect only processing by the more specialized hemisphere; (3) complete dependency, according to which RL decisions are the mean of Rand L decisions; (4) integration, which assumes that R and L decisions can be represented as vectors in a joint RL space; (5) correlation, according to which the Rand L decisions are assumed to be statistically dependent. Whether R, L, and RL trials were randomized together or RL trials were presented in separate blocks, models 1 and 4 could be clearly rejected. In general, the best predictor of RL performance was model 5. It is argued that the hemispheres function as an integrated system in letter identification.
Form Perception, Male, Pattern Recognition, Visual, Humans, Female, Models, Psychological, Visual Fields, Dominance, Cerebral, Probability
Form Perception, Male, Pattern Recognition, Visual, Humans, Female, Models, Psychological, Visual Fields, Dominance, Cerebral, Probability
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