Despite an obvious demand for a variety of statistical tests adapted to classification images, few have been proposed. We argue that two statistical tests based on random field theory (RFT) satisfy this need for smooth classification images. We illustrate these tests on classification images representative of the literature from F. Gosselin and P. G. Schyns (2001) and from A. B. Sekuler, C. M. Gaspar, J. M. Gold, and P. J. Bennett (2004). The necessary computations are performed using the Stat4Ci Matlab toolbox.
The determination of the visual features mediating letter identification has a long-standing history in cognitive science. Researchers have proposed many sets of letter features as important for letter identification, but no such sets have yet been derived directly from empirical data. In the study reported here, we applied the Bubbles technique to reveal directly which areas at five different spatial scales are efficient for the identification of lowercase and uppercase Arial letters. We provide the first empirical evidence that line terminations are the most important features for letter identification. We propose that these small features, represented at several spatial scales, help readers to discriminate among visually similar letters.
Configural processing in autism was studied in Experiment 1 by using the face inversion effect. A normal inversion effect was observed in the participants with autism, suggesting intact configural face processing. A priming paradigm using partial or complete faces served in Experiment 2 to assess both local and configural face processing. Overall, normal priming effects were found in participants with autism, irrespective of whether the partial face primes were intuitive face parts (i.e., eyes, nose, etc.) or arbitrary segments. An exception, however, was that participants with autism showed magnified priming with single face parts relative to typically developing control participants. The present findings argue for intact configural processing in autism along with an enhanced processing for individual face parts. The face-processing peculiarities known to characterize autism are discussed on the basis of these results and past congruent results with nonsocial stimuli.
The authors examined spatial frequency (SF) tuning of upright and inverted face identification using an SF variant of the Bubbles technique (F. Gosselin & P. G. Schyns, 2001). In Experiment 1, they validated the SF Bubbles technique in a plaid detection task. In Experiments 2a-c, the SFs used for identifying upright and inverted inner facial features were investigated. Although a clear inversion effect was present (mean accuracy was 24% higher and response times 455 ms shorter for upright faces), SF tunings were remarkably similar in both orientation conditions (mean r ϭ .98; an SF band of 1.9 octaves centered at 9.8 cycles per face width for faces of about 6°). In Experiments 3a and b, the authors demonstrated that their technique is sensitive to both subtle bottom-up and top-down induced changes in SF tuning, suggesting that the null results of Experiments 2a-c are real. The most parsimonious explanation of the findings is provided by the quantitative account of the face inversion effect: The same information is used for identifying upright and inverted inner facial features, but processing has greater sensitivity with the former.
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