The specialization of human face recognition for upright own-race faces is well-established. While experience is thought to play a key role in face specialization, establishing its direct causal contribution in humans is difficult, as natural experience cannot be systematically controlled. Recent advances in deep learning algorithms offer a solution: these algorithms were shown to generate human-like face specialization effects, including the face inversion and other-race effects. Critically, deep neural networks allow precise manipulation of their training experience, allowing us to test its sole contribution to human-like face expertise in artificial systems. In the present study, we systematically manipulated the amount of face experience provided to deep neural networks and examined its effect on the face inversion, the other-race and other-age effects. Mirroring human development, the magnitude of the other-group and face inversion effects increased with greater own-group upright face experience. These effects were primarily driven by a steep improvement in recognition of upright, own-group faces, with much shallower gains for other-group or inverted faces. These findings demonstrate that increased exposure to upright own-group faces selectively improves performance for this category, establishing that experience alone is sufficient to produce human-like face specialization effects in artificial systems.
A substantial recent literature has investigated readers' failure to detect transposed words in otherwise grammatical sentences. This phenomenon may reflect a process of rational inference, whereby a reader's prior over word strings overrides the bottom-up perceptual evidence. In three experiments, we tested the prediction emerging from the rational inference framework that failure to detect a transposition should be most common when the prior probability of the untransposed string is high. We found that the frequency of the trigram consisting of the two transposed words and the preceding word predicts failure to notice the transposition: Readers are more likely to miss a transposition of the final two words of a high-frequency trigram such as close the gate than a lower-frequency trigram such as close the pool. We also found a weaker role for the conditional probability of the transposed words based on the entire preceding sentence context. The results support a role for rational inference in 'correcting' errors, and also contribute further evidence that multi-word units play an important role in language processing.
This study examined visual statistical learning using EEG-based steady-state visual evoked potentials (SSVEP). Fifty-one adults were exposed to image sequences organized into triplets across three conditions (n = 17 per condition) in which the alignment of category-level and exemplar-level information was manipulated. Neural entrainment at the triplet frequency (1.11 Hz) differed significantly across conditions (η p 2 = .13), with stronger responses in the Single-Category and No-Category conditions than in the Mixed-Category condition. There were no differences at the image frequency (3.33 Hz; η p 2 = .05). Behavioral reaction times mirrored this pattern, showing faster responses to the last exemplar in the triplet in the Single-Category (η p 2 = .71) and No-Category (η p 2 = .22) conditions, but not in the Mixed-Category (η p 2 = .10) condition. Both signal-to-noise ratio (SNR) and inter-trial coherence (ITC) captured neural entrainment across fronto-central and parietal-occipital electrode clusters. These findings validate SSVEP as an online measure of visual statistical learning and demonstrate that category-exemplar mismatch interfered with statistical learning.
Can you perform an action intentionally if there was only a small chance your action would succeed? Researchers studying the folk concept of intentional action have documented complex patterns of intuitions in these cases. We propose to explain the data in terms of a causal theory of intentional action, according to which people consider an action intentional if there was a strong causal link between the agent's desire for the outcome and the outcome itself. When the outcome of an action is left to chance, people judge that the agent's desire was a weak cause of the outcome; this results in corresponding low intentionality judgment. Supporting our proposal, we find that in situations where people deny that a lucky outcome was brought about intentionally, they also deny that the outcome happened because of the agent's desire for that outcome. Intentionality judgments track causal judgments to a larger extent than they track other factors previously proposed to explain the luck effect. Our findings support the idea that a robust causal link between desire and outcome is a key component of the folk concept of intentional action.
Phonesthemes are sound clusters that recur in words with related meanings. For example, glow, gleam, and glitter begin with the phonestheme /gl/. Experiments with pseudowords provide evidence that phonesthemes affect how people retrieve and represent meanings, which suggests that phonesthemes capture language evolution in action, namely the emergence of compositionality. However, there is little evidence that phonesthemes affect how people process familiar words with established meanings. We therefore investigated whether phonesthemes facilitate visual word recognition and affect semantic representations in English. In two lexical decision experiments, people recognized words that contain phonesthemes faster and more accurately than control words, and phonesthemes amplified N170 ERPs; and in four lexical decision megastudies, phonesthemes predicted faster visual word recognition (but not faster auditory recognition). In two semantic relatedness experiments, we found only limited evidence that phonesthemes affect interpretation: Decisions were slower and less accurate for words containing incongruent phonesthemes (e.g., /gl/ misled people about the meaning of glove), but only in the online experiment, with a marginal effect of accuracy in the lab-based experiment and an amplified N400 ERP in frontal sites (but not the expected centroparietal sites). Our findings demonstrate that people process words which contain phonesthemes differently than they process controls, consistent with the hypothesis that phonesthemes inhabit a middle ground between morphemes and meaningless strings of letters, but our findings also demonstrate that, unsurprisingly, these quasi-meaningful constituents have only small effects in how people represent the meanings of familiar words. We discuss implications for morphology, language evolution, and natural language processing.
