According to the age-of-acquisition hypothesis, words acquired early in life are processed faster and more accurately than words acquired later. Connectionist models have begun to explore the influence of the age/order of acquisition of items (and also their frequency of encounter). This study attempts to reconcile two different methodological and theoretical approaches (proposed by Lambon Ralph & Ehsan, 2006 and Zevin & Seidenberg, 2002) to age-limited learning effects. The current simulations extend the findings reported by Zevin and Seidenberg (2002) that (...) have shown that frequency trajectories (FTs) have limited and specific effects on word-reading tasks. Using the methodological framework proposed by Lambon Ralph and Ehsan (2006), which makes it possible to compare word-reading and picture-naming tasks in connectionist networks, we were able to show that FT has a considerable influence on age-limited learning effects in a picture naming task. The findings show that when the input–output mappings are arbitrary (simulating picture naming tasks), the links formed by the network become entrenched as a result of early experience and that subsequent variations in frequency of exposure of the items have only a minor impact. In contrast, when the mappings between input-output are quasi-systematic or systematic (simulating word-reading tasks), the training of new items was generalized and resulted in the suppression of age-limited learning effects. At a theoretical level, we suggest that FT, which simultaneously takes account of time and the level of exposure across time, represents a more precise and modulated measure compared with the order of introduction of the items and may lead to innovative hypotheses in the field of age-limited learning effects. (shrink)

Previous studies have shown that the human visual system can detect a face and elicit a saccadic eye movement toward it very efficiently compared to other categories of visual stimuli. In the first experiment, we tested the influence of facial expressions on fast face detection using a saccadic choice task. Face‐vehicle pairs were simultaneously presented and participants were asked to saccade toward the target (the face or the vehicle). We observed that saccades toward faces were initiated faster, and more often (...) in the correct direction, than saccades toward vehicles, regardless of the facial expressions (happy, fearful, or neutral). We also observed that saccade endpoints on face images were lower when the face was happy and higher when it was neutral. In the second experiment, we explicitly tested the detection of facial expressions. We used a saccadic choice task with emotional‐neutral pairs of faces and participants were asked to saccade toward the emotional (happy or fearful) or the neutral face. Participants were faster when they were asked to saccade toward the emotional face. They also made fewer errors, especially when the emotional face was happy. Using computational modeling, we showed that this happy face advantage can, at least partly, be explained by perceptual factors. Also, saccade endpoints were lower when the target was happy than when it was fearful. Overall, we suggest that there is no automatic prioritization of emotional faces, at least for saccades with short latencies, but that salient local face features can automatically attract attention. (shrink)