Search

Localist models of spreading activation (SA) and models assuming distributed representations offer very different takes on semantic priming, a widely investigated paradigm in word recognition and semantic memory research. In this study, we implemented SA in an attractor neural network model with distributed representations and created a unified framework for the two approaches. Our models assume a synaptic depression mechanism leading to autonomous transitions between encoded memory patterns (latching dynamics), which account for the major characteristics of automatic semantic priming in humans. Using computer simulations, we demonstrated how findings that challenged attractor-based networks in the past, such as mediated and asymmetric priming, are a natural consequence of our present model's dynamics. Puzzling results regarding backward priming were also given a straightforward explanation. In addition, the current model addresses some of the differences between semantic and associative relatedness and explains how these differences interact with stimulus onset asynchrony in priming experiments. (Contains 13 notes and 9 figures.)

Prior semantic knowledge facilitates episodic recognition memory for faces. To examine the neural manifestation of the interplay between semantic and episodic memory, we investigated neuroelectric dynamics during the creation (study) and the retrieval (test) of episodic memories for famous and nonfamous faces. Episodic memory effects were evident in several EEG frequency bands: theta (4-8 Hz), alpha (9-13 Hz), and gamma (40-100 Hz). Activity in these bands was differentially modulated by preexisting semantic knowledge and by episodic memory, implicating their different functional roles in memory. More specifically, theta activity and alpha suppression were larger for old compared to new faces at test regardless of fame, but were both larger for famous faces during study. This pattern of selective semantic effects suggests that the theta and alpha responses, which are primarily associated with episodic memory, reflect utilization of semantic information only when it is beneficial for task performance. In contrast, gamma activity decreased between the first (study) and second (test) presentation of a face, but overall was larger for famous than nonfamous faces. Hence, the gamma rhythm seems to be primarily related to activation of preexisting neural representations that may contribute to the formation of new episodic traces. Taken together, these data provide new insights into the complex interaction between semantic and episodic memory for faces and the neural dynamics associated with mnemonic processes.

Numerous studies have demonstrated that Huntington's disease mutation-carriers have deficient explicit recognition of isolated facial expressions. There are no studies, however, which have investigated the recognition of facial expressions embedded within an emotional body and scene context. Real life facial expressions are typically embedded in contexts which may dramatically change the emotion recognized in the face. Moreover, a recent study showed that the magnitude of the contextual bias is modulated by the similarity between the actual expression of the presented face and the facial expression that would typically fit the context, e.g. disgust faces are more similar to anger than to sadness faces and, consequently, are more strongly influenced by contexts expressing anger than by contexts expressing sadness. Since context effects on facial expression perception are not explicitly controlled, their pattern serves as an implicit measure of the processing of facial expressions. In this study we took advantage of the face-in-context design to compare explicit recognition of face-expressions by Huntington's disease mutation-carriers, with evidence for processing the expressions deriving from implicit measures. In an initial experiment we presented a group of 21 Huntington's disease mutation-carriers with standard tests of face-expression recognition. Relative to controls, they displayed deficits in recognizing disgust and anger faces despite intact recognition of these emotions from non-facial images. In a subsequent experiment, we embedded the disgust faces on images of people conveying sadness and anger as expressed by body language and additional paraphernalia. In addition, sadness and anger faces were embedded on context images conveying disgust. In both cases participants were instructed to categorize the facial expressions, ignoring the context. Despite the deficient explicit recognition of isolated disgust and anger faces, the perception of the emotions expressed by the faces was affected by context in Huntington's disease mutation-carriers in a similar manner as in control participants. Specifically, they displayed the same sensitivity to face-context pairings. These findings suggest that, despite their impaired explicit recognition of facial expressions, Huntington's disease mutation-carriers display relatively preserved processing of the same facial configurations when embedded in context. The results also show intact utilization of the information elicited by contextual cues about faces expressing disgust even when the actually presented face expresses a different emotion. Overall, our findings shed light on the nature of the deficit in facial expression recognition in Huntington's disease mutation-carriers as well as underscore the importance of context in emotion perception.

Words become associated following repeated co-occurrence episodes. This process might be further determined by the semantic characteristics of the words. The present study focused on how semantic and episodic factors interact in incidental formation of word associations. First, we found that human participants associate semantically related words more easily than unrelated words; this advantage increased linearly with repeated co-occurrence. Second, we developed a computational model, SEMANT, suggesting a possible mechanism for this semantic-episodic interaction. In SEMANT, episodic associations are implemented through lateral connections between nodes in a pre-existent self-organized map of word semantics. These connections are strengthened at each instance of concomitant activation, proportionally with the amount of the overlapping activity waves of activated nodes. In computer simulations SEMANT replicated the dynamics of associative learning in humans and led to testable predictions concerning normal associative learning as well as impaired learning in a diffuse semantic system like that characteristic of schizophrenia.

This study of 508 Israeli kindergarten children learning to read Hebrew found that phonemic segmentation skills and reading acquisition are highly interrelated. Learning to read was the main factor accounting for the sharp increase in phonological awareness between six and seven years of age, and reading acquisition was facilitated by prior training in phonological awareness. (Author/JDD)

The reading skills of Hebrew and English readers are examined in the development of an orthographic representation to measure phonemic segmentation and phonological capability. Orthographic units are observed in terms of consonant-plus-vowel (CV) utterances and size differences for CV segments are considered. Phonological information conditioned phonological sensitivity and phonemic segmentation.

Abstract Background Loosening of associations and thought disruption are key features of schizophrenic psychopathology. Alterations in neural networks underlying this basic abnormality have not yet been sufficiently identified. Previously, we demonstrated that spatio-temporal clustering of magnetic brain responses to pictorial stimuli map categorical representations in temporal cortex. This result has opened the possibility to quantify associative strength within and across semantic categories in schizophrenic patients. We hypothesized that in contrast to controls, schizophrenic patients exhibit disordered representations of semantic categories. Methods The spatio-temporal clusters of brain magnetic activities elicited by object pictures related to super-ordinate (flowers, animals, furniture, clothes) and base-level (e.g. tulip, rose, orchid, sunflower) categories were analysed in the source space for the time epochs 170–210 and 210–450 ms following stimulus onset and were compared between 10 schizophrenic patients and 10 control subjects. Results Spatio-temporal correlations of responses elicited by base-level concepts and the difference of within vs. across super-ordinate categories were distinctly lower in patients than in controls. Additionally, in contrast to the well-defined categorical representation in control subjects, unsupervised clustering indicated poorly defined representation of semantic categories in patients. Within the patient group, distinctiveness of categorical representation in the temporal cortex was positively related to negative symptoms and tended to be inversely related to positive symptoms. Conclusion Schizophrenic patients show a less organized representation of semantic categories in clusters of magnetic brain responses than healthy adults. This atypical neural network architecture may be a correlate of loosening of associations, promoting positive symptoms.