Abstract& Cognitive models of word production correlate the word frequency effect (i.e., the fact that words which appear with less frequency take longer to produce) with an increased processing cost to activate the whole-word (lexical) phonological representation. We performed functional magnetic resonance imaging (fMRI) while subjects produced overt naming responses to photographs of animals and manipulable objects that had high name agreement but were of varying frequency, with the purpose of identifying neural structures participating specifically in activating whole-word phonological representations, as opposed to activating lexical semantic representations or articulatorymotor routines. Blood oxygen level-dependent responses were analyzed using a parametric approach based on the frequency with which each word produced appears in the language. Parallel analyses were performed for concept familiarity and word length, which provided indices of semantic and articulatory loads. These analyses permitted us to identify regions related to word frequency alone, and therefore, likely to be related specifically to activation of phonological word forms. We hypothesized that the increased processing cost of producing lower-frequency words would correlate with activation of the left posterior inferotemporal (IT) cortex, the left posterior superior temporal gyrus (pSTG), and the left inferior frontal gyrus (IFG). Scan-time response latencies demonstrated the expected word frequency effect. Analysis of the fMRI data revealed that activity in the pSTG was modulated by frequency but not word length or concept familiarity. In contrast, parts of IT and IFG demonstrated conjoint frequency and familiarity effects, and parts of both primary motor regions demonstrated conjoint effects of frequency and word length. The results are consistent with a model of word production in which lexical-semantic and lexical-phonological information are accessed by overlapping neural systems within posterior and anterior language-related cortices, with pSTG specifically involved in accessing lexical phonology. &

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. The CASE Network is a group of economic and social research centers in Poland, Kyrgyzstan, Ukraine, Georgia, Moldova, and Belarus. Organizations in the network regularly conduct joint research and advisory projects. The research covers a wide spectrum of economic and social issues, including economic effects of the European integration process, economic relations between the EU and CIS, monetary policy and euro-accession, innovation and competitiveness, and labour markets and social policy. The network aims to increase the range and quality of economic research and information available to policy-makers and civil society, and takes an active role in on-going debates on how to meet the economic challenges facing the EU, post-transition countries and the global economy. Terms of use: Documents inThe CASE network consists of: AcknowledgementsThis report is the result of a team effort and reflects the contributions of all those who have contributed to the country fiches, the country case studies as well as the interim and final reports, in particular:

No abstract

No abstract

Five computational models of lexical access during production are tested for their ability to account for the distribution of aphasic picture-naming errors. The naming profiles (N= 14) were chosen from the literature to represent patients who make a relatively large number of omission errors. The most successful models combined the damage assumptions of the semantic-phonological model of lexical access (Foygel & Dell, 2000) with a treatment of omission errors as largely independent from overt errors (Ruml, Caramazza, Shelton, &Chialant, 2000). An explanation for the occurrence of omission errors was provided by the addition of a lexical-threshold parameter (Laine, Tikkala, ocjuhola, 1998) to the model. Suggestions for further testing of these models are introduced, as is a new website that allows other researchers to make use of the models.

Theories of sentence production that involve a convergence of activation from conceptual-semantic and syntactic-sequential units inspired a connectionist model that was trained to produce simple sentences. The model used a learning algorithm that resulted in a sharing of responsibility (or "division of labor") between syntactic and semantic inputs for lexical activation according to their predictive power. Semantically rich, or "heavy", verbs in the model came to rely on semantic cues more than on syntactic cues, whereas semantically impoverished, or "light", verbs relied more on syntactic cues. When the syntactic and semantic inputs were lesioned, the model exhibited patterns of production characteristic of agrammatic and anomic aphasic patients, respectively. Anomic models tended to lose the ability to retrieve heavy verbs, whereas agrammatic models were more impaired in retrieving light verbs. These results obtained in both sentence production and single-word naming simulations. Moreover, simulated agrammatic lexical retrieval was more impaired overall in sentences than in single-word tasks, in agreement with the literature. The results provide a demonstration of the division-of-labor principle, as well as general support for the claim that connectionist learning principles can contribute to the understanding of non-transparent neuropsychological dissociations.

No abstract

No abstract