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Brain areas underlying retrieval of nouns and verbs: Grammatical class and task demand effects
No full textNouns and verbs in the brain: Grammatical class and task specific effects as revealed by fMRI
No full textThe wide variety of techniques and tasks used to study the neural correlates of noun and verb processing has resulted in a body of inconsistent evidence. We performed a functional magnetic resonance imaging (fMRI) experiment to detect grammatical class effects that generalize across tasks. A total of 12 participants undertook a grammatical-class switching task (GCST), in which they were presented with a noun (or a verb) and were asked to retrieve the corresponding verb (or noun), and a classical picture naming task (PNT) widely used in the previous aphasiological and imaging literature. The GCST was explicitly
designed to ensure control over confounding variables, such as stimulus complexity or imageability. Conjunction analyses of the haemodynamic responses measured in the two tasks indicated a shared verb-related activation of a dorsal premotor and posterior parietal network, pointing to a strong relationship between verb representation and action-oriented (visuo-)spatial knowledge. On the other hand, no brain area was consistently associated with nouns in both tasks. Moreover, there were task-dependent
differences between noun and verb retrieval both at behavioural and at physiological level; the grammatical class that elicited the longest reaction times in both tasks (i.e., verbs in the PNT and nouns in the
GCST) triggered a greater activation of the left inferior frontal gyrus. Therefore, we suggest that this area reflects a general increase in task demand rather than verb processing per se
Naming an action, not an object nor a celebrity: a selective deficit in retrieving common and proper nouns
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Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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