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This study describes ME, a patient in the chronic stage after a traumatic brain injury. During an extensive training programme ME tried to regain automaticity in the retrieval of simple multiplication facts. He succeeded in substantially decreasing response latencies in multiplication, reducing the handicap at his job. This improvement generalised to a non-trained operand order, to non-trained problems, and to a non-trained output modality. Moreover, these effects were maintained over at least four months. Interestingly, however, ME's training effects were operation specific: No significant improvement occurred in addition, subtraction, or division. As coloured presentation of multiplication problems proved to be a valuable cue in facilitating the patient's performance, this might turn out to be a useful tool in the rehabilitation of fact retrieval in general
Fakten, Fakten, Fakten!
(2004)
How do children determine the syntactic category of novel words? In this article we present the results of 2 experiments that investigated whether German children between 12 and 16 months of age can use distributional knowledge that determiners precede nouns and subject pronouns precede verbs to syntactically categorize adjacent novel words. Evidence from the head-turn preference paradigm shows that, although 12- to 13-month-olds cannot do this, 14- to 16- month-olds are able to use a determiner to categorize a following novel word as a noun. In contrast, no categorization effect was found for a novel word following a subject pronoun. To understand this difference we analyzed adult child- directed speech. This analysis showed that there are in fact stronger co-occurrence relations between determiners and nouns than between subject pronouns and verbs. Thus, in German determiners may be more reliable Cues to the syntactic category of an adjacent novel word than are subject pronouns. We propose that the capacity to syntactically categorize novel words, demonstrated here for the first time in children this young, mediates between the recognition of the specific morphosyntactic frame in which a novel word appears and the word-to-world mapping that is needed to build up a semantic representation for the novel word
German accent revisited
(2004)
In most experiments using event-related brain potentials (ERPs), there is a straightforward way to define-on theoretical grounds-which of the conditions tested is the experimental condition and which is the control condition. It, however, theoretical assumptions do not give sufficient and unambiguous information to decide this question, then the interpretation of an ERP effect becomes difficult, especially if one takes into account that certain effects can be both a positivity or a negativity on the basis of the morphology of the pattern as well as with respect to peak latency (regard for example, N400 and P345). Exemplified with an ERP experiment on language processing, we present such a critical case and offer a possible solution on the basis of nonlinear data analysis. We show that a generalized polarity histogram, the word statistics of symbolic dynamics, is in principle able to distinguish negative going ERP components from positive ones when an appropriate encoding strategy, the half wave encoding is employed. We propose statistical criteria which allow to determine ERP components on purely methodological grounds
We describe a part of the stimulus sentences of a German language processing ERP experiment using a context- free grammar and represent different processing preferences by its unambiguous partitions. The processing is modeled by deterministic pushdown automata. Using a theorem proven by Moore, we map these automata onto discrete time dynamical systems acting at the unit square, where the processing preferences are represented by a control parameter. The actual states of the automata are rectangles lying in the unit square that can be interpreted as cylinder sets in the context of symbolic dynamics theory. We show that applying a wrong processing preference to a certain input string leads to an unwanted invariant set in the parsers dynamics. Then, syntactic reanalysis and repair can be modeled by a switching of the control parameter - in analogy to phase transitions observed in brain dynamics. We argue that ERP components are indicators of these bifurcations and propose an ERP-like measure of the parsing model