Word Processing differences between dyslexic and control children

BACKGROUND: The aim of this study was to investigate brain responses triggered by different wordclasses in dyslexic and control children. The majority of dyslexic children have difficulties to phonologically assemble a word from sublexical parts following grapheme-to-phoneme correspondences. Therefore, we hypothesised that dyslexic children should mainly differ from controls processing low frequent words that are unfamiliar to the reader. METHODS: We presented different wordclasses (high and low frequent words, pseudowords) in a rapid serial visual word (RSVP) design and performed wavelet analysis on the evoked activity. RESULTS: Dyslexic children had lower evoked power amplitudes and a higher spectral frequency for low frequent words compared to control children. No group differences were found for high frequent words and pseudowords. Control children had higher evoked power amplitudes and a lower spectral frequency for low frequent words compared to high frequent words and pseudowords. This pattern was not present in the dyslexic group. CONCLUSION: Dyslexic children differed from control children only in their brain responses to low frequent words while showing no modulated brain activity in response to the three word types. This might support the hypothesis that dyslexic children are selectively impaired reading words that require sublexical processing. However, the lacking differences between word types raise the question if dyslexic children were able to process the words presented in rapid serial fashion in an adequate way. Therefore the present results should only be interpreted as evidence for a specific sublexical processing deficit with caution

Advanced AI search techniques in modern digital circuit synthesis

Progress in microelectronic technology is extremely fast and it is outstripping the designers' abilities to make use of the created opportunities. Development and application of new more suitable design methods and tools is therefore very important for the modern system industry. This paper shows the importance of the AI search techniques for the circuits and systems design space exploration, explains what sorts of search techniques are useful for this aim, and discusses the place, role and way of use of these techniques in circuit and system design. In particular, the paper explains the importance and usage of the heuristic search techniques for the automatic construction and selection of the most promising solutions to the circuit synthesis problems. The discussion and conclusions of the paper are illustrated with examples of three effective and efficient search algorithms, and experimental results from their application to two important circuit synthesis problems. The knowledge presented in the paper combines numerous valuable concepts of modern system engineering and artificial intelligence, and forms a base for further research and application of the AI search techniques to design of complex circuits and systems