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Christopoulos, for their constructive comments along the journey, which have not only helped me to integrate Study 1-3 into a coherent thesis, but also allow for the entire thesis to be substantially improved. Many thanks go to my colleagues and friends who have assisted me with participant recruitment, data analysis, rationale establishment, and proof reading through pushing forward my studies. In particular, I am truly impressed by the great support and help that have been

In this abstract, we present a novel method using the deep convolutional neural network combined with traditional mechanical control techniques to solve the problem of determining whether a robotic grasp is successful or not. To finish the task, we construct a data acquisition platform capable of robot arm grasping and photo capturing, and collect a diversity of pictures by adjusting the shape and posture of the objects and controlling the robot arm to move randomly. For the purpose of validating the generalization capability, we adopt a stochastic sampling method based on cross validation to test our model. The experiment shows that, with an increasing number of shapes of objects involved in training, the network can identify new samples in a more accurate and steadier way. The accuracy rises from 89.2% when we use only one category of shape for training to above 99.7% when we use 17 categories for training.

Purpose: Everyday social communication emphasizes speech comprehension. To date, most neurobiological models regarding auditory semantic processing are based on alphabetic languages, where the character-based languages such as Chinese are largely underrepresented. Thus, the current study attempted to investigate the neural network of speech comprehension specifically for the Chinese language. Methods: Twenty-two native Mandarin Chinese speakers were imaged while performing a passive listening task of forward and backward sentences. Sentences were used as task stimuli, as sentences compared with words were more frequently utilized in daily speech comprehension. Results: Our results suggested that spoken Chinese sentence comprehension may involve a neural network comprising the left middle temporal gyrus, the left anterior temporal lobe, and the bilateral posterior superior temporal lobes. The occipitotemporal visual cortex was not found to be significantly involved with the sentence-level network of spoken Chinese comprehension, as bottom-up visualization process from homophones to visual forms may be less needed due to the availability of top-down contextual controls in sentence processing. In addition, no significant functional connectivity was observed, likely obscured by the low cognitive demand of the task conditions. Limitations and future directions were discussed. Conclusion: The current Chinese network seems to largely resemble the auditory semantic network for alphabetic languages but with features specific to Chinese. While the left inferior parietal lobule in the dorsal stream may have little involvement in the listening comprehension of Chinese sentences, the ventral neural stream via the temporal cortex appears to be more emphasized. The current findings deepen our understanding of how the semantic nature of spoken Chinese sentences influences the neural mechanism engaged.

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Semantic processing is the ultimate goal of language communication. Chinese characters and Japanese kanji both contain semantic clues in their semantic radicals, However, as Japanese is learned phonologically instead of morphologically nowadays, these clues may be more conducive to Chinese comprehension. It is therefore plausible that these inherent language differences could contribute to differential neural substrates but this has not been directly examined. To address this research gap, the current meta-analysis conducted direct contrasts between foci reported in published Chinese and Japanese fMRI studies to seek convergent activation across studies. It was found that Chinese evoked increased right hemispheric activation than Japanese, suggesting that semantic radicals might be more beneficial to Chinese than Japanese comprehension. The involvement of left supramarginal gyrus in spoken Japanese but not in spoken Chinese suggested that Japanese was processed more like alphabetic languages even though it is visually represented by characters. It might be further inferred that orthographic processing was essential for Chinese comprehension whereas phonological processing was more relevant for Japanese. The findings deepen our understanding of how linguistic characteristics shape our brains in processing semantics.