3P2-P05 自閉症スペクトラム障害における部分的情報処理バイアスの計算論的モデル(脳・神経・認知ロボティクス)

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  • 3P2-P05 A Computational Model for Local Processing Bias in Autism Spectrum Disorders(Neurorobotics & Cognitive Robotics)

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It is known that people with Autism Spectrum Disorders (ASD) have a bias for local information processing, whereas normally developing people exhibit a global bias. This study examines its underlying mechanism inspired by an evidence from neuroscience studies. Our hypothesis is that an imbalance between excitation and inhibition neurons modifies a threshold for neural activities and thus changes a bias for local or global information. We employed a hierarchical neural network called neocognitron to examine the influence of the excitation/inhibition balance on the recognition of hierarchical compound letters (i.e., a global/large letter consisting of local/small letters). Our experiments demonstrated that hyper inhibitory connections made the network recognize a local letter better than a global letter, whereas a proper excitation/inhibition balance produced an opposite result. This empirically supports our hypothesis that the excitation/inhibition imbalance is a cause of a local processing bias in ASD.

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