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首页> 外文会议>Humaine Association Conference on Affective Computing and Intelligent Interaction >Development of a Binary fMRI-BCI for Alzheimer Patients: A Semantic Conditioning Paradigm Using Affective Unconditioned Stimuli
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Development of a Binary fMRI-BCI for Alzheimer Patients: A Semantic Conditioning Paradigm Using Affective Unconditioned Stimuli

机译：用于阿尔茨海默患者的二元FMRI-BCI的开发：使用情感无条件刺激的语义调理范例

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With the aim of developing a brain-computer interface for the communication of basic mental states, a classical conditioning paradigm with affective stimuli was used, assessing the possibility to discriminate between affirmative and negative thinking in an fMRI-BCI setting. 6 Alzheimer patients and 7 healthy control subjects participated to the study. Congruent and incongruent word-pairs were respectively associated to pleasant (baby laughter) and unpleasant (scream) affective stimuli. A Support Vector Machine classifier focusing on insula, amygdala and anterior cingulate cortex was used to discriminate between the activations relative to congruent and incongruent word-pairs (eliciting respectively affirmative and negative thinking), following the conditioning process. Classification accuracy was on average 71% for Alzheimer patients, reaching 85%, and on average 69% for control subjects, reaching 83%. This study shows that it is possible to extract information on individuals' mental states by exploiting affective responses, overcoming the typical obstacles of traditional BCIs, which generally require time-consuming trainings and intact cognition.
机译：凭借开发用于基本精神状态的通信的脑电电脑界面，使用具有情感刺激的古​​典调理范例，评估了在FMRI-BCI设置中判断肯定和消极思维之间的可能性。 6例阿尔茨海默患者和7名健康对照受试者参加了该研究。一致性和不一致的词对分别与令人愉快（婴儿笑声）和令人不快（尖叫）情感刺激相关联。在调节过程之后，使用聚焦在Inslua的支持向量机分类器，Amygdala和前铰接皮质，相对于一致性和不一致词对（分别肯定和消极思维）来区分激活。 Alzheimer患者的分类准确性平均为71％，达到85％，平均对照受试者平均为69％，达到83％。本研究表明，通过利用情感反应，可以提取对个人心理状态的信息，克服传统BCI的典型障碍，这通常需要耗时的培训和完整的认知。

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