EEG-based neural decoding of Intelligence Questions
Brain-Computer Interface(2015)
摘要
Decoding mental processes in single trials is one of the prerequisites for tailoring learning paradigms, which aim at improving performance in cognitive tasks. In this study user choices are predicted in a matrix reasoning task. By employing multivariate analysis techniques we are able to show that it is possible to decode the subjects' answers prior to their response by means of ERP-based EEG data. Our results indicate that parieto-occipital ERP components are most discriminative and lead to an average single-trial accuracy of 67.7 ± 6.3% across 5 subjects.
更多查看译文
关键词
cognition,electroencephalography,medical signal processing,neurophysiology,eeg-based neural decoding,erp-based eeg data,average single-trial accuracy,cognitive tasks,intelligence questions,learning paradigms,matrix reasoning task,mental process decoding,multivariate analysis techniques,parieto-occipital erp components,user choices,correlation,accuracy,electrodes,decoding
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络