Observation of cortical electrical activation during aphasic recovery with EEG approximate entropy / 中国康复医学杂志

ABSTRACT

Objective: ①To study whether changes of cortical electrical activations in two hemispheres correlated with speech tasks could be observed with approximate entropy analysis of EEG; ②To dynamically observe the correlation of speech improvements with cortical electrical activations in two hemispheres during speech treatment. Method: Changes of cortical electrical activations were observed with EEG in a conductive aphasic 7、9 and 30 weeks after stroke. EEG was recorded in 3 different conditions eyes closed, word repetition and non-word repetition. The EEG of a healthy man was recorded in 3 different conditions as control. Result: Compared with eye-closed condition, EEG approximate entropies(ApEn_s) of the healthy subject increased in T3, T5, C3, P3 and O1 for word and non-word repetition, and additional F7 and T6 for non-word repetition task. For the patient, ApEn of the first EEG increased in P3 for word repetition, and P4 for non-word repetition; ApEns of the second EEG increased in F3, F7, P3, C3, C4,T3, T5, O1, and decreased in F8, T4 and O2 in right hemisphere for word and non-word repetition; ApEns of the third EEG increased in T3, P3, F7, O1, O2 for word repetition,and T3, O2 for non-word repetition. The first aphasia assessment showed light impairment of semantic system and initial sound auditory identification and severely impairment of picture naming and word repetition. The semantic system and initial sound auditory identification improved significantly in the second assessment compared with the first; but the word repetition remained unchanged. The range of the activated regions in the left hemisphere decreased in the third EEG compared with the second EEG and the activated regions were less than the normal subject. Conclusion: The cortical electrical activities correlated with repetition tasks and the change of cortical electrical activities in different stages of language recovery could be observed with EEG nonlinear analysis.