RESUMEN
OBJECTIVE: To examine if nonlinear feature extraction method yields appropriate results in complex brainstem response classification of three different consonant vowels diotically presented in normal Persian speaking adults. METHODS: Speech-evoked auditory brainstem responses were obtained in 27 normal hearing young adults by using G.tec EEG recording system. 170ms synthetic consonant-vowel stimuli /ba/, /da/, /ga/ were presented binaurally and the recurrence quantification analysis was performed on the responses. The recurrence time of second type was proposed as a suitable feature. ANOVA was also used for testing the significance of extracted feature. Post-comparison statistical method was used for showing which means are significantly different from each other. RESULTS: Dimension embedding and state space reconstruction were helpful for visualizing nonlinearity in auditory system. The proposed feature was successful in the objective classification of responses in window time 20.1-35.3ms, which belonged to formant transition period of stimuli. Also the p value behavior of recurrence time of second type feature as a discriminant feature was close to the nature of the response that includes transient and sustained parts. On the other hand, the /ba/ and /ga/ classification period was wider than the others. CONCLUSION: The extracted feature shown in this paper is helpful for the objective of distinguishing individuals with auditory processing disorders in the structurally similar voices. On the other hand, differing nonlinear feature is meaningful in a special region of response, equal to formant transition period, and this feature is related to the state space changes of brainstem response. It can be assumed that more information is within this region of signal and it is a sign of processing role of brainstem. The state changes of system are dependent on input stimuli, so the existence of top down feedback from cortex to brainstem forces the system to act differently.