In studies of auditory perception, a dichotomy between envelope and temporal fine structure(TFS) has been emphasized. It has been shown that frequency-following responses(FFRs) in the rat inferior colliculus can be di...In studies of auditory perception, a dichotomy between envelope and temporal fine structure(TFS) has been emphasized. It has been shown that frequency-following responses(FFRs) in the rat inferior colliculus can be divided into the envelope component(FFREnv)and the temporal fine structure component(FFRTFS). However, the existing FFR models cannot successfully separate FFREnv and FFRTFS. This study was to develop a new FFR model to effectively distinguish FFREnv from FFRTFS by both combining the advantages of the two existing FFR models and simultaneously adding cellular properties of inferior colliculus neurons. To evaluate the validity of the present model, correlations between simulated FFRs and experimental data from the rat inferior colliculus were calculated. Different model parameters were tested, FFRs were calculated, and the parameters with highest prediction were chosen to establish an ideal FFR model. The results indicate that the new FFR model can provide reliable predictions for experimentally obtained FFREnv and FFRTFS.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.31470987)the National Basic Research Development Program of China(Grant No.2015CB351800)“985”grants from Peking University for Physiological Psychology and China Postdoctoral Science Foundation(Grant No.2016M601066)
文摘In studies of auditory perception, a dichotomy between envelope and temporal fine structure(TFS) has been emphasized. It has been shown that frequency-following responses(FFRs) in the rat inferior colliculus can be divided into the envelope component(FFREnv)and the temporal fine structure component(FFRTFS). However, the existing FFR models cannot successfully separate FFREnv and FFRTFS. This study was to develop a new FFR model to effectively distinguish FFREnv from FFRTFS by both combining the advantages of the two existing FFR models and simultaneously adding cellular properties of inferior colliculus neurons. To evaluate the validity of the present model, correlations between simulated FFRs and experimental data from the rat inferior colliculus were calculated. Different model parameters were tested, FFRs were calculated, and the parameters with highest prediction were chosen to establish an ideal FFR model. The results indicate that the new FFR model can provide reliable predictions for experimentally obtained FFREnv and FFRTFS.
