This program was written to estimate the peak sensitivity and bandwidth from behavioral amplitude modulation detection data. The data is fitted to a lowpass butterworth filter as done in Zeng (1999). Several studies on TMTF have performed statistical treatment on the raw modulation detection thresholds and ignore the important parameters such as peak sensitivity and bandwidth. This is often not being done in most studies due to the lack of tools for doing this and the amount of time to taken for performing the analysis one by one. With this small routine hearing researchers and audiologists will be able to do advanced analysis of their modulation detection data without any working knowledge of Matlab.
The data should be in csv format. The first row should contain the headers. The first column should contain the modulation frequencies and modulation detection thresholds per person should be separate columns. The regression equation used here is m = a+20*log10(1+(mf/b)^2 Where m is the modulation depth (modulation detection thresholds), a is the peak sensitivity, ms is the modulation frequency and b is the bandwidth with 3dB cutoff frequency.
Nike (2019). Temporal Modulation Transfer Function Regression Fit (https://www.mathworks.com/matlabcentral/fileexchange/58747-temporal-modulation-transfer-function-regression-fit), MATLAB Central File Exchange. Retrieved .
The last file was for a single subject data.
This one is for multiple subjects and is well documented