Data from Sabesan et al., 2023

This dataset contains the ABR recordings and a subset of the IC recordings analyzed in Sabesan et al., 2023. ABR The matlab file ABR_Data contains a structure with 12 entries, one for each experimental animal. Each entry has the following fields: <em><strong>spl_Left_Zero_Attn, spl_Right_Zero_Attn: </strong></em> the sound level in dB SPL measured by the ER10B+ probe microphone for each frequency with zero attenuation <em><strong>avg_waveforms:</strong></em> the average ABR waveform for each frequency and intensity [samples x frequencies x attenuations x channels] <em><strong>attns, freqs_kHz:</strong></em> the attenuations and frequencies corresponding to the indices in avg_waveforms <em><strong>type:</strong></em> the hearing status of the animal <em><strong>animal_id:</strong></em> the unique identifier for the animal IC The matlab file IC_Data contains a structure with 12 entries, one for each experimental animal. Each entry has the following fields: <em><strong>trial_1, trial_2: </strong></em> the multi-unit activity recorded on 512 channels in response to 5 minutes of speech from the TIMIT database presented at 65 dB SPL [time bins x channels]; each element of the matrix indicates the spike count in one 1.3 ms bin (exactly 32 samples of the corresponding audio) <em><strong>type:</strong></em> the hearing status of the animal <em><strong>animal_id:</strong></em> the unique identifier for the animal Sound The matlab file Sound contains the speech that elicited the responses in IC_Data. The sampling rate is 24414.0625 <br> Frames The zip file Ex_Frames_Zip contains a small dataset that can be used to the test the code for DNN model training that is available at github.com/nicklesica/dnn <br>