Data from: Nonlinear decoding models enable music reconstruction from human auditory cortex activity

<p>This dataset is associated with the manuscript &quot;Nonlinear decoding models enable music reconstruction from human auditory cortex activity&quot;, and provides all preprocessed files necessary to replicate&nbsp;the results.</p> <p>In this study, we recorded&nbsp;intracranial EEG data (specifically, ECoG) in 29 patients with pharmacoresistant epilepsy while they were passively listening to a Pink Floyd song.</p> <p>The present dataset consists of preprocessed neural activity (High-Frequency Activity, 70-150 Hz), electrode coordinates (in MNI template space) and auditory stimulus (raw wave file, and 32- and 128-frequency-bin auditory spectrogram). HFA and both auditory spectrograms have a sampling rate of 100 Hz, and are temporally aligned (duration of 190.72 s).</p> <p>The code we used to preprocess and analyze the data is hosted on GitHub, <a href="https://github.com/ludovicbellier/PF_HFAdecoding">here</a> for the manuscript and <a href="https://github.com/ludovicbellier/PF_HFAdecoding">there</a> for the predictive modeling functions.</p>