Data from: Reconstructing the spectrotemporal modulations of real-life sounds from fMRI response patterns

Ethological views of brain functioning suggest that sound representations
and computations in the auditory neural system are optimized finely to
process and discriminate behaviorally relevant acoustic features and
sounds (e.g., spectrotemporal modulations in the songs of zebra finches).
Here, we show that modeling of neural sound representations in terms of
frequency-specific spectrotemporal modulations enables accurate and
specific reconstruction of real-life sounds from high-resolution
functional magnetic resonance imaging (fMRI) response patterns in the
human auditory cortex. Region-based analyses indicated that response
patterns in separate portions of the auditory cortex are informative of
distinctive sets of spectrotemporal modulations. Most relevantly, results
revealed that in early auditory regions, and progressively more in
surrounding regions, temporal modulations in a range relevant for speech
analysis (∼2–4 Hz) were reconstructed more faithfully than other temporal
modulations. In early auditory regions, this effect was
frequency-dependent and only present for lower frequencies (<∼2
kHz), whereas for higher frequencies, reconstruction accuracy was higher
for faster temporal modulations. Further analyses suggested that auditory
cortical processing optimized for the fine-grained discrimination of
speech and vocal sounds underlies this enhanced reconstruction accuracy.
In sum, the present study introduces an approach to embed models of neural
sound representations in the analysis of fMRI response patterns.
Furthermore, it reveals that, in the human brain, even general purpose and
fundamental neural processing mechanisms are shaped by the physical
features of real-world stimuli that are most relevant for behavior (i.e.,
speech, voice).