Publications

Doelling, K.B., & Poeppel, D. (2015) Cortical entrainment to music and its modulation by expertise. Proceedings of the National Academy of Sciences, 112 (45), E6233-E6242. 

In this study, we extend our previous work on speech to music. We show that, in both nonmusicians and musicians, low frequency brain rhythms synchronize with the note rate in classical piano pieces. We chose pieces by Bach, Brahms and Beethoven with a wide range of tempi (from 0.5 to 8 note per second (nps)) and played them to both nonmusicians and musicians. Both groups were able to synchronize to the musical rhythm for pieces above 1 nps (though the brains of musicians synchronized better). This synchronization helped to improve behavior on a pitch perception task. Below 1 nps, nonmusicians were unable to synchronize. Instead, the brain responds separately to each individual note, suggesting they may not have been able to group them into a whole melody.

The figure to the right shows the brain response for an example musician and non-musician for a piece at 0.7 nps (Beethoven Sonato no. 23). In the musician's example  you can see the peaks in brain response (overlayed in red; peaks marked with blue line above) line up nicely with the onsets of notes (shown in black). The brain response begins before the note has even begun suggesting an active synchronization and prediction of the note onsets.  The non-musician shows more of a passive response profile. The response begins only after each note starts suggesting that no prediction is occurring. Interestingly the nonmusician shows a second peak which occurs just after the first and well before the next note. This may reflect how they struggle with the slow speed. It is almost as if they attempt to predict the next note but can't wait long enough. Because they peak too soon, they are unable to synchronize with very slow musical pieces. 

see here for stimuli

Doelling, K.B., Arnal, L.H., Ghitza, O. & Poeppel, D. (2014) Acoustic landmarks drive delta-theta oscillations to enable speech comprehension by facilitating perceptual parsing. NeuroImage 85, 761-768.

This MEG experiment uses fairly complex acoustic filtering to provide evidence that neural oscillations in auditory cortex track amplitude fluctuations in the speech envelope at the syllabic rate in order to parse the stimulus into syllables that can be decoded. The figure to the right shows the type of data we deal with. A is exemplar data of a speech envelope and the MEG recording while a subject is listening. B shows the time frequency analysis of each. The amount of coherence between these two signals peaks at the syllabic rate of the stimulus and C shows the topography is quite similar to basic auditory M100 response to a single tone.

Arnal, L.H., Doelling, K.B., & Poeppel, D. (2015) Delta-Beta coupled oscillations underlie temporal prediction accuracy. Cerebral Cortex, 25 (9), 3077-3085.

Here we used MEG to show that temporal predictions are mediated through interactions between delta (1-3 Hz) and beta (~18-22 Hz) oscillations. We used a temporal delay task in which participants heard 3 or 4 isochronous tones and a final tone that was either delayed or not with respect to the expected timing. Participants ability to detect was modulated by the interaction between these oscillations just prior to the onset of the final tone. The Figure shown here demonstrates the key findings that delta phase and beta power show different profiles allowing for a prediction of subject's accuracy prior to the final tone.

Presentations

Doelling, K.B. & Poeppel, D. (2014). Using music to investigate the nature of neural oscillations in auditory cortex. Cognitive Neuroscience Society: Annual Meeting 2014, Boston, Ma.
Doelling, K.B. & Poeppel, D. (2013). Neural oscillations in auditory cortex and the phase tracking of music. Society for Neuroscience: Annual Meeting 2013, San Diego, CA.
    Received a Hot Topic Award
Doelling, K.B., Arnal, L., Ghitza, O., & Poeppel, D. (2012). The role of slow oscillations in parsing speech into syllables for decoding. Society for Neuroscience: Annual Meeting 2012, New Orleans, LA.