Slow phase-locked endogenous modulations support selective attention to sound
Kachlicka, M.; Laffere, A.; Dick, F.; Tierney, A. T.
Show abstract
To make sense of complex soundscapes, listeners must select and attend to task-relevant streams while ignoring uninformative sounds. One possible neural mechanism underlying this process is alignment of endogenous oscillations with the temporal structure of the target sound stream. Such a mechanism has been suggested to mediate attentional modulation of neural phase-locking to the rhythms of attended sounds. However, such modulations are compatible with an alternate framework, where attention acts as a filter that enhances exogenously-driven neural auditory responses. Here we attempted to adjudicate between theoretical accounts by playing two tone steams varying across condition in tone duration and presentation rate; participants attended to one stream or listened passively. Attentional modulation of the evoked waveform was roughly sinusoidal and scaled with rate, while the passive response did not. This suggests that auditory attentional selection is carried out via phase-locking of slow endogenous neural rhythms.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Consonance perception in congenital amusia: behavioral and brain responses to harmonicity and beating cues 97%
- Implicit versus explicit timing - separate or shared mechanisms? 97%
- Beat-based and memory-based temporal expectations in rhythm: similar perceptual effects, different underlying mechanisms 97%
Similar papers in this journal
Similar papers in this journal
- Dimension-Selective Attention and Dimensional Salience Modulate Cortical Tracking of Acoustic Dimensions 99%
- Impoverished auditory cues limit engagement of brain networks controlling spatial selective attention 98%
- Sustained neural activity correlates with rapid perceptual learning of auditory patterns 97%
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.