Rhythm perception depends on the ability to predict the onset of rhythmic events. Previous studies indicate beta band modulation is involved in predicting the onset of auditory rhythmic events (Fujioka et al., 2009, 2012; Snyder & Large, 2005). We sought to determine if similar processes are recruited for prediction of visual rhythms by investigating whether beta band activity plays a role in a modality‐dependent manner for rhythm perception. We looked at electroencephalography time–frequency neural correlates of prediction using an omission paradigm with auditory and visual rhythms. By using omissions, we can separate out predictive timing activity from stimulus‐driven activity. We hypothesized that there would be modality‐independent markers of rhythm prediction in induced beta band oscillatory activity, and our results support this hypothesis. We find induced and evoked predictive timing in both auditory and visual modalities. Additionally, we performed an exploratory‐independent components‐based spatial clustering analysis, and describe all resulting clusters. This analysis reveals that there may be overlapping networks of predictive beta activity based on common activation in the parietal and right frontal regions, auditory‐specific predictive beta in bilateral sensorimotor regions, and visually specific predictive beta in midline central, and bilateral temporal/parietal regions. This analysis also shows evoked predictive beta activity in the left sensorimotor region specific to auditory rhythms and implicates modality‐dependent networks for auditory and visual rhythm perception.
A body of research demonstrates convincingly a role for synchronization of auditory cortex to rhythmic structure in sounds including speech and music. Some studies hypothesize that an oscillator in auditory cortex could underlie important temporal processes such as segmentation and prediction. An important critique of these findings raises the plausible concern that what is measured is perhaps not an oscillator but is instead a sequence of evoked responses. The two distinct mechanisms could look very similar in the case of rhythmic input, but an oscillator might better provide the computational roles mentioned above (i.e., segmentation and prediction). We advance an approach to adjudicate between the two models: analyzing the phase lag between stimulus and neural signal across different stimulation rates. We ran numerical simulations of evoked and oscillatory computational models, showing that in the evoked case,phase lag is heavily rate-dependent, while the oscillatory model displays marked phase concentration across stimulation rates. Next, we compared these model predictions with magnetoencephalography data recorded while participants listened to music of varying note rates. Our results show that the phase concentration of the experimental data is more in line with the oscillatory model than with the evoked model. This finding supports an auditory cortical signal that (
- NSF-PAR ID:
- 10102531
- Publisher / Repository:
- Proceedings of the National Academy of Sciences
- Date Published:
- Journal Name:
- Proceedings of the National Academy of Sciences
- ISSN:
- 0027-8424
- Page Range / eLocation ID:
- Article No. 201816414
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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