Listening to music typically induces a strong sense of an underlying beat. Although clearly related to periodicities contained in the stimulus, beat perception is internally generated since beat induction can occur in instances where no stimulation is present (i.e., in syncopated rhythms). Thus the capacity to extract a beat from periodic input provides an interesting phenomenon for examining the neural processes that temporally organise and ulitmately structure our perception of the world.
The neural mechanisms associated with beat-induction can be measured with a frequency tagging technique applied to EEG data recorded while participants listen to music. This approach involves examining the peaks in the frequency spectrum of EEG data that correspond to periodicities contained in the stimulus. By examining the activity evoked by syncopated rhythms (where the beat percept does not correspond to the sensory input), previous studies have shown that this technique indexes both periodic activity associated with the sensory input, and endogenous processes involved in extracting temporal structures from periodic input.
To further demonstrate the functional significance of this approach, Nozaradan, Peretz and Keller examined how neural entrainment measured with frequency tagging is correlated with individual differences in rhythmic motor control. The authors presented both unsyncopated and syncopated auditory rhythms whilst brain activity was recorded with EEG. Individual differences in ability to detect the beat in these rhythms were assessed offline with finger tapping tasks. In addition participants also completed another finger tapping task designed to assess temporal prediction. This stimulus comprised an aperiodic, predictable sequence of tones whereby the tempo continually varied between 400-600 ms (with a sinusoidal contour). This sequence was used to assess participants’ ability to anticipate the upcoming stimulus interval by quantifying the lag-1 and lag-0 correlation between the inter-stimulus interval and the inter-tap interval. Accurate prediction of the stimulus sequence would result in a larger lag-0 correlation than the lag-1 correlation, whereas tracking behaviour would be observed as a larger lag-1 correlation than lag-0 correlation.
The results showed that periodic stimulation produced peaks in the frequency spectrum of the recorded EEG data that corresponded to beat and non-beat frequencies. Importantly however, behavioural performance correlated selectively with the strength of entrainment in the beat frequencies. Tapping accuracy (mean asynchrony in the beat perception tasks) and the temporal prediction index (from the tempo change task) correlated positively with the height of the peaks for the beat induced frequencies, whereas the degree of entrainment in non-beat frequencies was negatively correlated with periodic tapping accuracy and was uncorrelated with prediction in tempo changing sequences. Together, these results highlight the functional significance of processes indexed by the frequency tagging approach, and show that beat perception is related to selective entrainment of neural activity to beat related frequencies.
The authors argue that the relationship between neural entrainment and temporal prediction is consistent with predictive coding models, whereby the brain optimises behaviour by forming internal models of the causes of sensory events. These internal models act as templates based on past experience that optimise sensory processing by providing predictions about the timing of upcoming sensory input. This argument is supported by another study published in 2016, which showed that temporal predictions associated with both periodic and aperiodic sequences lower sensory thresholds in a pitch discrimination task. Intriguingly, this study showed that isochronous stimulation also produced faster response times, whereas aperiodic stimulation did not. The authors of this paper argued that this dissociation may reflect the lowering of motor thresholds caused by simple sensory-motor coupling in the isochronous context, whereas changes in sensory processing may have been due to controlled processes that update internal models (i.e., linked to period correction). It remains to be seen whether the frequency tagging approach can be used to further dissociate the exogenous and endogenous processes involved in temporal prediction.
The MARCS Institute, Western Sydney University
