Stimulus Phase Locking of Cortical Oscillations for Rhythmic Tone Sequences in Rats - Noda, Takahiro; Amemiya, Tomoki; Shiramatsu, Tomoyo I.; Takahashi, Hirokazu (Frontiers in Neural Circuits, 2017)
Humans can detect regular patterns very rapidly (i.e., within a few cycles) without any special attention to the acoustic environment. This suggests that human sensory systems are equipped with a powerful mechanism for the automatic prediction of forthcoming stimuli in order to detect regularity. It has recently been hypothesized that the neural basis of sensory predictions exist not only for what happens (predictive coding), but also for when a particular stimulus occurs (predictive timing). We here hypothesized that the phase of neural oscillations is critical in predictive timing and that these oscillations are modulated in a band-specific manner when acoustic patterns become predictable, i.e., regular. A high-density microelectrode array (10 x 10 within 4 x 4 mm2) characterized spatial patterns of band-specific oscillations when a random tone sequence was switched to a regular tone sequence. Increasing the regularity of tone sequence enhanced the phase locking in a band-specific manner, irrespective of the type of regular sound pattern: gamma-band phase locking increased immediately after the transition from random to regular sequences, while beta-band phase locking gradually evolved with time after the transition. The amplitude of the tone-evoked response, on the other hand, increased with frequency separation with respect to the prior tone, suggesting that the evoked-response amplitude encodes the sequence information on a local scale, i.e., the local order of tones. In terms of a spatial pattern, the phase-locking modulation spread widely over the auditory cortex, while the amplitude modulation was locally confined around the activation foci. Thus, our data suggest that oscillatory phase, rather than amplitude, plays a more important role in neuronal detection of tone sequence regularity, which is closely related to predictive timing. Furthermore, their band-specific contributions may support the recent theories that the gamma oscillations encode bottom-up prediction error, whereas the beta oscillations are involved in top-down prediction.