Mismatch Negativity (MMN) is an N-methyl-d-aspartic acid (NMDA)-mediated, negative deflection in human auditory evoked potentials in response to a cognitively discriminable change. MMN-like responses have been extensively investigated in animal models, but the existence of MMN equivalent is still controversial. In this study, we aimed to investigate how closely the putative MMN (MMNp) in rats exhibited the comparable properties of human MMN. We used a surface microelectrode array with a grid of 10×7 recording sites within an area of 4.5×3.0 mm to densely map evoked potentials in the auditory cortex of anesthetized rats under the oddball paradigm. Firstly, like human MMN, deviant stimuli elicited negative deflections in auditory evoked potentials following the positive middle-latency response, termed P1. Secondly, MMNp exhibited deviance-detecting property, which could not be explained by simple stimulus specific adaptation (SSA). Thirdly, this MMNp occurred focally in the auditory cortex, including both the core and belt regions, while P1 activation focus was obtained in the core region, indicating that both P1 and MMNp are generated in the auditory cortex, yet the sources of these signals do not completely overlap. Fourthly, MMNp significantly decreased after the application of AP5 (D-(-)-2-amino-5-phosphonopentanoic acid), an antagonist at NMDA receptors. In stark contrast, AP5 affected neither P1 amplitude nor SSA of P1. These results provide compelling evidence that the MMNp we have examined in rats is functionally comparable to human MMN. The present work will stimulate translational research into MMN, which may help bridge the gap between electroencephalography (EEG)/magnetoencephalography (MEG) studies in humans and electrophysiological studies in animals.

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Humans can rapidly detect regular patterns (i.e., within few cycles) without any special attention to the acoustic environment. This suggests that human sensory systems are equipped with a powerful mechanism for automatically predicting forthcoming stimuli to detect regularity. It has recently been hypothesized that the neural basis of sensory predictions exists for not only what happens (predictive coding) but also when a particular stimulus occurs (predictive timing). Here, we hypothesize that the phases of neural oscillations are critical in predictive timing, and these oscillations are modulated in a band-specific manner when acoustic patterns become predictable, i.e., regular. A high-density microelectrode array (10 × 10 within 4 × 4 mm2) was used to characterize spatial patterns of band-specific oscillations when a random-tone sequence was switched to a regular-tone sequence. Increasing the regularity of the tone sequence enhanced phase locking in a band-specific manner, notwithstanding the type of the 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, in contrast, increased with frequency separation with respect to the prior tone, suggesting that the evoked-response amplitude encodes sequence information on a local scale, i.e., the local order of tones. The phase locking modulation spread widely over the auditory cortex, while the amplitude modulation was confined around the activation foci. Thus, our data suggest that oscillatory phase plays a more important role than amplitude in the neuronal detection of tone sequence regularity, which is closely related to predictive timing. Furthermore, band-specific contributions may support recent theories that gamma oscillations encode bottom-up prediction errors, whereas beta oscillations are involved in top-down prediction.

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