Perception is characterized by a reciprocal exchange of predictions and prediction error signals between neural regions. However, the relationship between such sensory mismatch responses and hierarchical predictive processing has not yet been demonstrated at the neuronal level in the auditory pathway. We recorded single-neuron activity from different auditory centers in anaesthetized rats and awake mice while animals were played a sequence of sounds, designed to separate the responses due to prediction error from those due to adaptation effects. Here we report that prediction error is organized hierarchically along the central auditory pathway. These prediction error signals are detectable in subcortical regions and increase as the signals move towards auditory cortex, which in turn demonstrates a large-scale mismatch potential. Finally, the predictive activity of single auditory neurons underlies automatic deviance detection at subcortical levels of processing. These results demonstrate that prediction error is a fundamental component of singly auditory neuron responses.

To identify sounds as novel, there must be some neural representation of commonly occurring sounds. Stimulus-specific adaptation (SSA) is a reduction in neural response to a repeated sound. Previous studies using an oddball stimulus paradigm have shown that SSA occurs at the cortex, but this study demonstrates that neurons in the inferior colliculus (IC) also show strong SSA using this paradigm. The majority (66%) of IC neurons showed some degree of SSA. Approximately 18% of neurons showed near-complete SSA. Neurons with SSA were found throughout the IC. Responses of IC neurons were reduced mainly during the onset component of the response, and latency was shorter in response to the oddball stimulus than to the standard. Neurons with near-complete SSA were broadly tuned to frequency, suggesting a high degree of convergence. Thus, some of the mechanisms that may underlie novelty detection and behavioral habituation to common sounds are already well developed at the midbrain.

The specific adaptation of neuronal responses to a repeated stimulus (Stimulus-specific adaptation, SSA), which does not fully generalize to other stimuli, provides a mechanism for emphasizing rare and potentially interesting sensory events. Previous studies have demonstrated that neurons in the auditory cortex and inferior colliculus show SSA. However, the contribution of the medial geniculate body (MGB) and its main subdivisions to SSA and detection of rare sounds remains poorly characterized. We recorded from single neurons in the MGB of anaesthetized rats while presenting a sequence composed of a rare tone presented in the context of a common tone (oddball sequences). We demonstrate that a significant percentage of neurons in MGB adapt in a stimulus-specific manner. Neurons in the medial and dorsal subdivisions showed the strongest SSA, linking this property to the non-lemniscal pathway. Some neurons in the non-lemniscal regions showed strong SSA even under extreme testing conditions (e.g., a frequency interval of 0.14 octaves combined with a stimulus onset asynchrony of 2000 ms). Some of these neurons were able to discriminate between two very close frequencies (frequency interval of 0.057 octaves), revealing evidence of hyperacuity in neurons at a subcortical level. Thus, SSA is expressed strongly in the rat auditory thalamus and contribute significantly to auditory change detection.

In this review, we attempt to integrate the empirical evidence regarding stimulus-specific adaptation (SSA) and mismatch negativity (MMN) under a predictive coding perspective (also known as Bayesian or hierarchical-inference model). We propose a renewed methodology for SSA study, which enables a further decomposition of deviance detection into repetition suppression and prediction error, thanks to the use of two controls previously introduced in MMN research: the many-standards and the cascade sequences. Focusing on data obtained with cellular recordings, we explain how deviance detection and prediction error are generated throughout hierarchical levels of processing, following two vectors of increasing computational complexity and abstraction along the auditory neuraxis: from subcortical toward cortical stations and from lemniscal toward nonlemniscal divisions. Then, we delve into the particular characteristics and contributions of subcortical and cortical structures to this generative mechanism of hierarchical inference, analyzing what is known about the role of neuromodulation and local microcircuitry in the emergence of mismatch signals. Finally, we describe how SSA and MMN are occurring at similar time frame and cortical locations, and both are affected by the manipulation of N-methyl-D-aspartate receptors. We conclude that there is enough empirical evidence to consider SSA and MMN, respectively, as the microscopic and macroscopic manifestations of the same physiological mechanism of deviance detection in the auditory cortex. Hence, the development of a common theoretical framework for SSA and MMN is all the more recommendable for future studies. In this regard, we suggest a shared nomenclature based on the predictive coding interpretation of deviance detection.