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The mismatch negativity (MMN) is an event-related potential component that reflects pre-attentive change detection in the brain. As an electrophysiological index of processing that responds to differences in incoming consecutive stimuli, the MMN can be elicited through, for example, the presentation of two different categories of sounds in an oddball paradigm where sounds from the "standard" category occur frequently and sounds from the "deviant" category occur rarely. The specificity of what can elicit the MMN is yet to be fully defined. Here we test whether the MMN can be generated by an abstract linguistic contrast with no reliable acoustic cue. Previous studies have shown that the way in which an acoustic cue is used to elicit MMN is influenced by linguistic knowledge, but have not shown that a nonacoustic, abstract linguistic contrast can itself elicit MMN. In this study, we test the strongest interpretation of the claim that the MMN can be generated through a purely linguistic contrast by contrasting tenses in ablauting irregular English verbs (where there is no reliable acoustic cue for tense). We find that this contrast elicits a negativity, as do other linguistic contrasts previously shown to elicit MMN (a contrast between phonologically voiced and phonologically voiceless segments and a purely acoustic contrast between aspirated and unaspirated segments). The findings provide evidence that the MMN is indeed sensitive to purely abstract linguistic categories.

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Sound localization in the front-back dimension is reported to be challenging, with individual differences. We investigated whether auditory discrimination processing in the brain differs based on front-back sound localization ability. This study conducted an auditory oddball task using speakers in front of and behind the participants. We used event-related brain potentials to examine the deviance detection process between groups that could and could not discriminate front-back sound localization. The results indicated that mismatch negativity (MMN) occurred during the deviance detection process, and P2 amplitude differed between standard and deviant locations in both groups. However, the latency of MMN was shorter in the group that could discriminate front-back sounds than in the group that could not. Additionally, N1 amplitude increased for deviant locations compared to standard ones only in the discriminating group. In conclusion, the sensory memories matching process based on traces of previously presented stimuli (MMN, P2) occurred regardless of discrimination ability. However, the response to changes in the physical properties of sounds (MMN latency, N1 amplitude) differed depending on the ability to discriminate front-back sounds. Our findings suggest that the brain may have different processing strategies for the two directions even without subjective recognition of the front-back direction of incoming sounds.

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It is not clear whether the brain can detect changes in native and non-native speech sounds in both unattended and attended conditions, but this information would be important to understand the nature of potential native language advantage in speech perception. We recorded event-related potentials (ERPs) for changes in duration and in Chinese lexical tone in a repeated vowel /a/ in native speakers of Finnish and Chinese in passive and active listening conditions. ERP amplitudes reflecting deviance detection (mismatch negativity; MMN and N2b) and attentional shifts towards changes in speech sounds (P3a and P3b) were investigated. In the passive listening condition, duration changes elicited increased amplitude in the MMN latency window for both standard and deviant sounds in the Finnish speakers compared to the Chinese speakers, but no group differences were observed for P3a. In passive listening to lexical tones, P3a was increased in amplitude for both standard and deviant stimuli in Chinese speakers compared to Finnish speakers, but the groups did not differ in MMN. In active listening, both tone and duration changes elicited N2b and P3b, but the groups differed only in pattern of results for the deviant type. The results thus suggest an overall increased sensitivity to native speech sounds, especially in passive listening, while the mechanisms of change detection and attentional shifting seem to work well for both native and non-native speech sounds in the attentive mode.

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The reactions to novelty manifesting in mismatch negativity in the rat brain were studied. During dissociative anesthesia, mismatch negativity-like waves were recorded from the somatosensory cortex using an epidural 32-electrode array. Experimental animals: 7 wild-type Wistar rats and 3 transgenic rats. During high-dose anesthesia, deviant 1,500 Hz tones were presented randomly among many standard 1,000 Hz tones in the oddball paradigm. "Deviant minus standard_before_deviant" difference waves were calculated using both the classical method of Naatanen and method of cross-correlation of sub-averages. Both methods gave consistent results: an early phasic component of the N40 and later N100 to 200 (mismatch negativity itself) tonic component. The gamma and delta rhythms power and the frequency of down-states (suppressed activity periods) were assessed. In all rats, the amplitude of tonic component grew with increasing sedation depth. At the same time, a decrease in gamma power with a simultaneous increase in delta power and the frequency of down-states. The earlier phasic frontocentral component is associated with deviance detection, while the later tonic one over the auditory cortex reflects the orienting reaction. Under anesthesia, this slow mismatch negativity-like wave most likely reflects the tendency of the system to respond to any influences with delta waves, K-complexes and down-states, or produce them spontaneously.

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According to the predictive processing framework, perception emerges from the reciprocal exchange of predictions and prediction errors (PEs) between hierarchically organized neural circuits. The nonlemniscal division of the inferior colliculus (IC) is the earliest source of auditory PE signals, but their neuronal generators, properties, and functional relevance have remained mostly undefined. We recorded single-unit mismatch responses to auditory oddball stimulation at different intensities, together with activity evoked by two sequences of alternating tones to control frequency-specific effects. Our results reveal a differential treatment of the unpredictable "many-standards" control and the predictable "cascade" control by lemniscal and nonlemniscal IC neurons that is not present in the auditory thalamus or cortex. Furthermore, we found that frequency response areas of nonlemniscal IC neurons reflect their role in subcortical predictive processing, distinguishing three hierarchical levels: (1) nonlemniscal neurons with sharply tuned receptive fields exhibit mild repetition suppression without signaling PEs, thereby constituting the input level of the local predictive processing circuitry. (2) Neurons with broadly tuned receptive fields form the main, "spectral" PE signaling system, which provides dynamic gain compensation to near-threshold unexpected sounds. This early enhancement of saliency reliant on spectral features was not observed in the auditory thalamus or cortex. (3) Untuned neurons form an accessory, "nonspectral" PE signaling system, which reports all surprising auditory deviances in a robust and consistent manner, resembling nonlemniscal neurons in the auditory cortex. These nonlemniscal IC neurons show unstructured and unstable receptive fields that could result from inhibitory input controlled by corticofugal projections conveying top-down predictions.

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Predictive processing theories conceptualize neocortical feedback as conveying expectations and contextual attention signals derived from internal cortical models, playing an essential role in the perception and interpretation of sensory information. However, few predictive processing frameworks outline concrete mechanistic roles for the corticothalamic (CT) feedback from layer 6 (L6), despite the fact that the number of CT axons is an order of magnitude greater than that of feedforward thalamocortical (TC) axons. Here we review the functional architecture of CT circuits and propose a mechanism through which L6 could regulate thalamic firing modes (burst, tonic) to detect unexpected inputs. Using simulations in a model of a TC cell, we show how the CT feedback could support prediction-based input discrimination in TC cells by promoting burst firing. This type of CT control can enable the thalamic circuit to implement spatial and context selective attention mechanisms. The proposed mechanism generates specific experimentally testable hypotheses. We suggest that the L6 CT feedback allows the thalamus to detect deviance from predictions of internal cortical models, thereby supporting contextual attention and routing operations, a far more powerful role than traditionally assumed.

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A fundamental property of sensory systems is their ability to detect novel stimuli in the ambient environment. The auditory brain contains neurons that decrease their response to repetitive sounds but increase their firing rate to novel or deviant stimuli; the difference between both responses is known as stimulus-specific adaptation or neuronal mismatch (nMM). Here, we tested the effect of microiontophoretic applications of ACh on the neuronal responses in the auditory cortex (AC) of anesthetized rats during an auditory oddball paradigm, including cascade controls. Results indicate that ACh modulates the nMM, affecting prediction error responses but not repetition suppression, and this effect is manifested predominantly in infragranular cortical layers. The differential effect of ACh on responses to standards, relative to deviants (in terms of averages and variances), was consistent with the representational sharpening that accompanies an increase in the precision of prediction errors. These findings suggest that ACh plays an important role in modulating prediction error signaling in the AC and gating the access of these signals to higher cognitive levels.

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Afferent inputs from the cochlea transmit auditory information to the central nervous system, where information is processed and passed up the hierarchy, ending in the auditory cortex. Through these brain pathways, spectral and temporal features of sounds are processed and sent to the cortex for perception. There are also many mechanisms in place for modulation of these inputs, with a major source of modulation being based in the medial prefrontal cortex (mPFC). Neurons of the rodent mPFC receive input from the auditory cortex and other regions such as thalamus, hippocampus and basal forebrain, allowing them to encode high-order information about sounds such as context, predictability and valence. The mPFC then exerts control over auditory perception via top-down modulation of the central auditory pathway, altering perception of and responses to sounds. The result is a higher-order control of auditory processing that produces such characteristics as deviance detection, attention, avoidance and fear conditioning. This review summarises connections between mPFC and the primary auditory pathway, responses of mPFC neurons to auditory stimuli, how mPFC outputs shape the perception of sounds, and how changes to these systems during hearing loss and tinnitus may contribute to these conditions.

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Detection of deviant stimuli is crucial to orient and adapt our behavior. Previous work shows that deviant stimuli elicit phasic activation of the locus coeruleus (LC), which releases noradrenaline and controls central arousal. However, it is unclear whether the detection of behaviorally relevant deviant stimuli selectively triggers LC responses or other neuromodulatory systems (dopamine, serotonin, and acetylcholine). We combine human functional MRI (fMRI) recordings optimized for brainstem imaging with pupillometry to perform a mapping of deviant-related responses in subcortical structures. Participants have to detect deviant items in a "local-global" paradigm that distinguishes between deviance based on the stimulus probability and the sequence structure. fMRI responses to deviant stimuli are distributed in many cortical areas. Both types of deviance elicit responses in the pupil, LC, and other neuromodulatory systems. Our results reveal that the detection of task-relevant deviant items recruits the same multiple subcortical systems across computationally different types of deviance.

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Una propiedad fundamental de los sistemas sensoriales es su capacidad para detectar estímulos novedosos en el entorno. El sistema nervioso posee neuronas que disminuyen su respuesta a los estímulos sonoros que se repiten a lo largo del tiempo y otras neuronas que aumentan su frecuencia de disparo ante estímulos novedosos, siendo la diferencia entre ambas respuestas conocida como adaptación-específica a estímulos. En las últimas décadas, se ha propuesto que el cerebro establece, continuamente, predicciones de los estímulos novedosos y del entorno basándose en sus experiencias previas y en modelos de representación internos, teoría denominada codificación predictiva. En esta revisión, abordaremos algunos conceptos de la adaptación-específica a estímulos y codificación predictiva, centrándonos principalmente en el sistema auditivo. Por último, propondremos una explicación teórica basada en el marco de la codificación predictiva para algunas disfunciones neuropsiquiátricas, auditivas y vestibulares.

A fundamental property of sensory systems is their ability to detect novel stimuli in the environment. The nervous system possesses neurons that decrease their response to sound stimuli that are repeated over time and other neurons that increase their firing rate to novel stimuli, the difference between the two responses being known as stimulus-specific adaptation. In recent decades, it has been proposed that the brain continuously makes predictions of novel stimuli and the environment based on its previous experiences and internal representational models, a theory called predictive coding. In this review, we will address some concepts of stimulus-specific adaptation and predictive coding, focusing mainly on the auditory system. Finally, we will propose a theoretical explanation based on the predictive coding framework for some neuropsychiatric, auditory, and vestibular dysfunctions.

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Various aspects of cortical face processing have been studied by assessing event related potentials (ERP). It has been described in the literature that mismatch negativity (MMN), a well-studied ERP, is not only modulated by sensory features but also emotional valence. However, the exact impact of emotion on the temporo-spatial profile of visual MMN during face processing remains inconsistent. By employing a sequential oddball paradigm using both neutral and emotional deviants, we were able to differentiate two distinct vMMN subcomponents. While an early subcomponent at 150-250 ms is elicited by emotional salient facial stimuli, the later subcomponent at 250-400 ms seems to reflect the detection of regularity violations in facial recognition per se, unaffected by emotional salience. Our results suggest that emotional valence is encoded in vMMN signal strength at an early stage of facial processing. Furthermore, we assume that of facial processing consists of temporo-spatially distinct, partially overlapping levels concerning different facial aspects.

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More experience results in better performance, usually. In most tasks, the more chances to learn we have, the better we are at it. This does not always appear to be the case in time perception however. In the current article, we use three different methods to investigate the role of the number of standard example durations presented on performance on three timing tasks: rhythm continuation, deviance detection, and final stimulus duration judgement. In Experiments 1a and 1b, rhythms were produced with the same accuracy whether one, two, three, or four examples of the critical duration were presented. In Experiment 2, participants were required to judge which of four stimuli had a different duration from the other three. This judgement did not depend on which of the four stimuli was the deviant one. In Experiments 3a and 3b, participants were just as accurate at judging the duration of a final stimulus in comparison to the prior stimuli regardless of the number of standards presented prior to the final stimulus. In summary, we never found any systematic effect of the number of standards presented on performance on any of the three timing tasks. In the discussion, we briefly relate these findings to three theories of time perception.

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The mismatch negativity (MMN) component of the human event-related potential (ERP) is frequently interpreted as a sensory prediction-error signal. However, there is ambiguity concerning the neurophysiology underlying hypothetical prediction and prediction-error signalling components, and whether these can be dissociated from overlapping obligatory components of the ERP that are sensitive to physical properties of sounds. In the present study, a hierarchical recurrent neural network (RNN) was fitted to ERP data from 38 subjects. After training the model to reproduce ERP waveforms evoked by 80 dB standard and 70 dB deviant stimuli, it was used to simulate a response to 90 dB deviant stimuli. Internal states of the RNN effectively combined to generate synthetic ERPs, where individual hidden units are loosely analogous to population-level sources. Model behaviour was characterised using principal component analysis of stimulus condition, layer, and individual unit responses. Hidden units were categorised according to their temporal response fields, and statistically significant differences among stimulus conditions were observed for amplitudes of units peaking in the 0-75 ms (P50), 75-125 ms (N1), and 250-400 ms (N3) latency ranges, surprisingly not including the measurement window of MMN. The model demonstrated opposite polarity changes in MMN amplitude produced by falling (70 dB) and rising (90 dB) intensity deviant stimuli, consistent with loudness dependence of sensory ERP components. This modelling study suggests that loudness dependence is a principal driver of intensity MMN, and future studies ought to clarify the distinction between loudness dependence, adaptation and prediction-error signalling.

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Electrophysiological sensory deviance detection signals, such as the mismatch negativity (MMN), have been interpreted from the predictive coding framework as manifestations of prediction error (PE). From a frequentist perspective of the classic oddball paradigm, deviant stimuli are unexpected because of their low probability. However, the amount of PE elicited by a stimulus can be dissociated from its probability of occurrence: when the observer cannot make confident predictions, any event holds little surprise value, no matter how improbable. Here we tested the hypothesis that the magnitude of the neural response elicited to an improbable sound (D) would scale with the precision of the prediction derived from the repetition of another sound (S), by manipulating repetition stability. We recorded the Electroencephalogram (EEG) from 20 participants while passively listening to 4 types of isochronous pure tone sequences differing in the probability of the S tone (880 Hz) while holding constant the probability of the D tone [1,046 Hz; p(D) = 1/11]: Oddball [p(S) = 10/11]; High confidence (7/11); Low confidence (4/11); and Random (1/11). Tones of 9 different frequencies were equiprobably presented as fillers [p(S) + p(D) + p(F) = 1]. Using a mass-univariate non-parametric, cluster-based correlation analysis controlling for multiple comparisons, we found that the amplitude of the deviant-elicited ERP became more negative with increasing S probability, in a time-electrode window consistent with the MMN (ca. 120-200 ms; frontal), suggesting that the strength of a PE elicited to an improbable event indeed increases with the precision of the predictive model.

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Mismatch negativity (MMN) is a candidate biomarker for neuropsychiatric disease. Understanding the extent to which it reflects cognitive deviance-detection or purely sensory processes will assist practitioners in making informed clinical interpretations. This study compares the utility of deviance-detection and sensory-processing theories for describing MMN-like auditory responses of a common marmoset monkey during roving oddball stimulation. The following exploratory analyses were performed on an existing dataset: responses during the transition and repetition sequence of the roving oddball paradigm (standard -> deviant/S1 -> S2 -> S3) were compared; long-latency potentials evoked by deviant stimuli were examined using a double-epoch waveform subtraction; effects of increasing stimulus repetitions on standard and deviant responses were analyzed; and transitions between standard and deviant stimuli were divided into ascending and descending frequency changes to explore contributions of frequency-sensitivity. An enlarged auditory response to deviant stimuli was observed. This decreased exponentially with stimulus repetition, characteristic of sensory gating. A slow positive deflection was viewed over approximately 300-800 ms after the deviant stimulus, which is more difficult to ascribe to afferent sensory mechanisms. When split into ascending and descending frequency transitions, the resulting difference waveforms were disproportionally influenced by descending frequency deviant stimuli. This asymmetry is inconsistent with the general deviance-detection theory of MMN. These findings tentatively suggest that MMN-like responses from common marmosets are predominantly influenced by rapid sensory adaptation and frequency preference of the auditory cortex, while deviance-detection may play a role in long-latency activity.

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When the brain tries to acquire an elaborate model of the world, multisensory integration should contribute to building predictions based on the various pieces of information, and deviance detection should repeatedly update these predictions by detecting "errors" from the actual sensory inputs. Accumulating evidence such as a hierarchical organization of the deviance-detection system indicates that the deviance-detection system can be interpreted in the predictive coding framework. Herein, we targeted mismatch negativity (MMN) as a type of prediction-error signal and investigated the relationship between multisensory integration and MMN. In particular, we studied whether and how cross-modal information processing affected MMN in rodents. We designed a new surface microelectrode array and simultaneously recorded visual and auditory evoked potentials from the visual and auditory cortices of rats under anesthesia. Then, we mapped MMNs for five types of deviant stimuli: single-modal deviants in (i) the visual oddball and (ii) auditory oddball paradigms, eliciting single-modal MMN; (iii) congruent audio-visual deviants, (iv) incongruent visual deviants, and (v) incongruent auditory deviants in the audio-visual oddball paradigm, eliciting cross-modal MMN. First, we demonstrated that visual MMN exhibited deviance detection properties and that the first-generation focus of visual MMN was localized in the visual cortex, as previously reported in human studies. Second, a comparison of MMN amplitudes revealed a non-linear relationship between single-modal and cross-modal MMNs. Moreover, congruent audio-visual MMN exhibited characteristics of both visual and auditory MMNs-its latency was similar to that of auditory MMN, whereas local blockage of N-methyl-D-aspartic acid receptors in the visual cortex diminished it as well as visual MMN. These results indicate that cross-modal information processing affects MMN without involving strong top-down effects, such as those of prior knowledge and attention. The present study is the first electrophysiological evidence of cross-modal MMN in animal models, and future studies on the neural mechanisms combining multisensory integration and deviance detection are expected to provide electrophysiological evidence to confirm the links between MMN and predictive coding theory.

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Mismatch negativity (MMN) elicited by decrements in sound pressure level has been asserted as evidence for its dependence upon general deviance detection, while refuting the proposition that it is simply caused by modulating the intrinsic sensory response with different physical properties of sound. However, reports of intensity-decrement MMN are sparse compared with MMN to stimulus frequency or duration changes, and verifying the mechanisms that shape difference waveform morphology is essential for their responsible use as clinical biomarkers. In the present study, open-access EEG data from 40 healthy young adults recorded during an intensity-decrement oddball paradigm was analyzed to establish the effects of transitions between different level stimuli on the auditory evoked response. Standard stimuli were 80 dB and deviant stimuli were 70 dB. Event-related potentials were extracted from standards after standards (sS), deviants after standards (sD), and standards after deviants (dS). Mean amplitude across a recommended measurement window for MMN (125 to 225 ms) was calculated for each ERP waveform. This revealed statistically significant negative amplitude shift elicited by lower-intensity deviant stimuli, as expected, and an opposite direction, positive amplitude shift elicited by higher-intensity standard stimuli that followed lower-intensity deviants, relative to standard stimuli presented consecutively. These findings indicate that intensity-modulation of the auditory response influences cortical activity measured during the latency range of MMN. To what extent the hypothesized deviance detection mechanisms may also contribute is uncertain and remains to be elucidated.

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Mismatch brain responses to unpredicted rare stimuli are suggested to be a neural indicator of prediction error, but this has rarely been studied in the somatosensory modality. Here, we investigated how the brain responds to unpredictable and predictable rare events. Magnetoencephalography responses were measured in adults frequently presented with somatosensory stimuli (FRE) that were occasionally replaced by two consecutively presented rare stimuli [unpredictable rare stimulus (UR) and predictable rare stimulus (PR); p = 0.1 for each]. The FRE and PR were electrical stimulations administered to either the little finger or the forefinger in a counterbalanced manner between the two conditions. The UR was a simultaneous electrical stimulation to both the forefinger and the little finger (for a smaller subgroup, the UR and FRE were counterbalanced for the stimulus properties). The grand-averaged responses were characterized by two main components: one at 30-100 ms (M55) and the other at 130-230 ms (M150) latency. Source-level analysis was conducted for the primary somatosensory cortex (SI) and the secondary somatosensory cortex (SII). The M55 responses were larger for the UR and PR than for the FRE in both the SI and the SII areas and were larger for the UR than for the PR. For M150, both investigated areas showed increased activity for the UR and the PR compared to the FRE. Interestingly, although the UR was larger in stimulus energy (stimulation of two fingers at the same time) and had a larger prediction error potential than the PR, the M150 responses to these two rare stimuli did not differ in source strength in either the SI or the SII area. The results suggest that M55, but not M150, can possibly be associated with prediction error signals. These findings highlight the need for disentangling prediction error and rareness-related effects in future studies investigating prediction error signals.

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Behavioral studies on auditory deviance detection in patients with Parkinson's disease (PD) have reported contradictory results. The primary aim of this study was to investigate auditory deviance detection of multiple auditory features in patients with PD by means of objective and reliable electroencephalographic (EEG) measurements. Twelve patients with early-stage PD and twelve age- and gender-matched healthy controls (HCs) were included in this study. Patients with PD participated without their regular dopaminergic medication. All subjects underwent an audiometric screening and performed a passive multi-feature mismatch negativity (MMN) paradigm. Repeated-measures analysis of variance (ANOVA) demonstrated no significant differences between patients with PD and HCs regarding MMN mean amplitude and latency for frequency, duration and gap deviants. Nevertheless, a trend towards increased MMN mean amplitude and latency was found in response to intensity deviants in patients with PD compared to HCs. Increased intensity MMN amplitude may indicate that more neural resources are allocated to the processing of intensity deviances in patients with PD compared to HCs. The interpretation of this intensity-specific MMN alteration is further discussed in the context of a compensatory mechanism for auditory intensity processing and involuntary attention switching in PD.

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Auditory prediction errors have been extensively associated with the mismatch negativity (MMN), a cortical auditory evoked potential that denotes deviance detection. Yet, many studies lacked the appropriate controls to disentangle sensory adaptation from prediction error. Furthermore, subcortical deviance detection has been shown in humans through recordings of the frequency-following response (FFR), an early auditory evoked potential that reflects the neural tracking of the periodic characteristics of a sound, suggesting the possibility that prediction errors emerge subcortically in the auditory pathway. The present study aimed at investigating the emergence of prediction error along the auditory hierarchy in humans through combined recordings of the FFR and the MMN, tapping at subcortical and cortical levels, respectively, while disentangling prediction error from sensory adaptation with the use of appropriate controls. "Oddball" sequences of pure tones featuring repeated "standard" stimuli (269 Hz; p = 0.8) and rare "deviant" stimuli (p = 0.2; of 289, 329 and 409 Hz delivered in separated blocks to test "frequency separation" effects) were presented to nineteen healthy young participants. "Reversed" oddball sequences (where standard and deviant tones swapped their roles) were presented allowing comparison of responses to same physical stimuli as a function of functional role (i.e., standard, deviant). Critically, control sequences featuring five equiprobable tones (p = 0.2) allowed to dissociate sensory adaptation from prediction error. Results revealed that the MMN amplitude increased as a function of frequency separation yet displayed the same amplitude when retrieved against the control sequences, confirming previous results. FFRs showed repetition enhancement effects across all frequency separations, as supported by larger spectral amplitude to standard than to deviant and control stimuli. This pattern of results provides insights into the hierarchy of the human prediction error system in audition, suggesting that prediction errors in humans emerge at cortical level.

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