Human auditory cortex is activated by omissions of auditory stimuli

Carrier-frequency specific omission-related neural activity in ordered sound sequences is independent of omission-predictability

Regularities in our surroundings lead to predictions about upcoming events. Previous research has shown that omitted sounds during otherwise regular tone sequences elicit frequency-specific neural activity related to the upcoming but omitted tone. We tested whether this neural response is depending on the unpredictability of the omission. Therefore, we recorded magnetencephalography (MEG) data while participants listened to ordered or random tone sequences with omissions occurring either ordered or randomly. Using multivariate pattern analysis shows that the frequency-specific neural pattern during omission within ordered tone sequences occurs independent of the regularity of the omissions. These results suggest that the auditory predictions based on sensory experiences are not immediately updated by violations of those expectations.

Effects of sensory modality and task relevance on omitted stimulus potentials

Omitted stimulus potentials (OSPs) occur when a sensory stimulus is unexpectedly omitted. They are thought to reflect predictions about upcoming sensory events. The present study examined how OSPs differ across the sensory modalities of predicted stimuli. Twenty-nine university students were asked to press a mouse button at a regular interval of 1-2 s, which was immediately followed by either a visual or auditory stimulus in different blocks. The stimuli were sometimes omitted (p = 0.2), to which event-related potentials (ERPs) were recorded. The results showed that stimulus omissions in both modalities elicited ERP waveforms consisting of three components, oN1, oN2, and oP3. The peak latencies of these components were shorter in the auditory modality than in the visual modality. The amplitudes of OSPs were larger when participants were told that the omission indicated their poor performance (i.e., they pressed a button at an irregular interval) than when it was irrelevant to their performance. These findings suggest that OSPs occur from around 100 ms in a modality-specific manner and increase in amplitude depending on the task relevance of stimulus omissions.

Distinct brain dynamics and networks for processing short and long auditory time intervals

Psychophysical studies suggest that time intervals above and below 1.2 s are processed differently in the human brain. However, the neural underpinnings of this dissociation remain unclear. Here, we investigate whether distinct or common brain networks and dynamics support the passive perception of short (below 1.2 s) and long (above 1.2 s) empty time intervals. Twenty participants underwent an EEG recording during an auditory oddball paradigm with .8- and 1.6-s standard time intervals and deviant intervals either shorter (early) or longer (delayed) than the standard interval. We computed the auditory ERPs for each condition at the sensor and source levels. We then performed whole brain cluster-based permutation statistics for the CNV, N1 and P2, components, testing deviants against standards. A CNV was found only for above 1.2 s intervals (delayed deviants), with generators in temporo-parietal, SMA, and motor regions. Deviance detection of above 1.2 s intervals occurred during the N1 period over fronto-central sensors for delayed deviants only, with generators in parietal and motor regions. Deviance detection of below 1.2 s intervals occurred during the P2 period over fronto-central sensors for delayed deviants only, with generators in primary auditory cortex, SMA, IFG, cingulate and parietal cortex. We then identified deviance related changes in directed connectivity using bivariate Granger causality to highlight the networks dynamics associated with interval processing above and below 1.2. These results suggest that distinct brain dynamics and networks support the perception of time intervals above and below 1.2 s.

Neuronal responses to omitted tones in the auditory brain: A neuronal correlate for predictive coding

Prediction provides key advantages for survival, and cognitive studies have demonstrated that the brain computes multilevel predictions. Evidence for predictions remains elusive at the neuronal level because of the complexity of separating neural activity into predictions and stimulus responses. We overcome this challenge by recording from single neurons from cortical and subcortical auditory regions in anesthetized and awake preparations, during unexpected stimulus omissions interspersed in a regular sequence of tones. We find a subset of neurons that responds reliably to omitted tones. In awake animals, omission responses are similar to anesthetized animals, but larger and more frequent, indicating that the arousal and attentional state levels affect the degree to which predictions are neuronally represented. Omission-sensitive neurons also responded to frequency deviants, with their omission responses getting emphasized in the awake state. Because omission responses occur in the absence of sensory input, they provide solid and empirical evidence for the implementation of a predictive process.

Omission responses in local field potentials in rat auditory cortex

BACKGROUND

Non-invasive recordings of gross neural activity in humans often show responses to omitted stimuli in steady trains of identical stimuli. This has been taken as evidence for the neural coding of prediction or prediction error. However, evidence for such omission responses from invasive recordings of cellular-scale responses in animal models is scarce. Here, we sought to characterise omission responses using extracellular recordings in the auditory cortex of anaesthetised rats. We profiled omission responses across local field potentials (LFP), analogue multiunit activity (AMUA), and single/multi-unit spiking activity, using stimuli that were fixed-rate trains of acoustic noise bursts where 5% of bursts were randomly omitted.

RESULTS

Significant omission responses were observed in LFP and AMUA signals, but not in spiking activity. These omission responses had a lower amplitude and longer latency than burst-evoked sensory responses, and omission response amplitude increased as a function of the number of preceding bursts.

CONCLUSIONS

Together, our findings show that omission responses are most robustly observed in LFP and AMUA signals (relative to spiking activity). This has implications for models of cortical processing that require many neurons to encode prediction errors in their spike output.

Evidence for predictions established by phantom sound

Predictions, the bridge between the internal and external worlds, are established by prior experience and updated by sensory stimuli. Responses to omitted but unexpected stimuli, known as omission responses, can break the one-to-one mapping of stimulus-response and can expose predictions established by the preceding stimulus built up. While research into exogenous predictions (driven by external stimuli) is often reported, that into endogenous predictions (driven by internal percepts) is rarely available in the literature. Here, we report evidence for endogenous predictions established by the Zwicker tone illusion, a phantom pure-tone-like auditory percept following notch noises. We found that MMN, P300, and theta oscillations could be recorded using an omission paradigm in subjects who can perceive Zwicker tone illusions, but could not in those who cannot. The MMN and P300 responses relied on attention, but theta oscillations did not. In-depth analysis shows that an increase in single-trial theta power, including total and induced theta, with the endogenous prediction, is lateralized to the left frontal brain areas. Our study depicts that the brain automatically analyzes internal perception, progressively establishes predictions and yields prediction errors in the left frontal region when a violation occurs.

Event-related responses reflect chunk boundaries in natural speech

Chunking language has been proposed to be vital for comprehension enabling the extraction of meaning from a continuous stream of speech. However, neurocognitive mechanisms of chunking are poorly understood. The present study investigated neural correlates of chunk boundaries intuitively identified by listeners in natural speech drawn from linguistic corpora using magneto- and electroencephalography (MEEG). In a behavioral experiment, subjects marked chunk boundaries in the excerpts intuitively, which revealed highly consistent chunk boundary markings across the subjects. We next recorded brain activity to investigate whether chunk boundaries with high and medium agreement rates elicit distinct evoked responses compared to non-boundaries. Pauses placed at chunk boundaries elicited a closure positive shift with the sources over bilateral auditory cortices. In contrast, pauses placed within a chunk were perceived as interruptions and elicited a biphasic emitted potential with sources located in the bilateral primary and non-primary auditory areas with right-hemispheric dominance, and in the right inferior frontal cortex. Furthermore, pauses placed at stronger boundaries elicited earlier and more prominent activation over the left hemisphere suggesting that brain responses to chunk boundaries of natural speech can be modulated by the relative strength of different linguistic cues, such as syntactic structure and prosody.

Prediction-Related Frontal-Temporal Network for Omission Mismatch Activity in the Macaque Monkey

Sensory prediction is considered an important element of mismatch negativity (MMN) whose reduction is well known in patients with schizophrenia. Omission MMN is a variant of the MMN which is elicited by the absence of a tone previously sequentially presented. Omission MMN can eliminate the effects of sound differences in typical oddball paradigms and affords the opportunity to identify prediction-related signals in the brain. Auditory predictions are thought to reflect bottom-up and top-down processing within hierarchically organized auditory areas. However, the communications between the various subregions of the auditory cortex and the prefrontal cortex that generate and communicate sensory prediction-related signals remain poorly understood. To explore how the frontal and temporal cortices communicate for the generation and propagation of such signals, we investigated the response in the omission paradigm using electrocorticogram (ECoG) electrodes implanted in the temporal, lateral prefrontal, and orbitofrontal cortices of macaque monkeys. We recorded ECoG data from three monkeys during the omission paradigm and examined the functional connectivity between the temporal and frontal cortices by calculating phase-locking values (PLVs). This revealed that theta- (4-8 Hz), alpha- (8-12 Hz), and low-beta- (12-25 Hz) band synchronization increased at tone onset between the higher auditory cortex and the frontal pole where an early omission response was observed in the event-related potential (ERP). These synchronizations were absent when the tone was omitted. Conversely, low-beta-band (12-25 Hz) oscillation then became stronger for tone omission than for tone presentation approximately 200 ms after tone onset. The results suggest that auditory input is propagated to the frontal pole via the higher auditory cortex and that a reciprocal network may be involved in the generation of auditory prediction and prediction error. As impairments of prediction may underlie MMN reduction in patients with schizophrenia, an aberrant hierarchical temporal-frontal network might be related to this pathological condition.

Suppression, Maintenance, and Surprise: Neuronal Correlates of Predictive Processing Specialization for Musical Rhythm

Auditory repetition suppression and omission activation are opposite neural phenomena and manifestations of principles of predictive processing. Repetition suppression describes the temporal decrease in neural activity when a stimulus is constant or repeated in an expected temporal fashion; omission activity is the transient increase in neural activity when a stimulus is temporarily and unexpectedly absent. The temporal, repetitive nature of musical rhythms is ideal for investigating these phenomena. During an fMRI session, 10 healthy participants underwent scanning while listening to musical rhythms with two levels of metric complexity, and with beat omissions with different positional complexity. Participants first listened to 16-s-long presentations of continuous rhythms, before listening to a longer continuous presentation with beat omissions quasi-randomly introduced. We found deactivation in bilateral superior temporal gyri during the repeated presentation of the normal, unaltered rhythmic stimulus, with more suppression of activity in the left hemisphere. Omission activation of bilateral middle temporal gyri was right lateralized. Persistent activity was found in areas including the supplementary motor area, caudate nucleus, anterior insula, frontal areas, and middle and posterior cingulate cortex, not overlapping with either listening, suppression, or omission activation. This suggests that the areas are perhaps specialized for working memory maintenance. We found no effect of metric complexity for either the normal presentation or omissions, but we found evidence for a small effect of omission position—at an uncorrected threshold—where omissions in the more metrical salient position, i.e., the first position in the bar, showed higher activation in anterior cingulate/medial superior frontal gyrus, compared to omissions in the less salient position, in line with the role of the anterior cingulate cortex for saliency detection. The results are consistent with findings in our previous studies on Parkinson’s disease, but are put into a bigger theoretical frameset.

Sustained neural rhythms reveal endogenous oscillations supporting speech perception

Rhythmic sensory or electrical stimulation will produce rhythmic brain responses. These rhythmic responses are often interpreted as endogenous neural oscillations aligned (or "entrained") to the stimulus rhythm. However, stimulus-aligned brain responses can also be explained as a sequence of evoked responses, which only appear regular due to the rhythmicity of the stimulus, without necessarily involving underlying neural oscillations. To distinguish evoked responses from true oscillatory activity, we tested whether rhythmic stimulation produces oscillatory responses which continue after the end of the stimulus. Such sustained effects provide evidence for true involvement of neural oscillations. In Experiment 1, we found that rhythmic intelligible, but not unintelligible speech produces oscillatory responses in magnetoencephalography (MEG) which outlast the stimulus at parietal sensors. In Experiment 2, we found that transcranial alternating current stimulation (tACS) leads to rhythmic fluctuations in speech perception outcomes after the end of electrical stimulation. We further report that the phase relation between electroencephalography (EEG) responses and rhythmic intelligible speech can predict the tACS phase that leads to most accurate speech perception. Together, we provide fundamental results for several lines of research-including neural entrainment and tACS-and reveal endogenous neural oscillations as a key underlying principle for speech perception.

Mental operations in rhythm: Motor-to-sensory transformation mediates imagined singing

What enables the mental activities of thinking verbally or humming in our mind? We hypothesized that the interaction between motor and sensory systems induces speech and melodic mental representations, and this motor-to-sensory transformation forms the neural basis that enables our verbal thinking and covert singing. Analogous with the neural entrainment to auditory stimuli, participants imagined singing lyrics of well-known songs rhythmically while their neural electromagnetic signals were recorded using magnetoencephalography (MEG). We found that when participants imagined singing the same song in similar durations across trials, the delta frequency band (1–3 Hz, similar to the rhythm of the songs) showed more consistent phase coherence across trials. This neural phase tracking of imagined singing was observed in a frontal-parietal-temporal network: the proposed motor-to-sensory transformation pathway, including the inferior frontal gyrus (IFG), insula (INS), premotor area, intra-parietal sulcus (IPS), temporal-parietal junction (TPJ), primary auditory cortex (Heschl’s gyrus [HG]), and superior temporal gyrus (STG) and sulcus (STS). These results suggest that neural responses can entrain the rhythm of mental activity. Moreover, the theta-band (4–8 Hz) phase coherence was localized in the auditory cortices. The mu (9–12 Hz) and beta (17–20 Hz) bands were observed in the right-lateralized sensorimotor systems that were consistent with the singing context. The gamma band was broadly manifested in the observed network. The coherent and frequency-specific activations in the motor-to-sensory transformation network mediate the internal construction of perceptual representations and form the foundation of neural computations for mental operations.

What enables our mental activities for thinking verbally or humming in our mind? Using an imagined singing paradigm with magnetoencephalography recordings, this study shows that neural oscillations in the motor-to-sensory transformation network tracked inner speech and covert singing.

Skipping a Beat: Heartbeat-Evoked Potentials Reflect Predictions during Interoceptive-Exteroceptive Integration

Several theories propose that emotions and self-awareness arise from the integration of internal and external signals and their respective precision-weighted expectations. Supporting these mechanisms, research indicates that the brain uses temporal cues from cardiac signals to predict auditory stimuli and that these predictions and their prediction errors can be observed in the scalp heartbeat-evoked potential (HEP). We investigated the effect of precision modulations on these cross-modal predictive mechanisms, via attention and interoceptive ability. We presented auditory sequences at short (perceived synchronous) or long (perceived asynchronous) cardio-audio delays, with half of the trials including an omission. Participants attended to the cardio-audio synchronicity of the tones (internal attention) or the auditory stimuli alone (external attention). Comparing HEPs during omissions allowed for the observation of pure predictive signals, without contaminating auditory input. We observed an early effect of cardio-audio delay, reflecting a difference in heartbeat-driven expectations. We also observed a larger positivity to the omissions of sounds perceived as synchronous than to the omissions of sounds perceived as asynchronous when attending internally only, consistent with the role of attentional precision for enhancing predictions. These results provide support for attentionally modulated cross-modal predictive coding and suggest a potential tool for investigating its role in emotion and self-awareness.

Do rat auditory event related potentials exhibit human mismatch negativity attributes related to predictive coding?

Rodent models play a significant role in understanding disease mechanisms and the screening of new treatments. With regard to psychiatric disorders such as schizophrenia, however, it is difficult to replicate the human symptoms in rodents because these symptoms are often either 'uniquely human' or are only conveyed via self-report. There is a growing interest in rodent mismatch responses (MMRs) as a translatable 'biomarker' for disorders such as schizophrenia. In this review, we will summarize the attributes of human MMN, and discuss the scope of exploring the attributes of human MMN in rodents. Here, we examine how reliably MMRs that are measured in rats mimic human attributes, and present original data examining whether manipulations of stimulus conditions known to modulate human MMN, do the same for rat MMRs. Using surgically-implanted epidural electroencephalographic electrodes and wireless telemetry in freely-moving rats, we observed human-like modulations of MMRs, namely that larger MMRs were elicited to unexpected (deviant) stimuli that a) had a larger change in pitch compared to the expected (standard) stimulus, b) were less frequently presented (lower probability), and c) had no jitter (stable stimulus onset asynchrony) compared to high jitter. Overall, these findings contribute to the mounting evidence for rat MMRs as a good analogue of human MMN, bolstering the development of a novel approach in future to validate the preclinical models based on a translatable biomarker, MMN.

The Role of Surface and Underlying Forms When Processing Tonal Alternations in Mandarin Chinese: A Mismatch Negativity Study

Phonological alternation (sound change depending on the phonological environment) poses challenges to spoken word recognition models. Mandarin Chinese T3 sandhi is such a phenomenon in which a tone 3 (T3) changes into a tone 2 (T2) when followed by another T3. In a mismatch negativity (MMN) study examining Mandarin Chinese T3 sandhi, participants passively listened to either a T2 word [tʂu2 je4] /tʂu2 je4/, a T3 word [tʂu3 je4] /tʂu3 je4/, a sandhi word [tʂu2 jen3] /tʂu3 jen3/, or a mix of T3 and sandhi word standards. The deviant in each condition was a T2 word [tʂu2]. Results showed an MMN only in the T2 and T3 conditions but not in the Sandhi or Mix conditions. All conditions also yielded omission MMNs. This pattern cannot be explained based on the surface forms of standards and deviants; rather these data suggest an underspecified or underlying T3 stored linguistic representation used in spoken word processing.

The Role of Glutamate Neurotransmission in Mismatch Negativity (MMN), A Measure of Auditory Synaptic Plasticity and Change-detection

Mismatch negativity (MMN) is an electrophysiological signature that occurs in response to unexpected stimuli. It is often referred to as a measure of memory-based change detection, because the elicitation of a prediction error response relies on the formation of a prediction, which in turn, is dependent upon intact memory of previous auditory stimulation. As such, the MMN is altered in conditions in which memory is affected, such as Alzheimer's disease, schizophrenia and healthy aging. The most prominent pharmacological finding for MMN strengthens the link between MMN and synaptic plasticity, as glutamate N-methyl-d-aspartate receptor (NMDA-R) antagonists reduce the MMN response. However, recent data has begun to demonstrate that the link between NMDA-R function and MMN is not as clear as once thought, with low dose and low affinity NMDA-R antagonists observed to facilitate MMN.

A generic deviance detection principle for cortical On/Off responses, omission response, and mismatch negativity

Neural responses to sudden changes can be observed in many parts of the sensory pathways at different organizational levels. For example, deviants that violate regularity at various levels of abstraction can be observed as simple On/Off responses of individual neurons or as cumulative responses of neural populations. The cortical deviance-related responses supporting different functionalities (e.g., gap detection, chunking, etc.) seem unlikely to arise from different function-specific neural circuits, given the relatively uniform and self-similar wiring patterns across cortical areas and spatial scales. Additionally, reciprocal wiring patterns (with heterogeneous combinations of excitatory and inhibitory connections) in the cortex naturally speak in favor of a generic deviance detection principle. Based on this concept, we propose a network model consisting of reciprocally coupled neural masses as a blueprint of a universal change detector. Simulation examples reproduce properties of cortical deviance-related responses including the On/Off responses, the omitted-stimulus response (OSR), and the mismatch negativity (MMN). We propose that the emergence of change detectors relies on the involvement of disinhibition. An analysis of network connection settings further suggests a supportive effect of synaptic adaptation and a destructive effect of N-methyl-D-aspartate receptor (NMDA-r) antagonists on change detection. We conclude that the nature of cortical reciprocal wiring gives rise to a whole range of local change detectors supporting the notion of a generic deviance detection principle. Several testable predictions are provided based on the network model. Notably, we predict that the NMDA-r antagonists would generally dampen the cortical Off response, the cortical OSR, and the MMN.

From alternation to repetition: Spatial attention biases contribute to sequential effects in a choice reaction-time task

Observers often take longer to respond to a visual target when it appears at a recently stimulated location than when it appears at a new location in the visual field. This behavioral impairment - known as inhibition of return (IOR) - is mirrored by a reduction of an event-related potential (ERP) component called the N2pc that has been associated with attentional selection. Together, these findings indicate that the mechanism underlying IOR operates to bias covert attention against re-visiting the most recently attended location. The goal of the present study was to determine how this inhibitory attention bias evolves across successive trials of a two-item search task. Initially, targets appearing at previously attended locations were associated with behavioral IOR and a concomitant reduction of the N2pc. After several successive trials, this initial inhibitory bias was superseded by expectancy-based biases associated with "predictable" inter-trial patterns of location repeats or location changes, in some cases leading to faster responses and a larger N2pc when the target location repeated (facilitation of return).  These results provide evidence that biases in the covert deployment of attention are updated dynamically according to the recent selection history and contribute to well-known sequential effects in serial choice reaction-time tasks.

Compensatory task-specific hypersensitivity in bilateral planum temporale and right superior temporal gyrus during auditory rhythm and omission processing in Parkinson's disease

Persons with Parkinson's disease have general timing deficits and have difficulties in rhythm discrimination tasks. The basal ganglia, a crucial part of Parkinson's disease pathology, is believed to play an important role in rhythm and beat processing, with a possible modulation of basal ganglia activity by level of rhythmic complexity. As dysfunction in basal ganglia impacts function in other brain areas in Parkinson's disease during temporal processing, investigating the neuronal basis for rhythm processing is important as it could shed light on the nature of basal ganglia dysfunction and compensatory mechanisms. We constructed an auditory beat-omission fMRI paradigm with two levels of rhythm complexity, to investigate if and where persons with Parkinson's disease showed abnormal activation during rhythm and omission processing, and whether such activations were modulated by the level of rhythmic complexity. We found no effect of complexity, but found crucial group differences. For the processing of normal rhythm presentations, the Parkinson-group showed higher bilateral planum temporal activity, an area previously associated with the processing of complex patterns. For the omissions, the Parkinson-group showed higher activity in an area in the right superior temporal gyrus previously associated with detection of auditory omissions. We believe this shows a pattern of "hypersensitive" activity, indicative of task-specific, compensatory mechanisms in the processing of temporal auditory information in persons with Parkinson's disease.

Automatic and feature-specific prediction-related neural activity in the human auditory system

Prior experience enables the formation of expectations of upcoming sensory events. However, in the auditory modality, it is not known whether prediction-related neural signals carry feature-specific information. Here, using magnetoencephalography (MEG), we examined whether predictions of future auditory stimuli carry tonotopic specific information. Participants passively listened to sound sequences of four carrier frequencies (tones) with a fixed presentation rate, ensuring strong temporal expectations of when the next stimulus would occur. Expectation of which frequency would occur was parametrically modulated across the sequences, and sounds were occasionally omitted. We show that increasing the regularity of the sequence boosts carrier-frequency-specific neural activity patterns during both the anticipatory and omission periods, indicating that prediction-related neural activity is indeed feature-specific. Our results illustrate that even without bottom-up input, auditory predictions can activate tonotopically specific templates.

After listening to a predictable sequence of sounds, we can anticipate and predict the next sound in the sequence. Here, the authors show that during expectation of a sound, the brain generates neural activity matching that which is produced by actually hearing the same sound.

The Neuronal Basis of Predictive Coding Along the Auditory Pathway: From the Subcortical Roots to Cortical Deviance 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.

Sensory representation of an auditory cued tactile stimulus in the posterior parietal cortex of the mouse

Sensory association cortices receive diverse inputs with their role in representing and integrating multi-sensory content remaining unclear. Here we examined the neuronal correlates of an auditory-tactile stimulus sequence in the posterior parietal cortex (PPC) using 2-photon calcium imaging in awake mice. We find that neuronal subpopulations in layer 2/3 of PPC reliably represent texture-touch events, in addition to auditory cues that presage the incoming tactile stimulus. Notably, altering the flow of sensory events through omission of the cued texture touch elicited large responses in a subset of neurons hardly responsive to or even inhibited by the tactile stimuli. Hence, PPC neurons were able to discriminate not only tactile stimulus features (i.e., texture graininess) but also between the presence and omission of the texture stimulus. Whereas some of the neurons responsive to texture omission were driven by looming-like auditory sounds others became recruited only with tactile sensory experience. These findings indicate that layer 2/3 neuronal populations in PPC potentially encode correlates of expectancy in addition to auditory and tactile stimuli.

Great Expectations: Is there Evidence for Predictive Coding in Auditory Cortex?

Predictive coding is possibly one of the most influential, comprehensive, and controversial theories of neural function. While proponents praise its explanatory potential, critics object that key tenets of the theory are untested or even untestable. The present article critically examines existing evidence for predictive coding in the auditory modality. Specifically, we identify five key assumptions of the theory and evaluate each in the light of animal, human and modeling studies of auditory pattern processing. For the first two assumptions - that neural responses are shaped by expectations and that these expectations are hierarchically organized - animal and human studies provide compelling evidence. The anticipatory, predictive nature of these expectations also enjoys empirical support, especially from studies on unexpected stimulus omission. However, for the existence of separate error and prediction neurons, a key assumption of the theory, evidence is lacking. More work exists on the proposed oscillatory signatures of predictive coding, and on the relation between attention and precision. However, results on these latter two assumptions are mixed or contradictory. Looking to the future, more collaboration between human and animal studies, aided by model-based analyses will be needed to test specific assumptions and implementations of predictive coding - and, as such, help determine whether this popular grand theory can fulfill its expectations.

Integrating speech in time depends on temporal expectancies and attention

Sensory information that unfolds in time, such as in speech perception, relies on efficient chunking mechanisms in order to yield optimally-sized units for further processing. Whether or not two successive acoustic events receive a one-unit or a two-unit interpretation seems to depend on the fit between their temporal extent and a stipulated temporal window of integration. However, there is ongoing debate on how flexible this temporal window of integration should be, especially for the processing of speech sounds. Furthermore, there is no direct evidence of whether attention may modulate the temporal constraints on the integration window. For this reason, we here examine how different word durations, which lead to different temporal separations of sound onsets, interact with attention. In an Electroencephalography (EEG) study, participants actively and passively listened to words where word-final consonants were occasionally omitted. Words had either a natural duration or were artificially prolonged in order to increase the separation of speech sound onsets. Omission responses to incomplete speech input, originating in left temporal cortex, decreased when the critical speech sound was separated from previous sounds by more than 250 msec, i.e., when the separation was larger than the stipulated temporal window of integration (125-150 msec). Attention, on the other hand, only increased omission responses for stimuli with natural durations. We complemented the event-related potential (ERP) analyses by a frequency-domain analysis on the stimulus presentation rate. Notably, the power of stimulation frequency showed the same duration and attention effects than the omission responses. We interpret these findings on the background of existing research on temporal integration windows and further suggest that our findings may be accounted for within the framework of predictive coding.

Silent Expectations: Dynamic Causal Modeling of Cortical Prediction and Attention to Sounds That Weren't

There is increasing evidence that human perception is realized by a hierarchy of neural processes in which predictions sent backward from higher levels result in prediction errors that are fed forward from lower levels, to update the current model of the environment. Moreover, the precision of prediction errors is thought to be modulated by attention. Much of this evidence comes from paradigms in which a stimulus differs from that predicted by the recent history of other stimuli (generating a so-called "mismatch response"). There is less evidence from situations where a prediction is not fulfilled by any sensory input (an "omission" response). This situation arguably provides a more direct measure of "top-down" predictions in the absence of confounding "bottom-up" input. We applied Dynamic Causal Modeling of evoked electromagnetic responses recorded by EEG and MEG to an auditory paradigm in which we factorially crossed the presence versus absence of "bottom-up" stimuli with the presence versus absence of "top-down" attention. Model comparison revealed that both mismatch and omission responses were mediated by increased forward and backward connections, differing primarily in the driving input. In both responses, modeling results suggested that the presence of attention selectively modulated backward "prediction" connections. Our results provide new model-driven evidence of the pure top-down prediction signal posited in theories of hierarchical perception, and highlight the role of attentional precision in strengthening this prediction.

SIGNIFICANCE STATEMENT

Human auditory perception is thought to be realized by a network of neurons that maintain a model of and predict future stimuli. Much of the evidence for this comes from experiments where a stimulus unexpectedly differs from previous ones, which generates a well-known "mismatch response." But what happens when a stimulus is unexpectedly omitted altogether? By measuring the brain's electromagnetic activity, we show that it also generates an "omission response" that is contingent on the presence of attention. We model these responses computationally, revealing that mismatch and omission responses only differ in the location of inputs into the same underlying neuronal network. In both cases, we show that attention selectively strengthens the brain's prediction of the future.

Convergent evidence for hierarchical prediction networks from human electrocorticography and magnetoencephalography

We propose that sensory inputs are processed in terms of optimised predictions and prediction error signals within hierarchical neurocognitive models. The combination of non-invasive brain imaging and generative network models has provided support for hierarchical frontotemporal interactions in oddball tasks, including recent identification of a temporal expectancy signal acting on prefrontal cortex. However, these studies are limited by the need to invert magnetoencephalographic or electroencephalographic sensor signals to localise activity from cortical 'nodes' in the network, or to infer neural responses from indirect measures such as the fMRI BOLD signal. To overcome this limitation, we examined frontotemporal interactions estimated from direct cortical recordings from two human participants with cortical electrode grids (electrocorticography - ECoG). Their frontotemporal network dynamics were compared to those identified by magnetoencephalography (MEG) in forty healthy adults. All participants performed the same auditory oddball task with standard tones interspersed with five deviant tone types. We normalised post-operative electrode locations to standardised anatomic space, to compare across modalities, and inverted the MEG to cortical sources using the estimated lead field from subject-specific head models. A mismatch negativity signal in frontal and temporal cortex was identified in all subjects. Generative models of the electrocorticographic and magnetoencephalographic data were separately compared using the free-energy estimate of the model evidence. Model comparison confirmed the same critical features of hierarchical frontotemporal networks in each patient as in the group-wise MEG analysis. These features included bilateral, feedforward and feedback frontotemporal modulated connectivity, in addition to an asymmetric expectancy driving input on left frontal cortex. The invasive ECoG provides an important step in construct validation of the use of neural generative models of MEG, which in turn enables generalisation to larger populations. Together, they give convergent evidence for the hierarchical interactions in frontotemporal networks for expectation and processing of sensory inputs.

Two different mechanisms for the detection of stimulus omission

Although we can detect slight changes in musical rhythm, the underlying neural mechanism remains elusive. Here we show that two distinct mechanisms are automatically selected depending on the speed of the rhythm. When human subjects detected a single omission of isochronous repetitive auditory stimuli, reaction time strongly depended on the stimulus onset asynchrony (SOA) for shorter SOAs (<250 ms), but was almost constant for longer SOAs. For shorter SOAs, subjects were unable to detect stimulus omission when either monaural stimuli or those in different frequencies were randomly presented. In contrast, for longer SOAs, reaction time increased when different tempos were presented simultaneously to different ears. These results suggest that depending on the speed of rhythms, the brain may use either temporal grouping of discrete sounds or temporal prediction of upcoming stimuli to detect the absence of a regular stimulus. Because we also found a similar relationship between reaction time and SOA for both visual and tactile stimuli, dual detection strategies could be generalized to other sensory modalities.

Neural Basis of the Time Window for Subjective Motor-Auditory Integration

Temporal contiguity between an action and corresponding auditory feedback is crucial to the perception of self-generated sound. However, the neural mechanisms underlying motor–auditory temporal integration are unclear. Here, we conducted four experiments with an oddball paradigm to examine the specific event-related potentials (ERPs) elicited by delayed auditory feedback for a self-generated action. The first experiment confirmed that a pitch-deviant auditory stimulus elicits mismatch negativity (MMN) and P300, both when it is generated passively and by the participant’s action. In our second and third experiments, we investigated the ERP components elicited by delayed auditory feedback for a self-generated action. We found that delayed auditory feedback elicited an enhancement of P2 (enhanced-P2) and a N300 component, which were apparently different from the MMN and P300 components observed in the first experiment. We further investigated the sensitivity of the enhanced-P2 and N300 to delay length in our fourth experiment. Strikingly, the amplitude of the N300 increased as a function of the delay length. Additionally, the N300 amplitude was significantly correlated with the conscious detection of the delay (the 50% detection point was around 200 ms), and hence reduction in the feeling of authorship of the sound (the sense of agency). In contrast, the enhanced-P2 was most prominent in short-delay (≤200 ms) conditions and diminished in long-delay conditions. Our results suggest that different neural mechanisms are employed for the processing of temporally deviant and pitch-deviant auditory feedback. Additionally, the temporal window for subjective motor–auditory integration is likely about 200 ms, as indicated by these auditory ERP components.

The brain timewise: how timing shapes and supports brain function

We discuss the importance of timing in brain function: how temporal dynamics of the world has left its traces in the brain during evolution and how we can monitor the dynamics of the human brain with non-invasive measurements. Accurate timing is important for the interplay of neurons, neuronal circuitries, brain areas and human individuals. In the human brain, multiple temporal integration windows are hierarchically organized, with temporal scales ranging from microseconds to tens and hundreds of milliseconds for perceptual, motor and cognitive functions, and up to minutes, hours and even months for hormonal and mood changes. Accurate timing is impaired in several brain diseases. From the current repertoire of non-invasive brain imaging methods, only magnetoencephalography (MEG) and scalp electroencephalography (EEG) provide millisecond time-resolution; our focus in this paper is on MEG. Since the introduction of high-density whole-scalp MEG/EEG coverage in the 1990s, the instrumentation has not changed drastically; yet, novel data analyses are advancing the field rapidly by shifting the focus from the mere pinpointing of activity hotspots to seeking stimulus- or task-specific information and to characterizing functional networks. During the next decades, we can expect increased spatial resolution and accuracy of the time-resolved brain imaging and better understanding of brain function, especially its temporal constraints, with the development of novel instrumentation and finer-grained, physiologically inspired generative models of local and network activity. Merging both spatial and temporal information with increasing accuracy and carrying out recordings in naturalistic conditions, including social interaction, will bring much new information about human brain function.

Predictions interact with missing sensory evidence in semantic processing areas

Human brain function draws on predictive mechanisms that exploit higher-level context during lower-level perception. These mechanisms are particularly relevant for situations in which sensory information is compromised or incomplete, as for example in natural speech where speech segments may be omitted due to sluggish articulation. Here, we investigate which brain areas support the processing of incomplete words that were predictable from semantic context, compared with incomplete words that were unpredictable. During functional magnetic resonance imaging (fMRI), participants heard sentences that orthogonally varied in predictability (semantically predictable vs. unpredictable) and completeness (complete vs. incomplete, i.e. missing their final consonant cluster). The effects of predictability and completeness interacted in heteromodal semantic processing areas, including left angular gyrus and left precuneus, where activity did not differ between complete and incomplete words when they were predictable. The same regions showed stronger activity for incomplete than for complete words when they were unpredictable. The interaction pattern suggests that for highly predictable words, the speech signal does not need to be complete for neural processing in semantic processing areas. Hum Brain Mapp 37:704-716, 2016. © 2015 Wiley Periodicals, Inc.

A predictive coding account of MMN reduction in schizophrenia

The mismatch negativity (MMN) is thought to be an index of the automatic activation of a specialized network for active prediction and deviance detection in the auditory cortex. It is consistently reduced in schizophrenic patients and has received a lot of interest as a clinical and translational tool. The main neuronal hypothesis regarding the mechanisms leading to a reduced MMN in schizophrenic patients is a dysfunction of NMDA receptors (NMDA-R). However, this hypothesis has never been implemented in a neuronal model. In this paper, we examine the consequences of NMDA-R dysfunction in a neuronal model of MMN based on predictive coding principle. I also investigate how predictive processes may interact with synaptic adaptation in MMN generations and examine the consequences of this interaction for the use of MMN paradigms in schizophrenia research.

Effects of refractive errors on visual evoked magnetic fields

Background

The latency and amplitude of visual evoked cortical responses are known to be affected by refractive states, suggesting that they may be used as an objective index of refractive errors. In order to establish an easy and reliable method for this purpose, we herein examined the effects of refractive errors on visual evoked magnetic fields (VEFs).

Methods

Binocular VEFs following the presentation of a simple grating of 0.16 cd/m² in the lower visual field were recorded in 12 healthy volunteers and compared among four refractive states: 0D, +1D, +2D, and +4D, by using plus lenses.

Results

The low-luminance visual stimulus evoked a main MEG response at approximately 120 ms (M100) that reversed its polarity between the upper and lower visual field stimulations and originated from the occipital midline area. When refractive errors were induced by plus lenses, the latency of M100 increased, while its amplitude decreased with an increase in power of the lens. Differences from the control condition (+0D) were significant for all three lenses examined. The results of dipole analyses showed that evoked fields for the control (+0D) condition were explainable by one dipole in the primary visual cortex (V1), while other sources, presumably in V3 or V6, slightly contributed to shape M100 for the +2D or +4D condition.

Conclusions

The present results showed that the latency and amplitude of M100 are both useful indicators for assessing refractive states. The contribution of neural sources other than V1 to M100 was modest under the 0D and +1D conditions. By considering the nature of the activity of M100 including its high sensitivity to a spatial frequency and lower visual field dominance, a simple low-luminance grating stimulus at an optimal spatial frequency in the lower visual field appears appropriate for obtaining data on high S/N ratios and reducing the load on subjects.

Hierarchical Organization of Frontotemporal Networks for the Prediction of Stimuli across Multiple Dimensions

Brain function can be conceived as a hierarchy of generative models that optimizes predictions of sensory inputs and minimizes "surprise." Each level of the hierarchy makes predictions of neural events at a lower level in the hierarchy, which returns a prediction error when these expectations are violated. We tested the generalization of this hypothesis to multiple sequential deviations, and we identified the most likely organization of the network that accommodates deviations in temporal structure of stimuli. Magnetoencephalography of healthy human participants during an auditory paradigm identified prediction error responses in bilateral primary auditory cortex, superior temporal gyrus, and lateral prefrontal cortex for deviation by frequency, intensity, location, duration, and silent gap. We examined the connectivity between cortical sources using a set of 21 generative models that embedded alternate hypotheses of frontotemporal network dynamics. Bayesian model selection provided evidence for two new features of functional network organization. First, an expectancy signal provided input to the prefrontal cortex bilaterally, related to the temporal structure of stimuli. Second, there are functionally significant lateral connections between superior temporal and/or prefrontal cortex. The results support a predictive coding hypothesis but go beyond previous work in demonstrating the generalization to multiple concurrent stimulus dimensions and the evidence for a temporal expectancy input at the higher level of the frontotemporal hierarchy. We propose that this framework for studying the brain's response to unexpected events is not limited to simple sensory tasks but may also apply to the neurocognitive mechanisms of higher cognitive functions and their disorders.

Noise occlusion in discrete tone sequences as a tool towards auditory predictive processing?

The notion of predictive coding is a common feature of many theories of auditory information processing. Experimental demonstrations of predictive auditory processing often rest on omitting predictable input in order to uncover the prediction made by the brain. Findings show that auditory cortical activity elicited by the omission of a predictable tone resembles the activity elicited by the actual tone. Here we attempted to extend this approach towards using noises instead of omissions in order to capture a more prevalent case of degraded sensory input. By applying a subtraction approach to remove ERP effects of the noise itself, auditory cortical activity elicited "behind" the noise was uncovered. We hypothesized that ERPs elicited behind noise stimuli covering predictable tones should be more similar to ERPs elicited by the actual tones than when the same comparison is made for unpredictable tones. ERP results during passive listening partly confirm this hypothesis, but also point towards some methodological caveats in this particular approach towards studying neural correlates of predictive auditory processing due to contributions from predictability-unrelated factors. A follow-up active listening condition indicated that participants were not more likely to perceive the tone sequence as continuous when a predictable tone was covered with noise than when this pertained to an unpredictable tone. Overall, the noise-based paradigm in its present form was not shown to be successful in revealing predictive processing in perceptual judgments or early neural correlates of sound processing. We discuss these findings in the contexts of predictive processing and illusory auditory continuity. This article is part of a Special Issue entitled SI: Prediction and Attention.

Experience-based Auditory Predictions Modulate Brain Activity to Silence as do Real Sounds

Interactions between stimuli's acoustic features and experience-based internal models of the environment enable listeners to compensate for the disruptions in auditory streams that are regularly encountered in noisy environments. However, whether auditory gaps are filled in predictively or restored a posteriori remains unclear. The current lack of positive statistical evidence that internal models can actually shape brain activity as would real sounds precludes accepting predictive accounts of filling-in phenomenon. We investigated the neurophysiological effects of internal models by testing whether single-trial electrophysiological responses to omitted sounds in a rule-based sequence of tones with varying pitch could be decoded from the responses to real sounds and by analyzing the ERPs to the omissions with data-driven electrical neuroimaging methods. The decoding of the brain responses to different expected, but omitted, tones in both passive and active listening conditions was above chance based on the responses to the real sound in active listening conditions. Topographic ERP analyses and electrical source estimations revealed that, in the absence of any stimulation, experience-based internal models elicit an electrophysiological activity different from noise and that the temporal dynamics of this activity depend on attention. We further found that the expected change in pitch direction of omitted tones modulated the activity of left posterior temporal areas 140-200 msec after the onset of omissions. Collectively, our results indicate that, even in the absence of any stimulation, internal models modulate brain activity as do real sounds, indicating that auditory filling in can be accounted for by predictive activity.

Spatial auditory regularity encoding and prediction: Human middle-latency and long-latency auditory evoked potentials

By encoding acoustic regularities present in the environment, the human brain can generate predictions of what is likely to occur next. Recent studies suggest that deviations from encoded regularities are detected within 10-50ms after stimulus onset, as indicated by electrophysiological effects in the middle latency response (MLR) range. This is upstream of previously known long-latency (LLR) signatures of deviance detection such as the mismatch negativity (MMN) component. In the present study, we created predictable and unpredictable contexts to investigate MLR and LLR signatures of the encoding of spatial auditory regularities and the generation of predictions from these regularities. Chirps were monaurally delivered in an either regular (predictable: left-right-left-right) or a random (unpredictable left/right alternation or repetition) manner. Occasional stimulus omissions occurred in both types of sequences. Results showed that the Na component (peaking at 34ms after stimulus onset) was attenuated for regular relative to random chirps, albeit no differences were observed for stimulus omission responses in the same latency range. In the LLR range, larger chirp-and omission-evoked responses were elicited for the regular than for the random condition, and predictability effects were more prominent over the right hemisphere. We discuss our findings in the framework of a hierarchical organization of spatial regularity encoding. This article is part of a Special Issue entitled SI: Prediction and Attention.

Temporal expectation and attention jointly modulate auditory oscillatory activity in the beta band

The neural response to a stimulus is influenced by endogenous factors such as expectation and attention. Current research suggests that expectation and attention exert their effects in opposite directions, where expectation decreases neural activity in sensory areas, while attention increases it. However, expectation and attention are usually studied either in isolation or confounded with each other. A recent study suggests that expectation and attention may act jointly on sensory processing, by increasing the neural response to expected events when they are attended, but decreasing it when they are unattended. Here we test this hypothesis in an auditory temporal cueing paradigm using magnetoencephalography in humans. In our study participants attended to, or away from, tones that could arrive at expected or unexpected moments. We found a decrease in auditory beta band synchrony to expected (versus unexpected) tones if they were unattended, but no difference if they were attended. Modulations in beta power were already evident prior to the expected onset times of the tones. These findings suggest that expectation and attention jointly modulate sensory processing.

Attention and prediction in human audition: a lesson from cognitive psychophysiology

Attention is a hypothetical mechanism in the service of perception that facilitates the processing of relevant information and inhibits the processing of irrelevant information. Prediction is a hypothetical mechanism in the service of perception that considers prior information when interpreting the sensorial input. Although both (attention and prediction) aid perception, they are rarely considered together. Auditory attention typically yields enhanced brain activity, whereas auditory prediction often results in attenuated brain responses. However, when strongly predicted sounds are omitted, brain responses to silence resemble those elicited by sounds. Studies jointly investigating attention and prediction revealed that these different mechanisms may interact, e.g. attention may magnify the processing differences between predicted and unpredicted sounds. Following the predictive coding theory, we suggest that prediction relates to predictions sent down from predictive models housed in higher levels of the processing hierarchy to lower levels and attention refers to gain modulation of the prediction error signal sent up to the higher level. As predictions encode contents and confidence in the sensory data, and as gain can be modulated by the intention of the listener and by the predictability of the input, various possibilities for interactions between attention and prediction can be unfolded. From this perspective, the traditional distinction between bottom-up/exogenous and top-down/endogenous driven attention can be revisited and the classic concepts of attentional gain and attentional trace can be integrated.

Predictive coding of visual-auditory and motor-auditory events: An electrophysiological study

The amplitude of auditory components of the event-related potential (ERP) is attenuated when sounds are self-generated compared to externally generated sounds. This effect has been ascribed to internal forward modals predicting the sensory consequences of one's own motor actions. Auditory potentials are also attenuated when a sound is accompanied by a video of anticipatory visual motion that reliably predicts the sound. Here, we investigated whether the neural underpinnings of prediction of upcoming auditory stimuli are similar for motor-auditory (MA) and visual-auditory (VA) events using a stimulus omission paradigm. In the MA condition, a finger tap triggered the sound of a handclap whereas in the VA condition the same sound was accompanied by a video showing the handclap. In both conditions, the auditory stimulus was omitted in either 50% or 12% of the trials. These auditory omissions induced early and mid-latency ERP components (oN1 and oN2, presumably reflecting prediction and prediction error), and subsequent higher-order error evaluation processes. The oN1 and oN2 of MA and VA were alike in amplitude, topography, and neural sources despite that the origin of the prediction stems from different brain areas (motor versus visual cortex). This suggests that MA and VA predictions activate a sensory template of the sound in auditory cortex. This article is part of a Special Issue entitled SI: Prediction and Attention.

Neural correlates of perceptual grouping effects in the processing of sound omission by musicians and nonmusicians

Perceptual grouping is the process of organizing sounds into perceptually meaningful elements. Psychological studies have found that tones presented as a regular frequency or temporal pattern are grouped according to gestalt principles, such as similarity, proximity, and good continuity. Predictive coding theory suggests that this process helps create an internal model for the prediction of sounds in a tone sequence and that an omission-related brain response reflects the violation of this prediction. However, it remains unclear which brain areas are related to this process, especially in paying attention to the stimuli. To clarify this uncertainty, the present study investigated the neural correlates of perceptual grouping effects. Using magnetoencephalography (MEG), we recorded the evoked response fields (ERFs) of amateur musicians and nonmusicians to sound omissions in tone sequences with a regular or random pattern of three different frequencies during an omission detection task. Omissions in the regular sequences were detected faster and evoked greater activity in the left Heschl's gyrus (HG), right postcentral gyrus, and bilateral superior temporal gyrus (STG) than did omissions in the irregular sequences. Additionally, an interaction between musical experience and regularity was found in the left HG/STG. Tone-evoked responses did not show this difference, indicating that the expertise effect did not reflect the superior tone processing acquired by amateur musicians due to musical training. These results suggest that perceptual grouping based on repetition of a pattern of frequencies affects the processing of omissions in tone sequences and induces more activation of the bilateral auditory cortex by violating internal models. The interaction in the left HG/STG may suggest different styles of processing for musicians and nonmusicians, although this difference was not reflected at the behavioral level.

Rhythmic complexity and predictive coding: a novel approach to modeling rhythm and meter perception in music

Musical rhythm, consisting of apparently abstract intervals of accented temporal events, has a remarkable capacity to move our minds and bodies. How does the cognitive system enable our experiences of rhythmically complex music? In this paper, we describe some common forms of rhythmic complexity in music and propose the theory of predictive coding (PC) as a framework for understanding how rhythm and rhythmic complexity are processed in the brain. We also consider why we feel so compelled by rhythmic tension in music. First, we consider theories of rhythm and meter perception, which provide hierarchical and computational approaches to modeling. Second, we present the theory of PC, which posits a hierarchical organization of brain responses reflecting fundamental, survival-related mechanisms associated with predicting future events. According to this theory, perception and learning is manifested through the brain’s Bayesian minimization of the error between the input to the brain and the brain’s prior expectations. Third, we develop a PC model of musical rhythm, in which rhythm perception is conceptualized as an interaction between what is heard (“rhythm”) and the brain’s anticipatory structuring of music (“meter”). Finally, we review empirical studies of the neural and behavioral effects of syncopation, polyrhythm and groove, and propose how these studies can be seen as special cases of the PC theory. We argue that musical rhythm exploits the brain’s general principles of prediction and propose that pleasure and desire for sensorimotor synchronization from musical rhythm may be a result of such mechanisms.

Effect of changes in stimulus site on activation of the posterior parietal cortex

A previous functional magnetic resonance imaging study elucidated the specific activity of the inferior parietal lobe (IPL) during a two-point discrimination task compared with that during an intensity discrimination task Akatsuka et al. (Neuroimage 40: 852-858, 2008). If the posterior parietal cortex (PPC), including IPL, is responsible for detecting changes in stimulus sites, PPC activity depends on the level of change at stimulus sites. The aim of this study was to clarify whether a particular site exists that could detect changes in stimulus sites using the oddball paradigm. Somatosensory-evoked magnetic fields were recorded in 10 right-handed subjects. Three oddball conditions were performed by all subjects, with the probability of deviant and standard stimuli being 20 and 80 %, respectively, under all three conditions. Deviant stimuli were always presented to the second digit of the hand and standard stimuli were presented to the first (small deviance: SD) and fifth digits (medium deviance: MD) of the hand and the first digit of the toe (large deviance: LD). Inter-stimulus intervals were set at 500 ms. A brain electrical source analysis showed that activities of areas 1 and 3b elicited by the deviant stimuli were not significantly different among the three conditions. In contrast, PPC activity was significantly greater for LD than for SD and MD. PPC activity tended to increase with greater deviance at stimulus sites, but activities of areas 1 and 3b did not differ. These findings suggest that PPC may have a functional role in automatic change detection systems with regard to deviance of stimulus sites.

Prediction in the service of comprehension: modulated early brain responses to omitted speech segments

Speech signals are often compromised by disruptions originating from external (e.g., masking noise) or internal (e.g., inaccurate articulation) sources. Speech comprehension thus entails detecting and replacing missing information based on predictive and restorative neural mechanisms. The present study targets predictive mechanisms by investigating the influence of a speech segment's predictability on early, modality-specific electrophysiological responses to this segment's omission. Predictability was manipulated in simple physical terms in a single-word framework (Experiment 1) or in more complex semantic terms in a sentence framework (Experiment 2). In both experiments, final consonants of the German words Lachs ([laks], salmon) or Latz ([lats], bib) were occasionally omitted, resulting in the syllable La ([la], no semantic meaning), while brain responses were measured with multi-channel electroencephalography (EEG). In both experiments, the occasional presentation of the fragment La elicited a larger omission response when the final speech segment had been predictable. The omission response occurred ∼125-165 msec after the expected onset of the final segment and showed characteristics of the omission mismatch negativity (MMN), with generators in auditory cortical areas. Suggestive of a general auditory predictive mechanism at work, this main observation was robust against varying source of predictive information or attentional allocation, differing between the two experiments. Source localization further suggested the omission response enhancement by predictability to emerge from left superior temporal gyrus and left angular gyrus in both experiments, with additional experiment-specific contributions. These results are consistent with the existence of predictive coding mechanisms in the central auditory system, and suggestive of the general predictive properties of the auditory system to support spoken word recognition.

Change-related auditory P50: a MEG study

Changes in continuous sounds elicit a preattentive component that peaks at around 100ms (Change-N1m) on electroencephalograms or magnetoencephalograms (MEG). Change-N1m is thought to reflect brain activity relating to the automatic detection of changes, which facilitate processes for the execution of appropriate behavior in response to new environmental events. The aim of the present MEG study was to elucidate whether a component relating to auditory changes existed earlier than N1m. Change-related cortical responses were evoked by abrupt sound movement in a train of clicks at 100Hz. Sound movement was created by inserting an interaural time delay (ITD) of 0.15, 0.25, 0.35, and 0.45ms into the right ear. Ten out of 12 participants exhibited clear change-related cortical responses earlier than Change-N1m at around 60ms (Change-P50m). The results of source analysis showed that Change-P50m originated from the superior temporal gyrus of both hemispheres and that its location did not differ significantly from dipoles for the response to the sound onset. The magnitude of Change-P50m increased and the peak latency shortened with an increase in the ITD, similar to those of Change-N1m. These results suggest that change-related cortical activity is present as early as its onset latency at around 50ms.

Hearing silences: human auditory processing relies on preactivation of sound-specific brain activity patterns

The remarkable capabilities displayed by humans in making sense of an overwhelming amount of sensory information cannot be explained easily if perception is viewed as a passive process. Current theoretical and computational models assume that to achieve meaningful and coherent perception, the human brain must anticipate upcoming stimulation. But how are upcoming stimuli predicted in the brain? We unmasked the neural representation of a prediction by omitting the predicted sensory input. Electrophysiological brain signals showed that when a clear prediction can be formulated, the brain activates a template of its response to the predicted stimulus before it arrives to our senses.