Order effects in task-free learning: Tuning to information-carrying sound features.

Event-related potentials (ERPs) acquired during task-free passive listening can be used to study how sensitivity to common pattern repetitions and rare deviations changes over time. These changes are purported to represent the formation and accumulation of precision in internal models that anticipate future states based on probabilistic and/or statistical learning. This study features an unexpected finding; a strong order-dependence in the speed with which deviant responses are elicited that anchors to first learning. Participants heard four repetitions of a sequence in which an equal number of short (30 msec) and long (60 msec) pure tones were arranged into four blocks in which one was common (the standard, p = .875) and the other rare (the deviant, p = .125) with probabilities alternating across blocks. Some participants always heard the sequences commencing with the 30 msec deviant block, and others always with the 60 msec deviant block first. A deviance-detection component known as mismatch negativity (MMN) was extracted from responses and the point in time at which MMN reached maximum amplitude was used as the dependent variable. The results show that if participants heard sequences commencing with the 60 msec deviant block first, the MMN to the 60 msec and 30 msec deviant peaked at an equivalent latency. However, if participants heard sequences commencing with the 30 msec deviant first, the MMN peaked earlier to the 60 msec deviant. Furthermore, while the 30 msec MMN latency did not differ as a function of sequence composition, the 60 msec MMN latency did and was earlier when the sequences began with a 30 msec deviant first. By examining MMN latency effects as a function of age and hearing level it was apparent that the differentiation in 30 msec and 60 msec MMN latency expands with older age and raised hearing threshold due to prolongation of the time taken for the 30 msec MMN to peak. The observations are discussed with reference to how the initial sound composition may tune the auditory system to be more sensitive to different cues (i.e., offset responses vs perceived loudness). The order-effect demonstrates a remarkably powerful anchoring to first learning that might reflect initial tuning to the most valuable discriminating feature within a given listening environment, an effect that defies explanation based on statistical information alone.

Delirium is associated with loss of feedback cortical connectivity.

INTRODUCTION: Post-operative delirium (POD) is associated with increased morbidity and mortality but is bereft of treatments, largely due to our limited understanding of the underlying pathophysiology. We hypothesized that delirium reflects a disturbance in cortical connectivity that leads to altered predictions of the sensory environment. METHODS: High-density electroencephalogram recordings during an oddball auditory roving paradigm were collected from 131 patients. Dynamic causal modeling (DCM) analysis facilitated inference about the neuronal connectivity and inhibition-excitation dynamics underlying auditory-evoked responses. RESULTS: Mismatch negativity amplitudes were smaller in patients with POD. DCM showed that delirium was associated with decreased left-sided superior temporal gyrus (l-STG) to auditory cortex feedback connectivity. Feedback connectivity also negatively correlated with delirium severity and systemic inflammation. Increased inhibition of l-STG, with consequent decreases in feed-forward and feed-back connectivity, occurred for oddball tones during delirium. DISCUSSION: Delirium is associated with decreased feedback cortical connectivity, possibly resulting from increased intrinsic inhibitory tone. HIGHLIGHTS: Mismatch negativity amplitude was reduced in patients with delirium. Patients with postoperative delirium had increased feedforward connectivity before surgery. Feedback connectivity was diminished from left-side superior temporal gyrus to left primary auditory sensory area during delirium. Feedback connectivity inversely correlated with inflammation and delirium severity.

Relationship between schematic and dynamic expectations of melodic patterns in music perception.

Prediction is fundamental in music listening. Two types of expectations have been proposed: schematic expectations, which arise from knowledge of tonal regularities (e.g., harmony and key) acquired through long-term plasticity and learning, and dynamic expectations, which arise from short-term regularity representations (e.g., rhythmic patterns and melodic contours) extracted from ongoing musical contexts. Although both expectations are indispensable in music listening, how they interact with each other in music prediction remains unclear. The present study examined the relationship between schematic and dynamic expectations in music processing using event-related potentials (ERPs). At the ending note of the melodies, the schematic expectation was violated by presenting a note with music-syntactic irregular (i.e., outof- key note), while the dynamic expectation was violated by presenting a contour deviant based on online statistical learning of melodic patterns. Schematic and dynamic expectations were manipulated to predict the same note. ERPs were recorded for the music-syntactic irregularity and the contour deviant, which occurred independently or simultaneously. The results showed that the music-syntactic irregularity elicited an early right anterior negativity (ERAN), reflecting the prediction error in the schematic expectation, while the contour deviant elicited a mismatch negativity (MMN), reflecting the prediction error in the dynamic expectation. Both components occurred within a similar latency range. Moreover, the ERP amplitude was multiplicatively increased when the irregularity and deviance occurred simultaneously. These findings suggest that schematic and dynamic expectations function concurrently in an interactive manner when both expectations predict the same note.

The pulvinar as a hub of visual processing and cortical integration.

The pulvinar nucleus of the thalamus is a crucial component of the visual system and plays significant roles in sensory processing and cognitive integration. The pulvinar's extensive connectivity with cortical regions allows for bidirectional communication, contributing to the integration of sensory information across the visual hierarchy. Recent findings underscore the pulvinar's involvement in attentional modulation, feature binding, and predictive coding. In this review, we highlight recent advances in clarifying the pulvinar's circuitry and function. We discuss the contributions of the pulvinar to signal modulation across the global cortical network and place these findings within theoretical frameworks of cortical processing, particularly the global neuronal workspace (GNW) theory and predictive coding.

Cognitive and sensory expectations independently shape musical expectancy and pleasure.

Expectation is crucial for our enjoyment of music, yet the underlying generative mechanisms remain unclear. While sensory models derive predictions based on local acoustic information in the auditory signal, cognitive models assume abstract knowledge of music structure acquired over the long term. To evaluate these two contrasting mechanisms, we compared simulations from four computational models of musical expectancy against subjective expectancy and pleasantness ratings of over 1000 chords sampled from 739 US Billboard pop songs. Bayesian model comparison revealed that listeners' expectancy and pleasantness ratings were predicted by the independent, non-overlapping, contributions of cognitive and sensory expectations. Furthermore, cognitive expectations explained over twice the variance in listeners' perceived surprise compared to sensory expectations, suggesting a larger relative importance of long-term representations of music structure over short-term sensory-acoustic information in musical expectancy. Our results thus emphasize the distinct, albeit complementary, roles of cognitive and sensory expectations in shaping musical pleasure, and suggest that this expectancy-driven mechanism depends on musical information represented at different levels of abstraction along the neural hierarchy. This article is part of the theme issue 'Art, aesthetics and predictive processing: theoretical and empirical perspectives'.

Mindfulness meditation and psychedelics: potential synergies and commonalities.

There has been increasing scientific and clinical interest in studying psychedelic and meditation-based interventions in recent years, both in the context of improving mental health and as tools for understanding the mind. Several authors suggest neurophysiological and phenomenological parallels and overlaps between psychedelic and meditative states and suggest synergistic effects of both methods. Both psychedelic-assisted therapy and meditation training in the form of mindfulness-based interventions have been experimentally validated with moderate to large effects as alternative treatments for a variety of mental health problems, including depression, addictions, and anxiety disorders. Both demonstrated significant post-acute and long-term decreases in clinical symptoms and enhancements in well-being in healthy participants, in addition. Postulated shared salutogenic mechanisms, include, among others the ability to alter self-consciousness, present-moment awareness and antidepressant action via corresponding neuromodulatory effects. These shared mechanisms between mindfulness training and psychedelic intervention have led to scientists theorizing, and recently demonstrating, positive synergistic effects when both are used in combination. Research findings suggest that these two approaches can complement each other, enhancing the positive effects of both interventions. However, more theoretical accounts and methodologically sound research are needed before they can be extended into clinical practice. The current review aims to discuss the theoretical rationale of combining psychedelics with mindfulness training, including the predictive coding framework as well as research findings regarding synergies and commonalities between mindfulness training and psychedelic intervention. In addition, suggestions how to combine the two modalities are provided.

Distinct roles of delta- and theta-band neural tracking for sharpening and predictive coding of multi-level speech features during spoken language processing.

The brain tracks and encodes multi-level speech features during spoken language processing. It is evident that this speech tracking is dominant at low frequencies (<8 Hz) including delta and theta bands. Recent research has demonstrated distinctions between delta- and theta-band tracking but has not elucidated how they differentially encode speech across linguistic levels. Here, we hypothesised that delta-band tracking encodes prediction errors (enhanced processing of unexpected features) while theta-band tracking encodes neural sharpening (enhanced processing of expected features) when people perceive speech with different linguistic contents. EEG responses were recorded when normal-hearing participants attended to continuous auditory stimuli that contained different phonological/morphological and semantic contents: (1) real-words, (2) pseudo-words and (3) time-reversed speech. We employed multivariate temporal response functions to measure EEG reconstruction accuracies in response to acoustic (spectrogram), phonetic and phonemic features with the partialling procedure that singles out unique contributions of individual features. We found higher delta-band accuracies for pseudo-words than real-words and time-reversed speech, especially during encoding of phonetic features. Notably, individual time-lag analyses showed that significantly higher accuracies for pseudo-words than real-words started at early processing stages for phonetic encoding (<100 ms post-feature) and later stages for acoustic and phonemic encoding (>200 and 400 ms post-feature, respectively). Theta-band accuracies, on the other hand, were higher when stimuli had richer linguistic content (real-words > pseudo-words > time-reversed speech). Such effects also started at early stages (<100 ms post-feature) during encoding of all individual features or when all features were combined. We argue these results indicate that delta-band tracking may play a role in predictive coding leading to greater tracking of pseudo-words due to the presence of unexpected/unpredicted semantic information, while theta-band tracking encodes sharpened signals caused by more expected phonological/morphological and semantic contents. Early presence of these effects reflects rapid computations of sharpening and prediction errors. Moreover, by measuring changes in EEG alpha power, we did not find evidence that the observed effects can be solitarily explained by attentional demands or listening efforts. Finally, we used directed information analyses to illustrate feedforward and feedback information transfers between prediction errors and sharpening across linguistic levels, showcasing how our results fit with the hierarchical Predictive Coding framework. Together, we suggest the distinct roles of delta and theta neural tracking for sharpening and predictive coding of multi-level speech features during spoken language processing.

Longitudinal Evidence for Attenuated Local-Global Deviance Detection as a Precursor of Working Memory Decline.

From the perspective of predictive coding, normal aging is accompanied by decreased weighting of sensory inputs and increased reliance on predictions, resulting in the attenuation of prediction errors in older age. Recent electroencephalography (EEG) research further revealed that the age-related shift from sensorium to predictions is hierarchy-selective, as older brains show little reduction in lower-level but significant suppression in higher-level prediction errors. Moreover, the disrupted propagation of prediction errors from the lower-level to the higher-level seems to be linked to deficient maintenance of information in working memory. However, it is unclear whether the hierarchical predictive processing continues to decline with advancing age as working memory. Here, we longitudinally followed a sample of 78 participants from three age groups (including seniors, adults, and adolescents) over three years' time. Seniors exhibited largely preserved local processing [consisting of comparable mismatch negativity (MMN), delayed P3a, and comparable reorienting negativity (RON)] but significantly compromised global processing (consisting of suppressed frontocentral negativity and suppressed P3b) in the auditory local-global paradigm. These electrophysiological responses did not change with the passing of time, unlike working memory which deteriorated with advancing age. Correlation analysis further showed that these electrophysiological responses signaling prediction errors are indicative of concurrent working memory. Moreover, there was a correlation between earlier predictive processing and later working memory but not between earlier working memory and later predictive processing. The temporal asymmetry suggested that the hierarchy-selective attenuation of prediction errors is likely a precursor of working memory decline.

Neurobiological mechanisms of dialectical behavior therapy and Morita therapy, two psychotherapies inspired by Zen.

Psychotherapy is a learning process. Updating the prediction models of the brain may be the mechanism underlying psychotherapeutic changes. Although developed in different eras and cultures, dialectical behavior therapy (DBT) and Morita therapy are influenced by Zen principles, and both emphasize the acceptance of reality and suffering. This article reviews these two treatments, their common and distinct therapeutic factors, and their neuroscientific implications. Additionally, it proposes a framework that includes the predictive function of the mind, constructed emotions, mindfulness, therapeutic relationship, and changes enabled via reward predictions. Brain networks, including the Default Mode Network (DMN), amygdala, fear circuitry, and reward pathways, contribute to the constructive process of brain predictions. Both treatments target the assimilation of prediction errors, gradual reorganization of predictive models, and creation of a life with step-by-step constructive rewards. By elucidating the possible neurobiological mechanisms of these psychotherapeutic techniques, this article is expected to serve as the first step towards filling the cultural gap and creating more teaching methods based on these concepts.

Temporal hierarchies in the predictive processing of melody - From pure tones to songs.

Listening to musical melodies is a complex task that engages perceptual and memoryrelated processes. The processes underlying melody cognition happen simultaneously on different timescales, ranging from milliseconds to minutes. Although attempts have been made, research on melody perception is yet to produce a unified framework of how melody processing is achieved in the brain. This may in part be due to the difficulty of integrating concepts such as perception, attention and memory, which pertain to different temporal scales. Recent theories on brain processing, which hold prediction as a fundamental principle, offer potential solutions to this problem and may provide a unifying framework for explaining the neural processes that enable melody perception on multiple temporal levels. In this article, we review empirical evidence for predictive coding on the levels of pitch formation, basic pitch-related auditory patterns,more complex regularity processing extracted from basic patterns and long-term expectations related to musical syntax. We also identify areas that would benefit from further inquiry and suggest future directions in research on musical melody perception.

Preterm neonates distinguish rhythm violation through a hierarchy of cortical processing.

Rhythm is a fundamental component of the auditory world, present even during the prenatal life. While there is evidence that some auditory capacities are already present before birth, whether and how the premature neural networks process auditory rhythm is yet not known. We investigated the neural response of premature neonates at 30-34 weeks gestational age to violations from rhythmic regularities in an auditory sequence using high-resolution electroencephalography and event-related potentials. Unpredicted rhythm violations elicited a fronto-central mismatch response, indicating that the premature neonates detected the rhythmic regularities. Next, we examined the cortical effective connectivity underlying the elicited mismatch response using dynamic causal modeling. We examined the connectivity between cortical sources using a set of 16 generative models that embedded alternate hypotheses about the role of the frontal cortex as well as backward fronto-temporal connection. Our results demonstrated that the processing of rhythm violations was not limited to the primary auditory areas, and as in the case of adults, encompassed a hierarchy of temporo-frontal cortical structures. The result also emphasized the importance of top-down (backward) projections from the frontal cortex in explaining the mismatch response. Our findings demonstrate a sophisticated cortical structure underlying predictive rhythm processing at the onset of the thalamocortical and cortico-cortical circuits, two months before term.

Sensory Target Detection at Local and Global Timescales Reveals a Hierarchy of Supramodal Dynamics in the Human Cortex.

To ensure survival in a dynamic environment, the human neocortex monitors input streams from different sensory organs for important sensory events. Which principles govern whether different senses share common or modality-specific brain networks for sensory target detection? We examined whether complex targets evoke sustained supramodal activity while simple targets rely on modality-specific networks with short-lived supramodal contributions. In a series of hierarchical multisensory target detection studies (n = 77, of either sex) using EEG, we applied a temporal cross-decoding approach to dissociate supramodal and modality-specific cortical dynamics elicited by rule-based global and feature-based local sensory deviations within and between the visual, somatosensory, and auditory modality. Our data show that each sense implements a cortical hierarchy orchestrating supramodal target detection responses, which operate at local and global timescales in successive processing stages. Across different sensory modalities, simple feature-based sensory deviations presented in temporal vicinity to a monotonous input stream triggered a mismatch negativity-like local signal which decayed quickly and early, whereas complex rule-based targets tracked across time evoked a P3b-like global neural response which generalized across a late time window. Converging results from temporal cross-modality decoding analyses across different datasets, we reveal that global neural responses are sustained in a supramodal higher-order network, whereas local neural responses canonically thought to rely on modality-specific regions evolve into short-lived supramodal activity. Together, our findings demonstrate that cortical organization largely follows a gradient in which short-lived modality-specific as well as supramodal processes dominate local responses, whereas higher-order processes encode temporally extended abstract supramodal information fed forward from modality-specific cortices.SIGNIFICANCE STATEMENT Each sense supports a cortical hierarchy of processes tracking deviant sensory events at multiple timescales. Conflicting evidence produced a lively debate around which of these processes are supramodal. Here, we manipulated the temporal complexity of auditory, tactile, and visual targets to determine whether cortical local and global ERP responses to sensory targets share cortical dynamics between the senses. Using temporal cross-decoding, we found that temporally complex targets elicit a supramodal sustained response. Conversely, local responses to temporally confined targets typically considered modality-specific rely on early short-lived supramodal activation. Our finding provides evidence for a supramodal gradient supporting sensory target detection in the cortex, with implications for multiple fields in which these responses are studied (e.g., predictive coding, consciousness, and attention).

Recurrent Neural Network Model of Human Event-related Potentials in Response to Intensity Oddball Stimulation.

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.

Consider the pons: bridging the gap on sensory prediction abnormalities in schizophrenia.

A shared mechanism across species heralds the arrival of self-generated sensations, helping the brain to anticipate, and therefore distinguish, self-generated from externally generated sensations. In mammals, this sensory prediction mechanism is supported by communication within a cortico-ponto-cerebellar-thalamo-cortical loop. Schizophrenia is associated with impaired sensory prediction as well as abnormal structural and functional connections between nodes in this circuit. Despite the pons' principal role in relaying and processing sensory information passed from the cortex to cerebellum, few studies have examined pons connectivity in schizophrenia. Here, we first briefly describe how the pons contributes to sensory prediction. We then summarize schizophrenia-related abnormalities in the cortico-ponto-cerebellar-thalamo-cortical loop, emphasizing the dearth of research on the pons relative to thalamic and cerebellar connections. We conclude with recommendations for advancing our understanding of how the pons relates to sensory prediction failures in schizophrenia.

Motor learning without movement.

Prediction errors guide many forms of learning, providing teaching signals that help us improve our performance. Implicit motor adaptation, for instance, is thought to be driven by sensory prediction errors (SPEs), which occur when the expected and observed consequences of a movement differ. Traditionally, SPE computation is thought to require movement execution. However, recent work suggesting that the brain can generate sensory predictions based on motor imagery or planning alone calls this assumption into question. Here, by measuring implicit motor adaptation during a visuomotor task, we tested whether motor planning and well-timed sensory feedback are sufficient for adaptation. Human participants were cued to reach to a target and were, on a subset of trials, rapidly cued to withhold these movements. Errors displayed both on trials with and without movements induced single-trial adaptation. Learning following trials without movements persisted even when movement trials had never been paired with errors and when the direction of movement and sensory feedback trajectories were decoupled. These observations indicate that the brain can compute errors that drive implicit adaptation without generating overt movements, leading to the adaptation of motor commands that are not overtly produced.

Increased context adjustment is associated with auditory sensitivities but not with autistic traits.

Bayesian models of autism suggest that alterations in context-sensitive prediction error weighting may underpin sensory perceptual alterations, such as hypersensitivities. We used an auditory oddball paradigm with pure tones arising from high or low uncertainty contexts to determine whether autistic individuals display differences in context adjustment relative to neurotypicals. We did not find group differences in early prediction error responses indexed by mismatch negativity. A dimensional approach revealed a positive correlation between context-dependent prediction errors and subjective reports of auditory sensitivities, but not with autistic traits. These findings suggest that autism studies may benefit from accounting for sensory sensitivities in group comparisons. LAY SUMMARY: We aimed to understand if autistic and non-autistic groups showed differences in their electrical brain activity measured by electroencephalography (EEG) when listening to surprising tones infrequently embedded in a statistical pattern. We found no differences between the autistic and the non-autistic group in their EEG response to the surprising sound even if the pattern switched, indicating their ability to learn a pattern. We did find that, as subjective sensory sensitivities (but not autistic traits) increased, there were increasingly large differences between the EEG responses to surprising tones that were embedded in the different statistical patterns of tones. These findings show that perceptual alterations may be a function of sensory sensitivities, but not necessarily autistic traits. We suggest that future EEG studies in autism may benefit from accounting for sensory sensitivities.

Late N1 and postimperative negative variation analysis depending on the previous trial history in paradigms of increasing auditory complexity.

Predictive coding reflects the ability of the human brain to extract environmental patterns in order to reformulate previous expectations. The present report analyzes through the late N1 auditory component and the postimperative negative variation (PINV) the updating of predictions regarding the characteristics of a new trial, depending on the previous trial history, complexity, and type of trial (standard or deviant). Data were obtained from 31 healthy subjects recorded in a previous study based on two paradigms composed of stimulus sequences of decreasing or increasing frequencies intermingled with the sporadic appearance of unexpected tone endings. Our results showed a higher amplitude for the most complex condition and deviant trials for both the late N1 and PINV components. Additionally, the N1 and PINV presented a different amplitude response to the standard and deviant trials as a function of previous trial history, suggesting a continuous updating of trial categorization. The results suggest that the late N1 and PINV components are involved in the generation of an internal model about the rules of external auditory stimulation.NEW & NOTEWORTHY The present study showed a higher amplitude for the late N1 and the PINV with reference to both the prediction performed in auditory paradigms of higher abstraction and the unexpected breaking of the extracted rules. Additionally, both components were modulated depending on the local probability, which would suggest that they are continuously being updated by the previous stimulus history.

Reduced Primacy Bias in Autism during Early Sensory Processing.

Recent theories of autism propose that a core deficit in autism would be a less context-sensitive weighting of prediction errors. There is also first support for this hypothesis on an early sensory level. However, an open question is whether this decreased context sensitivity is caused by faster updating of one's model of the world (i.e., higher weighting of new information), proposed by predictive coding theories, or slower model updating. Here, we differentiated between these two hypotheses by investigating how first impressions shape the mismatch negativity (MMN), reflecting early sensory prediction error processing. An autism and matched control group of human adults (both n = 27, 8 female) were compared on the multi-timescale MMN paradigm, in which tones were presented that were either standard (frequently occurring) or deviant (rare), and these roles reversed every block. A well-replicated observation is that the initial model (i.e., the standard and deviant sound in the first block) influences MMN amplitudes in later blocks. If autism is characterized by faster model updating, and thus a smaller primacy bias, we hypothesized (and demonstrate using a simple reinforcement learning model) that their MMN amplitudes should be less influenced by the initial context. In line with this hypothesis, we found that MMN responses in the autism group did not differ between the initial deviant and initial standard sounds as they did in the control group. These findings are consistent with the idea that autism is characterized by faster model updating during early sensory processing, as proposed by predictive coding accounts of autism.SIGNIFICANCE STATEMENT Recent theories of autism propose that a core deficit in autism is that they are faster to update their models of the world based on new sensory information. Here, we tested this hypothesis by investigating how first impressions shape brain responses during early sensory processing, and hypothesized that individuals with autism would be less influenced by these first impressions. In line with earlier studies, our results show that early sensory processing was influenced by first impressions in a control group. However, this was not the case in an autism group. This suggests that individuals with autism are faster to abandon their initial model, and is consistent with the proposal that they are faster to update their models of the world.

Corticofugal regulation of predictive coding.

Sensory systems must account for both contextual factors and prior experience to adaptively engage with the dynamic external environment. In the central auditory system, neurons modulate their responses to sounds based on statistical context. These response modulations can be understood through a hierarchical predictive coding lens: responses to repeated stimuli are progressively decreased, in a process known as repetition suppression, whereas unexpected stimuli produce a prediction error signal. Prediction error incrementally increases along the auditory hierarchy from the inferior colliculus (IC) to the auditory cortex (AC), suggesting that these regions may engage in hierarchical predictive coding. A potential substrate for top-down predictive cues is the massive set of descending projections from the AC to subcortical structures, although the role of this system in predictive processing has never been directly assessed. We tested the effect of optogenetic inactivation of the auditory cortico-collicular feedback in awake mice on responses of IC neurons to stimuli designed to test prediction error and repetition suppression. Inactivation of the cortico-collicular pathway led to a decrease in prediction error in IC. Repetition suppression was unaffected by cortico-collicular inactivation, suggesting that this metric may reflect fatigue of bottom-up sensory inputs rather than predictive processing. We also discovered populations of IC units that exhibit repetition enhancement, a sequential increase in firing with stimulus repetition. Cortico-collicular inactivation led to a decrease in repetition enhancement in the central nucleus of IC, suggesting that it is a top-down phenomenon. Negative prediction error, a stronger response to a tone in a predictable rather than unpredictable sequence, was suppressed in shell IC units during cortico-collicular inactivation. These changes in predictive coding metrics arose from bidirectional modulations in the response to the standard and deviant contexts, such that the units in IC responded more similarly to each context in the absence of cortical input. We also investigated how these metrics compare between the anesthetized and awake states by recording from the same units under both conditions. We found that metrics of predictive coding and deviance detection differ depending on the anesthetic state of the animal, with negative prediction error emerging in the central IC and repetition enhancement and prediction error being more prevalent in the absence of anesthesia. Overall, our results demonstrate that the AC provides cues about the statistical context of sound to subcortical brain regions via direct feedback, regulating processing of both prediction and repetition.

The sound of silence: Predictive error responses to unexpected sound omission in adults.

The human auditory system excels at detecting patterns needed for processing speech and music. According to predictive coding, the brain predicts incoming sounds, compares predictions to sensory input and generates a prediction error whenever a mismatch between the prediction and sensory input occurs. Predictive coding can be indexed in electroencephalography (EEG) with the mismatch negativity (MMN) and P3a, two components of event-related potentials (ERP) that are elicited by infrequent deviant sounds (e.g., differing in pitch, duration and loudness) in a stream of frequent sounds. If these components reflect prediction error, they should also be elicited by omitting an expected sound, but few studies have examined this. We compared ERPs elicited by infrequent randomly occurring omissions (unexpected silences) in tone sequences presented at two tones per second to ERPs elicited by frequent, regularly occurring omissions (expected silences) within a sequence of tones presented at one tone per second. We found that unexpected silences elicited significant MMN and P3a, although the magnitude of these components was quite small and variable. These results provide evidence for hierarchical predictive coding, indicating that the brain predicts silences and sounds.