Altering the primacy bias-How does a prior task affect mismatch negativity?

Deviants violating higher-order auditory regularities can become predictive and facilitate behaviour

The human auditory system is believed to represent regularities inherent in auditory information in internal models. Sounds not matching the standard regularity (deviants) elicit prediction error, alerting the system to information not explainable within currently active models. Here, we examine the widely neglected characteristic of deviants bearing predictive information themselves. In a modified version of the oddball paradigm, using higher-order regularities, we set up different expectations regarding the sound following a deviant. Higher-order regularities were defined by the relation of pitch within tone pairs (rather than absolute pitch of individual tones). In a deviant detection task participants listened to oddball sequences including two deviant types following diametrically opposed rules: one occurred mostly in succession (high repetition probability) and the other mostly in isolation (low repetition probability). Participants in Experiment 1 were not informed (naïve), whereas in Experiment 2 they were made aware of the repetition rules. Response times significantly decreased from first to second deviant when repetition probability was high-albeit more in the presence of explicit rule knowledge. There was no evidence of a facilitation effect when repetition probability was low. Significantly more false alarms occurred in response to standards following high compared with low repetition probability deviants, but only in participants aware of the repetition rules. These findings provide evidence that not only deviants violating lower- but also higher-order regularities can inform predictions about auditory events. More generally, they confirm the utility of this new paradigm to gather further insights into the predictive properties of the human brain.

Shorter Contextual Timescale Rather Than Memory Deficit in Aging

Many aspects of cognitive ability and brain function that change as we age look like deficits on account of measurable differences in comparison to younger adult groups. One such difference occurs in auditory sensory responses that index perceptual learning. Meta-analytic findings show reliable age-related differences in auditory responses to repetitive patterns of sound and to rare violations of those patterns, variously attributed to deficits in auditory sensory memory and inhibition. Here, we determine whether proposed deficits would render older adults less prone to primacy effects, robustly observed in young adults, which present as a tendency for first learning to have a disproportionate influence over later perceptual inference. The results confirm this reduced sensitivity to primacy effects but do not support impairment in auditory sensory memory as the origin of this difference. Instead, the aging brain produces data consistent with shorter timescales of contextual reference. In conclusion, age-related differences observed previously for perceptual inference appear highly context-specific necessitating reconsideration of whether and to what function the notion of deficit should be attributed, and even whether the notion of deficit is appropriate at all.

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.

Context is everything: How context shapes modulations of responses to unattended sound

The concept of perceptual inferences taking place over multiple timescales simultaneously raises questions about how the brain can balance the demands of remaining sensitive to local rarity while utilising more global longer-term predictability to modulate cortical responses. In the present study auditory evoked potentials to four presentations of the same sound sequence containing predictable structure on a local (milliseconds to seconds) and more global (many minutes) timescales were recorded. The results from 33 participants are used to demonstrate that predictions about both local (internal predictive models) and global (meta-models that define expected precisions associated with familiar internal model states) regularities are formed. The study exposes more local context-based modulations of the P1 but more global order-based modulations of the auditory evoked N2 components. The results are discussed in terms of theoretical links advocating that uncertainty at multiple timescales could lead to differential component modulations, and the importance of considering the broader learning context in auditory evoked potential studies.

Abstractness of human speech sound representations

We argue, based on a study of brain responses to speech sound differences in Japanese, that memory encoding of functional speech sounds-phonemes-are highly abstract. As an example, we provide evidence for a theory where the consonants/p t k b d g/ are not only made up of symbolic features but are underspecified with respect to voicing or laryngeal features, and that languages differ with respect to which feature value is underspecified. In a previous study we showed that voiced stops are underspecified in English [Hestvik, A., & Durvasula, K. (2016). Neurobiological evidence for voicing underspecification in English. Brain and Language], as shown by asymmetries in Mismatch Negativity responses to /t/ and /d/. In the current study, we test the prediction that the opposite asymmetry should be observed in Japanese, if voiceless stops are underspecified in that language. Our results confirm this prediction. This matches a linguistic architecture where phonemes are highly abstract and do not encode actual physical characteristics of the corresponding speech sounds, but rather different subsets of abstract distinctive features.

Making Sense of Mismatch Negativity

Evoked potentials provide valuable insight into brain processes that are integral to our ability to interact effectively and efficiently in the world. The mismatch negativity (MMN) component of the evoked potential has proven highly informative on the ways in which sensitivity to regularity contributes to perception and cognition. This review offers a compendium of research on MMN with a view to scaffolding an appreciation for its use as a tool to explore the way regularities contribute to predictions about the sensory environment over many timescales. In compiling this work, interest in MMN as an index of sensory encoding and memory are addressed, as well as attention. Perspectives on the possible underlying computational processes are reviewed as well as recent observations that invite consideration of how MMN relates to how we learn, what we learn, and why.

Time as context: The influence of hierarchical patterning on sensory inference

Time, or more specifically temporal structure, is a critical variable in understanding how the auditory system uses acoustic patterns to predict input, and to filter events based on their relevance. A key index of this filtering process is the auditory evoked potential component known as mismatch negativity or MMN. In this paper we review findings of smaller MMN in schizophrenia through the lens of time as an influential contextual variable. More specifically, we review studies that show how MMN to a locally rare pattern-deviation is modulated by the longer-term context in which it occurs. Empirical data is presented from a non-clinical sample confirming that the absence of a stable higher-order structure to sound sequences alters the way MMN amplitude changes over time. This result is discussed in relation to how hierarchical pattern learning might enrich our understanding of how and why MMN amplitude modulation is disrupted in schizophrenia.

Statistical learning leads to persistent memory: Evidence for one-year consolidation

Statistical learning is a robust mechanism of the brain that enables the extraction of environmental patterns, which is crucial in perceptual and cognitive domains. However, the dynamical change of processes underlying long-term statistical memory formation has not been tested in an appropriately controlled design. Here we show that a memory trace acquired by statistical learning is resistant to inference as well as to forgetting after one year. Participants performed a statistical learning task and were retested one year later without further practice. The acquired statistical knowledge was resistant to interference, since after one year, participants showed similar memory performance on the previously practiced statistical structure after being tested with a new statistical structure. These results could be key to understand the stability of long-term statistical knowledge.

Initial uncertainty impacts statistical learning in sound sequence processing

This paper features two studies confirming a lasting impact of first learning on how subsequent experience is weighted in early relevance-filtering processes. In both studies participants were exposed to sequences of sound that contained a regular pattern on two different timescales. Regular patterning in sound is readily detected by the auditory system and used to form "prediction models" that define the most likely properties of sound to be encountered in a given context. The presence and strength of these prediction models is inferred from changes in automatically elicited components of auditory evoked potentials. Both studies employed sound sequences that contained both a local and longer-term pattern. The local pattern was defined by a regular repeating pure tone occasionally interrupted by a rare deviating tone (p=0.125) that was physically different (a 30msvs. 60ms duration difference in one condition and a 1000Hz vs. 1500Hz frequency difference in the other). The longer-term pattern was defined by the rate at which the two tones alternated probabilities (i.e., the tone that was first rare became common and the tone that was first common became rare). There was no task related to the tones and participants were asked to ignore them while focussing attention on a movie with subtitles. Auditory-evoked potentials revealed long lasting modulatory influences based on whether the tone was initially encountered as rare and unpredictable or common and predictable. The results are interpreted as evidence that probability (or indeed predictability) assigns a differential information-value to the two tones that in turn affects the extent to which prediction models are updated and imposed. These effects are exposed for both common and rare occurrences of the tones. The studies contribute to a body of work that reveals that probabilistic information is not faithfully represented in these early evoked potentials and instead exposes that predictability (or conversely uncertainty) may trigger value-based learning modulations even in task-irrelevant incidental learning.

Is it time to move mismatch negativity into the clinic?

Since its inception in the 1970s, the mismatch negativity (MMN) event-related potential has improved our understanding of pre-attentive detection of rule violations, which is a fundamental cognitive process considered by some a form of "primitive intelligence". The body of research to date ranges from animal studies (i.e. when investigating the neural mechanisms and pharmacological properties of MMN generation) to researching the psychophysiological nature of human consciousness. MMN therefore offers the possibility to detect abnormal functioning in the neural system involved in MMN generation, such as it occurs in some neurodevelopmental disorders or patients in vegetative state. While the clinical research data holds considerable promise for translation into clinical practice, standardization and normative data of an optimized (i.e. disorder-specific) MMN recording algorithm is needed in order for MMN to become a valuable clinical investigation tool.

Auditory perceptual objects as generative models: Setting the stage for communication by sound

Communication by sounds requires that the communication channels (i.e. speech/speakers and other sound sources) had been established. This allows to separate concurrently active sound sources, to track their identity, to assess the type of message arriving from them, and to decide whether and when to react (e.g., reply to the message). We propose that these functions rely on a common generative model of the auditory environment. This model predicts upcoming sounds on the basis of representations describing temporal/sequential regularities. Predictions help to identify the continuation of the previously discovered sound sources to detect the emergence of new sources as well as changes in the behavior of the known ones. It produces auditory event representations which provide a full sensory description of the sounds, including their relation to the auditory context and the current goals of the organism. Event representations can be consciously perceived and serve as objects in various cognitive operations.

How does the extraction of local and global auditory regularities vary with context?

How does the human brain extract regularities from its environment? There is evidence that short range or ‘local’ regularities (within seconds) are automatically detected by the brain while long range or ‘global’ regularities (over tens of seconds or more) require conscious awareness. In the present experiment, we asked whether participants' attention was needed to acquire such auditory regularities, to detect their violation or both. We designed a paradigm in which participants listened to predictable sounds. Subjects could be distracted by a visual task at two moments: when they were first exposed to a regularity or when they detected violations of this regularity. MEG recordings revealed that early brain responses (100–130 ms) to violations of short range regularities were unaffected by visual distraction and driven essentially by local transitional probabilities. Based on global workspace theory and prior results, we expected that visual distraction would eliminate the long range global effect, but unexpectedly, we found the contrary, i.e. late brain responses (300–600 ms) to violations of long range regularities on audio-visual trials but not on auditory only trials. Further analyses showed that, in fact, visual distraction was incomplete and that auditory and visual stimuli interfered in both directions. Our results show that conscious, attentive subjects can learn the long range dependencies present in auditory stimuli even while performing a visual task on synchronous visual stimuli. Furthermore, they acquire a complex regularity and end up making different predictions for the very same stimulus depending on the context (i.e. absence or presence of visual stimuli). These results suggest that while short-range regularity detection is driven by local transitional probabilities between stimuli, the human brain detects and stores long-range regularities in a highly flexible, context dependent manner.

Mismatch negativity (MMN) to pitch change is susceptible to order-dependent bias

Pattern learning facilitates prediction about upcoming events. Within the auditory system such predictions can be studied by examining effects on a component of the auditory-evoked potential known as mismatch negativity (MMN). MMN is elicited when sound does not conform to the characteristics inferred from statistical probabilities derived from the recent past. Stable patterning in sequences elevates confidence in automatically generated perceptual inferences about what sound should come next and when. MMN amplitude should be larger when sequence is highly stable compared to when it is more volatile. This expectation has been tested using a multi-timescale paradigm. In this study, two sounds of different duration alternate roles as a predictable repetitive “standard” and rare MMN-eliciting “deviation.” The paradigm consists of sound sequences that differ in the rate at which the roles of two tones alternate, varying from slowly changing (high stability) to rapidly alternating (low stability). Previous studies using this paradigm discovered a “primacy bias” affecting how stability in patterning impacts MMN amplitude. The primacy bias refers to the observation that the effect of longer-term stability within sequences only appears to impact MMN to the sound first encountered as deviant (the sound that is rare when the sequence commences). This study determines whether this order-driven bias generalizes to sequences that contain two tones differing in pitch. By manipulating (within-subjects) the order in which sounds are encountered as deviants the data demonstrate the two defining characteristics of primacy bias: (1) sequence stability only ever impacts MMN amplitude to the first-deviant sound; and (2) within higher stability sequences, MMN is significantly larger when a sound is the first compared to when it is the second deviant. The results are consistent with a general order-driven bias exerting modulating effects on MMN amplitude over a longer timescale.