Predictability-Based Source Segregation and Sensory Deviance Detection in Auditory Aging

When multiple sound sources are present at the same time, auditory perception is often challenged with disentangling the resulting mixture and focusing attention on the target source. It has been repeatedly demonstrated that background (distractor) sound sources are easier to ignore when their spectrotemporal signature is predictable. Prior evidence suggests that this ability to exploit predictability for foreground-background segregation degrades with age. On a theoretical level, this has been related with an impairment in elderly adults’ capabilities to detect certain types of sensory deviance in unattended sound sequences. Yet the link between those two capacities, deviance detection and predictability-based sound source segregation, has not been empirically demonstrated. Here we report on a combined behavioral-EEG study investigating the ability of elderly listeners (60–75 years of age) to use predictability as a cue for sound source segregation, as well as their sensory deviance detection capacities. Listeners performed a detection task on a target stream that can only be solved when a concurrent distractor stream is successfully ignored. We contrast two conditions whose distractor streams differ in their predictability. The ability to benefit from predictability was operationalized as performance difference between the two conditions. Results show that elderly listeners can use predictability for sound source segregation at group level, yet with a high degree of inter-individual variation in this ability. In a further, passive-listening control condition, we measured correlates of deviance detection in the event-related brain potential (ERP) elicited by occasional deviations from the same spectrotemporal pattern as used for the predictable distractor sequence during the behavioral task. ERP results confirmed neural signatures of deviance detection in terms of mismatch negativity (MMN) at group level. Correlation analyses at single-subject level provide no evidence for the hypothesis that deviance detection ability (measured by MMN amplitude) is related to the ability to benefit from predictability for sound source segregation. These results are discussed in the frameworks of sensory deviance detection and predictive coding.

Auditory, Visual, and Cross-Modal Mismatch Negativities in the Rat Auditory and Visual Cortices

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

Somatosensory Deviance Detection ERPs and Their Relationship to Analogous Auditory ERPs and Interoceptive Accuracy

Automatic deviance detection has been widely explored in terms of mismatch responses (mismatch negativity or mismatch response) and P3a components of event-related potentials (ERPs) under a predictive coding framework; however, the somatosensory mismatch response has been investigated less often regarding the different types of changes than its auditory counterpart. It is not known whether the deviance detection responses from different modalities correlate, reflecting a general prediction error mechanism of the central nervous system. Furthermore, interoceptive functions have been associated with predictive coding theory, but whether interoceptive accuracy correlates with deviance detection brain responses has rarely been investigated. Here, we measured ERPs to changes in somatosensory stimuli’s location and intensity and in sound intensity in healthy adults ( n = 34). Interoceptive accuracy was measured with a heartbeat discrimination task, where participants indicated whether their heartbeats were simultaneous or non-simultaneous with sound stimuli. We found a mismatch response and a P3a response to somatosensory location and auditory intensity changes, but for somatosensory intensity changes, only a P3a response was found. Unexpectedly, there were neither correlations between the somatosensory location deviance and intensity deviance brain responses nor between auditory and somatosensory brain responses. In addition, the brain responses did not correlate with interoceptive accuracy. The results suggest that although deviance detection in the auditory and somatosensory modalities are likely based on similar neural mechanisms at a cellular level, their ERP indexes do not indicate a linear association in sensitivity for deviance detection between the modalities. Furthermore, although sensory deviance detection and interoceptive detection are both associated with predictive coding functions, under these experimental settings, functional relationships were not observed. These results should be taken into account in the future development of theories related to human sensory functions and in extensions of the predictive coding theory in particular.

EEG-based visual deviance detection in freely behaving mice

The mouse is widely used as an experimental model to study visual processing. To probe how the visual system detects changes in the environment, functional paradigms in freely behaving mice are strongly needed. We developed and validated the first EEG-based method to investigate visual deviance detection in freely behaving mice. Mice with EEG implants were exposed to a visual deviant detection paradigm that involved changes in light intensity as standard and deviant stimuli. By subtracting the standard from the deviant evoked waveform, deviant detection was evident as bi-phasic negativity (starting around 70 ms) in the difference waveform. Additionally, deviance-associated evoked (beta/gamma) and induced (gamma) oscillatory responses were found. We showed that the results were stimulus independent by applying a 'flip-flop' design and the results showed good repeatability in an independent measurement. Together, we put forward a validated, easy-to-use paradigm to measure visual deviance processing in freely behaving mice.

A Critical Review of the Deviance Detection Theory of Mismatch Negativity

Mismatch negativity (MMN) is a component of the difference waveform derived from passive auditory oddball stimulation. Since its inception in 1978, this has become one of the most popular event-related potential techniques, with over two-thousand published studies using this method. This is a testament to the ingenuity and commitment of generations of researchers engaging in basic, clinical and animal research. Despite this intensive effort, high-level descriptions of the mechanisms theorized to underpin mismatch negativity have scarcely changed over the past four decades. The prevailing deviance detection theory posits that MMN reflects inattentive detection of difference between repetitive standard and infrequent deviant stimuli due to a mismatch between the unexpected deviant and a memory representation of the standard. Evidence for these mechanisms is inconclusive, and a plausible alternative sensory processing theory considers fundamental principles of sensory neurophysiology to be the primary source of differences between standard and deviant responses evoked during passive oddball stimulation. By frequently being restated without appropriate methods to exclude alternatives, the potentially flawed deviance detection theory has remained largely dominant, which could lead some researchers and clinicians to assume its veracity implicitly. It is important to have a more comprehensive understanding of the source(s) of MMN generation before its widespread application as a clinical biomarker. This review evaluates issues of validity concerning the prevailing theoretical account of mismatch negativity and the passive auditory oddball paradigm, highlighting several limitations regarding its interpretation and clinical application.