A symptom network model of misophonia: From heightened sensory sensitivity to clinical comorbidity.

OBJECTIVES: Misophonia-an unusually strong intolerance of certain sounds-can cause significant distress and disruption to those who have it but is an enigma in terms of our scientific understanding. A key challenge for explaining misophonia is that, as with other disorders, it is likely to emerge from an interaction of traits that also occur in the general population (e.g., sensory sensitivity and anxiety) and that are transdiagnostic in nature (i.e., shared with other disorders). METHODS: In this preregistered study with a large sample of participants (N = 1430), we performed a cluster analysis (based on responses to questions relating to misophonia) and identified two misophonia subgroups differing in severity, as well as a third group without misophonia. A subset of this sample (N = 419) then completed a battery of measures designed to assess sensory sensitivity and clinical comorbidities. RESULTS: Clinical symptoms were limited to the most severe group of misophonics (including autistic traits, migraine with visual aura, anxiety sensitivity, obsessive-compulsive traits). Both the moderate and severe groups showed elevated attention-to-detail and hypersensitivity (across multiple senses). A novel symptom network model of the data shows the presence of a central hub linking misophonia to sensory sensitivity which, in turn, connects to other symptoms in the network (relating to autism, anxiety, etc.). CONCLUSION: The core features of misophonia are sensory-attentional in nature with severity linked strongly to comorbidities.

A phenomenological cartography of misophonia and other forms of sound intolerance.

People with misophonia have strong aversive reactions to specific "trigger" sounds. Here we challenge this key idea of specificity. Machine learning was used to identify a misophonic profile from a multivariate sound-response pattern. Misophonia could be classified from most sounds (traditional triggers and non-triggers) and, moreover, cross-classification showed that the profile was largely transferable across sounds (rather than idiosyncratic for each sound). By splitting our participants in other ways, we were able to show-using the same approach-a differential diagnostic profile factoring in potential co-morbidities (autism, hyperacusis, ASMR). The broad autism phenotype was classified via aversions to repetitive sounds rather than the eating sounds most easily classified in misophonia. Within misophonia, the presence of hyperacusis and sound-induced pain had widespread effects across all sounds. Overall, we show that misophonia is characterized by a distinctive reaction to most sounds that ultimately becomes most noticeable for a sub-set of those sounds.

Forgetting across a hierarchy of episodic representations.

Rich episodic experiences are represented in a hierarchical manner across a diverse network of brain regions, and as such, the way in which episodes are forgotten is likely to be similarly diverse. Using novel experimental approaches and statistical modelling, recent research has suggested that item-based representations, such as ones related to the colour and shape of an object, fragment over time, whereas higher-order event-based representations may be forgotten in a more 'holistic' uniform manner. We propose a framework that reconciles these findings, where complex episodes are represented in a hierarchical manner, from individual items, to small-scale events, to large-scale episodic narratives. Each level in the hierarchy is represented in distinct brain regions, from the perirhinal cortex, to posterior hippocampus, to anterior hippocampus and ventromedial prefrontal cortex. Critically, forgetting may be underpinned by different mechanisms at each level in the hierarchy, leading to different patterns of behaviour.

Individual differences in the tendency to see the expected.

Prior knowledge has been shown to facilitate the incorporation of visual stimuli into awareness. We adopted an individual differences approach to explore whether a tendency to 'see the expected' is general or method-specific. We administered a binocular rivalry task and manipulated selective attention, as well as induced expectations via predictive context, self-generated imagery, expectancy cues, and perceptual priming. Most prior manipulations led to a facilitated awareness of the biased percept in binocular rivalry, whereas strong signal primes led to a suppressed awareness, i.e., adaptation. Correlations and factor analysis revealed that the facilitatory effect of priors on visual awareness is closely related to attentional control. We also investigated whether expectation-based biases predict perceptual abilities. Adaptation to strong primes predicted improved naturalistic change detection and the facilitatory effect of weak primes predicted the experience of perceptual anomalies. Taken together, our results indicate that the facilitatory effect of priors may be underpinned by an attentional mechanism but the tendency to 'see the expected' is method-specific.

Individual differences in change blindness are predicted by the strength and stability of visual representations.

The phenomenon of change blindness reveals that people are surprisingly poor at detecting unexpected visual changes; however, research on individual differences in detection ability is scarce. Predictive processing accounts of visual perception suggest that better change detection may be linked to assigning greater weight to prediction error signals, as indexed by an increased alternation rate in perceptual rivalry or greater sensitivity to low-level visual signals. Alternatively, superior detection ability may be associated with robust visual predictions against which sensory changes can be more effectively registered, suggesting an association with high-level mechanisms of visual short-term memory (VSTM) and attention. We administered a battery of 10 measures to explore these predictions and to determine, for the first time, the test-retest reliability of commonly used change detection measures. Change detection performance was stable over time and generalized from displays of static scenes to video clips. An exploratory factor analysis revealed two factors explaining performance across the battery, that we identify as visual stability (loading on change detection, attention measures, VSTM and perceptual rivalry) and visual ability (loading on iconic memory, temporal order judgments and contrast sensitivity). These results highlight the importance of strong, stable representations and the ability to resist distraction, in order to successfully incorporate unexpected changes into the contents of visual awareness.

Detailed and gist-like visual memories are forgotten at similar rates over the course of a week.

A number of recent studies have highlighted the exceptional capacity and fidelity of visual long-term memory. For instance, Brady, Konkle, Alvarez, and Oliva (Proceedings of the National Academy of Sciences, 105, 14325-14329, 2008) presented participants with thousands of images for nearly 6 h and then tested their memory in a two-alternative forced choice (2AFC) task. Participants were 87% accurate, even when the foil was extremely similar to the target (e.g., when the same object was presented in a different state). In the present investigation, we extended these findings by including a one-week delay condition and by testing memory in a yes-no as well as a 2AFC task. We replicated the exceptional memory results at a short delay. However, following a week delay, recognition accuracy was greatly reduced in both tasks, with comparable reductions in performance when the foils were both similar and dissimilar. These findings suggest that detailed and gist-like visual memories decay at similar rates, which highlights important limitations of visual long-term memory.