Sensory Prediction Errors Are Less Modulated by Global Context in Autism Spectrum Disorder

Development of a Self-Report Measure of Prediction in Daily Life: The Prediction-Related Experiences Questionnaire

PURPOSE

Predictions are complex, multisensory, and dynamic processes involving real-time adjustments based on environmental inputs. Disruptions to prediction abilities have been proposed to underlie characteristics associated with autism. While there is substantial empirical literature related to prediction, the field lacks a self-assessment measure of prediction skills related to daily tasks. Such a measure would be useful to better understand the nature of day-to-day prediction-related activities and characterize these abilities in individuals who struggle with prediction.

METHODS

An interdisciplinary mixed-methods approach was utilized to develop and validate a self-report questionnaire of prediction skills for adults, the Prediction-Related Experiences Questionnaire (PRE-Q). Two rounds of online field testing were completed in samples of autistic and neurotypical (NT) adults. Qualitative feedback from a subset of these participants regarding question content and quality was integrated and Rasch modeling of the item responses was applied.

RESULTS

The final PRE-Q includes 19 items across 3 domains (Sensory, Motor, Social), with evidence supporting the validity of the measure's 4-point response categories, internal structure, and relationship to other outcome measures associated with prediction. Consistent with models of prediction challenges in autism, autistic participants indicated more prediction-related difficulties than the NT group.

CONCLUSIONS

This study provides evidence for the validity of a novel self-report questionnaire designed to measure the day-to-day prediction skills of autistic and non-autistic adults. Future research should focus on characterizing the relationship between the PRE-Q and lab-based measures of prediction, and understanding how the PRE-Q may be used to identify potential areas for clinical supports for individuals with prediction-related challenges.

Predictive processing of music and language in autism: Evidence from Mandarin and English speakers

Atypical predictive processing has been associated with autism across multiple domains, based mainly on artificial antecedents and consequents. As structured sequences where expectations derive from implicit learning of combinatorial principles, language and music provide naturalistic stimuli for investigating predictive processing. In this study, we matched melodic and sentence stimuli in cloze probabilities and examined musical and linguistic prediction in Mandarin- (Experiment 1) and English-speaking (Experiment 2) autistic and non-autistic individuals using both production and perception tasks. In the production tasks, participants listened to unfinished melodies/sentences and then produced the final notes/words to complete these items. In the perception tasks, participants provided expectedness ratings of the completed melodies/sentences based on the most frequent notes/words in the norms. While Experiment 1 showed intact musical prediction but atypical linguistic prediction in autism in the Mandarin sample that demonstrated imbalanced musical training experience and receptive vocabulary skills between groups, the group difference disappeared in a more closely matched sample of English speakers in Experiment 2. These findings suggest the importance of taking an individual differences approach when investigating predictive processing in music and language in autism, as the difficulty in prediction in autism may not be due to generalized problems with prediction in any type of complex sequence processing.

Probabilistic Learning of Cue-Outcome Associations is not Influenced by Autistic Traits

According to Bayesian/predictive coding models of autism, autistic individuals may have difficulties learning probabilistic cue-outcome associations, but empirical evidence has been mixed. The target cues used in previous studies were often straightforward and might not reflect real-life learning of such associations which requires learners to infer which cue(s) among many to track. Across two experiments, we compared adult learners with varying levels of autistic traits on their ability to infer the correct cue to learn probabilistic cue-outcome associations when explicitly instructed to do so or when exposed implicitly. We found no evidence for the effect of autistic traits on probabilistic learning accuracy, contrary to the predictions of Bayesian/predictive coding models. Implications for the current Bayesian/predictive coding models are discussed.

Exploring cognitive individuality and the underlying creativity in statistical learning and phase entrainment

Statistical learning starts at an early age and is intimately linked to brain development and the emergence of individuality. Through such a long period of statistical learning, the brain updates and constructs statistical models, with the model's individuality changing based on the type and degree of stimulation received. However, the detailed mechanisms underlying this process are unknown. This paper argues three main points of statistical learning, including 1) cognitive individuality based on "reliability" of prediction, 2) the construction of information "hierarchy" through chunking, and 3) the acquisition of "1-3Hz rhythm" that is essential for early language and music learning. We developed a Hierarchical Bayesian Statistical Learning (HBSL) model that takes into account both reliability and hierarchy, mimicking the statistical learning processes of the brain. Using this model, we conducted a simulation experiment to visualize the temporal dynamics of perception and production processes through statistical learning. By modulating the sensitivity to sound stimuli, we simulated three cognitive models with different reliability on bottom-up sensory stimuli relative to top-down prior prediction: hypo-sensitive, normal-sensitive, and hyper-sensitive models. We suggested that statistical learning plays a crucial role in the acquisition of 1-3 Hz rhythm. Moreover, a hyper-sensitive model quickly learned the sensory statistics but became fixated on their internal model, making it difficult to generate new information, whereas a hypo-sensitive model has lower learning efficiency but may be more likely to generate new information. Various individual characteristics may not necessarily confer an overall advantage over others, as there may be a trade-off between learning efficiency and the ease of generating new information. This study has the potential to shed light on the heterogeneous nature of statistical learning, as well as the paradoxical phenomenon in which individuals with certain cognitive traits that impede specific types of perceptual abilities exhibit superior performance in creative contexts.

EEG frequency tagging evidence of intact social interaction recognition in adults with autism

To explain the social difficulties in autism, many studies have been conducted on social stimuli processing. However, this research has mostly used basic social stimuli (e.g., eyes, faces, hands, single agent), not resembling the complexity of what we encounter in our daily social lives and what people with autism experience difficulties with. Third-party social interactions are complex stimuli that we come across often and are also highly relevant for social functioning. Interestingly, the existing behavioral studies point to altered social interaction processing in autism. However, it is not clear whether this is due to altered recognition or altered interpretation of social interactions. Here, we specifically investigated the recognition of social interaction in adults with and without autism. More precisely, we measured neural responses to social scenes depicting either social interaction or not with an electroencephalogram frequency tagging task and compared these responses between adults with and without autism (N = 61). The results revealed an enhanced response to social scenes with interaction, replicating previous findings in a neurotypical sample. Crucially, this effect was found in both groups, with no difference between them. This suggests that social interaction recognition is not atypical in adults with autism. Taken together with the previous behavioral evidence, our study thus suggests that individuals with autism are able to recognize social interactions, but that they might not extract the same information from those interactions or that they might use the extracted information differently.

Autism Spectrum Disorder and auditory sensory alterations: a systematic review on the integrity of cognitive and neuronal functions related to auditory processing

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition with a wide spectrum of symptoms, mainly characterized by social, communication, and cognitive impairments. Latest diagnostic criteria according to DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, 2013) now include sensory issues among the four restricted/repetitive behavior features defined as "hyper- or hypo-reactivity to sensory input or unusual interest in sensory aspects of environment". Here, we review auditory sensory alterations in patients with ASD. Considering the updated diagnostic criteria for ASD, we examined research evidence (2015-2022) of the integrity of the cognitive function in auditory-related tasks, the integrity of the peripheral auditory system, and the integrity of the central nervous system in patients diagnosed with ASD. Taking into account the different approaches and experimental study designs, we reappraise the knowledge on auditory sensory alterations and reflect on how these might be linked with behavior symptomatology in ASD.

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.

Reduced mismatch negativity in children and adolescents with autism spectrum disorder is associated with their impaired adaptive functioning

Children and adolescents on the autism spectrum display sensory disturbances, rigid and repetitive behavior, social communication problems and a high prevalence of impaired adaptive functioning. Autism is associated with slowed behavioral and neural habituation to repeated sensory input and decreased responses to sensory deviations. Mismatch negativity (MMN) reflects a pre‐attentive difference in the neural response to sensory deviations relative to regularities and studies overall suggest that children and adolescents with autism tend to have smaller MMN. However, it remains unclear whether reduced MMN in autism is coupled to severity of specific autistic symptoms or more generally to lower level of adaptive functioning. To address these questions, the present study used electroencephalography (EEG) to assess whether auditory MMN in 59 children and adolescents with autism aged 7–14 years compared to 59 typically developing children and adolescents were related to specific autistic symptoms or level in adaptive functioning. As hypothesized, the autism group had a lower MMN amplitude than controls. Smaller MMN amplitudes were specifically associated with lower adaptive functioning in the autistic subjects but not in controls while no apparent relationships were observed with autistic‐like social interaction and communication problems, atypical language, rigidity, stereotypy or sensory sensitivity symptoms. Our findings indicate that a blunted response to changes in sensory input may underlie or contribute to the generalized difficulties with adapting to daily life circumstances seen in children and adolescents with autism.

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.

Psychological and Neural Differences of Music Processing in Autistic Individuals: A Scoping Review

Despite abundant research and clinical evidence of the effectiveness of music interventions for people in the autism spectrum, understanding of music processing in this community is limited. We explored whether research evidence of differences in music processing within the autistic community is available. We developed a scoping review to search for literature with the terms "music", "processing," and "autism" (and variants). We searched PubMed, CINAHL, Scopus, Web of Science, PsycInfo, Academic Search Complete, ERIC, and Music Index databases for a total of 10,857 articles, with 5,236 duplicates. The remaining 5,621 titles and abstracts were screened for eligibility by a team of four undergraduate and graduate students and the PI. Seventy-five studies were included for data extraction. Data were analyzed with descriptive statistics regarding author, study, stimulus, and participant information, and a thematic analysis of outcome and findings. Our findings are preliminary given the emerging nature of the literature, the use of mostly non-musical auditory stimuli, passive listening experiences, and underreported demographics. However, the literature shows some evidence of differences in music processing for autistic individuals, including reduced habituation to non-musical and musical stimuli; truncated, delayed, or divergent developmental trajectories; and possible compensatory higher-order mechanisms that yield similar behavioral responses even in the presence of divergent neural correlates. Music therapists are encouraged to adopt a developmental perspective, not only of general skills, but specifically of music skill development in this community, and to extrapolate these findings with caution, given the current limitations in the evidence.

The autistic brain can process local but not global emotion regularities in facial and musical sequences

Whether autism spectrum disorder (ASD) is associated with a global processing deficit remains controversial. Global integration requires extraction of regularity across various timescales, yet little is known about how individuals with ASD process regularity at local (short timescale) versus global (long timescale) levels. To this end, we used event-related potentials to investigate whether individuals with ASD would show different neural responses to local (within trial) versus global (across trials) emotion regularities extracted from sequential facial expressions; and if so, whether this visual abnormality would generalize to the music (auditory) domain. Twenty individuals with ASD and 21 age- and IQ-matched individuals with typical development participated in this study. At an early processing stage, ASD participants exhibited preserved neural responses to violations of local emotion regularity for both faces and music. At a later stage, however, there was an absence of neural responses in ASD to violations of global emotion regularity for both faces and music. These findings suggest that the autistic brain responses to emotion regularity are modulated by the timescale of sequential stimuli, and provide insight into the neural mechanisms underlying emotional processing in ASD.

Oscillatory entrainment mechanisms and anticipatory predictive processes in children with autism spectrum disorder

Anticipating near-future events is fundamental to adaptive behavior, whereby neural processing of predictable stimuli is significantly facilitated relative to nonpredictable events. Neural oscillations appear to be a key anticipatory mechanism by which processing of upcoming stimuli is modified, and they often entrain to rhythmic environmental sequences. Clinical and anecdotal observations have led to the hypothesis that people with autism spectrum disorder (ASD) may have deficits in generating predictions, and as such, a candidate neural mechanism may be failure to adequately entrain neural activity to repetitive environmental patterns, to facilitate temporal predictions. We tested this hypothesis by interrogating temporal predictions and rhythmic entrainment using behavioral and electrophysiological approaches. We recorded high-density electroencephalography in children with ASD and typically developing (TD) age- and IQ-matched controls, while they reacted to an auditory target as quickly as possible. This auditory event was either preceded by predictive rhythmic visual cues or was not preceded by any cue. Both ASD and control groups presented comparable behavioral facilitation in response to the Cue versus No-Cue condition, challenging the hypothesis that children with ASD have deficits in generating temporal predictions. Analyses of the electrophysiological data, in contrast, revealed significantly reduced neural entrainment to the visual cues and altered anticipatory processes in the ASD group. This was the case despite intact stimulus-evoked visual responses. These results support intact behavioral temporal prediction in response to a cue in ASD, in the face of altered neural entrainment and anticipatory processes.NEW & NOTEWORTHY We examined behavioral and EEG indices of predictive processing in children with ASD to rhythmically predictable stimuli. Although behavioral measures of predictive processing and evoked neural responses were intact in the ASD group, neurophysiological measures of preparatory activity and entrainment were impaired. When sensory events are presented in a predictable temporal pattern, performance and neuronal responses in ASD may be governed more by the occurrence of the events themselves and less by their anticipated timing.

Intact predictive motor sequence learning in autism spectrum disorder

Atypical motor learning has been suggested to underpin the development of motoric challenges (e.g., handwriting difficulties) in autism. Bayesian accounts of autistic cognition propose a mechanistic explanation for differences in the learning process in autism. Specifically, that autistic individuals overweight incoming, at the expense of prior, information and are thus less likely to (a) build stable expectations of upcoming events and (b) react to statistically surprising events. Although Bayesian accounts have been suggested to explain differences in learning across a range of domains, to date, such accounts have not been extended to motor learning. 28 autistic and 35 non-autistic controls (IQ > 70) completed a computerised task in which they learned sequences of actions. On occasional "surprising" trials, an expected action had to be replaced with an unexpected action. Sequence learning was indexed as the reaction time difference between blocks which featured a predictable sequence and those that did not. Surprise-related slowing was indexed as the reaction time difference between surprising and unsurprising trials. No differences in sequence-learning or surprise-related slowing were observed between the groups. Bayesian statistics provided anecdotal to moderate evidence to support the conclusion that sequence learning and surprise-related slowing were comparable between the two groups. We conclude that individuals with autism do not show atypicalities in response to surprising events in the context of motor sequence-learning. These data demand careful consideration of the way in which Bayesian accounts of autism can (and cannot) be extended to the domain of motor learning.

Attentional Disengagement and the Locus Coeruleus - Norepinephrine System in Children With Autism Spectrum Disorder

Background

Differences in non-social attentional functions have been identified as among the earliest features that distinguish infants later diagnosed with autism spectrum disorder (ASD), and may contribute to the emergence of core ASD symptoms. Specifically, slowed attentional disengagement and difficulty reorienting attention have been found across the lifespan in those at risk for, or diagnosed with, ASD. Additionally, the locus coeruleus-norepinephrine (LC-NE) system, which plays a critical role in arousal regulation and selective attention, has been shown to function atypically in ASD. While activity of the LC-NE system is associated with attentional disengagement and reorienting in typically developing (TD) individuals, it has not been determined whether atypical LC-NE activity relates to attentional disengagement impairments observed in ASD.

Objective

To examine the relationship between resting pupil diameter (an indirect measure of tonic LC-NE activation) and attentional disengagement in children with ASD.

Methods

Participants were 21 school-aged children with ASD and 20 age- and IQ-matched TD children. The study consisted of three separate experiments: a resting eye-tracking task and visual and auditory gap-overlap paradigms. For the resting eye-tracking task, pupil diameter was monitored while participants fixated a central crosshair. In the gap-overlap paradigms, participants were instructed to fixate on a central stimulus and then move their eyes to peripherally presented visual or auditory targets. Saccadic reaction times (SRT), percentage of no-shift trials, and disengagement efficiency were measured.

Results

Children with ASD had significantly larger resting pupil size compared to their TD peers. The groups did not differ for overall SRT, nor were there differences in SRT for overlap and gap conditions between groups. However, the ASD group did evidence impairments in disengagement (larger step/gap effects, higher percentage of no-shift trials, and reduced disengagement efficiency) compared to their TD peers. Correlational analyses showed that slower, less efficient disengagement was associated with increased pupil diameter.

Conclusion

Consistent with prior reports, children with ASD show significantly larger resting pupil diameter, indicative of atypically elevated tonic LC-NE activity. Associations between pupil size and measures of attentional disengagement suggest that atypically increased tonic activation of the LC-NE system may be associated with poorer attentional disengagement in children with ASD.

Associative learning under uncertainty in adults with autism: Intact learning of the cue-outcome contingency, but slower updating of priors

LAY ABSTRACT

We have an internal representation of the world that guides our behavior, helps us predicting what comes next and therefore, reducing uncertainty. For instance, after hearing the noise of a door opening, we usually expect to see a person appearing, whose features differ depending on the context. In this example of associative learning, predictions need to be adjusted if there is a change in the environment (e.g. different person depending on the location). Recent theories suggest that the symptoms encountered in autism could be due to an atypical learning of predictions or to a decreased influence of these expectations on perception. Here, we conducted an experiment assessing whether adults with autism could learn and adjust their predictions in a changing environment. Throughout a behavioral task, participants learned to associate a sound with a visual outcome, but this association could sometimes reverse. Results showed that autistic adults could learn to make predictions that fitted the main sound-vision association, but were slower to adapt their expectations when there was an unannounced change in the environment. We also observed that both adults with and without autism tended to be biased by their expectations, as they reported seeing what they expected to see rather than what was actually shown. Altogether, our results indicate that autistic adults can learn predictions but are more inflexible to adjust these predictions in a changing environment. These results help refining recent theories of autism (called "predictive coding" theories), which intend to identify the core mechanisms underlying the autistic symptomatology.

Statistical Properties of Musical Creativity: Roles of Hierarchy and Uncertainty in Statistical Learning

Creativity is part of human nature and is commonly understood as a phenomenon whereby something original and worthwhile is formed. Owing to this ability, humans can produce innovative information that often facilitates growth in our society. Creativity also contributes to esthetic and artistic productions, such as music and art. However, the mechanism by which creativity emerges in the brain remains debatable. Recently, a growing body of evidence has suggested that statistical learning contributes to creativity. Statistical learning is an innate and implicit function of the human brain and is considered essential for brain development. Through statistical learning, humans can produce and comprehend structured information, such as music. It is thought that creativity is linked to acquired knowledge, but so-called "eureka" moments often occur unexpectedly under subconscious conditions, without the intention to use the acquired knowledge. Given that a creative moment is intrinsically implicit, we postulate that some types of creativity can be linked to implicit statistical knowledge in the brain. This article reviews neural and computational studies on how creativity emerges within the framework of statistical learning in the brain (i.e., statistical creativity). Here, we propose a hierarchical model of statistical learning: statistically chunking into a unit (hereafter and shallow statistical learning) and combining several units (hereafter and deep statistical learning). We suggest that deep statistical learning contributes dominantly to statistical creativity in music. Furthermore, the temporal dynamics of perceptual uncertainty can be another potential causal factor in statistical creativity. Considering that statistical learning is fundamental to brain development, we also discuss how typical versus atypical brain development modulates hierarchical statistical learning and statistical creativity. We believe that this review will shed light on the key roles of statistical learning in musical creativity and facilitate further investigation of how creativity emerges in the brain.

Prediction in Autism Spectrum Disorder: A Systematic Review of Empirical Evidence

According to a recent influential proposal, several phenotypic features of autism spectrum disorder (ASD) may be accounted for by differences in predictive skills between individuals with ASD and neurotypical individuals. In this systematic review, we describe results from 47 studies that have empirically tested this hypothesis. We assess the results based on two observable aspects of prediction: learning a pairing between an antecedent and a consequence and responding to an antecedent in a predictive manner. Taken together, these studies suggest distinct differences in both predictive learning and predictive response. Studies documenting differences in learning predictive pairings indicate challenges in detecting such relationships especially when predictive features of an antecedent have low salience or consistency, and studies showing differences in habituation and perceptual adaptation suggest low-level predictive processing differences in ASD. These challenges may account for the observed differences in the influence of predictive priors, in spontaneous predictive movement or gaze, and in social prediction. An important goal for future research will be to better define and constrain the broad domain-general hypothesis by testing multiple types of prediction within the same individuals. Additional promising avenues include studying prediction within naturalistic contexts and assessing the effect of prediction-based intervention on supporting functional outcomes for individuals with ASD. LAY SUMMARY: Researchers have suggested that many features of autism spectrum disorder (ASD) may be explained by differences in the prediction skills of people with ASD. We review results from 47 studies. These studies suggest that ASD may be associated with differences in the learning of predictive pairings (e.g., learning cause and effect) and in low-level predictive processing in the brain (e.g., processing repeated sounds). These findings lay the groundwork for research that can improve our understanding of ASD and inform interventions. Autism Res 2021, 14: 604-630. © 2021 International Society for Autism Research and Wiley Periodicals LLC.

Associations between sensory processing and electrophysiological and neurochemical measures in children with ASD: an EEG-MRS study

Background

Autism spectrum disorder (ASD) is associated with hyper- and/or hypo-sensitivity to sensory input. Spontaneous alpha power, which plays an important role in shaping responsivity to sensory information, is reduced across the lifespan in individuals with ASD. Furthermore, an excitatory/inhibitory imbalance has also been linked to sensory dysfunction in ASD and has been hypothesized to underlie atypical patterns of spontaneous brain activity. The present study examined whether resting-state alpha power differed in children with ASD as compared to TD children, and investigated the relationships between alpha levels, concentrations of excitatory and inhibitory neurotransmitters, and atypical sensory processing in ASD.

Methods

Participants included thirty-one children and adolescents with ASD and thirty-one age- and IQ-matched typically developing (TD) participants. Resting-state electroencephalography (EEG) was used to obtain measures of alpha power. A subset of participants (ASD = 16; TD = 16) also completed a magnetic resonance spectroscopy (MRS) protocol in order to measure concentrations of excitatory (glutamate + glutamine; Glx) and inhibitory (GABA) neurotransmitters.

Results

Children with ASD evidenced significantly decreased resting alpha power compared to their TD peers. MRS estimates of GABA and Glx did not differ between groups with the exception of Glx in the temporal-parietal junction. Inter-individual differences in alpha power within the ASD group were not associated with region-specific concentrations of GABA or Glx, nor were they associated with sensory processing differences. However, atypically decreased Glx was associated with increased sensory impairment in children with ASD.

Conclusions

Although we replicated prior reports of decreased alpha power in ASD, atypically reduced alpha was not related to neurochemical differences or sensory symptoms in ASD. Instead, reduced Glx in the temporal-parietal cortex was associated with greater hyper-sensitivity in ASD. Together, these findings may provide insight into the neural underpinnings of sensory processing differences present in ASD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s11689-020-09351-0.

Priors Bias Perceptual Decisions in Autism, But Are Less Flexibly Adjusted to the Context

According to the predictive coding framework, percepts emerge from combinations of sensory input and prior knowledge, whose relative contributions depend on their reliability. Recent predictive coding theories suggest that Autism Spectrum Disorder (ASD) could be characterized by an atypical weighting of priors. Here, we assessed whether individuals with ASD can flexibly adjust the weight (precision) of the prior to the context. Thirty-one neurotypical adults (NT) and 26 adults with ASD participated in a visual discrimination task designed to elicit a time-order effect (TOE). The TOE reflects the integration of priors with sensory estimates. We used two experimental contexts: a narrow stimulus range (Narrow condition) and a broader range (Broad condition) in order to induce a prior with a higher and lower precision, respectively. Both groups learned a prior that biased their perception, as shown with the TOE. As expected, the NT group had a larger TOE in the Narrow condition than in the Broad condition, revealing a contextual adjustment of the prior precision. In contrast, ASD participants were more inflexible: the extent of the TOE was not modulated by the context. In addition, the accuracy increased when the stimulus range decreased in both group, which may be interpreted as a contextual adjustment of the sensory precision. To conclude, adults with and without ASD implicitly learned a prior mean, but ASD participants failed to flexibly adjust the prior precision to the context. This increased inflexibility in ASD could account for many symptoms, such as their intolerance of uncertainty. LAY SUMMARY: Based on our experience, we have expectations about our environment. Theories suggest that the symptoms encountered in autism could be due to atypical expectations, leading to an impression of an unpredictable world. Using a visual discrimination task, we showed that adults with and without autism were biased by their expectations. Yet, the extent to which expectations biased perception did not depend on the context in autism. This higher inflexibility found in autism may explain symptoms such as resistance to change.

Autistic Traits Differently Account for Context-Based Predictions of Physical and Social Events

Autism is associated with difficulties in making predictions based on contextual cues. Here, we investigated whether the distribution of autistic traits in the general population, as measured through the Autistic Quotient (AQ), is associated with alterations of context-based predictions of social and non-social stimuli. Seventy-eight healthy participants performed a social task, requiring the prediction of the unfolding of an action as interpersonal (e.g., to give) or individual (e.g., to eat), and a non-social task, requiring the prediction of the appearance of a moving shape as a short (e.g., square) or a long (e.g., rectangle) figure. Both tasks consisted of (i) a familiarization phase, in which the association between each stimulus type and a contextual cue was manipulated with different probabilities of co-occurrence, and (ii) a testing phase, in which visual information was impoverished by early occlusion of video display, thus forcing participants to rely on previously learned context-based associations. Findings showed that the prediction of both social and non-social stimuli was facilitated when embedded in high-probability contexts. However, only the contextual modulation of non-social predictions was reduced in individuals with lower 'Attention switching' abilities. The results provide evidence for an association between weaker context-based expectations of non-social events and higher autistic traits.

The Relation Between Preference for Predictability and Autistic Traits

A common idea about individuals with autism spectrum disorder (ASD) is that they have an above-average preference for predictability and sameness. However, surprisingly little research has gone toward this core symptom, and some studies suggest the preference for predictability in ASD might be less general than commonly assumed. Here, we investigated this important symptom of ASD using three different paradigms, which allowed us to measure preference for predictability under well-controlled experimental conditions. Specifically, we used a dimensional approach by investigating correlations between autistic traits (as measured with the Autism-Spectrum Quotient and Social Responsiveness Scale in a neurotypical population) and the scores on three different tasks. The "music preference" task assessed preferences for tone sequences that varied in predictability. The "perceptual fluency" task required participants to evaluate stimuli that were preceded by a similar versus dissimilar subliminally presented prime. The "gambling" task presented four decks of cards that had equal outcome probabilities but varied in predictability. We observed positive correlations between autistic traits and a preference for predictability in both the music preference and perceptual fluency task. We did not find our hypothesized correlation with gambling behavior but did observe a post hoc correlation showing that participants with more autistic traits were faster to choose the predictable deck. Together, these findings show that a relation between autistic traits and preference for predictability can be observed in a standardized lab environment, and should be considered an important first step toward a better, more mechanistic understanding of insistence on sameness in ASD. Autism Res 2020, 13: 1144-1154. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: A core symptom of autism spectrum disorder (ASD) is a strong preference for predictability, but little research has gone toward it. We show that neurotypical adults with more autistic traits have stronger preferences for predictable tunes, evaluate images that can be predicted as more beautiful, and are faster in choosing a gambling option resulting in predictable reward. These results offer the first important evidence that insistence on sameness in ASD can be studied in controlled lab settings.

Autistic traits influence the strategic diversity of information sampling: Insights from two-stage decision models

Information sampling can reduce uncertainty in future decisions but is often costly. To maximize reward, people need to balance sampling cost and information gain. Here we aimed to understand how autistic traits influence the optimality of information sampling and to identify the particularly affected cognitive processes. Healthy human adults with different levels of autistic traits performed a probabilistic inference task, where they could sequentially sample information to increase their likelihood of correct inference and may choose to stop at any moment. We manipulated the cost and evidence associated with each sample and compared participants’ performance to strategies that maximize expected gain. We found that participants were overall close to optimal but also showed autistic-trait-related differences. Participants with higher autistic traits had a higher efficiency of winning rewards when the sampling cost was zero but a lower efficiency when the cost was high and the evidence was more ambiguous. Computational modeling of participants’ sampling choices and decision times revealed a two-stage decision process, with the second stage being an optional second thought. Participants may consider cost in the first stage and evidence in the second stage, or in the reverse order. The probability of choosing to stop sampling at a specific stage increases with increasing cost or increasing evidence. Surprisingly, autistic traits did not influence the decision in either stage. However, participants with higher autistic traits inclined to consider cost first, while those with lower autistic traits considered cost or evidence first in a more balanced way. This would lead to the observed autistic-trait-related advantages or disadvantages in sampling optimality, depending on whether the optimal sampling strategy is determined only by cost or jointly by cost and evidence.

Children with autism can spend hours practicing lining up toys or learning all about cars or lighthouses. This kind of behaviors, we think, may reflect suboptimal information sampling strategies, that is, a failure to balance the gain of information with the cost (time, energy, or money) of information sampling. We hypothesized that suboptimal information sampling is a general characteristic of people with autism or high level of autistic traits. In our experiment, we tested how participants may adjust their sampling strategies with the change of sampling cost and information gain in the environment. Though all participants were healthy young adults who had similar IQs, higher autistic traits were associated with higher or lower efficiency of winning rewards under different conditions. Counterintuitively, participants with different levels of autistic traits did not differ in the general tendency of oversampling or undersampling, or in the decision they would reach when a specific set of sampling cost or information gain was considered. Instead, participants with higher autistic traits consistently considered sampling cost first and only weighed information gain during a second thought, while those with lower autistic traits had more diverse sampling strategies that consequently better balanced sampling cost and information gain.

Thermal Perceptual Thresholds are typical in Autism Spectrum Disorder but Strongly Related to Intra-individual Response Variability

Individuals with autism spectrum disorder (ASD) are often reported to exhibit an apparent indifference to pain or temperature. Leading models suggest that this behavior is the result of elevated perceptual thresholds for thermal stimuli, but data to support these assertions are inconclusive. An alternative proposal suggests that the sensory features of ASD arise from increased intra-individual perceptual variability. In this study, we measured method-of-limits warm and cool detection thresholds in 142 individuals (83 with ASD, 59 with typical development [TD], aged 7-54 years), testing relationships with diagnostic group, demographics, and clinical measures. We also investigated the relationship between detection thresholds and a novel measure of intra-individual (trial-to-trial) threshold variability, a putative index of "perceptual noise." This investigation found no differences in thermal detection thresholds between individuals with ASD and typical controls, despite large differences between groups in sensory reactivity questionnaires and modest group differences in intra-individual variability. Lower performance IQ, male sex, and higher intra-individual variability in threshold estimates were the most significant predictors of elevated detection thresholds. Although no psychophysical measure was significantly correlated with questionnaire measures of sensory hyporeactivity, large intra-individual variability may partially explain the elevated psychophysical thresholds seen in a subset of the ASD population.

REBUS and the Anarchic Brain: Toward a Unified Model of the Brain Action of Psychedelics

This paper formulates the action of psychedelics by integrating the free-energy principle and entropic brain hypothesis. We call this formulation relaxed beliefs under psychedelics (REBUS) and the anarchic brain, founded on the principle that-via their entropic effect on spontaneous cortical activity-psychedelics work to relax the precision of high-level priors or beliefs, thereby liberating bottom-up information flow, particularly via intrinsic sources such as the limbic system. We assemble evidence for this model and show how it can explain a broad range of phenomena associated with the psychedelic experience. With regard to their potential therapeutic use, we propose that psychedelics work to relax the precision weighting of pathologically overweighted priors underpinning various expressions of mental illness. We propose that this process entails an increased sensitization of high-level priors to bottom-up signaling (stemming from intrinsic sources), and that this heightened sensitivity enables the potential revision and deweighting of overweighted priors. We end by discussing further implications of the model, such as that psychedelics can bring about the revision of other heavily weighted high-level priors, not directly related to mental health, such as those underlying partisan and/or overly-confident political, religious, and/or philosophical perspectives. SIGNIFICANCE STATEMENT: Psychedelics are capturing interest, with efforts underway to bring psilocybin therapy to marketing authorisation and legal access within a decade, spearheaded by the findings of a series of phase 2 trials. In this climate, a compelling unified model of how psychedelics alter brain function to alter consciousness would have appeal. Towards this end, we have sought to integrate a leading model of global brain function, hierarchical predictive coding, with an often-cited model of the acute action of psychedelics, the entropic brain hypothesis. The resulting synthesis states that psychedelics work to relax high-level priors, sensitising them to liberated bottom-up information flow, which, with the right intention, care provision and context, can help guide and cultivate the revision of entrenched pathological priors.

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.

Neural Correlates of Sensory Abnormalities Across Developmental Disabilities

Abnormalities in sensory processing are a common feature of many developmental disabilities (DDs). Sensory dysfunction can contribute to deficits in brain maturation, as well as many vital functions. Unfortunately, while some patients with DD benefit from the currently available treatments for sensory dysfunction, many do not. Deficiencies in clinical practice surrounding sensory dysfunction may be related to lack of understanding of the neural mechanisms that underlie sensory abnormalities. Evidence of overlap in sensory symptoms between diagnoses suggests that there may be common neural mechanisms that mediate many aspects of sensory dysfunction. Thus, the current manuscript aims to review the extant literature regarding the neural correlates of sensory dysfunction across DD in order to identify patterns of abnormality that span diagnostic categories. Such anomalies in brain structure, function, and connectivity may eventually serve as targets for treatment.