When the world becomes 'too real': a Bayesian explanation of autistic perception

Autistic young people adaptively use gaze to facilitate joint attention during multi-gestural dyadic interactions

LAY ABSTRACT

Autistic people have been said to have 'problems' with joint attention, that is, looking where someone else is looking. Past studies of joint attention have used tasks that require autistic people to continuously look at and respond to eye-gaze cues. But joint attention can also be done using other social cues, like pointing. This study looked at whether autistic and non-autistic young people use another person's eye gaze during joint attention in a task that did not require them to look at their partner's face. In the task, each participant worked together with their partner to find a computer-generated object in virtual reality. Sometimes the participant had to help guide their partner to the object, and other times, they followed their partner's lead. Participants were told to point to guide one another but were not told to use eye gaze. Both autistic and non-autistic participants often looked at their partner's face during joint attention interactions and were faster to respond to their partner's hand-pointing when the partner also looked at the object before pointing. This shows that autistic people can and do use information from another person's eyes, even when they don't have to. It is possible that, by not forcing autistic young people to look at their partner's face and eyes, they were better able to gather information from their partner's face when needed, without being overwhelmed. This shows how important it is to design tasks that provide autistic people with opportunities to show what they can do.

A common computational and neural anomaly across mouse models of autism

Computational psychiatry has suggested that humans within the autism spectrum disorder (ASD) inflexibly update their expectations (i.e., Bayesian priors). Here, we leveraged high-yield rodent psychophysics (n = 75 mice), extensive behavioral modeling (including principled and heuristics), and (near) brain-wide single cell extracellular recordings (over 53k units in 150 brain areas) to ask (1) whether mice with different genetic perturbations associated with ASD show this same computational anomaly, and if so, (2) what neurophysiological features are shared across genotypes in subserving this deficit. We demonstrate that mice harboring mutations in Fmr1 , Cntnap2 , and Shank3B show a blunted update of priors during decision-making. Neurally, the differentiating factor between animals flexibly and inflexibly updating their priors was a shift in the weighting of prior encoding from sensory to frontal cortices. Further, in mouse models of ASD frontal areas showed a preponderance of units coding for deviations from the animals' long-run prior, and sensory responses did not differentiate between expected and unexpected observations. These findings demonstrate that distinct genetic instantiations of ASD may yield common neurophysiological and behavioral phenotypes.

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.

Decision-making under conditions of explicit risk and uncertainty in autistic and typically developing adolescents and young adults

Adolescence has been characterized as a period of risky and possibly suboptimal decision-making, yet the development of decision-making in autistic adolescents is not well understood. To investigate decision-making in autism, we evaluated performance on 2 computerized tasks capturing decision-making under explicit risk and uncertainty in autistic and non-autistic adolescents/young adults ages 12-22 years. Participants completed the Game of Dice Task (32 IQ-matched participant pairs) to assess decision-making under explicit risk and the modified Iowa Gambling Task (35 IQ-matched pairs) to assess decision-making under uncertainty. Autistic participants overall made riskier decisions than non-autistic participants on the Game of Dice Task, and the odds of making riskier decisions varied by age and IQ. In contrast, the autistic group showed comparable levels of learning over trial blocks to the non-autistic group on the modified Iowa Gambling Task. For both tasks, younger autistic participants performed poorer than their non-autistic counterparts, while group differences diminished in older ages. This age-related pattern suggests positive development during adolescence on risk assessment and decision-making in autism but also implies differential developmental trajectories between groups. These findings also suggest differential performance by the risk type, with additional complex influences of IQ and fluid cognition, which warrants further investigations.

Giftedness and atypical sexual differentiation: enhanced perceptual functioning through estrogen deficiency instead of androgen excess

Syndromic autism spectrum conditions (ASC), such as Klinefelter syndrome, also manifest hypogonadism. Compared to the popular Extreme Male Brain theory, the Enhanced Perceptual Functioning model explains the connection between ASC, savant traits, and giftedness more seamlessly, and their co-emergence with atypical sexual differentiation. Overexcitability of primary sensory inputs generates a relative enhancement of local to global processing of stimuli, hindering the abstraction of communication signals, in contrast to the extraordinary local information processing skills in some individuals. Weaker inhibitory function through gamma-aminobutyric acid type A (GABAA) receptors and the atypicality of synapse formation lead to this difference, and the formation of unique neural circuits that process external information. Additionally, deficiency in monitoring inner sensory information leads to alexithymia (inability to distinguish one's own emotions), which can be caused by hypoactivity of estrogen and oxytocin in the interoceptive neural circuits, comprising the anterior insular and cingulate gyri. These areas are also part of the Salience Network, which switches between the Central Executive Network for external tasks and the Default Mode Network for self-referential mind wandering. Exploring the possibility that estrogen deficiency since early development interrupts GABA shift, causing sensory processing atypicality, it helps to evaluate the co-occurrence of ASC with attention deficit hyperactivity disorder, dyslexia, and schizophrenia based on phenotypic and physiological bases. It also provides clues for understanding the common underpinnings of these neurodevelopmental disorders and gifted populations.

Strategic social decision making undergoes significant changes in typically developing and autistic early adolescents

Information sampling about others' trustworthiness prior to cooperation allows humans to minimize the risk of exploitation. Here, we examined whether early adolescence or preadolescence, a stage defined as in between childhood and adolescence, is a significant developmental period for strategic social decisions. We also sought to characterize differences between autistic children and their typically developing (TD) peers. TD (N = 48) and autistic (N = 56) 8- to 12-year-olds played an online information sampling trust game. While both groups adapted their information sampling and cooperation to the various trustworthiness levels of the trustees, groups differed in how age and social skills modulated task behavior. In the TD group social skills were a stronger overall predictor of task behavior. In the autistic group, age was a stronger predictor and interacted with social skills. Computational modeling revealed that both groups used the same heuristic information sampling strategy-albeit older TD children were more efficient as reflected by decreasing decision noise with age. Autistic children had lower prior beliefs about the trustee's trustworthiness compared to TD children. These lower priors indicate that children believed the trustees to be less trustworthy. Lower priors scaled with lower social skills across groups. Notably, groups did not differ in prior uncertainty, meaning that the priors of TD and autistic children were equally strong. Taken together, we found significant development in information sampling and cooperation in early adolescence and nuanced differences between TD and autistic children. Our study highlights the importance of deep phenotyping of children including clinical measures, behavioral experiments and computational modeling. RESEARCH HIGHLIGHTS: We specified how early adolescents with and without an autism diagnosis sampled information about their interaction partners and made cooperation decisions in a strategic game. Early adolescence is a significant developmental period for strategic decision making, marked by significant changes in information sampling efficiency and adaptivity to the partner's behavior. Autistic and non-autistic groups differed in how age and social skills modulated task behavior; in non-autistic children behavior was more indicative of overall social skills. Computational modeling revealed differences between autistic and non-autistic groups in their initial beliefs about cooperation partners; autistic children expected their partners to be less trustworthy.

Autistic and nonautistic adolescents do not differ in adaptation to gaze direction

Predictive processing accounts of autism posit that autistic individuals' perception is less biased by expectations than nonautistic individuals', perhaps through stronger precision-weighting of prediction errors. Since precision-weighting is fundamental to all information processing, under this theory, the differences between autistic and nonautistic individuals should be domain-general and observable in both behavior and brain responses. This study used EEG, behavioral responses, and eye-tracking co-registration during gaze-direction adaptation, to investigate whether increased precision-weighting of prediction errors is evident through smaller adaptation after-effects in autistic adolescents compared with nonautistic peers. Multilevel modeling showed that autistic and nonautistic adolescents' responses were consistent with behavioral adaptation, with Bayesian statistics providing extremely strong evidence for the absence of a group difference. Cluster-based permutation testing of ERP responses did not show the expected adaptation after-effect but did show habituation to repeated stimulus presentation, and no group difference was detected, a result not consistent with the theoretical account. Combined with the few other available studies, the current findings raise challenges for the theory, suggesting no fundamental difference in precision-weighting of prediction errors in autism.

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.

Deep Aphantasia: a visual brain with minimal influence from priors or inhibitory feedback?

The authors are both self-described congenital aphantasics, who feel they have never been able to have volitional imagined visual experiences during their waking lives. In addition, Loren has atypical experiences of a number of visual phenomena that involve an extrapolation or integration of visual information across space. In this perspective, we describe Loren's atypical experiences of a number of visual phenomena, and we suggest these ensue because her visual experiences are not strongly shaped by inhibitory feedback or by prior expectations. We describe Loren as having Deep Aphantasia, and Derek as shallow, as for both a paucity of feedback might prevent the generation of imagined visual experiences, but for Loren this additionally seems to disrupt activity at a sufficiently early locus to cause atypical experiences of actual visual inputs. Our purpose in describing these subjective experiences is to alert others to the possibility of there being sub-classes of congenital aphantasia, one of which-Deep Aphantasia, would be characterized by atypical experiences of actual visual inputs.

Individual differences in internal models explain idiosyncrasies in scene perception

According to predictive processing theories, vision is facilitated by predictions derived from our internal models of what the world should look like. However, the contents of these models and how they vary across people remains unclear. Here, we use drawing as a behavioral readout of the contents of the internal models in individual participants. Participants were first asked to draw typical versions of scene categories, as descriptors of their internal models. These drawings were converted into standardized 3d renders, which we used as stimuli in subsequent scene categorization experiments. Across two experiments, participants' scene categorization was more accurate for renders tailored to their own drawings compared to renders based on others' drawings or copies of scene photographs, suggesting that scene perception is determined by a match with idiosyncratic internal models. Using a deep neural network to computationally evaluate similarities between scene renders, we further demonstrate that graded similarity to the render based on participants' own typical drawings (and thus to their internal model) predicts categorization performance across a range of candidate scenes. Together, our results showcase the potential of a new method for understanding individual differences - starting from participants' personal expectations about the structure of real-world scenes.

Category learning in autistic individuals: A meta-analysis

Learning new categories is a fundamental human skill. In the present article, we report the first comprehensive meta-analysis of category learning in autism. Including studies comparing groups of autistic and nonautistic individuals, we investigated whether autistic individuals differ in category learning from nonautistic individuals. In addition, we examined moderator variables accounting for variability between studies. A multilevel meta-analysis of k = 50 studies examining n = 1,220 autistic and n = 1,445 nonautistic individuals based on 112 effect sizes in terms of the standardized mean difference revealed lower-level category learning skills for autistic compared with nonautistic individuals, g = -0.55, 95% CI = [-0.73, -0.38], p < .0001. According to moderator analyses, the significant amount of heterogeneity, Q(111) = 617.88, p < .0001, was explained by only one of the moderator variables under investigation-namely, study language. For the remaining variables-namely, age, year of publication, risk of bias, type of control group, IQ of autistic group, percentage of male autistic participants, type of category, type of task, and type of dependent measure-there were no significant effects. Although hat values and Cook's distance statistics confirmed the robustness of findings, results of Egger's test and a funnel plot suggested the presence of publication bias reflecting an overrepresentation of disadvantageous findings for autistic groups. Objectives for future work include identifying additional moderator variables, examining downstream effects of suboptimal category learning skills, and developing interventions.

Reduced stereotypicality and spared use of facial expression predictions for social evaluation in autism

Background/Objective

Autism has been investigated through traditional emotion recognition paradigms, merely investigating accuracy, thereby constraining how potential differences across autistic and control individuals may be observed, identified, and described. Moreover, the use of emotional facial expression information for social functioning in autism is of relevance to provide a deeper understanding of the condition.

Method

Adult autistic individuals (n = 34) and adult control individuals (n = 34) were assessed with a social perception behavioral paradigm exploring facial expression predictions and their impact on social evaluation.

Results

Autistic individuals held less stereotypical predictions than controls. Importantly, despite such differences in predictions, the use of such predictions for social evaluation did not differ significantly between groups, as autistic individuals relied on their predictions to evaluate others to the same extent as controls.

Conclusions

These results help to understand how autistic individuals perceive social stimuli and evaluate others, revealing a deviation from stereotypicality beyond which social evaluation strategies may be intact.

Mental rotation and language in autism spectrum disorder

Though visuospatial skills are often considered a relative strength in autism spectrum disorder (ASD), unexplained difficulties relative to neurotypical (NT) peers have also been observed. Dissociations between spatial cognition and language skills in ASD may explain these difficulties given that these systems are linked in NT individuals. The current study examined performance on a mental rotation task that systematically varied stimulus features and the degree to which performance was associated with language in ASD relative to NT peers. Participants were children and young adults with ASD and 25 pairwise age- and IQ-matched NT peers (p's>0.53). The mental rotation task involved four conditions: two-dimensional (2D) abstract figures, three-dimensional (3D) abstract figures, 2D common objects, and 3D common objects. Structural language was measured using the grammar subscale from the Test of Language Development: Intermediate adapted for Norwegian. Mixed-effects model results indicated that autistic individuals were less accurate and had slower reaction time across mental rotation task conditions than NT peers. Language was associated with mental rotation accuracy for both groups across conditions, but with reaction time only for the NT group. The current study demonstrated selective associations between language and performance on a classic spatial cognition task in autistic individuals. Namely, there was a dissociation between language and in-the-moment efficiency in the ASD group, and this dissociation may reflect a broader dissociation between visuospatial and language systems.

Deep CANALs: a deep learning approach to refining the canalization theory of psychopathology

Psychedelic therapy has seen a resurgence of interest in the last decade, with promising clinical outcomes for the treatment of a variety of psychopathologies. In response to this success, several theoretical models have been proposed to account for the positive therapeutic effects of psychedelics. One of the more prominent models is "RElaxed Beliefs Under pSychedelics," which proposes that psychedelics act therapeutically by relaxing the strength of maladaptive high-level beliefs encoded in the brain. The more recent "CANAL" model of psychopathology builds on the explanatory framework of RElaxed Beliefs Under pSychedelics by proposing that canalization (the development of overly rigid belief landscapes) may be a primary factor in psychopathology. Here, we make use of learning theory in deep neural networks to develop a series of refinements to the original CANAL model. Our primary theoretical contribution is to disambiguate two separate optimization landscapes underlying belief representation in the brain and describe the unique pathologies which can arise from the canalization of each. Along each dimension, we identify pathologies of either too much or too little canalization, implying that the construct of canalization does not have a simple linear correlation with the presentation of psychopathology. In this expanded paradigm, we demonstrate the ability to make novel predictions regarding what aspects of psychopathology may be amenable to psychedelic therapy, as well as what forms of psychedelic therapy may ultimately be most beneficial for a given individual.

Word meaning is complex: Language-related generalization differences in autistic adults

The current study marries two important observations. First, there is a growing recognition that word meanings need to be flexibly extended in new ways as new contexts arise. Second, as evidenced primarily within the perceptual domain, autistic individuals tend to find generalization more challenging while showing stronger veridical memory in comparison to their neurotypical peers. Here we report that a group of 80 autistic adults finds it more challenging to flexibly extend the meanings of familiar words in new ways than a group of 80 neurotypical peers, while the autistic individuals outperform the neurotypicals on a novel word-learning task that does not require flexible extension. Results indicate that recognized differences in generalization present an ongoing challenge for autistic adults in the domain of language, separate from social cognition, executive function, or the ability to assign single fixed meanings to new words.

A matter of precision? Scene imagery in individuals with high-functioning autism spectrum disorder

The ability to create mental representations of scenes is essential for remembering, predicting, and imagining. In individuals with autism spectrum disorders (ASD) this ability may be impaired. Considering that autistic characteristics such as weak central coherence or reduced communication abilities may disadvantage autistic participants in traditional imagery tasks, this study attempted to use a novel task design to measure the ability of scene imagery. Thirty high-functioning adults with ASD and 27 non-autistic matched control adults were asked to describe imagined fictitious scenes using two types of scene imagery tasks. In a free imagery task, participants were asked to imagine a scene based on a given keyword. In a guided imagery task, participants had to imagine a scene based on a detailed description of the scene. Additionally, narrative abilities were assessed using the Narrative Scoring Scheme. Statistical analyses revealed no group effects in the free and guided imagery of fictional scenes. Participants with ASD performed worse than control participants in the narrative task. Narrative abilities correlated positively with performance in both imagery tasks in the ASD group only. Hence, individuals with ASD seem to show as good imagery abilities as non-autistic individuals. The results are discussed in the light of the differences between imagery and imagination and possible gender differences.

A generative model of memory construction and consolidation

Episodic memories are (re)constructed, share neural substrates with imagination, combine unique features with schema-based predictions and show schema-based distortions that increase with consolidation. Here we present a computational model in which hippocampal replay (from an autoassociative network) trains generative models (variational autoencoders) to (re)create sensory experiences from latent variable representations in entorhinal, medial prefrontal and anterolateral temporal cortices via the hippocampal formation. Simulations show effects of memory age and hippocampal lesions in agreement with previous models, but also provide mechanisms for semantic memory, imagination, episodic future thinking, relational inference and schema-based distortions including boundary extension. The model explains how unique sensory and predictable conceptual elements of memories are stored and reconstructed by efficiently combining both hippocampal and neocortical systems, optimizing the use of limited hippocampal storage for new and unusual information. Overall, we believe hippocampal replay training generative models provides a comprehensive account of memory construction, imagination and consolidation.

A novel model of divergent predictive perception

Predictive processing theories state that our subjective experience of reality is shaped by a balance of expectations based on previous knowledge about the world (i.e. priors) and confidence in sensory input from the environment. Divergent experiences (e.g. hallucinations and synaesthesia) are likely to occur when there is an imbalance between one's reliance on priors and sensory input. In a novel theoretical model, inspired by both predictive processing and psychological principles, we propose that predictable divergent experiences are associated with natural or environmentally induced prior/sensory imbalances: inappropriately strong or inflexible (i.e. maladaptive) high-level priors (beliefs) combined with low sensory confidence can result in reality discrimination issues, a characteristic of psychosis; maladaptive low-level priors (sensory expectations) combined with high sensory confidence can result in atypical sensory sensitivities and persistent divergent percepts, a characteristic of synaesthesia. Crucially, we propose that whether different divergent experiences manifest with dominantly sensory (e.g. hallucinations) or nonsensory characteristics (e.g. delusions) depends on mental imagery ability, which is a spectrum from aphantasia (absent or weak imagery) to hyperphantasia (extremely vivid imagery). We theorize that imagery is critically involved in shaping the sensory richness of divergent perceptual experience. In sum, to predict a range of divergent perceptual experiences in both clinical and general populations, three factors must be accounted for: a maladaptive use of priors, individual level of confidence in sensory input, and mental imagery ability. These ideas can be expressed formally using nonparametric regression modeling. We provide evidence for our theory from previous work and deliver predictions for future research.

Contextual Priors Shape Action Understanding before and beyond the Unfolding of Movement Kinematics

Previous studies have shown that contextual information may aid in guessing the intention underlying others' actions in conditions of perceptual ambiguity. Here, we aimed to evaluate the temporal deployment of contextual influence on action prediction with increasing availability of kinematic information during the observation of ongoing actions. We used action videos depicting an actor grasping an object placed on a container to perform individual or interpersonal actions featuring different kinematic profiles. Crucially, the container could be of different colors. First, in a familiarization phase, the probability of co-occurrence between each action kinematics and color cues was implicitly manipulated to 80% and 20%, thus generating contextual priors. Then, in a testing phase, participants were asked to predict action outcome when the same action videos were occluded at five different timeframes of the entire movement, ranging from when the actor was still to when the grasp of the object was fully accomplished. In this phase, all possible action-contextual cues' associations were equally presented. The results showed that for all occlusion intervals, action prediction was more facilitated when action kinematics deployed in high- than low-probability contextual scenarios. Importantly, contextual priors shaped action prediction even in the latest occlusion intervals, where the kinematic cues clearly unveiled an action outcome that was previously associated with low-probability scenarios. These residual contextual effects were stronger in individuals with higher subclinical autistic traits. Our findings highlight the relative contribution of kinematic and contextual information to action understanding and provide evidence in favor of their continuous integration during action observation.

Motor deficits in autism differ from that of developmental coordination disorder

LAY ABSTRACT

A vast majority of individuals with autism spectrum disorder experience impairments in motor skills. Those are often labelled as additional developmental coordination disorder despite the lack of studies comparing both disorders. Consequently, motor skills rehabilitation programmes in autism are often not specific but rather consist in standard programmes for developmental coordination disorder. Here, we compared motor performance in three groups of children: a control group, an autism spectrum disorder group and a developmental coordination disorder group. Despite similar level of motor skills evaluated by the standard movement assessment battery for children, in a Reach-to-Displace Task, children with autism spectrum disorder and developmental coordination disorder showed specific motor control deficits. Children with autism spectrum disorder failed to anticipate the object properties, but could correct their movement as well as typically developing children. In contrast, children with developmental coordination disorder were atypically slow, but showed a spared anticipation. Our study has important clinical implications as motor skills rehabilitations are crucial to both populations. Specifically, our findings suggest that individuals with autism spectrum disorder would benefit from therapies aiming at improving their anticipation, maybe through the support of their preserved representations and use of sensory information. Conversely, individuals with developmental coordination disorder would benefit from a focus on the use of sensory information in a timely fashion.

Perceptual confirmation bias and decision bias underlie adaptation to sequential regularities

Our perception does not depend exclusively on the immediate sensory input. It is also influenced by our internal predictions derived from prior observations and the temporal regularities of the environment, which can result in choice history biases. However, it is unclear how this flexible use of prior information to predict the future influences perceptual decisions. Prior information may bias decisions independently of the current sensory input, or it may modulate the weight of current sensory input based on its consistency with the expectation. To address this question, we used a visual decision-making task and manipulated the transitional probabilities between successive noisy grating stimuli. Using a reverse correlation analysis, we evaluated the contribution of stimulus-independent decision bias and stimulus-dependent sensitivity modulations to choice history biases. We found that both effects coexist, whereby there was increased bias to respond in line with the predicted orientation alongside modulations in perceptual sensitivity to favor perceptual information consistent with the prediction, akin to selective attention. Furthermore, at the individual differences level, we investigated the relationship between autistic-like traits and the adaptation of choice history biases to the sequential statistics of the environment. Over two studies, we found no convincing evidence of reduced adaptation to sequential regularities in individuals with high autistic-like traits. In sum, we present robust evidence for both perceptual confirmation bias and decision bias supporting adaptation to sequential regularities in the environment.

Autistic traits and event-related potentials in the general population: A scoping review and meta-analysis

BACKGROUND

Differences in short and long-latency Event-Related Potentials (ERPs) can help us infer abnormalities in brain processing, considering early and later stages of stimuli processing across tasks and conditions. In autism research, the adult population remains largely understudied compared to samples at early stages of development. In this context, this scoping review briefly summarises what has been described in community and subclinical adult samples of autism.

METHOD

The current scoping review and meta-analysis includes 50 records (N = 1652) and comprehensively explores short and long-latency ERP amplitudes and their relationship with autistic traits in adult community samples.

RESULTS

This meta-analysis identified, with small to medium effect sizes, distinctive patterns in late ERP amplitudes, indicating enhanced responses to visual stimuli and the opposite patterns to auditory tasks in the included sample. Additionally, a pattern of higher amplitudes was also found for the component P3b in autistic traits.

DISCUSSION

Differential effects in visual and auditory domains are explored in light of the predictive processing framework for Autism. It remains possible that different brain mechanisms operate to explain symptoms related with different sensory modalities. P3b is discussed as a possible component of interest in future studies as it revealed a more robust effect for differentiating severity in the expression of autistic traits in adulthood.

Müller-Lyer Illusion susceptibility is conditionally predicted by autistic trait expression

Müller-Lyer (ML) figures bias size estimation consistently, yet different methods can lead to different degrees of illusory bias. Autistic individuals may also be less likely to perceive illusory biases with varying levels of autistic trait expression proposed to modulate reported illusory biases. The Autism-Spectrum Quotient (AQ) and Systemizing Quotient (SQ) are self-report measures that quantify autistic trait expression and systemizing ability in neurotypical individuals. The current study sought to determine if perceptions of illusory size bias negatively correlate with autistic trait expression and the extent to which varying methods of illusion presentation change the magnitude of illusory bias. Thirty neurotypical adults completed both questionnaires as well as four size estimation tasks. Two tasks involved perceptual discrimination of ML figures by concurrent and successive presentation, where participants selected the longer figure by keypress. For Tasks 3 and 4, participants adjusted the size of a non-illusory line (Task 3) or complementary illusory figure (Task 4) to match the perceived length. Overall, task performance was not correlated with autistic trait expression. One exception was a negative correlation with AQ when adjusting a complementary illusory ML figure in Task 4. Illusory biases were also stronger when two illusory figures were presented concurrently. Given these results, illusion susceptibility to the ML is suggested to be reduced with increases in AQ, but only when the method of illusion measurement is adjustment of concurrent illusory figures. Taken together the results provide evidence that traits associated with autism in a neurotypical population may systematically modulate perception.

The world is nuanced but pixelated: Autistic individuals' perspective on HIPPEA

LAY ABSTRACT

Autism is a condition comprised of difficulties in social and communication contexts, sensory sensitivities as well as restrictive and repetitive behaviours. Many theories have tried to explain all the symptoms and behaviours associated with autism. We focus on one recent theory - High, Inflexible Precision of Prediction Errors in Autism (HIPPEA). We aim to understand how much this theory fits the experiences of autistic individuals. We collected data through 21 online questionnaires and 8 follow-up interviews. One of our participants was a parent of an autistic child, and the remaining were adults who reported a diagnosis of autism. We analysed the data by thinking about how it fitted with what we already knew and by looking for new insights which came up. Our results suggest that autistic individuals can make generalisations but that this happens more slowly across both social and non-social areas. These generalisations are very reliant on detail - in computer terms, they are 'pixelated'. This is in line with what HIPPEA suggests. We also showed that autistic individuals can be motivated to explore and engage socially, something that needs more consideration within HIPPEA. Overall, this study shows that HIPPEA can explain many autistic experiences, but that further refinement is needed.

A meta-analysis of cognitive flexibility in autism spectrum disorder

Cognitive flexibility is a fundamental process that underlies adaptive behaviour in response to environmental change. Studies examining the profile of cognitive flexibility in autism spectrum disorder (ASD) have reported inconsistent findings. To address whether difficulties with cognitive flexibility are characteristic of autism, we conducted a random-effects meta-analysis and employed subgroup analyses and meta-regression to assess the impact of relevant moderator variables such as task, outcomes, and age. Fifty-nine studies were included and comprised of 2122 autistic individuals without intellectual disabilities and 2036 neurotypical controls, with an age range of 4 to 85 years. The results showed that autistic individuals have greater difficulties with cognitive flexibility, with an overall statistically significant small to moderate effect size. Subgroup analyses revealed a significant difference between task outcomes, with perseverative errors obtaining the largest effect size. In summary, the present meta-analysis highlights the existence of cognitive flexibility difficulties in autistic people, in the absence of learning disabilities, but also that this profile is characterised by substantial heterogeneity. Potential contributing factors are discussed.

Bayesian Decision-Making Under Uncertainty in Borderline Personality Disorder

Bayesian decision theory suggests that optimal decision-making should use and weigh prior beliefs with current information, according to their relative uncertainties. However, some characteristics of borderline personality disorder (BPD) patients, such as fast, drastic changes in the overall perception of themselves and others, suggest they may be underrelying on priors. Here, we investigated if BPD patients have a general deficit in relying on or combining prior with current information. We analyzed this by having BPD patients (n = 23) and healthy controls (n = 18) perform a coin-catching sensorimotor task with varying levels of prior and current information uncertainty. Our results indicate that BPD patients learned and used prior information and combined it with current information in a qualitatively Bayesian-like way. Our results show that, at least in a lower-level, nonsocial sensorimotor task, BPD patients can appropriately use both prior and current information, illustrating that potential deficits using priors may not be widespread or domain-general.

Is Visual Prediction Impaired in Adolescents with Autism spectrum Disorder? Event-Related Potentials in a Cued Visual GO/NOGO Task

Aim: Deviant visual processing has been observed in autism spectrum disorder (ASD), manifesting as decreased P1 and P2 components of visual event-related potentials (ERPs). Alterations have been attributed to a failure of Bayesian inference, characterized by hypo-activation of top-down predictive abilities. To test this hypothesis, we measured the visual negativity (vN) as an ERP index of visual preparation hypothesized to mirror predictive brain activity. Method: ERPs in a cued visual GO/NOGO task in 63 adolescents with ASD (IQ > 70, attention-deficit hyperactivity disorder excluded) were compared with ERPs in a sex- and age-matched group of 60 typically developing (TD) controls. Results: The behavioral variables (omissions, commissions, reaction time, and reaction time variability), as well as ERP components reflecting, among other processes, cognitive control (contingent negative variation, P3 GO, P3 NOGO, N2 NOGO) did not differ between the groups. There were group differences in visually based ERPs. Besides P1 and P2 differences, the vN component differentiated the 2 groups with the highest effect size (d  =  0.74).Conclusion: This ERP study lends support to the hypothesis suggesting that a Bayesian hypo-prediction could underlie unique perceptual experiences in individuals with ASD. This could lead to a predisposition to perceive the world with reduced influence and modulation from contextual cues, prior experiences, and pre-existing expectations.

Sex modulation of faces prediction error in the autistic brain

Recent research suggests that autistic females may have superior socio-cognitive abilities compared to autistic males, potentially contributing to underdiagnosis in females. However, it remains unclear whether these differences arise from distinct neurophysiological functioning in autistic males and females. This study addresses this question by presenting 41 autistic and 48 non-autistic adults with a spatially filtered faces oddball paradigm. Analysis of event-related potentials from scalp electroencephalography reveal a neurophysiological profile in autistic females that fell between those of autistic males and non-autistic females, highlighting sex differences in autism from the initial stages of face processing. This finding underscores the urgent need to explore neurophysiological sex differences in autism and encourages efforts toward a better comprehension of compensation mechanism and a clearer definition of what is meant by camouflaging.

It's all in the timing: Delayed feedback in autism may weaken predictive mechanisms during contour integration

Humans rely on predictive mechanisms during visual processing to efficiently resolve incomplete or ambiguous sensory signals. While initial low-level sensory data are conveyed by feedforward connections, feedback connections are believed to shape sensory processing through conveyance of statistical predictions based on prior exposure to stimulus configurations. Individuals with autism spectrum disorder (ASD) show biases in stimulus processing toward parts rather than wholes, suggesting their sensory processing may be less shaped by statistical predictions acquired through prior exposure to global stimulus properties. Investigations of illusory contour (IC) processing in neurotypical (NT) adults have established a well-tested marker of contour integration characterized by a robust modulation of the visually evoked potential (VEP) - the IC-effect - that occurs over lateral occipital scalp during the timeframe of the N1 component. Converging evidence strongly supports the notion that this IC-effect indexes a signal with significant feedback contributions. Using high-density VEPs, we compared the IC-effect in 6-17-year-old children with ASD (n=32) or NT development (n=53). Both groups of children generated an IC-effect that was equivalent in amplitude. However, the IC-effect notably onset 21ms later in ASD, even though timing of initial VEP afference was identical across groups. This suggests that feedforward information predominated during perceptual processing for 15% longer in ASD compared to NT children. This delay in the feedback dependent IC-effect, in the context of known developmental differences between feedforward and feedback fibers, suggests a potential pathophysiological mechanism of visual processing in ASD, whereby ongoing stimulus processing is less shaped by statistical prediction mechanisms.

Everyday executive function issues from the perspectives of autistic adolescents and their parents: Theoretical and empirical implications

LAY ABSTRACT

Autism researchers have a long-time interest in a set of skills called executive function. These skills include planning, inhibition, and switching between one activity and another. There was a theory that these skills explained the social and thinking difficulties autistic people might have. After years of study into this, the evidence is confusing and contradictory. Autistic people tend to report struggling quite a lot with these skills. Yet, when researchers test these skills, they do not tend to find such big difficulties. In this study, we spoke to 12 autistic teenagers and seven of their mothers about this. We asked them what they thought about their own, or their child's, executive function skills. We wanted to know about things they were good at and things they struggled with. They told us that their skills were very changeable from one context to the next and from one time to the next. According to their reports, their skills depended on how motivated they were by doing the task. Another thing that influenced their skills were how anxious they felt at the time they needed to use the skill. Finally, they told us that sometimes they think differently about how best to perform a task. We discuss what these insights mean for autism researchers who study these skills. In future, research should ask people about their experiences alongside testing their abilities in different contexts. Combining these information sources will give us a better understanding of autistic people's everyday skills as well as how best to support them.

Elucidating multifinal and equifinal pathways to developmental disorders by constructing real-world neurorobotic models

Vigorous research has been conducted to accumulate biological and theoretical knowledge about neurodevelopmental disorders, including molecular, neural, computational, and behavioral characteristics; however, these findings remain fragmentary and do not elucidate integrated mechanisms. An obstacle is the heterogeneity of developmental pathways causing clinical phenotypes. Additionally, in symptom formations, the primary causes and consequences of developmental learning processes are often indistinguishable. Herein, we review developmental neurorobotic experiments tackling problems related to the dynamic and complex properties of neurodevelopmental disorders. Specifically, we focus on neurorobotic models under predictive processing lens for the study of developmental disorders. By constructing neurorobotic models with predictive processing mechanisms of learning, perception, and action, we can simulate formations of integrated causal relationships among neurodynamical, computational, and behavioral characteristics in the robot agents while considering developmental learning processes. This framework has the potential to bind neurobiological hypotheses (excitation-inhibition imbalance and functional disconnection), computational accounts (unusual encoding of uncertainty), and clinical symptoms. Developmental neurorobotic approaches may serve as a complementary research framework for integrating fragmented knowledge and overcoming the heterogeneity of neurodevelopmental disorders.

Higher Sensory Sensitivity is Linked to Greater Expansion Amongst Functional Connectivity Gradients

Insofar as the autistic-like phenotype presents in the general population, it consists of partially dissociable traits, such as social and sensory issues. Here, we investigate individual differences in cortical organisation related to autistic-like traits. Connectome gradient decomposition based on resting state fMRI data reliably reveals a principal gradient spanning from unimodal to transmodal regions, reflecting the transition from perception to abstract cognition. In our non-clinical sample, this gradient's expansion, indicating less integration between visual and default mode networks, correlates with subjective sensory sensitivity (measured using the Glasgow Sensory Questionnaire, GSQ), but not other autistic-like traits (measured using the Autism Spectrum Quotient, AQ). This novel brain-based correlate of the GSQ demonstrates sensory issues can be disentangled from the wider autistic-like phenotype.

Multisensory Integration and Causal Inference in Typical and Atypical Populations

Multisensory perception is critical for effective interaction with the environment, but human responses to multisensory stimuli vary across the lifespan and appear changed in some atypical populations. In this review chapter, we consider multisensory integration within a normative Bayesian framework. We begin by outlining the complex computational challenges of multisensory causal inference and reliability-weighted cue integration, and discuss whether healthy young adults behave in accordance with normative Bayesian models. We then compare their behaviour with various other human populations (children, older adults, and those with neurological or neuropsychiatric disorders). In particular, we consider whether the differences seen in these groups are due only to changes in their computational parameters (such as sensory noise or perceptual priors), or whether the fundamental computational principles (such as reliability weighting) underlying multisensory perception may also be altered. We conclude by arguing that future research should aim explicitly to differentiate between these possibilities.

Differences in temporal profile of brain responses by pleasantness of somatosensory stimulation in autistic individuals

Purpose/Aim. Autistic individuals may show either hyper- or hypo- responsiveness to touch compared to non-autistic individuals. These behavioural responses depend on perceptual and evaluative mechanisms, which unfold sequentially and thus can be distinguished by exploring the timing of neural responses. In this study, we examined neural response timing to pleasant, unpleasant, and affectively neutral textures, to determine whether these perceptual versus evaluative subprocesses differ in autism and how each subprocess contributes to behavioural responses.Materials and Methods. Our sample included n = 13 autistic and n = 14 non-autistic adults who completed functional magnetic resonance imaging. We analysed early, intermediate, and late phases of the tactile response, derived from studies of noxious tactile stimulation, to three different textures.Results. The autistic group showed distinct differences from the non-autistic group to each of the textures, showing earlier, somatosensory differences in response to the pleasantly and unpleasantly rated textures and later, frontomotor differences in response to the neutrally rated texture. Further, reduced early phase response to the pleasant texture correlated with increased sensory seeking behaviour.Conclusions. While preliminary, these results suggest distinct patterns between autistic and non-autistic individuals in how the neural response to touch unfolds and its correspondence with the perceived pleasantness of tactile experience. The findings suggest perceptual differences in response to affectively charged textures and evaluative differences in response to neutral, ambiguous textures. These temporal properties may inform future studies of tactile processing in autism, lending a better understanding of how individuals differ in their sensory experiences across contexts.

Disentangling sensory precision and prior expectation of change in autism during tactile discrimination

Predictive coding theories suggest that core symptoms in autism spectrum disorders (ASD) may stem from atypical mechanisms of perceptual inference (i.e., inferring the hidden causes of sensations). Specifically, there would be an imbalance in the precision or weight ascribed to sensory inputs relative to prior expectations. Using three tactile behavioral tasks and computational modeling, we specifically targeted the implicit dynamics of sensory adaptation and perceptual learning in ASD. Participants were neurotypical and autistic adults without intellectual disability. In Experiment I, tactile detection thresholds and adaptation effects were measured to assess sensory precision. Experiments II and III relied on two-alternative forced choice tasks designed to elicit a time-order effect, where prior knowledge biases perceptual decisions. Our results suggest a subtler explanation than a simple imbalance in the prior/sensory weights, having to do with the dynamic nature of perception, that is the adjustment of precision weights to context. Compared to neurotypicals, autistic adults showed no difference in average performance and sensory sensitivity. Both groups managed to implicitly learn and adjust a prior that biased their perception. However, depending on the context, autistic participants showed no, normal or slower adaptation, a phenomenon that computational modeling of trial-to-trial responses helped us to associate with a higher expectation for sameness in ASD, and to dissociate from another observed robust difference in terms of response bias. These results point to atypical perceptual learning rather than altered perceptual inference per se, calling for further empirical and computational studies to refine the current predictive coding theories of ASD.

Perceptual alterations in the relationship between sensory reactivity, intolerance of uncertainty, and anxiety in autistic children with and without ADHD

Sensory differences and anxiety disorders are highly prevalent in autistic individuals with and without ADHD. Studies have shown that sensory differences and anxiety are associated and that intolerance of uncertainty (IU) plays an important role in this relationship. However, it is unclear as to how different levels of the sensory processing pathway (i.e., perceptual, affective, or behavioral) contribute. Here, we used psychophysics to assess how alterations in tactile perception contribute to questionnaire measures of sensory reactivity, IU, and anxiety. Thirty-eight autistic children (aged 8-12 years; 27 with co-occurring ADHD) were included. Consistent with previous findings, mediation analyses showed that child-reported IU fully mediated an association between parent-reported sensory reactivity and parent-reported anxiety and that anxiety partially mediated an association between sensory reactivity and IU. Of the vibrotactile thresholds, only simultaneous frequency discrimination (SFD) thresholds correlated with sensory reactivity. Interestingly, we found that sensory reactivity fully mediated an association between SFD threshold and anxiety, and between SFD threshold and IU. Taken together, those findings suggest a mechanistic pathway whereby tactile perceptual alterations contribute to sensory reactivity at the affective level, leading in turn to increased IU and anxiety. This stepwise association can inform potential interventions for IU and anxiety in autism.

Storm on predictive brain: A neurocomputational account of ketamine antidepressant effect

For the past decade, ketamine, an N-methyl-D-aspartate receptor (NMDAr) antagonist, has been considered a promising treatment for major depressive disorder (MDD). Unlike the delayed effect of monoaminergic treatment, ketamine may produce fast-acting antidepressant effects hours after a single administration at subanesthetic dose. Along with these antidepressant effects, it may also induce transient dissociative (disturbing of the sense of self and reality) symptoms during acute administration which resolve within hours. To understand ketamine's rapid-acting antidepressant effect, several biological hypotheses have been explored, but despite these promising avenues, there is a lack of model to understand the timeframe of antidepressant and dissociative effects of ketamine. In this article, we propose a neurocomputational account of ketamine's antidepressant and dissociative effects based on the Predictive Processing (PP) theory, a framework for cognitive and sensory processing. PP theory suggests that the brain produces top-down predictions to process incoming sensory signals, and generates bottom-up prediction errors (PEs) which are then used to update predictions. This iterative dynamic neural process would relies on N-methyl-D-aspartate (NMDAr) and α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic receptors (AMPAr), two major component of the glutamatergic signaling. Furthermore, it has been suggested that MDD is characterized by over-rigid predictions which cannot be updated by the PEs, leading to miscalibration of hierarchical inference and self-reinforcing negative feedback loops. Based on former empirical studies using behavioral paradigms, neurophysiological recordings, and computational modeling, we suggest that ketamine impairs top-down predictions by blocking NMDA receptors, and enhances presynaptic glutamate release and PEs, producing transient dissociative symptoms and fast-acting antidepressant effect in hours following acute administration. Moreover, we present data showing that ketamine may enhance a delayed neural plasticity pathways through AMPAr potentiation, triggering a prolonged antidepressant effect up to seven days for unique administration. Taken together, the two sides of antidepressant effects with distinct timeframe could constitute the keystone of antidepressant properties of ketamine. These PP disturbances may also participate to a ketamine-induced time window of mental flexibility, which can be used to improve the psychotherapeutic process. Finally, these proposals could be used as a theoretical framework for future research into fast-acting antidepressants, and combination with existing antidepressant and psychotherapy.

A systematic review on speech-in-noise perception in autism

Individuals with autism spectrum disorder (ASD) exhibit atypical speech-in-noise (SiN) perception, but the scope of these impairments has not been clearly defined. We conducted a systematic review of the behavioural research on SiN perception in ASD, using a comprehensive search strategy across databases (Embase, Pubmed, Web of Science, APA PsycArticles, LLBA, clinicaltrials.gov and PsyArXiv). We withheld 20 studies that generally revealed intact speech perception in stationary noise, while impairments in speech discrimination were found in temporally modulated noise, concurrent speech, and audiovisual speech perception. An association with auditory temporal processing deficits, exacerbated by suboptimal language skills, is shown. Speech-in-speech perception might be further impaired due to deficient top-down processing of speech. Further research is needed to address remaining challenges and gaps in our understanding of these impairments, including the developmental aspects of SiN processing in ASD, and the impact of gender and social attentional orienting on this ability. Our findings have important implications for improving communication in ASD, both in daily interactions and in clinical and educational settings.

An Introduction to Predictive Processing Models of Perception and Decision-Making

The predictive processing framework includes a broad set of ideas, which might be articulated and developed in a variety of ways, concerning how the brain may leverage predictive models when implementing perception, cognition, decision-making, and motor control. This article provides an up-to-date introduction to the two most influential theories within this framework: predictive coding and active inference. The first half of the paper (Sections 2-5) reviews the evolution of predictive coding, from early ideas about efficient coding in the visual system to a more general model encompassing perception, cognition, and motor control. The theory is characterized in terms of the claims it makes at Marr's computational, algorithmic, and implementation levels of description, and the conceptual and mathematical connections between predictive coding, Bayesian inference, and variational free energy (a quantity jointly evaluating model accuracy and complexity) are explored. The second half of the paper (Sections 6-8) turns to recent theories of active inference. Like predictive coding, active inference models assume that perceptual and learning processes minimize variational free energy as a means of approximating Bayesian inference in a biologically plausible manner. However, these models focus primarily on planning and decision-making processes that predictive coding models were not developed to address. Under active inference, an agent evaluates potential plans (action sequences) based on their expected free energy (a quantity that combines anticipated reward and information gain). The agent is assumed to represent the world as a partially observable Markov decision process with discrete time and discrete states. Current research applications of active inference models are described, including a range of simulation work, as well as studies fitting models to empirical data. The paper concludes by considering future research directions that will be important for further development of both models.

Temporal dynamics of normalization reweighting

For decades, neural suppression in early visual cortex has been thought to be fixed. But recent work has challenged this assumption by showing that suppression can be reweighted based on recent history; when pairs of stimuli are repeatedly presented together, suppression between them strengthens. Here we investigate the temporal dynamics of this process using a steady-state visual evoked potential (SSVEP) paradigm that provides a time-resolved, direct index of suppression between pairs of stimuli flickering at different frequencies (5 and 7 Hz). Our initial analysis of an existing electroencephalography (EEG) dataset (N = 100) indicated that suppression increases substantially during the first 2-5 seconds of stimulus presentation (with some variation across stimulation frequency). We then collected new EEG data (N = 100) replicating this finding for both monocular and dichoptic mask arrangements in a preregistered study designed to measure reweighting. A third experiment (N = 20) used source-localized magnetoencephalography and found that these effects are apparent in primary visual cortex (V1), consistent with results from neurophysiological work. Because long-standing theories propose inhibition/excitation differences in autism, we also compared reweighting between individuals with high versus low autistic traits, and with and without an autism diagnosis, across our three datasets (total N = 220). We find no compelling differences in reweighting that are associated with autism. Our results support the normalization reweighting model and indicate that for prolonged stimulation, increases in suppression occur on the order of 2-5 seconds after stimulus onset.

Intact Utilization of Contextual Information in Speech Categorization in Autism

Current theories of Autism Spectrum Disorder (ASD) suggest atypical use of context in ASD, but little is known about how these atypicalities influence speech perception. We examined the influence of contextual information (lexical, spectral, and temporal) on phoneme categorization of people with ASD and in typically developed (TD) people. Across three experiments, we found that people with ASD used all types of contextual information for disambiguating speech sounds to the same extent as TD; yet they exhibited a shallower identification curve when phoneme categorization required temporal processing. Overall, the results suggest that the observed atypicalities in speech perception in ASD, including the reduced sensitivity observed here, cannot be attributed merely to the limited ability to utilize context during speech perception.

Dynamics of retrospective timing: A big data approach

Most interval timing research has focused on prospective timing tasks, in which participants are explicitly asked to pay attention to time as they are tested over multiple trials. Our current understanding of interval timing primarily relies on prospective timing. However, most real-life temporal judgments are made without knowing beforehand that the durations of events will need to be estimated (i.e., retrospective timing). The current study investigated the retrospective timing performance of ~24,500 participants with a wide range of intervals (5-90 min). Participants were asked to judge how long it took them to complete a set of questionnaires that were filled out at the participants' own pace. Participants overestimated and underestimated durations shorter and longer than 15 min, respectively. They were most accurate at estimating 15-min long events. The between-subject variability in duration estimates decreased exponentially as a function of time, reaching the lower asymptote after 30 min. Finally, a considerable proportion of participants exhibited whole number bias by rounding their duration estimates to the multiples of 5 min. Our results provide evidence for systematic biases in retrospective temporal judgments, and show that variability in retrospective timing is relatively higher for shorter durations (e.g., < 30 min). The primary findings gathered from our dataset were replicated based on the secondary analyses of another dataset (Blursday). The current study constitutes the most comprehensive study of retrospective timing regarding the range of durations and sample size tested.

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.

Comparing narrative writing of autistic and non-autistic College students

We compared short stories by autistic (n = 19) and non-autistic (n = 23) university students. We used automated software and content analysis to code students' stories. We found that writings were more similar than different. However, autistic students' stories were rated at a higher reading level (p = .013) than non-autistic students'. Autistic students' stories contained fewer grammatical errors (p = .02) but were less likely to include a climax (p = .026). Autistic students reported more positive writing affect than non-autistic students (p = .026). Higher writing affect was associated with writing highly fictional texts (p = .03) that contained more sentences (p = .005). Findings suggest writing may be a strength for autistic students and opportunities to write creatively may promote positive affect toward writing.

Habituation of auditory responses in young autistic and neurotypical children

Prior studies suggest that habituation of sensory responses is reduced in autism and that diminished habituation could be related to atypical autistic sensory experiences, for example, by causing brain responses to aversive stimuli to remain strong over time instead of being suppressed. While many prior studies exploring habituation in autism have repeatedly presented identical stimuli, other studies suggest group differences can still be observed in habituation to intermittent stimuli. The present study explored habituation of electrophysiological responses to auditory complex tones of varying intensities (50-80 dB SPL), presented passively in an interleaved manner, in a well-characterized sample of 127 autistic (MDQ  = 65.41, SD = 20.54) and 79 typically developing (MDQ  = 106.02, SD = 11.50) children between 2 and 5 years old. Habituation was quantified as changes in the amplitudes of single-trial responses to tones of each intensity over the course of the experiment. Habituation of the auditory N2 response was substantially reduced in autistic participants as compared to typically developing controls, although diagnostic groups did not clearly differ in habituation of the P1 response. Interestingly, the P1 habituated less to loud 80 dB sounds than softer sounds, whereas the N2 habituated less to soft 50 dB sounds than louder sounds. No associations were found between electrophysiological habituation and cognitive ability or participants' caregiver-reported sound tolerance (Sensory Profile Hyperacusis Index). The results present study results extend prior research suggesting habituation of certain sensory responses is reduced in autism; however, they also suggest that habituation differences observed using this study's paradigm might not be a primary driver of autistic participants' real-world sound intolerance.

Multisensory decisions from self to world

Classic Bayesian models of perceptual inference describe how an ideal observer would integrate 'unisensory' measurements (multisensory integration) and attribute sensory signals to their origin(s) (causal inference). However, in the brain, sensory signals are always received in the context of a multisensory bodily state-namely, in combination with other senses. Moreover, sensory signals from both interoceptive sensing of one's own body and exteroceptive sensing of the world are highly interdependent and never occur in isolation. Thus, the observer must fundamentally determine whether each sensory observation is from an external (versus internal, self-generated) source to even be considered for integration. Critically, solving this primary causal inference problem requires knowledge of multisensory and sensorimotor dependencies. Thus, multisensory processing is needed to separate sensory signals. These multisensory processes enable us to simultaneously form a sense of self and form distinct perceptual decisions about the external world. In this opinion paper, we review and discuss the similarities and distinctions between multisensory decisions underlying the sense of self and those directed at acquiring information about the world. We call attention to the fact that heterogeneous multisensory processes take place all along the neural hierarchy (even in forming 'unisensory' observations) and argue that more integration of these aspects, in theory and experiment, is required to obtain a more comprehensive understanding of multisensory brain function. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

Circuit-level theories for sensory dysfunction in autism: convergence across mouse models

Individuals with autism spectrum disorder (ASD) exhibit a diverse range of behavioral features and genetic backgrounds, but whether different genetic forms of autism involve convergent pathophysiology of brain function is unknown. Here, we analyze evidence for convergent deficits in neural circuit function across multiple transgenic mouse models of ASD. We focus on sensory areas of neocortex, where circuit differences may underlie atypical sensory processing, a central feature of autism. Many distinct circuit-level theories for ASD have been proposed, including increased excitation-inhibition (E-I) ratio and hyperexcitability, hypofunction of parvalbumin (PV) interneuron circuits, impaired homeostatic plasticity, degraded sensory coding, and others. We review these theories and assess the degree of convergence across ASD mouse models for each. Behaviorally, our analysis reveals that innate sensory detection behavior is heightened and sensory discrimination behavior is impaired across many ASD models. Neurophysiologically, PV hypofunction and increased E-I ratio are prevalent but only rarely generate hyperexcitability and excess spiking. Instead, sensory tuning and other aspects of neural coding are commonly degraded and may explain impaired discrimination behavior. Two distinct phenotypic clusters with opposing neural circuit signatures are evident across mouse models. Such clustering could suggest physiological subtypes of autism, which may facilitate the development of tailored therapeutic approaches.

Neural Signatures of Predictive Strategies Track Individuals Along the Autism-Schizophrenia Continuum

BACKGROUND AND HYPOTHESIS

Humans develop a constellation of different representations of the external environment, even in the face of the same sensory exposure. According to the Bayesian framework, these differentiations could be grounded in a different weight assigned to prior knowledge vs. new external inputs in predictive inference. Since recent advances in computational psychiatry suggest that autism (ASD) and schizophrenia (SSD) lie on the two diametric poles of the same predictive continuum, the adoption of a specific inferential style could be routed by dispositional factors related to autistic and schizotypal traits. However, no studies have directly investigated the role of ASD-SSD dimension in shaping the neuro-behavioral markers underlying perceptual inference.

STUDY DESIGN

We used a probabilistic detection task while simultaneously recording EEG to investigate whether neurobehavioral signatures related to prior processing were diametrically shaped by ASD and SSD traits in the general population (n = 80).

RESULTS

We found that the position along the ASD-SSD continuum directed the predictive strategies adopted by the individuals in decision-making. While proximity to the positive schizotypy pole was associated with the adoption of the predictive approach associated to the hyper-weighting of prior knowledge, proximity to ASD pole was related to strategies that favored sensory evidence in decision-making.

CONCLUSIONS

These findings revealed that the weight assigned to prior knowledge is a marker of the ASD-SSD continuum, potentially useful for identifying individuals at-risk of developing mental disorders and for understanding the mechanisms contributing to the onset of symptoms observed in ASD and SSD clinical forms.

'If I don't Do It, I'm Out of Rhythm and I Can't Focus As Well': Positive and Negative Adult Interpretations of Therapies Aimed at 'Fixing' Their Restricted and Repetitive Behaviours in Childhood

Restricted and repetitive behaviours (RRBs) are observed in many children presenting with characteristics of autism and are frequently the targets of psychological interventions. This study used Interpretative Phenomenological Analysis (IPA) to identify positive and negative interpretations from four young adults who received behavioural interventions in their childhood designed to 'fix' RRBs. Two superordinate themes were identified: (1) Doubt, stigma and being fixed according to others, and (2) Embracing Authenticity. They highlighted juxtaposed positions from exclusion, rejection, criticism, and self-doubt in childhood, to rejecting societal censure and embracing authentic growth in adult life. As adults, though the participants recognised themselves as neurologically different from others, they redefined themselves through a lens of neurodiversity, and therefore as not needing to be fixed.

Breathing in waves: Understanding respiratory-brain coupling as a gradient of predictive oscillations

Breathing plays a crucial role in shaping perceptual and cognitive processes by regulating the strength and synchronisation of neural oscillations. Numerous studies have demonstrated that respiratory rhythms govern a wide range of behavioural effects across cognitive, affective, and perceptual domains. Additionally, respiratory-modulated brain oscillations have been observed in various mammalian models and across diverse frequency spectra. However, a comprehensive framework to elucidate these disparate phenomena remains elusive. In this review, we synthesise existing findings to propose a neural gradient of respiratory-modulated brain oscillations and examine recent computational models of neural oscillations to map this gradient onto a hierarchical cascade of precision-weighted prediction errors. By deciphering the computational mechanisms underlying respiratory control of these processes, we can potentially uncover new pathways for understanding the link between respiratory-brain coupling and psychiatric disorders.